From b079577e08f8b5ce7f8aa1b67e2209418be7ebc6 Mon Sep 17 00:00:00 2001 From: Hui Zhang Date: Tue, 19 Oct 2021 08:42:21 +0000 Subject: [PATCH] merge parakeet repo into deepspeech --- .readthedocs.yml | 30 + README.md | 2 +- docs/images/audio_icon.png | Bin 0 -> 19332 bytes docs/images/fastpitch.png | Bin 0 -> 47821 bytes docs/images/fastspeech.png | Bin 0 -> 342636 bytes docs/images/fastspeech2.png | Bin 0 -> 119940 bytes docs/images/frame_level_am.png | Bin 0 -> 61193 bytes docs/images/logo-small.png | Bin 0 -> 33681 bytes docs/images/logo.png | Bin 0 -> 77034 bytes docs/images/news_icon.png | Bin 0 -> 118424 bytes docs/images/pwg.png | Bin 0 -> 70217 bytes docs/images/seq2seq_am.png | Bin 0 -> 41551 bytes docs/images/speedyspeech.png | Bin 0 -> 89192 bytes docs/images/tacotron.png | Bin 0 -> 134254 bytes docs/images/tacotron2.png | Bin 0 -> 311596 bytes docs/images/transformer.png | Bin 0 -> 146006 bytes docs/images/transformer_tts.png | Bin 0 -> 369287 bytes docs/source/{ => 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tests/unit/tts/test_data_table.py create mode 100644 tests/unit/tts/test_expansion.py create mode 100644 tests/unit/tts/test_optimizer.py create mode 100644 tests/unit/tts/test_pwg.py create mode 100644 tests/unit/tts/test_raise.py create mode 100644 tests/unit/tts/test_reporter.py create mode 100644 tests/unit/tts/test_snapshot.py create mode 100644 tests/unit/tts/test_stft.py create mode 100644 tests/unit/tts/test_to_static.py create mode 100644 utils/compute_statistics.py create mode 100644 utils/gen_duration_from_textgrid.py diff --git a/.readthedocs.yml b/.readthedocs.yml new file mode 100644 index 00000000..702ae6da --- /dev/null +++ b/.readthedocs.yml @@ -0,0 +1,30 @@ +# .readthedocs.yml +# Read the Docs configuration file +# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details + +# Required +version: 2 + +# Build documentation in the docs/ directory with Sphinx +sphinx: + configuration: docs/src/conf.py + +# Build documentation with MkDocs +#mkdocs: +# configuration: mkdocs.yml + +# Optionally build your docs in additional formats such as PDF +formats: [] + +# Optionally set the version of Python and requirements required to build your docs +python: + version: 3.7 + install: + - method: pip + path: . + extra_requirements: + - doc + + - requirements: docs/requirements.txt + + diff --git a/README.md b/README.md index e48079f6..8c101933 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,4 @@ -# PaddlePaddle Speech to Any toolkit +# PaddlePaddle Speech toolkit ![License](https://img.shields.io/badge/license-Apache%202-red.svg) ![python version](https://img.shields.io/badge/python-3.7+-orange.svg) diff --git a/docs/images/audio_icon.png b/docs/images/audio_icon.png new file mode 100644 index 0000000000000000000000000000000000000000..925ecff7024fcd45b521d665f18075ca16783994 GIT binary patch literal 19332 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    + + +## News +- Oct-12-2021, Refector examples code. +- Oct-12-2021, Parallel WaveGAN with LJSpeech. Check [examples/GANVocoder/parallelwave_gan/ljspeech](./examples/GANVocoder/parallelwave_gan/ljspeech). +- Oct-12-2021, FastSpeech2/FastPitch with LJSpeech. Check [examples/fastspeech2/ljspeech](./examples/fastspeech2/ljspeech). +- Sep-14-2021, Reconstruction of TransformerTTS. Check [examples/transformer_tts/ljspeech](./examples/transformer_tts/ljspeech). +- Aug-31-2021, Chinese Text Frontend. Check [examples/text_frontend](./examples/text_frontend). +- Aug-23-2021, FastSpeech2/FastPitch with AISHELL-3. Check [examples/fastspeech2/aishell3](./examples/fastspeech2/aishell3). +- Aug-03-2021, FastSpeech2/FastPitch with CSMSC. Check [examples/fastspeech2/baker](./examples/fastspeech2/baker). +- Jul-19-2021, SpeedySpeech with CSMSC. Check [examples/speedyspeech/baker](./examples/speedyspeech/baker). +- Jul-01-2021, Parallel WaveGAN with CSMSC. Check [examples/GANVocoder/parallelwave_gan/baker](./examples/GANVocoder/parallelwave_gan/baker). +- Jul-01-2021, Montreal-Forced-Aligner. Check [examples/use_mfa](./examples/use_mfa). +- May-07-2021, Voice Cloning in Chinese. Check [examples/tacotron2_aishell3](./examples/tacotron2_aishell3). + +## Overview + +In order to facilitate exploiting the existing TTS models directly and developing the new ones, Parakeet selects typical models and provides their reference implementations in PaddlePaddle. Further more, Parakeet abstracts the TTS pipeline and standardizes the procedure of data preprocessing, common modules sharing, model configuration, and the process of training and synthesis. The models supported here include Text FrontEnd, end-to-end Acoustic models and Vocoders: + +- Text FrontEnd + - Rule based Chinese frontend. + +- Acoustic Models + - [【FastSpeech2】FastSpeech 2: Fast and High-Quality End-to-End Text to Speech](https://arxiv.org/abs/2006.04558) + - [【SpeedySpeech】SpeedySpeech: Efficient Neural Speech Synthesis](https://arxiv.org/abs/2008.03802) + - [【Transformer TTS】Neural Speech Synthesis with Transformer Network](https://arxiv.org/abs/1809.08895) + - [【Tacotron2】Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions](https://arxiv.org/abs/1712.05884) +- Vocoders + - [【Parallel WaveGAN】Parallel WaveGAN: A fast waveform generation model based on generative adversarial networks with multi-resolution spectrogram](https://arxiv.org/abs/1910.11480) + - [【WaveFlow】WaveFlow: A Compact Flow-based Model for Raw Audio](https://arxiv.org/abs/1912.01219) +- Voice Cloning + - [Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis](https://arxiv.org/pdf/1806.04558v4.pdf) + - [【GE2E】Generalized End-to-End Loss for Speaker Verification](https://arxiv.org/abs/1710.10467) + +## Setup +It's difficult to install some dependent libraries for this repo in Windows system, we recommend that you **DO NOT** use Windows system, please use `Linux`. + +Make sure the library `libsndfile1` is installed, e.g., on Ubuntu. + +```bash +sudo apt-get install libsndfile1 +``` +### Install PaddlePaddle +See [install](https://www.paddlepaddle.org.cn/install/quick) for more details. This repo requires PaddlePaddle **2.1.2** or above. + +### Install Parakeet + +```bash +git clone https://github.com/PaddlePaddle/Parakeet +cd Parakeet +pip install -e . +``` + +If some python dependent packages cannot be installed successfully, you can run the following script first. +(replace `python3.6` with your own python version) +```bash +sudo apt install -y python3.6-dev +``` + +See [install](https://paddle-parakeet.readthedocs.io/en/latest/install.html) for more details. + +## Examples +Entries to the introduction, and the launch of training and synthsis for different example models: + +- [>>> Chinese Text Frontend](./examples/text_frontend) +- [>>> FastSpeech2/FastPitch](./examples/fastspeech2) +- [>>> Montreal-Forced-Aligner](./examples/use_mfa) +- [>>> Parallel WaveGAN](./examples/GANVocoder/parallelwave_gan) +- [>>> SpeedySpeech](./examples/speedyspeech) +- [>>> Tacotron2_AISHELL3](./examples/tacotron2_aishell3) +- [>>> GE2E](./examples/ge2e) +- [>>> WaveFlow](./examples/waveflow) +- [>>> TransformerTTS](./examples/transformer_tts) +- [>>> Tacotron2](./examples/tacotron2) + +## Audio samples +### TTS models (Acoustic Model + Neural Vocoder) +Check our [website](https://paddleparakeet.readthedocs.io/en/latest/demo.html) for audio sampels. + +## Released Model + +### Acoustic Model + +#### FastSpeech2/FastPitch +1. [fastspeech2_nosil_baker_ckpt_0.4.zip](https://paddlespeech.bj.bcebos.com/Parakeet/fastspeech2_nosil_baker_ckpt_0.4.zip) +2. [fastspeech2_nosil_aishell3_ckpt_0.4.zip](https://paddlespeech.bj.bcebos.com/Parakeet/fastspeech2_nosil_aishell3_ckpt_0.4.zip) +3. [fastspeech2_nosil_ljspeech_ckpt_0.5.zip](https://paddlespeech.bj.bcebos.com/Parakeet/fastspeech2_nosil_ljspeech_ckpt_0.5.zip) + +#### SpeedySpeech +1. [speedyspeech_nosil_baker_ckpt_0.5.zip](https://paddlespeech.bj.bcebos.com/Parakeet/speedyspeech_nosil_baker_ckpt_0.5.zip) + +#### TransformerTTS + +1. [transformer_tts_ljspeech_ckpt_0.4.zip](https://paddlespeech.bj.bcebos.com/Parakeet/transformer_tts_ljspeech_ckpt_0.4.zip) + +#### Tacotron2 + +1. [tacotron2_ljspeech_ckpt_0.3.zip](https://paddlespeech.bj.bcebos.com/Parakeet/tacotron2_ljspeech_ckpt_0.3.zip) +2. [tacotron2_ljspeech_ckpt_0.3_alternative.zip](https://paddlespeech.bj.bcebos.com/Parakeet/tacotron2_ljspeech_ckpt_0.3_alternative.zip) + +### Vocoder + +#### WaveFlow + +1. [waveflow_ljspeech_ckpt_0.3.zip](https://paddlespeech.bj.bcebos.com/Parakeet/waveflow_ljspeech_ckpt_0.3.zip) + +#### Parallel WaveGAN + +1. [pwg_baker_ckpt_0.4.zip](https://paddlespeech.bj.bcebos.com/Parakeet/pwg_baker_ckpt_0.4.zip) +2. [pwg_ljspeech_ckpt_0.5.zip](https://paddlespeech.bj.bcebos.com/Parakeet/pwg_ljspeech_ckpt_0.5.zip) + +### Voice Cloning + +#### Tacotron2_AISHELL3 + +1. [tacotron2_aishell3_ckpt_0.3.zip](https://paddlespeech.bj.bcebos.com/Parakeet/tacotron2_aishell3_ckpt_0.3.zip) + +#### GE2E + +1. [ge2e_ckpt_0.3.zip](https://paddlespeech.bj.bcebos.com/Parakeet/ge2e_ckpt_0.3.zip) + +## License + +Parakeet is provided under the [Apache-2.0 license](LICENSE). diff --git a/docs/source/tts/advanced_usage.md b/docs/source/tts/advanced_usage.md new file mode 100644 index 00000000..52980044 --- /dev/null +++ b/docs/source/tts/advanced_usage.md @@ -0,0 +1,333 @@ + +# Advanced Usage +This sections covers how to extend parakeet by implementing your own models and experiments. Guidelines on implementation are also elaborated. + +For the general deep learning experiment, there are several parts to deal with: +1. Preprocess the data according to the needs of the model, and iterate the dataset by batch. +2. Define the model, optimizer and other components. +3. Write out the training process (generally including forward / backward calculation, parameter update, log recording, visualization, periodic evaluation, etc.). +5. Configure and run the experiment. + +## Parakeet's Model Components +In order to balance the reusability and function of models, we divide models into several types according to its characteristics. + +For the commonly used modules that can be used as part of other larger models, we try to implement them as simple and universal as possible, because they will be reused. Modules with trainable parameters are generally implemented as subclasses of `paddle.nn.Layer`. Modules without trainable parameters can be directly implemented as a function, and its input and output are `paddle.Tensor`. + +Models for a specific task are implemented as subclasses of `paddle.nn.Layer`. Models could be simple, like a single layer RNN. For complicated models, it is recommended to split the model into different components. + +For a seq-to-seq model, it's natural to split it into encoder and decoder. For a model composed of several similar layers, it's natural to extract the sublayer as a separate layer. + +There are two common ways to define a model which consists of several modules. + +1. Define a module given the specifications. Here is an example with multilayer perceptron. + ```python + class MLP(nn.Layer): + def __init__(self, input_size, hidden_size, output_size): + self.linear1 = nn.Linear(input_size, hidden_size) + self.linear2 = nn.Linear(hidden_size, output_size) + + def forward(self, x): + return self.linear2(paddle.tanh(self.linear1(x)) + + module = MLP(16, 32, 4) # intialize a module + ``` + When the module is intended to be a generic and reusable layer that can be integrated into a larger model, we prefer to define it in this way. + + For considerations of readability and usability, we strongly recommend **NOT** to pack specifications into a single object. Here’s an example below. + ```python + class MLP(nn.Layer): + def __init__(self, hparams): + self.linear1 = nn.Linear(hparams.input_size, hparams.hidden_size) + self.linear2 = nn.Linear(hparams.hidden_size, hparams.output_size) + + def forward(self, x): + return self.linear2(paddle.tanh(self.linear1(x)) + ``` + For a module defined in this way, it’s harder for the user to initialize an instance. Users have to read the code to check what attributes are used. + + Also, code in this style tend to be abused by passing a huge config object to initialize every module used in an experiment, thought each module may not need the whole configuration. + + We prefer to be explicit. + +2. Define a module as a combination given its components. Here is an example for a sequence-to-sequence model. + ```python + class Seq2Seq(nn.Layer): + def __init__(self, encoder, decoder): + self.encoder = encoder + self.decoder = decoder + + def forward(self, x): + encoder_output = self.encoder(x) + output = self.decoder(encoder_output) + return output + + encoder = Encoder(...) + decoder = Decoder(...) + # compose two components + model = Seq2Seq(encoder, decoder) + ``` + When a model is a complicated and made up of several components, each of which has a separate functionality, and can be replaced by other components with the same functionality, we prefer to define it in this way. + +In the directory structure of Parakeet, modules with high reusability are placed in `parakeet.modules`, but models for specific tasks are placed in `parakeet.models`. When developing a new model, developers need to consider the feasibility of splitting the modules, and the degree of generality of the modules, and place them in appropriate directories. + +## Parakeet's Data Components +Another critical componnet for a deep learning project is data. +Parakeet uses the following methods for training data: +1. Preprocess the data. +2. Load the preprocessed data for training. + +Previously, we wrote the preprocessing in the `__getitem__` of the Dataset, which will process when accessing a certain batch samples, but encountered some problems: + +1. Efficiency problem. Even if Paddle has a design to load data asynchronously, when the batch size is large, each sample needs to be preprocessed and set up batches, which takes a lot of time , and may even seriously slow down the training process. +2. Data filtering problem. Some filtering conditions depend on the features of the processed sample. For example, filtering samples that are too short according to text length. If the text length can only be known after `__getitem__`, every time you filter, the entire dataset needed to be loaded once! In addition, if you do not pre-filter, A small exception (such as too short text ) in `__getitem__` will cause an exception in the entire data flow, which is not feasible, because `collate_fn ` presupposes that the acquisition of each sample can be normal. Even if some special flags, such as `None`, are used to mark data acquisition failures, and skip `collate_fn`, it will change batch_size . + +Therefore, it is not realistic to put preprocessing entirely on `__getitem__`. We use the method mentioned above instead. +During preprocessing, we can do filtering, We can also save more intermediate features, such as text length, audio length, etc., which can be used for subsequent filtering. Because of the habit of TTS field, data is stored in multiple files, and the processed results are stored in `npy` format. + +Use a list-like way to store metadata and store the file path in it, so that you can not be restricted by the specific storage location of the file. In addition to the file path, other metadata can also be stored in it. For example, the path of the text, the path of the audio, the path of the spectrum, the number of frames, the number of sampling points, and so on. + +Then for the path, there are multiple opening methods, such as `sf.read`, `np.load`, etc., so it's best to use a parameter that can be input, we don't even want to determine the reading method by it's extension, it's best to let the users input it , in this way, users can define their own method to parse the data. + +So we learned from the design of `DataFrame`, but our construction method is simpler, only need a `list of dicts`, a dict represents a record, and it's convenient to interact with formats such as `json`, `yaml`. For each selected field, we need to give a parser (called `converter` in the interface), and that's it. + +Then we need to select a format for saving metadata to the hard disk. There are two square brackets when storing the list of records in `json`, which is not convenient for stream reading and writing, so we use `jsonlines`. We don't use `yaml` because it occupies too many rows when storing the list of records. + +Meanwhile, `cache` is added here, and a multi-process Manager is used to share memory between multiple processes. When `num_workers` is used, it is guaranteed that each sub process will not cache a copy. + +The implementation of `DataTable` can be found in `parakeet/datasets/data_table.py`. +```python +class DataTable(Dataset): + """Dataset to load and convert data for general purpose. + + Parameters + ---------- + data : List[Dict[str, Any]] + Metadata, a list of meta datum, each of which is composed of + several fields + fields : List[str], optional + Fields to use, if not specified, all the fields in the data are + used, by default None + converters : Dict[str, Callable], optional + Converters used to process each field, by default None + use_cache : bool, optional + Whether to use cache, by default False + + Raises + ------ + ValueError + If there is some field that does not exist in data. + ValueError + If there is some field in converters that does not exist in fields. + """ + + def __init__(self, + data: List[Dict[str, Any]], + fields: List[str]=None, + converters: Dict[str, Callable]=None, + use_cache: bool=False): +``` +It's `__getitem__` method is to parse each field with their own parser, and then compose a dictionary to return. +```python +def _convert(self, meta_datum: Dict[str, Any]) -> Dict[str, Any]: + """Convert a meta datum to an example by applying the corresponding + converters to each fields requested. + + Parameters + ---------- + meta_datum : Dict[str, Any] + Meta datum + + Returns + ------- + Dict[str, Any] + Converted example + """ + example = {} + for field in self.fields: + converter = self.converters.get(field, None) + meta_datum_field = meta_datum[field] + if converter is not None: + converted_field = converter(meta_datum_field) + else: + converted_field = meta_datum_field + example[field] = converted_field + return example +``` + +## Parakeet's Training Components +A typical training process includes the following processes: +1. Iterate the dataset. +2. Process batch data. +3. Neural network forward/backward calculation. +4. Parameter update. +5. Evaluate the model on the validation dataset, when some special conditions are reached. +6. Write logs, visualize, and in some cases save necessary intermediate results. +7. Save the state of the model and optimizer. + +Here, we mainly introduce the training related components of Parakeet and why we designed it like this. +### Global Repoter +When training and modifying Deep Learning models，logging is often needed, and it has even become the key to model debugging and modifying. We usually use various visualization tools，such as , `visualdl` in `paddle`, `tensorboard` in `tensorflow` and `vidsom`, `wnb` ,etc. Besides, `logging` and `print` are usuaally used for different purpose. + +In these tools, `print` is the simplest，it doesn't have the concept of `logger` and `handler` in `logging` 、 `summarywriter` and `logdir` in `tensorboard`, when printing, there is no need for `global_step` ，It's light enough to appear anywhere in the code, and it's printed to a common stdout. Of course, its customizability is limited, for example, it is no longer intuitive when printing dictionaries or more complex objects. And it's fleeting, people need to use redirection to save information. + +For TTS models development，we hope to have a more universal multimedia stdout, which is actually a tool similar to `tensorboard`, which allows many multimedia forms, but it needs a `summary writer` when using, and a `step` when writing information. If the data are images or voices, some format control parameters are needed. + +This will destroy the modular design to a certain extent. For example, If my model is composed of multiple sublayers, and I want to record some important information in the forward method of some sublayers. For this reason, I may need to pass the `summary writer` to this sublayers, but for the sublayers, its function is calculation, it should not have extra considerations, and it's also difficult for us to tolerate that the initialization of an `nn.Linear` has an optional `visualizer` in the method. And, for a calculation module, **HOW** can it know the global step? These are things related to the training process! + +Therefore, a more common approach is not to put writing_log_code in the definition of layer, but return it, then obtain them during training, and write them to `summary writer`. However, the return values need to be modified. `summary writer ` is a broadcaster at the training level, and then each module transmits information to it by modifying the return values. + +We think this method is a little ugly. We prefer to return the necessary information only rather than change the return values to accommodate visualization and recording. When you need to report some information, you should be able to report it without difficult. So we imitate the design of `chainer` and use the `global repoter`. + +It takes advantage of the globality of Python's module level variables and the effect of context manager. + +There is a module level variable in `parakeet/training/reporter.py` `OBSERVATIONS`，which is a `Dict` to store key-value. +```python +# parakeet/training/reporter.py + +@contextlib.contextmanager +def scope(observations): + # make `observation` the target to report to. + # it is basically a dictionary that stores temporary observations + global OBSERVATIONS + old = OBSERVATIONS + OBSERVATIONS = observations + + try: + yield + finally: + OBSERVATIONS = old +``` + +Then we implement a context manager `scope`, which is used to switch the variables bound by the name of `OBSERVATIONS`. Then a `getter` function is defined to get the dictionary bound by `OBSERVATIONS`. +```python +def get_observations(): + global OBSERVATIONS + return OBSERVATIONS +``` +Then we define a function to get the current `OBSERVATIONS`，and write key-value pair into it. +```python +def report(name, value): + # a simple function to report named value + # you can use it everywhere, it will get the default target and writ to it + # you can think of it as std.out + observations = get_observations() + if observations is None: + return + else: + observations[name] = value +``` +The test code following shows the usage method. +- use `first` as the current `OBSERVATION`, write `first_begin=1`, +- then, open the second `OBSERVATION`, write `second_begin=2`, +- then, open the third `OBSERVATION`, write `third_begin=3` +- exit the third `OBSERVATION` , we back to the second `OBSERVATION` automatically +- write some context in the second `OBSERVATION` , then exit it, and we back to the first `OBSERVATION` automatically +```python +def test_reporter_scope(): + first = {} + second = {} + third = {} + + with scope(first): + report("first_begin", 1) + with scope(second): + report("second_begin", 2) + with scope(third): + report("third_begin", 3) + report("third_end", 4) + report("seconf_end", 5) + report("first_end", 6) + + assert first == {'first_begin': 1, 'first_end': 6} + assert second == {'second_begin': 2, 'seconf_end': 5} + assert third == {'third_begin': 3, 'third_end': 4} +``` + +In this way, when we write modular components, we can directly call `report`. The caller will decide where to report as long as it's ready for `OBSERVATION`, then it opens a `scope` and calls the component within this `scope`. + + The `Trainer` in Parakeet report the information in this way. +```python +while True: + self.observation = {} + # set observation as the report target + # you can use report freely in Updater.update() + + # updating parameters and state + with scope(self.observation): + update() # training for a step is defined here +``` +### Updater: Model Training Process + +In order to maintain the purity of function and the reusability of code, we abstract the model code into a subclass of `paddle.nn.Layer`, and write the core computing functions in it. + +We tend to write the forward process of training in `forward()`, but only write to the prediction result, not to the loss. Therefore, this module can be called by a larger module. + +However, when we compose an experiment, we need to add some other things, such as training process, evaluation process, checkpoint saving, visualization and the like. In this process, we will encounter some things that only exist in the training process, such as `optimizer`, `learning rate scheduler`, `visualizer`, etc. These things are not part of the model, they should **NOT** be written in the model code. + +We made an abstraction for these intermediate processes, that is, `Updater`, which takes the `model`, `optimizer`, and `data stream` as input, and its function is training. Since there may be differences in training methods of different models, we tend to write a corresponding `Updater` for each model. But this is different from the final training script, there is still a certain degree of encapsulation, just to extract the details of regular saving, visualization, evaluation, etc., and only retain the most basic function, that is, training the model. + +### Visualizer +Because we choose observation as the communication mode, we can simply write the things in observation into `visualizer`. + +## Parakeet's Configuration Components +Deep learning experiments often have many options to configure. These configurations can be roughly divided into several categories. +1. Data source and data processing mode configuration. +2. Save path configuration of experimental results. +3. Data preprocessing mode configuration. +4. Model structure and hyperparameterconfiguration. +5. Training process configuration. + +It’s common to change the running configuration to compare results. To keep track of running configuration, we use `yaml` configuration files. + +Also, we want to interact with command line options. Some options that usually change according to running environments is provided by command line arguments. In addition, we want to override an option in the config file without editing it. + +Taking these requirements in to consideration, we use [yacs](https://github.com/rbgirshick/yacs) as a config management tool. Other tools like [omegaconf](https://github.com/omry/omegaconf) are also powerful and have similar functions. + +In each example provided, there is a `config.py`, the default config is defined at `conf/default.yaml`. If you want to get the default config, import `config.py` and call `get_cfg_defaults()` to get it. Then it can be updated with `yaml` config file or command line arguments if needed. + +For details about how to use yacs in experiments, see [yacs](https://github.com/rbgirshick/yacs). + +The following is the basic `ArgumentParser`: +1. `--config` is used to support configuration file parsing, and the configuration file itself handles the unique options of each experiment. +2. `--train-metadata` is the path to the training data. +3. `--output-dir` is the dir to save the training results.（if there are checkpoints in `checkpoints/` of `--output-dir` , it's defalut to reload the newest checkpoint to train) +4. `--device` and `--nprocs` determine operation modes，`--device` specifies the type of running device, whether to run on `cpu` or `gpu`. `--nprocs` refers to the number of training processes. If `nprocs` > 1, it means that multi process parallel training is used. (Note: currently only GPU multi card multi process training is supported.) + +Developers can refer to the examples in `Parakeet/examples` to write the default configuration file when adding new experiments. + +## Parakeet's Experiment template + +The experimental codes in Parakeet are generally organized as follows: + +```text +├── conf +│ └── default.yaml (defalut config) +├── README.md (help information) +├── batch_fn.py (organize metadata into batch) +├── config.py (code to read default config) +├── *_updater.py (Updater of a specific model) +├── preprocess.py (data preprocessing code) +├── preprocess.sh (script to call data preprocessing.py) +├── synthesis.py (synthesis from metadata) +├── synthesis.sh (script to call synthesis.py) +├── synthesis_e2e.py (synthesis from raw text) +├── synthesis_e2e.sh (script to call synthesis_e2e.py) +├── train.py (train code) +└── run.sh (script to call train.py) +``` + +We add a named argument. `--output-dir` to each training script to specify the output directory. The directory structure is as follows, It's best for developers to follow this specification: +```text +exp/default/ +├── checkpoints/ +│ ├── records.jsonl (record file) +│ └── snapshot_iter_*.pdz (checkpoint files) +├── config.yaml (config fille of this experiment) +├── vdlrecords.*.log (visualdl record file) +├── worker_*.log (text logging, one file per process) +├── validation/ (output dir during training, information_iter_*/ is the output of each step, if necessary) +├── inference/ (output dir of exported static graph model, which is only used in the final stage of training, if implemented) +└── test/ (output dir of synthesis results) +``` + +You can view the examples we provide in `Parakeet/examples`. These experiments are provided to users as examples which can be run directly. Users are welcome to add new models and experiments and contribute code to Parakeet. diff --git a/docs/source/tts/basic_usage.md b/docs/source/tts/basic_usage.md new file mode 100644 index 00000000..fc2a5bad --- /dev/null +++ b/docs/source/tts/basic_usage.md @@ -0,0 +1,115 @@ +# Basic Usage +This section shows how to use pretrained models provided by parakeet and make inference with them. + +Pretrained models in v0.4 are provided in a archive. Extract it to get a folder like this: +``` +checkpoint_name/ +├──default.yaml +├──snapshot_iter_76000.pdz +├──speech_stats.npy +└──phone_id_map.txt +``` +`default.yaml` stores the config used to train the model. +`snapshot_iter_N.pdz` is the chechpoint file, where `N` is the steps it has been trained. +`*_stats.npy` is the stats file of feature if it has been normalized before training. +`phone_id_map.txt` is the map of phonemes to phoneme_ids. + +The example code below shows how to use the models for prediction. +## Acoustic Models (text to spectrogram) +The code below show how to use a `FastSpeech2` model. After loading the pretrained model, use it and normalizer object to construct a prediction object，then use fastspeech2_inferencet(phone_ids) to generate spectrograms, which can be further used to synthesize raw audio with a vocoder. + +```python +from pathlib import Path +import numpy as np +import paddle +import yaml +from yacs.config import CfgNode +from parakeet.models.fastspeech2 import FastSpeech2 +from parakeet.models.fastspeech2 import FastSpeech2Inference +from parakeet.modules.normalizer import ZScore +# Parakeet/examples/fastspeech2/baker/frontend.py +from frontend import Frontend + +# load the pretrained model +checkpoint_dir = Path("fastspeech2_nosil_baker_ckpt_0.4") +with open(checkpoint_dir / "phone_id_map.txt", "r") as f: + phn_id = [line.strip().split() for line in f.readlines()] +vocab_size = len(phn_id) +with open(checkpoint_dir / "default.yaml") as f: + fastspeech2_config = CfgNode(yaml.safe_load(f)) +odim = fastspeech2_config.n_mels +model = FastSpeech2( + idim=vocab_size, odim=odim, **fastspeech2_config["model"]) +model.set_state_dict( + paddle.load(args.fastspeech2_checkpoint)["main_params"]) +model.eval() + +# load stats file +stat = np.load(checkpoint_dir / "speech_stats.npy") +mu, std = stat +mu = paddle.to_tensor(mu) +std = paddle.to_tensor(std) +fastspeech2_normalizer = ZScore(mu, std) + +# construct a prediction object +fastspeech2_inference = FastSpeech2Inference(fastspeech2_normalizer, model) + +# load Chinese Frontend +frontend = Frontend(checkpoint_dir / "phone_id_map.txt") + +# text to spectrogram +sentence = "你好吗？" +input_ids = frontend.get_input_ids(sentence, merge_sentences=True) +phone_ids = input_ids["phone_ids"] +flags = 0 +# The output of Chinese text frontend is segmented +for part_phone_ids in phone_ids: + with paddle.no_grad(): + temp_mel = fastspeech2_inference(part_phone_ids) + if flags == 0: + mel = temp_mel + flags = 1 + else: + mel = paddle.concat([mel, temp_mel]) +``` + +## Vocoder (spectrogram to wave) +The code below show how to use a ` Parallel WaveGAN` model. Like the example above, after loading the pretrained model, use it and normalizer object to construct a prediction object，then use pwg_inference(mel) to generate raw audio (in wav format). + +```python +from pathlib import Path +import numpy as np +import paddle +import soundfile as sf +import yaml +from yacs.config import CfgNode +from parakeet.models.parallel_wavegan import PWGGenerator +from parakeet.models.parallel_wavegan import PWGInference +from parakeet.modules.normalizer import ZScore + +# load the pretrained model +checkpoint_dir = Path("parallel_wavegan_baker_ckpt_0.4") +with open(checkpoint_dir / "pwg_default.yaml") as f: + pwg_config = CfgNode(yaml.safe_load(f)) +vocoder = PWGGenerator(**pwg_config["generator_params"]) +vocoder.set_state_dict(paddle.load(args.pwg_params)) +vocoder.remove_weight_norm() +vocoder.eval() + +# load stats file +stat = np.load(checkpoint_dir / "pwg_stats.npy") +mu, std = stat +mu = paddle.to_tensor(mu) +std = paddle.to_tensor(std) +pwg_normalizer = ZScore(mu, std) + +# construct a prediction object +pwg_inference = PWGInference(pwg_normalizer, vocoder) + +# spectrogram to wave +wav = pwg_inference(mel) +sf.write( + audio_path, + wav.numpy(), + samplerate=fastspeech2_config.fs) +``` diff --git a/docs/source/tts/cn_text_frontend.md b/docs/source/tts/cn_text_frontend.md new file mode 100644 index 00000000..8a025179 --- /dev/null +++ b/docs/source/tts/cn_text_frontend.md @@ -0,0 +1,108 @@ +# Chinese Rule Based Text Frontend +TTS system mainly includes three modules: `text frontend`, `Acoustic model` and `Vocoder`. We provide a complete Chinese text frontend module in Parakeet, see exapmle in `Parakeet/examples/text_frontend/`. + +A text frontend module mainly includes: + - Text Segmentation + - Text Normalization (TN) + - Word Segmentation (mainly in Chinese) + - Part-of-Speech + - Prosody + - G2P (Grapheme-to-Phoneme, include Polyphone and Tone Sandhi, etc.) + - Linguistic Features/Charactors/Phonemes + +```text +• text: 90 后为中华人民共和国成立 70 周年准备了大礼 +• Text Normalization: 九零后为中华人民共和国成立七十周年准备了大礼 +• Word Segmentation: 九零后/为/中华人民/共和国/成立/七十/周年/准备/了/大礼 +• G2P: + jiu3 ling2 hou4 wei4 zhong1 hua2 ren2 min2 gong4 he2 guo2 ... +• Prosody (prosodic words #1, prosodic phrases #2, intonation phrases #3, sentence #4): + 九零后#1为中华人民#1共和国#2成立七十周年#3准备了大礼#4 +``` + +Among them, Text Normalization and G2P are the most important modules. We mainly introduce them here. + +## Text Normalization +### Supported NSW (Non-Standard-Word) Normalization + +|NSW type|raw|normalized| +|:--|:-|:-| +|serial number|电影中梁朝伟扮演的陈永仁的编号27149|电影中梁朝伟扮演的陈永仁的编号二七一四九| +|cardinal|这块黄金重达324.75克
    我们班的最高总分为583分|这块黄金重达三百二十四点七五克
    我们班的最高总分为五百八十三分| +|numeric range |12\~23
    -1.5\~2|十二到二十三
    负一点五到二| +|date|她出生于86年8月18日，她弟弟出生于1995年3月1日|她出生于八六年八月十八日， 她弟弟出生于一九九五年三月一日| +|time|等会请在12:05请通知我|等会请在十二点零五分请通知我 +|temperature|今天的最低气温达到-10°C|今天的最低气温达到零下十度 +|fraction|现场有7/12的观众投出了赞成票|现场有十二分之七的观众投出了赞成票| +|percentage|明天有62％的概率降雨|明天有百分之六十二的概率降雨| +|money|随便来几个价格12块5，34.5元，20.1万|随便来几个价格十二块五，三十四点五元，二十点一万| +|telephone|这是固话0421-33441122
    这是手机+86 18544139121|这是固话零四二一三三四四一一二二
    这是手机八六一八五四四一三九一二一| + + +## Grapheme-to-Phoneme +In Chinese, G2P is a very complex module, which mainly includes **polyphone** and **tone sandhi**. + +We use [g2pM](https://github.com/kakaobrain/g2pM) and [pypinyin](https://github.com/mozillazg/python-pinyin) as the defalut g2p tools. They can solve the problem of polyphone to a certain extent. In the future, we intend to use a trainable language model (for example, [BERT](https://arxiv.org/abs/1810.04805)) for polyphone. + +However, g2pM and pypinyin do not perform well in tone sandhi, we use rules to solve this problem, which requires relevant linguistic knowledge. + +The **tone sandhi** in Chinese mainly include: + + - soft tone sandhi (轻声变调) + - "一" "不" tone sandhi ("一" "不" 变调) + - three tone sandhi (三声变调) + +For ease of understanding, we list the tone sandhi rules in Chinese here +### 1. 轻声变调 +| |cases | +|:--|:-| +| 语气助词“吧、呢、啊”等 | 吃吧、走吗、去呢、跑啊 | +| 结构助词：“的、地、得”| 我的书、慢慢地走、跑得很快等 | +|有的轻声音节和非轻声音节构成对比区别意义 |买卖：一指生意；二指买和卖。
    地道：一指纯粹、真正；二指地下通道。
    大意：一指没有注意；二指主要的意思。
    东西：一指各种事物；二指东面与西面。
    言语：一指所说的话；二指开口，招呼。
    运气：一指一种锻炼的方法。二指幸运。
    | +|名词的后缀：“们、子、头”|你们、房子、石头 | +|名词或动词的第二个重叠音节 | 奶奶、姐姐、爸爸、试试、看看、说说、问问 | +|名词后面表示方位的：“上、下、里” |桌上、地下、院里 | +| 动态助词：“了、着、过” | 走了、看着、去过| +| 作宾语的人称代词：“我、你、他” | 找我、请你、麻烦他。 | +| 约定俗成 | 匀称、盘算、枇杷、篱笆、活泼、玄乎。狐狸、学生、拾掇、麻烦、蛤蟆、石榴。玫瑰、凉快、萝卜、朋友、奴才、云彩。脑袋、老爷、老婆、嘴巴、指头、指甲。委屈、喇叭、讲究、打发、打听、喜欢。点心、伙计、打扮、哑巴、女婿、首饰。自在、吓唬、力气、漂亮、队伍、地方。痛快、念叨、笑语、丈夫、志气、钥匙。月亮、正经、位置、秀气、上司、悟性。告示、动静、热闹、屁股、阔气、意思。等 | + + +### 2. "一" "不" 变调 +#### "一" 变调 +| | 是否变调 | cases| +|:--|:-|:-| +| 单独念 | 否 | 第一、一楼| +| 序数 |否 | | +| 用在语句末尾 | 否 | | +| 去声前变阳平（四声前变二声） | | 一栋yí dòng、一段yí duàn、一律yí lǜ、一路yí lù| +| 非去声前变去声（非四声前变四声） | | 阴平（一声）
    一发yì fā 、一端yì duān、一天yì tiān、一忽yì hū
    阳平（二声）
    一叠yì dié 、一同yì tóng 、一头yì tóu 、一条yì tiáo
    上声（三声）
    一统yì tǒng、一体yì tǐ、一览yì lǎn、一口yì kǒu| +|轻读，当“一”嵌在重叠式的动词之间 | | 听一听 tīng yi tīng| + +#### "不" 变调 +| | 是否变调 | cases| +|:--|:-|:-| +|单独念|否 | | +| 用在语句末尾| 否 | 我不| +|去声前变阳平（四声前变成二声） | | 不怕bú pà、不妙bú miào、不犯bú fàn、不忿bú fèn| +| 轻读，不”夹在重叠动词或重叠形容词之间、夹在动词和补语之间 | |懂不懂 dǒng bu dǒng 、看不清 kàn bu qīng | + + +### 3. 三声变调 +| | 子类别| 如何变调|cases| +|:--|:-|:-|:-| +|单独念 | | 否| | +|句末 | | 否| | +|在句中停顿并没被后音节影响 | |否 | | +|三声+三声 | | 二声+三声|保险、保养、党委、尽管、老板、本领、引导、古老、敏感、鼓舞、永远、语法、口语、岛屿、保姆、远景、北海、首长、母语 | +| 三个三声相连| 双音节+单音节（“双单格”结构）| 前两个变二声|演讲稿、跑马场、展览馆、管理组、水彩笔、蒙古语、选取法、古典舞、虎骨酒、洗脸水、草稿纸| +| | 单音节+双音节（“单双格”结构）|第二个变二声|史小姐、党小组、好小伙、跑百米、纸老虎、李厂长、老保姆、冷处理、很友好、小雨伞| +| | 单音节+单音节+单音节（“单三格”结构）| 前两个变二声| 软懒散、稳准狠| +| 更多三声音节相连时| | 按语意与若干二字组成三字组，然后按以上变调规律处理|岂有 / 此理。
    请你 / 给我 / 打点儿 / 洗脸水。
    手表厂 / 有五种 /好产品。| + +## References + + - [chinese_text_normalization](https://github.com/speechio/chinese_text_normalization) + - [声调篇｜这些“一、不”变调规律，你不得不知](https://zhuanlan.zhihu.com/p/36156170) + - [TTS前端模块中的普通话变调规则](https://zhuanlan.zhihu.com/p/65091429) + - [轻声和变调](https://wenku.baidu.com/view/ad2016d94693daef5ef73db1.html) + - [必读轻声词语表546条](http://www.chaziwang.com/article-view-504.html) diff --git a/docs/source/tts/demo.rst b/docs/source/tts/demo.rst new file mode 100644 index 00000000..a6f18f88 --- /dev/null +++ b/docs/source/tts/demo.rst @@ -0,0 +1,583 @@ +Audio Sample +================== + +The main processes of TTS include: + +1. Convert the original text into characters/phonemes, through ``text frontend`` module. + +2. Convert characters/phonemes into acoustic features , such as linear spectrogram, mel spectrogram, LPC features, etc. through ``Acoustic models``. + +3. Convert acoustic features into waveforms through ``Vocoders``. + +When training ``Tacotron2``、``TransformerTTS`` and ``WaveFlow``, we use English single speaker TTS dataset `LJSpeech `_ by default. However, when training ``SpeedySpeech``, ``FastSpeech2`` and ``ParallelWaveGAN``, we use Chinese single speaker dataset `CSMSC `_ by default. + +In the future, ``Parakeet`` will mainly use Chinese TTS datasets for default examples. + +Here, we will display three types of audio samples: + +1. Analysis/synthesis (ground-truth spectrograms + Vocoder) + +2. TTS (Acoustic model + Vocoder) + +3. Chinese TTS with/without text frontend (mainly tone sandhi) + +Analysis/synthesis +-------------------------- + +Audio samples generated from ground-truth spectrograms with a vocoder. + +.. raw:: html + + LJSpeech(English) +
    +
    + + + + + + + + + + +
    GT WaveFlow
    + + + + + + + + + + + +
    + +
    +
    + CSMSC(Chinese) +
    +
    + + + + + + + + + + + + +
    GT (convert to 24k) ParallelWaveGAN
    + + + + + + + + + + + +
    + + +TTS +------------------- + +Audio samples generated by a TTS system. Text is first transformed into spectrogram by a text-to-spectrogram model, then the spectrogram is converted into raw audio by a vocoder. + +.. raw:: html + + + + + + + + + + +
    TransformerTTS + WaveFlow Tacotron2 + WaveFlow
    + + + + + + + + + + + + + + + + + + + +
    + + + + + + + + + + +
    SpeedySpeech + ParallelWaveGAN FastSpeech2 + ParallelWaveGAN
    + + + + + + + + + + + + + + + + + + + +
    + + + +Chinese TTS with/without text frontend +-------------------------------------- + +We provide a complete Chinese text frontend module in ``Parakeet``. ``Text Normalization`` and ``G2P`` are the most important modules in text frontend, We assume that the texts are normalized already, and mainly compare ``G2P`` module here. + +We use ``FastSpeech2`` + ``ParallelWaveGAN`` here. + +.. raw:: html + + + + + + + + + + + + +
    With Text Frontend Without Text Frontend
    + + + + + + + + + + + + + + + + + + + + + +
    \ No newline at end of file diff --git a/docs/source/tts/index.rst b/docs/source/tts/index.rst new file mode 100644 index 00000000..74abe60d --- /dev/null +++ b/docs/source/tts/index.rst @@ -0,0 +1,45 @@ +.. parakeet documentation master file, created by + sphinx-quickstart on Fri Sep 10 14:22:24 2021. + You can adapt this file completely to your liking, but it should at least + contain the root `toctree` directive. + +Parakeet +==================================== + +``parakeet`` is a deep learning based text-to-speech toolkit built upon ``paddlepaddle`` framework. It aims to provide a flexible, efficient and state-of-the-art text-to-speech toolkit for the open-source community. It includes many influential TTS models proposed by `Baidu Research `_ and other research groups. + +``parakeet`` mainly consists of components below. + +#. Implementation of models and commonly used neural network layers. +#. Dataset abstraction and common data preprocessing pipelines. +#. Ready-to-run experiments. + +.. toctree:: + :maxdepth: 1 + :caption: Introduction + + introduction + +.. toctree:: + :maxdepth: 1 + :caption: Getting started + + install + basic_usage + advanced_usage + cn_text_frontend + released_models + +.. toctree:: + :maxdepth: 1 + :caption: Demos + + demo + + +Indices and tables +================== + +* :ref:`genindex` +* :ref:`modindex` +* :ref:`search` diff --git a/docs/source/tts/install.md b/docs/source/tts/install.md new file mode 100644 index 00000000..24e44b17 --- /dev/null +++ b/docs/source/tts/install.md @@ -0,0 +1,47 @@ +# Installation +## Install PaddlePaddle +Parakeet requires PaddlePaddle as its backend. Note that 2.1.2 or newer versions of paddle is required. + +Since paddlepaddle has multiple packages depending on the device (cpu or gpu) and the dependency libraries, it is recommended to install a proper package of paddlepaddle with respect to the device and dependency library versons via `pip`. + +Installing paddlepaddle with conda or build paddlepaddle from source is also supported. Please refer to [PaddlePaddle installation](https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/install/pip/linux-pip.html) for more details. + +Example instruction to install paddlepaddle via pip is listed below. + +### PaddlePaddle with GPU +```python +# CUDA10.1 的 PaddlePaddle +python -m pip install paddlepaddle-gpu==2.1.2.post101 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html +# CUDA10.2 的 PaddlePaddle +python -m pip install paddlepaddle-gpu -i https://mirror.baidu.com/pypi/simple +# CUDA11.0 的 PaddlePaddle +python -m pip install paddlepaddle-gpu==2.1.2.post110 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html +# CUDA11.2 的 PaddlePaddle +python -m pip install paddlepaddle-gpu==2.1.2.post112 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html +``` +### PaddlePaddle with CPU +```python +python -m pip install paddlepaddle==2.1.2 -i https://mirror.baidu.com/pypi/simple +``` +## Install libsndfile +Experimemts in parakeet often involve audio and spectrum processing, thus `librosa` and `soundfile` are required. `soundfile` requires a extra C library `libsndfile`, which is not always handled by pip. + +For Windows and Mac users, `libsndfile` is also installed when installing `soundfile` via pip, but for Linux users, installing `libsndfile` via system package manager is required. Example commands for popular distributions are listed below. +```bash +# ubuntu, debian +sudo apt-get install libsndfile1 +# centos, fedora +sudo yum install libsndfile +# openSUSE +sudo zypper in libsndfile +``` +For any problem with installtion of soundfile, please refer to [SoundFile](https://pypi.org/project/SoundFile/). +## Install Parakeet +There are two ways to install parakeet according to the purpose of using it. + + 1. If you want to run experiments provided by parakeet or add new models and experiments, it is recommended to clone the project from github (Parakeet), and install it in editable mode. + ```python + git clone https://github.com/PaddlePaddle/Parakeet + cd Parakeet + pip install -e . + ``` diff --git a/docs/source/tts/introduction.md b/docs/source/tts/introduction.md new file mode 100644 index 00000000..d350565c --- /dev/null +++ b/docs/source/tts/introduction.md @@ -0,0 +1,27 @@ +# Parakeet - PAddle PARAllel text-to-speech toolKIT + +## What is Parakeet? +Parakeet is a deep learning based text-to-speech toolkit built upon paddlepaddle framework. It aims to provide a flexible, efficient and state-of-the-art text-to-speech toolkit for the open-source community. It includes many influential TTS models proposed by Baidu Research and other research groups. + +## What can Parakeet do? +Parakeet mainly consists of components below: +- Implementation of models and commonly used neural network layers. +- Dataset abstraction and common data preprocessing pipelines. +- Ready-to-run experiments. + +Parakeet provides you with a complete TTS pipeline, including: +- Text FrontEnd + - Rule based Chinese frontend. +- Acoustic Models + - FastSpeech2 + - SpeedySpeech + - TransformerTTS + - Tacotron2 +- Vocoders + - Parallel WaveGAN + - WaveFlow +- Voice Cloning + - Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis + - GE2E + +Parakeet helps you to train TTS models with simple commands. diff --git a/docs/source/tts/released_models.md b/docs/source/tts/released_models.md new file mode 100644 index 00000000..7899c1c5 --- /dev/null +++ b/docs/source/tts/released_models.md @@ -0,0 +1,295 @@ +# Released Models +TTS system mainly includes three modules: `text frontend`, `Acoustic model` and `Vocoder`. We introduce a rule based Chinese text frontend in [cn_text_frontend.md](./cn_text_frontend.md). Here, we will introduce acoustic models and vocoders, which are trainable models. + +The main processes of TTS include: +1. Convert the original text into characters/phonemes, through `text frontend` module. +2. Convert characters/phonemes into acoustic features , such as linear spectrogram, mel spectrogram, LPC features, etc. through `Acoustic models`. +3. Convert acoustic features into waveforms through `Vocoders`. + +A simple text frontend module can be implemented by rules. Acoustic models and vocoders need to be trained. The models provided by Parakeet are acoustic models and vocoders. + +## Acoustic Models +### Modeling Objectives of Acoustic Models +Modeling the mapping relationship between text sequences and speech features： +```text +text X = {x1,...,xM} +specch Y = {y1,...yN} +``` +Modeling Objectives: +```text +Ω = argmax p(Y|X,Ω) +``` +### Modeling process of Acoustic Models +At present, there are two mainstream acoustic model structures. + +- Frame level acoustic model: + - Duration model (M Tokens - > N Frames). + - Acoustic decoder (N Frames - > N Frames). + +
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    + +- Sequence to sequence acoustic model: + - M Tokens - > N Frames. + +
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    + +### Tacotron2 + [Tacotron](https://arxiv.org/abs/1703.10135) is the first end-to-end acoustic model based on deep learning, and it is also the most widely used acoustic model. + +[Tacotron2](https://arxiv.org/abs/1712.05884) is the Improvement of Tacotron. +#### Tacotron +**Features of Tacotron:** +- Encoder. + - CBHG. + - Input: character sequence. +- Decoder. + - Global soft attention. + - unidirectional RNN. + - Autoregressive teacher force training (input real speech feature). + - Multi frame prediction. + - CBHG postprocess. + - Vocoder: Griffin-Lim. +
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    + +**Advantage of Tacotron:** +- No need for complex text frontend analysis modules. +- No need for additional duration model. +- Greatly simplifies the acoustic model construction process and reduces the dependence of speech synthesis tasks on domain knowledge. + +**Disadvantages of Tacotron:** +- The CBHG is complex and the amount of parameters is relatively large. +- Global soft attention. +- Poor stability for speech synthesis tasks. +- In training, the less the number of speech frames predicted at each moment, the more difficult it is to train. +- Phase problem in Griffin-Lim casues speech distortion during wave reconstruction. +- The autoregressive decoder cannot be stopped during the generation process. + +#### Tacotron2 +**Features of Tacotron2:** +- Reduction of parameters. + - CBHG -> PostNet (3 Conv layers + BLSTM or 5 Conv layers). + - remove Attention RNN. +- Speech distortion caused by Griffin-Lim. + - WaveNet. +- Improvements of PostNet. + - CBHG -> 5 Conv layers. + - The input and output of the PostNet calculate `L2` loss with real Mel spectrogram. + - Residual connection. +- Bad stop in autoregressive decoder. + - Predict whether it should stop at each moment of decoding (stop token). + - Set a threshold to determine whether to stop generating when decoding. +- Stability of attention. + - Location-aware attention. + - The alignment matrix of previous time is considered at the step `t` of decoder. + +
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    + +You can find Parakeet's tacotron2 example at `Parakeet/examples/tacotron2`. + +### TransformerTTS +**Disadvantages of the Tacotrons:** +- Encodr and decoder are relatively weak at global information modeling + - Vanishing gradient of RNN. + - Fixed-length context modeling problem in CNN kernel. +- Training is relatively inefficient. +- The attention is not robust enough and the stability is poor. + +Transformer TTS is a combination of Tacotron2 and Transformer. + +#### Transformer + [Transformer](https://arxiv.org/abs/1706.03762) is a seq2seq model based entirely on attention mechanism. + +**Features of Transformer:** +- Encoder. + - `N` blocks based on self-attention mechanism. + - Positional Encoding. +- Decoder. + - `N` blocks based on self-attention mechanism. + - Add Mask to the self-attention in blocks to cover up the information after `t` step. + - Attentions between encoder and decoder. + - Positional Encoding. + +
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    + +#### Transformer TTS +Transformer TTS is a seq2seq acoustic model based on Transformer and Tacotron2. + +**Motivations：** +- RNNs in Tacotron2 make the inefficiency of training. +- Vanishing gradient of RNN makes the model's ability to model long-term contexts weak. +- Self-attention doesn't contain any recursive structure which can be trained in parallel. +- Self-attention can model global context information well. + +**Features of Transformer TTS:** +- Add conv based PreNet in encoder and decoder. +- Stop Token in decoder controls when to stop autoregressive generation. +- Add PostNet after decoder to improve the quality of synthetic speech. +- Scaled position encoding. + - Uniform scale position encoding may have a negative impact on input or output sequences. + +
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    + +**Disadvantages of Transformer TTS:** +- The ability of position encoding for timing information is still relatively weak. +- The ability to perceive local information is weak, and local information is more related to pronunciation. +- Stability is worse than Tacotron2. + +You can find Parakeet's Transformer TTS example at `Parakeet/examples/transformer_tts`. + + +### FastSpeech2 +**Disadvantage of seq2seq models:** +- In the seq2seq model based on attention, no matter how to improve the attention mechanism, it's difficult to avoid generation errors in the decoding stage. + +Frame level acoustic models use duration models to determine the pronunciation duration of phonemes, and the frame level mapping does not have the uncertainty of sequence generation. + +In seq2saq models, the concept of duration models is used as the alignment module of two sequences to replace attention, which can avoid the uncertainty in attention, and significantly improve the stability of the seq2saq models. + +#### FastSpeech +Instead of using the encoder-attention-decoder based architecture as adopted by most seq2seq based autoregressive and non-autoregressive generation, [FastSpeech](https://arxiv.org/abs/1905.09263) is a novel feed-forward structure, which can generate a target mel spectrogram sequence in parallel. + +**Features of FastSpeech:** +- Encoder: based on Transformer. +- Change `FFN` to `CNN` in self-attention. + - Model local dependency. +- Length regulator. + - Use real phoneme durations to expand output frame of encoder during training. +- Non autoregressive decode. + - Improve generation efficiency. + +**Length predictor:** +- Pretrain a TransformerTTS model. +- Get alignment matrix of train data. +- Caculate the phoneme durations according to the probability of the alignment matrix. +- Use the output of encoder to predict the phoneme durations and calculate the MSE loss. +- Use real phoneme durations to expand output frame of encoder during training. +- Use phoneme durations predicted by the duration model to expand the frame during prediction. + - Attentrion can not control phoneme durations. The explicit duration modeling can control durations through duration coefficient (duration coefficient is `1` during training). + +**Advantages of non-autoregressive decoder:** +- The built-in duration model of the seq2seq model has converted the input length `M` to the output length `N`. +- The length of output is known, `stop token` is no longer used, avoiding the problem of being unable to stop. +• Can be generated in parallel (decoding time is less affected by sequence length) + +
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    + +#### FastPitch +[FastPitch](https://arxiv.org/abs/2006.06873) follows FastSpeech. A single pitch value is predicted for every temporal location, which improves the overall quality of synthesized speech. + +
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    + +#### FastSpeech2 +**Disadvantages of FastSpeech:** +- The teacher-student distillation pipeline is complicated and time-consuming. +- The duration extracted from the teacher model is not accurate enough. +- The target mel spectrograms distilled from teacher model suffer from information loss due to data simplification. + +[FastSpeech2](https://arxiv.org/abs/2006.04558) addresses the issues in FastSpeech and better solves the one-to-many mapping problem in TTS. + +**Features of FastSpeech2:** +- Directly training the model with ground-truth target instead of the simplified output from teacher. +- Introducing more variation information of speech as conditional inputs, extract `duration`, `pitch` and `energy` from speech waveform and directly take them as conditional inputs in training and use predicted values in inference. + +FastSpeech2 is similar to FastPitch but introduces more variation information of speech. + +
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    + +You can find Parakeet's FastSpeech2/FastPitch example at `Parakeet/examples/fastspeech2`, We use token-averaged pitch and energy values introduced in FastPitch rather than frame level ones in FastSpeech2. + +### SpeedySpeech +[SpeedySpeech](https://arxiv.org/abs/2008.03802) simplify the teacher-student architecture of FastSpeech and provide a fast and stable training procedure. + +**Features of SpeedySpeech:** +- Use a simpler, smaller and faster-to-train convolutional teacher model ([Deepvoice3](https://arxiv.org/abs/1710.07654) and [DCTTS](https://arxiv.org/abs/1710.08969)) with a single attention layer instead of Transformer used in FastSpeech. +- Show that self-attention layers in the student network are not needed for high-quality speech synthesis. +- Describe a simple data augmentation technique that can be used early in the training to make the teacher network robust to sequential error propagation. + +
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    + +You can find Parakeet's SpeedySpeech example at `Parakeet/examples/speedyspeech/baker`. + +## Vocoders +In speech synthesis, the main task of the vocoder is to convert the spectral parameters predicted by the acoustic model into the final speech waveform. + +Taking into account the short-term change frequency of the waveform, the acoustic model usually avoids direct modeling of the speech waveform, but firstly models the spectral features extracted from the speech waveform, and then reconstructs the waveform by the decoding part of the vocoder. + +A vocoder usually consists of a pair of encoders and decoders for speech analysis and synthesis. The encoder estimate the parameters, and then the decoder restores the speech. + +Vocoders based on neural networks usually is speech synthesis, which learns the mapping relationship from spectral features to waveforms through training data. + +### Categories of neural vocodes +- Autoregression + - WaveNet + - WaveRNN + - LPCNet + +- Flow + - **WaveFlow** + - WaveGlow + - FloWaveNet + - Parallel WaveNet +- GAN + - WaveGAN + - **Parallel WaveGAN** + - MelGAN + - HiFi-GAN +- VAE + - Wave-VAE +- Diffusion + - WaveGrad + - DiffWave + +**Motivations of GAN-based vocoders:** +- Modeling speech signal by estimating probability distribution usually has high requirements for the expression ability of the model itself. In addition, specific assumptions need to be made about the distribution of waveforms. +- Although autoregressive neural vocoders can obtain high-quality synthetic speech, such models usually have a **slow generation speed**. +- The training of inverse autoregressive flow vocoders is complex, and they also require the modeling capability of long term context information. +- Vocoders based on Bipartite Transformation converge slowly and are complex. +- GAN-based vocoders don't need to make assumptions about the speech distribution, and train through adversarial learning. + +Here, we introduce a Flow-based vocoder WaveFlow and a GAN-based vocoder Parallel WaveGAN. + +### WaveFlow + [WaveFlow](https://arxiv.org/abs/1912.01219) is proposed by Baidu Research. + +**Features of WaveFlow:** +- It can synthesize 22.05 kHz high-fidelity speech around 40x faster than real-time on a Nvidia V100 GPU without engineered inference kernels, which is faster than [WaveGlow](https://github.com/NVIDIA/waveglow) and serveral orders of magnitude faster than WaveNet. +- It is a small-footprint flow-based model for raw audio. It has only 5.9M parameters, which is 15x smalller than WaveGlow (87.9M). +- It is directly trained with maximum likelihood without probability density distillation and auxiliary losses as used in [Parallel WaveNet](https://arxiv.org/abs/1711.10433) and [ClariNet](https://openreview.net/pdf?id=HklY120cYm), which simplifies the training pipeline and reduces the cost of development. + +You can find Parakeet's WaveFlow example at `Parakeet/examples/waveflow`. + +### Parallel WaveGAN +[Parallel WaveGAN](https://arxiv.org/abs/1910.11480) trains a non-autoregressive WaveNet variant as a generator in a GAN based training method. + +**Features of Parallel WaveGAN:** + +- Use non-causal convolution instead of causal convolution. +- The input is random Gaussian white noise. +- The model is non-autoregressive both in training and prediction, which is fast +- Multi-resolution STFT loss. + +
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    + +You can find Parakeet's Parallel WaveGAN example at `Parakeet/examples/parallelwave_gan/baker`. diff --git a/examples/aishell3/README.md b/examples/aishell3/README.md new file mode 100644 index 00000000..2111901d --- /dev/null +++ b/examples/aishell3/README.md @@ -0,0 +1,4 @@ +# Aishell3 + +* tts0 - fastspeech2 +* vc0 - tactron2 voice clone diff --git a/examples/aishell3/tts0/run.sh b/examples/aishell3/tts0/run.sh new file mode 100644 index 00000000..e69de29b diff --git a/examples/aishell3/vc0/local/tacotron2/README_cn.md b/examples/aishell3/vc0/local/tacotron2/README_cn.md new file mode 100644 index 00000000..a364994a --- /dev/null +++ b/examples/aishell3/vc0/local/tacotron2/README_cn.md @@ -0,0 +1,112 @@ +## Tacotron2 + AISHELL-3 数据集训练语音克隆模型 + +本实验的内容是利用 AISHELL-3 数据集和 Tacotron 2 模型进行语音克隆任务，使用的模型大体结构和论文 [Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis](https://arxiv.org/pdf/1806.04558.pdf) 相同。大致步骤如下： + +1. Speaker Encoder: 我们使用了一个 Speaker Verification 任务训练一个 speaker encoder。这部分任务所用的数据集和训练 Tacotron 2 的数据集不同，因为不需要 transcription 的缘故，我们使用了较多的训练数据，可以参考实现 [ge2e](../ge2e)。 +2. Synthesizer: 然后使用训练好的 speaker encoder 为 AISHELL-3 数据集中的每个句子生成对应的 utterance embedding. 这个 Embedding 作为 Tacotron 模型中的一个额外输入和 encoder outputs 拼接在一起。 +3. Vocoder: 我们使用的声码器是 WaveFlow，参考实验 [waveflow](../waveflow). + +## 数据处理 + +### utterance embedding 的生成 + +使用训练好的 speaker encoder 为 AISHELL-3 数据集中的每个句子生成对应的 utterance embedding. 以和音频文件夹同构的方式存储。存储格式是 `.npy` 文件。 + +首先 cd 到 [ge2e](../ge2e) 文件夹。下载训练好的 [模型](https://paddlespeech.bj.bcebos.com/Parakeet/ge2e_ckpt_0.3.zip)，然后运行脚本生成每个句子的 utterance embedding. + +```bash +python inference.py --input= --output= --device="gpu" --checkpoint_path= +``` + +其中 input 是只包含音频文件夹的文件。这里可以用 `~/datasets/aishell3/train/wav`，然后 output 是用于存储 utterance embed 的文件夹，这里可以用 `~/datasets/aishell3/train/embed`。Utterance embedding 会以和音频文件夹相同的文件结构存储，格式为 `.npy`. + +utterance embedding 的计算可能会用几个小时的时间，请耐心等待。 + +### 音频处理 + +因为 AISHELL-3 数据集前后有一些空白，静音片段，而且语音幅值很小，所以我们需要进行空白移除和音量规范化。空白移除可以简单的使用基于音量或者能量的方法，但是效果不是很好，对于不同的句子很难取到一个一致的阈值。我们使用的是先利用 Force Aligner 进行文本和语音的对齐。然后根据对齐结果截除空白。 + +我们使用的工具是 Montreal Force Aligner 1.0. 因为 aishell 的标注包含拼音标注，所以我们提供给 Montreal Force Aligner 的是拼音 transcription 而不是汉字 transcription. 而且需要把其中的韵律标记(`$` 和 `%`)去除，并且处理成 Montreal Force Alinger 所需要的文件形式。和音频同名的文本文件，扩展名为 `.lab`. + +此外还需要准备词典文件。其中包含把拼音序列转换为 phone 序列的映射关系。在这里我们只做声母和韵母的切分，而声调则归为韵母的一部分。我们使用的[词典文件](./lexicon.txt)可以下载。 + +准备好之后运行训练和对齐。首先下载 [Montreal Force Aligner 1.0](https://github.com/MontrealCorpusTools/Montreal-Forced-Aligner/releases/tag/v1.0.1).下载之后解压即可运行。cd 到其中的 bin 文件夹运行命令，即可进行训练和对齐。前三个命令行参数分别是音频文件夹的路径，词典路径和对齐文件输出路径。可以通过`-o` 传入训练得到的模型保存路径。 + +```bash +./mfa_train_and_align \ + ~/datasets/aishell3/train/wav \ + lexicon.txt \ + ~/datasets/aishell3/train/alignment \ + -o aishell3_model \ + -v +``` + +因为训练和对齐的时间比较长。我们提供了对齐后的 [alignment 文件](https://paddlespeech.bj.bcebos.com/Parakeet/alignment_aishell3.tar.gz)，其中每个句子对应的文件为 `.TextGrid` 格式的文本。 + +得到了对齐文件之后，可以运行 `process_wav.py` 脚本来处理音频。 + +```bash +python process_wav.py --input= --output= --alignment= +``` + +默认 input, output, alignment 分别是 `~/datasets/aishell3/train/wav`, `~/datasets/aishell3/train/normalized_wav`, `~/datasets/aishell3/train/alignment`. + +处理结束后，会将处理好的音频保存在 `` 文件夹中。 + +### 转录文本处理 + +把文本转换成为 phone 和 tone 的形式，并存储起来。值得注意的是，这里我们的处理和用于 montreal force aligner 的不一样。我们把声调分了出来。这是一个处理方式，当然也可以只做声母和韵母的切分。 + +运行脚本处理转录文本。 + +```bash +python preprocess_transcription.py --input= --output= +``` + +默认的 input 是 `~/datasets/aishell3/train`，其中会包含 `label_train-set.txt` 文件，处理后的结果会 `metadata.yaml` 和 `metadata.pickle`. 前者是文本格式，方便查看，后者是二进制格式，方便直接读取。 + +### mel 频谱提取 + +对处理后的音频进行 mel 频谱的提取，并且以和音频文件夹同构的方式存储，存储格式是 `.npy` 文件。 + +```python +python extract_mel.py --input= --output= +``` + +input 是处理后的音频所在的文件夹，output 是输出频谱的文件夹。 + +## 训练 + +运行脚本训练。 + +```python +python train.py --data= --output= --device="gpu" +``` + +我们的模型去掉了 tacotron2 模型中的 stop token prediction。因为实践中由于 stop token prediction 是一个正负样例比例极不平衡的问题，每个句子可能有几百帧对应负样例，只有一帧正样例，而且这个 stop token prediction 对音频静音的裁切十分敏感。我们转用 attention 的最高点到达 encoder 侧的最后一个符号为终止条件。 + +另外，为了加速模型的收敛，我们加上了 guided attention loss, 诱导 encoder-decoder 之间的 alignment 更快地呈现对角线。 + +可以使用 visualdl 查看训练过程的 log。 + +```bash +visualdl --logdir= --host=$HOSTNAME +``` + +示例 training loss / validation loss 曲线如下。 + +![train](./images/train.png) + +![valid](./images/valid.png) + +alignment-step2000 + +大约从训练 2000 步左右就从 validation 过程中产出的 alignement 中可以观察到模糊的对角线。随着训练步数增加，对角线会更加清晰。但因为 validation 也是以 teacher forcing 的方式进行的，所以要在真正的 auto regressive 合成中产出的 alignment 中观察到对角线，需要更长的时间。 + +## 预训练模型 + +预训练模型下载链接。[tacotron2_aishell3_ckpt_0.3.zip](https://paddlespeech.bj.bcebos.com/Parakeet/tacotron2_aishell3_ckpt_0.3.zip). + +## 使用 + +本实验包含了一个简单的使用示例，用户可以替换作为参考的声音以及文本，用训练好的模型来合成语音。使用方式参考 [notebook](./voice_cloning.ipynb) 上的使用说明。 diff --git a/examples/aishell3/vc0/local/tacotron2/aishell3.py b/examples/aishell3/vc0/local/tacotron2/aishell3.py new file mode 100644 index 00000000..c53cf59d --- /dev/null +++ b/examples/aishell3/vc0/local/tacotron2/aishell3.py @@ -0,0 +1,88 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import pickle +from pathlib import Path + +import numpy as np +from paddle.io import Dataset +from parakeet.frontend import Vocab +from parakeet.data import batch_text_id, batch_spec + +from preprocess_transcription import _phones, _tones + +voc_phones = Vocab(sorted(list(_phones))) +print("vocab_phones:\n", voc_phones) +voc_tones = Vocab(sorted(list(_tones))) +print("vocab_tones:\n", voc_tones) + + +class AiShell3(Dataset): + """Processed AiShell3 dataset.""" + + def __init__(self, root): + super().__init__() + self.root = Path(root).expanduser() + self.embed_dir = self.root / "embed" + self.mel_dir = self.root / "mel" + + with open(self.root / "metadata.pickle", 'rb') as f: + self.records = pickle.load(f) + + def __getitem__(self, index): + metadatum = self.records[index] + sentence_id = metadatum["sentence_id"] + speaker_id = sentence_id[:7] + phones = metadatum["phones"] + tones = metadatum["tones"] + phones = np.array( + [voc_phones.lookup(item) for item in phones], dtype=np.int64) + tones = np.array( + [voc_tones.lookup(item) for item in tones], dtype=np.int64) + mel = np.load(str(self.mel_dir / speaker_id / (sentence_id + ".npy"))) + embed = np.load( + str(self.embed_dir / speaker_id / (sentence_id + ".npy"))) + return phones, tones, mel, embed + + def __len__(self): + return len(self.records) + + +def collate_aishell3_examples(examples): + phones, tones, mel, embed = list(zip(*examples)) + + text_lengths = np.array([item.shape[0] for item in phones], dtype=np.int64) + spec_lengths = np.array([item.shape[1] for item in mel], dtype=np.int64) + T_dec = np.max(spec_lengths) + stop_tokens = ( + np.arange(T_dec) >= np.expand_dims(spec_lengths, -1)).astype(np.float32) + phones, _ = batch_text_id(phones) + tones, _ = batch_text_id(tones) + mel, _ = batch_spec(mel) + mel = np.transpose(mel, (0, 2, 1)) + embed = np.stack(embed) + # 7 fields + # (B, T), (B, T), (B, T, C), (B, C), (B,), (B,), (B, T) + return phones, tones, mel, embed, text_lengths, spec_lengths, stop_tokens + + +if __name__ == "__main__": + dataset = AiShell3("~/datasets/aishell3/train") + example = dataset[0] + + examples = [dataset[i] for i in range(10)] + batch = collate_aishell3_examples(examples) + + for field in batch: + print(field.shape, field.dtype) diff --git a/examples/aishell3/vc0/local/tacotron2/chinese_g2p.py b/examples/aishell3/vc0/local/tacotron2/chinese_g2p.py new file mode 100644 index 00000000..e2437f06 --- /dev/null +++ b/examples/aishell3/vc0/local/tacotron2/chinese_g2p.py @@ -0,0 +1,39 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from typing import List, Tuple +from pypinyin import lazy_pinyin, Style +from preprocess_transcription import split_syllable + + +def convert_to_pinyin(text: str) -> List[str]: + """convert text into list of syllables, other characters that are not chinese, thus + cannot be converted to pinyin are splited. + """ + syllables = lazy_pinyin( + text, style=Style.TONE3, neutral_tone_with_five=True) + return syllables + + +def convert_sentence(text: str) -> List[Tuple[str]]: + """convert a sentence into two list: phones and tones""" + syllables = convert_to_pinyin(text) + phones = [] + tones = [] + for syllable in syllables: + p, t = split_syllable(syllable) + phones.extend(p) + tones.extend(t) + + return phones, tones diff --git a/examples/aishell3/vc0/local/tacotron2/config.py b/examples/aishell3/vc0/local/tacotron2/config.py new file mode 100644 index 00000000..440bdbd9 --- /dev/null +++ b/examples/aishell3/vc0/local/tacotron2/config.py @@ -0,0 +1,82 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from yacs.config import CfgNode as CN + +_C = CN() +_C.data = CN( + dict( + batch_size=32, # batch size + valid_size=64, # the first N examples are reserved for validation + sample_rate=22050, # Hz, sample rate + n_fft=1024, # fft frame size + win_length=1024, # window size + hop_length=256, # hop size between ajacent frame + fmax=8000, # Hz, max frequency when converting to mel + fmin=0, # Hz, min frequency when converting to mel + d_mels=80, # mel bands + padding_idx=0, # text embedding's padding index + )) + +_C.model = CN( + dict( + vocab_size=70, + n_tones=10, + reduction_factor=1, # reduction factor + d_encoder=512, # embedding & encoder's internal size + encoder_conv_layers=3, # number of conv layer in tacotron2 encoder + encoder_kernel_size=5, # kernel size of conv layers in tacotron2 encoder + d_prenet=256, # hidden size of decoder prenet + # hidden size of the first rnn layer in tacotron2 decoder + d_attention_rnn=1024, + # hidden size of the second rnn layer in tacotron2 decoder + d_decoder_rnn=1024, + d_attention=128, # hidden size of decoder location linear layer + attention_filters=32, # number of filter in decoder location conv layer + attention_kernel_size=31, # kernel size of decoder location conv layer + d_postnet=512, # hidden size of decoder postnet + postnet_kernel_size=5, # kernel size of conv layers in postnet + postnet_conv_layers=5, # number of conv layer in decoder postnet + p_encoder_dropout=0.5, # droput probability in encoder + p_prenet_dropout=0.5, # droput probability in decoder prenet + + # droput probability of first rnn layer in decoder + p_attention_dropout=0.1, + # droput probability of second rnn layer in decoder + p_decoder_dropout=0.1, + p_postnet_dropout=0.5, # droput probability in decoder postnet + guided_attention_loss_sigma=0.2, + d_global_condition=256, + + # whether to use a classifier to predict stop probability + use_stop_token=False, + # whether to use guided attention loss in training + use_guided_attention_loss=True, )) + +_C.training = CN( + dict( + lr=1e-3, # learning rate + weight_decay=1e-6, # the coeff of weight decay + grad_clip_thresh=1.0, # the clip norm of grad clip. + valid_interval=1000, # validation + save_interval=1000, # checkpoint + max_iteration=500000, # max iteration to train + )) + + +def get_cfg_defaults(): + """Get a yacs CfgNode object with default values for my_project.""" + # Return a clone so that the defaults will not be altered + # This is for the "local variable" use pattern + return _C.clone() diff --git a/examples/aishell3/vc0/local/tacotron2/extract_mel.py b/examples/aishell3/vc0/local/tacotron2/extract_mel.py new file mode 100644 index 00000000..b7bafb86 --- /dev/null +++ b/examples/aishell3/vc0/local/tacotron2/extract_mel.py @@ -0,0 +1,96 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +import multiprocessing as mp +from functools import partial +from pathlib import Path + +import numpy as np +from parakeet.audio import AudioProcessor +from parakeet.audio.spec_normalizer import NormalizerBase, LogMagnitude + +import tqdm + +from config import get_cfg_defaults + + +def extract_mel(fname: Path, + input_dir: Path, + output_dir: Path, + p: AudioProcessor, + n: NormalizerBase): + relative_path = fname.relative_to(input_dir) + out_path = (output_dir / relative_path).with_suffix(".npy") + out_path.parent.mkdir(parents=True, exist_ok=True) + wav = p.read_wav(fname) + mel = p.mel_spectrogram(wav) + mel = n.transform(mel) + np.save(out_path, mel) + + +def extract_mel_multispeaker(config, input_dir, output_dir, extension=".wav"): + input_dir = Path(input_dir).expanduser() + fnames = list(input_dir.rglob(f"*{extension}")) + output_dir = Path(output_dir).expanduser() + output_dir.mkdir(parents=True, exist_ok=True) + + p = AudioProcessor(config.sample_rate, config.n_fft, config.win_length, + config.hop_length, config.n_mels, config.fmin, + config.fmax) + n = LogMagnitude(1e-5) + + func = partial( + extract_mel, input_dir=input_dir, output_dir=output_dir, p=p, n=n) + + with mp.Pool(16) as pool: + list( + tqdm.tqdm( + pool.imap(func, fnames), total=len(fnames), unit="utterance")) + + +if __name__ == "__main__": + parser = argparse.ArgumentParser( + description="Extract mel spectrogram from processed wav in AiShell3 training dataset." + ) + parser.add_argument( + "--config", + type=str, + help="yaml config file to overwrite the default config") + parser.add_argument( + "--input", + type=str, + default="~/datasets/aishell3/train/normalized_wav", + help="path of the processed wav folder") + parser.add_argument( + "--output", + type=str, + default="~/datasets/aishell3/train/mel", + help="path of the folder to save mel spectrograms") + parser.add_argument( + "--opts", + nargs=argparse.REMAINDER, + help="options to overwrite --config file and the default config, passing in KEY VALUE pairs" + ) + default_config = get_cfg_defaults() + + args = parser.parse_args() + if args.config: + default_config.merge_from_file(args.config) + if args.opts: + default_config.merge_from_list(args.opts) + default_config.freeze() + audio_config = default_config.data + + extract_mel_multispeaker(audio_config, args.input, args.output) diff --git 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zn#;myr0b~Dp8Nbmo{K~RPkaqZJSHgjq?hY;mD&r^g+fRsN$sx$Pj>YqT!Tt@;M)*3 zLxi)i!=e@5QHAfOiX7e8yWVo3fQ94yPWchy)f*@2bI)cy8%g< zFd~nc`m19I{RTAsg~;=FHHN{TT{vAqr#x8$C2cj~tFIn*om9|WO=^C^@UE@=;#osIEp1qH7eRr^JNk0wu}=fq`8cI z6aNz<4kL&Ok_N@1!R(wctC+vKq|YrE+$1R1!x+uUt-^?JhO`tomFA#HC^u;mN-&Mo z_pO0cYPbN-44USA^rGlTD4A{wyq1_}cmd17tmSadNxS=@exwB*9X&=1qhkCZ1=x!1 zE4yckH2d_i_j2;;bMXqj@p}O}B3Li8VW~_efwwt%yB3`#T|0&a&X;4>f*xD9Dk{wa z->&30Nk0kVa=OS&Dv{}PdKR(8hQJe^tH{Wle({_^#c=~WS!U9S(%70x(cP?~9A_12 zl+CT-`Tst+0)})%uCtU#sk2W7agkh2yolIfKe5xaU(}WS8}yPf92k;7*hfnf#6zwe ztIx+^5=$QcbKq&O{jtQ48g`YY+}(&yXET|$j(vvzJH`JpQOeS@lE-$BOFxV9HsxiT z{fglX)9LLBtmj$U4G^o~&tAV5(^V$20G^H(fXJuUOXdB*05O5LjFcUoO{ z6{J#F1$haA-PL9LxPc6Q4?KM@wr#|SX`v#?{!QWsKNEWfi^N_$QrF75lctIG8m(Ml zvJZP=4j#Sy%O)+VaM1xwgn', '', '', '0', '1', '2', '3', '4', '5'} + +_pauses = {'%', '$'} + +_initials = { + 'b', + 'p', + 'm', + 'f', + 'd', + 't', + 'n', + 'l', + 'g', + 'k', + 'h', + 'j', + 'q', + 'x', + 'zh', + 'ch', + 'sh', + 'r', + 'z', + 'c', + 's', +} + +_finals = { + 'ii', + 'iii', + 'a', + 'o', + 'e', + 'ea', + 'ai', + 'ei', + 'ao', + 'ou', + 'an', + 'en', + 'ang', + 'eng', + 'er', + 'i', + 'ia', + 'io', + 'ie', + 'iai', + 'iao', + 'iou', + 'ian', + 'ien', + 'iang', + 'ieng', + 'u', + 'ua', + 'uo', + 'uai', + 'uei', + 'uan', + 'uen', + 'uang', + 'ueng', + 'v', + 've', + 'van', + 'ven', + 'veng', +} + +_ernized_symbol = {'&r'} + +_specials = {'', '', '', ''} + +_phones = _initials | _finals | _ernized_symbol | _specials | _pauses + + +def is_zh(word): + global zh_pattern + match = zh_pattern.search(word) + return match is not None + + +def ernized(syllable): + return syllable[:2] != "er" and syllable[-2] == 'r' + + +def convert(syllable): + # expansion of o -> uo + syllable = re.sub(r"([bpmf])o$", r"\1uo", syllable) + # syllable = syllable.replace("bo", "buo").replace("po", "puo").replace("mo", "muo").replace("fo", "fuo") + # expansion for iong, ong + syllable = syllable.replace("iong", "veng").replace("ong", "ueng") + + # expansion for ing, in + syllable = syllable.replace("ing", "ieng").replace("in", "ien") + + # expansion for un, ui, iu + syllable = syllable.replace("un", "uen").replace("ui", + "uei").replace("iu", "iou") + + # rule for variants of i + syllable = syllable.replace("zi", "zii").replace("ci", "cii").replace("si", "sii")\ + .replace("zhi", "zhiii").replace("chi", "chiii").replace("shi", "shiii")\ + .replace("ri", "riii") + + # rule for y preceding i, u + syllable = syllable.replace("yi", "i").replace("yu", "v").replace("y", "i") + + # rule for w + syllable = syllable.replace("wu", "u").replace("w", "u") + + # rule for v following j, q, x + syllable = syllable.replace("ju", "jv").replace("qu", + "qv").replace("xu", "xv") + + return syllable + + +def split_syllable(syllable: str): + """Split a syllable in pinyin into a list of phones and a list of tones. + Initials have no tone, represented by '0', while finals have tones from + '1,2,3,4,5'. + + e.g. + + zhang -> ['zh', 'ang'], ['0', '1'] + """ + if syllable in _pauses: + # syllable, tone + return [syllable], ['0'] + + tone = syllable[-1] + syllable = convert(syllable[:-1]) + + phones = [] + tones = [] + + global _initials + if syllable[:2] in _initials: + phones.append(syllable[:2]) + tones.append('0') + phones.append(syllable[2:]) + tones.append(tone) + elif syllable[0] in _initials: + phones.append(syllable[0]) + tones.append('0') + phones.append(syllable[1:]) + tones.append(tone) + else: + phones.append(syllable) + tones.append(tone) + return phones, tones + + +def load_aishell3_transcription(line: str): + sentence_id, pinyin, text = line.strip().split("|") + syllables = pinyin.strip().split() + + results = [] + + for syllable in syllables: + if syllable in _pauses: + results.append(syllable) + elif not ernized(syllable): + results.append(syllable) + else: + results.append(syllable[:-2] + syllable[-1]) + results.append('&r5') + + phones = [] + tones = [] + for syllable in results: + p, t = split_syllable(syllable) + phones.extend(p) + tones.extend(t) + for p in phones: + assert p in _phones, p + return { + "sentence_id": sentence_id, + "text": text, + "syllables": results, + "phones": phones, + "tones": tones + } + + +def process_aishell3(dataset_root, output_dir): + dataset_root = Path(dataset_root).expanduser() + output_dir = Path(output_dir).expanduser() + output_dir.mkdir(parents=True, exist_ok=True) + + prosody_label_path = dataset_root / "label_train-set.txt" + with open(prosody_label_path, 'rt') as f: + lines = [line.strip() for line in f] + + records = lines[5:] + + processed_records = [] + for record in tqdm.tqdm(records): + new_record = load_aishell3_transcription(record) + processed_records.append(new_record) + print(new_record) + + with open(output_dir / "metadata.pickle", 'wb') as f: + pickle.dump(processed_records, f) + + with open(output_dir / "metadata.yaml", 'wt', encoding="utf-8") as f: + yaml.safe_dump( + processed_records, f, default_flow_style=None, allow_unicode=True) + + print("metadata done!") + + +if __name__ == "__main__": + parser = argparse.ArgumentParser( + description="Preprocess transcription of AiShell3 and save them in a compact file(yaml and pickle)." + ) + parser.add_argument( + "--input", + type=str, + default="~/datasets/aishell3/train", + help="path of the training dataset,(contains a label_train-set.txt).") + parser.add_argument( + "--output", + type=str, + help="the directory to save the processed transcription." + "If not provided, it would be the same as the input.") + args = parser.parse_args() + if args.output is None: + args.output = args.input + + process_aishell3(args.input, args.output) diff --git a/examples/aishell3/vc0/local/tacotron2/process_wav.py b/examples/aishell3/vc0/local/tacotron2/process_wav.py new file mode 100644 index 00000000..34d40897 --- /dev/null +++ b/examples/aishell3/vc0/local/tacotron2/process_wav.py @@ -0,0 +1,95 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +from pathlib import Path +from multiprocessing import Pool +from functools import partial + +import numpy as np +import librosa +import soundfile as sf +from tqdm import tqdm +from praatio import tgio + + +def get_valid_part(fpath): + f = tgio.openTextgrid(fpath) + + start = 0 + phone_entry_list = f.tierDict['phones'].entryList + first_entry = phone_entry_list[0] + if first_entry.label == "sil": + start = first_entry.end + + last_entry = phone_entry_list[-1] + if last_entry.label == "sp": + end = last_entry.start + else: + end = last_entry.end + return start, end + + +def process_utterance(fpath, source_dir, target_dir, alignment_dir): + rel_path = fpath.relative_to(source_dir) + opath = target_dir / rel_path + apath = (alignment_dir / rel_path).with_suffix(".TextGrid") + opath.parent.mkdir(parents=True, exist_ok=True) + + start, end = get_valid_part(apath) + wav, _ = librosa.load(fpath, sr=22050, offset=start, duration=end - start) + normalized_wav = wav / np.max(wav) * 0.999 + sf.write(opath, normalized_wav, samplerate=22050, subtype='PCM_16') + # print(f"{fpath} => {opath}") + + +def preprocess_aishell3(source_dir, target_dir, alignment_dir): + source_dir = Path(source_dir).expanduser() + target_dir = Path(target_dir).expanduser() + alignment_dir = Path(alignment_dir).expanduser() + + wav_paths = list(source_dir.rglob("*.wav")) + print(f"there are {len(wav_paths)} audio files in total") + fx = partial( + process_utterance, + source_dir=source_dir, + target_dir=target_dir, + alignment_dir=alignment_dir) + with Pool(16) as p: + list( + tqdm(p.imap(fx, wav_paths), total=len(wav_paths), unit="utterance")) + + +if __name__ == "__main__": + parser = argparse.ArgumentParser( + description="Process audio in AiShell3, trim silence according to the alignment " + "files generated by MFA, and normalize volume by peak.") + parser.add_argument( + "--input", + type=str, + default="~/datasets/aishell3/train/wav", + help="path of the original audio folder in aishell3.") + parser.add_argument( + "--output", + type=str, + default="~/datasets/aishell3/train/normalized_wav", + help="path of the folder to save the processed audio files.") + parser.add_argument( + "--alignment", + type=str, + default="~/datasets/aishell3/train/alignment", + help="path of the alignment files.") + args = parser.parse_args() + + preprocess_aishell3(args.input, args.output, args.alignment) diff --git a/examples/aishell3/vc0/local/tacotron2/train.py b/examples/aishell3/vc0/local/tacotron2/train.py new file mode 100644 index 00000000..de018116 --- /dev/null +++ b/examples/aishell3/vc0/local/tacotron2/train.py @@ -0,0 +1,262 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import time +from pathlib import Path +from collections import defaultdict + +import numpy as np +from matplotlib import pyplot as plt + +import paddle +from paddle import distributed as dist +from paddle.io import DataLoader, DistributedBatchSampler + +from parakeet.data import dataset +from parakeet.training.cli import default_argument_parser +from parakeet.training.experiment import ExperimentBase +from parakeet.utils import display, mp_tools +from parakeet.models.tacotron2 import Tacotron2, Tacotron2Loss + +from config import get_cfg_defaults +from aishell3 import AiShell3, collate_aishell3_examples + + +class Experiment(ExperimentBase): + def compute_losses(self, inputs, outputs): + texts, tones, mel_targets, utterance_embeds, text_lens, output_lens, stop_tokens = inputs + + mel_outputs = outputs["mel_output"] + mel_outputs_postnet = outputs["mel_outputs_postnet"] + alignments = outputs["alignments"] + + losses = self.criterion(mel_outputs, mel_outputs_postnet, mel_targets, + alignments, output_lens, text_lens) + return losses + + def train_batch(self): + start = time.time() + batch = self.read_batch() + data_loader_time = time.time() - start + + self.optimizer.clear_grad() + self.model.train() + texts, tones, mels, utterance_embeds, text_lens, output_lens, stop_tokens = batch + outputs = self.model( + texts, + text_lens, + mels, + output_lens, + tones=tones, + global_condition=utterance_embeds) + losses = self.compute_losses(batch, outputs) + loss = losses["loss"] + loss.backward() + self.optimizer.step() + iteration_time = time.time() - start + + losses_np = {k: float(v) for k, v in losses.items()} + # logging + msg = "Rank: {}, ".format(dist.get_rank()) + msg += "step: {}, ".format(self.iteration) + msg += "time: {:>.3f}s/{:>.3f}s, ".format(data_loader_time, + iteration_time) + msg += ', '.join('{}: {:>.6f}'.format(k, v) + for k, v in losses_np.items()) + self.logger.info(msg) + + if dist.get_rank() == 0: + for key, value in losses_np.items(): + self.visualizer.add_scalar(f"train_loss/{key}", value, + self.iteration) + + @mp_tools.rank_zero_only + @paddle.no_grad() + def valid(self): + valid_losses = defaultdict(list) + for i, batch in enumerate(self.valid_loader): + texts, tones, mels, utterance_embeds, text_lens, output_lens, stop_tokens = batch + outputs = self.model( + texts, + text_lens, + mels, + output_lens, + tones=tones, + global_condition=utterance_embeds) + losses = self.compute_losses(batch, outputs) + for key, value in losses.items(): + valid_losses[key].append(float(value)) + + attention_weights = outputs["alignments"] + self.visualizer.add_figure( + f"valid_sentence_{i}_alignments", + display.plot_alignment(attention_weights[0].numpy().T), + self.iteration) + self.visualizer.add_figure( + f"valid_sentence_{i}_target_spectrogram", + display.plot_spectrogram(mels[0].numpy().T), self.iteration) + mel_pred = outputs['mel_outputs_postnet'] + self.visualizer.add_figure( + f"valid_sentence_{i}_predicted_spectrogram", + display.plot_spectrogram(mel_pred[0].numpy().T), self.iteration) + + # write visual log + valid_losses = {k: np.mean(v) for k, v in valid_losses.items()} + + # logging + msg = "Valid: " + msg += "step: {}, ".format(self.iteration) + msg += ', '.join('{}: {:>.6f}'.format(k, v) + for k, v in valid_losses.items()) + self.logger.info(msg) + + for key, value in valid_losses.items(): + self.visualizer.add_scalar(f"valid/{key}", value, self.iteration) + + @mp_tools.rank_zero_only + @paddle.no_grad() + def eval(self): + """Evaluation of Tacotron2 in autoregressive manner.""" + self.model.eval() + mel_dir = Path(self.output_dir / ("eval_{}".format(self.iteration))) + mel_dir.mkdir(parents=True, exist_ok=True) + for i, batch in enumerate(self.test_loader): + texts, tones, mels, utterance_embeds, *_ = batch + outputs = self.model.infer( + texts, tones=tones, global_condition=utterance_embeds) + + display.plot_alignment(outputs["alignments"][0].numpy().T) + plt.savefig(mel_dir / f"sentence_{i}.png") + plt.close() + np.save(mel_dir / f"sentence_{i}", + outputs["mel_outputs_postnet"][0].numpy().T) + print(f"sentence_{i}") + + def setup_model(self): + config = self.config + model = Tacotron2( + vocab_size=config.model.vocab_size, + n_tones=config.model.n_tones, + d_mels=config.data.d_mels, + d_encoder=config.model.d_encoder, + encoder_conv_layers=config.model.encoder_conv_layers, + encoder_kernel_size=config.model.encoder_kernel_size, + d_prenet=config.model.d_prenet, + d_attention_rnn=config.model.d_attention_rnn, + d_decoder_rnn=config.model.d_decoder_rnn, + attention_filters=config.model.attention_filters, + attention_kernel_size=config.model.attention_kernel_size, + d_attention=config.model.d_attention, + d_postnet=config.model.d_postnet, + postnet_kernel_size=config.model.postnet_kernel_size, + postnet_conv_layers=config.model.postnet_conv_layers, + reduction_factor=config.model.reduction_factor, + p_encoder_dropout=config.model.p_encoder_dropout, + p_prenet_dropout=config.model.p_prenet_dropout, + p_attention_dropout=config.model.p_attention_dropout, + p_decoder_dropout=config.model.p_decoder_dropout, + p_postnet_dropout=config.model.p_postnet_dropout, + d_global_condition=config.model.d_global_condition, + use_stop_token=config.model.use_stop_token, ) + + if self.parallel: + model = paddle.DataParallel(model) + + grad_clip = paddle.nn.ClipGradByGlobalNorm( + config.training.grad_clip_thresh) + optimizer = paddle.optimizer.Adam( + learning_rate=config.training.lr, + parameters=model.parameters(), + weight_decay=paddle.regularizer.L2Decay( + config.training.weight_decay), + grad_clip=grad_clip) + criterion = Tacotron2Loss( + use_stop_token_loss=config.model.use_stop_token, + use_guided_attention_loss=config.model.use_guided_attention_loss, + sigma=config.model.guided_attention_loss_sigma) + self.model = model + self.optimizer = optimizer + self.criterion = criterion + + def setup_dataloader(self): + args = self.args + config = self.config + ljspeech_dataset = AiShell3(args.data) + + valid_set, train_set = dataset.split(ljspeech_dataset, + config.data.valid_size) + batch_fn = collate_aishell3_examples + + if not self.parallel: + self.train_loader = DataLoader( + train_set, + batch_size=config.data.batch_size, + shuffle=True, + drop_last=True, + collate_fn=batch_fn) + else: + sampler = DistributedBatchSampler( + train_set, + batch_size=config.data.batch_size, + shuffle=True, + drop_last=True) + self.train_loader = DataLoader( + train_set, batch_sampler=sampler, collate_fn=batch_fn) + + self.valid_loader = DataLoader( + valid_set, + batch_size=config.data.batch_size, + shuffle=False, + drop_last=False, + collate_fn=batch_fn) + + self.test_loader = DataLoader( + valid_set, + batch_size=1, + shuffle=False, + drop_last=False, + collate_fn=batch_fn) + + +def main_sp(config, args): + exp = Experiment(config, args) + exp.setup() + exp.resume_or_load() + if not args.test: + exp.run() + else: + exp.eval() + + +def main(config, args): + if args.nprocs > 1 and args.device == "gpu": + dist.spawn(main_sp, args=(config, args), nprocs=args.nprocs) + else: + main_sp(config, args) + + +if __name__ == "__main__": + config = get_cfg_defaults() + parser = default_argument_parser() + parser.add_argument("--test", action="store_true") + args = parser.parse_args() + if args.config: + config.merge_from_file(args.config) + if args.opts: + config.merge_from_list(args.opts) + config.freeze() + print(config) + print(args) + + main(config, args) diff --git a/examples/aishell3/vc0/local/tacotron2/voice_cloning.ipynb b/examples/aishell3/vc0/local/tacotron2/voice_cloning.ipynb new file mode 100644 index 00000000..fc4705fc --- /dev/null +++ b/examples/aishell3/vc0/local/tacotron2/voice_cloning.ipynb @@ -0,0 +1,383 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import paddle\n", + "from matplotlib import pyplot as plt\n", + "from IPython import display as ipd\n", + "import soundfile as sf\n", + "import librosa.display\n", + "from parakeet.utils import display\n", + "paddle.set_device(\"gpu:0\")\n", + "import sys\n", + "sys.path.append(\"../../\")" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 加载模型" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "vocab_phones:\n", + " Vocab(size: 68,\n", + "stoi:\n", + "OrderedDict([('', 0), ('', 1), ('', 2), ('', 3), ('$', 4), ('%', 5), ('&r', 6), ('a', 7), ('ai', 8), ('an', 9), ('ang', 10), ('ao', 11), ('b', 12), ('c', 13), ('ch', 14), ('d', 15), ('e', 16), ('ea', 17), ('ei', 18), ('en', 19), ('eng', 20), ('er', 21), ('f', 22), ('g', 23), ('h', 24), ('i', 25), ('ia', 26), ('iai', 27), ('ian', 28), ('iang', 29), ('iao', 30), ('ie', 31), ('ien', 32), ('ieng', 33), ('ii', 34), ('iii', 35), ('io', 36), ('iou', 37), ('j', 38), ('k', 39), ('l', 40), ('m', 41), ('n', 42), ('o', 43), ('ou', 44), ('p', 45), ('q', 46), ('r', 47), ('s', 48), ('sh', 49), ('t', 50), ('u', 51), ('ua', 52), ('uai', 53), ('uan', 54), ('uang', 55), ('uei', 56), ('uen', 57), ('ueng', 58), ('uo', 59), ('v', 60), ('van', 61), ('ve', 62), ('ven', 63), ('veng', 64), ('x', 65), ('z', 66), ('zh', 67)]))\n", + "vocab_tones:\n", + " Vocab(size: 10,\n", + "stoi:\n", + "OrderedDict([('', 0), ('', 1), ('', 2), ('', 3), ('0', 4), ('1', 5), ('2', 6), ('3', 7), ('4', 8), ('5', 9)]))\n" + ] + } + ], + "source": [ + "from examples.ge2e.audio_processor import SpeakerVerificationPreprocessor\n", + "from parakeet.models.lstm_speaker_encoder import LSTMSpeakerEncoder\n", + "\n", + "# speaker encoder\n", + "p = SpeakerVerificationPreprocessor(\n", + " sampling_rate=16000, \n", + " audio_norm_target_dBFS=-30, \n", + " vad_window_length=30, \n", + " vad_moving_average_width=8, \n", + " vad_max_silence_length=6, \n", + " mel_window_length=25, \n", + " mel_window_step=10, \n", + " n_mels=40, \n", + " partial_n_frames=160, \n", + " min_pad_coverage=0.75, \n", + " partial_overlap_ratio=0.5)\n", + "speaker_encoder = LSTMSpeakerEncoder(n_mels=40, num_layers=3, hidden_size=256, output_size=256)\n", + "speaker_encoder_params_path = \"../../pretrained/ge2e/ge2e_ckpt_0.3/step-3000000.pdparams\"\n", + "speaker_encoder.set_state_dict(paddle.load(speaker_encoder_params_path))\n", + "speaker_encoder.eval()\n", + "\n", + "# synthesizer\n", + "from parakeet.models.tacotron2 import Tacotron2\n", + "from examples.tacotron2_aishell3.chinese_g2p import convert_sentence\n", + "from examples.tacotron2_aishell3.aishell3 import voc_phones, voc_tones\n", + "\n", + "synthesizer = Tacotron2(\n", + " vocab_size=68,\n", + " n_tones=10,\n", + " d_mels= 80,\n", + " d_encoder= 512,\n", + " encoder_conv_layers = 3,\n", + " encoder_kernel_size= 5,\n", + " d_prenet= 256,\n", + " d_attention_rnn= 1024,\n", + " d_decoder_rnn = 1024,\n", + " attention_filters = 32,\n", + " attention_kernel_size = 31,\n", + " d_attention= 128,\n", + " d_postnet = 512,\n", + " postnet_kernel_size = 5,\n", + " postnet_conv_layers = 5,\n", + " reduction_factor = 1,\n", + " p_encoder_dropout = 0.5,\n", + " p_prenet_dropout= 0.5,\n", + " p_attention_dropout= 0.1,\n", + " p_decoder_dropout= 0.1,\n", + " p_postnet_dropout= 0.5,\n", + " d_global_condition=256,\n", + " use_stop_token=False,\n", + ")\n", + "params_path = \"../../pretrained/tacotron2_aishell3/tacotron2_aishell3_ckpt_0.3/step-450000.pdparams\"\n", + "synthesizer.set_state_dict(paddle.load(params_path))\n", + "synthesizer.eval()\n", + "\n", + "# vocoder\n", + "from parakeet.models import ConditionalWaveFlow\n", + "vocoder = ConditionalWaveFlow(upsample_factors=[16, 16], n_flows=8, n_layers=8, n_group=16, channels=128, n_mels=80, kernel_size=[3, 3])\n", + "params_path = \"../../pretrained/waveflow/waveflow_ljspeech_ckpt_0.3/step-2000000.pdparams\"\n", + "vocoder.set_state_dict(paddle.load(params_path))\n", + "vocoder.eval()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 生成 speaker encoding" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "首先在当前文件夹下新建文件夹 `ref_audio`，把要作为参考的音频存在在这个文件夹中。格式要求是 wav 格式，采样率会被重采样至 16kHz." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ref_name = \"女声2.wav\"\n", + "ref_audio_path = f\"./ref_audio/{ref_name}\"\n", + "ipd.Audio(ref_audio_path, normalize=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "mel_sequences: (2, 160, 40)\n", + "embed shape: [256]\n" + ] + } + ], + "source": [ + "mel_sequences = p.extract_mel_partials(p.preprocess_wav(ref_audio_path))\n", + "print(\"mel_sequences: \", mel_sequences.shape)\n", + "with paddle.no_grad():\n", + " embed = speaker_encoder.embed_utterance(paddle.to_tensor(mel_sequences))\n", + "print(\"embed shape: \", embed.shape)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 合成频谱" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "因为 AISHELL-3 数据集中使用 `%` 和 `$` 表示韵律词和韵律短语的边界，它们大约对应着较短和较长的停顿，在文本中可以使用 `%` 和 `$` 来调节韵律。\n", + "\n", + "值得的注意的是，句子的有效字符集仅包含汉字和 `%`, `$`, 因此输入的句子只能包含这些字符。" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['m', 'ei', 'd', 'ang', 'n', 'i', 'j', 've', 'd', 'e', '%', 'x', 'iang', 'iao', 'p', 'i', 'p', 'ieng', 'sh', 'en', 'm', 'e', 'r', 'en', 'd', 'e', 'sh', 'iii', 'h', 'ou', '$', 'n', 'i', 'q', 'ie', 'iao', 'j', 'i', 'zh', 'e', '%', 'zh', 'e', 'g', 'e', 'sh', 'iii', 'j', 'ie', 'sh', 'ang', 'd', 'e', 'r', 'en', '%', 'b', 'ieng', 'f', 'ei', 'd', 'ou', 'j', 'v', 'b', 'ei', 'n', 'i', 'b', 'ieng', 'iou', 'd', 'e', 't', 'iao', 'j', 'ian', '$']\n", + "['0', '3', '0', '1', '0', '3', '0', '2', '0', '5', '0', '0', '3', '4', '0', '1', '0', '2', '0', '2', '0', '5', '0', '2', '0', '5', '0', '2', '0', '4', '0', '0', '3', '0', '4', '4', '0', '4', '0', '5', '0', '0', '4', '0', '4', '0', '4', '0', '4', '0', '4', '0', '5', '0', '2', '0', '0', '4', '0', '1', '0', '1', '0', '4', '0', '4', '0', '3', '0', '3', '3', '0', '5', '0', '2', '0', '4', '0']\n" + ] + } + ], + "source": [ + "sentence = \"每当你觉得%想要批评什么人的时候$你切要记着%这个世界上的人%并非都具备你禀有的条件$\"\n", + "phones, tones = convert_sentence(sentence)\n", + "print(phones)\n", + "print(tones)\n", + "\n", + "phones = np.array([voc_phones.lookup(item) for item in phones], dtype=np.int64)\n", + "tones = np.array([voc_tones.lookup(item) for item in tones], dtype=np.int64)\n", + "\n", + "phones = paddle.to_tensor(phones).unsqueeze(0)\n", + "tones = paddle.to_tensor(tones).unsqueeze(0)\n", + "utterance_embeds = paddle.unsqueeze(embed, 0)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 73%|███████▎ | 733/1000 [00:02<00:01, 255.71it/s]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "content exhausted!\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "

    " + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "outputs = synthesizer.infer(phones, tones=tones, global_condition=utterance_embeds)\n", + "mel_input = paddle.transpose(outputs[\"mel_outputs_postnet\"], [0, 2, 1])\n", + "fig = display.plot_alignment(outputs[\"alignments\"][0].numpy().T)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 合成语音" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "合成的语音会保存在 `syn_audio` 目录下，使用和 reference 相同的文件名。" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "time: 19.793312788009644s\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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SgmpWAdDsomzxgLE/V7mJfbS4+EIZZXPUqj2k3YgJJ7MIK/yYzs9YvQu/pWYrSzb57xI0Qp31qhX8+z4qnUzmZJQP2L85Ld9qPUM2qsL5rzkbdV/X4iTxTttfQB0wYKUDWSMnGQ4a1QwdM880auyPby9Gl8e+QtbISRj40hz0/bv7CDOrqqda7PweamIh+EYccLiQpGC3KJoRTsO/nPrwp6/aiQ8WWi8KZo2cpJuMstRkIcdsAXeTjmC+/q29ixQA3lRluSo3JivMblxZIyfhRF4+5v6811aYph/h1eqy2O/Mz3X0WaNm72bng5FI9X++eCbpJRPZKau3l3Sn2unsZYTd0N2JJr0BtMfX3lzslkJWsoqvHfc9Pvthq+sGNIr7OKxe2k6JheAXGHyX/wypt6rTWi+jHfrTb3lvCR78bIVlKCkAjJm1AVkjJ5UY2Rgt1Fm5Wd6dn6v7eq9nZ1raIQA8/qW5/7TL49Mdj5IX5/6Ka8YtxPrdhy2F7sHPSqfXO0HbEETb7N1p1I3RSDd37xHD5upOw+zMcBIea1QqWbugPuy1+fhimX919K2uLatzwK7wdn3iq6Lj3ffRcsM6WXrfYdbISUUDsp7PWF8bdtinueHIKhGtJRaC/8Zc/VFmWI0NnEainHRZd/zy1+ZjxITltjJl1dUmtTVSAOCNORvR+7lZpvtQYqO1rjK9kb8WOwlnB46ewlKHgv+hKvzxEYt6P14Lo2nFdt56/8L3jEaUMmcpc9bvtR3TbrbIrg2CuGe8/KSpIjssCptZ/TluEwCNSmgv3ax/vj742QrTnInJK+wvcgMl13/+POFHtPnLFEeft0ssBN9IcMxGMHoLHGq8FFuzqvmhZvjYBZ4yAD9evBXXjlvo6DN6NVKMeqlq2bL/KI75WDnT6dRX3bxits/hpdrRpZlrwQtCGC/k60Vi6GFnveLYyXws+MX7TStXp2rmI1+sRM9nvpHeJtFqMBV0mRLt4dRCbhZ1dPv7Sx0dR93iUr2GJptYCL7RoEfJjv1B5y583qhvTPdp1RRDFk4XYfSq/pn55BVaP1Q8IvAySoxaO7itv8qt0eME3wQfQJrBQv7BY6dsRcKs3/Ob5TavfbvBU90VhROnSov6O/M3Ycv+Y3hB8nVkJfhBdyzbdajkrE/t1otj5dV4CL6Fgl366jzH+/Sz5s2PW93v20nVPyO8FIeys25gF73mH3ZHsGEQlJTk5RfoiqjCBzayeD//wfpmJKu1370fGbtwtKGoXrEab9gRfJm5Nn9XdZU6eOxUqXWduBELwfeCUVyrn2VytXX0g8aLG/jrNfJqoL+uqnGvdAXz2h1MO+KKI/+asxFjTUIUt1u4I4MmyCS6PKMIjRR2Zl1uc230XMTqa6nzY9NNawDpkV8gInWTKPOCr5eU4jcxaHBlyLRV+oLvpkyA8pnPf9gmrRm8nQVkt6j/Rtm+aTXTVu3CMRMRWL6l+Jw1EtuFEnzzfuC1DMpEC0Hd6qDTU/kMZ/KmW/rb4yL6C1/9hPYPT3OVFPibDyVZYiH4ezwsevp54Rolbfih904uJDd9Xa1o+9eptqKF1MxcV7jI+uy0ddLs0HPF3freEtyjqXXjhhOqUDi3FUbthuyaud3mqqo5dnxkmm4o665D0SkFrI5WOWJR2M0KqzUkdRKmVRG5IV0aOjq2XoZvuXRvEvnPmYWh4z/vcp59m/OyvZmKk7LVsRB8LzGp75skMHkdjRitxGtjamVw6Ji12G5N1UPJ9WEUfDKvwPXNUxsx5eV7f312aZfQ1FU7HU+19Xj7u1wAhQv+Rs00rNwbtvvAOvgK9gRQPtoL7xmUzHaDdX/o4sdWN+WPFzsrT62XR7J2p/XiuBFqV46bQavdUutOAi1iIfhumWuRKLMhVfPC7dTJKOZXGYXaSdu2i51QSbcNKuxiVMrCKV7us3sPn8RN79jL4nXK8dS02yyk98DRk6bhwJk2R4RO+iaY9el9wiLZLQjUf4ud9oFmNYmsEvOiXllVzXHVwvxjJjkkXgee9zrIiyjTgn+NRfz6sZOFP4gfkYgFBQJ/+Jez+HkzptqoVvj0ZH/7ynR+fLqU/SiRFm5zIWasKRYVbc14vxHCfESleGqsImR2Olh8XpRrLIJWTduDQB1ZZjUTFUJ4KkPgd0e55VsOGFbbdYravWc2616w0Vtk3AwHgRaxF3wvd8e3vvPvYpmy0n7FvzdtXLRGcdtqvraYDkcF5ReTEY3yx7cXW29kE7vzl+MmC3CKb/6SV+LX1EUGVus8i3J/lTRPBMbMMi6t4rT8icKQV77DEEm/nTbiyGhwcuxUcFE8sRd8L6PzU6kPe51S6XHHB/Yz7axq0ADWjSyiil7Ti/mpjkNR6yX9+bLtlsXBXp21HlNM0uY/shFDXxZRBPanXeY+72On8j1HvigYtdsErEs0mOG2kJoW7drjH99erHsjmv1TcC0XYy/4XmqgV0iFbcUhjPK56fYyGv2MSnLDUZ1ICiV7doJJ7e+weMYioujD77folq5QWLXdfcmOOKMUVOvRopbpdkIIaWtBfuI0Is0uz00vfX69PS/Xl2PpEXvBV/tznfJzqpZ90OnafvLqTLmZj155wKQVoFVj8TCwU/foLzrlLxTi4laTzf0fF5YZsJq1vTd/k5TkOatZ+bRV3s4to+qhTtAzURvF5bXgn1MiL/hWP+zdH7qPv1YW1nbEZOXfTrnbCUv9K7zkBnVMucKDn61w1RVIjVsfrRVGNewZexiVhFbYf/Qkpjhol2iE1RrZiE+81RBastkfIdbK2XMWM0ohBPLyC2w1ordD5AXfbPosC6+jgaCwU4dmi4NMxDDx0hUIAI6czLPVBzQM/LoZxQEr//eW/cekuHRe91iiwwoZwQCfLLXhsrT4Ko6ezPeUC6Al8oK/1aC5skzGzrbf1SlMth7w/7uIC8PHLvBl0VdGOrsfQQB6PK/jDw4TO+tHew+fwGoPpcmBwnwTp639wkAJTlCjPWetgu+I3NcG0iPygv+5hAxKKy7qUN/3Y8igesVyYZsQGVZtP+RL/oRRLSEnBDXAf9lmxzeJLZVNmbdhH07LTLfcziqb1gqzhuJRQs89OHnFTkdu6I0WfXkV7A4yoi/4Fj5BGfzHp7rnsikoEKiQGfmfLDCiutgeNbuCugFNWbEDV5zVxHK7tvWqeDqOUStOLVVPy/B0HL9QV/zU9gzWYrUmomC3T3fk1aNh9QphmxAZ8gqEYaekJCIjksIPJpl0QirLjF+0BRk2phOdm1TzdBy7NXK6Na3h6TgrPLqNvrfRW8Iq6zgj3d71brdXdOQFv3tWTV/373f9GZmczCvw1NykrNHj6a/DNkGXn2PicvADIaxFymtFTbt4LSLoR3liLQ9f3MH0/de/tbe+eJvNloqRF/zW9aqgUnlrv6BbZFb685sRE5YH2oyCcYfHirqx5t0FmyxnXkHNgH7Za7NyaYgoCWtBEflT89GJq3DkhH8jgicn22vu7TdCCORanKBxiExggB9s9CAuq/hd3CxI3vexTMaW/UcxfdVOLJSYeLV+t3X4ZuQFP6dTg8CiDMJk6eYD6P3crLDNYCSQ5Dj8soSfM5GhY+bhlveWOO7KZcbN7y6x3Cbygl+vajIWbYeOcd6InYkmMkdtTNlE6al9wkNzJy12XFiRF/y8fBFYWBnDMEyc+U6nlIkaKYJPRAOIaB0RrSeikTrvlyeij1LvLySiLLv7jlr1R4ZhmKhy9RvmTZc8Cz4RpQN4BcBAAO0BDCei9prN/gvAr0KIVgBeADDa7v4PHItmvRSGYZgoUq5+q25G78kY4XcHsF4IsVEIcRLAeABDNNsMAfBO6vEEAP3IRkB5QYEIvHwowzBMWUVG7nEjAOqavFsBnG20jRAij4gOAqgFoITDiYhuAXALANSs1xAtHpwswTyGYRgGiNiirRBirBAiWwiR3axRAzwzrFPYJjEMw5QZZAj+NgDqikmNU6/pbkNEGQCqAShdO1RtGAFXZDfB8O5NJZjIMAzDyBD8RQBaE1FzIioH4CoAEzXbTARwferxMADfCJv1PKtXzJRgIsMwTDI4uXO9YQaWZ8EXQuQBuBPANABrAHwshFhFRI8T0eDUZuMA1CKi9QDuB1AqdNMImZloDMMwZZlnhpq7waUUjBZCTAYwWfPaw6rHxwFc7mbfGWmENAqupjfDMExcueKsJrjS5P3ID5+PnyqQ0gMz6tx/YZuwTWAkUbMSdyZj7CHTg2FnX5EX/DfmbkR+xDoI+cFdfVvh3T92D9sMRgLt6nvr6MREg+7N/evFMeHWc3B775ZSa+l8cHMPy20iL/hPDOloq0+mW/7Uq4Vv+3YCEeGCNnXCNoORQPsGVcM2ITRqlKEgi9t6t/Rt39lZNTFiQDvUqVJe2j7PbFLdcpvIC/6Bo6dwzMeuVLf3auXbvmUz5Z6evjaDYeRQwccBStR5KKe9pWuhV0ADm3pVvYlp+QA62Tw06HRp+0qzUUc+8oI/x6L6m1eqxWhEUiEzHSj73i3bzBnRJ2wTdKl2WnzOKdmkkXXJX69CbBevM63MACIER09da/r+1Wfby0MaddkZtraLvOD/sje5/UG1ZKQR672KqI6kr+nRLGwTQuG8VrVsbbftwDFPx7mofb1AjpPdzFsT9M42XCx7UnXxjahYzt453qutvVlT5AW/d5u6vh+j/+n2TqCwSUsjHA2oAXQcSI9oK7So2RWUPTed3wITl2+33O679aZJ9pbccG6Wre1+2uVtsGijvqMpRq6tMxpVK3qcnWV+U+nZ2p6Q161ir1FU5AX/iuwm1ht5ZO76Pb4fQwZHuIF5EZXKpfvS+vKcFvZGqWYEpfddbIwggeBaLnbLqoG9h81HrADQsZE3V0snm3932OgVE7iwfT18evu5qm3M92F1Q1Cwe1OPvOC3qV/Z92PEpV5P9QT7hrXM+O9evghZoxqned6H15GhXT6/47xAjmOXqhUyLQWsftUKnhdtK5fPQO3K0c91aFG7tHZlpBEyHSwGCwG8dFUXaTZFXvAz0/w38UKbPsGwqVU5mMWuIHjrxrM8fb5ulQqRTXCKmEcnUKxCqGtXKSclkXLEgHae92HGi1d6F1m9kG/tWMBqyHJaZjoGdmzg2RaFyAu+VajRf3vIUFUEo229eCTK2BGSm85v7r8hDqhSoXT1jicv7Yg+bb2tzaSnkS8jaRk5fkGN8KPIZV0bm75fISMd57b07ja79MxGpu97za+RETqaZuM8GN7d3GWdlkYol5GG3FE5nu0BYiD4Vlx3Tpbrz/Y/vVB04nKB2rHz3oiVaNBzOygjvCiGL2amW3/Hj/5e28GzmK5N4+Ffls0DAwtH3JV1bvBqbuvdEq0lDLCs3CJe82vSbZwHVuhdrlUrlDznLz3T/AYpm9gLvpdEJCXiJQ5T8Ft72cv6q1xeSj08aejZowj9C1d2DtocSx7KMU+EaVW3MsqbuC06NU6m4CsDr/kbzCNwMtPTIGIQXKwVZlk8rDNYCDIzO/aC7yXkrCA1f/ejONtfLIRDzTU9rBeNG1SzF3YVNepVLW33RR0K10yiViJpSJeGqGJxob91w1mm7qgbz8uSbFU8OC0VL251nsqcTPdsXdvSnjDJ0MxCbu3VEhXLlR4A/c/vgpuVx17wvbhjrlfcQT6M8J0k3zw+uKOUY8qsy+Enytcto7lNGFVGa1Qytlu5yJ9NaHvO2haBBee0qCUtW3y0Se33ci6zZJ+69Ax8cLO2Jbc7ymkEf+RA/YXmIF3KsRd8M6zSjf2M8qiQmW74A2uxUwPDzkLXBzfJOVGNWPKX/lL2o5zg3Zq5q0ao9v3f3a+1FJvsQgRkmESOFaRCRS+XmD9iti5wto8VHe0y6Iz6RY8zLHzfGelpts53I9SDGjuLok75w9lNcW5L45mDE9R/ZrNaFQ23u8BmcpURTWsa71tLmRb8qyzi65vVqgQAqGqx0GSE0aJjq7qF8bd2/e52sJNJp51CykbWBeZlL+XS07D8kYuk2KHFjl2Vy2eYuhHt5gY4Kb07rJvxzeOjP51jez9+0Vm1bjGgY32TLQupWdF4oGXlEurW1Fu5gyBRzzJuM9ECr5nQ6kQuK8q04APAFdnGq6HK398AABgNSURBVODKD+J2SvVng1hgJ3dcu9hZnM5KjSL8mrm4jVzQum68jPCuP7e0q6xF7UpSFr6uS6Xs547Kwbf/21t3m+omYgXor1no4sCtkVVb/vkkE3WIpJ1Bgdnvf+055q5Q9eSqosU1oZ552GHEgLalXvPS20C9HtRRVU7BLlqXkBGVdNYFjIiF4Deq7j770c8CW38wqGTnh0fOzuhduXH5ccPZ+NQgx5ELfVIFnW48V15uwEUdSl/EX93fC1/edb7nfaszmW0Ltwa7i4UFJivW6hnnjPsvQI/m3uPW/aSu6rvy2rvC6oahDrCwOh+XbT7g6Nj92pVOwDyV761ByZAuDQGYu3SMmGUw6NDiZIE6FoLvBS83C7fEJKxfF6NKhG5G5coN6J7+rdGiTiVPdinU0VkUTE8jT7MGBfVMz8+BwlkW9VHUo9xWdavo/m2/79xQul0y8OqeUHJjjKjqIHdj+8Hjjo6tuGLVeF1fHnVZJ8z9cx/L6C89GvqgXWVe8G/uGXxHK5kLdm7wcpKeKdFHOlglSt/8d28A9kJQzciqLefGESZ392ttur5TuXz0EtKCotpp5i4zO/Xhn7vcXX6H3s1KPRGb/0Bf9G3nLEP8tHLpaFwjOi65MiH4b96Qbfie0cjPz5LIv9NxO9ilm8ca3AA8BbjbWXSzyyU66e8NqgU/47JLUBOzKhUyTRvv/JeN8hh2Uv9lzW7/MfxMw/cUl4UsrCYIdtYIhnWTl72qDq+uX7WCa1dfVIiF4OuVGQWAhqkV/b46vrf/u9U8esFuJ5mgmaBjt53KgD8/ObDocUDVcAOhsYTqlW6RUSpZjzQqDt/Ue89ODHmXJtaLgA8OOr2o5IEX9PIllEXyx4fIySFRsBL0AGoplqBT4+LvmYjQtl6x28dul6koEQvBN/LbmS1WnJVlHvbWx+HUTI2TLNrcUTmWyShq9CKGJt7pbEFSL3W9TT17ZaazalVEhUz/TosMhz5eteDb/RvcohUbP7NmjW7Kdv22LetYfxeZ6eRptqmgl9A3+Z6eyB2VI70ektVajB9Z8WZox5rXq5qv9DPxEtzjMD9E7f70EhlkRSwE3+jLM0uA8ROnC3pGMxQrnru8M3JH5dgSAbVY3XR+6XWL6ff1sixJ3LN1bdchquqRkBmtHYr2bb2Li2D9/XJ5dcH10AqbzPUMLV5vqnZ+p95t60rpdtWufsmQVzsuJ7dYRflY/Tk1XGZvG2Vsa5u1KN/7wI71TTPb7+3vTPAvV4WPT767J74b2dfR5+0SC8E3muIahUX6jdOL6B6HP/6Dg9phYMf6tnyRvdvWQe6onBI21TdIXrEqSXxXX307Nz41yNKONCLLUq+/PD1I1/1mRpfG1fHQoMIZ1RkWN5Up9/R0tG8t2hmj1pVmVrtFD6MSvg2qnWbYrcpNNIcRTsoL2C1z8fGfzsFfLzauFuoVK5utFkDtNhf5j2rWPLx7E+R00q85r1f7JndUDsZc0w2AsevY6cBJXaI9LY18iy6MheAbfXeyQv2c4nR01sThKv0tF7QsOqHMWPe3AXj7xu6lXu/qcmTasHrpG8VZWTVshzw+fVkn1ePS/k2nF0HuqBxUq5iJmy9oYaseuFN3kRVEVCIZ52IDUTDCaGZXp0p5w+/iDIP2f+o8gyY1g1vXCKPfs1lopvamrC05Yncwpgwenh3WCU9f1smWi0wPK9dx1IiH4Bv47dwGo6x+/HcerAEGd25UYoSg5nKdUblZko1T1OsH5TP0p79moyT14q4WZfSkjgAZf4u91H2tfp1hM7Nw+cPyyiQYzWy8oE6J79XG2bqPzMVz9eAmXfNljx7qffHQbtkMO1FkZxrU/rmvv71Cd01r2h/IPXFJyUVjteDrNd9Rs/aJAbZCqP92SUeMu944EvDaHs2w4IF+yB2Vg5eu6mIaNWiF05G9k/VBICaCX9Fgcdbo5Jv5P70N9/XkpR11p2lOSE+johHC2icGlHjvfJ1pf57EK/+mni0weugZWPP4AOuNdbAz5VVP2W03R04JhlIl0u7io1l4olNkukMUiKiozILVDUXr8pGZgKc+Z/M1A4g2Og1FnHZIus6ipIFyw7FzPqj94ep+0VaF1RSchFW20ORlqMMmb+ttXsvK7lrcNT2amS7QPnFJx6JzY0iXRo7dlkDx7Pc+k+qvejewbIdh3LEQfKNpUyWDZh/NDEoLPPr79rj6bPtli+1g56RxU0fDjCvPamqZTu00QURN4xoVsfGpQY5uKooOKL7QqPabdUOdKuVRxUZjmff+q2S1Uq96bxRrP6xryVGpdjalzuS1uukseKAfpt7bE9kGlUsV374TYTm/VfGNT+1ysVsV0skamdY19tjgDsXvBRzR4wU7pc1r6VxTTtcTYyH4TtPmtdsro4yeEvpUWqHnm20QQrKGevrsJp48LY0c1eioVanwhHVTUTPqpSgqlsvAisdKugH/dIF1BrebiCfl+8uqVbFUSKXiitRmK2vrLKlvFFZRL/WrVUC7+lUNo1+UTPUrz7KfPa7+u9UDj6Yu6sk4RfbgKkroBVVYBTJoiVY/PJ948pKOyEwnNK/lfZF36V8vNH0/itrlZ1y9wu19WqaOlY4FD/Rz9NmJd5yP3/9zrh9m+cbIge3w+uyNptvouVrM+OS2c9Ey5TqZ9b99Sr1fPiMdzWtXQi0Lv+11qljxWpXLY9Vjv0OHR6aZfqaFwaKlUqnTaL3IiO9G9kXdKuVLlIuOSg/jsII97GAWg1+3aunf3elM3pMSEFFNIvqKiH5O/a877yOifCJalvo30csx3ZCWRnh8SEfTmYKeKDbU8dlauSr0pl1lCaPiauqcCKeLp05HKW6wahTidGpsZ/R+ay9ndZy6NathWn45PY1M16cUtFUkjVyfaox+M0XoOzaqhlk2jq3QqPppyExPQ4XMdHx4cw/88nTJ0N7uJtEtsmZ8RvsZ2jXYxuF2yR2VYzpD0XMfO3Wdeh36jQTwtRCiNYCvU8/1OCaE6JL6N9jNgZY9bD6y9ope5yQ3DUXObSWnW45X2jesilf+0BWf3n4uRktst3ezgSvDSzN5Pb644zyp+7ujTyvTfIINNnINnBJk67ogcFu47pyWtUp9F2//0TwJ0E/cJkKGjbKOou6AFnSUzhAA76QevwPgEo/7M8Sq8YRX9M4Bv0cafpKeRsjp1ABdm9aw1S3Lro1GNcibSXCXqZFdpOr8VrWllFBm5OA1Uk6NkuXtNDIpbhARpt7bEy+bFLOzwqvg1xNC7Eg93gnAKB6pAhEtJqIFROTbTcELenf9JMmD3cXWtj7V+VC7wl66qov0mHoWe+fIKLxmhrarmFXJBqPudf8c3tWyNaIat4mJUaBd/aqOR/VqLAWfiGYQ0Uqdf0PU24lCxTSaKzUTQmQD+AOAF4lIN0CWiG5J3RgW79mzp9T7F5hE2ZzuscWdXqj8cE1P3Mu66qfKlwX+doncqodOUXeyGnSGs4xWNVYNNF75Q1fX+y5r3N23VYnn2kzlHj5VC1XQzgr7Wfx2D/++g+7rTWtVxHydQAEjz00bH4uTBYGX5jyWgi+E6C+E6Kjz7wsAu4ioAQCk/t9tsI9tqf83ApgFQHdOIoQYK4TIFkJk16lTWtxlp86XPHbp19o3tFc0ymrVPw6+XL1OUkHy6ODiZC+79VD0eMyiXK+VqMhmpM+jZC9o16gaaEprdDao9yOTK7OboEuT6hjWrTE6NDRfvHd6/etVjQWMEznjhNs8F68unYkArk89vh7AF9oNiKgGEZVPPa4N4DwAq90czOzn7t3WW4y9Xtu5ZjUroZLq5DA6IUf8LroXtV3CvifJqnzqpuiUX5UJAZh2tgob7SDnhSu6YFi3xlj28IVSS16YMXpYJ3x+x3l47vLORWGbbnI59DAa4ctcPwgLt/kGXq+yUQAuJKKfAfRPPQcRZRPRG6ltTgewmIiWA5gJYJQQwpXg36magr6tKfVr1SfUim6qz795QzZ+eXqQ7UQRmV2igkap0qedzQSNjDK+Ctf2KJlNbVQJUSHTZ/9+VOLPrcjOqonnLu+M6hXLSS154RS9In6Av32G48aN52Whn4tsek+CL4TYJ4ToJ4RonXL97E+9vlgIcVPq8TwhxBlCiM6p/8e5PZ66Prm2VnlPm2nbRijxxs9f0Rl929UrcsNceVY0O2N5ob1qveOVqwt92l5aD8rSywcGtsOYq7372NXp9UBJv30YM5nxt/Sw3Ob8iITzRgFZI3AlEENb074s0KdtXYy7wXloayxKK6i59MxGGNq1calRkxe/r0LuqBxcpknK+EvO6Vjx6EWWxaXihLq8bqu6lT2Hs8la3PtTr5YY6GHBVsEsIkcvY1TGaNbMdWMUUKAOCvBS+wiwLp+hNxq0mvnEHSUaR4Y2lBVi9028cGUX/P0Kd13p3ZCWRqhSIVN6784wUeqjyGLc9eEl0cjAadkAhcGdGxaNzBtZ9N59fEjhrKNSiQXDYiez1zUoBaN7nZ5bKS6uJrcoIcQ1fM7hiRPxX73QYFSLmynGqhaLU5wUWStLKAkwM1bvwrmtzEfY152ThYe/WIVHBuuHFlp1crLi6h5NMX/jvlLurCKiHygmnfIpn39Tg+q5SSR2I3wrPrzZ2l8aJdwsvDDRon/7erb9zkO6FDerVrecdNKOUI+cMxrg4Yvb49pzsjztJyrccG4WblAVgXND5VQNobLuunJCmRP8sMML40BNj1Pcm3xsYi2bCQY9R8Mgd1ROCfeR4ts366ZkFyLCH01+F9mlKvzm0cEdpBU5Y0kopky5dPq2q4tMSfHcTrmwfT18tXqX488NVo34gsLrImUcXDgNq1XA9oPHI51G36RmRXRuXA3nBRChM6hjA4yZtaHEa1EfHHWQECrcpl5lNK9dCSsevQjlM9I9z6TiTpkS/DddhCnJ4vkrOuPQ8TzHn/NaEiIM4lBs8IUru+DKsQsiX0PnC4PeyLLRE3cvNVmCQMZvN/2+XhIsKTuUKcEPkyoVMl31VJXZ4NwpXV0ucMdhYfzsFrXKfPVEhnFKsuc3ESAvPzzBd3tos4bOTDyoqtMQmyn7sOCHTGOL+G0/ae6hx+iN52XJMyREqodYQiBMRg+V1xSHiQ98mw8Zvxu7GDFnRB9PNecf+X0H3NuvDX47cUqiVcHz/YP9wzYhFCrEYOEdAJ4Z1gkjJvyIe/uX7kjHOIcFP6E0kZCMUq1iZqhFtmSQ9KiNqHNFdhP0aVsXdapEe4E5LvDZzjAJoIbL+ulRgMVeHiz4AfHUpWeEbQKTYLR9AtrHMByY8Q4LfkD42a2LcUabepXDNiF04pZ5y8iBBZ9JHJyMwyQVFvyAaBvzxskMw8QfFvyAaFOvtOD35wQmhmEChAU/IPRqmbAvmWGYIGHBD5FLz2wUtgkMwyQIFnwmsTx9GYfKMsmCBT8g4lBSOGmEWamUYcKABT9EWG7CpYnHPrIMEze4lk5A6C3acjJWeGx4ahDS+ftnEgaP8EOkRR2O0gkLFnsmibDgMwzDJAQW/IAol85fNcMw4cIqFBBRb6bNMEzZhwWfYRIG15dPLiz4DJMQLmhTBwAwg6uFJhYWfIZJCJkpt2Lc21Iy7uE4fIZJCNf0aIYG1bnxSZJhwWeYhNCnXV30aVc3bDOYEPHk0iGiy4loFREVEFG2yXYDiGgdEa0nopFejskwDMO4w6sPfyWAywDMNtqAiNIBvAJgIID2AIYTUXuPx2UYhmEc4smlI4RYAwCkVyimmO4A1gshNqa2HQ9gCIDVXo7NMAzDOCOIKJ1GALaonm9NvVYKIrqFiBYT0eI9e/YEYBrDMExysBzhE9EMAPV13npICPGFTGOEEGMBjAWA7Oxsrh7MMAwjEUvBF0L093iMbQCaqJ43Tr3GMAzDBEgQLp1FAFoTUXMiKgfgKgATAzguwzAMo8JrWOalRLQVwDkAJhHRtNTrDYloMgAIIfIA3AlgGoA1AD4WQqzyZjbDMAzjFK9ROp8B+Ezn9e0ABqmeTwYw2cuxGIZhGG9wLR2GYZiEwILPMAyTEFjwGYZhEgILPsMwTEJgwQ+QPw9oF7YJDMMkGBb8AKl6GlejZhgmPFjwA+Sqs5qiRZ1KYZvBMExCYcEPkPQ0Qss6lcM2g2GYhMKCHzDNalYM2wSGYRIKC37AVCxf6Me/q2+rkC1hGCZpsOAHTPesmgCAW3u1DNkShmGSBoeNBMz5rWsjd1RO2GYwDJNAeITPMAyTEFjwGYZhEgILPsMwTEJgwWcYhkkILPgMwzAJgQWfYRgmIbDgMwzDJAQWfIZhmIRAQoiwbdCFiH4DsC5sO0yoDWBv2EYYEGXbgGjbx7a5J8r2Jcm2ZkKIOnpvRDnTdp0QIjtsI4wgosVRtS/KtgHRto9tc0+U7WPbCmGXDsMwTEJgwWcYhkkIURb8sWEbYEGU7YuybUC07WPb3BNl+9g2RHjRlmEYhpFLlEf4DMMwjERY8BmGYRJCJAWfiAYQ0ToiWk9EI8O2Rw0RvUlEu4loZdi2aCGiJkQ0k4hWE9EqIronbJsUiKgCEX1PRMtTtj0Wtk1aiCidiH4goi/DtkULEeUS0QoiWkZEi8O2Rw0RVSeiCUS0lojWENE5YdukQERtU9+Z8u8QEd0btl0KRHRf6npYSUQfElEFX48XNR8+EaUD+AnAhQC2AlgEYLgQYnWohqUgogsAHAbwrhCiY9j2qCGiBgAaCCGWElEVAEsAXBKF746ICEAlIcRhIsoEMBfAPUKIBSGbVgQR3Q8gG0BVIcTFYdujhohyAWQLISKXPERE7wCYI4R4g4jKAagohDgQtl1aUtqyDcDZQohNEbCnEQqvg/ZCiGNE9DGAyUKIt/06ZhRH+N0BrBdCbBRCnAQwHsCQkG0qQggxG8D+sO3QQwixQwixNPX4NwBrADQK16pCRCGHU08zU/8iM9ogosYAcgC8EbYtcYKIqgG4AMA4ABBCnIyi2KfoB2BDFMReRQaA04goA0BFANv9PFgUBb8RgC2q51sREdGKE0SUBeBMAAvDtaSYlMtkGYDdAL4SQkTGNgAvAhgBoCBsQwwQAKYT0RIiuiVsY1Q0B7AHwFspd9gbRFQpbKMMuArAh2EboSCE2AbgOQCbAewAcFAIMd3PY0ZR8BmPEFFlAJ8AuFcIcShsexSEEPlCiC4AGgPoTkSRcIkR0cUAdgshloRtiwnnCyG6AhgI4I6UazEKZADoCmCMEOJMAEcARGrdDQBSrqbBAP4vbFsUiKgGCr0XzQE0BFCJiK7x85hRFPxtAJqonjdOvcbYIOUf/wTA+0KIT8O2R4/UlH8mgAFh25LiPACDU37y8QD6EtG/wzWpJKnRIIQQuwF8hkLXZxTYCmCrarY2AYU3gKgxEMBSIcSusA1R0R/AL0KIPUKIUwA+BXCunweMouAvAtCaiJqn7spXAZgYsk2xILUwOg7AGiHE82Hbo4aI6hBR9dTj01C4KL82XKsKEUI8IIRoLITIQuH59o0QwteRlhOIqFJqER4pd8lFACIRJSaE2AlgCxG1Tb3UD0DoQQI6DEeE3DkpNgPoQUQVU9duPxSuu/lG5KplCiHyiOhOANMApAN4UwixKmSziiCiDwH0BlCbiLYCeEQIMS5cq4o4D8C1AFakfOUA8KAQYnKINik0APBOKlIiDcDHQojIhT9GlHoAPivUBGQA+EAIMTVck0pwF4D3UwO0jQBuDNmeEqRukhcC+FPYtqgRQiwkogkAlgLIA/ADfC6zELmwTIZhGMYfoujSYRiGYXyABZ9hGCYhsOAzDMMkBBZ8hmGYhMCCzzAMkxBY8BkGABHVUlVU3ElE21KPDxPRq2HbxzAy4LBMhtFARI8COCyEeC5sWxhGJjzCZxgTiKi3Uh+fiB4loneIaA4RbSKiy4jomVSd+qmpshYgom5E9G2q0Nm0VNlqhgkdFnyGcUZLAH1RWIjr3wBmCiHOAHAMQE5K9P8BYJgQohuANwE8GZaxDKMmcqUVGCbiTBFCnCKiFSgs/aGUOFgBIAtAWwAdAXyVKoWQjsLStwwTOiz4DOOMEwAghCggolOieBGsAIXXEwFYJYSITJs/hlFglw7DyGUdgDpKX1ciyiSiDiHbxDAAWPAZRiqptpzDAIwmouUAlsHnGucMYxcOy2QYhkkIPMJnGIZJCCz4DMMwCYEFn2EYJiGw4DMMwyQEFnyGYZiEwILPMAyTEFjwGYZhEsL/A/dtCXm6BAJfAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
    " + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "with paddle.no_grad():\n", + " wav = vocoder.infer(mel_input)\n", + "wav = wav.numpy()[0]\n", + "sf.write(f\"syn_audio/{ref_name}\", wav, samplerate=22050)\n", + "librosa.display.waveplot(wav)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ipd.Audio(wav, rate=22050)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/examples/aishell3/vc0/run.sh b/examples/aishell3/vc0/run.sh new file mode 100644 index 00000000..e69de29b diff --git a/examples/csmsc/speedyspeech/baker/README.md b/examples/csmsc/speedyspeech/baker/README.md new file mode 100644 index 00000000..0484d484 --- /dev/null +++ b/examples/csmsc/speedyspeech/baker/README.md @@ -0,0 +1,226 @@ +# Speedyspeech with CSMSC + +This example contains code used to train a [Speedyspeech](http://arxiv.org/abs/2008.03802) model with [Chinese Standard Mandarin Speech Copus](https://www.data-baker.com/open_source.html). NOTE that we only implement the student part of the Speedyspeech model. The ground truth alignment used to train the model is extracted from the dataset using [MFA](https://github.com/MontrealCorpusTools/Montreal-Forced-Aligner). + +## Dataset +### Download and Extract the datasaet +Download CSMSC from it's [Official Website](https://test.data-baker.com/data/index/source). + +### Get MFA result of CSMSC and Extract it +We use [MFA](https://github.com/MontrealCorpusTools/Montreal-Forced-Aligner) to get durations for SPEEDYSPEECH. +You can download from here [baker_alignment_tone.tar.gz](https://paddlespeech.bj.bcebos.com/MFA/BZNSYP/with_tone/baker_alignment_tone.tar.gz), or train your own MFA model reference to [use_mfa example](https://github.com/PaddlePaddle/Parakeet/tree/develop/examples/use_mfa) of our repo. + +## Preprocess the dataset +Assume the path to the dataset is `~/datasets/BZNSYP`. +Assume the path to the MFA result of CSMSC is `./baker_alignment_tone`. +Run the command below to preprocess the dataset. +```bash +./preprocess.sh +``` +When it is done. A `dump` folder is created in the current directory. The structure of the dump folder is listed below. + +```text +dump +├── dev +│ ├── norm +│ └── raw +├── test +│ ├── norm +│ └── raw +└── train + ├── norm + ├── raw + └── feats_stats.npy +``` + +The dataset is split into 3 parts, namely `train`, `dev` and `test`, each of which contains a `norm` and `raw` sub folder. The raw folder contains log magnitude of mel spectrogram of each utterances, while the norm folder contains normalized spectrogram. The statistics used to normalize the spectrogram is computed from the training set, which is located in `dump/train/feats_stats.npy`. + +Also there is a `metadata.jsonl` in each subfolder. It is a table-like file which contains phones, tones, durations, path of spectrogram, and id of each utterance. + +## Train the model +`./run.sh` calls `../train.py`. +```bash +./run.sh +``` +Here's the complete help message. + +```text +usage: train.py [-h] [--config CONFIG] [--train-metadata TRAIN_METADATA] + [--dev-metadata DEV_METADATA] [--output-dir OUTPUT_DIR] + [--device DEVICE] [--nprocs NPROCS] [--verbose VERBOSE] + [--use-relative-path USE_RELATIVE_PATH] + [--phones-dict PHONES_DICT] [--tones-dict TONES_DICT] + +Train a Speedyspeech model with sigle speaker dataset. + +optional arguments: + -h, --help show this help message and exit + --config CONFIG config file. + --train-metadata TRAIN_METADATA + training data. + --dev-metadata DEV_METADATA + dev data. + --output-dir OUTPUT_DIR + output dir. + --device DEVICE device type to use. + --nprocs NPROCS number of processes. + --verbose VERBOSE verbose. + --use-relative-path USE_RELATIVE_PATH + whether use relative path in metadata + --phones-dict PHONES_DICT + phone vocabulary file. + --tones-dict TONES_DICT + tone vocabulary file. +``` + +1. `--config` is a config file in yaml format to overwrite the default config, which can be found at `conf/default.yaml`. +2. `--train-metadata` and `--dev-metadata` should be the metadata file in the normalized subfolder of `train` and `dev` in the `dump` folder. +3. `--output-dir` is the directory to save the results of the experiment. Checkpoints are save in `checkpoints/` inside this directory. +4. `--device` is the type of the device to run the experiment, 'cpu' or 'gpu' are supported. +5. `--nprocs` is the number of processes to run in parallel, note that nprocs > 1 is only supported when `--device` is 'gpu'. +6. `--phones-dict` is the path of the phone vocabulary file. +7. `--tones-dict` is the path of the tone vocabulary file. + +## Pretrained Model +Pretrained SpeedySpeech model with no silence in the edge of audios. [speedyspeech_nosil_baker_ckpt_0.5.zip](https://paddlespeech.bj.bcebos.com/Parakeet/speedyspeech_nosil_baker_ckpt_0.5.zip) + +SpeedySpeech checkpoint contains files listed below. +```text +speedyspeech_nosil_baker_ckpt_0.5 +├── default.yaml # default config used to train speedyspeech +├── feats_stats.npy # statistics used to normalize spectrogram when training speedyspeech +├── phone_id_map.txt # phone vocabulary file when training speedyspeech +├── snapshot_iter_11400.pdz # model parameters and optimizer states +└── tone_id_map.txt # tone vocabulary file when training speedyspeech +``` + +## Synthesize +We use [parallel wavegan](https://github.com/PaddlePaddle/Parakeet/tree/develop/examples/parallelwave_gan/baker) as the neural vocoder. +Download pretrained parallel wavegan model from [pwg_baker_ckpt_0.4.zip](https://paddlespeech.bj.bcebos.com/Parakeet/pwg_baker_ckpt_0.4.zip) and unzip it. +```bash +unzip pwg_baker_ckpt_0.4.zip +``` +Parallel WaveGAN checkpoint contains files listed below. +```text +pwg_baker_ckpt_0.4 +├── pwg_default.yaml # default config used to train parallel wavegan +├── pwg_snapshot_iter_400000.pdz # model parameters of parallel wavegan +└── pwg_stats.npy # statistics used to normalize spectrogram when training parallel wavegan +``` +`synthesize.sh` calls `../synthesize.py`, which can synthesize waveform from `metadata.jsonl`. +```bash +./synthesize.sh +``` +```text +usage: synthesize.py [-h] [--speedyspeech-config SPEEDYSPEECH_CONFIG] + [--speedyspeech-checkpoint SPEEDYSPEECH_CHECKPOINT] + [--speedyspeech-stat SPEEDYSPEECH_STAT] + [--pwg-config PWG_CONFIG] + [--pwg-checkpoint PWG_CHECKPOINT] [--pwg-stat PWG_STAT] + [--phones-dict PHONES_DICT] [--tones-dict TONES_DICT] + [--test-metadata TEST_METADATA] [--output-dir OUTPUT_DIR] + [--inference-dir INFERENCE_DIR] [--device DEVICE] + [--verbose VERBOSE] + +Synthesize with speedyspeech & parallel wavegan. + +optional arguments: + -h, --help show this help message and exit + --speedyspeech-config SPEEDYSPEECH_CONFIG + config file for speedyspeech. + --speedyspeech-checkpoint SPEEDYSPEECH_CHECKPOINT + speedyspeech checkpoint to load. + --speedyspeech-stat SPEEDYSPEECH_STAT + mean and standard deviation used to normalize + spectrogram when training speedyspeech. + --pwg-config PWG_CONFIG + config file for parallelwavegan. + --pwg-checkpoint PWG_CHECKPOINT + parallel wavegan generator parameters to load. + --pwg-stat PWG_STAT mean and standard deviation used to normalize + spectrogram when training speedyspeech. + --phones-dict PHONES_DICT + phone vocabulary file. + --tones-dict TONES_DICT + tone vocabulary file. + --test-metadata TEST_METADATA + test metadata + --output-dir OUTPUT_DIR + output dir + --inference-dir INFERENCE_DIR + dir to save inference models + --device DEVICE device type to use + --verbose VERBOSE verbose +``` +`synthesize_e2e.sh` calls `synthesize_e2e.py`, which can synthesize waveform from text file. +```bash +./synthesize_e2e.sh +``` +```text +usage: synthesize_e2e.py [-h] [--speedyspeech-config SPEEDYSPEECH_CONFIG] + [--speedyspeech-checkpoint SPEEDYSPEECH_CHECKPOINT] + [--speedyspeech-stat SPEEDYSPEECH_STAT] + [--pwg-config PWG_CONFIG] + [--pwg-checkpoint PWG_CHECKPOINT] + [--pwg-stat PWG_STAT] [--text TEXT] + [--phones-dict PHONES_DICT] [--tones-dict TONES_DICT] + [--output-dir OUTPUT_DIR] + [--inference-dir INFERENCE_DIR] [--device DEVICE] + [--verbose VERBOSE] + +Synthesize with speedyspeech & parallel wavegan. + +optional arguments: + -h, --help show this help message and exit + --speedyspeech-config SPEEDYSPEECH_CONFIG + config file for speedyspeech. + --speedyspeech-checkpoint SPEEDYSPEECH_CHECKPOINT + speedyspeech checkpoint to load. + --speedyspeech-stat SPEEDYSPEECH_STAT + mean and standard deviation used to normalize + spectrogram when training speedyspeech. + --pwg-config PWG_CONFIG + config file for parallelwavegan. + --pwg-checkpoint PWG_CHECKPOINT + parallel wavegan checkpoint to load. + --pwg-stat PWG_STAT mean and standard deviation used to normalize + spectrogram when training speedyspeech. + --text TEXT text to synthesize, a 'utt_id sentence' pair per line + --phones-dict PHONES_DICT + phone vocabulary file. + --tones-dict TONES_DICT + tone vocabulary file. + --output-dir OUTPUT_DIR + output dir + --inference-dir INFERENCE_DIR + dir to save inference models + --device DEVICE device type to use + --verbose VERBOSE verbose +``` +1. `--speedyspeech-config`, `--speedyspeech-checkpoint`, `--speedyspeech-stat` are arguments for speedyspeech, which correspond to the 3 files in the speedyspeech pretrained model. +2. `--pwg-config`, `--pwg-checkpoint`, `--pwg-stat` are arguments for parallel wavegan, which correspond to the 3 files in the parallel wavegan pretrained model. +3. `--text` is the text file, which contains sentences to synthesize. +4. `--output-dir` is the directory to save synthesized audio files. +5. `--inference-dir` is the directory to save exported model, which can be used with paddle infernece. +6. `--device` is the type of device to run synthesis, 'cpu' and 'gpu' are supported. 'gpu' is recommended for faster synthesis. +6. `--phones-dict` is the path of the phone vocabulary file. +7. `--tones-dict` is the path of the tone vocabulary file. + +You can use the following scripts to synthesize for `../sentences.txt` using pretrained speedyspeech and parallel wavegan models. +```bash +FLAGS_allocator_strategy=naive_best_fit \ +FLAGS_fraction_of_gpu_memory_to_use=0.01 \ +python3 synthesize_e2e.py \ + --speedyspeech-config=speedyspeech_nosil_baker_ckpt_0.5/default.yaml \ + --speedyspeech-checkpoint=speedyspeech_nosil_baker_ckpt_0.5/snapshot_iter_11400.pdz \ + --speedyspeech-stat=speedyspeech_nosil_baker_ckpt_0.5/feats_stats.npy \ + --pwg-config=pwg_baker_ckpt_0.4/pwg_default.yaml \ + --pwg-checkpoint=pwg_baker_ckpt_0.4/pwg_snapshot_iter_400000.pdz \ + --pwg-stat=pwg_baker_ckpt_0.4/pwg_stats.npy \ + --text=../sentences.txt \ + --output-dir=exp/default/test_e2e \ + --inference-dir=exp/default/inference \ + --device="gpu" \ + --phones-dict=speedyspeech_nosil_baker_ckpt_0.5/phone_id_map.txt \ + --tones-dict=speedyspeech_nosil_baker_ckpt_0.5/tone_id_map.txt +``` diff --git a/examples/csmsc/speedyspeech/baker/conf/default.yaml b/examples/csmsc/speedyspeech/baker/conf/default.yaml new file mode 100644 index 00000000..e93b5082 --- /dev/null +++ b/examples/csmsc/speedyspeech/baker/conf/default.yaml @@ -0,0 +1,50 @@ +########################################################### +# FEATURE EXTRACTION SETTING # +########################################################### +fs: 24000 # Sampling rate. +n_fft: 2048 # FFT size. +n_shift: 300 # Hop size. +win_length: 1200 # Window length. + # If set to null, it will be the same as fft_size. +window: "hann" # Window function. +n_mels: 80 # Number of mel basis. +fmin: 80 # Minimum freq in mel basis calculation. +fmax: 7600 # Maximum frequency in mel basis calculation. + +########################################################### +# DATA SETTING # +########################################################### +batch_size: 64 +num_workers: 4 + +########################################################### +# MODEL SETTING # +########################################################### +model: + encoder_hidden_size: 128 + encoder_kernel_size: 3 + encoder_dilations: [1, 3, 9, 27, 1, 3, 9, 27, 1, 1] + duration_predictor_hidden_size: 128 + decoder_hidden_size: 128 + decoder_output_size: 80 + decoder_kernel_size: 3 + decoder_dilations: [1, 3, 9, 27, 1, 3, 9, 27, 1, 3, 9, 27, 1, 3, 9, 27, 1, 1] + +########################################################### +# OPTIMIZER SETTING # +########################################################### +optimizer: + optim: adam # optimizer type + learning_rate: 0.002 # learning rate + max_grad_norm: 1 + +########################################################### +# TRAINING SETTING # +########################################################### +max_epoch: 200 +num_snapshots: 5 + +########################################################### +# OTHER SETTING # +########################################################### +seed: 10086 \ No newline at end of file diff --git a/examples/csmsc/speedyspeech/baker/inference.py b/examples/csmsc/speedyspeech/baker/inference.py new file mode 100644 index 00000000..a1d18540 --- /dev/null +++ b/examples/csmsc/speedyspeech/baker/inference.py @@ -0,0 +1,146 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +import os +from pathlib import Path + +import soundfile as sf +from paddle import inference +from parakeet.frontend.zh_frontend import Frontend + + +def main(): + parser = argparse.ArgumentParser( + description="Paddle Infernce with speedyspeech & parallel wavegan.") + parser.add_argument( + "--inference-dir", type=str, help="dir to save inference models") + parser.add_argument( + "--text", + type=str, + help="text to synthesize, a 'utt_id sentence' pair per line") + parser.add_argument("--output-dir", type=str, help="output dir") + parser.add_argument( + "--enable-auto-log", action="store_true", help="use auto log") + parser.add_argument( + "--phones-dict", + type=str, + default="phones.txt", + help="phone vocabulary file.") + parser.add_argument( + "--tones-dict", + type=str, + default="tones.txt", + help="tone vocabulary file.") + + args, _ = parser.parse_known_args() + + frontend = Frontend( + phone_vocab_path=args.phones_dict, tone_vocab_path=args.tones_dict) + print("frontend done!") + + speedyspeech_config = inference.Config( + str(Path(args.inference_dir) / "speedyspeech.pdmodel"), + str(Path(args.inference_dir) / "speedyspeech.pdiparams")) + speedyspeech_config.enable_use_gpu(100, 0) + speedyspeech_config.enable_memory_optim() + speedyspeech_predictor = inference.create_predictor(speedyspeech_config) + + pwg_config = inference.Config( + str(Path(args.inference_dir) / "pwg.pdmodel"), + str(Path(args.inference_dir) / "pwg.pdiparams")) + pwg_config.enable_use_gpu(100, 0) + pwg_config.enable_memory_optim() + pwg_predictor = inference.create_predictor(pwg_config) + + if args.enable_auto_log: + import auto_log + os.makedirs("output", exist_ok=True) + pid = os.getpid() + logger = auto_log.AutoLogger( + model_name="speedyspeech", + model_precision='float32', + batch_size=1, + data_shape="dynamic", + save_path="./output/auto_log.log", + inference_config=speedyspeech_config, + pids=pid, + process_name=None, + gpu_ids=0, + time_keys=['preprocess_time', 'inference_time', 'postprocess_time'], + warmup=0) + + output_dir = Path(args.output_dir) + output_dir.mkdir(parents=True, exist_ok=True) + sentences = [] + + with open(args.text, 'rt') as f: + for line in f: + utt_id, sentence = line.strip().split() + sentences.append((utt_id, sentence)) + + for utt_id, sentence in sentences: + if args.enable_auto_log: + logger.times.start() + + input_ids = frontend.get_input_ids( + sentence, merge_sentences=True, get_tone_ids=True) + phone_ids = input_ids["phone_ids"] + tone_ids = input_ids["tone_ids"] + phones = phone_ids[0] + tones = tone_ids[0] + + if args.enable_auto_log: + logger.times.stamp() + + input_names = speedyspeech_predictor.get_input_names() + phones_handle = speedyspeech_predictor.get_input_handle(input_names[0]) + tones_handle = speedyspeech_predictor.get_input_handle(input_names[1]) + + phones_handle.reshape(phones.shape) + phones_handle.copy_from_cpu(phones) + tones_handle.reshape(tones.shape) + tones_handle.copy_from_cpu(tones) + + speedyspeech_predictor.run() + output_names = speedyspeech_predictor.get_output_names() + output_handle = speedyspeech_predictor.get_output_handle( + output_names[0]) + output_data = output_handle.copy_to_cpu() + + input_names = pwg_predictor.get_input_names() + mel_handle = pwg_predictor.get_input_handle(input_names[0]) + mel_handle.reshape(output_data.shape) + mel_handle.copy_from_cpu(output_data) + + pwg_predictor.run() + output_names = pwg_predictor.get_output_names() + output_handle = pwg_predictor.get_output_handle(output_names[0]) + wav = output_data = output_handle.copy_to_cpu() + + if args.enable_auto_log: + logger.times.stamp() + + sf.write(output_dir / (utt_id + ".wav"), wav, samplerate=24000) + + if args.enable_auto_log: + logger.times.end(stamp=True) + print(f"{utt_id} done!") + + if args.enable_auto_log: + logger.report() + + +if __name__ == "__main__": + main() diff --git a/examples/csmsc/speedyspeech/baker/inference.sh b/examples/csmsc/speedyspeech/baker/inference.sh new file mode 100755 index 00000000..880a1fd5 --- /dev/null +++ b/examples/csmsc/speedyspeech/baker/inference.sh @@ -0,0 +1,8 @@ +#!/bin/bash + +python3 inference.py \ + --inference-dir=exp/default/inference \ + --text=../sentences.txt \ + --output-dir=exp/default/pd_infer_out \ + --phones-dict=dump/phone_id_map.txt \ + --tones-dict=dump/tone_id_map.txt diff --git a/examples/csmsc/speedyspeech/baker/preprocess.sh b/examples/csmsc/speedyspeech/baker/preprocess.sh new file mode 100755 index 00000000..422caa31 --- /dev/null +++ b/examples/csmsc/speedyspeech/baker/preprocess.sh @@ -0,0 +1,65 @@ +#!/bin/bash + +stage=0 +stop_stage=100 + +export MAIN_ROOT=`realpath ${PWD}/../../../` + +if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then + # get durations from MFA's result + echo "Generate durations.txt from MFA results ..." + python3 ${MAIN_ROOT}/utils/gen_duration_from_textgrid.py \ + --inputdir=./baker_alignment_tone \ + --output=durations.txt \ + --config=conf/default.yaml +fi + +if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then + echo "Extract features ..." + python3 ../preprocess.py \ + --dataset=baker \ + --rootdir=~/datasets/BZNSYP/ \ + --dumpdir=dump \ + --dur-file=durations.txt \ + --config=conf/default.yaml \ + --num-cpu=20 \ + --cut-sil=True \ + --use-relative-path=True +fi + +if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then + echo "Get features' stats ..." + python3 ${MAIN_ROOT}/utils/compute_statistics.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --field-name="feats" \ + --use-relative-path=True +fi + +if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then + # normalize and covert phone/tone to id, dev and test should use train's stats + echo "Normalize ..." + python3 ../normalize.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --dumpdir=dump/train/norm \ + --stats=dump/train/feats_stats.npy \ + --phones-dict=dump/phone_id_map.txt \ + --tones-dict=dump/tone_id_map.txt \ + --use-relative-path=True + + python3 ../normalize.py \ + --metadata=dump/dev/raw/metadata.jsonl \ + --dumpdir=dump/dev/norm \ + --stats=dump/train/feats_stats.npy \ + --phones-dict=dump/phone_id_map.txt \ + --tones-dict=dump/tone_id_map.txt \ + --use-relative-path=True + + python3 ../normalize.py \ + --metadata=dump/test/raw/metadata.jsonl \ + --dumpdir=dump/test/norm \ + --stats=dump/train/feats_stats.npy \ + --phones-dict=dump/phone_id_map.txt \ + --tones-dict=dump/tone_id_map.txt \ + --use-relative-path=True + +fi diff --git a/examples/csmsc/speedyspeech/baker/run.sh b/examples/csmsc/speedyspeech/baker/run.sh new file mode 100755 index 00000000..64936ef3 --- /dev/null +++ b/examples/csmsc/speedyspeech/baker/run.sh @@ -0,0 +1,12 @@ + +#!/bin/bash + +python ../train.py \ + --train-metadata=dump/train/norm/metadata.jsonl \ + --dev-metadata=dump/dev/norm/metadata.jsonl \ + --config=conf/default.yaml \ + --output-dir=exp/default \ + --nprocs=2 \ + --phones-dict=dump/phone_id_map.txt \ + --tones-dict=dump/tone_id_map.txt \ + --use-relative-path=True diff --git a/examples/csmsc/speedyspeech/baker/synthesize.sh b/examples/csmsc/speedyspeech/baker/synthesize.sh new file mode 100755 index 00000000..7c37c5bd --- /dev/null +++ b/examples/csmsc/speedyspeech/baker/synthesize.sh @@ -0,0 +1,16 @@ +#!/bin/bash +FLAGS_allocator_strategy=naive_best_fit \ +FLAGS_fraction_of_gpu_memory_to_use=0.01 \ +python3 ../synthesize.py \ + --speedyspeech-config=conf/default.yaml \ + --speedyspeech-checkpoint=exp/default/checkpoints/snapshot_iter_11400.pdz \ + --speedyspeech-stat=dump/train/feats_stats.npy \ + --pwg-config=pwg_baker_ckpt_0.4/pwg_default.yaml \ + --pwg-checkpoint=pwg_baker_ckpt_0.4/pwg_snapshot_iter_400000.pdz \ + --pwg-stat=pwg_baker_ckpt_0.4/pwg_stats.npy \ + --test-metadata=dump/test/norm/metadata.jsonl \ + --output-dir=exp/default/test \ + --inference-dir=exp/default/inference \ + --phones-dict=dump/phone_id_map.txt \ + --tones-dict=dump/tone_id_map.txt \ + --device="gpu" diff --git a/examples/csmsc/speedyspeech/baker/synthesize_e2e.py b/examples/csmsc/speedyspeech/baker/synthesize_e2e.py new file mode 100644 index 00000000..6dd3abd1 --- /dev/null +++ b/examples/csmsc/speedyspeech/baker/synthesize_e2e.py @@ -0,0 +1,196 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +import logging +import os +from pathlib import Path + +import numpy as np +import soundfile as sf +import paddle +import yaml +from paddle import jit +from paddle.static import InputSpec +from parakeet.frontend.zh_frontend import Frontend +from parakeet.models.speedyspeech import SpeedySpeech +from parakeet.models.speedyspeech import SpeedySpeechInference +from parakeet.models.parallel_wavegan import PWGGenerator +from parakeet.models.parallel_wavegan import PWGInference +from parakeet.modules.normalizer import ZScore +from yacs.config import CfgNode + + +def evaluate(args, speedyspeech_config, pwg_config): + # dataloader has been too verbose + logging.getLogger("DataLoader").disabled = True + + # construct dataset for evaluation + sentences = [] + with open(args.text, 'rt') as f: + for line in f: + utt_id, sentence = line.strip().split() + sentences.append((utt_id, sentence)) + + with open(args.phones_dict, "r") as f: + phn_id = [line.strip().split() for line in f.readlines()] + vocab_size = len(phn_id) + print("vocab_size:", vocab_size) + with open(args.tones_dict, "r") as f: + tone_id = [line.strip().split() for line in f.readlines()] + tone_size = len(tone_id) + print("tone_size:", tone_size) + + model = SpeedySpeech( + vocab_size=vocab_size, + tone_size=tone_size, + **speedyspeech_config["model"]) + model.set_state_dict( + paddle.load(args.speedyspeech_checkpoint)["main_params"]) + model.eval() + + vocoder = PWGGenerator(**pwg_config["generator_params"]) + vocoder.set_state_dict(paddle.load(args.pwg_checkpoint)["generator_params"]) + vocoder.remove_weight_norm() + vocoder.eval() + print("model done!") + + stat = np.load(args.speedyspeech_stat) + mu, std = stat + mu = paddle.to_tensor(mu) + std = paddle.to_tensor(std) + speedyspeech_normalizer = ZScore(mu, std) + + stat = np.load(args.pwg_stat) + mu, std = stat + mu = paddle.to_tensor(mu) + std = paddle.to_tensor(std) + pwg_normalizer = ZScore(mu, std) + + speedyspeech_inference = SpeedySpeechInference(speedyspeech_normalizer, + model) + speedyspeech_inference.eval() + speedyspeech_inference = jit.to_static( + speedyspeech_inference, + input_spec=[ + InputSpec([-1], dtype=paddle.int64), InputSpec( + [-1], dtype=paddle.int64) + ]) + paddle.jit.save(speedyspeech_inference, + os.path.join(args.inference_dir, "speedyspeech")) + speedyspeech_inference = paddle.jit.load( + os.path.join(args.inference_dir, "speedyspeech")) + + pwg_inference = PWGInference(pwg_normalizer, vocoder) + pwg_inference.eval() + pwg_inference = jit.to_static( + pwg_inference, input_spec=[ + InputSpec([-1, 80], dtype=paddle.float32), + ]) + paddle.jit.save(pwg_inference, os.path.join(args.inference_dir, "pwg")) + pwg_inference = paddle.jit.load(os.path.join(args.inference_dir, "pwg")) + + frontend = Frontend( + phone_vocab_path=args.phones_dict, tone_vocab_path=args.tones_dict) + print("frontend done!") + + output_dir = Path(args.output_dir) + output_dir.mkdir(parents=True, exist_ok=True) + + for utt_id, sentence in sentences: + input_ids = frontend.get_input_ids( + sentence, merge_sentences=True, get_tone_ids=True) + phone_ids = input_ids["phone_ids"] + tone_ids = input_ids["tone_ids"] + + flags = 0 + for i in range(len(phone_ids)): + part_phone_ids = phone_ids[i] + part_tone_ids = tone_ids[i] + with paddle.no_grad(): + mel = speedyspeech_inference(part_phone_ids, part_tone_ids) + temp_wav = pwg_inference(mel) + if flags == 0: + wav = temp_wav + flags = 1 + else: + wav = paddle.concat([wav, temp_wav]) + sf.write( + output_dir / (utt_id + ".wav"), + wav.numpy(), + samplerate=speedyspeech_config.fs) + print(f"{utt_id} done!") + + +def main(): + # parse args and config and redirect to train_sp + parser = argparse.ArgumentParser( + description="Synthesize with speedyspeech & parallel wavegan.") + parser.add_argument( + "--speedyspeech-config", type=str, help="config file for speedyspeech.") + parser.add_argument( + "--speedyspeech-checkpoint", + type=str, + help="speedyspeech checkpoint to load.") + parser.add_argument( + "--speedyspeech-stat", + type=str, + help="mean and standard deviation used to normalize spectrogram when training speedyspeech." + ) + parser.add_argument( + "--pwg-config", type=str, help="config file for parallelwavegan.") + parser.add_argument( + "--pwg-checkpoint", + type=str, + help="parallel wavegan checkpoint to load.") + parser.add_argument( + "--pwg-stat", + type=str, + help="mean and standard deviation used to normalize spectrogram when training speedyspeech." + ) + parser.add_argument( + "--text", + type=str, + help="text to synthesize, a 'utt_id sentence' pair per line") + parser.add_argument( + "--phones-dict", type=str, default=None, help="phone vocabulary file.") + parser.add_argument( + "--tones-dict", type=str, default=None, help="tone vocabulary file.") + parser.add_argument("--output-dir", type=str, help="output dir") + parser.add_argument( + "--inference-dir", type=str, help="dir to save inference models") + parser.add_argument( + "--device", type=str, default="gpu", help="device type to use") + parser.add_argument("--verbose", type=int, default=1, help="verbose") + + args, _ = parser.parse_known_args() + + paddle.set_device(args.device) + + with open(args.speedyspeech_config) as f: + speedyspeech_config = CfgNode(yaml.safe_load(f)) + with open(args.pwg_config) as f: + pwg_config = CfgNode(yaml.safe_load(f)) + + print("========Args========") + print(yaml.safe_dump(vars(args))) + print("========Config========") + print(speedyspeech_config) + print(pwg_config) + + evaluate(args, speedyspeech_config, pwg_config) + + +if __name__ == "__main__": + main() diff --git a/examples/csmsc/speedyspeech/baker/synthesize_e2e.sh b/examples/csmsc/speedyspeech/baker/synthesize_e2e.sh new file mode 100755 index 00000000..4800a0f7 --- /dev/null +++ b/examples/csmsc/speedyspeech/baker/synthesize_e2e.sh @@ -0,0 +1,16 @@ +#!/bin/bash +FLAGS_allocator_strategy=naive_best_fit \ +FLAGS_fraction_of_gpu_memory_to_use=0.01 \ +python synthesize_e2e.py \ + --speedyspeech-config=conf/default.yaml \ + --speedyspeech-checkpoint=exp/default/checkpoints/snapshot_iter_11400.pdz \ + --speedyspeech-stat=dump/train/feats_stats.npy \ + --pwg-config=pwg_baker_ckpt_0.4/pwg_default.yaml \ + --pwg-checkpoint=pwg_baker_ckpt_0.4/pwg_snapshot_iter_400000.pdz \ + --pwg-stat=pwg_baker_ckpt_0.4/pwg_stats.npy \ + --text=../sentences.txt \ + --output-dir=exp/default/test_e2e \ + --inference-dir=exp/default/inference \ + --device="gpu" \ + --phones-dict=dump/phone_id_map.txt \ + --tones-dict=dump/tone_id_map.txt diff --git a/examples/csmsc/speedyspeech/normalize.py b/examples/csmsc/speedyspeech/normalize.py new file mode 100644 index 00000000..eeb58bb7 --- /dev/null +++ b/examples/csmsc/speedyspeech/normalize.py @@ -0,0 +1,159 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Normalize feature files and dump them.""" + +import argparse +import logging +from operator import itemgetter +from pathlib import Path + +import jsonlines +import numpy as np +from parakeet.datasets.data_table import DataTable +from sklearn.preprocessing import StandardScaler +from tqdm import tqdm + + +def main(): + """Run preprocessing process.""" + parser = argparse.ArgumentParser( + description="Normalize dumped raw features (See detail in parallel_wavegan/bin/normalize.py)." + ) + parser.add_argument( + "--metadata", + type=str, + required=True, + help="directory including feature files to be normalized. " + "you need to specify either *-scp or rootdir.") + parser.add_argument( + "--dumpdir", + type=str, + required=True, + help="directory to dump normalized feature files.") + parser.add_argument( + "--stats", type=str, required=True, help="statistics file.") + parser.add_argument( + "--phones-dict", type=str, default=None, help="phone vocabulary file.") + parser.add_argument( + "--tones-dict", type=str, default=None, help="tone vocabulary file.") + + parser.add_argument( + "--verbose", + type=int, + default=1, + help="logging level. higher is more logging. (default=1)") + + def str2bool(str): + return True if str.lower() == 'true' else False + + parser.add_argument( + "--use-relative-path", + type=str2bool, + default=False, + help="whether use relative path in metadata") + args = parser.parse_args() + + # set logger + if args.verbose > 1: + logging.basicConfig( + level=logging.DEBUG, + format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s" + ) + elif args.verbose > 0: + logging.basicConfig( + level=logging.INFO, + format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s" + ) + else: + logging.basicConfig( + level=logging.WARN, + format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s" + ) + logging.warning('Skip DEBUG/INFO messages') + + dumpdir = Path(args.dumpdir).expanduser() + # use absolute path + dumpdir = dumpdir.resolve() + dumpdir.mkdir(parents=True, exist_ok=True) + + # get dataset + with jsonlines.open(args.metadata, 'r') as reader: + metadata = list(reader) + if args.use_relative_path: + # if use_relative_path in preprocess, covert it to absolute path here + metadata_dir = Path(args.metadata).parent + for item in metadata: + item["feats"] = str(metadata_dir / item["feats"]) + + dataset = DataTable( + metadata, converters={ + 'feats': np.load, + }) + logging.info(f"The number of files = {len(dataset)}.") + + # restore scaler + scaler = StandardScaler() + scaler.mean_ = np.load(args.stats)[0] + scaler.scale_ = np.load(args.stats)[1] + # from version 0.23.0, this information is needed + scaler.n_features_in_ = scaler.mean_.shape[0] + + vocab_phones = {} + with open(args.phones_dict, 'rt') as f: + phn_id = [line.strip().split() for line in f.readlines()] + for phn, id in phn_id: + vocab_phones[phn] = int(id) + + vocab_tones = {} + with open(args.tones_dict, 'rt') as f: + tone_id = [line.strip().split() for line in f.readlines()] + for tone, id in tone_id: + vocab_tones[tone] = int(id) + + # process each file + output_metadata = [] + + for item in tqdm(dataset): + utt_id = item['utt_id'] + mel = item['feats'] + # normalize + mel = scaler.transform(mel) + + # save + mel_path = dumpdir / f"{utt_id}_feats.npy" + np.save(mel_path, mel.astype(np.float32), allow_pickle=False) + phone_ids = [vocab_phones[p] for p in item['phones']] + tone_ids = [vocab_tones[p] for p in item['tones']] + if args.use_relative_path: + # convert absolute path to relative path: + mel_path = mel_path.relative_to(dumpdir) + output_metadata.append({ + 'utt_id': utt_id, + 'phones': phone_ids, + 'tones': tone_ids, + 'num_phones': item['num_phones'], + 'num_frames': item['num_frames'], + 'durations': item['durations'], + 'feats': str(mel_path), + }) + output_metadata.sort(key=itemgetter('utt_id')) + output_metadata_path = Path(args.dumpdir) / "metadata.jsonl" + with jsonlines.open(output_metadata_path, 'w') as writer: + for item in output_metadata: + writer.write(item) + logging.info(f"metadata dumped into {output_metadata_path}") + + +if __name__ == "__main__": + main() diff --git a/examples/csmsc/speedyspeech/preprocess.py b/examples/csmsc/speedyspeech/preprocess.py new file mode 100644 index 00000000..647c9b36 --- /dev/null +++ b/examples/csmsc/speedyspeech/preprocess.py @@ -0,0 +1,293 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from operator import itemgetter +from typing import Any +from typing import Dict +from typing import List + +import argparse +import jsonlines +import librosa +import numpy as np +import re +import tqdm +import yaml +from concurrent.futures import ThreadPoolExecutor +from parakeet.data.get_feats import LogMelFBank +from parakeet.datasets.preprocess_utils import compare_duration_and_mel_length +from parakeet.datasets.preprocess_utils import get_phones_tones +from parakeet.datasets.preprocess_utils import get_phn_dur +from parakeet.datasets.preprocess_utils import merge_silence +from pathlib import Path +from yacs.config import CfgNode + + +def process_sentence(config: Dict[str, Any], + fp: Path, + sentences: Dict, + output_dir: Path, + mel_extractor=None, + cut_sil: bool=True): + utt_id = fp.stem + record = None + if utt_id in sentences: + # reading, resampling may occur + wav, _ = librosa.load(str(fp), sr=config.fs) + if len(wav.shape) != 1 or np.abs(wav).max() > 1.0: + return record + assert len(wav.shape) == 1, f"{utt_id} is not a mono-channel audio." + assert np.abs(wav).max( + ) <= 1.0, f"{utt_id} is seems to be different that 16 bit PCM." + phones = sentences[utt_id][0] + durations = sentences[utt_id][1] + speaker = sentences[utt_id][2] + d_cumsum = np.pad(np.array(durations).cumsum(0), (1, 0), 'constant') + # little imprecise than use *.TextGrid directly + times = librosa.frames_to_time( + d_cumsum, sr=config.fs, hop_length=config.n_shift) + if cut_sil: + start = 0 + end = d_cumsum[-1] + if phones[0] == "sil" and len(durations) > 1: + start = times[1] + durations = durations[1:] + phones = phones[1:] + if phones[-1] == 'sil' and len(durations) > 1: + end = times[-2] + durations = durations[:-1] + phones = phones[:-1] + sentences[utt_id][0] = phones + sentences[utt_id][1] = durations + start, end = librosa.time_to_samples([start, end], sr=config.fs) + wav = wav[start:end] + + # extract mel feats + logmel = mel_extractor.get_log_mel_fbank(wav) + # change duration according to mel_length + compare_duration_and_mel_length(sentences, utt_id, logmel) + labels = sentences[utt_id][0] + # extract phone and duration + phones = [] + tones = [] + for label in labels: + # split tone from finals + match = re.match(r'^(\w+)([012345])$', label) + if match: + phones.append(match.group(1)) + tones.append(match.group(2)) + else: + phones.append(label) + tones.append('0') + durations = sentences[utt_id][1] + num_frames = logmel.shape[0] + assert sum(durations) == num_frames + assert len(phones) == len(tones) == len(durations) + + mel_path = output_dir / (utt_id + "_feats.npy") + np.save(mel_path, logmel) # (num_frames, n_mels) + record = { + "utt_id": utt_id, + "phones": phones, + "tones": tones, + "num_phones": len(phones), + "num_frames": num_frames, + "durations": durations, + "feats": str(mel_path), # Path object + } + return record + + +def process_sentences(config, + fps: List[Path], + sentences: Dict, + output_dir: Path, + mel_extractor=None, + nprocs: int=1, + cut_sil: bool=True, + use_relative_path: bool=False): + if nprocs == 1: + results = [] + for fp in tqdm.tqdm(fps, total=len(fps)): + record = process_sentence(config, fp, sentences, output_dir, + mel_extractor, cut_sil) + if record: + results.append(record) + else: + with ThreadPoolExecutor(nprocs) as pool: + futures = [] + with tqdm.tqdm(total=len(fps)) as progress: + for fp in fps: + future = pool.submit(process_sentence, config, fp, + sentences, output_dir, mel_extractor, + cut_sil) + future.add_done_callback(lambda p: progress.update()) + futures.append(future) + + results = [] + for ft in futures: + record = ft.result() + if record: + results.append(record) + + results.sort(key=itemgetter("utt_id")) + output_dir = Path(output_dir) + metadata_path = output_dir / "metadata.jsonl" + # NOTE: use relative path to the meta jsonlines file for Full Chain Project + with jsonlines.open(metadata_path, 'w') as writer: + for item in results: + if use_relative_path: + item["feats"] = str(Path(item["feats"]).relative_to(output_dir)) + writer.write(item) + print("Done") + + +def main(): + # parse config and args + parser = argparse.ArgumentParser( + description="Preprocess audio and then extract features.") + + parser.add_argument( + "--dataset", + default="baker", + type=str, + help="name of dataset, should in {baker} now") + + parser.add_argument( + "--rootdir", default=None, type=str, help="directory to dataset.") + parser.add_argument( + "--dumpdir", + type=str, + required=True, + help="directory to dump feature files.") + + parser.add_argument( + "--dur-file", + default=None, + type=str, + help="path to baker durations.txt.") + + parser.add_argument("--config", type=str, help="fastspeech2 config file.") + + parser.add_argument( + "--verbose", + type=int, + default=1, + help="logging level. higher is more logging. (default=1)") + parser.add_argument( + "--num-cpu", type=int, default=1, help="number of process.") + + def str2bool(str): + return True if str.lower() == 'true' else False + + parser.add_argument( + "--cut-sil", + type=str2bool, + default=True, + help="whether cut sil in the edge of audio") + + parser.add_argument( + "--use-relative-path", + type=str2bool, + default=False, + help="whether use relative path in metadata") + + args = parser.parse_args() + + rootdir = Path(args.rootdir).expanduser() + dumpdir = Path(args.dumpdir).expanduser() + # use absolute path + dumpdir = dumpdir.resolve() + dumpdir.mkdir(parents=True, exist_ok=True) + dur_file = Path(args.dur_file).expanduser() + + assert rootdir.is_dir() + assert dur_file.is_file() + + with open(args.config, 'rt') as f: + config = CfgNode(yaml.safe_load(f)) + + if args.verbose > 1: + print(vars(args)) + print(config) + + sentences, speaker_set = get_phn_dur(dur_file) + + merge_silence(sentences) + phone_id_map_path = dumpdir / "phone_id_map.txt" + tone_id_map_path = dumpdir / "tone_id_map.txt" + get_phones_tones(sentences, phone_id_map_path, tone_id_map_path, + args.dataset) + + if args.dataset == "baker": + wav_files = sorted(list((rootdir / "Wave").rglob("*.wav"))) + # split data into 3 sections + num_train = 9800 + num_dev = 100 + train_wav_files = wav_files[:num_train] + dev_wav_files = wav_files[num_train:num_train + num_dev] + test_wav_files = wav_files[num_train + num_dev:] + + train_dump_dir = dumpdir / "train" / "raw" + train_dump_dir.mkdir(parents=True, exist_ok=True) + dev_dump_dir = dumpdir / "dev" / "raw" + dev_dump_dir.mkdir(parents=True, exist_ok=True) + test_dump_dir = dumpdir / "test" / "raw" + test_dump_dir.mkdir(parents=True, exist_ok=True) + + # Extractor + mel_extractor = LogMelFBank( + sr=config.fs, + n_fft=config.n_fft, + hop_length=config.n_shift, + win_length=config.win_length, + window=config.window, + n_mels=config.n_mels, + fmin=config.fmin, + fmax=config.fmax) + + # process for the 3 sections + if train_wav_files: + process_sentences( + config, + train_wav_files, + sentences, + train_dump_dir, + mel_extractor, + nprocs=args.num_cpu, + cut_sil=args.cut_sil, + use_relative_path=args.use_relative_path) + if dev_wav_files: + process_sentences( + config, + dev_wav_files, + sentences, + dev_dump_dir, + mel_extractor, + cut_sil=args.cut_sil, + use_relative_path=args.use_relative_path) + if test_wav_files: + process_sentences( + config, + test_wav_files, + sentences, + test_dump_dir, + mel_extractor, + nprocs=args.num_cpu, + cut_sil=args.cut_sil, + use_relative_path=args.use_relative_path) + + +if __name__ == "__main__": + main() diff --git a/examples/csmsc/speedyspeech/sentences.txt b/examples/csmsc/speedyspeech/sentences.txt new file mode 100644 index 00000000..3aa5376b --- /dev/null +++ b/examples/csmsc/speedyspeech/sentences.txt @@ -0,0 +1,16 @@ +001 凯莫瑞安联合体的经济崩溃，迫在眉睫。 +002 对于所有想要离开那片废土，去寻找更美好生活的人来说。 +003 克哈，是你们所有人安全的港湾。 +004 为了保护尤摩扬人民不受异虫的残害，我所做的，比他们自己的领导委员会都多。 +005 无论他们如何诽谤我，我将继续为所有泰伦人的最大利益，而努力奋斗。 +006 身为你们的元首，我带领泰伦人实现了人类统治领地和经济的扩张。 +007 我们将继续成长，用行动回击那些只会说风凉话，不愿意和我们相向而行的害群之马。 +008 帝国武装力量，无数的优秀儿女，正时刻守卫着我们的家园大门，但是他们孤木难支。 +009 凡是今天应征入伍者，所获的所有刑罚罪责，减半。 +010 激进分子和异见者希望你们一听见枪声，就背弃多年的和平与繁荣。 +011 他们没有勇气和能力，带领人类穿越一个充满危险的星系。 +012 法治是我们的命脉，然而它却受到前所未有的挑战。 +013 我将恢复我们帝国的荣光，绝不会向任何外星势力低头。 +014 我已经驯服了异虫，荡平了星灵。如今它们的创造者，想要夺走我们拥有的一切。 +015 永远记住，谁才是最能保护你们的人。 +016 不要听信别人的谗言，我不是什么克隆人。 \ No newline at end of file diff --git a/examples/csmsc/speedyspeech/synthesize.py b/examples/csmsc/speedyspeech/synthesize.py new file mode 100644 index 00000000..4225071e --- /dev/null +++ b/examples/csmsc/speedyspeech/synthesize.py @@ -0,0 +1,180 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import os +import logging +import argparse +from pathlib import Path + +import jsonlines +import numpy as np +import soundfile as sf +import paddle +import yaml +from paddle import jit +from paddle.static import InputSpec +from yacs.config import CfgNode + +from parakeet.datasets.data_table import DataTable +from parakeet.models.speedyspeech import SpeedySpeech +from parakeet.models.speedyspeech import SpeedySpeechInference +from parakeet.models.parallel_wavegan import PWGGenerator +from parakeet.models.parallel_wavegan import PWGInference +from parakeet.modules.normalizer import ZScore + + +def evaluate(args, speedyspeech_config, pwg_config): + # dataloader has been too verbose + logging.getLogger("DataLoader").disabled = True + + # construct dataset for evaluation + with jsonlines.open(args.test_metadata, 'r') as reader: + test_metadata = list(reader) + test_dataset = DataTable( + data=test_metadata, fields=["utt_id", "phones", "tones"]) + + with open(args.phones_dict, "r") as f: + phn_id = [line.strip().split() for line in f.readlines()] + vocab_size = len(phn_id) + print("vocab_size:", vocab_size) + with open(args.tones_dict, "r") as f: + tone_id = [line.strip().split() for line in f.readlines()] + tone_size = len(tone_id) + print("tone_size:", tone_size) + + model = SpeedySpeech( + vocab_size=vocab_size, + tone_size=tone_size, + **speedyspeech_config["model"]) + model.set_state_dict( + paddle.load(args.speedyspeech_checkpoint)["main_params"]) + model.eval() + + vocoder = PWGGenerator(**pwg_config["generator_params"]) + vocoder.set_state_dict(paddle.load(args.pwg_checkpoint)["generator_params"]) + vocoder.remove_weight_norm() + vocoder.eval() + print("model done!") + + stat = np.load(args.speedyspeech_stat) + mu, std = stat + mu = paddle.to_tensor(mu) + std = paddle.to_tensor(std) + speedyspeech_normalizer = ZScore(mu, std) + speedyspeech_normalizer.eval() + + stat = np.load(args.pwg_stat) + mu, std = stat + mu = paddle.to_tensor(mu) + std = paddle.to_tensor(std) + pwg_normalizer = ZScore(mu, std) + pwg_normalizer.eval() + + speedyspeech_inference = SpeedySpeechInference(speedyspeech_normalizer, + model) + speedyspeech_inference.eval() + speedyspeech_inference = jit.to_static( + speedyspeech_inference, + input_spec=[ + InputSpec([-1], dtype=paddle.int64), InputSpec( + [-1], dtype=paddle.int64) + ]) + paddle.jit.save(speedyspeech_inference, + os.path.join(args.inference_dir, "speedyspeech")) + speedyspeech_inference = paddle.jit.load( + os.path.join(args.inference_dir, "speedyspeech")) + + pwg_inference = PWGInference(pwg_normalizer, vocoder) + pwg_inference.eval() + pwg_inference = jit.to_static( + pwg_inference, input_spec=[ + InputSpec([-1, 80], dtype=paddle.float32), + ]) + paddle.jit.save(pwg_inference, os.path.join(args.inference_dir, "pwg")) + pwg_inference = paddle.jit.load(os.path.join(args.inference_dir, "pwg")) + + output_dir = Path(args.output_dir) + output_dir.mkdir(parents=True, exist_ok=True) + + for datum in test_dataset: + utt_id = datum["utt_id"] + phones = paddle.to_tensor(datum["phones"]) + tones = paddle.to_tensor(datum["tones"]) + + with paddle.no_grad(): + wav = pwg_inference(speedyspeech_inference(phones, tones)) + sf.write( + output_dir / (utt_id + ".wav"), + wav.numpy(), + samplerate=speedyspeech_config.fs) + print(f"{utt_id} done!") + + +def main(): + # parse args and config and redirect to train_sp + parser = argparse.ArgumentParser( + description="Synthesize with speedyspeech & parallel wavegan.") + parser.add_argument( + "--speedyspeech-config", type=str, help="config file for speedyspeech.") + parser.add_argument( + "--speedyspeech-checkpoint", + type=str, + help="speedyspeech checkpoint to load.") + parser.add_argument( + "--speedyspeech-stat", + type=str, + help="mean and standard deviation used to normalize spectrogram when training speedyspeech." + ) + parser.add_argument( + "--pwg-config", type=str, help="config file for parallelwavegan.") + parser.add_argument( + "--pwg-checkpoint", + type=str, + help="parallel wavegan generator parameters to load.") + parser.add_argument( + "--pwg-stat", + type=str, + help="mean and standard deviation used to normalize spectrogram when training speedyspeech." + ) + parser.add_argument( + "--phones-dict", type=str, default=None, help="phone vocabulary file.") + parser.add_argument( + "--tones-dict", type=str, default=None, help="tone vocabulary file.") + parser.add_argument("--test-metadata", type=str, help="test metadata") + parser.add_argument("--output-dir", type=str, help="output dir") + parser.add_argument( + "--inference-dir", type=str, help="dir to save inference models") + parser.add_argument( + "--device", type=str, default="gpu", help="device type to use") + parser.add_argument("--verbose", type=int, default=1, help="verbose") + + args, _ = parser.parse_known_args() + + paddle.set_device(args.device) + + with open(args.speedyspeech_config) as f: + speedyspeech_config = CfgNode(yaml.safe_load(f)) + with open(args.pwg_config) as f: + pwg_config = CfgNode(yaml.safe_load(f)) + + print("========Args========") + print(yaml.safe_dump(vars(args))) + print("========Config========") + print(speedyspeech_config) + print(pwg_config) + + evaluate(args, speedyspeech_config, pwg_config) + + +if __name__ == "__main__": + main() diff --git a/examples/csmsc/speedyspeech/train.py b/examples/csmsc/speedyspeech/train.py new file mode 100644 index 00000000..f7a4e301 --- /dev/null +++ b/examples/csmsc/speedyspeech/train.py @@ -0,0 +1,224 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +import logging +import os +import shutil + +import jsonlines +import numpy as np +import paddle +import yaml +from paddle import distributed as dist +from paddle import DataParallel +from paddle.io import DataLoader +from paddle.io import DistributedBatchSampler +from parakeet.datasets.data_table import DataTable +from parakeet.datasets.am_batch_fn import speedyspeech_batch_fn +from parakeet.models.speedyspeech import SpeedySpeech +from parakeet.models.speedyspeech import SpeedySpeechEvaluator +from parakeet.models.speedyspeech import SpeedySpeechUpdater +from parakeet.training.extensions.snapshot import Snapshot +from parakeet.training.extensions.visualizer import VisualDL +from parakeet.training.optimizer import build_optimizers +from parakeet.training.seeding import seed_everything +from parakeet.training.trainer import Trainer +from pathlib import Path +from visualdl import LogWriter +from yacs.config import CfgNode + + +def train_sp(args, config): + # decides device type and whether to run in parallel + # setup running environment correctly + world_size = paddle.distributed.get_world_size() + if not paddle.is_compiled_with_cuda(): + paddle.set_device("cpu") + else: + paddle.set_device("gpu") + if world_size > 1: + paddle.distributed.init_parallel_env() + + # set the random seed, it is a must for multiprocess training + seed_everything(config.seed) + + print( + f"rank: {dist.get_rank()}, pid: {os.getpid()}, parent_pid: {os.getppid()}", + ) + + # dataloader has been too verbose + logging.getLogger("DataLoader").disabled = True + + # construct dataset for training and validation + with jsonlines.open(args.train_metadata, 'r') as reader: + train_metadata = list(reader) + if args.use_relative_path: + # if use_relative_path in preprocess, covert it to absolute path here + metadata_dir = Path(args.train_metadata).parent + for item in train_metadata: + item["feats"] = str(metadata_dir / item["feats"]) + + train_dataset = DataTable( + data=train_metadata, + fields=[ + "phones", "tones", "num_phones", "num_frames", "feats", "durations" + ], + converters={ + "feats": np.load, + }, ) + with jsonlines.open(args.dev_metadata, 'r') as reader: + dev_metadata = list(reader) + if args.use_relative_path: + # if use_relative_path in preprocess, covert it to absolute path here + metadata_dir = Path(args.dev_metadata).parent + for item in dev_metadata: + item["feats"] = str(metadata_dir / item["feats"]) + + dev_dataset = DataTable( + data=dev_metadata, + fields=[ + "phones", "tones", "num_phones", "num_frames", "feats", "durations" + ], + converters={ + "feats": np.load, + }, ) + + # collate function and dataloader + train_sampler = DistributedBatchSampler( + train_dataset, + batch_size=config.batch_size, + shuffle=True, + drop_last=True) + print("samplers done!") + + train_dataloader = DataLoader( + train_dataset, + batch_sampler=train_sampler, + collate_fn=speedyspeech_batch_fn, + num_workers=config.num_workers) + dev_dataloader = DataLoader( + dev_dataset, + shuffle=False, + drop_last=False, + batch_size=config.batch_size, + collate_fn=speedyspeech_batch_fn, + num_workers=config.num_workers) + print("dataloaders done!") + with open(args.phones_dict, "r") as f: + phn_id = [line.strip().split() for line in f.readlines()] + vocab_size = len(phn_id) + print("vocab_size:", vocab_size) + with open(args.tones_dict, "r") as f: + tone_id = [line.strip().split() for line in f.readlines()] + tone_size = len(tone_id) + print("tone_size:", tone_size) + + model = SpeedySpeech( + vocab_size=vocab_size, tone_size=tone_size, **config["model"]) + if world_size > 1: + model = DataParallel(model) + print("model done!") + optimizer = build_optimizers(model, **config["optimizer"]) + print("optimizer done!") + + output_dir = Path(args.output_dir) + output_dir.mkdir(parents=True, exist_ok=True) + if dist.get_rank() == 0: + config_name = args.config.split("/")[-1] + # copy conf to output_dir + shutil.copyfile(args.config, output_dir / config_name) + + updater = SpeedySpeechUpdater( + model=model, + optimizer=optimizer, + dataloader=train_dataloader, + output_dir=output_dir) + + trainer = Trainer(updater, (config.max_epoch, 'epoch'), output_dir) + + evaluator = SpeedySpeechEvaluator( + model, dev_dataloader, output_dir=output_dir) + + if dist.get_rank() == 0: + trainer.extend(evaluator, trigger=(1, "epoch")) + writer = LogWriter(str(output_dir)) + trainer.extend(VisualDL(writer), trigger=(1, "iteration")) + trainer.extend( + Snapshot(max_size=config.num_snapshots), trigger=(1, 'epoch')) + trainer.run() + + +def main(): + # parse args and config and redirect to train_sp + parser = argparse.ArgumentParser( + description="Train a Speedyspeech model with sigle speaker dataset.") + parser.add_argument("--config", type=str, help="config file.") + parser.add_argument("--train-metadata", type=str, help="training data.") + parser.add_argument("--dev-metadata", type=str, help="dev data.") + parser.add_argument("--output-dir", type=str, help="output dir.") + parser.add_argument( + "--device", type=str, default="gpu", help="device type to use.") + parser.add_argument( + "--nprocs", type=int, default=1, help="number of processes.") + parser.add_argument("--verbose", type=int, default=1, help="verbose.") + + def str2bool(str): + return True if str.lower() == 'true' else False + + parser.add_argument( + "--use-relative-path", + type=str2bool, + default=False, + help="whether use relative path in metadata") + + parser.add_argument( + "--phones-dict", type=str, default=None, help="phone vocabulary file.") + + parser.add_argument( + "--tones-dict", type=str, default=None, help="tone vocabulary file.") + + # 这里可以多传入 max_epoch 等 + args, rest = parser.parse_known_args() + if args.device == "cpu" and args.nprocs > 1: + raise RuntimeError("Multiprocess training on CPU is not supported.") + with open(args.config) as f: + config = CfgNode(yaml.safe_load(f)) + + if rest: + extra = [] + # to support key=value format + for item in rest: + # remove "--" + item = item[2:] + extra.extend(item.split("=", maxsplit=1)) + config.merge_from_list(extra) + + print("========Args========") + print(yaml.safe_dump(vars(args))) + print("========Config========") + print(config) + print( + f"master see the word size: {dist.get_world_size()}, from pid: {os.getpid()}" + ) + + # dispatch + if args.nprocs > 1: + dist.spawn(train_sp, (args, config), nprocs=args.nprocs) + else: + train_sp(args, config) + + +if __name__ == "__main__": + main() diff --git a/examples/ljspeech/README.md b/examples/ljspeech/README.md new file mode 100644 index 00000000..db87b149 --- /dev/null +++ b/examples/ljspeech/README.md @@ -0,0 +1,6 @@ + +# LJSpeech + +* tts0 - Tactron2 +* tts1 - TransformerTTS +* voc0 - WaveFlow diff --git a/examples/ljspeech/tts0/local/tacotron2/README.md b/examples/ljspeech/tts0/local/tacotron2/README.md new file mode 100644 index 00000000..e5f159df --- /dev/null +++ b/examples/ljspeech/tts0/local/tacotron2/README.md @@ -0,0 +1,92 @@ +# Tacotron2 + +PaddlePaddle dynamic graph implementation of Tacotron2, a neural network architecture for speech synthesis directly from text. The implementation is based on [Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions](https://arxiv.org/abs/1712.05884). + +## Project Structure + +```text +├── config.py # default configuration file +├── ljspeech.py # dataset and dataloader settings for LJSpeech +├── preprocess.py # script to preprocess LJSpeech dataset +├── synthesize.py # script to synthesize spectrogram from text +├── train.py # script for tacotron2 model training +├── synthesize.ipynb # notebook example for end-to-end TTS +``` + +## Dataset + +We experiment with the LJSpeech dataset. Download and unzip [LJSpeech](https://keithito.com/LJ-Speech-Dataset/). + +```bash +wget https://data.keithito.com/data/speech/LJSpeech-1.1.tar.bz2 +tar xjvf LJSpeech-1.1.tar.bz2 +``` + +Then you need to preprocess the data by running ``preprocess.py``, the preprocessed data will be placed in ``--output`` directory. + +```bash +python preprocess.py \ +--input=${DATAPATH} \ +--output=${PREPROCESSEDDATAPATH} \ +-v \ +``` + +For more help on arguments + +``python preprocess.py --help``. + +## Train the model + +Tacotron2 model can be trained by running ``train.py``. + +```bash +python train.py \ +--data=${PREPROCESSEDDATAPATH} \ +--output=${OUTPUTPATH} \ +--device=gpu \ +``` + +If you want to train on CPU, just set ``--device=cpu``. +If you want to train on multiple GPUs, just set ``--nprocs`` as num of GPU. +By default, training will be resumed from the latest checkpoint in ``--output``, if you want to start a new training, please use a new ``${OUTPUTPATH}`` with no checkpoint. And if you want to resume from an other existing model, you should set ``checkpoint_path`` to be the checkpoint path you want to load. + +**Note: The checkpoint path cannot contain the file extension.** + +For more help on arguments + +``python train_transformer.py --help``. + +## Synthesize + +After training the Tacotron2, spectrogram can be synthesized by running ``synthesize.py``. + +```bash +python synthesize.py \ +--config=${CONFIGPATH} \ +--checkpoint_path=${CHECKPOINTPATH} \ +--input=${TEXTPATH} \ +--output=${OUTPUTPATH} +--device=gpu +``` + +The ``${CONFIGPATH}`` needs to be matched with ``${CHECKPOINTPATH}``. + +For more help on arguments + +``python synthesize.py --help``. + +Then you can find the spectrogram files in ``${OUTPUTPATH}``, and then they can be the input of vocoder like [waveflow](../waveflow/README.md#Synthesis) to get audio files. + + +## Pretrained Models + +Pretrained Models can be downloaded from links below. We provide 2 models with different configurations. + +1. This model use a binary classifier to predict the stop token. [tacotron2_ljspeech_ckpt_0.3.zip](https://paddlespeech.bj.bcebos.com/Parakeet/tacotron2_ljspeech_ckpt_0.3.zip) + +2. This model does not have a stop token predictor. It uses the attention peak position to decided whether all the contents have been uttered. Also guided attention loss is used to speed up training. This model is trained with `configs/alternative.yaml`.[tacotron2_ljspeech_ckpt_0.3_alternative.zip](https://paddlespeech.bj.bcebos.com/Parakeet/tacotron2_ljspeech_ckpt_0.3_alternative.zip) + + +## Notebook: End-to-end TTS + +See [synthesize.ipynb](./synthesize.ipynb) for details about end-to-end TTS with tacotron2 and waveflow. diff --git a/examples/ljspeech/tts0/local/tacotron2/config.py b/examples/ljspeech/tts0/local/tacotron2/config.py new file mode 100644 index 00000000..e370e77a --- /dev/null +++ b/examples/ljspeech/tts0/local/tacotron2/config.py @@ -0,0 +1,76 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from yacs.config import CfgNode as CN + +_C = CN() +_C.data = CN( + dict( + batch_size=32, # batch size + valid_size=64, # the first N examples are reserved for validation + sample_rate=22050, # Hz, sample rate + n_fft=1024, # fft frame size + win_length=1024, # window size + hop_length=256, # hop size between ajacent frame + fmax=8000, # Hz, max frequency when converting to mel + fmin=0, # Hz, min frequency when converting to mel + n_mels=80, # mel bands + padding_idx=0, # text embedding's padding index + )) + +_C.model = CN( + dict( + vocab_size=37, # set this according to the frontend's vocab size + n_tones=None, + reduction_factor=1, # reduction factor + d_encoder=512, # embedding & encoder's internal size + encoder_conv_layers=3, # number of conv layer in tacotron2 encoder + encoder_kernel_size=5, # kernel size of conv layers in tacotron2 encoder + d_prenet=256, # hidden size of decoder prenet + d_attention_rnn=1024, # hidden size of the first rnn layer in tacotron2 decoder + d_decoder_rnn=1024, # hidden size of the second rnn layer in tacotron2 decoder + d_attention=128, # hidden size of decoder location linear layer + attention_filters=32, # number of filter in decoder location conv layer + attention_kernel_size=31, # kernel size of decoder location conv layer + d_postnet=512, # hidden size of decoder postnet + postnet_kernel_size=5, # kernel size of conv layers in postnet + postnet_conv_layers=5, # number of conv layer in decoder postnet + p_encoder_dropout=0.5, # droput probability in encoder + p_prenet_dropout=0.5, # droput probability in decoder prenet + p_attention_dropout=0.1, # droput probability of first rnn layer in decoder + p_decoder_dropout=0.1, # droput probability of second rnn layer in decoder + p_postnet_dropout=0.5, # droput probability in decoder postnet + d_global_condition=None, + use_stop_token=True, # wherther to use binary classifier to predict when to stop + use_guided_attention_loss=False, # whether to use guided attention loss + guided_attention_loss_sigma=0.2 # sigma in guided attention loss + )) + +_C.training = CN( + dict( + lr=1e-3, # learning rate + weight_decay=1e-6, # the coeff of weight decay + grad_clip_thresh=1.0, # the clip norm of grad clip. + plot_interval=1000, # plot attention and spectrogram + valid_interval=1000, # validation + save_interval=1000, # checkpoint + max_iteration=500000, # max iteration to train + )) + + +def get_cfg_defaults(): + """Get a yacs CfgNode object with default values for my_project.""" + # Return a clone so that the defaults will not be altered + # This is for the "local variable" use pattern + return _C.clone() diff --git a/examples/ljspeech/tts0/local/tacotron2/ljspeech.py b/examples/ljspeech/tts0/local/tacotron2/ljspeech.py new file mode 100644 index 00000000..76e4b3a6 --- /dev/null +++ b/examples/ljspeech/tts0/local/tacotron2/ljspeech.py @@ -0,0 +1,94 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from pathlib import Path +import pickle + +import numpy as np +from paddle.io import Dataset + +from parakeet.data.batch import batch_spec, batch_text_id + + +class LJSpeech(Dataset): + """A simple dataset adaptor for the processed ljspeech dataset.""" + + def __init__(self, root): + self.root = Path(root).expanduser() + records = [] + with open(self.root / "metadata.pkl", 'rb') as f: + metadata = pickle.load(f) + for mel_name, text, ids in metadata: + mel_name = self.root / "mel" / (mel_name + ".npy") + records.append((mel_name, text, ids)) + self.records = records + + def __getitem__(self, i): + mel_name, _, ids = self.records[i] + mel = np.load(mel_name) + return ids, mel + + def __len__(self): + return len(self.records) + + +class LJSpeechCollector(object): + """A simple callable to batch LJSpeech examples.""" + + def __init__(self, padding_idx=0, padding_value=0., padding_stop_token=1.0): + self.padding_idx = padding_idx + self.padding_value = padding_value + self.padding_stop_token = padding_stop_token + + def __call__(self, examples): + texts = [] + mels = [] + text_lens = [] + mel_lens = [] + + for data in examples: + text, mel = data + text = np.array(text, dtype=np.int64) + text_lens.append(len(text)) + mels.append(mel) + texts.append(text) + mel_lens.append(mel.shape[1]) + + # Sort by text_len in descending order + texts = [ + i + for i, _ in sorted( + zip(texts, text_lens), key=lambda x: x[1], reverse=True) + ] + mels = [ + i + for i, _ in sorted( + zip(mels, text_lens), key=lambda x: x[1], reverse=True) + ] + + mel_lens = [ + i + for i, _ in sorted( + zip(mel_lens, text_lens), key=lambda x: x[1], reverse=True) + ] + + mel_lens = np.array(mel_lens, dtype=np.int64) + text_lens = np.array(sorted(text_lens, reverse=True), dtype=np.int64) + + # Pad sequence with largest len of the batch + texts, _ = batch_text_id(texts, pad_id=self.padding_idx) + mels, _ = batch_spec(mels, pad_value=self.padding_value) + mels = np.transpose(mels, axes=(0, 2, 1)) + + return texts, mels, text_lens, mel_lens diff --git a/examples/ljspeech/tts0/local/tacotron2/preprocess.py b/examples/ljspeech/tts0/local/tacotron2/preprocess.py new file mode 100644 index 00000000..aa7bf244 --- /dev/null +++ b/examples/ljspeech/tts0/local/tacotron2/preprocess.py @@ -0,0 +1,99 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import os +import pickle +import argparse +from pathlib import Path + +import tqdm +import numpy as np + +from parakeet.datasets import LJSpeechMetaData +from parakeet.audio import AudioProcessor, LogMagnitude +from parakeet.frontend import EnglishCharacter + +from config import get_cfg_defaults + + +def create_dataset(config, source_path, target_path, verbose=False): + # create output dir + target_path = Path(target_path).expanduser() + mel_path = target_path / "mel" + os.makedirs(mel_path, exist_ok=True) + + meta_data = LJSpeechMetaData(source_path) + frontend = EnglishCharacter() + processor = AudioProcessor( + sample_rate=config.data.sample_rate, + n_fft=config.data.n_fft, + n_mels=config.data.n_mels, + win_length=config.data.win_length, + hop_length=config.data.hop_length, + fmax=config.data.fmax, + fmin=config.data.fmin) + normalizer = LogMagnitude() + + records = [] + for (fname, text, _) in tqdm.tqdm(meta_data): + wav = processor.read_wav(fname) + mel = processor.mel_spectrogram(wav) + mel = normalizer.transform(mel) + ids = frontend(text) + mel_name = os.path.splitext(os.path.basename(fname))[0] + + # save mel spectrogram + records.append((mel_name, text, ids)) + np.save(mel_path / mel_name, mel) + if verbose: + print("save mel spectrograms into {}".format(mel_path)) + + # save meta data as pickle archive + with open(target_path / "metadata.pkl", 'wb') as f: + pickle.dump(records, f) + if verbose: + print("saved metadata into {}".format(target_path / "metadata.pkl")) + + print("Done.") + + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="create dataset") + parser.add_argument( + "--config", + type=str, + metavar="FILE", + help="extra config to overwrite the default config") + parser.add_argument( + "--input", type=str, help="path of the ljspeech dataset") + parser.add_argument( + "--output", type=str, help="path to save output dataset") + parser.add_argument( + "--opts", + nargs=argparse.REMAINDER, + help="options to overwrite --config file and the default config, passing in KEY VALUE pairs" + ) + parser.add_argument( + "-v", "--verbose", action="store_true", help="print msg") + + config = get_cfg_defaults() + args = parser.parse_args() + if args.config: + config.merge_from_file(args.config) + if args.opts: + config.merge_from_list(args.opts) + config.freeze() + print(config.data) + + create_dataset(config, args.input, args.output, args.verbose) diff --git a/examples/ljspeech/tts0/local/tacotron2/synthesize.ipynb b/examples/ljspeech/tts0/local/tacotron2/synthesize.ipynb new file mode 100644 index 00000000..f71182f2 --- /dev/null +++ b/examples/ljspeech/tts0/local/tacotron2/synthesize.ipynb @@ -0,0 +1,342 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## TTS with Tacotron2 + Waveflow" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import paddle\n", + "from matplotlib import pyplot as plt\n", + "from IPython import display as ipd\n", + "%matplotlib inline\n", + "\n", + "from parakeet.utils import display\n", + "from parakeet.utils import layer_tools\n", + "paddle.set_device(\"gpu:0\")\n", + "\n", + "import sys\n", + "sys.path.append(\"../..\")\n", + "import examples" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Tacotron2: synthesizer model\n", + "\n", + "Tacotron2 is used here as a phonemes to spectrogram model. Here we will use an alternative config. In this config, the tacotron2 model does not have a binary classifier to predict whether the generation should stop.\n", + "\n", + "Instead, the peak position is used as the criterion. When the peak position of the attention reaches the end of the encoder outputs, it implies that the content is exhausted. So we stop the generated after 10 frames." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "from parakeet.models.tacotron2 import Tacotron2\n", + "from parakeet.frontend import EnglishCharacter" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "data:\n", + " batch_size: 32\n", + " fmax: 8000\n", + " fmin: 0\n", + " hop_length: 256\n", + " n_fft: 1024\n", + " n_mels: 80\n", + " padding_idx: 0\n", + " sample_rate: 22050\n", + " valid_size: 64\n", + " win_length: 1024\n", + "model:\n", + " attention_filters: 32\n", + " attention_kernel_size: 31\n", + " d_attention: 128\n", + " d_attention_rnn: 1024\n", + " d_decoder_rnn: 1024\n", + " d_encoder: 512\n", + " d_global_condition: None\n", + " d_postnet: 512\n", + " d_prenet: 256\n", + " encoder_conv_layers: 3\n", + " encoder_kernel_size: 5\n", + " guided_attention_loss_sigma: 0.2\n", + " n_tones: None\n", + " p_attention_dropout: 0.1\n", + " p_decoder_dropout: 0.1\n", + " p_encoder_dropout: 0.5\n", + " p_postnet_dropout: 0.5\n", + " p_prenet_dropout: 0.5\n", + " postnet_conv_layers: 5\n", + " postnet_kernel_size: 5\n", + " reduction_factor: 1\n", + " use_guided_attention_loss: True\n", + " use_stop_token: False\n", + " vocab_size: 37\n", + "training:\n", + " grad_clip_thresh: 1.0\n", + " lr: 0.001\n", + " max_iteration: 500000\n", + " plot_interval: 1000\n", + " save_interval: 1000\n", + " valid_interval: 1000\n", + " weight_decay: 1e-06\n" + ] + } + ], + "source": [ + "from examples.tacotron2 import config as tacotron2_config\n", + "synthesizer_config = tacotron2_config.get_cfg_defaults()\n", + "synthesizer_config.merge_from_file(\"configs/alternative.yaml\")\n", + "print(synthesizer_config)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[checkpoint] Rank 0: loaded model from ../../pretrained/tacotron2/tacotron2_ljspeech_ckpt_0.3_alternative/step-50000.pdparams\n" + ] + } + ], + "source": [ + "frontend = EnglishCharacter()\n", + "model = Tacotron2.from_pretrained(\n", + " synthesizer_config, \"../../pretrained/tacotron2/tacotron2_ljspeech_ckpt_0.3_alternative/step-50000\")\n", + "model.eval()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 36%|███▋ | 365/1000 [00:01<00:02, 256.89it/s]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "content exhausted!\n" + ] + } + ], + "source": [ + "sentence = \"Life was like a box of chocolates, you never know what you're gonna get.\" \n", + "sentence = paddle.to_tensor(frontend(sentence)).unsqueeze(0)\n", + "\n", + "with paddle.no_grad():\n", + " outputs = model.infer(sentence)\n", + "mel_output = outputs[\"mel_outputs_postnet\"][0].numpy().T\n", + "alignment = outputs[\"alignments\"][0].numpy().T" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
    " + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = display.plot_alignment(alignment)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## WaveFlow: vocoder model\n", + "Generated spectrogram is converted to raw audio using a pretrained waveflow model." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "from parakeet.models.waveflow import ConditionalWaveFlow" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "data:\n", + " batch_size: 8\n", + " clip_frames: 65\n", + " fmax: 8000\n", + " fmin: 0\n", + " hop_length: 256\n", + " n_fft: 1024\n", + " n_mels: 80\n", + " sample_rate: 22050\n", + " valid_size: 16\n", + " win_length: 1024\n", + "model:\n", + " channels: 128\n", + " kernel_size: [3, 3]\n", + " n_flows: 8\n", + " n_group: 16\n", + " n_layers: 8\n", + " sigma: 1.0\n", + " upsample_factors: [16, 16]\n", + "training:\n", + " lr: 0.0002\n", + " max_iteration: 3000000\n", + " save_interval: 10000\n", + " valid_interval: 1000\n" + ] + } + ], + "source": [ + "from examples.waveflow import config as waveflow_config\n", + "vocoder_config = waveflow_config.get_cfg_defaults()\n", + "print(vocoder_config)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[checkpoint] Rank 0: loaded model from ../../pretrained/waveflow/waveflow_ljspeech_ckpt_0.3/step-2000000.pdparams\n" + ] + } + ], + "source": [ + "vocoder = ConditionalWaveFlow.from_pretrained(\n", + " vocoder_config, \n", + " \"../../pretrained/waveflow/waveflow_ljspeech_ckpt_0.3/step-2000000\")\n", + "layer_tools.recursively_remove_weight_norm(vocoder)\n", + "vocoder.eval()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "time: 9.412613868713379s\n" + ] + } + ], + "source": [ + "audio = vocoder.infer(paddle.transpose(outputs[\"mel_outputs_postnet\"], [0, 2, 1]))\n", + "wav = audio[0].numpy()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ipd.Audio(wav, rate=22050)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/examples/ljspeech/tts0/local/tacotron2/synthesize.py b/examples/ljspeech/tts0/local/tacotron2/synthesize.py new file mode 100644 index 00000000..f933c32c --- /dev/null +++ b/examples/ljspeech/tts0/local/tacotron2/synthesize.py @@ -0,0 +1,95 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +from pathlib import Path + +import paddle +import numpy as np +from matplotlib import pyplot as plt + +from parakeet.frontend import EnglishCharacter +from parakeet.models.tacotron2 import Tacotron2 +from parakeet.utils import display + +from config import get_cfg_defaults + + +def main(config, args): + paddle.set_device(args.device) + + # model + frontend = EnglishCharacter() + model = Tacotron2.from_pretrained(config, args.checkpoint_path) + model.eval() + + # inputs + input_path = Path(args.input).expanduser() + with open(input_path, "rt") as f: + sentences = f.readlines() + + if args.output is None: + output_dir = input_path.parent / "synthesis" + else: + output_dir = Path(args.output).expanduser() + output_dir.mkdir(exist_ok=True) + + for i, sentence in enumerate(sentences): + sentence = paddle.to_tensor(frontend(sentence)).unsqueeze(0) + outputs = model.infer(sentence) + mel_output = outputs["mel_outputs_postnet"][0].numpy().T + alignment = outputs["alignments"][0].numpy().T + + np.save(str(output_dir / f"sentence_{i}"), mel_output) + display.plot_alignment(alignment) + plt.savefig(str(output_dir / f"sentence_{i}.png")) + if args.verbose: + print("spectrogram saved at {}".format(output_dir / + f"sentence_{i}.npy")) + + +if __name__ == "__main__": + config = get_cfg_defaults() + + parser = argparse.ArgumentParser( + description="generate mel spectrogram with TransformerTTS.") + parser.add_argument( + "--config", + type=str, + metavar="FILE", + help="extra config to overwrite the default config") + parser.add_argument( + "--checkpoint_path", type=str, help="path of the checkpoint to load.") + parser.add_argument("--input", type=str, help="path of the text sentences") + parser.add_argument("--output", type=str, help="path to save outputs") + parser.add_argument( + "--device", type=str, default="cpu", help="device type to use.") + parser.add_argument( + "--opts", + nargs=argparse.REMAINDER, + help="options to overwrite --config file and the default config, passing in KEY VALUE pairs" + ) + parser.add_argument( + "-v", "--verbose", action="store_true", help="print msg") + + args = parser.parse_args() + if args.config: + config.merge_from_file(args.config) + if args.opts: + config.merge_from_list(args.opts) + config.freeze() + print(config) + print(args) + + main(config, args) diff --git a/examples/ljspeech/tts0/local/tacotron2/train.py b/examples/ljspeech/tts0/local/tacotron2/train.py new file mode 100644 index 00000000..82dd4c32 --- /dev/null +++ b/examples/ljspeech/tts0/local/tacotron2/train.py @@ -0,0 +1,218 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import time +from collections import defaultdict + +import numpy as np +import paddle +from paddle.io import DataLoader +from paddle.io import DistributedBatchSampler +from paddle import distributed as dist +from parakeet.data import dataset +from parakeet.training.cli import default_argument_parser +from parakeet.training.experiment import ExperimentBase +from parakeet.utils import display, mp_tools +from parakeet.models.tacotron2 import Tacotron2, Tacotron2Loss + +from config import get_cfg_defaults +from ljspeech import LJSpeech, LJSpeechCollector + + +class Experiment(ExperimentBase): + def compute_losses(self, inputs, outputs): + texts, mel_targets, plens, slens = inputs + + mel_outputs = outputs["mel_output"] + mel_outputs_postnet = outputs["mel_outputs_postnet"] + attention_weight = outputs["alignments"] + if self.config.model.use_stop_token: + stop_logits = outputs["stop_logits"] + else: + stop_logits = None + + losses = self.criterion(mel_outputs, mel_outputs_postnet, mel_targets, + attention_weight, slens, plens, stop_logits) + return losses + + def train_batch(self): + start = time.time() + batch = self.read_batch() + data_loader_time = time.time() - start + + self.optimizer.clear_grad() + self.model.train() + texts, mels, text_lens, output_lens = batch + outputs = self.model(texts, text_lens, mels, output_lens) + losses = self.compute_losses(batch, outputs) + loss = losses["loss"] + loss.backward() + self.optimizer.step() + iteration_time = time.time() - start + + losses_np = {k: float(v) for k, v in losses.items()} + # logging + msg = "Rank: {}, ".format(dist.get_rank()) + msg += "step: {}, ".format(self.iteration) + msg += "time: {:>.3f}s/{:>.3f}s, ".format(data_loader_time, + iteration_time) + msg += ', '.join('{}: {:>.6f}'.format(k, v) + for k, v in losses_np.items()) + self.logger.info(msg) + + if dist.get_rank() == 0: + for k, v in losses_np.items(): + self.visualizer.add_scalar(f"train_loss/{k}", v, self.iteration) + + @mp_tools.rank_zero_only + @paddle.no_grad() + def valid(self): + valid_losses = defaultdict(list) + for i, batch in enumerate(self.valid_loader): + texts, mels, text_lens, output_lens = batch + outputs = self.model(texts, text_lens, mels, output_lens) + losses = self.compute_losses(batch, outputs) + for k, v in losses.items(): + valid_losses[k].append(float(v)) + + attention_weights = outputs["alignments"] + self.visualizer.add_figure( + f"valid_sentence_{i}_alignments", + display.plot_alignment(attention_weights[0].numpy().T), + self.iteration) + self.visualizer.add_figure( + f"valid_sentence_{i}_target_spectrogram", + display.plot_spectrogram(mels[0].numpy().T), self.iteration) + self.visualizer.add_figure( + f"valid_sentence_{i}_predicted_spectrogram", + display.plot_spectrogram(outputs['mel_outputs_postnet'][0] + .numpy().T), self.iteration) + + # write visual log + valid_losses = {k: np.mean(v) for k, v in valid_losses.items()} + + # logging + msg = "Valid: " + msg += "step: {}, ".format(self.iteration) + msg += ', '.join('{}: {:>.6f}'.format(k, v) + for k, v in valid_losses.items()) + self.logger.info(msg) + + for k, v in valid_losses.items(): + self.visualizer.add_scalar(f"valid/{k}", v, self.iteration) + + def setup_model(self): + config = self.config + model = Tacotron2( + vocab_size=config.model.vocab_size, + d_mels=config.data.n_mels, + d_encoder=config.model.d_encoder, + encoder_conv_layers=config.model.encoder_conv_layers, + encoder_kernel_size=config.model.encoder_kernel_size, + d_prenet=config.model.d_prenet, + d_attention_rnn=config.model.d_attention_rnn, + d_decoder_rnn=config.model.d_decoder_rnn, + attention_filters=config.model.attention_filters, + attention_kernel_size=config.model.attention_kernel_size, + d_attention=config.model.d_attention, + d_postnet=config.model.d_postnet, + postnet_kernel_size=config.model.postnet_kernel_size, + postnet_conv_layers=config.model.postnet_conv_layers, + reduction_factor=config.model.reduction_factor, + p_encoder_dropout=config.model.p_encoder_dropout, + p_prenet_dropout=config.model.p_prenet_dropout, + p_attention_dropout=config.model.p_attention_dropout, + p_decoder_dropout=config.model.p_decoder_dropout, + p_postnet_dropout=config.model.p_postnet_dropout, + use_stop_token=config.model.use_stop_token) + + if self.parallel: + model = paddle.DataParallel(model) + + grad_clip = paddle.nn.ClipGradByGlobalNorm( + config.training.grad_clip_thresh) + optimizer = paddle.optimizer.Adam( + learning_rate=config.training.lr, + parameters=model.parameters(), + weight_decay=paddle.regularizer.L2Decay( + config.training.weight_decay), + grad_clip=grad_clip) + criterion = Tacotron2Loss( + use_stop_token_loss=config.model.use_stop_token, + use_guided_attention_loss=config.model.use_guided_attention_loss, + sigma=config.model.guided_attention_loss_sigma) + self.model = model + self.optimizer = optimizer + self.criterion = criterion + + def setup_dataloader(self): + args = self.args + config = self.config + ljspeech_dataset = LJSpeech(args.data) + + valid_set, train_set = dataset.split(ljspeech_dataset, + config.data.valid_size) + batch_fn = LJSpeechCollector(padding_idx=config.data.padding_idx) + + if not self.parallel: + self.train_loader = DataLoader( + train_set, + batch_size=config.data.batch_size, + shuffle=True, + drop_last=True, + collate_fn=batch_fn) + else: + sampler = DistributedBatchSampler( + train_set, + batch_size=config.data.batch_size, + shuffle=True, + drop_last=True) + self.train_loader = DataLoader( + train_set, batch_sampler=sampler, collate_fn=batch_fn) + + self.valid_loader = DataLoader( + valid_set, + batch_size=config.data.batch_size, + shuffle=False, + drop_last=False, + collate_fn=batch_fn) + + +def main_sp(config, args): + exp = Experiment(config, args) + exp.setup() + exp.resume_or_load() + exp.run() + + +def main(config, args): + if args.nprocs > 1 and args.device == "gpu": + dist.spawn(main_sp, args=(config, args), nprocs=args.nprocs) + else: + main_sp(config, args) + + +if __name__ == "__main__": + config = get_cfg_defaults() + parser = default_argument_parser() + args = parser.parse_args() + if args.config: + config.merge_from_file(args.config) + if args.opts: + config.merge_from_list(args.opts) + config.freeze() + print(config) + print(args) + + main(config, args) diff --git a/examples/ljspeech/tts0/run.sh b/examples/ljspeech/tts0/run.sh new file mode 100644 index 00000000..e69de29b diff --git a/examples/ljspeech/tts1/local/transformer_tts/ljspeech/README.md b/examples/ljspeech/tts1/local/transformer_tts/ljspeech/README.md new file mode 100644 index 00000000..b6b2ac9a --- /dev/null +++ b/examples/ljspeech/tts1/local/transformer_tts/ljspeech/README.md @@ -0,0 +1,194 @@ +# TransformerTTS with LJSpeech +## Dataset +### Download the datasaet +```bash +wget https://data.keithito.com/data/speech/LJSpeech-1.1.tar.bz2 +``` +### Extract the dataset +```bash +tar xjvf LJSpeech-1.1.tar.bz2 +``` +### Preprocess the dataset +Assume the path to the dataset is `~/datasets/LJSpeech-1.1`. +Run the command below to preprocess the dataset. + +```bash +./preprocess.sh. +``` +When it is done. A `dump` folder is created in the current directory. The structure of the dump folder is listed below. +```text +dump +├── dev +│ ├── norm +│ └── raw +├── phone_id_map.txt +├── speaker_id_map.txt +├── test +│ ├── norm +│ └── raw +└── train + ├── norm + ├── raw + └── speech_stats.npy +``` +The dataset is split into 3 parts, namely `train`, `dev` and` test`, each of which contains a `norm` and `raw` sub folder. The raw folder contains speech feature of each utterances, while the norm folder contains normalized ones. The statistics used to normalize features are computed from the training set, which is located in `dump/train/speech_stats.npy`. + +Also there is a `metadata.jsonl` in each subfolder. It is a table-like file which contains phones, text_lengths, speech_lengths, path of speech features, speaker and id of each utterance. + +## Train the model +`./run.sh` calls `../train.py`. +```bash +./run.sh +``` +Here's the complete help message. +```text +usage: train.py [-h] [--config CONFIG] [--train-metadata TRAIN_METADATA] + [--dev-metadata DEV_METADATA] [--output-dir OUTPUT_DIR] + [--device DEVICE] [--nprocs NPROCS] [--verbose VERBOSE] + [--phones-dict PHONES_DICT] + +Train a TransformerTTS model with LJSpeech TTS dataset. + +optional arguments: + -h, --help show this help message and exit + --config CONFIG config file to overwrite default config. + --train-metadata TRAIN_METADATA + training data. + --dev-metadata DEV_METADATA + dev data. + --output-dir OUTPUT_DIR + output dir. + --device DEVICE device type to use. + --nprocs NPROCS number of processes. + --verbose VERBOSE verbose. + --phones-dict PHONES_DICT + phone vocabulary file. +``` +1. `--config` is a config file in yaml format to overwrite the default config, which can be found at `conf/default.yaml`. +2. `--train-metadata` and `--dev-metadata` should be the metadata file in the normalized subfolder of `train` and `dev` in the `dump` folder. +3. `--output-dir` is the directory to save the results of the experiment. Checkpoints are save in `checkpoints/` inside this directory. +4. `--device` is the type of the device to run the experiment, 'cpu' or 'gpu' are supported. +5. `--nprocs` is the number of processes to run in parallel, note that nprocs > 1 is only supported when `--device` is 'gpu'. +6. `--phones-dict` is the path of the phone vocabulary file. + +## Pretrained Model +Pretrained Model can be downloaded here. [transformer_tts_ljspeech_ckpt_0.4.zip](https://paddlespeech.bj.bcebos.com/Parakeet/transformer_tts_ljspeech_ckpt_0.4.zip) + +TransformerTTS checkpoint contains files listed below. +```text +transformer_tts_ljspeech_ckpt_0.4 +├── default.yaml # default config used to train transformer_tts +├── phone_id_map.txt # phone vocabulary file when training transformer_tts +├── snapshot_iter_201500.pdz # model parameters and optimizer states +└── speech_stats.npy # statistics used to normalize spectrogram when training transformer_tts +``` +## Synthesize +We use [waveflow](https://github.com/PaddlePaddle/Parakeet/tree/develop/examples/waveflow) as the neural vocoder. +Download Pretrained WaveFlow Model with residual channel equals 128 from [waveflow_ljspeech_ckpt_0.3.zip](https://paddlespeech.bj.bcebos.com/Parakeet/waveflow_ljspeech_ckpt_0.3.zip) and unzip it. +```bash +unzip waveflow_ljspeech_ckpt_0.3.zip +``` +WaveFlow checkpoint contains files listed below. +```text +waveflow_ljspeech_ckpt_0.3 +├── config.yaml # default config used to train waveflow +└── step-2000000.pdparams # model parameters of waveflow +``` +`synthesize.sh` calls `../synthesize.py`, which can synthesize waveform from `metadata.jsonl`. +```bash +./synthesize.sh +``` +```text +usage: synthesize.py [-h] [--transformer-tts-config TRANSFORMER_TTS_CONFIG] + [--transformer-tts-checkpoint TRANSFORMER_TTS_CHECKPOINT] + [--transformer-tts-stat TRANSFORMER_TTS_STAT] + [--waveflow-config WAVEFLOW_CONFIG] + [--waveflow-checkpoint WAVEFLOW_CHECKPOINT] + [--phones-dict PHONES_DICT] + [--test-metadata TEST_METADATA] [--output-dir OUTPUT_DIR] + [--device DEVICE] [--verbose VERBOSE] + +Synthesize with transformer tts & waveflow. + +optional arguments: + -h, --help show this help message and exit + --transformer-tts-config TRANSFORMER_TTS_CONFIG + transformer tts config file. + --transformer-tts-checkpoint TRANSFORMER_TTS_CHECKPOINT + transformer tts checkpoint to load. + --transformer-tts-stat TRANSFORMER_TTS_STAT + mean and standard deviation used to normalize + spectrogram when training transformer tts. + --waveflow-config WAVEFLOW_CONFIG + waveflow config file. + --waveflow-checkpoint WAVEFLOW_CHECKPOINT + waveflow checkpoint to load. + --phones-dict PHONES_DICT + phone vocabulary file. + --test-metadata TEST_METADATA + test metadata. + --output-dir OUTPUT_DIR + output dir. + --device DEVICE device type to use. + --verbose VERBOSE verbose. +``` +`synthesize_e2e.sh` calls `synthesize_e2e.py`, which can synthesize waveform from text file. +```bash +./synthesize_e2e.sh +``` +```text +usage: synthesize_e2e.py [-h] + [--transformer-tts-config TRANSFORMER_TTS_CONFIG] + [--transformer-tts-checkpoint TRANSFORMER_TTS_CHECKPOINT] + [--transformer-tts-stat TRANSFORMER_TTS_STAT] + [--waveflow-config WAVEFLOW_CONFIG] + [--waveflow-checkpoint WAVEFLOW_CHECKPOINT] + [--phones-dict PHONES_DICT] [--text TEXT] + [--output-dir OUTPUT_DIR] [--device DEVICE] + [--verbose VERBOSE] + +Synthesize with transformer tts & waveflow. + +optional arguments: + -h, --help show this help message and exit + --transformer-tts-config TRANSFORMER_TTS_CONFIG + transformer tts config file. + --transformer-tts-checkpoint TRANSFORMER_TTS_CHECKPOINT + transformer tts checkpoint to load. + --transformer-tts-stat TRANSFORMER_TTS_STAT + mean and standard deviation used to normalize + spectrogram when training transformer tts. + --waveflow-config WAVEFLOW_CONFIG + waveflow config file. + --waveflow-checkpoint WAVEFLOW_CHECKPOINT + waveflow checkpoint to load. + --phones-dict PHONES_DICT + phone vocabulary file. + --text TEXT text to synthesize, a 'utt_id sentence' pair per line. + --output-dir OUTPUT_DIR + output dir. + --device DEVICE device type to use. + --verbose VERBOSE verbose. +``` +1. `--transformer-tts-config`, `--transformer-tts-checkpoint`, `--transformer-tts-stat` and `--phones-dict` are arguments for transformer_tts, which correspond to the 4 files in the transformer_tts pretrained model. +2. `--waveflow-config`, `--waveflow-checkpoint` are arguments for waveflow, which correspond to the 2 files in the waveflow pretrained model. +3. `--test-metadata` should be the metadata file in the normalized subfolder of `test` in the `dump` folder. +4. `--text` is the text file, which contains sentences to synthesize. +5. `--output-dir` is the directory to save synthesized audio files. +6. `--device` is the type of device to run synthesis, 'cpu' and 'gpu' are supported. 'gpu' is recommended for faster synthesis. + +You can use the following scripts to synthesize for `../sentences.txt` using pretrained transformer_tts and waveflow models. +```bash +FLAGS_allocator_strategy=naive_best_fit \ +FLAGS_fraction_of_gpu_memory_to_use=0.01 \ +python3 synthesize_e2e.py \ + --transformer-tts-config=transformer_tts_ljspeech_ckpt_0.4/default.yaml \ + --transformer-tts-checkpoint=transformer_tts_ljspeech_ckpt_0.4/snapshot_iter_201500.pdz \ + --transformer-tts-stat=transformer_tts_ljspeech_ckpt_0.4/speech_stats.npy \ + --waveflow-config=waveflow_ljspeech_ckpt_0.3/config.yaml \ + --waveflow-checkpoint=waveflow_ljspeech_ckpt_0.3/step-2000000.pdparams \ + --text=../sentences.txt \ + --output-dir=exp/default/test_e2e \ + --device="gpu" \ + --phones-dict=transformer_tts_ljspeech_ckpt_0.4/phone_id_map.txt +``` diff --git a/examples/ljspeech/tts1/local/transformer_tts/ljspeech/conf/default.yaml b/examples/ljspeech/tts1/local/transformer_tts/ljspeech/conf/default.yaml new file mode 100644 index 00000000..350212da --- /dev/null +++ b/examples/ljspeech/tts1/local/transformer_tts/ljspeech/conf/default.yaml @@ -0,0 +1,92 @@ + +fs : 22050 # Hz, sample rate +n_fft : 1024 # fft frame size +win_length : 1024 # window size +n_shift : 256 # hop size between ajacent frame +fmin : 0 # Hz, min frequency when converting to mel +fmax : 8000 # Hz, max frequency when converting to mel +n_mels : 80 # mel bands +window: "hann" # Window function. + +########################################################### +# DATA SETTING # +########################################################### +batch_size: 16 +num_workers: 2 + +########################################################## +# TTS MODEL SETTING # +########################################################## +tts: transformertts # model architecture +model: # keyword arguments for the selected model + embed_dim: 0 # embedding dimension in encoder prenet + eprenet_conv_layers: 0 # number of conv layers in encoder prenet + # if set to 0, no encoder prenet will be used + eprenet_conv_filts: 0 # filter size of conv layers in encoder prenet + eprenet_conv_chans: 0 # number of channels of conv layers in encoder prenet + dprenet_layers: 2 # number of layers in decoder prenet + dprenet_units: 256 # number of units in decoder prenet + adim: 512 # attention dimension + aheads: 8 # number of attention heads + elayers: 6 # number of encoder layers + eunits: 1024 # number of encoder ff units + dlayers: 6 # number of decoder layers + dunits: 1024 # number of decoder ff units + positionwise_layer_type: conv1d # type of position-wise layer + positionwise_conv_kernel_size: 1 # kernel size of position wise conv layer + postnet_layers: 5 # number of layers of postnset + postnet_filts: 5 # filter size of conv layers in postnet + postnet_chans: 256 # number of channels of conv layers in postnet + use_scaled_pos_enc: True # whether to use scaled positional encoding + encoder_normalize_before: True # whether to perform layer normalization before the input + decoder_normalize_before: True # whether to perform layer normalization before the input + reduction_factor: 1 # reduction factor + init_type: xavier_uniform # initialization type + init_enc_alpha: 1.0 # initial value of alpha of encoder scaled position encoding + init_dec_alpha: 1.0 # initial value of alpha of decoder scaled position encoding + eprenet_dropout_rate: 0.0 # dropout rate for encoder prenet + dprenet_dropout_rate: 0.5 # dropout rate for decoder prenet + postnet_dropout_rate: 0.5 # dropout rate for postnet + transformer_enc_dropout_rate: 0.1 # dropout rate for transformer encoder layer + transformer_enc_positional_dropout_rate: 0.1 # dropout rate for transformer encoder positional encoding + transformer_enc_attn_dropout_rate: 0.1 # dropout rate for transformer encoder attention layer + transformer_dec_dropout_rate: 0.1 # dropout rate for transformer decoder layer + transformer_dec_positional_dropout_rate: 0.1 # dropout rate for transformer decoder positional encoding + transformer_dec_attn_dropout_rate: 0.1 # dropout rate for transformer decoder attention layer + transformer_enc_dec_attn_dropout_rate: 0.1 # dropout rate for transformer encoder-decoder attention layer + num_heads_applied_guided_attn: 2 # number of heads to apply guided attention loss + num_layers_applied_guided_attn: 2 # number of layers to apply guided attention loss + + + +########################################################### +# UPDATER SETTING # +########################################################### +updater: + use_masking: true # whether to apply masking for padded part in loss calculation + loss_type: L1 + use_guided_attn_loss: true # whether to use guided attention loss + guided_attn_loss_sigma: 0.4 # sigma in guided attention loss + guided_attn_loss_lambda: 10.0 # lambda in guided attention loss + modules_applied_guided_attn: ["encoder-decoder"] # modules to apply guided attention loss + bce_pos_weight: 5.0 # weight of positive sample in binary cross entropy calculation + + +########################################################## +# OPTIMIZER & SCHEDULER SETTING # +########################################################## +optimizer: + optim: adam # optimizer type + learning_rate: 0.001 # learning rate + +########################################################### +# TRAINING SETTING # +########################################################### +max_epoch: 500 +num_snapshots: 5 + + +########################################################### +# OTHER SETTING # +########################################################### +seed: 10086 \ No newline at end of file diff --git a/examples/ljspeech/tts1/local/transformer_tts/ljspeech/preprocess.sh b/examples/ljspeech/tts1/local/transformer_tts/ljspeech/preprocess.sh new file mode 100755 index 00000000..7fc5247b --- /dev/null +++ b/examples/ljspeech/tts1/local/transformer_tts/ljspeech/preprocess.sh @@ -0,0 +1,50 @@ +#!/bin/bash + +stage=1 +stop_stage=100 + +export MAIN_ROOT=`realpath ${PWD}/../../../` + +if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then + # extract features + echo "Extract features ..." + python3 ../preprocess.py \ + --dataset=ljspeech \ + --rootdir=~/datasets/LJSpeech-1.1/ \ + --dumpdir=dump \ + --config-path=conf/default.yaml \ + --num-cpu=8 +fi + +if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then + # get features' stats(mean and std) + echo "Get features' stats ..." + python3 ${MAIN_ROOT}/utils/compute_statistics.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --field-name="speech" +fi + +if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then + # normalize and covert phone to id, dev and test should use train's stats + echo "Normalize ..." + python3 ../normalize.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --dumpdir=dump/train/norm \ + --speech-stats=dump/train/speech_stats.npy \ + --phones-dict=dump/phone_id_map.txt \ + --speaker-dict=dump/speaker_id_map.txt + + python3 ../normalize.py \ + --metadata=dump/dev/raw/metadata.jsonl \ + --dumpdir=dump/dev/norm \ + --speech-stats=dump/train/speech_stats.npy \ + --phones-dict=dump/phone_id_map.txt \ + --speaker-dict=dump/speaker_id_map.txt + + python3 ../normalize.py \ + --metadata=dump/test/raw/metadata.jsonl \ + --dumpdir=dump/test/norm \ + --speech-stats=dump/train/speech_stats.npy \ + --phones-dict=dump/phone_id_map.txt \ + --speaker-dict=dump/speaker_id_map.txt +fi diff --git a/examples/ljspeech/tts1/local/transformer_tts/ljspeech/run.sh b/examples/ljspeech/tts1/local/transformer_tts/ljspeech/run.sh new file mode 100755 index 00000000..f448bdfc --- /dev/null +++ b/examples/ljspeech/tts1/local/transformer_tts/ljspeech/run.sh @@ -0,0 +1,9 @@ +#!/bin/bash + +python3 ../train.py \ + --train-metadata=dump/train/norm/metadata.jsonl \ + --dev-metadata=dump/dev/norm/metadata.jsonl \ + --config=conf/default.yaml \ + --output-dir=exp/default \ + --nprocs=2 \ + --phones-dict=dump/phone_id_map.txt diff --git a/examples/ljspeech/tts1/local/transformer_tts/ljspeech/synthesize.sh b/examples/ljspeech/tts1/local/transformer_tts/ljspeech/synthesize.sh new file mode 100755 index 00000000..164e5ba2 --- /dev/null +++ b/examples/ljspeech/tts1/local/transformer_tts/ljspeech/synthesize.sh @@ -0,0 +1,13 @@ +#!/bin/bash +FLAGS_allocator_strategy=naive_best_fit \ +FLAGS_fraction_of_gpu_memory_to_use=0.01 \ +python3 ../synthesize.py \ + --transformer-tts-config=conf/default.yaml \ + --transformer-tts-checkpoint=exp/default/checkpoints/snapshot_iter_201500.pdz \ + --transformer-tts-stat=dump/train/speech_stats.npy \ + --waveflow-config=waveflow_ljspeech_ckpt_0.3/config.yaml \ + --waveflow-checkpoint=waveflow_ljspeech_ckpt_0.3/step-2000000.pdparams \ + --test-metadata=dump/test/norm/metadata.jsonl \ + --output-dir=exp/default/test \ + --device="gpu" \ + --phones-dict=dump/phone_id_map.txt diff --git a/examples/ljspeech/tts1/local/transformer_tts/ljspeech/synthesize_e2e.py b/examples/ljspeech/tts1/local/transformer_tts/ljspeech/synthesize_e2e.py new file mode 100644 index 00000000..7ca75a8f --- /dev/null +++ b/examples/ljspeech/tts1/local/transformer_tts/ljspeech/synthesize_e2e.py @@ -0,0 +1,161 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +import logging +from pathlib import Path + +import numpy as np +import paddle +import soundfile as sf +import yaml +from yacs.config import CfgNode +from parakeet.frontend import English +from parakeet.models.transformer_tts import TransformerTTS +from parakeet.models.transformer_tts import TransformerTTSInference +from parakeet.models.waveflow import ConditionalWaveFlow +from parakeet.modules.normalizer import ZScore +from parakeet.utils import layer_tools + + +def evaluate(args, acoustic_model_config, vocoder_config): + # dataloader has been too verbose + logging.getLogger("DataLoader").disabled = True + + # construct dataset for evaluation + sentences = [] + with open(args.text, 'rt') as f: + for line in f: + line_list = line.strip().split() + utt_id = line_list[0] + sentence = " ".join(line_list[1:]) + sentences.append((utt_id, sentence)) + + with open(args.phones_dict, "r") as f: + phn_id = [line.strip().split() for line in f.readlines()] + + vocab_size = len(phn_id) + phone_id_map = {} + for phn, id in phn_id: + phone_id_map[phn] = int(id) + print("vocab_size:", vocab_size) + odim = acoustic_model_config.n_mels + model = TransformerTTS( + idim=vocab_size, odim=odim, **acoustic_model_config["model"]) + + model.set_state_dict( + paddle.load(args.transformer_tts_checkpoint)["main_params"]) + model.eval() + + # remove ".pdparams" in waveflow_checkpoint + vocoder_checkpoint_path = args.waveflow_checkpoint[:-9] if args.waveflow_checkpoint.endswith( + ".pdparams") else args.waveflow_checkpoint + vocoder = ConditionalWaveFlow.from_pretrained(vocoder_config, + vocoder_checkpoint_path) + layer_tools.recursively_remove_weight_norm(vocoder) + vocoder.eval() + print("model done!") + + frontend = English() + print("frontend done!") + + stat = np.load(args.transformer_tts_stat) + mu, std = stat + mu = paddle.to_tensor(mu) + std = paddle.to_tensor(std) + transformer_tts_normalizer = ZScore(mu, std) + + transformer_tts_inference = TransformerTTSInference( + transformer_tts_normalizer, model) + + output_dir = Path(args.output_dir) + output_dir.mkdir(parents=True, exist_ok=True) + + for utt_id, sentence in sentences: + phones = frontend.phoneticize(sentence) + # remove start_symbol and end_symbol + phones = phones[1:-1] + phones = [phn for phn in phones if not phn.isspace()] + phones = [phn if phn in phone_id_map else "," for phn in phones] + phone_ids = [phone_id_map[phn] for phn in phones] + with paddle.no_grad(): + mel = transformer_tts_inference(paddle.to_tensor(phone_ids)) + # mel shape is (T, feats) and waveflow's input shape is (batch, feats, T) + mel = mel.unsqueeze(0).transpose([0, 2, 1]) + # wavflow's output shape is (B, T) + wav = vocoder.infer(mel)[0] + + sf.write( + str(output_dir / (utt_id + ".wav")), + wav.numpy(), + samplerate=acoustic_model_config.fs) + print(f"{utt_id} done!") + + +def main(): + # parse args and config and redirect to train_sp + parser = argparse.ArgumentParser( + description="Synthesize with transformer tts & waveflow.") + parser.add_argument( + "--transformer-tts-config", + type=str, + help="transformer tts config file.") + parser.add_argument( + "--transformer-tts-checkpoint", + type=str, + help="transformer tts checkpoint to load.") + parser.add_argument( + "--transformer-tts-stat", + type=str, + help="mean and standard deviation used to normalize spectrogram when training transformer tts." + ) + parser.add_argument( + "--waveflow-config", type=str, help="waveflow config file.") + # not normalize when training waveflow + parser.add_argument( + "--waveflow-checkpoint", type=str, help="waveflow checkpoint to load.") + parser.add_argument( + "--phones-dict", + type=str, + default="phone_id_map.txt", + help="phone vocabulary file.") + parser.add_argument( + "--text", + type=str, + help="text to synthesize, a 'utt_id sentence' pair per line.") + parser.add_argument("--output-dir", type=str, help="output dir.") + parser.add_argument( + "--device", type=str, default="gpu", help="device type to use.") + parser.add_argument("--verbose", type=int, default=1, help="verbose.") + + args = parser.parse_args() + + paddle.set_device(args.device) + + with open(args.transformer_tts_config) as f: + transformer_tts_config = CfgNode(yaml.safe_load(f)) + with open(args.waveflow_config) as f: + waveflow_config = CfgNode(yaml.safe_load(f)) + + print("========Args========") + print(yaml.safe_dump(vars(args))) + print("========Config========") + print(transformer_tts_config) + print(waveflow_config) + + evaluate(args, transformer_tts_config, waveflow_config) + + +if __name__ == "__main__": + main() diff --git a/examples/ljspeech/tts1/local/transformer_tts/ljspeech/synthesize_e2e.sh b/examples/ljspeech/tts1/local/transformer_tts/ljspeech/synthesize_e2e.sh new file mode 100755 index 00000000..4fb69238 --- /dev/null +++ b/examples/ljspeech/tts1/local/transformer_tts/ljspeech/synthesize_e2e.sh @@ -0,0 +1,13 @@ +#!/bin/bash +FLAGS_allocator_strategy=naive_best_fit \ +FLAGS_fraction_of_gpu_memory_to_use=0.01 \ +python3 synthesize_e2e.py \ + --transformer-tts-config=conf/default.yaml \ + --transformer-tts-checkpoint=exp/default/checkpoints/snapshot_iter_201500.pdz \ + --transformer-tts-stat=dump/train/speech_stats.npy \ + --waveflow-config=waveflow_ljspeech_ckpt_0.3/config.yaml \ + --waveflow-checkpoint=waveflow_ljspeech_ckpt_0.3/step-2000000.pdparams \ + --text=../sentences.txt \ + --output-dir=exp/default/test_e2e \ + --device="gpu" \ + --phones-dict=dump/phone_id_map.txt diff --git a/examples/ljspeech/tts1/local/transformer_tts/normalize.py b/examples/ljspeech/tts1/local/transformer_tts/normalize.py new file mode 100644 index 00000000..a666ca2f --- /dev/null +++ b/examples/ljspeech/tts1/local/transformer_tts/normalize.py @@ -0,0 +1,143 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Normalize feature files and dump them.""" + +import argparse +import logging +from operator import itemgetter +from pathlib import Path + +import jsonlines +import numpy as np +from parakeet.datasets.data_table import DataTable +from sklearn.preprocessing import StandardScaler +from tqdm import tqdm + + +def main(): + """Run preprocessing process.""" + parser = argparse.ArgumentParser( + description="Normalize dumped raw features (See detail in parallel_wavegan/bin/normalize.py)." + ) + parser.add_argument( + "--metadata", + type=str, + required=True, + help="directory including feature files to be normalized. " + "you need to specify either *-scp or rootdir.") + + parser.add_argument( + "--dumpdir", + type=str, + required=True, + help="directory to dump normalized feature files.") + parser.add_argument( + "--speech-stats", + type=str, + required=True, + help="speech statistics file.") + parser.add_argument( + "--phones-dict", type=str, default=None, help="phone vocabulary file.") + parser.add_argument( + "--speaker-dict", type=str, default=None, help="speaker id map file.") + parser.add_argument( + "--verbose", + type=int, + default=1, + help="logging level. higher is more logging. (default=1)") + args = parser.parse_args() + + # set logger + if args.verbose > 1: + logging.basicConfig( + level=logging.DEBUG, + format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s" + ) + elif args.verbose > 0: + logging.basicConfig( + level=logging.INFO, + format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s" + ) + else: + logging.basicConfig( + level=logging.WARN, + format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s" + ) + logging.warning('Skip DEBUG/INFO messages') + + # check directory existence + dumpdir = Path(args.dumpdir).resolve() + dumpdir.mkdir(parents=True, exist_ok=True) + + # get dataset + with jsonlines.open(args.metadata, 'r') as reader: + metadata = list(reader) + dataset = DataTable( + metadata, converters={ + "speech": np.load, + }) + logging.info(f"The number of files = {len(dataset)}.") + + # restore scaler + speech_scaler = StandardScaler() + speech_scaler.mean_ = np.load(args.speech_stats)[0] + speech_scaler.scale_ = np.load(args.speech_stats)[1] + speech_scaler.n_features_in_ = speech_scaler.mean_.shape[0] + + vocab_phones = {} + with open(args.phones_dict, 'rt') as f: + phn_id = [line.strip().split() for line in f.readlines()] + for phn, id in phn_id: + vocab_phones[phn] = int(id) + + vocab_speaker = {} + with open(args.speaker_dict, 'rt') as f: + spk_id = [line.strip().split() for line in f.readlines()] + for spk, id in spk_id: + vocab_speaker[spk] = int(id) + + # process each file + output_metadata = [] + + for item in tqdm(dataset): + utt_id = item['utt_id'] + speech = item['speech'] + # normalize + speech = speech_scaler.transform(speech) + speech_dir = dumpdir / "data_speech" + speech_dir.mkdir(parents=True, exist_ok=True) + speech_path = speech_dir / f"{utt_id}_speech.npy" + np.save(speech_path, speech.astype(np.float32), allow_pickle=False) + + phone_ids = [vocab_phones[p] for p in item['phones']] + spk_id = vocab_speaker[item["speaker"]] + record = { + "utt_id": item['utt_id'], + "spk_id": spk_id, + "text": phone_ids, + "text_lengths": item['text_lengths'], + "speech_lengths": item['speech_lengths'], + "speech": str(speech_path), + } + output_metadata.append(record) + output_metadata.sort(key=itemgetter('utt_id')) + output_metadata_path = Path(args.dumpdir) / "metadata.jsonl" + with jsonlines.open(output_metadata_path, 'w') as writer: + for item in output_metadata: + writer.write(item) + logging.info(f"metadata dumped into {output_metadata_path}") + + +if __name__ == "__main__": + main() diff --git a/examples/ljspeech/tts1/local/transformer_tts/preprocess.py b/examples/ljspeech/tts1/local/transformer_tts/preprocess.py new file mode 100644 index 00000000..0f998bc3 --- /dev/null +++ b/examples/ljspeech/tts1/local/transformer_tts/preprocess.py @@ -0,0 +1,281 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +from concurrent.futures import ThreadPoolExecutor +from operator import itemgetter +from pathlib import Path +from typing import Any +from typing import Dict +from typing import List + +import jsonlines +import librosa +import numpy as np +import tqdm +import yaml +from parakeet.data.get_feats import LogMelFBank +from parakeet.frontend import English +from yacs.config import CfgNode as Configuration + + +def get_lj_sentences(file_name, frontend): + ''' + read MFA duration.txt + Parameters + ---------- + file_name : str or Path + Returns + ---------- + Dict + sentence: {'utt': ([char], [int])} + ''' + f = open(file_name, 'r') + sentence = {} + speaker_set = set() + for line in f: + line_list = line.strip().split('|') + utt = line_list[0] + speaker = utt.split("-")[0][:2] + speaker_set.add(speaker) + raw_text = line_list[-1] + phonemes = frontend.phoneticize(raw_text) + phonemes = phonemes[1:-1] + phonemes = [phn for phn in phonemes if not phn.isspace()] + sentence[utt] = (phonemes, speaker) + f.close() + return sentence, speaker_set + + +def get_input_token(sentence, output_path): + ''' + get phone set from training data and save it + Parameters + ---------- + sentence : Dict + sentence: {'utt': ([char], str)} + output_path : str or path + path to save phone_id_map + ''' + phn_token = set() + for utt in sentence: + for phn in sentence[utt][0]: + if phn != "": + phn_token.add(phn) + phn_token = list(phn_token) + phn_token.sort() + phn_token = ["", ""] + phn_token + phn_token += [""] + + with open(output_path, 'w') as f: + for i, phn in enumerate(phn_token): + f.write(phn + ' ' + str(i) + '\n') + + +def get_spk_id_map(speaker_set, output_path): + speakers = sorted(list(speaker_set)) + with open(output_path, 'w') as f: + for i, spk in enumerate(speakers): + f.write(spk + ' ' + str(i) + '\n') + + +def process_sentence(config: Dict[str, Any], + fp: Path, + sentences: Dict, + output_dir: Path, + mel_extractor=None): + utt_id = fp.stem + record = None + if utt_id in sentences: + # reading, resampling may occur + wav, _ = librosa.load(str(fp), sr=config.fs) + if len(wav.shape) != 1 or np.abs(wav).max() > 1.0: + return record + assert len(wav.shape) == 1, f"{utt_id} is not a mono-channel audio." + assert np.abs(wav).max( + ) <= 1.0, f"{utt_id} is seems to be different that 16 bit PCM." + phones = sentences[utt_id][0] + speaker = sentences[utt_id][1] + logmel = mel_extractor.get_log_mel_fbank(wav, base='e') + # change duration according to mel_length + num_frames = logmel.shape[0] + mel_dir = output_dir / "data_speech" + mel_dir.mkdir(parents=True, exist_ok=True) + mel_path = mel_dir / (utt_id + "_speech.npy") + np.save(mel_path, logmel) + record = { + "utt_id": utt_id, + "phones": phones, + "text_lengths": len(phones), + "speech_lengths": num_frames, + "speech": str(mel_path), + "speaker": speaker + } + return record + + +def process_sentences(config, + fps: List[Path], + sentences: Dict, + output_dir: Path, + mel_extractor=None, + nprocs: int=1): + if nprocs == 1: + results = [] + for fp in tqdm.tqdm(fps, total=len(fps)): + record = process_sentence(config, fp, sentences, output_dir, + mel_extractor) + if record: + results.append(record) + else: + with ThreadPoolExecutor(nprocs) as pool: + futures = [] + with tqdm.tqdm(total=len(fps)) as progress: + for fp in fps: + future = pool.submit(process_sentence, config, fp, + sentences, output_dir, mel_extractor) + future.add_done_callback(lambda p: progress.update()) + futures.append(future) + + results = [] + for ft in futures: + record = ft.result() + if record: + results.append(record) + + results.sort(key=itemgetter("utt_id")) + with jsonlines.open(output_dir / "metadata.jsonl", 'w') as writer: + for item in results: + writer.write(item) + print("Done") + + +def main(): + # parse config and args + parser = argparse.ArgumentParser( + description="Preprocess audio and then extract features.") + + parser.add_argument( + "--dataset", + default="ljspeech", + type=str, + help="name of dataset, should in {ljspeech} now") + + parser.add_argument( + "--rootdir", default=None, type=str, help="directory to dataset.") + + parser.add_argument( + "--dumpdir", + type=str, + required=True, + help="directory to dump feature files.") + + parser.add_argument( + "--config-path", + default="conf/default.yaml", + type=str, + help="yaml format configuration file.") + + parser.add_argument( + "--verbose", + type=int, + default=1, + help="logging level. higher is more logging. (default=1)") + parser.add_argument( + "--num-cpu", type=int, default=1, help="number of process.") + + args = parser.parse_args() + + config_path = Path(args.config_path).resolve() + root_dir = Path(args.rootdir).expanduser() + dumpdir = Path(args.dumpdir).expanduser() + # use absolute path + dumpdir = dumpdir.resolve() + dumpdir.mkdir(parents=True, exist_ok=True) + + assert root_dir.is_dir() + + with open(config_path, 'rt') as f: + _C = yaml.safe_load(f) + _C = Configuration(_C) + config = _C.clone() + + if args.verbose > 1: + print(vars(args)) + print(config) + + phone_id_map_path = dumpdir / "phone_id_map.txt" + speaker_id_map_path = dumpdir / "speaker_id_map.txt" + + if args.dataset == "ljspeech": + wav_files = sorted(list((root_dir / "wavs").rglob("*.wav"))) + frontend = English() + sentences, speaker_set = get_lj_sentences(root_dir / "metadata.csv", + frontend) + get_input_token(sentences, phone_id_map_path) + get_spk_id_map(speaker_set, speaker_id_map_path) + # split data into 3 sections + num_train = 12900 + num_dev = 100 + train_wav_files = wav_files[:num_train] + dev_wav_files = wav_files[num_train:num_train + num_dev] + test_wav_files = wav_files[num_train + num_dev:] + + train_dump_dir = dumpdir / "train" / "raw" + train_dump_dir.mkdir(parents=True, exist_ok=True) + dev_dump_dir = dumpdir / "dev" / "raw" + dev_dump_dir.mkdir(parents=True, exist_ok=True) + test_dump_dir = dumpdir / "test" / "raw" + test_dump_dir.mkdir(parents=True, exist_ok=True) + + # Extractor + mel_extractor = LogMelFBank( + sr=config.fs, + n_fft=config.n_fft, + hop_length=config.n_shift, + win_length=config.win_length, + window=config.window, + n_mels=config.n_mels, + fmin=config.fmin, + fmax=config.fmax) + + # process for the 3 sections + if train_wav_files: + process_sentences( + config, + train_wav_files, + sentences, + train_dump_dir, + mel_extractor, + nprocs=args.num_cpu) + if dev_wav_files: + process_sentences( + config, + dev_wav_files, + sentences, + dev_dump_dir, + mel_extractor, + nprocs=args.num_cpu) + if test_wav_files: + process_sentences( + config, + test_wav_files, + sentences, + test_dump_dir, + mel_extractor, + nprocs=args.num_cpu) + + +if __name__ == "__main__": + main() diff --git a/examples/ljspeech/tts1/local/transformer_tts/sentences.txt b/examples/ljspeech/tts1/local/transformer_tts/sentences.txt new file mode 100644 index 00000000..36b73a52 --- /dev/null +++ b/examples/ljspeech/tts1/local/transformer_tts/sentences.txt @@ -0,0 +1,9 @@ +001 Life was like a box of chocolates, you never know what you're gonna get. +002 With great power there must come great responsibility. +003 To be or not to be, that’s a question. +004 A man can be destroyed but not defeated +005 Do not, for one repulse, give up the purpose that you resolved to effort. +006 Death is just a part of life, something we're all destined to do. +007 I think it's hard winning a war with words. +008 Don’t argue with the people of strong determination, because they may change the fact! +009 Love you three thousand times. \ No newline at end of file diff --git a/examples/ljspeech/tts1/local/transformer_tts/synthesize.py b/examples/ljspeech/tts1/local/transformer_tts/synthesize.py new file mode 100644 index 00000000..21614c53 --- /dev/null +++ b/examples/ljspeech/tts1/local/transformer_tts/synthesize.py @@ -0,0 +1,142 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +import logging +from pathlib import Path + +import jsonlines +import numpy as np +import paddle +import soundfile as sf +import yaml +from yacs.config import CfgNode +from parakeet.datasets.data_table import DataTable +from parakeet.models.transformer_tts import TransformerTTS +from parakeet.models.transformer_tts import TransformerTTSInference +from parakeet.models.waveflow import ConditionalWaveFlow +from parakeet.modules.normalizer import ZScore +from parakeet.utils import layer_tools + + +def evaluate(args, acoustic_model_config, vocoder_config): + # dataloader has been too verbose + logging.getLogger("DataLoader").disabled = True + + # construct dataset for evaluation + with jsonlines.open(args.test_metadata, 'r') as reader: + test_metadata = list(reader) + test_dataset = DataTable(data=test_metadata, fields=["utt_id", "text"]) + + with open(args.phones_dict, "r") as f: + phn_id = [line.strip().split() for line in f.readlines()] + vocab_size = len(phn_id) + print("vocab_size:", vocab_size) + odim = acoustic_model_config.n_mels + model = TransformerTTS( + idim=vocab_size, odim=odim, **acoustic_model_config["model"]) + + model.set_state_dict( + paddle.load(args.transformer_tts_checkpoint)["main_params"]) + model.eval() + # remove ".pdparams" in waveflow_checkpoint + vocoder_checkpoint_path = args.waveflow_checkpoint[:-9] if args.waveflow_checkpoint.endswith( + ".pdparams") else args.waveflow_checkpoint + vocoder = ConditionalWaveFlow.from_pretrained(vocoder_config, + vocoder_checkpoint_path) + layer_tools.recursively_remove_weight_norm(vocoder) + vocoder.eval() + print("model done!") + + stat = np.load(args.transformer_tts_stat) + mu, std = stat + mu = paddle.to_tensor(mu) + std = paddle.to_tensor(std) + transformer_tts_normalizer = ZScore(mu, std) + + transformer_tts_inference = TransformerTTSInference( + transformer_tts_normalizer, model) + + output_dir = Path(args.output_dir) + output_dir.mkdir(parents=True, exist_ok=True) + + for datum in test_dataset: + utt_id = datum["utt_id"] + text = paddle.to_tensor(datum["text"]) + + with paddle.no_grad(): + mel = transformer_tts_inference(text) + # mel shape is (T, feats) and waveflow's input shape is (batch, feats, T) + mel = mel.unsqueeze(0).transpose([0, 2, 1]) + # wavflow's output shape is (B, T) + wav = vocoder.infer(mel)[0] + + sf.write( + str(output_dir / (utt_id + ".wav")), + wav.numpy(), + samplerate=acoustic_model_config.fs) + print(f"{utt_id} done!") + + +def main(): + # parse args and config and redirect to train_sp + parser = argparse.ArgumentParser( + description="Synthesize with transformer tts & waveflow.") + parser.add_argument( + "--transformer-tts-config", + type=str, + help="transformer tts config file.") + parser.add_argument( + "--transformer-tts-checkpoint", + type=str, + help="transformer tts checkpoint to load.") + parser.add_argument( + "--transformer-tts-stat", + type=str, + help="mean and standard deviation used to normalize spectrogram when training transformer tts." + ) + parser.add_argument( + "--waveflow-config", type=str, help="waveflow config file.") + # not normalize when training waveflow + parser.add_argument( + "--waveflow-checkpoint", type=str, help="waveflow checkpoint to load.") + parser.add_argument( + "--phones-dict", type=str, default=None, help="phone vocabulary file.") + + parser.add_argument("--test-metadata", type=str, help="test metadata.") + parser.add_argument("--output-dir", type=str, help="output dir.") + parser.add_argument( + "--device", type=str, default="gpu", help="device type to use.") + parser.add_argument("--verbose", type=int, default=1, help="verbose.") + + args = parser.parse_args() + + paddle.set_device(args.device) + + with open(args.transformer_tts_config) as f: + transformer_tts_config = CfgNode(yaml.safe_load(f)) + with open(args.waveflow_config) as f: + waveflow_config = CfgNode(yaml.safe_load(f)) + + print("========Args========") + print(yaml.safe_dump(vars(args))) + print("========Config========") + print(transformer_tts_config) + print(waveflow_config) + + evaluate(args, transformer_tts_config, waveflow_config) + + +if __name__ == "__main__": + main() diff --git a/examples/ljspeech/tts1/local/transformer_tts/train.py b/examples/ljspeech/tts1/local/transformer_tts/train.py new file mode 100644 index 00000000..b1263bcc --- /dev/null +++ b/examples/ljspeech/tts1/local/transformer_tts/train.py @@ -0,0 +1,199 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +import os +import logging +import shutil +from pathlib import Path + +import jsonlines +import numpy as np +import paddle +import yaml +from paddle import DataParallel +from paddle import distributed as dist +from paddle.io import DataLoader +from paddle.io import DistributedBatchSampler +from parakeet.datasets.data_table import DataTable +from parakeet.datasets.am_batch_fn import transformer_single_spk_batch_fn +from parakeet.models.transformer_tts import TransformerTTS +from parakeet.models.transformer_tts import TransformerTTSUpdater +from parakeet.models.transformer_tts import TransformerTTSEvaluator +from parakeet.training.extensions.snapshot import Snapshot +from parakeet.training.extensions.visualizer import VisualDL +from parakeet.training.optimizer import build_optimizers +from parakeet.training.seeding import seed_everything +from parakeet.training.trainer import Trainer +from visualdl import LogWriter +from yacs.config import CfgNode + + +def train_sp(args, config): + # decides device type and whether to run in parallel + # setup running environment correctly + if not paddle.is_compiled_with_cuda(): + paddle.set_device("cpu") + else: + paddle.set_device("gpu") + world_size = paddle.distributed.get_world_size() + if world_size > 1: + paddle.distributed.init_parallel_env() + + # set the random seed, it is a must for multiprocess training + seed_everything(config.seed) + + print( + f"rank: {dist.get_rank()}, pid: {os.getpid()}, parent_pid: {os.getppid()}", + ) + + # dataloader has been too verbose + logging.getLogger("DataLoader").disabled = True + + # construct dataset for training and validation + with jsonlines.open(args.train_metadata, 'r') as reader: + train_metadata = list(reader) + train_dataset = DataTable( + data=train_metadata, + fields=[ + "text", + "text_lengths", + "speech", + "speech_lengths", + ], + converters={ + "speech": np.load, + }, ) + with jsonlines.open(args.dev_metadata, 'r') as reader: + dev_metadata = list(reader) + dev_dataset = DataTable( + data=dev_metadata, + fields=[ + "text", + "text_lengths", + "speech", + "speech_lengths", + ], + converters={ + "speech": np.load, + }, ) + + # collate function and dataloader + train_sampler = DistributedBatchSampler( + train_dataset, + batch_size=config.batch_size, + shuffle=True, + drop_last=True) + + print("samplers done!") + + train_dataloader = DataLoader( + train_dataset, + batch_sampler=train_sampler, + collate_fn=transformer_single_spk_batch_fn, + num_workers=config.num_workers) + + dev_dataloader = DataLoader( + dev_dataset, + shuffle=False, + drop_last=False, + batch_size=config.batch_size, + collate_fn=transformer_single_spk_batch_fn, + num_workers=config.num_workers) + print("dataloaders done!") + + with open(args.phones_dict, "r") as f: + phn_id = [line.strip().split() for line in f.readlines()] + vocab_size = len(phn_id) + print("vocab_size:", vocab_size) + + odim = config.n_mels + model = TransformerTTS(idim=vocab_size, odim=odim, **config["model"]) + if world_size > 1: + model = DataParallel(model) + print("model done!") + + optimizer = build_optimizers(model, **config["optimizer"]) + print("optimizer done!") + + output_dir = Path(args.output_dir) + output_dir.mkdir(parents=True, exist_ok=True) + if dist.get_rank() == 0: + config_name = args.config.split("/")[-1] + # copy conf to output_dir + shutil.copyfile(args.config, output_dir / config_name) + + updater = TransformerTTSUpdater( + model=model, + optimizer=optimizer, + dataloader=train_dataloader, + output_dir=output_dir, + **config["updater"]) + + trainer = Trainer(updater, (config.max_epoch, 'epoch'), output_dir) + + evaluator = TransformerTTSEvaluator( + model, dev_dataloader, output_dir=output_dir, **config["updater"]) + + if dist.get_rank() == 0: + trainer.extend(evaluator, trigger=(1, "epoch")) + writer = LogWriter(str(output_dir)) + trainer.extend(VisualDL(writer), trigger=(1, "iteration")) + trainer.extend( + Snapshot(max_size=config.num_snapshots), trigger=(1, 'epoch')) + # print(trainer.extensions) + trainer.run() + + +def main(): + # parse args and config and redirect to train_sp + parser = argparse.ArgumentParser(description="Train a TransformerTTS " + "model with LJSpeech TTS dataset.") + parser.add_argument( + "--config", type=str, help="config file to overwrite default config.") + parser.add_argument("--train-metadata", type=str, help="training data.") + parser.add_argument("--dev-metadata", type=str, help="dev data.") + parser.add_argument("--output-dir", type=str, help="output dir.") + parser.add_argument( + "--device", type=str, default="gpu", help="device type to use.") + parser.add_argument( + "--nprocs", type=int, default=1, help="number of processes.") + parser.add_argument("--verbose", type=int, default=1, help="verbose.") + parser.add_argument( + "--phones-dict", type=str, default=None, help="phone vocabulary file.") + + args = parser.parse_args() + if args.device == "cpu" and args.nprocs > 1: + raise RuntimeError("Multiprocess training on CPU is not supported.") + + with open(args.config) as f: + config = CfgNode(yaml.safe_load(f)) + + print("========Args========") + print(yaml.safe_dump(vars(args))) + print("========Config========") + print(config) + print( + f"master see the word size: {dist.get_world_size()}, from pid: {os.getpid()}" + ) + + # dispatch + if args.nprocs > 1: + dist.spawn(train_sp, (args, config), nprocs=args.nprocs) + else: + train_sp(args, config) + + +if __name__ == "__main__": + main() diff --git a/examples/ljspeech/tts1/run.sh b/examples/ljspeech/tts1/run.sh new file mode 100644 index 00000000..e69de29b diff --git a/examples/ljspeech/voc0/local/waveflow/README.md b/examples/ljspeech/voc0/local/waveflow/README.md new file mode 100644 index 00000000..b3be1e4a --- /dev/null +++ b/examples/ljspeech/voc0/local/waveflow/README.md @@ -0,0 +1,52 @@ +# WaveFlow with LJSpeech + +## Dataset + +### Download the datasaet. + +```bash +wget https://data.keithito.com/data/speech/LJSpeech-1.1.tar.bz2 +``` + +### Extract the dataset. + +```bash +tar xjvf LJSpeech-1.1.tar.bz2 +``` + +### Preprocess the dataset. + +Assume the path to save the preprocessed dataset is `ljspeech_waveflow`. Run the command below to preprocess the dataset. + +```bash +python preprocess.py --input=LJSpeech-1.1/ --output=ljspeech_waveflow +``` + +## Train the model + +The training script requires 4 command line arguments. +`--data` is the path of the training dataset, `--output` is the path of the output directory (we recommend to use a subdirectory in `runs` to manage different experiments.) + +`--device` should be "cpu" or "gpu", `--nprocs` is the number of processes to train the model in parallel. + +```bash +python train.py --data=ljspeech_waveflow/ --output=runs/test --device="gpu" --nprocs=1 +``` + +If you want distributed training, set a larger `--nprocs` (e.g. 4). Note that distributed training with cpu is not supported yet. + +## Synthesize + +Synthesize waveform. We assume the `--input` is a directory containing several mel spectrograms(log magnitude) in `.npy` format. The output would be saved in `--output` directory, containing several `.wav` files, each with the same name as the mel spectrogram does. + +`--checkpoint_path` should be the path of the parameter file (`.pdparams`) to load. Note that the extention name `.pdparmas` is not included here. + +`--device` specifies to device to run synthesis on. + +```bash +python synthesize.py --input=mels/ --output=wavs/ --checkpoint_path='step-2000000' --device="gpu" --verbose +``` + +## Pretrained Model + +Pretrained Model with residual channel equals 128 can be downloaded here. [waveflow_ljspeech_ckpt_0.3.zip](https://paddlespeech.bj.bcebos.com/Parakeet/waveflow_ljspeech_ckpt_0.3.zip). diff --git a/examples/ljspeech/voc0/local/waveflow/config.py b/examples/ljspeech/voc0/local/waveflow/config.py new file mode 100644 index 00000000..d009a2c8 --- /dev/null +++ b/examples/ljspeech/voc0/local/waveflow/config.py @@ -0,0 +1,56 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from yacs.config import CfgNode as CN + +_C = CN() +_C.data = CN( + dict( + batch_size=8, # batch size + valid_size=16, # the first N examples are reserved for validation + sample_rate=22050, # Hz, sample rate + n_fft=1024, # fft frame size + win_length=1024, # window size + hop_length=256, # hop size between ajacent frame + fmin=0, + fmax=8000, # Hz, max frequency when converting to mel + n_mels=80, # mel bands + clip_frames=65, # mel clip frames + )) + +_C.model = CN( + dict( + upsample_factors=[16, 16], + n_flows=8, # number of flows in WaveFlow + n_layers=8, # number of conv block in each flow + n_group=16, # folding factor of audio and spectrogram + channels=128, # resiaudal channel in each flow + kernel_size=[3, 3], # kernel size in each conv block + sigma=1.0, # stddev of the random noise + )) + +_C.training = CN( + dict( + lr=2e-4, # learning rates + valid_interval=1000, # validation + save_interval=10000, # checkpoint + max_iteration=3000000, # max iteration to train + )) + + +def get_cfg_defaults(): + """Get a yacs CfgNode object with default values for my_project.""" + # Return a clone so that the defaults will not be altered + # This is for the "local variable" use pattern + return _C.clone() diff --git a/examples/ljspeech/voc0/local/waveflow/ljspeech.py b/examples/ljspeech/voc0/local/waveflow/ljspeech.py new file mode 100644 index 00000000..afeba391 --- /dev/null +++ b/examples/ljspeech/voc0/local/waveflow/ljspeech.py @@ -0,0 +1,89 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from pathlib import Path + +import numpy as np +import pandas +from paddle.io import Dataset + +from parakeet.data.batch import batch_spec, batch_wav + + +class LJSpeech(Dataset): + """A simple dataset adaptor for the processed ljspeech dataset.""" + + def __init__(self, root): + self.root = Path(root).expanduser() + meta_data = pandas.read_csv( + str(self.root / "metadata.csv"), + sep="\t", + header=None, + names=["fname", "frames", "samples"]) + + records = [] + for row in meta_data.itertuples(): + mel_path = str(self.root / "mel" / (row.fname + ".npy")) + wav_path = str(self.root / "wav" / (row.fname + ".npy")) + records.append((mel_path, wav_path)) + self.records = records + + def __getitem__(self, i): + mel_name, wav_name = self.records[i] + mel = np.load(mel_name) + wav = np.load(wav_name) + return mel, wav + + def __len__(self): + return len(self.records) + + +class LJSpeechCollector(object): + """A simple callable to batch LJSpeech examples.""" + + def __init__(self, padding_value=0.): + self.padding_value = padding_value + + def __call__(self, examples): + mels = [example[0] for example in examples] + wavs = [example[1] for example in examples] + mels, _ = batch_spec(mels, pad_value=self.padding_value) + wavs, _ = batch_wav(wavs, pad_value=self.padding_value) + return mels, wavs + + +class LJSpeechClipCollector(object): + def __init__(self, clip_frames=65, hop_length=256): + self.clip_frames = clip_frames + self.hop_length = hop_length + + def __call__(self, examples): + mels = [] + wavs = [] + for example in examples: + mel_clip, wav_clip = self.clip(example) + mels.append(mel_clip) + wavs.append(wav_clip) + mels = np.stack(mels) + wavs = np.stack(wavs) + return mels, wavs + + def clip(self, example): + mel, wav = example + frames = mel.shape[-1] + start = np.random.randint(0, frames - self.clip_frames) + mel_clip = mel[:, start:start + self.clip_frames] + wav_clip = wav[start * self.hop_length:(start + self.clip_frames) * + self.hop_length] + return mel_clip, wav_clip diff --git a/examples/ljspeech/voc0/local/waveflow/preprocess.py b/examples/ljspeech/voc0/local/waveflow/preprocess.py new file mode 100644 index 00000000..199081c0 --- /dev/null +++ b/examples/ljspeech/voc0/local/waveflow/preprocess.py @@ -0,0 +1,162 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import os +import argparse +from pathlib import Path + +import tqdm +import numpy as np +import librosa +import pandas as pd + +from parakeet.datasets import LJSpeechMetaData +from parakeet.audio import LogMagnitude + +from config import get_cfg_defaults + + +class Transform(object): + def __init__(self, sample_rate, n_fft, win_length, hop_length, n_mels, fmin, + fmax): + self.sample_rate = sample_rate + self.n_fft = n_fft + self.win_length = win_length + self.hop_length = hop_length + self.n_mels = n_mels + self.fmin = fmin + self.fmax = fmax + + self.spec_normalizer = LogMagnitude(min=1e-5) + + def __call__(self, example): + wav_path, _, _ = example + + sr = self.sample_rate + n_fft = self.n_fft + win_length = self.win_length + hop_length = self.hop_length + n_mels = self.n_mels + fmin = self.fmin + fmax = self.fmax + + wav, loaded_sr = librosa.load(wav_path, sr=None) + assert loaded_sr == sr, "sample rate does not match, resampling applied" + + # Pad audio to the right size. + frames = int(np.ceil(float(wav.size) / hop_length)) + fft_padding = (n_fft - hop_length) // 2 # sound + desired_length = frames * hop_length + fft_padding * 2 + pad_amount = (desired_length - wav.size) // 2 + + if wav.size % 2 == 0: + wav = np.pad(wav, (pad_amount, pad_amount), mode='reflect') + else: + wav = np.pad(wav, (pad_amount, pad_amount + 1), mode='reflect') + + # Normalize audio. + wav = wav / np.abs(wav).max() * 0.999 + + # Compute mel-spectrogram. + # Turn center to False to prevent internal padding. + spectrogram = librosa.core.stft( + wav, + hop_length=hop_length, + win_length=win_length, + n_fft=n_fft, + center=False) + spectrogram_magnitude = np.abs(spectrogram) + + # Compute mel-spectrograms. + mel_filter_bank = librosa.filters.mel( + sr=sr, n_fft=n_fft, n_mels=n_mels, fmin=fmin, fmax=fmax) + mel_spectrogram = np.dot(mel_filter_bank, spectrogram_magnitude) + + # log scale mel_spectrogram. + mel_spectrogram = self.spec_normalizer.transform(mel_spectrogram) + + # Extract the center of audio that corresponds to mel spectrograms. + audio = wav[fft_padding:-fft_padding] + assert mel_spectrogram.shape[1] * hop_length == audio.size + + # there is no clipping here + return audio, mel_spectrogram + + +def create_dataset(config, input_dir, output_dir): + input_dir = Path(input_dir).expanduser() + dataset = LJSpeechMetaData(input_dir) + + output_dir = Path(output_dir).expanduser() + output_dir.mkdir(exist_ok=True) + + transform = Transform(config.sample_rate, config.n_fft, config.win_length, + config.hop_length, config.n_mels, config.fmin, + config.fmax) + file_names = [] + + for example in tqdm.tqdm(dataset): + fname, _, _ = example + base_name = os.path.splitext(os.path.basename(fname))[0] + wav_dir = output_dir / "wav" + mel_dir = output_dir / "mel" + wav_dir.mkdir(exist_ok=True) + mel_dir.mkdir(exist_ok=True) + + audio, mel = transform(example) + np.save(str(wav_dir / base_name), audio) + np.save(str(mel_dir / base_name), mel) + + file_names.append((base_name, mel.shape[-1], audio.shape[-1])) + + meta_data = pd.DataFrame.from_records(file_names) + meta_data.to_csv( + str(output_dir / "metadata.csv"), sep="\t", index=None, header=None) + print("saved meta data in to {}".format( + os.path.join(output_dir, "metadata.csv"))) + + print("Done!") + + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="create dataset") + parser.add_argument( + "--config", + type=str, + metavar="FILE", + help="extra config to overwrite the default config") + parser.add_argument( + "--input", type=str, help="path of the ljspeech dataset") + parser.add_argument( + "--output", type=str, help="path to save output dataset") + parser.add_argument( + "--opts", + nargs=argparse.REMAINDER, + help="options to overwrite --config file and the default config, passing in KEY VALUE pairs" + ) + parser.add_argument( + "-v", "--verbose", action="store_true", help="print msg") + + config = get_cfg_defaults() + args = parser.parse_args() + if args.config: + config.merge_from_file(args.config) + if args.opts: + config.merge_from_list(args.opts) + config.freeze() + if args.verbose: + print(config.data) + print(args) + + create_dataset(config.data, args.input, args.output) diff --git a/examples/ljspeech/voc0/local/waveflow/synthesize.py b/examples/ljspeech/voc0/local/waveflow/synthesize.py new file mode 100644 index 00000000..e25cec3e --- /dev/null +++ b/examples/ljspeech/voc0/local/waveflow/synthesize.py @@ -0,0 +1,83 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import os +import argparse +from pathlib import Path + +import numpy as np +import soundfile as sf +import paddle + +from parakeet.models.waveflow import ConditionalWaveFlow +from parakeet.utils import layer_tools + +from config import get_cfg_defaults + + +def main(config, args): + paddle.set_device(args.device) + model = ConditionalWaveFlow.from_pretrained(config, args.checkpoint_path) + layer_tools.recursively_remove_weight_norm(model) + model.eval() + + mel_dir = Path(args.input).expanduser() + output_dir = Path(args.output).expanduser() + output_dir.mkdir(parents=True, exist_ok=True) + for file_path in mel_dir.glob("*.npy"): + mel = np.load(str(file_path)) + with paddle.amp.auto_cast(): + audio = model.predict(mel) + audio_path = output_dir / (os.path.splitext(file_path.name)[0] + ".wav") + sf.write(audio_path, audio, config.data.sample_rate) + print("[synthesize] {} -> {}".format(file_path, audio_path)) + + +if __name__ == "__main__": + config = get_cfg_defaults() + + parser = argparse.ArgumentParser( + description="generate mel spectrogram with TransformerTTS.") + parser.add_argument( + "--config", + type=str, + metavar="FILE", + help="extra config to overwrite the default config") + parser.add_argument( + "--checkpoint_path", type=str, help="path of the checkpoint to load.") + parser.add_argument( + "--input", + type=str, + help="path of directory containing mel spectrogram (in .npy format)") + parser.add_argument("--output", type=str, help="path to save outputs") + parser.add_argument( + "--device", type=str, default="cpu", help="device type to use.") + parser.add_argument( + "--opts", + nargs=argparse.REMAINDER, + help="options to overwrite --config file and the default config, passing in KEY VALUE pairs" + ) + parser.add_argument( + "-v", "--verbose", action="store_true", help="print msg") + + args = parser.parse_args() + if args.config: + config.merge_from_file(args.config) + if args.opts: + config.merge_from_list(args.opts) + config.freeze() + print(config) + print(args) + + main(config, args) diff --git a/examples/ljspeech/voc0/local/waveflow/train.py b/examples/ljspeech/voc0/local/waveflow/train.py new file mode 100644 index 00000000..359670fa --- /dev/null +++ b/examples/ljspeech/voc0/local/waveflow/train.py @@ -0,0 +1,158 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import time + +import numpy as np +import paddle +from paddle import distributed as dist +from paddle.io import DataLoader, DistributedBatchSampler + +from parakeet.data import dataset +from parakeet.models.waveflow import ConditionalWaveFlow, WaveFlowLoss +from parakeet.utils import mp_tools +from parakeet.training.cli import default_argument_parser +from parakeet.training.experiment import ExperimentBase + +from config import get_cfg_defaults +from ljspeech import LJSpeech, LJSpeechClipCollector, LJSpeechCollector + + +class Experiment(ExperimentBase): + def setup_model(self): + config = self.config + model = ConditionalWaveFlow( + upsample_factors=config.model.upsample_factors, + n_flows=config.model.n_flows, + n_layers=config.model.n_layers, + n_group=config.model.n_group, + channels=config.model.channels, + n_mels=config.data.n_mels, + kernel_size=config.model.kernel_size) + + if self.parallel: + model = paddle.DataParallel(model) + optimizer = paddle.optimizer.Adam( + config.training.lr, parameters=model.parameters()) + criterion = WaveFlowLoss(sigma=config.model.sigma) + + self.model = model + self.optimizer = optimizer + self.criterion = criterion + + def setup_dataloader(self): + config = self.config + args = self.args + + ljspeech_dataset = LJSpeech(args.data) + valid_set, train_set = dataset.split(ljspeech_dataset, + config.data.valid_size) + + batch_fn = LJSpeechClipCollector(config.data.clip_frames, + config.data.hop_length) + + if not self.parallel: + train_loader = DataLoader( + train_set, + batch_size=config.data.batch_size, + shuffle=True, + drop_last=True, + collate_fn=batch_fn) + else: + sampler = DistributedBatchSampler( + train_set, + batch_size=config.data.batch_size, + num_replicas=dist.get_world_size(), + rank=dist.get_rank(), + shuffle=True, + drop_last=True) + train_loader = DataLoader( + train_set, batch_sampler=sampler, collate_fn=batch_fn) + + valid_batch_fn = LJSpeechCollector() + valid_loader = DataLoader( + valid_set, batch_size=1, collate_fn=valid_batch_fn) + + self.train_loader = train_loader + self.valid_loader = valid_loader + + def compute_outputs(self, mel, wav): + # model_core = model._layers if isinstance(model, paddle.DataParallel) else model + z, log_det_jocobian = self.model(wav, mel) + return z, log_det_jocobian + + def train_batch(self): + start = time.time() + batch = self.read_batch() + data_loader_time = time.time() - start + + self.model.train() + self.optimizer.clear_grad() + mel, wav = batch + z, log_det_jocobian = self.compute_outputs(mel, wav) + loss = self.criterion(z, log_det_jocobian) + loss.backward() + self.optimizer.step() + iteration_time = time.time() - start + + loss_value = float(loss) + msg = "Rank: {}, ".format(dist.get_rank()) + msg += "step: {}, ".format(self.iteration) + msg += "time: {:>.3f}s/{:>.3f}s, ".format(data_loader_time, + iteration_time) + msg += "loss: {:>.6f}".format(loss_value) + self.logger.info(msg) + if dist.get_rank() == 0: + self.visualizer.add_scalar("train/loss", loss_value, self.iteration) + + @mp_tools.rank_zero_only + @paddle.no_grad() + def valid(self): + valid_iterator = iter(self.valid_loader) + valid_losses = [] + mel, wav = next(valid_iterator) + z, log_det_jocobian = self.compute_outputs(mel, wav) + loss = self.criterion(z, log_det_jocobian) + valid_losses.append(float(loss)) + valid_loss = np.mean(valid_losses) + self.visualizer.add_scalar("valid/loss", valid_loss, self.iteration) + + +def main_sp(config, args): + exp = Experiment(config, args) + exp.setup() + exp.resume_or_load() + exp.run() + + +def main(config, args): + if args.nprocs > 1 and args.device == "gpu": + dist.spawn(main_sp, args=(config, args), nprocs=args.nprocs) + else: + main_sp(config, args) + + +if __name__ == "__main__": + config = get_cfg_defaults() + parser = default_argument_parser() + args = parser.parse_args() + if args.config: + config.merge_from_file(args.config) + if args.opts: + config.merge_from_list(args.opts) + config.freeze() + print(config) + print(args) + + main(config, args) diff --git a/examples/ljspeech/voc0/run.sh b/examples/ljspeech/voc0/run.sh new file mode 100644 index 00000000..e69de29b diff --git a/examples/1xt2x/.gitignore b/examples/other/1xt2x/.gitignore similarity index 100% rename from examples/1xt2x/.gitignore rename to examples/other/1xt2x/.gitignore diff --git a/examples/1xt2x/README.md b/examples/other/1xt2x/README.md similarity index 100% rename from examples/1xt2x/README.md rename to examples/other/1xt2x/README.md diff --git a/examples/1xt2x/aishell/.gitignore b/examples/other/1xt2x/aishell/.gitignore similarity index 100% rename from examples/1xt2x/aishell/.gitignore rename to examples/other/1xt2x/aishell/.gitignore diff --git a/examples/1xt2x/aishell/conf/augmentation.json b/examples/other/1xt2x/aishell/conf/augmentation.json similarity index 100% rename from examples/1xt2x/aishell/conf/augmentation.json rename to examples/other/1xt2x/aishell/conf/augmentation.json diff --git a/examples/1xt2x/aishell/conf/deepspeech2.yaml b/examples/other/1xt2x/aishell/conf/deepspeech2.yaml similarity index 100% rename from examples/1xt2x/aishell/conf/deepspeech2.yaml rename to examples/other/1xt2x/aishell/conf/deepspeech2.yaml diff --git a/examples/1xt2x/aishell/local/data.sh b/examples/other/1xt2x/aishell/local/data.sh similarity index 100% rename from examples/1xt2x/aishell/local/data.sh rename to examples/other/1xt2x/aishell/local/data.sh diff --git a/examples/1xt2x/aishell/local/download_lm_ch.sh b/examples/other/1xt2x/aishell/local/download_lm_ch.sh similarity index 100% rename from examples/1xt2x/aishell/local/download_lm_ch.sh rename to examples/other/1xt2x/aishell/local/download_lm_ch.sh diff --git a/examples/1xt2x/aishell/local/download_model.sh b/examples/other/1xt2x/aishell/local/download_model.sh similarity index 100% rename from examples/1xt2x/aishell/local/download_model.sh rename to examples/other/1xt2x/aishell/local/download_model.sh diff --git a/examples/1xt2x/aishell/local/test.sh b/examples/other/1xt2x/aishell/local/test.sh similarity index 100% rename from examples/1xt2x/aishell/local/test.sh rename to examples/other/1xt2x/aishell/local/test.sh diff --git a/examples/1xt2x/aishell/path.sh b/examples/other/1xt2x/aishell/path.sh similarity index 91% rename from examples/1xt2x/aishell/path.sh rename to examples/other/1xt2x/aishell/path.sh index 40c7cec2..ce44e65c 100644 --- a/examples/1xt2x/aishell/path.sh +++ b/examples/other/1xt2x/aishell/path.sh @@ -1,4 +1,4 @@ -export MAIN_ROOT=`realpath ${PWD}/../../../` +export MAIN_ROOT=`realpath ${PWD}/../../../../` export LOCAL_DEEPSPEECH2=`realpath ${PWD}/../` export PATH=${MAIN_ROOT}:${MAIN_ROOT}/utils:${PATH} diff --git a/examples/1xt2x/aishell/run.sh b/examples/other/1xt2x/aishell/run.sh similarity index 100% rename from examples/1xt2x/aishell/run.sh rename to examples/other/1xt2x/aishell/run.sh diff --git a/examples/1xt2x/baidu_en8k/.gitignore b/examples/other/1xt2x/baidu_en8k/.gitignore similarity index 100% rename from examples/1xt2x/baidu_en8k/.gitignore rename to examples/other/1xt2x/baidu_en8k/.gitignore diff --git a/examples/1xt2x/baidu_en8k/conf/augmentation.json b/examples/other/1xt2x/baidu_en8k/conf/augmentation.json similarity index 100% rename from examples/1xt2x/baidu_en8k/conf/augmentation.json rename to examples/other/1xt2x/baidu_en8k/conf/augmentation.json diff --git a/examples/1xt2x/baidu_en8k/conf/deepspeech2.yaml b/examples/other/1xt2x/baidu_en8k/conf/deepspeech2.yaml similarity index 100% rename from examples/1xt2x/baidu_en8k/conf/deepspeech2.yaml rename to examples/other/1xt2x/baidu_en8k/conf/deepspeech2.yaml diff --git a/examples/1xt2x/baidu_en8k/local/data.sh b/examples/other/1xt2x/baidu_en8k/local/data.sh similarity index 100% rename from examples/1xt2x/baidu_en8k/local/data.sh rename to examples/other/1xt2x/baidu_en8k/local/data.sh diff --git a/examples/1xt2x/baidu_en8k/local/download_lm_en.sh b/examples/other/1xt2x/baidu_en8k/local/download_lm_en.sh similarity index 100% rename from examples/1xt2x/baidu_en8k/local/download_lm_en.sh rename to examples/other/1xt2x/baidu_en8k/local/download_lm_en.sh diff --git a/examples/1xt2x/baidu_en8k/local/download_model.sh b/examples/other/1xt2x/baidu_en8k/local/download_model.sh similarity index 100% rename from examples/1xt2x/baidu_en8k/local/download_model.sh rename to examples/other/1xt2x/baidu_en8k/local/download_model.sh diff --git a/examples/1xt2x/baidu_en8k/local/test.sh b/examples/other/1xt2x/baidu_en8k/local/test.sh similarity index 100% rename from examples/1xt2x/baidu_en8k/local/test.sh rename to examples/other/1xt2x/baidu_en8k/local/test.sh diff --git a/examples/1xt2x/baidu_en8k/path.sh b/examples/other/1xt2x/baidu_en8k/path.sh similarity index 91% rename from examples/1xt2x/baidu_en8k/path.sh rename to examples/other/1xt2x/baidu_en8k/path.sh index 40c7cec2..ce44e65c 100644 --- a/examples/1xt2x/baidu_en8k/path.sh +++ b/examples/other/1xt2x/baidu_en8k/path.sh @@ -1,4 +1,4 @@ -export MAIN_ROOT=`realpath ${PWD}/../../../` +export MAIN_ROOT=`realpath ${PWD}/../../../../` export LOCAL_DEEPSPEECH2=`realpath ${PWD}/../` export PATH=${MAIN_ROOT}:${MAIN_ROOT}/utils:${PATH} diff --git a/examples/1xt2x/baidu_en8k/run.sh b/examples/other/1xt2x/baidu_en8k/run.sh similarity index 100% rename from examples/1xt2x/baidu_en8k/run.sh rename to examples/other/1xt2x/baidu_en8k/run.sh diff --git a/examples/1xt2x/librispeech/.gitignore b/examples/other/1xt2x/librispeech/.gitignore similarity index 100% rename from examples/1xt2x/librispeech/.gitignore rename to examples/other/1xt2x/librispeech/.gitignore diff --git a/examples/1xt2x/librispeech/conf/augmentation.json b/examples/other/1xt2x/librispeech/conf/augmentation.json similarity index 100% rename from examples/1xt2x/librispeech/conf/augmentation.json rename to examples/other/1xt2x/librispeech/conf/augmentation.json diff --git a/examples/1xt2x/librispeech/conf/deepspeech2.yaml b/examples/other/1xt2x/librispeech/conf/deepspeech2.yaml similarity index 100% rename from examples/1xt2x/librispeech/conf/deepspeech2.yaml rename to examples/other/1xt2x/librispeech/conf/deepspeech2.yaml diff --git a/examples/1xt2x/librispeech/local/data.sh b/examples/other/1xt2x/librispeech/local/data.sh similarity index 100% rename from examples/1xt2x/librispeech/local/data.sh rename to examples/other/1xt2x/librispeech/local/data.sh diff --git a/examples/1xt2x/librispeech/local/download_lm_en.sh b/examples/other/1xt2x/librispeech/local/download_lm_en.sh similarity index 100% rename from examples/1xt2x/librispeech/local/download_lm_en.sh rename to examples/other/1xt2x/librispeech/local/download_lm_en.sh diff --git a/examples/1xt2x/librispeech/local/download_model.sh b/examples/other/1xt2x/librispeech/local/download_model.sh similarity index 100% rename from examples/1xt2x/librispeech/local/download_model.sh rename to examples/other/1xt2x/librispeech/local/download_model.sh diff --git a/examples/1xt2x/librispeech/local/test.sh b/examples/other/1xt2x/librispeech/local/test.sh similarity index 100% rename from examples/1xt2x/librispeech/local/test.sh rename to examples/other/1xt2x/librispeech/local/test.sh diff --git a/examples/1xt2x/librispeech/path.sh b/examples/other/1xt2x/librispeech/path.sh similarity index 90% rename from examples/1xt2x/librispeech/path.sh rename to examples/other/1xt2x/librispeech/path.sh index a146956e..e3696ddd 100644 --- a/examples/1xt2x/librispeech/path.sh +++ b/examples/other/1xt2x/librispeech/path.sh @@ -1,4 +1,4 @@ -export MAIN_ROOT=`realpath ${PWD}/../../../` +export MAIN_ROOT=`realpath ${PWD}/../../../../` export LOCAL_DEEPSPEECH2=`realpath ${PWD}/../` export PATH=${MAIN_ROOT}:${MAIN_ROOT}/utils:${PATH} diff --git a/examples/1xt2x/librispeech/run.sh b/examples/other/1xt2x/librispeech/run.sh similarity index 100% rename from examples/1xt2x/librispeech/run.sh rename to examples/other/1xt2x/librispeech/run.sh diff --git a/examples/1xt2x/src_deepspeech2x/__init__.py b/examples/other/1xt2x/src_deepspeech2x/__init__.py similarity index 100% rename from examples/1xt2x/src_deepspeech2x/__init__.py rename to examples/other/1xt2x/src_deepspeech2x/__init__.py diff --git a/examples/1xt2x/src_deepspeech2x/bin/test.py b/examples/other/1xt2x/src_deepspeech2x/bin/test.py similarity index 100% rename from examples/1xt2x/src_deepspeech2x/bin/test.py rename to examples/other/1xt2x/src_deepspeech2x/bin/test.py diff --git a/examples/1xt2x/src_deepspeech2x/models/__init__.py b/examples/other/1xt2x/src_deepspeech2x/models/__init__.py similarity index 100% rename from examples/1xt2x/src_deepspeech2x/models/__init__.py rename to examples/other/1xt2x/src_deepspeech2x/models/__init__.py diff --git a/examples/1xt2x/src_deepspeech2x/models/ds2/__init__.py b/examples/other/1xt2x/src_deepspeech2x/models/ds2/__init__.py similarity index 100% rename from examples/1xt2x/src_deepspeech2x/models/ds2/__init__.py rename to examples/other/1xt2x/src_deepspeech2x/models/ds2/__init__.py diff --git a/examples/1xt2x/src_deepspeech2x/models/ds2/deepspeech2.py b/examples/other/1xt2x/src_deepspeech2x/models/ds2/deepspeech2.py similarity index 100% rename from examples/1xt2x/src_deepspeech2x/models/ds2/deepspeech2.py rename to examples/other/1xt2x/src_deepspeech2x/models/ds2/deepspeech2.py diff --git a/examples/1xt2x/src_deepspeech2x/models/ds2/rnn.py b/examples/other/1xt2x/src_deepspeech2x/models/ds2/rnn.py similarity index 100% rename from examples/1xt2x/src_deepspeech2x/models/ds2/rnn.py rename to examples/other/1xt2x/src_deepspeech2x/models/ds2/rnn.py diff --git a/examples/1xt2x/src_deepspeech2x/test_model.py b/examples/other/1xt2x/src_deepspeech2x/test_model.py similarity index 100% rename from examples/1xt2x/src_deepspeech2x/test_model.py rename to examples/other/1xt2x/src_deepspeech2x/test_model.py diff --git a/examples/augmentation/augmentation.json b/examples/other/augmentation/augmentation.json similarity index 100% rename from examples/augmentation/augmentation.json rename to examples/other/augmentation/augmentation.json diff --git a/examples/cc-cedict/.gitignore b/examples/other/cc-cedict/.gitignore similarity index 100% rename from examples/cc-cedict/.gitignore rename to examples/other/cc-cedict/.gitignore diff --git a/examples/cc-cedict/README.md b/examples/other/cc-cedict/README.md similarity index 100% rename from examples/cc-cedict/README.md rename to examples/other/cc-cedict/README.md diff --git a/examples/cc-cedict/local/parser.py b/examples/other/cc-cedict/local/parser.py similarity index 100% rename from examples/cc-cedict/local/parser.py rename to examples/other/cc-cedict/local/parser.py diff --git a/examples/ngram_lm/s0/path.sh b/examples/other/cc-cedict/path.sh similarity index 100% rename from examples/ngram_lm/s0/path.sh rename to examples/other/cc-cedict/path.sh diff --git a/examples/cc-cedict/run.sh b/examples/other/cc-cedict/run.sh similarity index 100% rename from examples/cc-cedict/run.sh rename to examples/other/cc-cedict/run.sh diff --git a/examples/g2p/.gitignore b/examples/other/g2p/.gitignore similarity index 100% rename from examples/g2p/.gitignore rename to examples/other/g2p/.gitignore diff --git a/examples/g2p/README.md b/examples/other/g2p/README.md similarity index 100% rename from examples/g2p/README.md rename to examples/other/g2p/README.md diff --git a/examples/g2p/zh/README.md b/examples/other/g2p/zh/README.md similarity index 100% rename from examples/g2p/zh/README.md rename to examples/other/g2p/zh/README.md diff --git a/examples/g2p/zh/local/convert_transcription.py b/examples/other/g2p/zh/local/convert_transcription.py similarity index 100% rename from examples/g2p/zh/local/convert_transcription.py rename to examples/other/g2p/zh/local/convert_transcription.py diff --git a/examples/g2p/zh/local/extract_pinyin_label.py b/examples/other/g2p/zh/local/extract_pinyin_label.py similarity index 100% rename from examples/g2p/zh/local/extract_pinyin_label.py rename to examples/other/g2p/zh/local/extract_pinyin_label.py diff --git a/examples/g2p/zh/local/ignore_sandhi.py b/examples/other/g2p/zh/local/ignore_sandhi.py similarity index 100% rename from examples/g2p/zh/local/ignore_sandhi.py rename to examples/other/g2p/zh/local/ignore_sandhi.py diff --git a/examples/g2p/zh/local/prepare_dataset.sh b/examples/other/g2p/zh/local/prepare_dataset.sh similarity index 100% rename from examples/g2p/zh/local/prepare_dataset.sh rename to examples/other/g2p/zh/local/prepare_dataset.sh diff --git a/examples/g2p/zh/path.sh b/examples/other/g2p/zh/path.sh similarity index 81% rename from examples/g2p/zh/path.sh rename to examples/other/g2p/zh/path.sh index f475ed83..9f6354c6 100644 --- a/examples/g2p/zh/path.sh +++ b/examples/other/g2p/zh/path.sh @@ -1,4 +1,4 @@ -export MAIN_ROOT=`realpath ${PWD}/../../../` +export MAIN_ROOT=`realpath ${PWD}/../../../../` export PATH=${MAIN_ROOT}:${MAIN_ROOT}/utils:${PATH} export LC_ALL=C diff --git a/examples/g2p/zh/requirements.txt b/examples/other/g2p/zh/requirements.txt similarity index 100% rename from examples/g2p/zh/requirements.txt rename to examples/other/g2p/zh/requirements.txt diff --git a/examples/g2p/zh/run.sh b/examples/other/g2p/zh/run.sh similarity index 100% rename from examples/g2p/zh/run.sh rename to examples/other/g2p/zh/run.sh diff --git a/examples/ngram_lm/.gitignore b/examples/other/ngram_lm/.gitignore similarity index 100% rename from examples/ngram_lm/.gitignore rename to examples/other/ngram_lm/.gitignore diff --git a/examples/ngram_lm/READEME.md b/examples/other/ngram_lm/READEME.md similarity index 100% rename from examples/ngram_lm/READEME.md rename to examples/other/ngram_lm/READEME.md diff --git a/examples/ngram_lm/s0/.gitignore b/examples/other/ngram_lm/s0/.gitignore similarity index 100% rename from examples/ngram_lm/s0/.gitignore rename to examples/other/ngram_lm/s0/.gitignore diff --git a/examples/ngram_lm/s0/README.md b/examples/other/ngram_lm/s0/README.md similarity index 100% rename from examples/ngram_lm/s0/README.md rename to examples/other/ngram_lm/s0/README.md diff --git a/examples/ngram_lm/s0/data/README.md b/examples/other/ngram_lm/s0/data/README.md similarity index 100% rename from examples/ngram_lm/s0/data/README.md rename to examples/other/ngram_lm/s0/data/README.md diff --git a/examples/ngram_lm/s0/data/custom_confusion.txt b/examples/other/ngram_lm/s0/data/custom_confusion.txt similarity index 100% rename from examples/ngram_lm/s0/data/custom_confusion.txt rename to examples/other/ngram_lm/s0/data/custom_confusion.txt diff --git a/examples/ngram_lm/s0/data/text_correct.txt b/examples/other/ngram_lm/s0/data/text_correct.txt similarity index 100% rename from examples/ngram_lm/s0/data/text_correct.txt rename to examples/other/ngram_lm/s0/data/text_correct.txt diff --git a/examples/ngram_lm/s0/local/build_zh_lm.sh b/examples/other/ngram_lm/s0/local/build_zh_lm.sh similarity index 100% rename from examples/ngram_lm/s0/local/build_zh_lm.sh rename to examples/other/ngram_lm/s0/local/build_zh_lm.sh diff --git a/examples/ngram_lm/s0/local/download_lm_zh.sh b/examples/other/ngram_lm/s0/local/download_lm_zh.sh similarity index 100% rename from examples/ngram_lm/s0/local/download_lm_zh.sh rename to examples/other/ngram_lm/s0/local/download_lm_zh.sh diff --git a/examples/ngram_lm/s0/local/kenlm_score_test.py b/examples/other/ngram_lm/s0/local/kenlm_score_test.py similarity index 100% rename from examples/ngram_lm/s0/local/kenlm_score_test.py rename to examples/other/ngram_lm/s0/local/kenlm_score_test.py diff --git a/examples/cc-cedict/path.sh b/examples/other/ngram_lm/s0/path.sh similarity index 66% rename from examples/cc-cedict/path.sh rename to examples/other/ngram_lm/s0/path.sh index f8fdd82d..61ffa159 100644 --- a/examples/cc-cedict/path.sh +++ b/examples/other/ngram_lm/s0/path.sh @@ -1,4 +1,4 @@ -export MAIN_ROOT=`realpath ${PWD}/../../` +export MAIN_ROOT=`realpath ${PWD}/../../../../` export PATH=${MAIN_ROOT}:${MAIN_ROOT}/utils:${PATH} export LC_ALL=C @@ -7,4 +7,4 @@ export LC_ALL=C export PYTHONIOENCODING=UTF-8 export PYTHONPATH=${MAIN_ROOT}:${PYTHONPATH} -export LD_LIBRARY_PATH=/usr/local/lib/:${LD_LIBRARY_PATH} \ No newline at end of file +export LD_LIBRARY_PATH=/usr/local/lib/:${LD_LIBRARY_PATH} diff --git a/examples/ngram_lm/s0/requirements.txt b/examples/other/ngram_lm/s0/requirements.txt similarity index 100% rename from examples/ngram_lm/s0/requirements.txt rename to examples/other/ngram_lm/s0/requirements.txt diff --git a/examples/ngram_lm/s0/run.sh b/examples/other/ngram_lm/s0/run.sh similarity index 100% rename from examples/ngram_lm/s0/run.sh rename to examples/other/ngram_lm/s0/run.sh diff --git a/examples/punctuation_restoration/README.md b/examples/other/punctuation_restoration/README.md similarity index 100% rename from examples/punctuation_restoration/README.md rename to examples/other/punctuation_restoration/README.md diff --git a/examples/spm/.gitignore b/examples/other/spm/.gitignore similarity index 100% rename from examples/spm/.gitignore rename to examples/other/spm/.gitignore diff --git a/examples/spm/README.md b/examples/other/spm/README.md similarity index 100% rename from examples/spm/README.md rename to examples/other/spm/README.md diff --git a/examples/spm/path.sh b/examples/other/spm/path.sh similarity index 85% rename from examples/spm/path.sh rename to examples/other/spm/path.sh index 20237889..32717707 100644 --- a/examples/spm/path.sh +++ b/examples/other/spm/path.sh @@ -1,4 +1,4 @@ -export MAIN_ROOT=`realpath ${PWD}/../../` +export MAIN_ROOT=`realpath ${PWD}/../../../` export PATH=${MAIN_ROOT}:${MAIN_ROOT}/utils:${PATH} export LC_ALL=C diff --git a/examples/spm/run.sh b/examples/other/spm/run.sh similarity index 100% rename from examples/spm/run.sh rename to examples/other/spm/run.sh diff --git a/examples/spm/text b/examples/other/spm/text similarity index 100% rename from examples/spm/text rename to examples/other/spm/text diff --git a/examples/other/text_frontend/README.md b/examples/other/text_frontend/README.md new file mode 100644 index 00000000..d5c6dd4d --- /dev/null +++ b/examples/other/text_frontend/README.md @@ -0,0 +1,24 @@ +# Chinese Text Frontend Example +Here's an example for Chinese text frontend, including g2p and text normalization. +## G2P +For g2p, we use BZNSYP's phone label as the ground truth and we delete silence tokens in labels and predicted phones. + +You should Download BZNSYP from it's [Official Website](https://test.data-baker.com/data/index/source) and extract it. Assume the path to the dataset is `~/datasets/BZNSYP`. + +We use `WER` as evaluation criterion. +## Text Normalization +For text normalization, the test data is `data/textnorm_test_cases.txt`, we use `|` as the separator of raw_data and normed_data. + +We use `CER` as evaluation criterion. +## Start +If you want to use sclite to get more detail information of WER, you should run the command below to make sclite first. +```bash +./make_sclite.sh +``` +Run the command below to get the results of test. +```bash +./run.sh +``` +The `avg WER` of g2p is: 0.027495061517943988 + +The `avg CER` of text normalization is: 0.006388318503308237 diff --git a/examples/other/text_frontend/data/textnorm_test_cases.txt b/examples/other/text_frontend/data/textnorm_test_cases.txt new file mode 100644 index 00000000..e9a479b4 --- /dev/null +++ b/examples/other/text_frontend/data/textnorm_test_cases.txt @@ -0,0 +1,125 @@ +今天的最低气温达到-10°C.|今天的最低气温达到零下十度. +只要有33/4的人同意，就可以通过决议。|只要有四分之三十三的人同意，就可以通过决议。 +1945年5月2日，苏联士兵在德国国会大厦上升起了胜利旗，象征着攻占柏林并战胜了纳粹德国。|一九四五年五月二日，苏联士兵在德国国会大厦上升起了胜利旗，象征着攻占柏林并战胜了纳粹德国。 +4月16日，清晨的战斗以炮击揭幕，数以千计的大炮和喀秋莎火箭炮开始炮轰德军阵地，炮击持续了数天之久。|四月十六日，清晨的战斗以炮击揭幕，数以千计的大炮和喀秋莎火箭炮开始炮轰德军阵地，炮击持续了数天之久。 +如果剩下的30.6%是过去，那么还有69.4%.|如果剩下的百分之三十点六是过去，那么还有百分之六十九点四. +事情发生在2020/03/31的上午8:00.|事情发生在二零二零年三月三十一日的上午八点. +警方正在找一支.22口径的手枪。|警方正在找一支零点二二口径的手枪。 +欢迎致电中国联通，北京2022年冬奥会官方合作伙伴为您服务|欢迎致电中国联通，北京二零二二年冬奥会官方合作伙伴为您服务 +充值缴费请按1，查询话费及余量请按2，跳过本次提醒请按井号键。|充值缴费请按一，查询话费及余量请按二，跳过本次提醒请按井号键。 +快速解除流量封顶请按星号键，腾讯王卡产品介绍、使用说明、特权及活动请按9，查询话费、套餐余量、积分及活动返款请按1，手机上网流量开通及取消请按2，查询本机号码及本号所使用套餐请按4，密码修改及重置请按5，紧急开机请按6，挂失请按7，查询充值记录请按8，其它自助服务及人工服务请按0|快速解除流量封顶请按星号键，腾讯王卡产品介绍、使用说明、特权及活动请按九，查询话费、套餐余量、积分及活动返款请按一，手机上网流量开通及取消请按二，查询本机号码及本号所使用套餐请按四，密码修改及重置请按五，紧急开机请按六，挂失请按七，查询充值记录请按八，其它自助服务及人工服务请按零 +智能客服助理快速查话费、查流量请按9，了解北京联通业务请按1，宽带IPTV新装、查询请按2，障碍报修请按3，充值缴费请按4，投诉建议请按5，政企业务请按7，人工服务请按0，for english severice press star key|智能客服助理快速查话费、查流量请按九，了解北京联通业务请按一，宽带IPTV新装、查询请按二，障碍报修请按三，充值缴费请按四，投诉建议请按五，政企业务请按七，人工服务请按零，for english severice press star key 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+除此之外，摄像头方面再次升级，增加了前摄全新超广角摄像头，支持人物居中功能，搭配超广角可实现视频中始终让人物居中效果。|除此之外，摄像头方面再次升级，增加了前摄全新超广角摄像头，支持人物居中功能，搭配超广角可实现视频中始终让人物居中效果。 +屏幕方面，iPad Pro 12.9版本支持XDR体验的Mini-LEDS显示屏，支持HDR10、杜比视界，还支持杜比全景声。|屏幕方面，iPad Pro 十二点九版本支持XDR体验的Mini-LEDS显示屏，支持HDR十、杜比视界，还支持杜比全景声。 +iPad Pro的秒控键盘这次也推出白色版本。|iPad Pro的秒控键盘这次也推出白色版本。 +售价方面，11英寸版本售价799美元起，12.9英寸售价1099美元起。|售价方面，十一英寸版本售价七百九十九美元起，十二点九英寸售价一千零九十九美元起。 +这块黄金重达324.75克|这块黄金重达三百二十四点七五克 +她出生于86年8月18日，她弟弟出生于1995年3月1日|她出生于八六年八月十八日，她弟弟出生于一九九五年三月一日 +电影中梁朝伟扮演的陈永仁的编号27149|电影中梁朝伟扮演的陈永仁的编号二七一四九 +现场有7/12的观众投出了赞成票|现场有十二分之七的观众投出了赞成票 +随便来几个价格12块5，34.5元，20.1万|随便来几个价格十二块五，三十四点五元，二十点一万 +明天有62%的概率降雨|明天有百分之六十二的概率降雨 +这是固话0421-33441122|这是固话零四二一三三四四一一二二 +这是手机+86 18544139121|这是手机八六一八五四四一三九一二一 +小王的身高是153.5cm,梦想是打篮球!我觉得有0.1%的可能性。|小王的身高是一百五十三点五cm,梦想是打篮球!我觉得有百分之零点一的可能性。 +不管三七二十一|不管三七二十一 +九九八十一难|九九八十一难 +2018年5月23号上午10点10分|二零一八年五月二十三号上午十点十分 +10076|一零零七六 +32.68%|百分之三十二点六八 +比分测试17:16|比分测试十七比十六 +比分测试37:16|比分测试三十七比十六 +1.1|一点一 +一点一滴|一点一滴 +八九十|八九十 +1个人一定要|一个人一定要 +10000棵树|一万棵树 +1234个人|一千二百三十四个人 +35553座楼|三万五千五百五十三座楼 +15873690|一五八七三六九零 +27930122|二七九三零一二二 +85307499|八五三零七四九九 +26149787|二六一四九七八七 +15964862|一五九六四八六二 +45698723|四五六九八七二三 +48615964|四八六一五九六四 +17864589|一七八六四五八九 +123加456|一百二十三加四百五十六 +9786加3384|九千七百八十六加三千三百八十四 +发电站每天发电30029度电|发电站每天发电三万零二十九度电 +银行月交易总额七千九百零三亿元|银行月交易总额七千九百零三亿元 +深圳每月平均工资在13000元|深圳每月平均工资在一万三千元 +每月房租要交1500元|每月房租要交一千五百元 +我每月交通费用在400元左右|我每月交通费用在四百元左右 +本月开销费用是51328元|本月开销费用是五万一千三百二十八元 +如果你中了五千万元奖金会分我一半吗|如果你中了五千万元奖金会分我一半吗 +这个月工资我发了3529元|这个月工资我发了三千五百二十九元 +学会了这个技能你至少可以涨薪5000元|学会了这个技能你至少可以涨薪五千元 +我们的会议时间定在9点25分开始|我们的会议时间定在九点二十五分开始 +上课时间是8点15分请不要迟到|上课时间是八点十五分请不要迟到 +昨天你9点21分才到教室|昨天你九点二十一分才到教室 +今天是2019年1月31号|今天是二零一九年一月三十一号 +今年的除夕夜是2019年2月4号|今年的除夕夜是二零一九年二月四号 +这根水管的长度不超过35米|这根水管的长度不超过三十五米 +400米是最短的长跑距离|四百米是最短的长跑距离 +最高的撑杆跳为11米|最高的撑杆跳为十一米 +等会请在12:05请通知我|等会请在十二点零五分请通知我 +23点15分开始|二十三点十五分开始 +你生日那天我会送你999朵玫瑰|你生日那天我会送你九百九十九朵玫瑰 +给我1双鞋我可以跳96米远|给我一双鞋我可以跳九十六米远 +虽然我们的身高相差356毫米也不影响我们交往|虽然我们的身高相差三百五十六毫米也不影响我们交往 +我们班的最高总分为583分|我们班的最高总分为五百八十三分 +今天考试老师多扣了我21分|今天考试老师多扣了我二十一分 +我量过这张桌子总长为1.37米|我量过这张桌子总长为一点三七米 +乘务员身高必须超过185公分|乘务员身高必须超过一百八十五公分 +这台电脑分辨率为1024|这台电脑分辨率为一零二四 +手机价格不超过1500元|手机价格不超过一千五百元 +101.23|一百零一点二三 +123.116|一百二十三点一一六 +456.147|四百五十六点一四七 +0.1594|零点一五九四 +3.1415|三点一四一五 +0.112233|零点一一二二三三 +0.1|零点一 +40001.987|四万零一点九八七 +56.878|五十六点八七八 +0.00123|零点零零一二三 +0.0001|零点零零零一 +0.92015|零点九二零一五 +999.0001|九百九十九点零零零一 +10000.123|一万点一二三 +666.555|六百六十六点五五五 +444.789|四百四十四点七八九 +789.666|七百八十九点六六六 +0.12345|零点一二三四五 +1.05649|一点零五六四九 +环比上调1.86%|环比上调百分之一点八六 +环比分别下跌3.46%及微涨0.70%|环比分别下跌百分之三点四六及微涨百分之零点七 +单价在30000元的二手房购房个案当中|单价在三万元的二手房购房个案当中 +6月仍有7%单价在30000元的房源|六月仍有百分之七单价在三万元的房源 +最终也只是以总积分1分之差屈居第2|最终也只是以总积分一分之差屈居第二 +中新网8月29日电今日|中新网八月二十九日电今日 +自6月底呼和浩特市率先宣布取消限购后|自六月底呼和浩特市率先宣布取消限购后 +仅1个多月的时间里|仅一个多月的时间里 +除了北京上海广州深圳4个一线城市和三亚之外|除了北京上海广州深圳四个一线城市和三亚之外 +46个限购城市当中|四十六个限购城市当中 +41个已正式取消或变相放松了限购|四十一个已正式取消或变相放松了限购 +其中包括对拥有一套住房并已结清相应购房贷款的家庭|其中包括对拥有一套住房并已结清相应购房贷款的家庭 +这个后来被称为930新政策的措施|这个后来被称为九三零新政策的措施 +今年有望超三百亿美元|今年有望超三百亿美元 +就连一向看多的任志强|就连一向看多的任志强 +近期也一反常态地发表看空言论|近期也一反常态地发表看空言论 +985|九八五 +12~23|十二到二十三 +12-23|十二到二十三 \ No newline at end of file diff --git a/examples/other/text_frontend/get_g2p_data.py b/examples/other/text_frontend/get_g2p_data.py new file mode 100644 index 00000000..78535b66 --- /dev/null +++ b/examples/other/text_frontend/get_g2p_data.py @@ -0,0 +1,90 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +from collections import defaultdict +from pathlib import Path + +from praatio import tgio + + +def get_baker_data(root_dir): + alignment_files = sorted( + list((root_dir / "PhoneLabeling").rglob("*.interval"))) + text_file = root_dir / "ProsodyLabeling/000001-010000.txt" + text_file = Path(text_file).expanduser() + # filter out several files that have errors in annotation + exclude = {'000611', '000662', '002365', '005107'} + alignment_files = [f for f in alignment_files if f.stem not in exclude] + data_dict = defaultdict(dict) + for alignment_fp in alignment_files: + alignment = tgio.openTextgrid(alignment_fp) + # only with baker's annotation + utt_id = alignment.tierNameList[0].split(".")[0] + intervals = alignment.tierDict[alignment.tierNameList[0]].entryList + phones = [] + for interval in intervals: + label = interval.label + phones.append(label) + data_dict[utt_id]["phones"] = phones + for line in open(text_file, "r"): + if line.startswith("0"): + utt_id, raw_text = line.strip().split() + if utt_id in data_dict: + data_dict[utt_id]['text'] = raw_text + else: + pinyin = line.strip().split() + if utt_id in data_dict: + data_dict[utt_id]['pinyin'] = pinyin + return data_dict + + +def get_g2p_phones(data_dict, frontend): + for utt_id in data_dict: + g2p_phones = frontend.get_phonemes(data_dict[utt_id]['text']) + data_dict[utt_id]["g2p_phones"] = g2p_phones + return data_dict + + +def main(): + parser = argparse.ArgumentParser(description="g2p example.") + parser.add_argument( + "--root-dir", + default=None, + type=str, + help="directory to baker dataset.") + parser.add_argument( + "--output-dir", + default="data/g2p", + type=str, + help="directory to output.") + + args = parser.parse_args() + root_dir = Path(args.root_dir).expanduser() + output_dir = Path(args.output_dir).expanduser() + output_dir.mkdir(parents=True, exist_ok=True) + assert root_dir.is_dir() + data_dict = get_baker_data(root_dir) + raw_path = output_dir / "text" + ref_path = output_dir / "text.ref" + wf_raw = open(raw_path, "w") + wf_ref = open(ref_path, "w") + for utt_id in data_dict: + wf_raw.write(utt_id + " " + data_dict[utt_id]['text'] + "\n") + wf_ref.write(utt_id + " " + " ".join(data_dict[utt_id]['phones']) + + "\n") + + +if __name__ == "__main__": + main() diff --git a/examples/other/text_frontend/get_textnorm_data.py b/examples/other/text_frontend/get_textnorm_data.py new file mode 100644 index 00000000..8058e058 --- /dev/null +++ b/examples/other/text_frontend/get_textnorm_data.py @@ -0,0 +1,50 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +from pathlib import Path + + +def main(): + parser = argparse.ArgumentParser(description="text normalization example.") + parser.add_argument( + "--test-file", + default="data/textnorm_test_cases.txt", + type=str, + help="path of text normalization test file.") + parser.add_argument( + "--output-dir", + default="data/textnorm", + type=str, + help="directory to output.") + + args = parser.parse_args() + test_file = Path(args.test_file).expanduser() + output_dir = Path(args.output_dir).expanduser() + output_dir.mkdir(parents=True, exist_ok=True) + + raw_path = output_dir / "text" + ref_path = output_dir / "text.ref" + wf_raw = open(raw_path, "w") + wf_ref = open(ref_path, "w") + + with open(test_file, "r") as rf: + for i, line in enumerate(rf): + raw_text, normed_text = line.strip().split("|") + wf_raw.write("utt_" + str(i) + " " + raw_text + "\n") + wf_ref.write("utt_" + str(i) + " " + normed_text + "\n") + + +if __name__ == "__main__": + main() diff --git a/examples/other/text_frontend/make_sclite.sh b/examples/other/text_frontend/make_sclite.sh new file mode 100755 index 00000000..db8c921c --- /dev/null +++ b/examples/other/text_frontend/make_sclite.sh @@ -0,0 +1,13 @@ +#!/bin/bash + +if [ ! -d "./SCTK" ];then + echo "Clone SCTK ..." + git clone https://github.com/usnistgov/SCTK + echo "Clone SCTK done!" +fi + +if [ ! -d "./SCTK/bin" ];then + echo "Start make SCTK ..." + pushd SCTK && make config && make all && make check && make install && make doc && popd + echo "SCTK make done!" +fi diff --git a/examples/other/text_frontend/run.sh b/examples/other/text_frontend/run.sh new file mode 100755 index 00000000..9882b057 --- /dev/null +++ b/examples/other/text_frontend/run.sh @@ -0,0 +1,25 @@ +#!/bin/bash + +USE_SCLITE=true + +# test g2p +echo "Start get g2p test data ..." +python3 get_g2p_data.py --root-dir=~/datasets/BZNSYP --output-dir=data/g2p +echo "Start test g2p ..." +python3 test_g2p.py --input-dir=data/g2p --output-dir=exp/g2p + +# test text normalization +echo "Start get text normalization test data ..." +python3 get_textnorm_data.py --test-file=data/textnorm_test_cases.txt --output-dir=data/textnorm +echo "Start test text normalization ..." +python3 test_textnorm.py --input-dir=data/textnorm --output-dir=exp/textnorm + +# whether use sclite to get more detail information of WER +if [ "$USE_SCLITE" = true ];then + echo "Start sclite g2p ..." + ./SCTK/bin/sclite -i wsj -r ./exp/g2p/text.ref.clean trn -h ./exp/g2p/text.g2p trn -e utf-8 -o all + echo + + echo "Start sclite textnorm ..." + ./SCTK/bin/sclite -i wsj -r ./exp/textnorm/text.ref.clean trn -h ./exp/textnorm/text.tn trn -e utf-8 -o all +fi \ No newline at end of file diff --git a/examples/other/text_frontend/test_g2p.py b/examples/other/text_frontend/test_g2p.py new file mode 100644 index 00000000..0515e994 --- /dev/null +++ b/examples/other/text_frontend/test_g2p.py @@ -0,0 +1,99 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +import re +from pathlib import Path + +from parakeet.frontend.zh_frontend import Frontend as zhFrontend +from parakeet.utils.error_rate import word_errors + +SILENCE_TOKENS = {"sp", "sil", "sp1", "spl"} + + +def text_cleaner(raw_text): + text = re.sub('#[1-4]|“|”|（|）', '', raw_text) + text = text.replace("…。", "。") + text = re.sub('：|；|——|……|、|…|—', '，', text) + return text + + +def get_avg_wer(raw_dict, ref_dict, frontend, output_dir): + edit_distances = [] + ref_lens = [] + wf_g2p = open(output_dir / "text.g2p", "w") + wf_ref = open(output_dir / "text.ref.clean", "w") + for utt_id in raw_dict: + if utt_id not in ref_dict: + continue + raw_text = raw_dict[utt_id] + text = text_cleaner(raw_text) + g2p_phones = frontend.get_phonemes(text) + g2p_phones = sum(g2p_phones, []) + gt_phones = ref_dict[utt_id].split(" ") + # delete silence tokens in predicted phones and ground truth phones + g2p_phones = [phn for phn in g2p_phones if phn not in SILENCE_TOKENS] + gt_phones = [phn for phn in gt_phones if phn not in SILENCE_TOKENS] + gt_phones = " ".join(gt_phones) + g2p_phones = " ".join(g2p_phones) + wf_ref.write(gt_phones + "(baker_" + utt_id + ")" + "\n") + wf_g2p.write(g2p_phones + "(baker_" + utt_id + ")" + "\n") + edit_distance, ref_len = word_errors(gt_phones, g2p_phones) + edit_distances.append(edit_distance) + ref_lens.append(ref_len) + + return sum(edit_distances) / sum(ref_lens) + + +def main(): + parser = argparse.ArgumentParser(description="g2p example.") + parser.add_argument( + "--input-dir", + default="data/g2p", + type=str, + help="directory to preprocessed test data.") + parser.add_argument( + "--output-dir", + default="exp/g2p", + type=str, + help="directory to save g2p results.") + + args = parser.parse_args() + input_dir = Path(args.input_dir).expanduser() + output_dir = Path(args.output_dir).expanduser() + output_dir.mkdir(parents=True, exist_ok=True) + assert input_dir.is_dir() + raw_dict, ref_dict = dict(), dict() + raw_path = input_dir / "text" + ref_path = input_dir / "text.ref" + + with open(raw_path, "r") as rf: + for line in rf: + line = line.strip() + line_list = line.split(" ") + utt_id, raw_text = line_list[0], " ".join(line_list[1:]) + raw_dict[utt_id] = raw_text + with open(ref_path, "r") as rf: + for line in rf: + line = line.strip() + line_list = line.split(" ") + utt_id, phones = line_list[0], " ".join(line_list[1:]) + ref_dict[utt_id] = phones + frontend = zhFrontend() + avg_wer = get_avg_wer(raw_dict, ref_dict, frontend, output_dir) + print("The avg WER of g2p is:", avg_wer) + + +if __name__ == "__main__": + main() diff --git a/examples/other/text_frontend/test_textnorm.py b/examples/other/text_frontend/test_textnorm.py new file mode 100644 index 00000000..99eed290 --- /dev/null +++ b/examples/other/text_frontend/test_textnorm.py @@ -0,0 +1,97 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +import re +from pathlib import Path + +from parakeet.frontend.zh_normalization.text_normlization import TextNormalizer +from parakeet.utils.error_rate import char_errors + + +# delete english characters +# e.g. "你好aBC" -> "你 好" +def del_en_add_space(input: str): + output = re.sub('[a-zA-Z]', '', input) + output = [char + " " for char in output] + output = "".join(output).strip() + return output + + +def get_avg_cer(raw_dict, ref_dict, text_normalizer, output_dir): + edit_distances = [] + ref_lens = [] + wf_ref = open(output_dir / "text.ref.clean", "w") + wf_tn = open(output_dir / "text.tn", "w") + for text_id in raw_dict: + if text_id not in ref_dict: + continue + raw_text = raw_dict[text_id] + gt_text = ref_dict[text_id] + textnorm_text = text_normalizer.normalize_sentence(raw_text) + + gt_text = del_en_add_space(gt_text) + textnorm_text = del_en_add_space(textnorm_text) + wf_ref.write(gt_text + "(" + text_id + ")" + "\n") + wf_tn.write(textnorm_text + "(" + text_id + ")" + "\n") + edit_distance, ref_len = char_errors(gt_text, textnorm_text) + edit_distances.append(edit_distance) + ref_lens.append(ref_len) + + return sum(edit_distances) / sum(ref_lens) + + +def main(): + parser = argparse.ArgumentParser(description="text normalization example.") + parser.add_argument( + "--input-dir", + default="data/textnorm", + type=str, + help="directory to preprocessed test data.") + parser.add_argument( + "--output-dir", + default="exp/textnorm", + type=str, + help="directory to save textnorm results.") + + args = parser.parse_args() + input_dir = Path(args.input_dir).expanduser() + output_dir = Path(args.output_dir).expanduser() + output_dir.mkdir(parents=True, exist_ok=True) + assert input_dir.is_dir() + raw_dict, ref_dict = dict(), dict() + raw_path = input_dir / "text" + ref_path = input_dir / "text.ref" + + with open(raw_path, "r") as rf: + for line in rf: + line = line.strip() + line_list = line.split(" ") + text_id, raw_text = line_list[0], " ".join(line_list[1:]) + raw_dict[text_id] = raw_text + with open(ref_path, "r") as rf: + for line in rf: + line = line.strip() + line_list = line.split(" ") + text_id, normed_text = line_list[0], " ".join(line_list[1:]) + ref_dict[text_id] = normed_text + + text_normalizer = TextNormalizer() + + avg_cer = get_avg_cer(raw_dict, ref_dict, text_normalizer, output_dir) + print("The avg CER of text normalization is:", avg_cer) + + +if __name__ == "__main__": + main() diff --git a/examples/tn/.gitignore b/examples/other/tn/.gitignore similarity index 100% rename from examples/tn/.gitignore rename to examples/other/tn/.gitignore diff --git a/examples/tn/README.md b/examples/other/tn/README.md similarity index 100% rename from examples/tn/README.md rename to examples/other/tn/README.md diff --git a/examples/tn/data/sentences.txt b/examples/other/tn/data/sentences.txt similarity index 100% rename from examples/tn/data/sentences.txt rename to examples/other/tn/data/sentences.txt diff --git a/examples/tn/local/test_normalization.py b/examples/other/tn/local/test_normalization.py similarity index 100% rename from examples/tn/local/test_normalization.py rename to examples/other/tn/local/test_normalization.py diff --git a/examples/tn/path.sh b/examples/other/tn/path.sh similarity index 83% rename from examples/tn/path.sh rename to examples/other/tn/path.sh index 30689eee..c330c623 100644 --- a/examples/tn/path.sh +++ b/examples/other/tn/path.sh @@ -1,4 +1,4 @@ -export MAIN_ROOT=`realpath ${PWD}/../../` +export MAIN_ROOT=`realpath ${PWD}/../../../` export PATH=${MAIN_ROOT}:${MAIN_ROOT}/utils:${PATH} export LC_ALL=C diff --git a/examples/tn/run.sh b/examples/other/tn/run.sh similarity index 100% rename from examples/tn/run.sh rename to examples/other/tn/run.sh diff --git a/examples/other/use_mfa/README.md b/examples/other/use_mfa/README.md new file mode 100644 index 00000000..c24524ab --- /dev/null +++ b/examples/other/use_mfa/README.md @@ -0,0 +1,6 @@ +# Use Montreal-Forced-Aligner +Here is an example to use [MFA1.x](https://github.com/MontrealCorpusTools/Montreal-Forced-Aligner). +Run the following script to get started, for more detail, please see `run.sh`. +```bash +./run.sh +``` diff --git a/examples/other/use_mfa/local/cmudict-0.7b b/examples/other/use_mfa/local/cmudict-0.7b new file mode 100644 index 00000000..35e2d252 --- /dev/null +++ b/examples/other/use_mfa/local/cmudict-0.7b @@ -0,0 +1,134373 @@ +!EXCLAMATION-POINT EH2 K S K L AH0 M EY1 SH AH0 N P OY2 N T +"CLOSE-QUOTE K L OW1 Z K W OW1 T +"DOUBLE-QUOTE D AH1 B AH0 L K W OW1 T +"END-OF-QUOTE EH1 N D AH0 V K W OW1 T +"END-QUOTE EH1 N D K W OW1 T +"IN-QUOTES IH1 N K W OW1 T S +"QUOTE K W OW1 T +"UNQUOTE AH1 N K W OW1 T +#HASH-MARK HH AE1 M AA2 R K +#POUND-SIGN P AW1 N D S AY2 N +#SHARP-SIGN SH AA1 R P S AY2 N +%PERCENT P ER0 S EH1 N T +&ERSAND AE1 M P ER0 S AE2 N D +'ALLO AA2 L OW1 +'APOSTROPHE AH0 P AA1 S T R AH0 F IY0 +'BOUT B AW1 T +'CAUSE K AH0 Z +'COURSE K AO1 R S +'CUSE K Y UW1 Z +'EM AH0 M +'END-INNER-QUOTE EH1 N D IH1 N ER0 K W OW1 T +'END-QUOTE EH1 N D K W OW1 T +'FRISCO F R IH1 S K OW0 +'GAIN G EH1 N +'INNER-QUOTE IH1 N ER0 K W OW1 T +'KAY K EY1 +'M AH0 M +'N AH0 N +'QUOTE K W OW1 T +'ROUND R AW1 N D +'S EH1 S +'SINGLE-QUOTE S IH1 NG G AH0 L K W OW1 T +'TIL T IH1 L +'TIS T IH1 Z +'TWAS T W AH1 Z +(BEGIN-PARENS B IH0 G IH1 N P ER0 EH1 N Z +(IN-PARENTHESES 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AE1 K S +ACTUAL AE1 K CH AH0 W AH0 L +ACTUAL(1) AE1 K SH AH0 L +ACTUALITY AE2 K CH UW0 AE1 L AH0 T IY2 +ACTUALIZE AE1 K CH UW2 AH0 L AY2 Z +ACTUALLY AE1 K CH UW2 AH0 L IY0 +ACTUALLY(1) AE1 K CH L IY0 +ACTUALLY(2) AE1 K SH AH0 L IY0 +ACTUARIAL AE2 K CH UW2 EH1 R IY0 AH0 L +ACTUARIES AE1 K CH UW2 EH1 R IY2 Z +ACTUARY AE1 K CH UW0 EH1 R IY2 +ACTUATE AE1 K CH UW2 EY1 T +ACTUATOR AE1 K T Y UW0 EY2 T ER0 +ACTUATOR(1) AE1 K CH UW0 EY2 T ER0 +ACTUATORS AE1 K T Y UW0 EY2 T ER0 Z +ACTUATORS(1) AE1 K CH UW0 EY2 T ER0 Z +ACTUS AE1 K T AH0 S +ACUFF AH0 K AH1 F +ACUITY AH0 K Y UW1 AH0 T IY0 +ACUMEN AH0 K Y UW1 M AH0 N +ACUNA AA0 K UW1 N AH0 +ACUPUNCTURE AE1 K Y UW0 P AH2 NG K CH ER0 +ACURA AE1 K Y ER0 AH0 +ACURA'S AE1 K Y ER0 AH0 Z +ACURAS AE1 K Y ER0 AH0 Z +ACUSON AE2 K Y UW1 S AH0 N +ACUSTAR AE1 K Y UW0 S T AA2 R +ACUSYST AE1 K Y UW0 S IH0 S T +ACUTE AH0 K Y UW1 T +ACUTELY AH0 K Y UW1 T L IY0 +ACUTENESS AH0 K Y UW1 T N AH0 S +ACYCLOVIR AH0 S IH1 K L OW0 V IH2 R +AD AE1 D +AD'S AE1 D Z +AD-HOC AE1 D HH AA1 K +AD-LIB AE1 D L IH1 B +AD-NAUSEAM AE1 D N AO1 Z IY0 AA0 M +AD-NAUSEUM AE1 D N AO1 Z IY0 AH0 M +ADA EY1 D AH0 +ADA'S EY1 D AH0 Z +ADABEL AE1 D AH0 B EH0 L +ADABELLE AE1 D AH0 B AH0 L +ADACHI AA0 D AA1 K IY0 +ADAGE AE1 D AH0 JH +ADAGIO AH0 D AA1 ZH IY0 OW2 +ADAH AE1 D AA0 +ADAIR AH0 D EH1 R +ADAIRE AA0 D EH1 R +ADAK AH0 D AE1 K +ADALAH AA0 D AA1 L AH0 +ADALIA AA0 D AA1 L IY0 AH0 +ADAM AE1 D AH0 M +ADAM'S AE1 D AH0 M Z +ADAMANT AE1 D AH0 M AH0 N T +ADAMANTLY AE1 D AH0 M AH0 N T L IY0 +ADAMCIK AA1 D AH0 M CH IH0 K +ADAMCZAK AA1 D AH0 M CH AE0 K +ADAMCZYK AA1 D AH0 M CH IH0 K +ADAME AA0 D AA1 M IY0 +ADAMEC AH0 D AA1 M EH0 K +ADAMEK AH0 D AA1 M EH0 K +ADAMES AH0 D EY1 M Z +ADAMI AA0 D AA1 M IY0 +ADAMIK AH0 D AA1 M IH0 K +ADAMINA AA0 D AA0 M IY1 N AH0 +ADAMKUS AE1 D AH0 M K AH0 S +ADAMO AA0 D AA1 M OW0 +ADAMOWICZ AH0 D AA1 M AH0 V IH0 CH +ADAMS AE1 D AH0 M Z +ADAMS' AE1 D AH0 M Z +ADAMS'S AE1 D AH0 M Z IH0 Z +ADAMSKI AH0 D AE1 M S K IY2 +ADAMSON AE1 D AH0 M S AH0 N +ADAMSTOWN AE1 D AH0 M S T AW2 N +ADAN EY1 D AH0 N +ADAPSO AH0 D AE1 P S OW0 +ADAPT AH0 D AE1 P T +ADAPTABILITY AH0 D AE2 P T AH0 B IH1 L AH0 T IY0 +ADAPTABLE AH0 D AE1 P T AH0 B AH0 L +ADAPTAPLEX AH0 D AE1 P T AH0 P L EH2 K S +ADAPTATION AE2 D AH0 P T EY1 SH AH0 N +ADAPTATIONS AE2 D AE0 P T EY1 SH AH0 N Z +ADAPTATIONS(1) AE2 D AH0 P T EY1 SH AH0 N Z +ADAPTEC AH0 D AE1 P T EH2 K +ADAPTEC'S AH0 D AE1 P T EH2 K S +ADAPTED AH0 D AE1 P T IH0 D +ADAPTER AH0 D AE1 P T ER0 +ADAPTERS AH0 D AE1 P T ER0 Z +ADAPTING AH0 D AE1 P T IH0 NG +ADAPTIVE AH0 D AE1 P T IH0 V +ADAPTOR AH0 D AE1 P T ER0 +ADAPTORS AH0 D AE1 P T ER0 Z +ADAPTS AH0 D AE1 P T S +ADAR AH0 D AA1 R +ADARAND AE1 D AH0 R AE2 N D +ADAS EY1 D AH0 Z +ADAY AH0 D EY1 +ADAZA AH0 D AA1 Z AH0 +ADCOCK AH0 D K AA1 K +ADCOX AH0 D K AA1 K S +ADD AE1 D +ADDAIR AH0 D EH1 R +ADDAMS AE1 D AH0 M Z +ADDED AE1 D IH0 D +ADDENDUM AH0 D EH1 N D AH0 M +ADDENDUMS AH0 D EH1 N D AH0 M Z +ADDEO AA1 D IY0 OW0 +ADDER AE1 D ER0 +ADDERLEY AH0 D ER1 L IY0 +ADDICKS AE1 D IH0 K S +ADDICT AH0 D IH1 K T +ADDICT(1) AE1 D IH2 K T +ADDICTED AH0 D IH1 K T IH0 D +ADDICTING AH0 D IH1 K T IH0 NG +ADDICTION AH0 D IH1 K SH AH0 N +ADDICTIONS AH0 D IH1 K SH AH0 N Z +ADDICTIVE AH0 D IH1 K T IH0 V +ADDICTS AH0 D IH1 K T S +ADDICTS(1) AE1 D IH2 K T S +ADDIDAS AH0 D IY1 D AH0 S +ADDIDAS' AH0 D IY1 D AH0 S +ADDIDAS'S AH0 D IY1 D AH0 S IH0 Z +ADDIDASES AH0 D IY1 D AH0 S IH0 Z +ADDIE AE1 D IY0 +ADDING AE1 D IH0 NG +ADDINGTON AE1 D IH0 NG T AH0 N +ADDIS AA1 D IH0 S +ADDIS-ABABA AA1 D IH0 S AH0 B AA1 B AA0 +ADDIS-ABABA(1) AA1 D IY0 S AH0 B AA1 B AA0 +ADDISON AE1 D IH0 S AH0 N +ADDISON'S AE1 D IH0 S AH0 N Z +ADDITION AH0 D IH1 SH AH0 N +ADDITIONAL AH0 D IH1 SH AH0 N AH0 L +ADDITIONALLY AH0 D IH1 SH AH0 N AH2 L IY0 +ADDITIONS AH0 D IH1 SH AH0 N Z +ADDITIVE AE1 D IH0 T IH0 V +ADDITIVES AE1 D IH0 T IH0 V Z +ADDLE AE1 D AH0 L +ADDLED AE1 D AH0 L D +ADDLEMAN AE1 D AH0 L M AH0 N +ADDRESS AE1 D R EH2 S +ADDRESS(1) AE0 D R EH1 S +ADDRESSABLE AE0 D R EH1 S AH0 B AH0 L +ADDRESSED AH0 D R EH1 S T +ADDRESSEE AE2 D R EH0 S IY1 +ADDRESSES AE1 D R EH1 S IH0 Z +ADDRESSES(1) AE0 D R EH1 S IH0 Z +ADDRESSING AE0 D R EH1 S IH0 NG +ADDS AE1 D Z +ADDUCI AA0 D UW1 CH IY0 +ADDUCT AE1 D AH0 K T +ADDWEST AE2 D W EH1 S T +ADDY AE1 D IY0 +ADDYSTON AE1 D IY0 S T AH0 N +ADE EY1 D +ADEE AH0 D IY1 +ADEL AH0 D EH1 L +ADELA AH0 D EH1 L AH0 +ADELAAR AE1 D AH0 L AA2 R +ADELAIDE AE1 D AH0 L EY2 D +ADELANTO AE0 D AH0 L AA1 N T OW0 +ADELBERT AH0 D EH1 L B ER0 T +ADELE AH0 D EH1 L +ADELE'S AH0 D EH1 L Z +ADELINE AE1 D AH0 L AY2 N +ADELIZZI AE2 D AH0 L IY1 Z IY0 +ADELL AH0 D EH1 L +ADELL'S AH0 D EH1 L Z +ADELLE AH0 D EH1 L +ADELMAN AE1 D AH0 L M AH0 N +ADELMAN(1) EH1 D AH0 L M AH0 N +ADELMANN AE1 D AH0 L M AH0 N +ADELPHA AH0 D EH1 L F AH0 +ADELPHI AH0 D EH1 L F IY0 +ADELPHIA AH0 D EH1 L F IY0 AH0 +ADELPHIA'S AH0 D EH1 L F IY0 AH0 Z +ADELSBERGER AE1 D IH0 L Z B ER0 G ER0 +ADELSON AE1 D AH0 L S AH0 N +ADELSTEIN AE1 D AH0 L S T AY0 N +ADELSTEIN(1) AE1 D AH0 L S T IY0 N +ADEN EY1 D AH0 N +ADENA AE1 D IH0 N 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AH0 JH AH1 S T AH0 B AH0 L +ADJUSTABLES AH0 JH AH1 S T AH0 B AH0 L Z +ADJUSTED AH0 JH AH1 S T IH0 D +ADJUSTER AH0 JH AH1 S T ER0 +ADJUSTERS AH0 JH AH1 S T ER0 Z +ADJUSTING AH0 JH AH1 S T IH0 NG +ADJUSTMENT AH0 JH AH1 S T M AH0 N T +ADJUSTMENTS AH0 JH AH1 S T M AH0 N T S +ADJUSTS AH0 JH AH1 S T S +ADJUTANT AE1 JH AH0 T AH0 N T +ADKINS AE1 D K IH0 N Z +ADKINSON AE1 D K IH0 N S AH0 N +ADKISON AE1 D K IH0 S AH0 N +ADKISSON AE1 D K IH0 S AH0 N +ADL-TABATABA AA2 D AH0 L T AA2 B AH0 T AA1 B AH0 +ADL-TABATABAI AA2 D AH0 L T AA2 B AH0 T AH2 B AY1 +ADLAI AA0 D L AA1 IY0 +ADLER AE1 D L ER0 +ADLER'S AE1 D L ER0 Z +ADLERS AE1 D L ER0 Z +ADLEY AE1 D L IY0 +ADLON AE1 D L AA0 N +ADLONG AE1 D L AO0 NG +ADMAN AE1 D M AH0 N +ADMEN AE1 D M AH0 N +ADMIN AE1 D M IH0 N +ADMINISTER AH0 D M IH1 N IH0 S T ER0 +ADMINISTERED AH0 D M IH1 N IH0 S T ER0 D +ADMINISTERING AE0 D M IH1 N IH0 S T ER2 IH0 NG +ADMINISTERS AE0 D M IH1 N IH0 S T ER0 Z +ADMINISTRATE AE0 D M IH1 N IH0 S T R EY2 T +ADMINISTRATING AH0 D M IH1 N IH0 S T R EY2 T IH0 NG +ADMINISTRATION AE0 D M IH2 N IH0 S T R EY1 SH AH0 N +ADMINISTRATION'S AE0 D M IH2 N IH0 S T R EY1 SH AH0 N Z +ADMINISTRATIONS AE0 D M IH2 N IH0 S T R EY1 SH AH0 N Z +ADMINISTRATIONS' AE0 D M IH2 N IH0 S T R EY1 SH AH0 N Z +ADMINISTRATIVE AH0 D M IH1 N IH0 S T R EY2 T IH0 V +ADMINISTRATIVELY AE0 D M IH2 N IH0 S T R EY1 T IH0 V L IY0 +ADMINISTRATOR AH0 D M IH1 N IH0 S T R EY2 T ER0 +ADMINISTRATOR'S AE0 D M IH1 N IH0 S T R EY2 T ER0 Z +ADMINISTRATORS AE0 D M IH1 N IH0 S T R EY2 T ER0 Z +ADMINISTRATORS' AE0 D M IH1 N IH0 S T R EY2 T ER0 Z +ADMINS AE1 D M IH0 N Z +ADMIRA AE0 D M AY1 R AH0 +ADMIRA'S AE0 D M AY1 R AH0 Z +ADMIRABLE AE1 D M ER0 AH0 B AH0 L +ADMIRABLE(1) AE1 D M R AH0 B AH0 L +ADMIRABLY AE1 D M ER0 AH0 B L IY0 +ADMIRAL AE1 D M ER0 AH0 L +ADMIRAL'S AE1 D M ER0 AH0 L Z +ADMIRALS AE1 D M ER0 AH0 L Z +ADMIRALTY AE1 D M ER0 AH0 L T IY0 +ADMIRATION AE2 D M ER0 EY1 SH AH0 N +ADMIRATIONS AE2 D M ER0 EY1 SH AH0 N Z +ADMIRE AE0 D M AY1 R +ADMIRED AH0 D M AY1 ER0 D 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D OW1 B IY0 Z +ADOLESCENCE AE2 D AH0 L EH1 S AH0 N S +ADOLESCENCE(1) AE2 D OW0 L EH1 S AH0 N S +ADOLESCENT AE2 D AH0 L EH1 S AH0 N T +ADOLESCENT(1) AE2 D OW0 L EH1 S AH0 N T +ADOLESCENTS AE2 D AH0 L EH1 S AH0 N T S +ADOLESCENTS(1) AE2 D OW0 L EH1 S AH0 N T S +ADOLF EY1 D AA0 L F +ADOLF'S EY1 D AA0 L F S +ADOLFO AH0 D AA1 L F OW2 +ADOLPH EY1 D AO0 L F +ADOLPHA AA0 D OW1 L F AH0 +ADOLPHSON AE1 D OW0 L F S AH0 N +ADOLPHUS AH0 D AO1 L F AH0 S +ADON AA0 D AO1 N +ADONIA AA0 D OW1 N IY0 AH0 +ADONIS AH0 D AA1 N AH0 S +ADOPT AH0 D AA1 P T +ADOPTABLE AH0 D AA1 P T AH0 B AH0 L +ADOPTED AH0 D AA1 P T IH0 D +ADOPTEE AH0 D AA1 P T IY1 +ADOPTEES AH0 D AA1 P T IY1 Z +ADOPTER AH0 D AA1 P T ER0 +ADOPTERS AH0 D AA1 P T ER0 Z +ADOPTING AH0 D AA1 P T IH0 NG +ADOPTION AH0 D AA1 P SH AH0 N +ADOPTIONS AH0 D AA1 P SH AH0 N Z +ADOPTIVE AH0 D AA1 P T IH0 V +ADOPTS AH0 D AA1 P T S +ADOR AA0 D AO1 R +ADORA AA0 D AO1 R AH0 +ADORABELLE AE1 D ER0 AH0 B AH0 L +ADORABLE AH0 D AO1 R AH0 B AH0 L +ADORATION AE2 D ER0 EY1 SH AH0 N +ADORE AH0 D AO1 R +ADORED AH0 D AO1 R D +ADOREE AE0 D ER0 IY1 +ADOREES AE0 D ER0 IY1 Z +ADORES AH0 D AO1 R Z +ADORING AH0 D AO1 R IH0 NG +ADORN AH0 D AO1 R N +ADORNA AA0 D AO1 R N AH0 +ADORNED AH0 D AO1 R N D +ADORNING AH0 D AO1 R N IH0 NG +ADORNMENT AH0 D AO1 R N M AH0 N T +ADORNO AA0 D AO1 R N OW0 +ADORNS AH0 D AO1 R N Z +ADRA EY1 D R AH0 +ADRAGNA AA0 D R AA1 G N AH0 +ADRDA EY1 D ER0 D AH0 +ADREA AA1 D R IY0 AH0 +ADRENAL AH0 D R IY1 N AH0 L +ADRENALIN AH0 D R EH1 N AH0 L IH0 N +ADRENALINE AH0 D R EH1 N AH0 L AH0 N +ADRENERGIC AH0 D R EH0 N EH1 R JH IH0 K +ADRIA AA1 D R IY0 AH0 +ADRIAN EY1 D R IY0 AH0 N +ADRIANA EY2 D R IY0 AE1 N AH0 +ADRIANCE AA0 D R IY1 AH0 N S +ADRIANO AA0 D R IY0 AA1 N OW0 +ADRIATIC EY2 D R IY0 AE1 T IH0 K +ADRIEL AH0 D R IY1 L +ADRIENNE AA0 D R IY0 EH1 N +ADRIFT AH0 D R IH1 F T +ADROIT AH0 D R OY1 T +ADROITLY AH0 D R OY1 T L IY0 +ADS AE1 D Z +ADS' AE1 D Z +ADSIT AE1 D S IH0 T +ADSL EY2 D IY2 EH2 S EH1 L +ADSORPTION AH0 D S AO1 R P SH AH0 N +ADSS AE1 D S 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T S +AFTERTASTES(1) AE1 F T ER0 T EY2 S +AFTERTAX AE1 F T ER0 T AE2 K S +AFTERTHOUGHT AE1 F T ER0 TH AA2 T +AFTERTHOUGHT(1) AE1 F T ER0 TH AO2 T +AFTERTHOUGHTS AE1 F T ER0 TH AA2 T S +AFTERTHOUGHTS(1) AE1 F T ER0 TH AO2 T S +AFTERWARD AE1 F T ER0 W ER0 D +AFTERWARDS AE1 F T ER0 W ER0 D Z +AFULA AH0 F UW1 L AH0 +AFULA'S AH0 F UW1 L AH0 Z +AG AE1 G +AG(1) EY1 G IY1 +AG'S AE1 G Z +AGA AA1 G AH0 +AGACHE AE1 G AE0 CH +AGACHE'S AE1 G AE0 CH AH0 Z +AGACHES AE1 G AE0 CH AH0 Z +AGAIN AH0 G EH1 N +AGAIN(1) AH0 G EY1 N +AGAINST AH0 G EH1 N S T +AGAINST(1) AH0 G EY1 N S T +AGAMEMNON AE2 G AH0 M EH1 M N AA2 N +AGAMEMNON'S AE2 G AH0 M EH1 M N AA2 N Z +AGAN EY1 G AH0 N +AGANA AH0 G AA1 N AH0 +AGANBEGYAN AE2 G AH0 N B EH1 G Y AH0 N +AGANS AA1 G AA0 N Z +AGAPE AH0 G EY1 P +AGAR EY1 G ER0 +AGARD AE1 G ER0 D +AGARWAL AA1 G AA0 R W AA0 L +AGASP AH0 G AE1 S P +AGASSI AE1 G AH0 S IY0 +AGASSIZ AH0 G AE1 S IH0 Z +AGATE AE1 G AH0 T +AGATES AE1 G AH0 T S +AGATHA AE1 G AH0 TH AH0 +AGAWAM AE1 G AH0 W AA2 M +AGCO 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EH1 R L IH2 NG K +AIRLINKS EH1 R L IH2 NG K S +AIRLOCK EH1 R L AO2 K +AIRLOCKS EH1 R L AO2 K S +AIRMAIL EH1 R M EY2 L +AIRMAN EH1 R M AH0 N +AIRMAN'S EH1 R M AH0 N Z +AIRMEN EH1 R M EH2 N +AIRMOTIVE EH2 R M OW1 T IH0 V +AIRPLANE EH1 R P L EY2 N +AIRPLANE'S EH1 R P L EY0 N Z +AIRPLANES EH1 R P L EY0 N Z +AIRPORT EH1 R P AO2 R T +AIRPORT'S EH1 R P AO2 R T S +AIRPORTER EH1 R P AO2 R T ER0 +AIRPORTERS EH1 R P AO2 R T ER0 Z +AIRPORTS EH1 R P AO2 R T S +AIRPOWER EH1 R P AW2 ER0 +AIRS EH1 R Z +AIRSHARE EH1 R SH EH0 R +AIRSHIP EH1 R SH IH2 P +AIRSHIPS EH1 R SH IH2 P S +AIRSPACE EH1 R S P EY2 S +AIRSPACES EH1 R S P EY2 S IH0 Z +AIRSPEED EH1 R S P IY2 D +AIRSTRIKE EH1 R S T R AY2 K +AIRSTRIKES EH1 R S T R AY2 K S +AIRSTRIP EH1 R S T R IH2 P +AIRSTRIPS EH1 R S T R IH2 P S +AIRTIGHT EH1 R T AY2 T +AIRTIME EH1 R T AY2 M +AIRTOUCH EH1 R T AH2 CH +AIRTRAN EH1 R T R AE2 N +AIRWAVE EH1 R W EY2 V +AIRWAVES EH1 R W EY2 V Z +AIRWAY EH1 R W EY2 +AIRWAY'S EH1 R W EY2 Z +AIRWAYS EH1 R W EY2 Z +AIRWAYS' EH1 R 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HH IY1 T OW0 +AKA AA1 K AH0 +AKA(1) EY1 K EY1 EY1 +AKAI AH0 K AY1 +AKAKA AH0 K AA1 K AH0 +AKALI AH0 K AA1 L IY0 +AKAMINE AE1 K AH0 M AY2 N +AKANA AA0 K AA1 N AH0 +AKAO AH0 K EY1 OW0 +AKAO(1) AH0 K AA1 W +AKARD AE1 K ER0 D +AKASHI AH0 K AA1 SH IY0 +AKASHI'S AH0 K AA1 SH IY0 Z +AKBAR AE1 K B ER0 +AKBAR(1) AA1 K B AA2 R +AKBASH AE1 K B AE0 SH +AKC AE1 K +AKE EY1 K +AKEBONO AE2 K IY0 B OW1 N OW0 +AKEL AH0 K EH1 L +AKELLA AH0 K EH1 L AH0 +AKEN EY1 K AH0 N +AKENS EY1 K AH0 N Z +AKER AE1 K ER0 +AKER(1) EY1 K ER0 +AKERLEY AH0 K ER1 L IY0 +AKERMAN AE1 K ER0 M AH0 N +AKERS EY1 K ER0 Z +AKERS'S EY1 K ER0 Z IH0 Z +AKERSON AE1 K ER0 S AH0 N +AKEY AH0 K IY1 +AKHTAR AE1 K T ER0 +AKI AA1 K IY0 +AKIBA AH0 K IY1 B AH0 +AKIHITO AA2 K IY0 HH IY1 T OW2 +AKIKO AH0 K IY1 K OW0 +AKIMBO AH0 K IH1 M B OW2 +AKIN AH0 K IH1 N +AKIN(1) EY1 K IH0 N +AKINS AH0 K IH1 N Z +AKINS(1) EY1 K IH0 N Z +AKIO AA1 K IY0 OW0 +AKIRA AH0 K IY1 R AH0 +AKITA AH0 K IY1 T AH0 +AKITA'S AH0 K IY1 T AH0 Z +AKIVA AH0 K IY1 V AH0 +AKIYAMA 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+BALZAC B AA0 L Z AE1 K +BALZANO B AA0 L Z AA1 N OW0 +BALZARINI B AA0 L Z AA0 R IY1 N IY0 +BALZER B EY1 L Z ER0 +BAM B AE1 M +BAMAKO B AE1 M AH0 K OW0 +BAMBA B AE1 M B AH0 +BAMBACH B AE1 M B AA2 K +BAMBENEK B AE0 M B EH1 N EH0 K +BAMBER B AE1 M B ER0 +BAMBERG B AE1 M B ER0 G +BAMBERGER B AE1 M B ER0 G ER0 +BAMBI B AE1 M B IY0 +BAMBINO B AE2 M B IY1 N OW0 +BAMBINOS B AE2 M B IY1 N OW0 Z +BAMBOO B AE0 M B UW1 +BAMBRICK B AE1 M B R IH0 K +BAMBURG B AE1 M B ER0 G +BAME B EY1 M +BAMFORD B AE1 M F ER0 D +BAMUT B AE1 M AH0 T +BAN B AE1 N +BAN'S B AE1 N Z +BANACCI B AH0 N AA1 CH IY0 +BANACH B AE1 N AH0 K +BANAL B AH0 N AA1 L +BANALITIES B AH0 N AE1 L IH0 T IY0 Z +BANALITY B AH0 N AE1 L IH0 T IY0 +BANAMEX B AE1 N AH0 M EH2 K S +BANANA B AH0 N AE1 N AH0 +BANANAS B AH0 N AE1 N AH0 Z +BANAS B AE1 N AH0 Z +BANASIAK B AH0 N AA1 S IY0 AE0 K +BANASZAK B AH0 N AA1 SH AH0 K +BANBURY B AE1 N B EH2 R IY0 +BANC B AE1 NG K +BANCA B AE1 NG K AH0 +BANCA(1) B AA1 NG K AH0 +BANCAIRE B AE0 N K EH1 R +BANCARIO B AE0 N K EH1 R IY0 OW0 +BANCO B AE1 NG K OW0 +BANCOKLAHOMA B AE0 NG K AA2 K L AH0 HH OW1 M AH0 +BANCOMER B AE1 NG K AH0 M ER0 +BANCOR B AE1 N K AO2 R +BANCORP B AE1 NG K AO0 R P +BANCORP(1) B AE1 N K AO0 R P +BANCORP'S B AE1 NG K AO0 R P S +BANCORP'S(1) B AE1 N K AO0 R P S +BANCORPORATION B AE1 N K AO2 R P ER0 EY0 SH AH0 N +BANCROFT B AE1 NG K R AO0 F T +BANCROFT'S B AE1 N K R AO2 F T S +BANCSERVE B AE1 N K S ER0 V +BANCSHARES B AE1 NG K SH EH0 R Z +BANCSHARES' B AE0 NG K SH EH1 R Z +BANCTEC B AE1 NG K T EH2 K +BANCTEXAS B AE0 NG K T EH1 K S AH0 S +BAND B AE1 N D +BAND'S B AE1 N D Z +BANDA B AE1 N D AH0 +BANDAG B AE1 N D AE2 G +BANDAGE B AE1 N D IH0 JH +BANDAGED B AE1 N D AH0 JH D +BANDAGES B AE1 N D AH0 JH AH0 Z +BANDAGES(1) B AE1 N D IH0 JH IH0 Z +BANDAI B AE2 N D AY1 +BANDAID B AE1 N D EY0 D +BANDANA B AE2 N D AE1 N AH0 +BANDANAS B AE2 N D AE1 N AH0 Z +BANDAR B AE1 N D AA0 R +BANDED B AE1 N D IH0 D +BANDEL B AE1 N D AH0 L +BANDEMER B AE1 N D IY0 M ER0 +BANDER B AE1 N D ER0 +BANDERAS B AE0 N D ER1 AH0 S +BANDERAS(1) B AA0 N D ER0 AH1 S +BANDICOOT B AE1 N D IH0 K UW2 T +BANDICOOT(1) B AE1 N D IY0 K UW2 T +BANDICOOTS B AE1 N D IH0 K UW2 T S +BANDICOOTS(1) B AE1 N D IY0 K UW2 T S +BANDIED B AE1 N D IY0 D +BANDING B AE1 N D IH0 NG +BANDIT B AE1 N D AH0 T +BANDITRY B AE1 N D AH0 T R IY0 +BANDITS B AE1 N D AH0 T S +BANDLEADER B AE1 N D L IY0 D ER0 +BANDLEADERS B AE1 N D L IY0 D ER0 Z +BANDOLIER B AE2 N D AH0 L IH1 R +BANDOLIERS B AE2 N D AH0 L IH1 R Z +BANDOW B AE1 N D AW2 +BANDOW'S B AE1 N D AW2 Z +BANDS B AE1 N D Z +BANDSHELL B AE0 N D SH EH1 L +BANDSTAND B AE1 N D S T AE2 N D +BANDT B AE1 N T +BANDUCCI B AA0 N D UW1 CH IY0 +BANDWAGON B AE1 N D W AE2 G AH0 N +BANDWIDTH B AE1 N D W IH0 D TH +BANDY B AE1 N D IY0 +BANE B EY1 N +BANEGAS B AE1 N IH0 G AH0 Z +BANERJEE B AH0 N ER1 JH IY0 +BANES B EY1 N Z +BANESTO B AH0 N EH1 S T OW0 +BANESTO'S B AH0 N EH1 S T OW0 Z +BANET B AE1 N IH0 T +BANEY B EY1 N IY0 +BANFF B AE1 N F +BANFIELD B AE1 N F IY2 L D +BANFORD B AE1 N F ER0 D +BANG B AE1 NG +BANGALA B AA0 N G AA1 L AH0 +BANGALOR B AE1 NG G AH0 L AO2 R +BANGALORE B AE1 NG G AH0 L AO2 R +BANGALORE'S B AE1 NG G AH0 L AO2 R Z +BANGE B AE1 N JH +BANGED B AE1 NG D +BANGEE B AE1 N JH IY0 +BANGEMANN B AE1 NG G AH0 M AH0 N +BANGER B AE1 NG ER0 +BANGERS B AE1 NG ER0 Z +BANGERT B EY1 NG G ER0 T +BANGERTER B EY1 NG G ER0 T ER0 +BANGHART B AE1 NG HH AA2 R T +BANGING B AE1 NG IH0 NG +BANGISH B AE1 NG IH0 SH +BANGKOK B AE0 NG K AA1 K +BANGKOK(1) B AE1 NG K AA0 K +BANGKOK'S B AE1 NG K AA0 K S +BANGLA B AE1 NG L AA2 +BANGLADESH B AE1 NG L AH0 D EH2 SH +BANGLADESH'S B AE1 NG L AH0 D EH2 SH IH0 Z +BANGLADESHI B AE1 NG L AH0 D EH2 SH IY0 +BANGLADESHI'S B AE1 NG L AH0 D EH2 SH IY0 Z +BANGLADESHIS B AE1 NG L AH0 D EH2 SH IY0 Z +BANGLE B AE1 NG G AH0 L +BANGLES B AE1 NG G AH0 L Z +BANGO B AA1 NG G OW0 +BANGOR B AE1 NG G ER0 +BANGOR(1) B AE1 NG G AO2 R +BANGS B AE1 NG Z +BANH B AA1 N +BANIA B AA1 N IY0 AH0 +BANICK B AE1 N IH0 K +BANIK B AE1 N IH0 K +BANIS B AE1 N IH0 S +BANISH B AE1 N IH0 SH +BANISHED B AE1 N IH0 SH T +BANISHING B AE1 N IH0 SH IH0 NG +BANISHMENT B AE1 N IH0 SH M AH0 N T +BANISTER B AE1 N IH0 S T ER0 +BANJA B AA1 N Y AH0 +BANJO B AE1 N JH OW2 +BANK B AE1 NG K +BANK'S B AE1 NG K S +BANKABLE B AE1 NG K AH0 B AH0 L +BANKAMERICA B AE2 NG K AH0 M EH1 R IH0 K AH0 +BANKAMERICA'S B AE2 NG K AH0 M EH1 R IH0 K AH0 Z +BANKATLANTIC B AE2 NG K AH0 T L AE1 N T IH0 K +BANKBOOK B AE1 NG K B UH2 K +BANKCARD B AE1 NG K AA2 R D +BANKCARDS B AE1 NG K AA2 R D Z +BANKCORP B AE1 NG K AO2 R P +BANKE B AE1 NG K +BANKEAST B AE2 NG K IY1 S T +BANKED B AE1 NG K T +BANKEN B AE1 NG K AH0 N +BANKER B AE1 NG K ER0 +BANKER'S B AE1 NG K ER0 Z +BANKERS B AE1 NG K ER0 Z +BANKERS' B AE1 NG K ER0 Z +BANKERT B AE1 NG K ER0 T +BANKES B AE1 NG K S +BANKEY B AE1 N K IY2 +BANKHEAD B AE1 NG K HH EH2 D +BANKHOLDING B AE1 NG K HH OW2 L D IH0 NG +BANKING B AE1 NG K IH0 NG +BANKING'S B AE1 NG K IH0 NG Z +BANKNOTE B AE1 NG K N OW2 T +BANKNOTES B AE1 NG K N OW2 T S +BANKO B AE1 NG K OW0 +BANKOWSKI B AH0 NG K AO1 F S K IY0 +BANKROLL B AE1 NG K R OW2 L +BANKROLLED B AE1 NG K R OW2 L D +BANKROLLING B AE1 NG K R OW2 L IH0 NG +BANKROLLS B AE1 NG K R OW2 L Z +BANKRUPCTY B AE1 NG K R AH0 P T S IY0 +BANKRUPT B AE1 NG K R AH0 P T +BANKRUPTCIES B AE1 NG K R AH0 P T S IY0 Z +BANKRUPTCY B AE1 NG K R AH0 P S IY0 +BANKRUPTCY(1) B AE1 NG K R AH0 P T S IY0 +BANKRUPTCY'S B AE1 NG K R AH0 P S IY0 Z +BANKRUPTED B AE1 NG K R AH0 P T IH0 D +BANKRUPTING B AE1 NG K R AH2 P T IH0 NG +BANKS B AE1 NG K S +BANKS' B AE1 NG K S +BANKS'S B AE1 NG K S IH0 Z +BANKSHARE B AE1 NG K SH EH2 R +BANKSHARES B AE1 NG K SH EH2 R Z +BANKSON B AE1 NG K S AH0 N +BANKSTON B AE1 NG K S T AH0 N +BANKVEREIN B AE1 NG K V ER0 AY2 N +BANKVERMONT B AE1 NG K V ER0 M AA1 N T +BANKWORCESTER B AE1 NG K W ER1 CH EH2 S T ER0 +BANKWORCESTER(1) B AE1 NG K W UW1 S T ER0 +BANN B AE1 N +BANNAN B AE1 N AH0 N +BANNED B AE1 N D +BANNER B AE1 N ER0 +BANNER'S B AE1 N ER0 Z +BANNERMAN B AE1 N ER0 M AH0 N +BANNERS B AE1 N ER0 Z +BANNICK B AE1 N IH0 K +BANNING B AE1 N IH0 NG +BANNINGS B AE1 N IH0 NG Z +BANNISTER B AE1 N AH0 S T ER0 +BANNISTER(1) B AE1 N IH0 S T ER0 +BANNON B AE1 N AH0 N +BANOS B AA1 N OW0 Z +BANOUN B AH0 N UW1 N +BANPAIS B AE2 N P EY1 +BANPONCE B AE1 N P AA0 N S +BANQUE B AE1 NG K +BANQUET B AE1 NG K W AH0 T +BANQUETS B AE1 NG K W AH0 T S +BANQUO'S B AE1 NG K W OW0 Z +BANS B AE1 N Z +BANSAL B AA0 N S AA1 L +BANSHEE B AE0 N SH IY1 +BANSHEE(1) B AE1 N SH IY0 +BANTA B AE1 N T AH0 +BANTAM B AE1 N T AH0 M +BANTAM'S B AE1 N T AH0 M Z +BANTAMS B AE1 N T AH0 M Z +BANTER B AE1 N T ER0 +BANTERED B AE1 N T ER0 D +BANTERING B AE1 N T ER0 IH0 NG +BANTLE B AE1 N T AH0 L +BANTON B AE1 N T AH0 N +BANTU B AE1 N T UW0 +BANTZ B AE1 N T S +BANUELOS B AA0 N W EH1 L OW0 Z +BANVILLE B AA1 N V IH0 L +BANWART B AE1 N W AO2 R T +BANXQUOTE B AE1 NG K S K W OW2 T +BANYA B AA1 N Y AH0 +BANYA(1) B AE1 N Y AH0 +BANYALUCA B AE1 N Y AH0 L UW2 K AH0 +BANYAN B AE1 N Y AH0 N +BANYAS B AA1 N Y AH0 Z +BANYAS(1) B AE1 N Y AH0 Z +BANYU B AA1 N Y UW2 +BANZHAF B AE1 N Z HH AH0 F +BAO B AW1 +BAOGUANG B AA1 AO0 G W AE2 NG +BAPLEY B AE1 P L IY0 +BAPNA B AA1 P N AH0 +BAPTISM B AE1 P T IH0 Z AH0 M +BAPTISMAL B AE0 P T IH1 Z M AH0 L +BAPTISMS B AE1 P T IH2 Z AH0 M Z +BAPTIST B AE1 P T AH0 S T +BAPTIST(1) B AE1 P T IH0 S T +BAPTISTA B AE2 P T IH1 S T AH0 +BAPTISTE B AH0 P T IH1 S T +BAPTISTERY B AE1 P T AH0 S T R IY0 +BAPTISTS B AE1 P T AH0 S T S +BAPTISTS(1) B AE1 P T AH0 S +BAPTIZE B AE0 P T AY1 Z +BAPTIZED B AE0 P T AY1 Z D +BAPTIZED(1) B AE1 P T AY2 Z D +BAR B AA1 R +BAR'S B AA1 R Z +BAR-MITZVAH B AA1 R M IH1 T S V AH0 +BARA B AA1 R AH0 +BARABAR B EH1 R AH0 B AA0 R +BARACH B AH0 R AA1 K +BARACH(1) B ER0 AA1 K +BARACK B AA1 R AH0 K +BARAFF B AA0 R AA1 F +BARAGI B AH0 R AA1 G IY0 +BARAHONA B AE2 R AH0 HH OW1 N AH0 +BARAJAS B AA0 R AA1 Y AA0 Z +BARAK B AA1 R AH0 K +BARAKAT B AA1 R AH0 K AA2 T +BARAM B EH1 R AE0 M +BARAN B AA0 R AA1 N +BARANEK B AE1 R AH0 N IH0 K +BARANOSKI B ER0 AH0 N AW1 S K IY0 +BARANOWSKI B ER0 AH0 N AO1 F S K IY0 +BARANSKI B ER0 AE1 N S K IY0 +BARANY B ER0 AO1 N IY0 +BARASCH B AE1 R AH0 SH +BARASH B AE1 R AH0 SH +BARATH B AE1 R AH0 TH +BARATTA B AA0 R AA1 T AH0 +BARB B AA1 R B +BARB'S B AA1 R B Z +BARBA B AA1 R B AH0 +BARBADOS B AA0 R B EY1 D OW0 S +BARBAGALLO B AA2 R B AH0 G AE1 L OW0 +BARBAKOW B AA1 R B AH0 K AW2 +BARBANEL B AA1 R B AH0 N AH0 L +BARBANO B AA0 R B AA1 N OW0 +BARBARA B AA1 R B ER0 AH0 +BARBARA(1) B AA1 R B R AH0 +BARBARA'S B AA1 R B ER0 AH0 Z +BARBAREE B AA1 R B ER0 IY1 +BARBARIAN B AA0 R B EH1 R IY0 AH0 N +BARBARIANS B AA0 R B EH1 R IY0 AH0 N Z +BARBARIC B AA0 R B AE1 R IH0 K +BARBARIC(1) B AA0 R B EH1 R IH0 K +BARBARINO B AA0 R B AA0 R IY1 N OW0 +BARBARISM B AA1 R B ER0 IH2 Z AH0 M +BARBARITY B AA0 R B AE1 R AH0 T IY0 +BARBARITY(1) B AA0 R B EH1 R AH0 T IY0 +BARBARO B AA0 R B AA1 R OW0 +BARBAROUS B AA1 R B ER0 AH0 S +BARBARY B AA1 R B ER0 IY0 +BARBASH B AA1 R B AE2 SH +BARBATO B AA0 R B AA1 T OW0 +BARBE B AA1 R B +BARBEAU B AA0 R B OW1 +BARBECUE B AA1 R B IH0 K Y UW2 +BARBECUE'S B AA1 R B IH0 K Y UW2 Z +BARBECUED B AA1 R B IH0 K Y UW2 D +BARBECUEING B AA1 R B IH0 K Y UW2 IH0 NG +BARBECUES B AA1 R B IH0 K Y UW2 Z +BARBED B AA1 R B D +BARBED-WIRE B AA1 R B D W AY1 R +BARBEE B AA1 R B IY1 +BARBEL B AA1 R B EH2 L +BARBELL B AA1 R B EH2 L +BARBELLA B AA2 R B EH1 L AH0 +BARBELLS B AA1 R B EH2 L Z +BARBELS B AA1 R B AH0 L Z +BARBEQUE B AA1 R B IH0 K Y UW2 +BARBEQUED B AA1 R B IH0 K Y UW2 D +BARBEQUEING B AA1 R B IH0 K Y UW2 IH0 NG +BARBEQUES B AA1 R B IH0 K Y UW2 Z +BARBER B AA1 R B ER0 +BARBER'S B AA1 R B ER0 Z +BARBERA B AA0 R B EH1 R AH0 +BARBERI B AA0 R B EH1 R IY0 +BARBERIO B AA2 R B IY1 R IY0 OW0 +BARBERIS B AA1 R B ER0 IH0 S +BARBERO B AA0 R B EH1 R OW0 +BARBERS B AA1 R B ER0 Z +BARBERSHOP B AA1 R B ER0 SH AA2 P +BARBETTE B AA0 R B EH1 T +BARBIAN B AA1 R B IY0 AH0 N +BARBIE B AA1 R B IY0 +BARBIE'S B AA1 R B IY0 Z +BARBIER B AA1 R B IY0 ER0 +BARBIERI B AA0 R B IH1 R IY0 +BARBIERI'S B AA0 R B IH1 R IY0 Z +BARBIES B AA1 R B IY0 Z +BARBIN B AA1 R B IH0 N +BARBITURATE B AA0 R B IH1 CH ER0 AH0 T +BARBITURATES B AA0 R B IH1 CH ER0 AH0 T S +BARBO B AA1 R B OW0 +BARBONE B AA1 R B OW2 N +BARBOSA B AA0 R B OW1 S AH0 +BARBOUR B AA1 R B ER0 +BARBOUR'S B AA1 R B ER0 Z +BARBOURSVILLE B AA1 B ER0 Z V IH0 L +BARBOZA B AA0 R B OW1 Z AH0 +BARBRA B AA1 R B R AH0 +BARBRE B AA1 R B ER0 +BARBS B AA1 R B Z +BARBUDA B AA0 R B UW1 D AH0 +BARBY B AA1 R B IY0 +BARCA B AA1 R K AH0 +BARCELLA B AA2 R S EH1 L AH0 +BARCELLOS B AA0 R S EH1 L OW0 Z +BARCELO B AA0 R CH EH1 L OW0 +BARCELONA B AA2 R S IH0 L OW1 N AH0 +BARCENAS B AA1 R S IH0 N AH0 Z +BARCH B AA1 R K +BARCHEFSKY B AA0 CH EH1 F S K IY0 +BARCIA B AA1 R CH AH0 +BARCLAY B AA1 R K L EY2 +BARCLAY(1) B AA1 R K L IY2 +BARCLAY'S B AA1 R K L IY0 Z +BARCLAY'S(1) B AA1 R K L EY0 Z +BARCLAYS B AA1 R K L IY0 Z +BARCLAYS(1) B AA1 R K L EY0 Z +BARCLAYS' B AA1 R K L IY0 Z +BARCLAYS'(1) B AA1 R K L EY0 Z +BARCLAYS'S B AA1 R K L IY2 Z IH0 Z +BARCLAYS'S(1) B AA1 R K L EY2 Z IH0 Z +BARCLIFT B AA1 R K L IH0 F T +BARCO B AA1 R K OW0 +BARCO'S B AA1 R K OW0 Z +BARCOMB B AA1 R K AH0 M +BARCROFT B AA1 R K R AO2 F T +BARCUS B AA1 R K AH0 S +BARCZAK B AA1 R CH AE0 K +BARD B AA1 R D +BARD'S B AA1 R D Z +BARDELL B AA0 R D EH1 L +BARDEN B AA1 R D AH0 N +BARDERA B AA2 R D EH1 R AH0 +BARDIN B AA1 R D IH0 N +BARDO B AA1 R D OW0 +BARDOLF B AA1 R D OW2 L F +BARDOLPH B AA1 R D AA0 L F +BARDON B AA0 R D AO1 N +BARDRICK B AA1 R D R IH0 K +BARDSLEY B AA1 R D S L IY0 +BARDULF B AA1 R D AH0 L F +BARDULPH B AA1 R D AH0 L F +BARDWELL B AA1 R D W EH2 L +BARE B EH1 R +BARED B EH1 R D +BAREFIELD B AE1 R IH0 F IY0 L D +BAREFIELD(1) B AE1 R F IY0 L D +BAREFOOT B EH1 R F UH2 T +BAREIS B AE1 R AY0 Z +BARELA B AA0 R EH1 L AH0 +BARELY B EH1 R L IY0 +BARENBOIM B EH1 R AH0 N B OY2 M +BARENBOIM'S B EH1 R AH0 N B OY2 M Z +BARENS B EH1 R AH0 N Z +BARENTINE B AA0 R EH0 N T IY1 N IY0 +BARENTINE(1) B EH1 R AH0 N T IY1 N +BARENTINE(2) B EH1 R AH0 N T AY1 N +BARENTS B EH1 R AH0 N T S +BARES B EH1 R Z +BAREST B EH1 R AH0 S T +BAREY B EH1 R IY0 +BARF B AA1 R F +BARFIELD B AA1 R F IY2 L D +BARFKNECHT B AA1 R F K N EH0 K T +BARFKNECHT(1) B AA1 R F N EH0 K T +BARFOOT B AA1 R F UH2 T +BARFUSS B AA1 R F AH2 S +BARG B AA1 R G +BARGA B AA1 R G AH0 +BARGAIN B AA1 R G AH0 N +BARGAIN(1) B AA1 R G IH0 N +BARGAINED B AA1 R G AH0 N D +BARGAINER B AA1 R G IH0 N ER0 +BARGAINERS B AA1 R G IH0 N ER0 Z +BARGAINING B AA1 R G IH0 N IH0 NG +BARGAINS B AA1 R G AH0 N Z +BARGAINS(1) B AA1 R G IH0 N Z +BARGANIER B AA1 R G AH0 N IY0 ER0 +BARGAR B AA0 R G AA1 R +BARGAS B AA1 R G AH0 Z +BARGE B AA1 R JH +BARGED B AA1 R JH D +BARGER B AA1 R JH ER0 +BARGERON B AA1 R G ER0 AH0 N +BARGES B AA1 R JH AH0 Z +BARGES(1) B AA1 R JH IH0 Z +BARGING B AA1 R JH IH0 NG +BARGMAN B AA1 R G M AH0 N +BARGMANN B AA1 R G M AH0 N +BARGO B AA1 R G OW2 +BARHAM B AA1 R HH AH0 M +BARHORST B AA1 R HH AO0 R S T +BARI B AA1 R IY0 +BARI'S B AA1 R IY0 Z +BARIBEAU B AE1 R IH0 B OW0 +BARICH B AE1 R IH0 K +BARIL B EH1 R AH0 L +BARILE B AA1 R AH0 L +BARILLARI B EH2 R IH0 L EH1 R IY0 +BARILLARI'S B EH2 R IH0 L EH1 R IY0 Z +BARILLO B ER0 IH1 L OW0 +BARINCO B ER0 IH1 NG K OW2 +BARING B EH1 R IH0 NG +BARING'S B EH1 R IH0 NG Z +BARINGER B EH1 R IH0 NG ER0 +BARINGS B EH1 R IH0 NG Z +BARINGS' B EH1 R IH0 NG Z +BARIS B AA1 R IY0 Z +BARISH B EH1 R IH0 SH +BARITE B EH1 R AY0 T +BARITES B EH1 R AY0 T S +BARITONE B EH1 R AH0 T OW2 N +BARITONES B EH1 R AH0 T OW2 N Z +BARIUM B EH1 R IY0 AH0 M +BARK B AA1 R K +BARKAI B AA0 R K AY1 +BARKALOW B AA1 R K AH0 L OW2 +BARKAN B AA1 R K AH0 N +BARKDOLL B AA1 R K D AH0 L +BARKDULL B AA1 R K D AH0 L +BARKE B AA1 R K +BARKED B AA1 R K T +BARKELEY B AA1 R K L IY0 +BARKER B AA1 R K ER0 +BARKERS B AA1 R K ER0 Z +BARKES B AA1 R K S +BARKETT B AA1 R K IH0 T +BARKEY B AA1 R K IY2 +BARKHURST B AA1 R K HH ER0 S T +BARKIN B AA1 R K IH0 N +BARKING B AA1 R K IH0 NG +BARKLEY B AA1 R K L IY0 +BARKLOW B AA1 R K L OW2 +BARKMAN B AA1 R K M AH0 N +BARKO B AA1 R K OW0 +BARKOCY B AA1 R K AH0 S IY0 +BARKOW B AA1 R K OW0 +BARKS B AA1 R K S +BARKSDALE B AA1 R K S D EY2 L +BARKSHIRE B AA1 R K SH AY2 R +BARKUS B AA1 R K AH0 S +BARLAGE B AA1 R L IH0 JH +BARLETT B AA1 R L IH0 T +BARLETTA B AA0 R L EH1 T AH0 +BARLETTESVILLE B AA1 R L AH0 T S V IH2 L +BARLEY B AA1 R L IY0 +BARLOON B AA0 R L UW1 N +BARLOW B AA1 R L OW2 +BARLOWE B AA1 R L OW2 +BARMAN B AA1 R M AH0 N +BARMORE B AA1 R M AO0 R +BARN B AA1 R N +BARNA B AA1 R N AH0 +BARNABAS B AA1 R N AH0 B AH0 S +BARNABY B AA1 R N AH0 B IY0 +BARNABY'S B AA1 R N AH0 B IY0 Z +BARNACLE B AA1 R N AH0 K AH0 L +BARNACLES B AA1 R N AH0 K AH0 L Z +BARNARD B AA1 R N AA0 R D +BARNARD'S B AA1 R N AA0 R D Z +BARNARDS B AA1 R N ER0 D Z +BARNAS B AA1 R N AH0 Z +BARNDT B AA1 R N T +BARNELL B AA1 R N AH0 L +BARNER B AA1 R N ER0 +BARNES B AA1 R N Z +BARNET B AA1 R N IH0 T +BARNETT B AA0 R N EH1 T +BARNETT'S B AA0 R N EH1 T S +BARNETTE B AA1 R N EH1 T +BARNEVIK B AA0 R N EH1 V IH0 K +BARNEY B AA1 R N IY0 +BARNEY'S B AA1 R N IY0 Z +BARNEYS B AA1 R N IY0 Z +BARNFIELD B AA1 R N F IY2 L D +BARNHARD B AA1 R N HH AA2 R D 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B AA1 R IY0 L IY1 F +BAS-RELIEF(1) B AA1 S R IY0 L IY1 F +BAS-RELIEFS B AA1 R IY0 L IY1 F S +BAS-RELIEFS(1) B AA1 S R IY0 L IY1 F S +BASA B AA1 S AH0 +BASAL B EY1 S AH0 L +BASALDUA B AA0 S AA0 L D UW1 AH0 +BASALT B AH0 S AO1 L T +BASALTS B AH0 S AO1 L T S +BASAM B AH0 S AA1 M +BASARA B AH0 S EH1 R AH0 +BASARA'S B AH0 S EH1 R AH0 Z +BASAYEV B AE1 S AA0 Y EH2 V +BASAYEV(1) B AE1 S AA0 Y EH2 F +BASCAY B AE1 S K EY0 +BASCH B AE1 SH +BASCO B AA1 S K OW0 +BASCOM B AE1 S K AH0 M +BASDEN B AE1 S D AH0 N +BASE B EY1 S +BASE'S B EY1 S AH0 Z +BASEBALL B EY1 S B AO1 L +BASEBALL'S B EY1 S B AO1 L Z +BASEBALLS B EY1 S B AO1 L Z +BASEBOARD B EY1 S B AO2 R D +BASEBOARDS B EY1 S B AO2 R D Z +BASED B EY1 S T +BASEHORE B AE1 S IH0 HH AO0 R +BASEHORE(1) B EY1 S HH AO0 R +BASEL B AA1 Z AH0 L +BASELESS B EY1 S L AH0 S +BASELINE B EY1 S L AY2 N +BASELINES B EY1 S L AY2 N Z +BASEMAN B EY1 S M AH0 N +BASEMENT B EY1 S M AH0 N T +BASEMENTS B EY1 S M AH0 N T S +BASENJI B AH0 S EH1 N JH IY0 +BASER B EY1 S ER0 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EY1 S +BASS'S B EY1 S IH0 Z +BASS'S(1) B AE1 S IH0 Z +BASSA B AE1 S AH0 +BASSAM B AE1 S AH0 M +BASSE B AE1 S +BASSES B AE1 S IH0 Z +BASSES(1) B EY1 S IH0 Z +BASSET B AE1 S IH0 T +BASSETT B AE1 S IH0 T +BASSETTE B AH0 S EH1 T +BASSETTI B AA0 S EH1 T IY0 +BASSFORD B AE1 S F ER0 D +BASSHAM B AE1 SH AH0 M +BASSI B AE1 S IY0 +BASSIN B AE1 S IH0 N +BASSINGER B AE1 S IH0 N JH ER0 +BASSIR B AH0 S IH1 R +BASSIR'S B AH0 S IH1 R Z +BASSIST B EY1 S IH0 S T +BASSISTS B EY1 S IH0 S T S +BASSLER B AE1 S L ER0 +BASSMAN B AE1 S M AH0 N +BASSO B AE1 S OW0 +BASSOON B AH0 S UW1 N +BASSOONIST B AH0 S UW1 N IH0 S T +BAST B AE1 S T +BASTA B AE1 S T AH0 +BASTARACHE B AA0 S T AA1 R EY0 K +BASTARD B AE1 S T ER0 D +BASTARD'S B AE1 S T ER0 D Z +BASTARDS B AE1 S T ER0 D Z +BASTE B EY1 S T +BASTED B EY1 S T AH0 D +BASTEDO B AA0 S T EY1 D OW0 +BASTEN B EY1 S T AH0 N +BASTIAN B AE1 S CH IH0 N +BASTIEN B AE1 S T AH0 N +BASTILLE B AE1 S T IH0 L +BASTILLE(1) B AE2 S T IH1 L +BASTIN B AE1 S T IH0 N +BASTING B EY1 S T IH0 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+BENTON B EH1 N T AH0 N +BENTONITE B EH1 N T AH0 N AY2 T +BENTONVILLE B EH1 N T AH0 N V IH2 L +BENTSEN B EH1 N T S AH0 N +BENTSEN'S B EH1 N T S AH0 N Z +BENTSON B EH1 N T S AH0 N +BENTZ B EH1 N T S +BENTZEL B EH1 N T Z AH0 L +BENTZEN B EH1 N T Z AH0 N +BENVENISTE B EH0 N V EH0 N IY1 S T IY0 +BENVENUTI B EH0 N V EH0 N UW1 T IY0 +BENVENUTO B EH0 N V EH0 N UW1 T OW0 +BENWARE B EH1 N W EH0 R +BENWAY B EH1 N W EY2 +BENYAMIN B EH2 N Y AH0 M IY1 N +BENYO B EY1 N Y OW0 +BENZ B EH1 N Z +BENZ(1) B AE1 N Z +BENZ'S B EH1 N Z IH0 Z +BENZEL B EH1 N Z AH0 L +BENZENE B EH0 N Z IY1 N +BENZENE(1) B EH1 N Z IY0 N +BENZES B EH1 N Z IH0 Z +BENZIE B EH1 N Z IY0 +BENZIGER B EH1 N Z IH0 G ER0 +BENZINE B EH1 N Z IY0 N +BENZING B EH1 N Z IH0 NG +BENZINGER B EH1 N Z IH0 NG ER0 +BENZODIAZEPINE B EH2 N Z OW0 D IY0 AE1 Z AH0 P IY0 N +BEOUGHER B AW1 F ER0 +BEOWULF B EY1 AH0 W UH2 L F +BEQUEATH B IH0 K W IY1 TH +BEQUEATHED B AH0 K W IY1 TH T +BEQUEST B IH0 K W EH1 S T +BEQUESTS B IH0 K W EH1 S T S +BEQUETTE B IH0 K EH1 T +BERA B EH1 R AH0 +BERADINO B EH2 R AA0 D IY1 N OW2 +BERAN B EH1 R AH0 N +BERANDINO B EH2 R AH0 N D IY1 N OW2 +BERANEK B EH1 R AH0 N IH0 K +BERARD B ER0 AA1 R D +BERARDI B ER0 AA1 R D IY0 +BERARDINELLI B ER0 AA0 R D IY0 N EH1 L IY0 +BERARDINO B ER0 AA0 R D IY1 N OW0 +BERARDO B ER0 AA1 R D OW0 +BERARDUCCI B ER0 AA0 R D UW1 CH IY0 +BERATE B IH0 R EY1 T +BERATED B IH0 R EY1 T IH0 D +BERATING B IH0 R EY1 T IH0 NG +BERBER B ER1 B ER0 +BERBERIAN B ER0 B IH1 R IY0 AH0 N +BERBERICH B ER1 B ER0 IH0 K +BERBICK B ER1 B IH0 K +BERCAW B ER1 K AO0 +BERCH B ER1 K +BERCHENALL B ER1 K AH0 N AA2 L +BERCHTESGADEN B ER1 K T AH0 S G AA2 D AH0 N +BERCHTOLD B ER1 K T OW0 L D +BERCIER B ER1 K IY0 ER0 +BERCOR B ER1 K AO2 R +BERDAHL B ER1 D AA0 L +BERDAN B ER1 D AH0 N +BERDINE B ER0 D IY1 N IY0 +BERE B IH1 R +BEREA B ER0 IY1 AH0 +BEREAVE B ER0 IY1 V +BEREAVED B ER0 IY1 V D +BEREAVEMENT B ER0 IY1 V M AH0 N T +BEREFT B ER0 EH1 F T +BEREGOVOY B ER0 EH1 G AH0 V OY2 +BEREGOVOY(1) B EH2 R AH0 G OW1 V OY2 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ER0 S AH0 N +BERGES B ER1 JH IH0 Z +BERGESON B ER1 G IH0 S AH0 N +BERGET B ER1 G EH0 T +BERGEVIN B ER1 G EH0 V IH0 N +BERGEY B ER1 JH IY0 +BERGFELD B ER1 G F EH0 L D +BERGGREN B ER1 G R EH0 N +BERGH B ER1 G +BERGHOF B ER1 G HH AO0 F +BERGHOFF B ER1 G HH AO0 F +BERGHUIS B ER1 G HH UW0 IH0 Z +BERGIN B ER1 G IH2 N +BERGLAND B ER1 G L AE2 N D +BERGLING B ER1 G L IH0 NG +BERGLUND B ER1 G L AH0 N D +BERGMAN B ER1 G M AH0 N +BERGMANN B ER1 G M AH0 N +BERGNER B ER1 G N ER0 +BERGQUIST B ER1 G K W IH0 S T +BERGREN B ER1 G R EH0 N +BERGS B ER1 G Z +BERGSCHNEIDER B ER1 G SH N AY0 D ER0 +BERGSMA B EH1 R G Z M AH0 +BERGSTEDT B ER1 G S T EH0 T +BERGSTEIN B ER1 G S T AY2 N +BERGSTEIN(1) B ER1 G S T IY2 N +BERGSTEN B ER1 G S AH0 N +BERGSTRAND B ER1 G S T R AE2 N D +BERGSTRAUSSER B ER1 G S T R AW2 S ER0 +BERGSTRAUSSER'S B ER1 G S T R AW2 S ER0 Z +BERGSTRESSER B ER1 G S T R EH2 S ER0 +BERGSTROM B ER1 G S T R AA0 M +BERGTHOLD B ER1 G TH OW2 L D +BERGUM B ER1 G AH0 M +BERHOW B ER1 HH OW0 +BERIA B EH1 R IY0 AH0 +BERING B EH1 R IH0 NG +BERINGER B EH1 R IH0 NG ER0 +BERISFORD B EH1 R IH0 S F ER0 D +BERISH B ER1 IH0 SH +BERJAYA B ER0 JH AY1 AH0 +BERK B ER1 K +BERKA B ER1 K AH0 +BERKE B ER1 K +BERKEBILE B ER1 K IH0 B AH0 L +BERKEL B ER1 K AH0 L +BERKELEY B ER1 K L IY0 +BERKELEY'S B ER1 K L IY0 Z +BERKELMAN B ER1 K AH0 L M AH0 N +BERKEMEIER B ER1 K IH0 M AY0 ER0 +BERKEN B ER1 K AH0 N +BERKERY B ER1 K ER0 IY0 +BERKES B ER1 K S +BERKEY B ER1 K IY0 +BERKHEIMER B ER1 K HH AY0 M ER0 +BERKLAND B ER1 K L AH0 N D +BERKLEE B ER1 K L IY0 +BERKLEY B ER1 K L IY0 +BERKLINE B ER1 K L AY2 N +BERKMAN B ER1 K M AH0 N +BERKO B ER1 K OW0 +BERKOFF B ER1 K AO0 F +BERKOVITZ B ER1 K AH0 V IH0 T S +BERKOWITZ B ER1 K AH0 W IH0 T S +BERKSHIRE B ER1 K SH ER0 +BERKSHIRE(1) B ER1 K SH AY2 R +BERKSHIRES B ER1 K SH IH2 R Z +BERKSHIRES(1) B ER1 K SH AY2 R Z +BERKSON B ER1 K S AH0 N +BERKSTRESSER B ER1 K S T R IH0 S ER0 +BERLACK B ER1 L AE0 K +BERLAND B ER1 L AH0 N D +BERLANGA B ER0 L AA1 NG G AH0 +BERLASCONE B EH2 R L AH0 S K OW1 N IY0 +BERLASCONE'S B EH2 R L AH0 S K OW1 N IY0 Z +BERLE B ER1 L +BERLE'S B ER1 L Z +BERLES B ER1 L Z +BERLES' B ER1 L Z +BERLET B ER2 L EH1 T +BERLET'S B ER1 L EH1 T S +BERLEX B ER1 L EH2 K S +BERLIN B ER0 L IH1 N +BERLIN'S B ER0 L IH1 N Z +BERLINER B ER0 L IH1 N ER0 +BERLINER(1) B ER0 L AY1 N ER0 +BERLINER'S B ER0 L IH1 N ER0 Z +BERLINER'S(1) B ER0 L AY1 N ER0 Z +BERLINERS B ER0 L IH1 N ER0 Z +BERLINERS(1) B ER0 L AY1 N ER0 Z +BERLING B ER1 L IH0 NG +BERLINGER B ER1 L IH0 NG ER0 +BERLIOZ B ER1 L IY0 OW0 Z +BERLITZ B ER0 L IH1 T S +BERLOTTES B ER0 L AA1 T S +BERLS B ER1 L Z +BERLUSCONI B ER2 L AH0 S K OW1 N IY0 +BERLUSCONI'S B ER2 L AH0 S K OW1 N IY0 Z +BERM B ER1 M +BERMAN B ER1 M AH0 N +BERMAN'S B ER1 M AH0 N Z +BERMANS B ER1 M AH0 N Z +BERMEA B EH1 R M IY0 AH0 +BERMEL B ER1 M AH0 L +BERMS B ER1 M Z +BERMUDA B ER0 M Y UW1 D AH0 +BERMUDAS B ER0 M Y UW1 D AH0 Z +BERMUDES B ER0 M Y UW1 D Z +BERMUDEZ B ER0 M Y UW1 D EH2 Z +BERMUDEZ(1) B ER2 M Y UW1 D EH2 Z +BERN B ER1 N +BERNA B EH1 R N AH0 +BERNABE B ER1 N AH0 B +BERNABEI B ER1 N AH0 B AY0 +BERNACKI B ER0 N AA1 T S K IY0 +BERNADENE B ER1 N AH0 D IY0 N +BERNADETTE B ER0 N AH0 D EH1 T +BERNADIN B ER1 N AH0 D IH0 N +BERNADINE B ER0 N AH0 D IY1 N +BERNADINO B ER2 N AH0 D IY1 N OW0 +BERNAL B ER1 N AH0 L +BERNAMA B ER0 N AA1 M AH0 +BERNARD B ER0 N AA1 R D +BERNARD(1) B ER1 N ER0 D +BERNARD'S B ER0 N AA1 R D Z +BERNARDI B ER0 N AA1 R D IY0 +BERNARDIN B ER1 N AA0 R D IY0 N +BERNARDINI B ER0 N AA0 R D IY1 N IY0 +BERNARDINO B ER0 N AH0 D IY1 N OW0 +BERNARDINO(1) B ER2 N AA0 R D IY1 N OW0 +BERNARDO B ER0 N AA1 R D OW0 +BERNARDO'S B ER0 N AA1 R D OW0 Z +BERNARDS B ER0 N AA1 R D Z +BERNARDY B ER0 N AA1 R D IY0 +BERNAS B ER1 N AH0 Z +BERNASCONI B ER0 N AA0 S K OW1 N IY0 +BERNAT B ER1 N AH0 T +BERNATH B ER1 N AH0 TH +BERNAUER B ER1 N AW0 ER0 +BERNAY B ER0 N EY1 +BERNBACH B ER1 N B AA2 K +BERND B ER1 N T +BERNDT B ER1 N T +BERNE B ER1 N +BERNEICE B ER0 N AY1 S +BERNER B ER1 N ER0 +BERNET B ER0 N EH1 T +BERNETT B ER1 N IH0 T 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EH1 R Z +BERRETH B EH1 R IH0 TH +BERRETT B EH1 R IH0 T +BERREY B EH1 R IY0 +BERRI B EH1 R IY0 +BERRIAN B EH1 R IY0 AH0 N +BERRIDGE B EH1 R IH0 JH +BERRIE B EH1 R IY0 +BERRIEN B EH1 R IY0 AH0 N +BERRIER B EH1 R IY0 ER0 +BERRIES B EH1 R IY0 Z +BERRIGAN B EH1 R IH0 G AH0 N +BERRILL B EH1 R AH0 L +BERRINGER B EH1 R IH0 NG ER0 +BERRIOS B EH0 R IY1 OW0 Z +BERRIS B EH1 R IY0 Z +BERRONG B EH1 R AO0 NG +BERRY B EH1 R IY0 +BERRY'S B EH1 R IY0 Z +BERRYHILL B EH1 R IY0 HH IH2 L +BERRYLIKE B EH1 R IY0 L AY2 K +BERRYMAN B EH1 R IY0 M AH0 N +BERSCH B ER1 SH +BERSERK B ER0 S ER1 K +BERSHAD B ER0 SH AA1 D +BERSON B ER1 S AH0 N +BERST B ER1 S T +BERSTEIN B ER1 S T IY0 N +BERSTEIN(1) B ER1 S T AY0 N +BERT B ER1 T +BERTA B ER1 T AH0 +BERTCH B ER1 CH +BERTE B ER1 T +BERTELLI B ER0 T EH1 L IY0 +BERTELS B ER1 T AH0 L Z +BERTELSEN B ER1 T IH0 L S AH0 N +BERTELSMANN B ER1 T AH0 L Z M AH0 N +BERTELSMANN'S B ER1 T AH0 L Z M AH0 N Z +BERTELSON B ER1 T IH0 L S AH0 N +BERTH B ER1 TH +BERTHA B ER1 TH AH0 +BERTHELOT 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B ER1 T S +BERUBE B EH1 R UW0 B +BERUDI B AH0 R UW1 D IY0 +BERUMEN B IH1 R UW0 M EH0 N +BERWALD B ER1 W AO0 L D +BERWANGER B ER1 W AO0 NG ER0 +BERWICK B ER1 W IH0 K +BERWYN B ER1 W IH0 N +BERYL B EH1 R AH0 L +BERYLLIUM B ER0 IH1 L IY0 AH0 M +BERZIN B ER1 Z IH0 N +BERZINS B ER1 Z IH0 N Z +BES B IY1 Z +BESANCON B IH0 S AE1 N K AH0 N +BESANT B EH1 Z AH0 N T +BESAW B IY1 S AO0 +BESCH B EH1 SH +BESCHLOSS B EH1 SH L AO2 S +BESCHLOSS' B EH1 SH L AO2 S +BESCHLOSS'S B EH1 SH L AO2 S IH0 S +BESECKER B EH1 S IH0 K ER0 +BESEECH B IY0 S IY1 CH +BESEECHED B IY0 S IY1 CH T +BESEECHING B IY0 S IY1 CH IH0 NG +BESEIGED B IH0 S IY1 JH D +BESEMER B EH1 S IY0 M ER0 +BESET B IH0 S EH1 T +BESETTING B IH0 S EH1 T IH0 NG +BESHARA B IH0 SH AA1 R AH0 +BESHAROV B EH1 SH ER0 AA0 V +BESHEARS B EH1 SH IY0 R Z +BESHLOSS B EH1 SH L AO0 S +BESHORE B EH1 SH ER0 +BESIDE B IH0 S AY1 D +BESIDE(1) B IY2 S AY1 D +BESIDES B IH0 S AY1 D Z +BESIDES(1) B IY2 S AY1 D Z +BESIEGE B IH0 S IY1 JH +BESIEGED B IH0 S IY1 JH D +BESIEGING B IH0 S IY1 JH IH0 NG +BESKE B EH1 S K +BESLER B EH1 S AH0 L ER0 +BESLER(1) B EH1 S L ER0 +BESNER B EH1 S N ER0 +BESNER'S B EH1 S N ER0 Z +BESOTTED B IH0 S AO1 T IH0 D +BESPEAK B IH0 S P IY1 K +BESPEAKS B IH0 S P IY1 K S +BESPECTACLE B IH0 S P EH1 K T AH0 K AH0 L +BESPECTACLED B IH0 S P EH1 K T AH0 K AH0 L D +BESPOKE B UH0 S P OW1 K +BESS B EH1 S +BESSE B EH1 S +BESSEMER B EH1 S AH0 M ER0 +BESSENT B EH1 S AH0 N T +BESSER B EH1 S ER0 +BESSERT B EH1 S ER0 T +BESSETTE B IH0 S EH1 T +BESSEY B EH1 S IY0 +BESSIE B EH1 S IY0 +BESSINGER B EH1 S IH0 N JH ER0 +BESSIRE B EH0 S IH1 R IY0 +BESSLER B EH1 S L ER0 +BESSO B EH1 S OW0 +BESSON B EH1 S AH0 N +BESSY B EH1 S IY0 +BEST B EH1 S T +BEST'S B EH1 S T S +BEST-WESTERN B EH1 S T W EH1 S T ER0 N +BESTE B EH1 S T +BESTED B EH1 S T IH0 D +BESTER B EH1 S T ER0 +BESTIAL B EH1 S CH AH0 L +BESTIALITY B EH0 S CH AE1 L IH0 T IY0 +BESTING B EH1 S T IH0 NG +BESTOW B IH0 S T OW1 +BESTOWED B IH0 S T OW1 D +BESTOWING B IH0 S T OW1 IH0 NG +BESTOWS B IH0 S T OW1 Z 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+BITTNER B IH1 T N ER0 +BITTON B IH1 T AH0 N +BITTY B IH1 T IY0 +BITUMEN B IH2 T UW1 M AH0 N +BITUMEN(1) B AY2 T UW1 M AH0 N +BITUMINOUS B IH0 T UW1 M AH0 N AH0 S +BITZ B IH1 T S +BITZER B IH1 T Z ER0 +BIVALVE B AY1 V AE2 L V +BIVALVES B AY1 V AE2 L V Z +BIVEN B AY1 V AH0 N +BIVENS B AY1 V AH0 N Z +BIVIANO B IY2 V IY0 AA1 N OW0 +BIVIN B IH1 V IH0 N +BIVINS B IH1 V IH0 N Z +BIVONA B IH0 V OW1 N AH0 +BIVOUAC B IH1 V W AE0 K +BIWEEKLY B AY0 W IY1 K L IY0 +BIX B IH1 K S +BIXBY B IH1 K S B IY0 +BIXEL B IH1 K S AH0 L +BIXLER B IH1 K S L ER0 +BIZ B IH1 Z +BIZANGO B IH0 Z AE1 NG G OW0 +BIZARRE B AH0 Z AA1 R +BIZARRE(1) B IH0 Z AA1 R +BIZET B IH0 Z EH1 T +BIZMART B IH1 Z M AA2 R T +BIZRATE B IH1 Z EY2 T +BIZUB B IH1 Z AH0 B +BIZZARO B IH0 Z AA1 R OW0 +BIZZELL B IH1 Z AH0 L +BIZZY B IH1 Z IY0 +BJELASNICA B Y EH0 L AE1 S N IH0 K AH0 +BJELLAND B Y EH1 L AH0 N D +BJERKE B Y ER1 K +BJOERN B Y AO1 R N +BJORGE B Y AO1 R G +BJORK B Y AO1 R K +BJORKLUND B Y AO1 R K L AH0 N D +BJORKMAN B Y AO1 R K M AH0 N +BJORN B Y AO1 R N +BJORNSTAD B Y AO1 R N S T AH0 D +BLAB B L AE1 B +BLABBED B L AE1 B D +BLABBER B L AE1 B ER0 +BLABBERS B L AE1 B ER0 Z +BLACHLY B L AA1 CH L IY0 +BLACHLY(1) B L AA1 K L IY0 +BLACK B L AE1 K +BLACK'S B L AE1 K S +BLACKARD B L AE1 K ER0 D +BLACKBALL B L AE1 K B AO2 L +BLACKBERRIES B L AE1 K B EH2 R IY0 Z +BLACKBERRY B L AE1 K B EH2 R IY0 +BLACKBIRD B L AE1 K B ER0 D +BLACKBIRDS B L AE1 K B ER0 D Z +BLACKBOARD B L AE1 K B AO2 R D +BLACKBOARDS B L AE1 K B AO2 R D Z +BLACKBURN B L AE1 K B ER0 N +BLACKED B L AE1 K T +BLACKEN B L AE1 K AH0 N +BLACKENED B L AE1 K AH0 N D +BLACKENING B L AE1 K AH0 N IH0 NG +BLACKENING(1) B L AE1 K N IH0 NG +BLACKENS B L AE1 K AH0 N Z +BLACKER B L AE1 K ER0 +BLACKERBY B L AE1 K ER0 B IY0 +BLACKEST B L AE1 K AH0 S T +BLACKETER B L AE1 K IY0 T ER0 +BLACKETT B L AE1 K IH0 T +BLACKFOOT B L AE1 K F UH2 T +BLACKFORD B L AE1 K F ER0 D +BLACKHAM B L AE1 K HH AH0 M +BLACKHAWK B L AE1 K HH AO2 K +BLACKHAWK'S B L AE1 K HH AO2 K S +BLACKHAWKS B L AE1 K HH AO2 K S +BLACKHEATH B L AE1 K HH IY2 TH +BLACKHURST B L AE1 K HH ER0 S T +BLACKIE B L AE1 K IY0 +BLACKJACK B L AE1 K JH AE2 K +BLACKLEDGE B L AE1 K L EH2 JH +BLACKLEY B L AE1 K L IY0 +BLACKLIST B L AE1 K L IH2 S T +BLACKLISTED B L AE1 K L IH2 S T IH0 D +BLACKLISTING B L AE1 K L IH2 S T IH0 NG +BLACKLOCK B L AE1 K L AA2 K +BLACKMAIL B L AE1 K M EY2 L +BLACKMAILED B L AE1 K M EY2 L D +BLACKMAILING B L AE1 K M EY2 L IH0 NG +BLACKMAN B L AE1 K M AH0 N +BLACKMER B L AE1 K M ER0 +BLACKMON B L AE1 K M AH0 N +BLACKMORE B L AE1 K M AO0 R +BLACKMUN B L AE1 K M AH0 N +BLACKMUN'S B L AE1 K M AH0 N Z +BLACKNESS B L AE1 K N AH0 S +BLACKOUT B L AE1 K AW2 T +BLACKOUTS B L AE1 K AW2 T S +BLACKPOOL B L AE1 K P UW2 L +BLACKROCK B L AE1 K R AA2 K +BLACKS B L AE1 K S +BLACKS' B L AE1 K S +BLACKSBURG B L AE1 K S B ER0 G +BLACKSHEAR B L AE1 K SH IH0 R +BLACKSHER B L AE1 K SH ER0 +BLACKSHIRE B L AE1 K SH AY2 R +BLACKSMITH B L AE1 K S M IH2 TH +BLACKSON B L AE1 K S AH0 N +BLACKSTOCK B L AE1 K S T AA2 K +BLACKSTON B L AE1 K S T AH0 N +BLACKSTONE B L AE1 K S T OW2 N +BLACKSTONE'S B L AE1 K S T OW2 N Z +BLACKTOP B L AE1 K T AA2 P +BLACKWELDER B L AE1 K W EH2 L D ER0 +BLACKWELL B L AE1 K W EH2 L +BLACKWOOD B L AE1 K W UH2 D +BLADDER B L AE1 D ER0 +BLADDERS B L AE1 D ER0 Z +BLADE B L EY1 D +BLADED B L EY1 D IH0 D +BLADEN B L EY1 D AH0 N +BLADES B L EY1 D Z +BLADING B L EY1 D IH0 NG +BLADOW B L AE1 D OW0 +BLAESE B L EY1 Z +BLAESING B L EH1 S IH0 NG +BLAGDEN B L AE1 G D AH0 N +BLAGG B L AE1 G +BLAH B L AA1 +BLAHA B L AA1 HH AH0 +BLAHNIK B L AA1 N IH0 K +BLAHUT B L AE1 HH AH0 T +BLAICH B L EY1 CH +BLAIKIE B L EY1 K IY0 +BLAIN B L EY1 N +BLAINE B L EY1 N +BLAIR B L EH1 R +BLAIR'S B L EH1 R Z +BLAIS B L EH1 Z +BLAISDELL B L EY1 S D AH0 L +BLAISE B L EY1 Z +BLAISER B L EY1 Z ER0 +BLAIZE B L EY1 Z +BLAKE B L EY1 K +BLAKE'S B L EY1 K S +BLAKELEY B L EY1 K L IY0 +BLAKELEY'S B L EY1 K L IY0 Z +BLAKELY B L EY1 K L IY0 +BLAKELY'S B L EY1 K L IY0 Z +BLAKEMAN B L EY1 K M AH0 N +BLAKEMORE B L EY1 K M AO0 R +BLAKENEY B L EY1 K N IY0 +BLAKENEY'S B L EY1 K N IY0 Z +BLAKENHAM B L EY1 K AH0 N HH AE2 M +BLAKENSHIP B L EY1 K AH0 N SH IH0 P +BLAKER B L EY1 K ER0 +BLAKES B L EY1 K S +BLAKESLEE B L EY1 K S L IY0 +BLAKESLEY B L EY1 K S L IY0 +BLAKEY B L EY1 K IY0 +BLAKLEY B L AE1 K L IY0 +BLAKNEY B L AE1 K N IY0 +BLALACK B L AE1 L AH0 K +BLALOCK B L AE1 L AA0 K +BLAME B L EY1 M +BLAMED B L EY1 M D +BLAMELESS B L EY1 M L AH0 S +BLAMES B L EY1 M Z +BLAMESTRORM B L EY1 M S T AO2 R M +BLAMING B L EY1 M IH0 NG +BLAMPIED B L AE1 M P IY0 D +BLAN B L AE1 N +BLANC B L AE1 NG K +BLANCA B L AA1 NG K AH0 +BLANCETT B L AE1 N S IH0 T +BLANCH B L AE1 N CH +BLANCHARD B L AE1 N CH ER0 D +BLANCHARD'S B L AE1 N CH ER0 D Z +BLANCHARDS B L AE1 N CH ER0 D Z +BLANCHE B L AE1 N CH +BLANCHET B L AE1 N K IH0 T +BLANCHETT B L AE1 N CH IH0 T +BLANCHETTE B L AH0 N SH EH1 T +BLANCHFIELD B L AE1 N CH F IY2 L D +BLANCK B L AE1 NG K +BLANCMANGE B L AH0 M AA1 N JH +BLANCO B L AE1 NG K OW0 +BLAND B L AE1 N D +BLANDA B L AE1 N D AH0 +BLANDER B L AE1 N D ER0 +BLANDFORD B L AE1 N D F AO0 R D +BLANDIN B L AE1 N D IH0 N +BLANDING B L AE1 N D IH0 NG +BLANDINO B L AA0 N D IY1 N OW0 +BLANDISHMENT B L AE1 N D IH0 SH M AH0 N T +BLANDISHMENTS B L AE1 N D IH0 SH M AH0 N T S +BLANDLY B L AE1 N D L IY0 +BLANDNESS B L AE1 N D N AH0 S +BLANDO B L AE1 N D OW0 +BLANDON B L AE1 N D IH0 N +BLANE B L EY1 N +BLANEY B L EY1 N IY0 +BLANFORD B L AE1 N F ER0 D +BLANK B L AE1 NG K +BLANKE B L AE1 NG K +BLANKED B L AE1 NG K T +BLANKEN B L AE1 NG K AH0 N +BLANKENBAKER B L AE1 NG K AH0 N B EY2 K ER0 +BLANKENBECKLER B L AE1 NG K AH0 N B EH2 K L ER0 +BLANKENBURG B L AE1 NG K AH0 N B ER0 G +BLANKENHORN B L AE1 NG K IH0 N HH ER0 N +BLANKENSHIP B L AE1 NG K AH0 N SH IH2 P +BLANKET B L AE1 NG K AH0 T +BLANKET(1) B L AE1 NG K IH0 T +BLANKETED B L AE1 NG K AH0 T IH0 D +BLANKETING B L AE1 NG K AH0 T IH0 NG +BLANKETS B L AE1 NG K AH0 T S +BLANKIE B L AE1 NG K IY2 +BLANKIES B L AE1 NG K IY2 Z +BLANKING B L AE1 NG K IH0 NG +BLANKINSHIP B L AE1 NG K IH0 N SH IH0 P +BLANKLEY B L AE1 NG K L IY0 +BLANKLY B L AE1 NG K L IY0 +BLANKLY'S B L AE1 NG K L IY0 Z +BLANKS B L AE1 NG K S +BLANKY B L AE1 NG K IY2 +BLANN B L AE1 N +BLANQUITA B L AA0 N K IY1 T AH0 +BLANSETT B L AE1 N S IH0 T +BLANTON B L AE1 N T AH0 N +BLARE B L EH1 R +BLARED B L EH1 R D +BLARES B L EH1 R Z +BLARING B L EH1 R IH0 NG +BLAS B L AA1 S +BLASCHKE B L AE1 SH K +BLASCO B L AA1 S K OW0 +BLASDEL B L AE1 S D AH0 L +BLASDELL B L AE1 S D AH0 L +BLASE B L EY1 Z +BLASER B L EY1 Z ER0 +BLASI B L EY1 Z IY0 +BLASIA B L AA1 S IY0 AH0 +BLASIER B L EY1 Z IY0 ER0 +BLASIER(1) B L EY1 ZH ER0 +BLASIER'S B L EY1 Z IY0 ER0 Z +BLASIER'S(1) B L EY1 ZH ER0 Z +BLASING B L EY1 Z IH0 NG +BLASINGAME B L AA0 S IH0 NG G AA1 M IY0 +BLASINI B L AH0 S IY1 N IY0 +BLASIO B L AE1 Z IY0 OW2 +BLASIUS B L EY1 S IY0 IH0 S +BLASKE B L EY1 S K +BLASKO B L AA1 S K OW0 +BLASPHEMOUS B L AE1 S F AH0 M AH0 S +BLASPHEMY B L AE1 S F AH0 M IY0 +BLASS B L AE1 S +BLASSIE B L AE1 S IY0 +BLASSIE'S B L AE1 S IY0 Z +BLASSINGAME B L AA0 S IH0 NG G AA1 M IY0 +BLAST B L AE1 S T +BLASTDOWN B L AE1 S T D AW2 N +BLASTED B L AE1 S T AH0 D +BLASTED(1) B L AE1 S T IH0 D +BLASTER B L AE1 S T ER0 +BLASTFURNACE B L AE1 S T F ER2 N AH0 S +BLASTING B L AE1 S T IH0 NG +BLASTODERM B L AE1 S T AH0 D ER0 M +BLASTOFF B L AE1 S T AO2 F +BLASTOMA B L AE2 S T OW1 M AH0 +BLASTS B L AE1 S T S +BLASZAK B L AA1 SH AH0 K +BLASZCZYK B L AA1 SH CH IH0 K +BLATANT B L EY1 T AH0 N T +BLATANTLY B L EY1 T AH0 N T L IY0 +BLATCHFORD B L AE1 CH F ER0 D +BLATCHLEY B L AE1 CH L IY0 +BLATHER B L AE1 DH ER0 +BLATNIK B L AE1 T N IH0 K +BLATT B L AE1 T +BLATTER B L AE1 T ER0 +BLATTNER B L AE1 T N ER0 +BLATZ B L AE1 T S +BLAU B L AW1 +BLAUCH B L AO1 CH +BLAUER B L AW1 R +BLAUM B L AO1 M +BLAUSER B L AW1 S ER0 +BLAUSTEIN B L AW1 S T AY0 N +BLAUSTEIN(1) B L AW1 S T IY0 N +BLAUVELT B L AW1 V IH0 L T +BLAY B L EY1 +BLAYDES B L EY1 D Z +BLAYDON B L EY1 D AH0 N +BLAYLOCK B L EY1 L AH0 K +BLAYNE B L EY1 N +BLAYNEY B L EY1 N IY0 +BLAYZE B L EY1 Z +BLAZE B L EY1 Z +BLAZED B L EY1 Z D +BLAZEJEWSKI B L AH0 Z EY0 EH1 F S K IY0 +BLAZEK B L AA1 Z EH0 K +BLAZER B L EY1 Z ER0 +BLAZERS B L EY1 Z ER0 Z +BLAZES B L EY1 Z IH0 Z +BLAZIER B L EY1 Z IY0 ER0 +BLAZINA B L AA0 Z IY1 N AH0 +BLAZING B L EY1 Z IH0 NG +BLEA B L IY1 +BLEACH B L IY1 CH +BLEACHED B L IY1 CH T +BLEACHER B L IY1 CH ER0 +BLEACHERS B L IY1 CH ER0 Z +BLEACHING B L IY1 CH IH0 NG +BLEAK B L IY1 K +BLEAKER B L IY1 K ER0 +BLEAKEST B L IY1 K AH0 S T +BLEAKLEY B L IY1 K L IY0 +BLEAKNESS B L IY1 K N AH0 S +BLEAKNEY B L IY1 K N IY0 +BLEAM B L IY1 M +BLEARY B L IH1 R IY0 +BLEAU B L OW1 +BLECH B L EH1 K +BLECH'S B L EH1 K S +BLECHA B L EH1 CH AH0 +BLECHER B L EH1 K ER0 +BLECHLEY B L EH1 K L IY0 +BLECHMAN B L EH1 K M AH0 N +BLECK B L EH1 K +BLECKER B L EH1 K ER0 +BLED B L EH1 D +BLEDSOE B L EH1 D S OW0 +BLEECKER B L IY1 K ER0 +BLEED B L IY1 D +BLEEDING B L IY1 D IH0 NG +BLEEDS B L IY1 D Z +BLEEKER B L IY1 K ER0 +BLEEP B L IY1 P +BLEEPING B L IY1 P IH0 NG +BLEGEN B L EH1 G AH0 N +BLEHM B L EH1 M +BLEICH B L AY1 K +BLEICHER B L AY1 K ER0 +BLEIER B L AY1 ER0 +BLEIL B L IY1 L +BLEILER B L AY1 L ER0 +BLEILERS B L AY1 L ER0 Z +BLELLOCH B L EH1 L AA0 K +BLEMISH B L EH1 M IH0 SH +BLEMISHED B L EH1 M IH0 SH T +BLEMISHES B L EH1 M IH0 SH IH0 Z +BLEND B L EH1 N D +BLENDA B L EH1 N D AH0 +BLENDAX B L EH1 N D AE2 K S +BLENDED B L EH1 N D IH0 D +BLENDER B L EH1 N D ER0 +BLENDERS B L EH1 N D ER0 Z +BLENDING B L EH1 N D IH0 NG +BLENDS B L EH1 N D Z +BLENHEIM B L EH1 N HH AY2 M +BLEPHARISMA B L EH2 F ER0 IH1 Z M AH0 +BLESER B L IY1 Z ER0 +BLESS B L EH1 S +BLESSED B L EH1 S T +BLESSEDLY B L EH1 S AH0 D L IY0 +BLESSEDNESS B L EH1 S AH0 D N AH0 S +BLESSES B L EH1 S IH0 Z +BLESSING B L EH1 S IH0 NG +BLESSINGER B L EH1 S IH0 NG ER0 +BLESSINGS B L EH1 S IH0 NG Z +BLESSINGTON B L EH1 S IH0 NG T AH0 N +BLEST B L EH1 S T +BLETHEN B L EH1 TH AH0 N +BLEU B L UW1 +BLEVENS B L EH1 V IH0 N Z +BLEVINS B L EH1 V IH0 N Z +BLEW B L UW1 +BLEWETT B L UW1 IH0 T +BLEWITT B L UW1 IH0 T +BLEY B L EY1 +BLICK B L IH1 K +BLICKENSTAFF B L IH1 K IH0 N S T AH0 F +BLIDA B L AY1 D AH0 +BLIGH B L AY1 +BLIGHT B L AY1 T +BLIGHTED B L AY1 T IH0 D +BLILEY B L AY1 L IY0 +BLIMP B L IH1 M P +BLIMPS B L IH1 M P S +BLINCOE B L IH0 N K OW1 +BLIND B L AY1 N D +BLINDED B L AY1 N D IH0 D +BLINDER B L AY1 N D ER0 +BLINDER'S B L AY1 N D ER0 Z +BLINDERS B L AY1 N D ER0 Z +BLINDFOLD B L AY1 N D F OW2 L D +BLINDFOLDED B L AY1 N D F OW2 L D IH0 D +BLINDING B L AY1 N D IH0 NG +BLINDLY B L AY1 N D L IY0 +BLINDNESS B L AY1 N D N AH0 S +BLINDS B L AY1 N D Z +BLINDSIDE B L AY1 N D S AY2 D +BLINDSIDED B L AY1 N D S AY2 D IH0 D +BLINK B L IH1 NG K +BLINKED B L IH1 NG K T +BLINKEN B L IH1 NG K AH0 N +BLINKING B L IH1 NG K IH0 NG +BLINKS B L IH1 NG K S +BLINN B L IH1 N +BLIP B L IH1 P +BLIPS B L IH1 P S +BLISCOLL B L IH1 S K AO0 L +BLISH B L IH1 SH +BLISS B L IH1 S +BLISS' B L IH1 S +BLISSETT B L IH1 S IH0 T +BLISSFUL B L IH1 S F AH0 L +BLISSFULLY B L IH1 S F AH0 L IY0 +BLISTER B L IH1 S T ER0 +BLISTERED B L IH1 S T ER0 D +BLISTERING B L IH1 S T ER0 IH0 NG +BLISTERS B L IH1 S T ER0 Z +BLITCH B L IH1 CH +BLITHE B L AY1 DH +BLITHELY B L AY1 TH L IY0 +BLITSTEIN B L IH1 T S T IY0 N +BLITSTEIN(1) B L IH1 T S T AY0 N +BLITZ B L IH1 T S +BLITZED B L IH1 T S T +BLITZEN B L IH1 T S AH0 N +BLITZER B L IH1 T S ER0 +BLITZER'S B L IH1 T S ER0 Z +BLITZES B L IH1 T S IH0 Z +BLITZKRIEG B L IH1 T S K R IY2 G +BLIVEN B L AY1 V AH0 N +BLIXT B L IH1 K S T +BLIZARD B L IH1 Z ER0 D +BLIZZARD B L IH1 Z ER0 D +BLIZZARDS B L IH1 Z ER0 D Z +BLOAT B L OW1 T +BLOATED B L OW1 T IH0 D +BLOATEDNESS B L OW1 T IH0 D N AH0 S +BLOATING B L OW1 T IH0 NG +BLOATS B L OW1 T S +BLOB B L AA1 B +BLOBBY B L AA1 B IY0 +BLOBS B L AA1 B Z +BLOC B L AA1 K +BLOC'S B L AA1 K S +BLOCH B L AA1 K +BLOCH'S B L AA1 K S +BLOCHER B L AA1 K ER0 +BLOCK B L AA1 K +BLOCK'S B L AA1 K S +BLOCKADE B L AA2 K EY1 D +BLOCKADED B L AA2 K EY1 D IH0 D +BLOCKADER B L AA2 K EY1 D ER0 +BLOCKADERS B L AA2 K EY1 D ER0 Z +BLOCKADES B L AA2 K EY1 D Z +BLOCKADING B L AA2 K EY1 D IH0 NG +BLOCKAGE B L AA1 K IH0 JH +BLOCKAGES B L AA1 K IH0 JH IH0 Z +BLOCKBUSTER B L AA1 K B AH2 S T ER0 +BLOCKBUSTER'S B L AA1 K B AH2 S T ER0 Z +BLOCKBUSTERS B L AA1 K B AH2 S T ER0 Z +BLOCKED B L AA1 K T +BLOCKER B L AA1 K ER0 +BLOCKERS B L AA1 K ER0 Z +BLOCKHEAD B L AA1 K HH EH2 D +BLOCKHEADS B L AA1 K HH EH2 D Z +BLOCKHOUSE B L AA1 K HH AW2 S +BLOCKHOUSES B L AA1 K HH AW2 S AH0 Z +BLOCKING B L AA1 K IH0 NG +BLOCKS B L AA1 K S +BLOCS B L AA1 K S +BLODGETT B L AA1 JH IH0 T +BLOEDEL B L OW1 D AH0 L +BLOEDORN B L OW1 D ER0 N +BLOEM B L OW1 M +BLOEMER B L OW1 M ER0 +BLOEMKER B L OW1 M K ER0 +BLOG B L AO1 G +BLOGGER B L AO1 G ER0 +BLOGGERS B L AO1 G ER0 Z +BLOGGING B L AO1 G IH0 NG +BLOGOSPHERE B L AO1 G AO0 S F IY1 R +BLOGS B L AO1 G Z +BLOHM B L OW1 M +BLOK B L AA1 K +BLOKE B L OW1 K +BLOKES B L OW1 K S +BLOM B L AA1 M +BLOMBERG B L AA1 M B ER0 G +BLOME B L OW1 M +BLOMGREN B L AO1 M G R EH0 N +BLOMKVIST B L AO1 M K W IH2 S T +BLOMQUIST B L AO1 M K W IH2 S T +BLOMSTROM B L AO1 M S T R AH0 M +BLOND B L AA1 N D +BLONDE B L AA1 N D +BLONDE'S B L AA1 N D Z +BLONDELL B L AA1 N D AH0 L +BLONDER B L AA1 N D ER0 +BLONDES B L AA1 N D Z +BLONDEST B L AA1 N D AH0 S T +BLONDIE B L AA1 N D IY0 +BLONDIN B L AA1 N D IH0 N +BLONDS B L AA1 N D Z +BLOOD B L AH1 D +BLOOD'S B L AH1 D Z +BLOODBATH B L AH1 D B AE2 TH +BLOODED B L AH1 D IH0 D +BLOODGOOD B L AH1 D G UH2 D +BLOODHOUND B L AH1 D HH AW0 N D +BLOODHOUNDS B L AH1 D HH AW0 N D Z +BLOODHOUNDS(1) B L AH1 D HH AW0 N Z +BLOODIED B L AH1 D IY0 D +BLOODIER B L AH1 D IY0 ER0 +BLOODIEST B L AH1 D IY0 AH0 S T +BLOODLESS B L AH1 D L AH0 S +BLOODLETTING B L AH1 D L EH2 T IH0 NG +BLOODLINE B L AH1 D L AY2 N +BLOODLINES B L AH1 D L AY2 N Z +BLOODS B L AH1 D Z +BLOODSHED B L AH1 D SH EH2 D +BLOODSTAIN B L AH1 D S T EY2 N +BLOODSTAINED B L AH1 D S T EY2 N D +BLOODSTAINS B L AH1 D S T EY2 N Z +BLOODSTONE B L AH1 D S T OW2 N +BLOODSTREAM B L AH1 D S T R IY2 M +BLOODSUCKER B L AH1 D S AH2 K ER0 +BLOODSUCKERS B L AH1 D S AH2 K ER0 Z +BLOODSUCKING B L AH1 D S AH2 K IH0 NG +BLOODSWORTH B L AH1 D Z W ER2 TH +BLOODTHIRSTY B L AH1 D TH ER2 S T IY0 +BLOODWORTH B L AH1 D W ER2 TH +BLOODY B L AH1 D IY0 +BLOOM B L UW1 M +BLOOM'S B L UW1 M Z +BLOOMBERG B L UW1 M B ER0 G +BLOOMBERG'S B L UW1 M B ER0 G Z +BLOOMED B L UW1 M D +BLOOMER B L UW1 M ER0 +BLOOMERS B L UW1 M ER0 Z +BLOOMFIELD B L UW1 M F IY2 L D +BLOOMING B L UW1 M IH0 NG +BLOOMINGDALE B L UW1 M IH0 NG D EY2 L +BLOOMINGDALE'S B L UW1 M IH0 NG D EY2 L Z +BLOOMINGDALES B L UW1 M IH0 NG D EY2 L Z +BLOOMINGTON B L UW1 M IH0 NG T AH0 N +BLOOMQUIST B L UW1 M K W IH2 S T +BLOOMS B L UW1 M Z +BLOOPER B L UW1 P ER0 +BLOOPERS B L UW1 P ER0 Z +BLOOR B L UH1 R +BLOSE B L OW1 Z +BLOSS B L AO1 S +BLOSSER B L AO1 S ER0 +BLOSSOM B L AA1 S AH0 M +BLOSSOMED B L AA1 S AH0 M D +BLOSSOMING B L AA1 S AH0 M IH0 NG +BLOSSOMS B L AA1 S AH0 M Z +BLOT B L AA1 T +BLOTCH B L AA1 T CH +BLOTCHED B L AA1 T CH T +BLOTCHES B L AA1 T CH AH0 Z +BLOTCHIER B L AA1 T CH IY0 ER0 +BLOTCHIEST B L AA1 T CH IY0 AH0 S T +BLOTCHING B L AA1 T CH IH0 NG +BLOTCHY B L AA1 T CH IY0 +BLOTNICK B L AA1 T N IH0 K +BLOTS B L AA1 T S +BLOTTED B L AA1 T AH0 D +BLOTTER B L AA1 T ER0 +BLOTTING B L AA1 T IH0 NG +BLOUCH B L AW1 CH +BLOUGH B L AW1 +BLOUIN B L W IY1 N +BLOUNT B L AW1 N T +BLOUSE B L AW1 S +BLOUSES B L AW1 S AH0 Z +BLOUSES(1) B L AW1 S IH0 Z +BLOW B L OW1 +BLOWDRIED B L OW1 D R AY2 D +BLOWDRIES B L OW1 D R AY2 Z +BLOWDRY B L OW1 D R AY2 +BLOWDRYER B L OW1 D R AY2 ER0 +BLOWDRYERS B L OW1 D R AY2 ER0 Z +BLOWDRYING B L OW1 D R AY2 IH0 NG +BLOWE B L OW1 +BLOWED B L OW1 D +BLOWER B L OW1 ER0 +BLOWERS B L OW1 ER0 Z +BLOWFISH B L OW1 F IH0 SH +BLOWGUN B L OW1 G AH2 N +BLOWGUNS B L OW1 G AH2 N Z +BLOWHARD B L OW1 HH AA2 R D +BLOWHARDS B L OW1 HH AA2 R D Z +BLOWHOLE B L OW1 HH OW2 L +BLOWHOLES B L OW1 HH OW2 L Z +BLOWIER B L OW1 IY0 ER0 +BLOWIEST B L OW1 IY0 AH0 S T +BLOWING B L OW1 IH0 NG +BLOWJOB B L OW1 JH AA2 B +BLOWJOBS B L OW1 JH AA2 B Z +BLOWN B L OW1 N +BLOWOUT B L OW1 AW2 T +BLOWOUTS B L OW1 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+BRANK B R AE1 NG K +BRANK'S B R AE1 NG K S +BRANKI B R AE1 NG K IY0 +BRANKO B R AE1 NG K OW0 +BRANKS B R AE1 NG K S +BRANN B R AE1 N +BRANNA B R AE1 N AH0 +BRANNAM B R AE1 N AH0 M +BRANNAN B R AE1 N AH0 N +BRANNEN B R AE1 N AH0 N +BRANNER B R AE1 N ER0 +BRANNICK B R AE1 N IH0 K +BRANNIGAN B R AE1 N IH0 G AH0 N +BRANNING B R AE1 N IH0 NG +BRANNOCK B R AE1 N AH0 K +BRANNON B R AE1 N AH0 N +BRANNUM B R AE1 N AH0 M +BRANON B R AE1 N AH0 N +BRANSCOM B R AE1 N S K AH0 M +BRANSCOMB B R AE1 N S K AH0 M +BRANSCOME B R AE1 N Z K AH2 M +BRANSCUM B R AE1 N S K AH0 M +BRANSFIELD B R AE1 N Z F IY2 L D +BRANSFORD B R AE1 N S F ER0 D +BRANSOM B R AE1 N S AH0 M +BRANSON B R AE1 N S AH0 N +BRANSON'S B R AE1 N S AH2 N Z +BRANSTAD B R AE1 N S T AE2 D +BRANSTETTER B R AE1 N S T IH0 T ER0 +BRANT B R AE1 N T +BRANTLEY B R AE1 N T L IY0 +BRANTLY B R AE1 N T L IY0 +BRANTNER B R AE1 N T N ER0 +BRANTON B R AE1 N T AH0 N +BRANUM B R AE1 N AH0 M +BRANYON B R AE1 N Y AH0 N +BRANZ B R AE1 N Z +BRAQUE B R AE1 K +BRAS B R AE1 S +BRAS(1) B R AA1 S +BRASCADE B R AH0 S K EY1 D +BRASCAN B R AE1 S K AH0 N +BRASCH B R AE1 SH +BRASCO B R AE1 S K OW0 +BRASE B R EY1 Z +BRASEL B R AE1 S AH0 L +BRASELTON B R AH0 S EH1 L T AH0 N +BRASFIELD B R AE1 S F IY0 L D +BRASH B R AE1 SH +BRASHEAR B R AE1 SH IY0 R +BRASHEARS B R AE1 SH IY0 R Z +BRASHER B R AE1 SH ER0 +BRASHERS B R AE1 SH ER0 Z +BRASHIER B R AE1 SH IY0 ER0 +BRASHNESS B R AE1 SH N AH0 S +BRASIL B R AE1 S AH0 L +BRASIL(1) B R AH0 S IY1 L +BRASILIA B R AH0 Z IH1 L Y AH0 +BRASILIA(1) B R AH0 S IH1 L Y AH0 +BRASINGTON B R AE1 S IH0 NG T AH0 N +BRASOW B R AE1 S OW0 +BRASOW(1) B R AE1 Z OW0 +BRASS B R AE1 S +BRASSARD B R AE1 S ER0 D +BRASSEAUX B R AA0 S OW1 +BRASSELL B R AE1 S AH0 L +BRASSERIE B R AE1 S AH0 R IY2 +BRASSES B R AE1 S IH0 Z +BRASSEUR B R AE1 S ER2 +BRASSEUX B R AA1 S UH2 +BRASSFIELD B R AE1 S F IY2 L D +BRASSO B R AE1 S OW0 +BRASSO'S B R AE1 S OW0 Z +BRASSY B R AE1 S IY0 +BRASWELL B R AE1 S W EH0 L +BRAT B R AE1 T +BRATCHER B R AE1 CH ER0 +BRATON B R AE1 T IH0 N +BRATS B R AE1 T S +BRATSCH B R AE1 CH +BRATT B R AE1 T +BRATTAIN B R AH0 T EY1 N +BRATTASLAVA B R AA2 T AH0 S L AA1 V AH0 +BRATTASLAVA'S B R AA2 T AH0 S L AA1 V AH0 Z +BRATTEN B R AE1 T AH0 N +BRATTIN B R AE1 T IH0 N +BRATTLE B R AE1 T AH0 L +BRATTON B R AE1 T AH0 N +BRATWURST B R AE1 T W ER0 S T +BRATZ B R AE1 T S +BRAU B R AW1 +BRAUCH B R AO1 CH +BRAUCHER B R AO1 CH ER0 +BRAUCHLI B R AO1 CH L IY0 +BRAUD B R AO1 D +BRAUDE B R AO1 D +BRAUER B R AW1 ER0 +BRAUGHTON B R AO1 T AH0 N +BRAUHAU B R AA1 HH AA2 +BRAULT B R AO1 L T +BRAUN B R AO1 N +BRAUN'S B R AO1 N Z +BRAUND B R AO1 N D +BRAUNE B R AO1 N +BRAUNER B R AO1 N ER0 +BRAUNS B R AO1 N Z +BRAUNSCHWEIG B R AW1 N SH W AY0 G +BRAUNSTEIN B R AO1 N S T IY2 N +BRAUNSTEIN(1) B R AO1 N S T AY2 N +BRAUNWALD B R AO1 N W AO2 L D +BRAUSE B R AO1 Z +BRAUTIGAM B R OW1 T IH0 G AH0 M +BRAUTIGAMS B R AO1 T IH0 G AE0 M Z +BRAVADO B R AH0 V AA1 D OW0 +BRAVE B R EY1 V +BRAVED B R EY1 V D +BRAVEHEART B R EY1 V HH AA0 R T +BRAVELY B R EY1 V L IY0 +BRAVER B R EY1 V ER0 +BRAVERMAN B R EY1 V ER0 M AH0 N +BRAVERY B R EY1 V ER0 IY0 +BRAVES B R EY1 V Z +BRAVES' B R EY1 V Z +BRAVEST B R EY1 V AH0 S T +BRAVING B R EY1 V IH0 NG +BRAVO B R AA1 V OW0 +BRAVURA B R AH0 V Y UH1 R AH0 +BRAWER B R AO1 ER0 +BRAWL B R AO1 L +BRAWLEY B R AO1 L IY0 +BRAWLING B R AO1 L IH0 NG +BRAWLS B R AO1 L Z +BRAWN B R AO1 N +BRAWNER B R AO1 N ER0 +BRAWNY B R AO1 N IY0 +BRAXTON B R AE1 K S T AH0 N +BRAY B R EY1 +BRAYBOY B R EY1 B OY2 +BRAYER B R EY1 ER0 +BRAYFIELD B R EY1 F IY2 L D +BRAYMAN B R EY1 M AH0 N +BRAYTON B R EY1 T AH0 N +BRAZ B R AE1 Z +BRAZDA B R AE1 Z D AH0 +BRAZEAL B R AH0 Z IY1 L +BRAZEAU B R AH0 Z OW1 +BRAZEE B R AE1 Z IY0 +BRAZEL B R AE1 Z AH0 L +BRAZELL B R AE1 Z AH0 L +BRAZELTON B R AH0 Z EH1 L T AH0 N +BRAZEN B R EY1 Z AH0 N +BRAZENLY B R EY1 Z AH0 N L IY0 +BRAZENNESS B R EY1 Z AH0 N AH0 S +BRAZIEL B R AH0 Z IY1 L +BRAZIER B R EY1 Z IY0 ER0 +BRAZIERS B R EY1 ZH ER0 Z +BRAZIL B R AH0 Z IH1 L +BRAZIL'S B R AH0 Z IH1 L Z +BRAZILE B R AA1 Z AY0 L +BRAZILIAN B R AH0 Z IH1 L Y AH0 N +BRAZILIANS B R AH0 Z IH1 L Y AH0 N Z +BRAZILL B R AE1 Z AH0 L +BRAZOS B R AA1 Z OW0 S +BRAZZAVILLE B R AE1 Z AH0 V IH0 L +BRAZZAVILLE'S B R AE1 Z AH0 V IH0 L Z +BRAZZEL B R AE1 Z AH0 L +BRAZZELL B R AE1 Z AH0 L +BRCA B R IH1 K AH0 +BRCKO B ER1 CH K OW0 +BRCKO'S B ER1 CH K OW0 Z +BREA B R IY1 +BREACH B R IY1 CH +BREACHED B R IY1 CH T +BREACHES B R IY1 CH IH0 Z +BREACHING B R IY1 CH IH0 NG +BREAD B R EH1 D +BREADBASKET B R EH1 D B AE2 S K AH0 T +BREADBOX B R EH1 D B AA2 K S +BREADED B R EH1 D IH0 D +BREADFRUIT B R EH1 D F R UW2 T +BREADING B R EH1 D IH0 NG +BREADS B R EH1 D Z +BREADTH B R EH1 D TH +BREADWINNER B R EH1 D W IH2 N ER0 +BREADWINNERS B R EH1 D W IH2 N ER0 Z +BREADY B R EH1 D IY0 +BREAK B R EY1 K +BREAK-IN B R EY1 K IH2 N +BREAKABLE B R EY1 K AH0 B AH0 L +BREAKAGE B R EY1 K IH0 JH +BREAKAWAY B R EY1 K AH0 W EY2 +BREAKDOWN B R EY1 K D AW2 N +BREAKDOWNS B R EY1 K D AW2 N Z +BREAKER B R EY1 K ER0 +BREAKERS B R EY1 K ER0 Z +BREAKEVEN B R EY1 K IY2 V AH0 N +BREAKEY B R EY1 K IY0 +BREAKFAST B R EH1 K F AH0 S T +BREAKFASTS B R EH1 K F AH0 S T S +BREAKFIELD B R EY1 K F IY2 L D +BREAKING B R EY1 K IH0 NG +BREAKMATE B R EY1 K M EY2 T +BREAKNECK B R EY1 K N EH2 K +BREAKOUT B R EY1 K AW2 T +BREAKOUTS B R EY1 K AW2 T S +BREAKS B R EY1 K S +BREAKTHROUGH B R EY1 K TH R UW2 +BREAKTHROUGHS B R EY1 K TH R UW2 Z +BREAKUP B R EY1 K AH2 P +BREAKUPS B R EY1 K AH0 P S +BREAKWATER B R EY1 K W AO2 T ER0 +BREAKY B R EY1 K IY0 +BREAM B R IY1 M +BREAN B R IY1 N +BREARLEY B R ER1 L IY0 +BREAST B R EH1 S T +BREASTED B R EH1 S T AH0 D +BREASTED(1) B R EH1 S T IH0 D +BREASTFED B R EH1 S T F EH2 D +BREASTFEED B R EH1 S T F IY0 D +BREASTFEEDING B R EH1 S T F IY0 D IH0 NG +BREASTFEEDING'S B R EH1 S T F IY0 D IH0 NG Z +BREASTFEEDS B R EH1 S T F IY0 D Z +BREASTING B R EH1 S T IH0 NG +BREASTPLATE B R EH1 S T P L EY2 T +BREASTS B R EH1 S T S +BREATH B R EH1 TH +BREATHE B R IY1 DH +BREATHED B R IY1 DH D +BREATHER B R IY1 DH ER0 +BREATHES B R IY1 DH Z +BREATHING B R IY1 DH IH0 NG +BREATHLESS B R EH1 TH L AH0 S +BREATHLESSLY B R EH1 TH L AH0 S L IY0 +BREATHS B R EH1 TH S +BREATHTAKING B R EH1 TH T EY2 K IH0 NG +BREATHTAKINGLY B R EH1 TH T EY2 K IH0 NG L IY0 +BREATHY B R EH1 TH IY0 +BREAU B R OW1 +BREAULT B R OW1 +BREAUX B R OW1 +BREAUX(1) B R UW1 +BREAZEALE B R IY1 Z IY2 L +BREBACH B R EH1 B AH0 K +BRECHBILL B R EH1 K B AH0 L +BRECHEEN B R EH1 K IY0 N +BRECHEISEN B R EH1 K AY0 S AH0 N +BRECHER B R EH1 K ER0 +BRECHT B R EH1 K T +BRECHTEL B R EH1 K T AH0 L +BRECK B R EH1 K +BRECKENRIDGE B R EH1 K AH0 N R IH2 JH +BRECKER B R EH1 K ER0 +BRECO B R EH1 K OW0 +BRED B R EH1 D +BREDA B R EY1 D AH0 +BREDE B R IY1 D +BREDEN B R IY1 D AH0 N +BREDESON B R EH1 D IH0 S AH0 N +BREE B R IY1 +BREECE B R IY1 S +BREECH B R IY1 CH +BREECHES B R IY1 CH IH0 Z +BREECHING B R IY1 CH IH0 NG +BREED B R IY1 D +BREED'S B R IY1 D Z +BREEDEN B R IY1 D AH0 N +BREEDEN'S B R IY1 D AH0 N Z +BREEDER B R IY1 D ER0 +BREEDERS B R IY1 D ER0 Z +BREEDERS' B R IY1 D ER0 Z +BREEDING B R IY1 D IH0 NG +BREEDLOVE B R IY1 D L AH2 V +BREEDS B R IY1 D Z +BREELAND B R IY1 L AH0 N D +BREEN B R IY1 N +BREES B R IY1 Z +BREESE B R IY1 Z +BREEZE B R IY1 Z +BREEZED B R IY1 Z D +BREEZES B R IY1 Z IH0 Z +BREEZEWAY B R IY1 Z W EY2 +BREEZY B R IY1 Z IY0 +BREGE B R IY1 JH +BREGER B R IY1 G ER0 +BREGLIO B R EH1 G L IY0 OW0 +BREGMAN B R EH1 G M AH0 N +BREGUET B R IY1 G AH0 T +BREHM B R EH1 M +BREHMER B R EH1 M ER0 +BREIDENBACH B R AY1 D IH0 N B AA0 K +BREIDENSTEIN B R AY1 D AH0 N S T AY0 N +BREIDENSTEIN(1) B R AY1 D AH0 N S T IY0 N +BREIER B R AY1 ER0 +BREIGHNER B R EY1 N ER0 +BREIGHTON B R AY1 T AH0 N +BREINER B R AY1 N ER0 +BREINING B R AY1 N IH0 NG +BREININGER B R AY1 N IH0 NG ER0 +BREISCH B R AY1 SH +BREIT B R IY1 T +BREITBACH B R AY1 T B AA2 K +BREITBARTH B R AY1 T B AA2 R TH +BREITENBACH B R AY1 T IH0 N B AA0 K +BREITENSTEIN B R AY1 T AH0 N S T AY0 N +BREITENSTEIN(1) B R AY1 T AH0 N S T IY0 N +BREITHAUPT B R AY1 TH AW0 P T +BREITKREUTZ B R AY1 T K R OY2 T S +BREITLING B R AY1 T AH0 L IH0 NG +BREITLING(1) B R AY1 T L IH0 NG +BREITMAN B R AY1 T M AH0 N +BREITSCHWERDT B R AY1 CH W ER0 T +BREITWEISER B R AY1 T W AY2 S ER0 +BREITZMAN B R AY1 T S M AH0 N +BREKKE B R EH1 K +BRELAND B R EH1 L AH0 N D +BRELSFORD B R EH1 L S F ER0 D +BREM B R EH1 M +BREMEN B R EH1 M AH0 N +BREMER B R IY1 M ER0 +BREMMER B R EH1 M ER0 +BREMNER B R EH1 M N ER0 +BREMS B R EH1 M Z +BREN B R EH1 N +BRENDA B R EH1 N D AH0 +BRENDA'S B R EH1 N D AH0 Z +BRENDAN B R EH1 N D AH0 N +BRENDEL B R EH1 N D AH0 L +BRENDEN B R EH1 N D AH0 N +BRENDER B R EH1 N D ER0 +BRENDLE B R EH1 N D AH0 L +BRENDLINGER B R EH1 N D AH0 L IH0 NG ER0 +BRENDLINGER(1) B R EH1 N D L IH0 NG ER0 +BRENDON B R EH1 N D AH0 N +BRENDOR B R EH1 N D ER0 +BRENDSEL B R EH1 N D S AH0 L +BRENEMAN B R IY1 N M AH0 N +BRENER B R IY1 N ER0 +BRENES B R IY1 N Z +BRENGLE B R IH1 NG AH0 L +BRENIZER B R EH1 N AY0 Z ER0 +BRENN B R EH1 N +BRENNA B R EH1 N AH0 +BRENNAN B R EH1 N AH0 N +BRENNAN'S B R EH1 N AH0 N Z +BRENNANS B R EH1 N AH0 N Z +BRENNECKE B R EH1 N IH0 K +BRENNEKE B R EH1 N AH0 K IY0 +BRENNEMAN B R EH1 N M AH0 N +BRENNEN B R EH1 N AH0 N +BRENNER B R EH1 N ER0 +BRENNING B R EH1 N IH0 NG +BRENSINGER B R EH1 N S IH0 NG ER0 +BRENT B R EH1 N T +BRENTANO B R EH2 N T AA1 N OW0 +BRENTANOS B R EH2 N T AA1 N OW0 Z +BRENTLINGER B R EH1 N T AH0 L IH0 NG ER0 +BRENTLINGER(1) B R EH1 N T L IH0 NG ER0 +BRENTON B R EH1 N T AH0 N +BRENTS B R EH1 N T S +BRENTWOOD B R EH1 N T W UH2 D +BREON B R IY1 AH0 N +BRESCA B R EH1 S K AH0 +BRESCIA B R EH1 S CH AH0 +BRESEE B R IH0 S IY1 +BRESETTE B R IH0 S EH1 T +BRESHEARS B R EH1 SH IY0 R Z +BRESLAW B R EH1 S L AA0 +BRESLER B R EH1 S L ER0 +BRESLIN B R EH1 S L IH0 N +BRESLOW B R EH1 S L OW0 +BRESNAHAN B R EH1 S N AH0 HH AE0 N +BRESNAN B R EH1 S N AH0 N +BRESNICK B R EH1 S N IH0 K +BRESS B R EH1 S +BRESSE B R EH1 S +BRESSEAU B R EH1 S OW0 +BRESSER B R EH1 S ER0 +BRESSER'S B R EH1 S ER0 Z +BRESSETTE B R EH2 S EH1 T +BRESSLER B R EH1 S L ER0 +BRESSMAN B R EH1 S M AH0 N +BRESSON B R EH1 S AH0 N +BREST B R EH1 S T +BRESTER B R EH1 S T ER0 +BRET B R EH1 T +BRETH B R EH1 TH +BRETHAUER B R EH1 TH AW0 ER0 +BRETHEN B R IY1 TH AH0 N +BRETHREN B R EH1 DH R AH0 N +BRETON B R EH1 T AH0 N +BRETSCHNEIDER B R EH1 CH N AY0 D ER0 +BRETT B R EH1 T +BRETTHAUER B R EH1 T HH AW2 ER0 +BRETTON B R EH1 T AH0 N +BRETTS B R EH1 T S +BRETTSCHNEIDER B R EH1 CH N AY2 D ER0 +BRETTSCHNEIDER(1) B R EH1 T S N AY2 D ER0 +BRETZ B R EH1 T S +BREUER B R UW1 ER0 +BREUNIG B R UW1 N IH0 G +BREUNINGER B R UW1 N IH0 NG ER0 +BREVARD B R EH1 V ER0 D +BREVETS B R AH0 V EH1 T S +BREVIG B R EH1 V IH0 G +BREVIK B R EH1 V IH0 K +BREVITY B R EH1 V AH0 T IY0 +BREW B R UW1 +BREWBAKER B R UW1 B EY2 K ER0 +BREWED B R UW1 D +BREWER B R UW1 ER0 +BREWER'S B R UW1 ER0 Z +BREWERIES B R UW1 ER0 IY0 Z +BREWERIES(1) B R UW1 R IY0 Z +BREWERS B R UW1 ER0 Z +BREWERS' B R UW1 ER0 Z +BREWERY B R UW1 ER0 IY0 +BREWING B R UW1 IH0 NG +BREWINGTON B R UW1 IH0 NG T AH0 N +BREWRY B R UW1 R IY0 +BREWS B R UW1 Z +BREWSTER B R UW1 S T ER0 +BREWTON B R UW1 T AH0 N +BREY B R EY1 +BREYER B R EY1 ER0 +BREYER'S B R EY1 ER0 Z +BREYFOGLE B R EY1 F OW2 G AH0 L +BREZA B R EH1 Z AH0 +BREZHNEV B R EH1 Z N AH0 V +BREZHNEV(1) B R EH1 Z N EH0 F +BREZHNEV'S B R EH1 Z N AH0 V Z +BREZHNEV'S(1) B R EH1 Z N EH0 F S +BREZINA B R EH0 Z IY1 N AH0 +BREZINSKI B R IH0 Z IH1 N S K IY0 +BRIA B R IY1 AH0 +BRIAN B R AY1 AH0 N +BRIAN'S B R AY1 AH0 N Z +BRIANA B R IY0 AE1 N AH0 +BRIANA(1) B R IY0 AA1 N AH0 +BRIANA'S B R IY0 AE1 N AH0 Z +BRIANA'S(1) B R IY0 AA1 N AH0 Z +BRIANCON B R AY1 AH0 N S AH0 N +BRIAND B R AY1 AH0 N D +BRIANNA B R IY0 AE1 N AH0 +BRIANNA'S B R IY0 AE1 N AH0 Z +BRIANT B R AY1 AH0 N T +BRIAR B R AY1 ER0 +BRIARCLIFF B R AY1 R K L IH2 F +BRIBE B R AY1 B +BRIBED B R AY1 B D +BRIBERY B R AY1 B ER0 IY0 +BRIBES B R AY1 B Z +BRIBING B R AY1 B IH0 NG +BRIC B R IH1 K +BRICCETTI B R IH0 CH EH1 T IY0 +BRICCO B R IH1 K OW0 +BRICE B R AY1 S +BRICENO B R IY0 CH EH1 N OW0 +BRICK B R IH1 K +BRICKBAT B R IH1 K B AE2 T +BRICKBATS B R IH1 K B AE2 T S +BRICKEL B R IH1 K AH0 L +BRICKELL B R IH1 K AH0 L +BRICKER B R IH1 K ER0 +BRICKEY B R IH1 K IY0 +BRICKHOUSE B R IH1 K HH AW2 S +BRICKLAYER B R IH1 K L EY2 ER0 +BRICKLAYERS B R IH1 K L EY2 ER0 Z +BRICKLE B R IH1 K AH0 L +BRICKLER B R IH1 K L ER0 +BRICKLEY B R IH1 K L IY0 +BRICKLIN B R IH1 K L IH0 N +BRICKLIN'S B R IH1 K L IH0 N Z +BRICKMAN B R IH1 K M AH0 N +BRICKNER B R IH1 K N ER0 +BRICKS B R IH1 K S +BRICKYARD B R IH1 K Y AA2 R D +BRICOM B R IH1 K AH0 M +BRIDAL B R AY1 D AH0 L +BRIDE B R AY1 D +BRIDE'S B R AY1 D Z +BRIDEAU B R IH0 D OW1 +BRIDEGROOM B R AY1 D G R UW2 M +BRIDEGROOM'S B R AY1 D G R UW2 M Z +BRIDEN B R AY1 D AH0 N +BRIDENBAUGH B R IH1 D IH0 N B AW0 +BRIDENSTINE B R IH1 D IH0 N S T IY0 N +BRIDES B R AY1 D Z +BRIDESBURG B R AY1 D Z B AH0 R G +BRIDESMAID B R AY1 D Z M EY2 D +BRIDESMAID'S B R AY1 D Z M EY2 D Z +BRIDESMAIDS B R AY1 D Z M EY2 D Z +BRIDESMAIDS' B R AY1 D Z M EY2 D Z +BRIDGE B R IH1 JH +BRIDGE'S B R IH1 JH IH0 Z +BRIDGED B R IH1 JH D +BRIDGEFORD B R IH1 JH F AO0 R D +BRIDGEFORTH B R IH1 JH F AO2 R TH +BRIDGEHEAD B R IH1 JH HH EH2 D +BRIDGEMAN B R IH1 JH M AH0 N +BRIDGEPORT B R IH1 JH P AO2 R T +BRIDGER B R IH1 JH ER0 +BRIDGERS B R IH1 JH ER0 Z +BRIDGES B R IH1 JH AH0 Z +BRIDGES(1) B R IH1 JH IH0 Z +BRIDGESTONE B R IH1 JH S T OW2 N +BRIDGESTONE'S B R IH1 JH S T OW2 N Z +BRIDGET B R IH1 JH AH0 T +BRIDGET(1) B R IH1 JH IH0 T +BRIDGET'S B R IH1 JH AH0 T S +BRIDGETON B R IH1 JH T AH0 N +BRIDGETOWN B R IH1 JH T AW2 N +BRIDGETT B R IH1 JH IH0 T +BRIDGETTE B R IH1 JH IH0 T +BRIDGETTE(1) B R IH2 JH IY1 T +BRIDGEWATER B R IH1 JH W AO2 T ER0 +BRIDGHAM B R IH1 JH HH AH0 M +BRIDGING B R IH1 JH IH0 NG +BRIDGMAN B R IH1 JH M AH0 N +BRIDIE B R IH1 D IY0 +BRIDLE B R AY1 D AH0 L +BRIDLED B R AY1 D AH0 L D +BRIDWELL B R IH1 D W EH2 L +BRIE B R IY1 +BRIEANT B R IY1 AH0 N T +BRIEF B R IY1 F +BRIEFCASE B R IY1 F K EY2 S +BRIEFCASES B R IY1 F K EY2 S IH0 Z +BRIEFED B R IY1 F T +BRIEFER B R IY1 F ER0 +BRIEFERS B R IY1 F ER0 Z +BRIEFEST B R IY1 F AH0 S T +BRIEFING B R IY1 F IH0 NG +BRIEFINGS B R IY1 F IH0 NG Z +BRIEFLY B R IY1 F L IY0 +BRIEFS B R IY1 F S +BRIEGEL B R IY1 G AH0 L +BRIEGER B R IY1 G ER0 +BRIEL B R IY1 L +BRIEN B R AY1 IH0 N +BRIENZA B R IY1 N Z AH0 +BRIER B R AY1 ER0 +BRIERE B R IH1 R +BRIERLEY B R AY1 ER0 L IY0 +BRIERLY B R AY1 ER0 L IY0 +BRIESE B R IY1 Z +BRIETZKE B R IY1 T S K IY0 +BRIG B R IH1 G +BRIGADE B R AH0 G EY1 D +BRIGADE(1) B R IH0 G EY1 D +BRIGADEER B R IH2 G AH0 D IH1 R +BRIGADES B R IH0 G EY1 D Z +BRIGADIER B R IH2 G AH0 D IH1 R +BRIGANCE B R IH1 G AH0 N S +BRIGANDI B R IH0 G AE1 N D IY0 +BRIGANTE B R IY0 G AA1 N T IY0 +BRIGANTI B R IH0 G AE1 N T IY0 +BRIGANTINE B R IH2 G AH0 N T IY1 N +BRIGGS B R IH1 G Z +BRIGGSTONE B R IH1 G S T OW0 N +BRIGHAM B R IH1 G AH0 M +BRIGHAM'S B R IH1 G AH0 M Z +BRIGHAMS B R IH1 G AH0 M Z +BRIGHT B R AY1 T +BRIGHT'S B R AY1 T S +BRIGHTBILL B R AY1 T B IH2 L +BRIGHTEN B R AY1 T AH0 N +BRIGHTENED B R AY1 T AH0 N D +BRIGHTENING B R AY1 T AH0 N IH0 NG +BRIGHTENING(1) B R AY1 T N IH0 NG +BRIGHTENS B R AY1 T AH0 N Z +BRIGHTER B R AY1 T ER0 +BRIGHTEST B R AY1 T AH0 S T +BRIGHTLY B R AY1 T L IY0 +BRIGHTMAN B R AY1 T M AH0 N +BRIGHTNESS B R AY1 T N AH0 S +BRIGHTON B R AY1 T AH0 N +BRIGHTWELL B R AY1 T W EH2 L +BRIGITTE B R IH1 JH IH0 T +BRIGMAN B R IH1 G M AH0 N +BRIGNAC B R IH1 G N AH0 K +BRIGNER B R AY1 G N ER0 +BRIGODE B R IH0 G OW1 D AH0 +BRIGUGLIO B R IH0 G AH1 G L IY0 OW0 +BRILES B R AY1 L Z +BRILEY B R IH1 L IY0 +BRILL B R IH1 L +BRILL'S B R IH1 L Z +BRILLHART B R IH1 L HH AA2 R T +BRILLIANCE B R IH1 L Y AH0 N S +BRILLIANT B R IH1 L Y AH0 N T +BRILLIANTLY B R IH1 L Y AH0 N T L IY0 +BRILLSTEIN B R IH1 L S T IY2 N +BRILLSTEIN(1) B R IH1 L S T AY2 N +BRIM B R IH1 M +BRIMBERRY B R IH1 M B EH2 R IY0 +BRIMELOW B R IH1 M AH0 L OW0 +BRIMER B R AY1 M ER0 +BRIMHALL B R IH1 M HH AO2 L +BRIMM B R IH1 M +BRIMMED B R IH1 M D +BRIMMER B R IH1 M ER0 +BRIMMING B R IH1 M IH0 NG +BRIMSTONE B R IH1 M S T OW0 N +BRIN B R IH1 N +BRINDEL B R IH1 N D EH2 L +BRINDLE B R IH1 N D AH0 L +BRINDLEY B R IH1 N D L IY0 +BRINE B R AY1 N +BRINEGAR B R IH1 N IH0 G ER0 +BRINER B R AY1 N ER0 +BRINES B R AY1 N Z +BRINEY B R IH1 N IY0 +BRING B R IH1 NG +BRINGHURST B R IH1 NG HH ER0 S T +BRINGING B R IH1 NG IH0 NG +BRINGLE B R IH1 NG G AH0 L +BRINGMAN B R IH1 NG M AH0 N +BRINGS B R IH1 NG Z +BRINGTON B R IH1 NG T AH0 N +BRINING B R AY1 N IH0 NG +BRINK B R IH1 NG K +BRINK'S B R IH1 NG K S +BRINKER B R IH1 NG K ER0 +BRINKERHOFF B R IH1 NG K ER0 HH AO2 F +BRINKLEY B R IH1 NG K L IY0 +BRINKLEY'S B R IH1 NG K L IY0 Z +BRINKLY B R IH1 NG K L IY0 +BRINKMAN B R IH1 NG K M AH0 N +BRINKMANN B R IH1 NG K M AH0 N +BRINKMANN'S B R IH1 NG K M AH0 N Z +BRINKMANSHIP B R IH1 NG K M AH0 N SH IH2 P +BRINKMEIER B R IH1 NG K M AY0 ER0 +BRINKMEYER B R IH1 NG K M AY0 ER0 +BRINKS B R IH1 NG K S +BRINKSMANSHIP B R IH1 NG K S M AH0 N SH IH2 P +BRINLEE B R IH1 N L IY0 +BRINLEY B R IH1 N L IY0 +BRINN B R IH1 N +BRINNER B R IH1 N ER0 +BRINSER B R IH1 N S ER0 +BRINSFIELD B R IH1 N S F IY0 L D +BRINSON B R IH1 N S AH0 N +BRINTEC B R IH1 N T EH2 K +BRINTON B R IH1 N T AH0 N +BRIO B R AY1 OW0 +BRIOCHE B R IY2 OW1 SH +BRIOCHE(1) B R IY1 AA0 SH +BRIODY B R AY1 AH0 D IY0 +BRION B R AY1 AH0 N +BRIONES B R IY0 OW1 N EH0 S +BRIONY B R AY1 AH0 N IY2 +BRIONY'S B R AY1 AH0 N IY2 Z +BRIQUEMONT B R IH1 K M AO0 N T +BRISBANE B R IH1 Z B EY2 N +BRISBIN B R IH1 Z B IH0 N +BRISBOIS B R IH0 Z B W AA1 +BRISBOIS(1) B R IH1 Z B W AA2 +BRISBON B R IH1 Z B AH0 N +BRISBURG B R IH1 S B ER0 G +BRISCO B R IY1 S K OW0 +BRISCOE B R IH1 S K OW0 +BRISENDINE B R IH1 S IH0 N D AY2 N +BRISENO B R IY0 S EH1 N OW0 +BRISENO'S B R IY0 S EH1 N OW0 Z +BRISK B R IH1 S K +BRISKER B R IH1 S K ER0 +BRISKET B R IH1 S K AH0 T +BRISKEY B R IH1 S K IY0 +BRISKI B R IH1 S K IY0 +BRISKIN B R IH1 S K IH0 N +BRISKLY B R IH1 S K L IY0 +BRISKY B R IH1 S K IY0 +BRISLIN B R IH1 S L IH0 N +BRISON B R IH1 S AH0 N +BRISSETTE B R IH0 S EH1 T +BRISSEY B R IH1 S IY0 +BRISSON B R IH1 S AH0 N +BRISTER B R IH1 S T ER0 +BRISTLE B R IH1 S AH0 L +BRISTLED B R IH1 S AH0 L D +BRISTLES B R IH1 S AH0 L Z +BRISTLING B R IH1 S AH0 L IH0 NG +BRISTLING(1) B R IH1 S L IH0 NG +BRISTOL B R IH1 S T AH0 L +BRISTOL'S B R IH1 S T AH0 L Z +BRISTOW B R IH1 S T OW0 +BRIT B R IH1 T +BRITA B R IY1 T AH0 +BRITAIN B R IH1 T AH0 N +BRITAIN'S B R IH1 T AH0 N Z +BRITAINS B R IH1 T AH0 N Z +BRITANNIA B R IH0 T AE1 N IY0 AH0 +BRITANNICA B R IH0 T AE1 N IH0 K AH0 +BRITCHER B R IH1 CH ER0 +BRITCHES B R IH1 CH AH0 Z +BRITE B R AY1 T +BRITIAN B R IH1 SH AH0 N +BRITISH B R IH1 T IH0 SH +BRITNELL B R IH1 T N AH0 L +BRITNEY B R IH1 T N IY2 +BRITNEY'S B R IH1 T N IY2 Z +BRITO B R IY1 T OW0 +BRITOIL B R IH0 T OY1 L +BRITON B R IH1 T AH0 N +BRITONS B R IH1 T AH0 N Z +BRITONS' B R IH1 T AH0 N Z +BRITS B R IH1 T S +BRITSCH B R IH1 CH +BRITT B R IH1 T +BRITTAIN B R IH1 T AH0 N +BRITTAN B R IH1 T AH0 N +BRITTANIA B R IH0 T AE1 N IY0 AH0 +BRITTANIA(1) B R IH0 T AE1 N Y AH0 +BRITTANY B R IH1 T AH0 N IY0 +BRITTEN B R IH1 T AH0 N +BRITTENHAM B R IH1 T IH0 N HH AH0 M +BRITTIAN B R IH1 T IY0 AH0 N +BRITTIN B R IH1 T IH0 N +BRITTINGHAM B R IH1 T IH0 NG HH AE0 M +BRITTLE B R IH1 T AH0 L +BRITTLER B R IH1 T L ER0 +BRITTLEST B R IH1 T L IH0 S T +BRITTON B R IH1 T AH0 N +BRITTS B R IH1 T S +BRITZ B R IH1 T S +BRIX B R IH1 K S +BRIXEY B R IH1 K S IY0 +BRIXIUS B R AY1 K S IY0 IH0 S +BRIZENDINE B R IY0 Z EH0 N D IY1 N IY0 +BRIZILL B R IH0 Z IH1 L +BRIZOLA B R IH0 Z OW1 L AH0 +BRIZZI B R IH1 Z IY0 +BRIZZOLARA B R IY0 T S OW0 L AA1 R AH0 +BRO B R OW1 +BRO'S B R OW1 Z +BROACH B R OW1 CH +BROACHED B R OW1 CH T +BROACHES B R OW1 CH IH0 Z +BROACHING B R OW1 CH IH0 NG +BROAD B R AO1 D +BROAD'S B R AO1 D Z +BROADACRE B R AO1 D EY0 K ER0 +BROADAWAY B R AO1 D AH0 W EY2 +BROADBAND B R AO1 D B AE2 N D +BROADBASE B R AO1 D B EY2 S +BROADBASED B R AO1 D B EY2 S T +BROADBEACH B R AO1 D B IY2 CH +BROADBENT B R AO1 D B EH2 N T +BROADCAST B R AO1 D K AE2 S T +BROADCASTER B R AO1 D K AE2 S T ER0 +BROADCASTER'S B R AO1 D K AE2 S T ER0 Z +BROADCASTERS B R AO1 D K AE2 S T ER0 Z +BROADCASTERS' B R AO1 D K AE2 S T ER0 Z +BROADCASTING B R AO1 D K AE2 S T IH0 NG +BROADCASTING'S B R AO1 D K AE2 S T IH0 NG Z +BROADCASTS B R AO1 D K AE2 S T S +BROADDUS B R AO1 D IH0 S +BROADEN B R AO1 D AH0 N +BROADENED B R AO1 D AH0 N D +BROADENING B R AO1 D AH0 N IH0 NG +BROADENING(1) B R AO1 D N IH0 NG +BROADENS B R AO1 D AH0 N Z +BROADER B R AO1 D ER0 +BROADEST B R AO1 D IH0 S T +BROADHEAD B R AO1 D HH EH2 D +BROADHURST B R AO1 D HH ER0 S T +BROADIE B R AO1 D IY0 +BROADLEY B R AO1 D L IY0 +BROADLY B R AO1 D L IY0 +BROADNAX B R AO1 D N AE0 K S +BROADPFOOT B R AO1 D F UH0 T +BROADRICK B R AO1 D R IH0 K +BROADSIDE B R AO1 D S AY2 D +BROADSIDED B R AO1 D S AY2 D IH0 D +BROADSTREET B R AO1 D S T R IY2 T +BROADSWORD B R AO1 D S AO2 R D +BROADUS B R OW1 D AH0 S +BROADVIEW B R AO1 D V Y UW2 +BROADWAY B R AO1 D W EY2 +BROADWAY'S B R AO1 D W EY2 Z +BROADWELL B R AO1 D W EH2 L +BROADY B R AO1 D IY0 +BROBDINGNAGIAN B R AO2 B D IH0 G N AE1 G IY0 AH0 N +BROBDINGNAGIANS B R AO2 B D IH0 G N AE1 G IY0 AH0 N Z +BROBECK B R OW1 B EH2 K +BROBERG B R OW1 B ER0 G +BROBST B R AA1 B S T +BROC B R AA1 K +BROCADE B R OW0 K EY1 D +BROCADES B R OW0 K EY1 D Z +BROCATO B R OW0 K AA1 T OW0 +BROCCO B R AA1 K OW0 +BROCCOLI B R AA1 K AH0 L IY0 +BROCCOLI(1) B R AA1 K L IY0 +BROCE B R OW1 S +BROCHU B R OW1 K UW0 +BROCHURE B R OW0 SH UH1 R +BROCHURES B R OW0 SH UH1 R Z +BROCIOUS B R AH0 SH IY1 S +BROCK B R AA1 K +BROCK'S B R AA1 K S +BROCKBANK B R AA1 K B AH0 NG K +BROCKEL B R AA1 K AH0 L +BROCKER B R AA1 K ER0 +BROCKERT B R AA1 K ER0 T +BROCKETT B R AA1 K IH0 T +BROCKHAUS B R AA1 K HH AW2 S +BROCKHOFF B R AA1 K HH AO2 F +BROCKHOUSE B R AA1 K HH AW2 S +BROCKIE B R AA1 K IY0 +BROCKINGTON B R AA1 K IH0 NG T AH0 N +BROCKLEHURST B R AA1 K AH0 L HH ER0 S T +BROCKLEY B R AA1 K L IY0 +BROCKLIN B R AA1 K L IH0 N +BROCKLIN'S B R AA1 K L IH0 N Z +BROCKMAN B R AA1 K M AH0 N +BROCKMANN B R AA1 K M AH0 N +BROCKMEIER B R AA1 K M AY0 ER0 +BROCKMEYER B R AA1 K M AY0 ER0 +BROCKNER B R AA1 K N ER0 +BROCKSMITH B R AA1 K S M IH2 TH +BROCKTON B R AA1 K T AH0 N +BROCKWAY B R AA1 K W EY2 +BROCKWAY'S B R AA1 K W EY2 Z +BROCKWELL B R AA1 K W EH2 L +BROD B R AA1 D +BRODA B R OW1 D AH0 +BRODBECK B R AA1 D B EH2 K +BRODE B R OW1 D +BRODEN B R OW1 D AH0 N +BRODER B R OW1 D ER0 +BRODER'S B R OW1 D ER0 Z +BRODERBUND B R OW1 T ER0 B AH0 N D +BRODERICK B R AA1 D ER0 IH0 K +BRODERICK(1) B R AA1 D R IH0 K +BRODERICK'S B R AA1 D ER0 IH0 K Z +BRODERICK'S(1) B R AA1 D R IH0 K Z +BRODERSEN B R AA1 D ER0 S AH0 N +BRODERSOHN B R OW1 T ER0 S AH0 N +BRODERSON B R AA1 D ER0 S AH0 N +BRODEUR B R AA1 D ER0 +BRODHEAD B R AA1 D HH EH2 D +BRODIE B R OW1 T IY0 +BRODIN B R OW1 D IH0 N +BRODKIN B R AA1 D K IH0 N +BRODMAN B R AA1 D M AH0 N +BRODNAX B R AA1 D N AE0 K S +BRODOWSKI B R AH0 D AO1 F S K IY0 +BRODRICK B R AA1 D R IH0 K +BRODRY B R AA1 D R IY0 +BRODSKY B R AA1 D S K IY0 +BRODT B R AA1 D T +BRODY B R OW1 D IY0 +BRODY'S B R OW1 D IY0 Z +BRODZINSKI B R AH0 JH IH1 N S K IY0 +BROE B R OW1 +BROECKER B R OW1 K ER0 +BROEKER B R OW1 K ER0 +BROER B R OW1 ER0 +BROERMAN B R OW1 ER0 M AH0 N +BROERS B R OW1 ER0 Z +BROGAN B R OW1 G AH0 N +BROGDEN B R AA1 G D AH0 N +BROGDON B R AA1 G D AH0 N +BROGNA B R OW1 G N AH0 +BROICH B R OY1 CH +BROIL B R OY1 L +BROILED B R OY1 L D +BROILER B R OY1 L ER0 +BROILERS B R OY1 L ER0 Z +BROILING B R OY1 L IH0 NG +BROIN B R OY1 N +BROK B R AA1 K +BROKAW B R OW1 K AO0 +BROKE B R OW1 K +BROKEN B R OW1 K AH0 N +BROKEN-TOOTH B R OW1 K AH0 N T UW2 TH +BROKEN-WIND B R OW1 K AH0 N W IH1 N D +BROKEN-WINDED B R OW1 K AH0 N W IH1 N D IH0 D +BROKER B R OW1 K ER0 +BROKER'S B R OW1 K ER0 Z +BROKERAGE B R OW1 K ER0 IH0 JH +BROKERAGE(1) B R OW1 K R IH0 JH +BROKERAGE'S B R OW1 K ER0 IH0 JH IH0 Z +BROKERAGE'S(1) B R OW1 K R IH0 JH IH0 Z +BROKERAGES B R OW1 K ER0 IH0 JH IH0 Z +BROKERAGES(1) B R OW1 K R IH0 JH IH0 Z +BROKERAGES' B R OW1 K ER0 IH0 JH IH0 Z +BROKERAGES'(1) B R OW1 K R IH0 JH IH0 Z +BROKERED B R OW1 K ER0 D +BROKERING B R OW1 K ER0 IH0 NG +BROKERS B R OW1 K ER0 Z +BROKERS' B R OW1 K ER0 Z +BROKING B R OW1 K IH0 NG +BROKINI B R AH0 K IY1 N IY0 +BROLIN B R OW1 L IH0 N +BROLLY B R AA1 L IY0 +BROM B R AA1 M +BROMAN B R OW1 M AH0 N +BROMBERG B R AA1 M B ER0 G +BROMFIELD B R AA1 M F IY2 L D +BROMFIELD'S B R AA1 M F IY2 L D Z +BROMIDE B R OW1 M AY2 D +BROMIDES B R OW1 M AY2 D Z +BROMINE B R OW1 M IY2 N +BROMLEY B R AA1 M L IY0 +BROMM B R AA1 M +BROMMER B R AA1 M ER0 +BROMONT B R OW1 M AA2 N T +BROMPHERIL B R AA1 M F EH0 R IH0 L +BROMWELL B R AA1 M W EH2 L +BROMWICH B R AA1 M W IH0 CH +BRONAUGH B R AA1 N AO0 +BRONC B R AA1 NG K +BRONCHIAL B R AA1 N CH IY0 AH0 L +BRONCHITIS B R AA0 NG K AY1 T AH0 S +BRONCHOSCOPE B R AA1 N K AH0 S K OW1 P +BRONCO B R AA1 NG K OW0 +BRONCOS B R AA1 NG K OW0 Z +BRONDER B R AA1 N D ER0 +BRONER B R OW1 N ER0 +BRONFMAN B R AA1 N F M AH0 N +BRONFMAN'S B R AA1 N F M AH0 N Z +BRONFMANS B R AA1 N F M AH0 N Z +BRONK B R AA1 NG K +BRONKEMA B R AH0 NG K IY1 M AH0 +BRONN B R AA1 N +BRONNER B R AA1 N ER0 +BRONS B R AA1 N Z +BRONSON B R AA1 N S AH0 N +BRONSTEIN B R AA1 N S T IY2 N +BRONSTEIN(1) B R AA1 N S T AY2 N +BRONSTON B R AA1 N S T AH0 N +BRONTE B R AA1 N T IY0 +BRONTE'S B R AA1 N T IY0 Z +BRONTOSAURUS B R AO2 N T AH0 S AO1 R AH0 S +BRONTOSAURUS(1) B R AO2 N AH0 S AO1 R AH0 S +BRONWEN B R AO1 N W IH0 N +BRONWYN B R AA1 N W IH0 N +BRONX B R AA1 NG K S +BRONY B R OW1 N IY2 +BRONZE B R AA1 N Z +BRONZED B R AA1 N Z D +BRONZEN B R AA1 N Z AH0 N +BRONZES B R AA1 N Z AH0 Z +BRONZES(1) B R AA1 N Z IH0 Z +BROOCH B R UW1 CH +BROOCH(1) B R OW1 CH +BROOD B R UW1 D +BROODED B R UW1 D IH0 D +BROODING B R UW1 D IH0 NG +BROODY B R UW1 D IY0 +BROOK B R UH1 K +BROOK'S B R UH1 K S +BROOKBANK B R UH1 K B AE2 NG K +BROOKE B R UH1 K +BROOKE'S B R UH1 K S +BROOKEHILL B R UH1 K HH IH2 L +BROOKEN B R UH1 K AH0 N +BROOKENS B R UH1 K AH0 N Z +BROOKER B R UH1 K ER0 +BROOKES B R UH1 K S +BROOKFIELD B R UH1 K F IY2 L D +BROOKHART B R UW1 K HH AA0 R T +BROOKHAVEN B R UH1 K HH EY2 V AH0 N +BROOKHURST B R UH1 K HH ER2 S T +BROOKING B R UH1 K IH0 NG +BROOKINGS B R UH1 K IH0 NG Z +BROOKINS B R UW1 K IH0 N Z +BROOKLINE B R UH1 K L AY2 N +BROOKLYN B R UH1 K L AH0 N +BROOKLYN(1) B R UH1 K L IH0 N +BROOKLYN'S B R UH1 K L AH0 N Z +BROOKLYN'S(1) B R UH1 K L IH0 N Z +BROOKMAN B R UH1 K M AH0 N +BROOKNER B R UH1 K N ER0 +BROOKNER'S B R UH1 K N ER0 Z +BROOKOVER B R UH1 K OW2 V ER0 +BROOKS B R UH1 K S +BROOKS' B R UH1 K S +BROOKS'S B R UH1 K S IH0 Z +BROOKS'S(1) B R UH1 K S +BROOKSHIER B R UW1 K SH IY0 ER0 +BROOKSHIRE B R UW1 K SH AY0 R +BROOKSIDE B R UH1 K S AY2 D +BROOKSTONE B R UH1 K S T OW2 N +BROOKSVILLE B R UH1 K S V IH0 L +BROOKSVILLE'S B R UH1 K S V IH0 L Z +BROOM B R UW1 M +BROOMALL B R UW1 M AH0 L +BROOME B R UW1 M +BROOMFIELD B R UW1 M F IY2 L D +BROOMS B R UW1 M Z +BROOMSTICK B R UW1 M S T IH2 K +BROOMSTICKS B R UW1 M S T IH2 K S +BROPHY B R OW1 F IY0 +BROSCH B R AO1 SH +BROSE B R OW1 Z +BROSH B R AA1 SH +BROSHEARS B R AA1 SH IH0 R Z +BROSIOUS B R OW1 Z IY0 AH0 S +BROSIUS B R OW1 S IY0 IH0 S +BROSKI B R AW1 S K IY0 +BROSKY B R AA1 S K IY0 +BROSNAHAN B R AA1 S N AH0 HH AE0 N +BROSNAN B R AA1 S N AH0 N +BROSS B R AO1 S +BROSSARD B R AH0 S AA1 R D +BROSSART B R AA1 S AA0 R T +BROSSEAU B R AH0 S OW1 +BROSSER B R AA1 S ER0 +BROSSETTE B R AH0 S EH1 T +BROSSMAN B R AO1 S M AH0 N +BROST B R AA1 S T +BROSTROM B R AA1 S T R AH0 M +BROSZ B R AA1 SH +BROTEN B R OW1 T AH0 N +BROTH B R AO1 TH +BROTHEL B R AA1 TH AH0 L +BROTHELS B R AA1 TH AH0 L Z +BROTHER B R AH1 DH ER0 +BROTHER'S B R AH1 DH ER0 Z +BROTHER-IN-LAW B R AH1 DH ER0 IH0 N L AO2 +BROTHERHOOD B R AH1 DH ER0 HH UH2 D +BROTHERLY B R AH1 DH ER0 L IY0 +BROTHERS B R AH1 DH ER0 Z +BROTHERS' B R AH1 DH ER0 Z +BROTHERS'S B R AH1 DH ER0 Z IH0 Z +BROTHERS-IN-LAW B R AH1 DH ER0 Z IH0 N L AO2 +BROTHERSON B R AH1 DH ER0 S AH0 N +BROTHERTON B R AH1 DH ER0 T AH0 N +BROTHS B R AO1 TH S +BROTMAN B R AA1 T M AH0 N +BROTT B R AA1 T +BROTZMAN B R AA1 T S M AH0 N +BROUCEK B R UW1 CH EH0 K +BROUDY B R AW1 D IY0 +BROUGH B R AW1 +BROUGHAM B R UW1 G AH0 M +BROUGHER B R AW1 ER0 +BROUGHMAN B R AW1 M AH0 N +BROUGHT B R 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B ER0 EH1 L Z +BURRER B ER1 ER0 +BURRES B ER1 Z +BURRESS B ER1 AH0 S +BURRI B UH1 R IY0 +BURRIDGE B AO1 R IH0 JH +BURRIER B ER1 IY0 ER0 +BURRIGHT B AO1 R AY0 T +BURRILL B AO1 R AH0 L +BURRINGTON B ER1 IH0 NG T AH0 N +BURRIS B ER1 IH0 S +BURRISS B ER1 IH0 S IH0 Z +BURRITO B ER0 IY1 T OW0 +BURRITOS B ER0 IY1 T OW0 S +BURRITT B ER1 IH0 T +BURRO B ER1 OW0 +BURROLA B UH0 R OW1 L AH0 +BURROS B ER1 OW0 Z +BURROUGH B ER1 OW0 +BURROUGHS B AH1 R OW0 Z +BURROUGHS(1) B ER1 OW0 Z +BURROUS B ER1 AH0 S +BURROW B ER1 OW0 +BURROWER B ER1 OW0 ER0 +BURROWERS B ER1 OW0 ER0 Z +BURROWES B ER1 OW2 Z +BURROWING B ER1 OW0 IH0 NG +BURROWS B ER1 OW0 Z +BURRUS B UH1 R AH0 S +BURRUSS B UH1 R AH0 S +BURRY B ER1 IY0 +BURSCH B ER1 SH +BURSE B ER1 S +BURSEY B ER1 S IY0 +BURSLEY B ER1 S L IY0 +BURSON B ER1 S AH0 N +BURST B ER1 S T +BURSTEIN B ER1 S T AY0 N +BURSTEIN(1) B ER1 S T IY0 N +BURSTING B ER1 S T IH0 NG +BURSTON B ER1 S T AH0 N +BURSTS B ER1 S T S +BURT B ER1 T +BURTCH B ER1 CH +BURTIS B ER1 T IH0 S +BURTNER B 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N Z +BYROM B AY1 R AH0 M +BYRON B AY1 R AH0 N +BYRON'S B AY1 R AH0 N Z +BYRUM B IH1 R AH0 M +BYSTANDER B AY1 S T AE2 N D ER0 +BYSTANDERS B AY1 S T AE2 N D ER0 Z +BYSTROM B IH1 S T R AH0 M +BYTE B AY1 T +BYTES B AY1 T S +BYU B IY1 W AY1 Y UW1 +BYUN B Y AH1 N +BYUS B AY1 AH0 S +BYWATER B AY1 W AO2 T ER0 +BYWAY B AY1 W EY2 +BYWAYS B AY1 W EY2 Z +BYWORD B AY1 W ER2 D +BYZANTINE B IH1 Z AH0 N T AY2 N +BYZANTINE(1) B IH1 Z AH0 N T IY2 N +BYZANTIUM B AH0 Z AE1 N T IY0 AH0 M +C S IY1 +C'EST S EH1 S T +C'EST(1) S EY1 +C'MON K AH0 M AA1 N +C'S S IY1 Z +C-CODE S IY1 K OW1 D +C-CODES S IY1 K OW1 D Z +C-SPAN S IY1 S P AE2 N +C-SPAN'S S IY1 S P AE2 N Z +C. S IY1 +C.'S S IY1 Z +C.D.S S IY1 D IY1 Z +C.O.D. S IY1 OW1 D IY1 +C.S S IY1 Z +C1 S IY1 W AH1 N +C2 S IY1 T UW1 +C3 S IY1 TH R IY1 +C4 S IY1 F AO1 R +C5 S IY1 F AY1 V +CA K AH1 +CA(1) S IY1 EY1 +CA(2) K AA1 +CAAN K AA1 N +CAB K AE1 B +CAB'S K AE1 B Z +CABA K AA1 B AH0 +CABAL K AH0 B AA1 L +CABALLERO K AE2 B AH0 Y EH1 R OW0 +CABAN K EY1 B AH0 N +CABANA K AH0 B AE1 N AH0 +CABANAS K AH0 B AE1 N AH0 Z +CABANISS K AE1 B AH0 N IH0 S +CABARET K AE2 B ER0 EY1 +CABARETS K AE2 B ER0 EY1 Z +CABBAGE K AE1 B AH0 JH +CABBAGE(1) K AE1 B IH0 JH +CABBAGES K AE1 B IH0 JH IH0 Z +CABBIE K AE1 B IY0 +CABBIES K AE1 B IY0 Z +CABBY K AE1 B IY0 +CABDRIVER K AE1 B D R AY2 V ER0 +CABDRIVERS K AE1 B D R AY2 V ER0 Z +CABE K EY1 B +CABELA K AA2 B EH1 L AH0 +CABELA'S K AA2 B EH1 L AH0 +CABELL K AA0 B EH1 L +CABELLO K AH0 B EH1 L OW0 +CABERNET K AE2 B ER0 N EY1 +CABERNETS K AE2 B ER0 N EH1 T S +CABERNETS(1) K AE2 B ER0 N EY1 Z +CABEY K EY1 B IY0 +CABEZAS K AH0 B EY1 Z AH0 Z +CABIN K AE1 B AH0 N +CABINDA K AH0 B IH1 N D AH0 +CABINESS K EY1 B IY0 N IH0 S +CABINET K AE1 B AH0 N AH0 T +CABINET(1) K AE1 B N AH0 T +CABINET'S K AE1 B N AH0 T S +CABINETRY K AE1 B N AH0 T R IY0 +CABINETS K AE1 B AH0 N AH0 T S +CABINETS(1) K AE1 B N AH0 T S +CABINS K AE1 B AH0 N Z +CABLE K EY1 B AH0 L +CABLE'S K EY1 B AH0 L Z +CABLEC K AE1 B L AH0 K +CABLEC(1) K EY1 B AH0 L S IY1 +CABLEC(2) K EY1 B L EH0 K +CABLECOMM K EY1 B AH0 L K AA2 M +CABLECOMMS K EY1 B AH0 L K AA2 M Z +CABLED K EY1 B AH0 L D +CABLEGRAM K EY1 B AH0 L G R AE2 M +CABLEONE K EY1 B AH0 L W AH2 N +CABLER K EY1 B AH0 L ER0 +CABLER(1) K EY1 B L ER0 +CABLES K EY1 B AH0 L Z +CABLESYSTEM K EY1 B AH0 L S IH2 S T AH0 M +CABLESYSTEMS K EY1 B AH0 L S IH2 S T AH0 M Z +CABLETRON K EY1 B AH0 L T R AO2 N +CABLETRON'S K EY1 B AH0 L T R AO2 N Z +CABLEVISION K EY1 B AH0 L V IH2 ZH AH0 N +CABLEVISION'S K EY1 B AH0 L V IH2 ZH AH0 N Z +CABO K AE0 B OW1 +CABO(1) S IY1 EY1 B IY1 OW1 +CABOK AE1 B OW0 +CABOODLE K AH0 B UW1 D AH0 L +CABOOSE K AH0 B UW1 S +CABOOSES K AH0 B UW1 S IH0 Z +CABOT K AE1 B AH0 T +CABOT'S K AE1 B AH0 T S +CABOTAGE K AE1 B AH0 T IH0 JH +CABRAL K AE1 B R AH0 L +CABRALES K AA0 B R AA1 L EH0 S +CABRALL K AH0 B R AA1 L +CABRALL'S K AH0 B R AA1 L Z +CABRANES K AH0 B R EY1 N Z +CABRERA K AA0 B R EH1 R AH0 +CABRINI K AH0 B R IY1 N IY0 +CABRINI'S K AH0 B R IY1 N IY0 Z +CABRIOLET K AE2 B R IY0 OW0 L EY1 +CABRIOLET(1) K AE2 B R IY0 OW0 L EH1 T +CABS K AE1 B Z +CAC K AE1 K +CAC(1) S IY1 EY1 S IY1 +CAC'S K AE1 K S +CACACE K AE1 K AH0 S +CACACI K AH0 K AA1 S IY0 +CACAO K AH0 K EY1 OW0 +CACCAMISE K AA0 K AA1 M IH0 S +CACCAMO K AA0 K AA1 M OW0 +CACCAVALE K AA0 K AH0 V AA1 L IY0 +CACCIA K AA1 CH AH0 +CACCIATORE K AA0 CH AH0 T AO1 R IY0 +CACCIOLA K AA0 K CH OW1 L AH0 +CACERES K AA0 S EH1 R EH0 S +CACHE K AE1 SH +CACHE(1) K AE0 SH EY1 +CACHED K AE1 SH T +CACHES K AE1 SH IH0 Z +CACHES(1) K AE0 SH EY1 Z +CACHET K AE1 SH EY0 +CACHING K AE1 SH IH0 NG +CACHO K AE1 CH OW0 +CACIOPPO K AA0 CH OW1 P OW0 +CACIQUE K AH0 S IY1 K +CACKLE K AE1 K AH0 L +CACKLING K AE1 K AH0 L IH0 NG +CACKLING(1) K AE1 K L IH0 NG +CACLD K AE1 K AH0 L D +CACLD(1) S IY1 EY1 S IY1 EH1 L D IY1 +CACOPHONY K AE0 K AA1 F AH0 N IY0 +CACTI K AE1 K T AY0 +CACTI(1) K AE1 K T IY0 +CACTUS K AE1 K T AH0 S +CAD K AE1 D +CADA K AA1 D AH0 +CADAM K AE1 D AH0 M +CADAVER K AH0 D AE1 V ER0 +CADAVERS K AH0 D AE1 V ER0 Z +CADBURY K AE1 D B EH2 R IY0 +CADBURY'S K AE1 D B EH2 R IY0 Z +CADBY K AE1 D B IY0 +CADDELL K AE1 D AH0 L +CADDEN K AE1 D AH0 N +CADDICK K AE1 D IH0 K +CADDIES K AE1 D IY0 Z +CADDOCK K AE1 D AH0 K +CADDY K AE1 D IY0 +CADDYSHACK K AE1 D IY0 SH AE2 K +CADE K EY1 D +CADELL K AA0 D EY1 L +CADENA K AH0 D IY1 N AH0 +CADENCE K EY1 D AH0 N S +CADENCES K EY1 D AH0 N S IH0 Z +CADENHEAD K EY1 D AH0 N HH EH2 D +CADET K AH0 D EH1 T +CADETS K AH0 D EH1 T S +CADGE K AE1 JH +CADIDDLEHOPPER K AH0 D IH1 D AH0 L HH AO2 P ER0 +CADIEUX K AE1 D IY0 OW0 +CADILLAC K AE1 D AH0 L AE2 K +CADILLAC'S K AE1 D AH0 L AE2 K S +CADILLACS K AE1 D AH0 L AE2 K S +CADIZ K AH0 D IY1 Z +CADLE K EY1 D AH0 L +CADMAN K AE1 D M AH0 N +CADMIUM K AE1 D M IY0 AH0 M +CADMUS K AE1 D M AH0 S +CADNETIX K AE2 D N EH1 T IH0 K S +CADOGAN K AA0 D OW0 G AA1 N +CADORETTE K AE1 D ER0 EH0 T +CADOTTE K AH0 D AO1 T +CADRE K AE1 D R IY0 +CADRES K AE1 D R IY0 Z +CADRONE K AH0 D R OW1 N +CADRONE(1) K AH0 D R OW1 N IY0 +CADS K AE1 D S +CADWALADER K AE2 D W AO1 L AH0 D ER0 +CADWALADER'S K AE2 D W AO1 L AH0 D ER0 Z +CADWALLADER K AE2 D W AO1 L AH0 D ER0 +CADWELL K AE1 D W EH2 L +CADY K EY1 D IY0 +CAEN K AE1 N +CAEN(1) K AA1 N +CAEN'S K AE1 N Z +CAEN'S(1) K AA1 N Z +CAESAR S IY1 Z ER0 +CAESAR'S S IY1 Z ER0 Z +CAESAREA K EY2 S ER0 IY1 AH0 +CAESAREAN K EY1 S ER0 IY2 N +CAESAREANS K EY1 S ER0 IY2 N Z +CAESARS S IY1 Z ER0 Z +CAESARS' S IY1 Z ER0 Z +CAETANO K AH0 T AA1 N OW0 +CAFARELLA K AA0 F AA0 R EH1 L AH0 +CAFARELLI K AA0 F AA0 R EH1 L IY0 +CAFARO K AA0 F AA1 R OW0 +CAFE K AH0 F EY1 +CAFE(1) K AE0 F EY1 +CAFES K AE2 F EY1 Z +CAFETERIA K AE2 F AH0 T IH1 R IY0 AH0 +CAFETERIAS K AE2 F AH0 T IH1 R IY0 AH0 Z +CAFETIZER K AE1 F IH0 T AY2 Z ER0 +CAFFEE K AE1 F IY0 +CAFFEINATE K AE1 F IH0 N EY2 T +CAFFEINATED K AE1 F IH0 N EY2 T AH0 D +CAFFEINE K AE0 F IY1 N +CAFFERTY K AE1 F ER0 T IY0 +CAFFERY K AE1 F ER0 IY0 +CAFFEY K AE1 F IY0 +CAFFREY K AE1 F R IY0 +CAFIERO K AE2 F IY0 EH1 R OW0 +CAFTAN K AE1 F T AE2 N +CAFTANS K AE1 F T AE2 N Z +CAGAN K EY1 G AH0 N +CAGE K EY1 JH +CAGE'S K EY1 JH IH0 Z +CAGED K EY1 JH D +CAGES K EY1 JH IH0 Z +CAGEY K EY1 JH IY0 +CAGGIANO K AA0 JH IY0 AA1 N OW0 +CAGLE K EY1 G AH0 L +CAGLEY K AE1 G L IY0 +CAGLIARI K AE2 G L IY0 AA1 R IY0 +CAGNEY K AE1 G N IY0 +CAGUAS K AA1 G W AA2 S +CAHALAN K AE1 HH AH0 L AH0 N +CAHALL K AE1 HH AH0 L +CAHAN K AE1 HH AH0 N +CAHASA K AH0 HH AA1 S AH0 +CAHILL K EY1 HH IH2 L +CAHN K AE1 N +CAHNERS K AA1 N ER0 Z +CAHOON K AH0 HH UW1 N +CAHOOT K AH0 HH UW1 T +CAHOOTS K AH0 HH UW1 T S +CAHORA K AH0 HH AO1 R AH0 +CAHOUET K AH0 HH UW1 T +CAI K AY1 +CAIAZZO K AA0 Y AA1 Z OW0 +CAICEDO K AH0 CH EY1 D OW0 +CAIL K EY1 L +CAILLEBOTTE K AY0 B AO1 T +CAILLIER K EY1 L IY0 ER0 +CAILLOUET K EY2 L UW1 T +CAIN K EY1 N +CAIN'S K EY1 N Z +CAINE K EY1 N +CAINES K EY1 N Z +CAIOLA K AY1 OW0 L AH0 +CAIRE K EH1 R +CAIRN K EH1 R N +CAIRNES K EH1 R N Z +CAIRNS K EH1 R N Z +CAIRO K AY1 R OW0 +CAIRO'S K AY1 R OW0 Z +CAISON K EY1 Z AH0 N +CAISSE K EY1 S +CAISSIE K EY1 S IY0 +CAISSON K EY1 S AH0 N +CAISSON(1) K EH1 S AH0 N +CAISSONS K EY1 S AH0 N Z +CAISSONS(1) K EH1 S AH0 N Z +CAITLIN K EY1 T L IH0 N +CAITO K EY1 T OW0 +CAJOLE K AH0 JH OW1 L +CAJOLED K AH0 JH OW1 L D +CAJOLING K AH0 JH OW1 L IH0 NG +CAJUN K EY1 JH AH0 N +CAJUNS K EY1 JH AH0 N Z +CAKE K EY1 K +CAKE'S K EY1 K S +CAKED K EY1 K T +CAKES K EY1 K S +CAL K AE1 L +CALA K AA1 L AH0 +CALABASAS K AE2 L AH0 B AA1 S AH0 S +CALABRESE K AA0 L AA0 B R EY1 Z IY0 +CALABRIA K AH0 L AE1 B R IY0 AH0 +CALABRO K AH0 L AE1 B R OW0 +CALADIUMS K AH0 L EY1 D IY0 AH0 M Z +CALAF K AE1 L AH0 F +CALAHAN K AE1 L AH0 HH AE0 N +CALAIS K AH0 L EY1 +CALAMANDER K AE1 L AH0 M AE2 N D ER0 +CALAMARI K AA0 L AA0 M AA1 R IY0 +CALAME K AA0 L AA1 M IY0 +CALAMIA K AH0 L EY1 M IY0 AH0 +CALAMINE K AE1 L AH0 M AY2 N +CALAMINE'S K AE1 L AH0 M AY2 N Z +CALAMITIES K AH0 L AE1 M AH0 T IY0 Z +CALAMITOUS K AH0 L AE1 M AH0 T AH0 S +CALAMITY K AH0 L AE1 M AH0 T IY0 +CALAMITY(1) K AH0 L AE1 M IH0 T IY0 +CALAN K EY1 L AH0 N +CALANDRA K AH0 L AE1 N D R AH0 +CALANDRO K AH0 L AE1 N D R OW0 +CALANTHA K AH0 L AE1 N TH AH0 +CALARCO K AH0 L AA1 R K OW0 +CALAVERAS K AE0 L AH0 V EH1 R AH0 Z +CALAWAY K AA1 L AH0 W EY0 +CALBERT K AE1 L B ER0 T +CALBOS K AA1 L B OW0 S +CALCAGNI K AA0 L K AA1 G N IY0 +CALCAGNO K AA0 L K AA1 G N OW0 +CALCATERRA K AE2 L K AH0 T EH1 R AH0 +CALCIFIED K AE1 L S AH0 F AY2 D +CALCIFY K AE1 L S AH0 F AY2 +CALCITE K AE1 L S AY2 T +CALCIUM K AE1 L S IY0 AH0 M +CALCOMP K AO1 L K AA2 M P +CALCOTE K AA0 L K OW1 T IY0 +CALCULATE K AE1 L K Y AH0 L EY2 T +CALCULATED K AE1 L K Y AH0 L EY2 T AH0 D +CALCULATED(1) K AE1 L K Y AH0 L EY2 T IH0 D +CALCULATES K AE1 L K Y AH0 L EY2 T S +CALCULATING K AE1 L K Y AH0 L EY2 T IH0 NG +CALCULATION K AE2 L K Y AH0 L EY1 SH AH0 N 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AH0 L AH0 +CALER K EY1 L ER0 +CALERO K AH0 L EH1 R OW0 +CALES K EY1 L Z +CALEY K EY1 L IY0 +CALF K AE1 F +CALF'S K AE1 F S +CALFED K AE1 F T +CALFED(1) K AE1 L F EH2 D +CALFED'S K AE1 L F EH2 D Z +CALFEE K AE1 L F IY0 +CALGARY K AE1 L G ER0 IY0 +CALGENE K AE1 L JH IY2 N +CALGENE'S K AE1 L JH IY2 N Z +CALGON K AE1 L G AO0 N +CALGROUP K AE1 L G R UW2 P +CALHOON K AE0 L HH UW1 N +CALHOUN K AE0 L HH UW1 N +CALI K AA1 L IY0 +CALI(1) K AE1 L IY0 +CALIA K AA1 L IY0 AH0 +CALIBER K AE1 L AH0 B ER0 +CALIBRATE K AE1 L AH0 B R EY2 T +CALIBRATED K AE1 L AH0 B R EY2 T AH0 D +CALIBRATION K AE2 L AH0 B R EY1 SH AH0 N +CALICO K AE1 L AH0 K OW2 +CALIDA K AA0 L IY1 D AH0 +CALIENDO K AA0 L IY0 EH1 N D OW0 +CALIF K AE1 L IH0 F +CALIFANO K AA0 L IY0 F AA1 N OW0 +CALIFF K AE1 L IH0 F +CALIFORNIA K AE2 L AH0 F AO1 R N Y AH0 +CALIFORNIA'S K AE2 L IH0 F AO1 R N Y AH0 Z +CALIFORNIAN K AE2 L IH0 F AO1 R N Y AH0 N +CALIFORNIAN'S K AE2 L IH0 F AO1 R N Y AH0 N Z +CALIFORNIANS K AE2 L IH0 F AO1 R N Y AH0 N Z +CALIGIURI K AE2 L AH0 JH IH1 R IY0 +CALILL K AH0 L IH1 L +CALILLS K AH0 L IH1 L Z +CALIPER K AE1 L AH0 P ER0 +CALIPERS K AE1 L AH0 P ER0 Z +CALIPH K AE1 L AH0 F +CALIRI K AA0 L IH1 R IY0 +CALISE K AA1 L AY0 Z +CALISTA K AH0 L IH1 S T AH0 +CALISTHENIC K AE2 L AH0 S TH EH1 N IH0 K +CALISTHENICS K AE2 L AH0 S TH EH1 N IH0 K S +CALITE K AE1 L AY2 T +CALITE(1) K EY1 L AY2 T +CALIX K AE1 L IH0 K S +CALIX(1) K EY1 L AH0 K S +CALK K AO1 K +CALKIN K AE1 L K IH0 N +CALKINS K AE1 L K IH0 N Z +CALL K AO1 L +CALL'S K AO1 L Z +CALL'S(1) K AA1 L Z +CALLA K AE1 L AH0 +CALLABLE K AO1 L AH0 B AH0 L +CALLACE K AE1 L AH0 S +CALLAGHAN K AE1 L AH0 HH AE0 N +CALLAHAM K AE1 L AH0 HH AE2 M +CALLAHAN K AE1 L AH0 HH AE2 N +CALLAHAN'S K AE1 L AH0 HH AE2 N Z +CALLAIS K AH0 L EY1 +CALLAN K AE1 L AH0 N +CALLANAN K AE1 L AH0 N AH0 N +CALLAND K AE1 L AH0 N D +CALLANDER K AE1 L AH0 N D ER0 +CALLARI K AA0 L AA1 R IY0 +CALLAS K AE1 L AH0 Z +CALLAWAY K AE1 L AH0 W EY0 +CALLAWAY'S K AO1 L AH0 W EY2 Z +CALLE K EY1 L 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IY0 T R AH2 S T +CITYWIDE S IH1 T IY0 W AY2 D +CIUCCI CH UW1 CH IY0 +CIUDAD S IY2 UW0 D AE1 D +CIULLA CH UW1 L AH0 +CIULLO CH UW1 L OW0 +CIVET S IH1 V AH0 T +CIVIC S IH1 V IH0 K +CIVICS S IH1 V IH0 K S +CIVIL S IH1 V AH0 L +CIVILETTI S IY2 V IH0 L EH1 T IY0 +CIVILIAN S AH0 V IH1 L Y AH0 N +CIVILIANS S AH0 V IH1 L Y AH0 N Z +CIVILITY S AH0 V IH1 L AH0 T IY0 +CIVILIZATION S IH2 V AH0 L IH0 Z EY1 SH AH0 N +CIVILIZATIONS S IH2 V AH0 L IH0 Z EY1 SH AH0 N Z +CIVILIZE S IH1 V AH0 L AY2 Z +CIVILIZED S IH1 V AH0 L AY2 Z D +CIVILLY S IH1 V IH0 L IY0 +CIVITELLO CH IY0 V IY0 T EH1 L OW0 +CIZEK CH IH1 Z EH0 K +CIZIK S IY1 Z IH0 K +CIZNEROS S IH2 Z N EH1 R OW0 S +CLAAR K L AA1 R +CLAASSEN K L AA1 S AH0 N +CLABAUGH K L AE1 B AO0 +CLABIR K L AE1 B IH0 R +CLABO K L AA1 B OW0 +CLABORN K L AE1 B ER0 N +CLABOUGH K L AE1 B AW0 +CLACK K L AE1 K +CLACKAMAS K L AE1 K AH0 M AH0 S +CLAD K L AE1 D +CLADDAGH K L AE1 D AH2 +CLADIFICATION K L AE2 D AH0 F AH0 K EY1 SH AH0 N +CLAES K L EY1 Z +CLAEYS K L EY1 Z +CLAFFEY K L AE1 F IY0 +CLAFLIN K L AE1 F L IH0 N +CLAGETT K L AE1 JH IH0 T +CLAGG K L AE1 G +CLAGGETT K L AE1 G IH0 T +CLAGUE K L AA1 G +CLAIBORN K L EY1 B ER0 N +CLAIBORNE K L EY1 B ER0 N +CLAIBORNE'S K L EY1 B AO0 R N Z +CLAIBORNE'S(1) K L EY1 B ER0 N Z +CLAIM K L EY1 M +CLAIMANT K L EY1 M AH0 N T +CLAIMANTS K L EY1 M AH0 N T S +CLAIMANTS' K L EY1 M AH0 N T S +CLAIMED K L EY1 M D +CLAIMING K L EY1 M IH0 NG +CLAIMS K L EY1 M Z +CLAIR K L EH1 R +CLAIRE K L EH1 R +CLAIRE'S K L EH1 R Z +CLAIRMONT K L EH1 R M AH0 N T +CLAIROL K L EH1 R AA0 L +CLAIRSON K L EH1 R S AH0 N +CLAIRVOYANCE K L EH0 R V OY1 AH0 N S +CLAIRVOYANT K L EH0 R V OY1 AH0 N T +CLAM K L AE1 M +CLAMBER K L AE1 M B ER0 +CLAMBERED K L AE1 M B ER0 D +CLAMEN K L EY1 M AH0 N +CLAMMED K L AE1 M D +CLAMMY K L AE1 M IY0 +CLAMOR K L AE1 M ER0 +CLAMORED K L AE1 M ER0 D +CLAMORING K L AE1 M ER0 IH0 NG +CLAMOUR K L AE1 M ER0 +CLAMP K L AE1 M P +CLAMPDOWN K L AE1 M P D AW2 N +CLAMPED K L AE1 M P T +CLAMPETT K L AE1 M P EH0 T +CLAMPING K L AE1 M P IH0 NG +CLAMPITT K L AH0 M P IH1 T +CLAMPS K L AE1 M P S +CLAMS K L AE1 M Z +CLAMSHELL K L AE1 M SH EH2 L +CLAN K L AE1 N +CLANCEY K L AE1 N S IY0 +CLANCY K L AE1 N S IY0 +CLANCY'S K L AE1 N S IY0 Z +CLANDESTINE K L AE0 N D EH1 S T IH0 N +CLANDESTINELY K L AE0 N D EH1 S T AH0 N L IY0 +CLANG K L AE1 NG +CLANGING K L AE1 NG IH0 NG +CLANIN K L AE1 N IH0 N +CLANK K L AE1 NG K +CLANKING K L AE1 NG K IH0 NG +CLANNISH K L AE1 N IH0 SH +CLANS K L AE1 N Z +CLANTON K L AE1 N T AH0 N +CLAP K L AE1 P +CLAPBOARD K L AE1 P B AO2 R D +CLAPBOARDS K L AE1 P B AO2 R D Z +CLAPHAM K L AE1 F AH0 M +CLAPMAN K L AE1 P M AH0 N +CLAPP K L AE1 P +CLAPPED K L AE1 P T +CLAPPER K L AE1 P ER0 +CLAPPING K L AE1 P IH0 NG +CLAPS K L AE1 P S +CLAPSADDLE K L AE1 P S AE2 D AH0 L +CLAPTON K L AE1 P T AH0 N +CLAPTON'S K L AE1 P T AH0 N Z +CLAR K L AA1 R +CLARA K L AE1 R AH0 +CLARA(1) K L EH1 R AH0 +CLARA'S K L AE1 R AH0 Z +CLARA'S(1) K L EH1 R AH0 Z +CLARABELLE K L AE1 R AH0 B AH0 L +CLARABELLE(1) K L AE1 R AH0 B EH2 L +CLARAMAE K L AA0 R AA1 M AY0 +CLARAN K L EH1 R AH0 N +CLARCOR K L AA1 R K AO2 R +CLARDY K L AA1 R D IY0 +CLARE K L EH1 R +CLAREMONT K L EH1 R M AA2 N T +CLAREN K L AE1 R AH0 N +CLARENCE K L EH1 R AH0 N S +CLARENDON K L EH1 R AH0 N D AH0 N +CLARESTA K L AA0 R EH1 S T AH0 +CLARETTE K L ER0 EH1 T +CLAREY K L AE1 R IY0 +CLARIBEL K L EH1 R AH0 B EH2 L +CLARICE K L ER0 IY1 S +CLARIDA K L AA0 R IY1 D AH0 +CLARIDGE K L EH1 R IH0 JH +CLARIDGES K L EH1 R IH0 JH IH0 Z +CLARIDON K L EH1 R AH0 D AA0 N +CLARIFICATION K L EH2 R AH0 F AH0 K EY1 SH AH0 N +CLARIFICATIONS K L EH2 R IH0 F IH0 K EY1 SH AH0 N Z +CLARIFIED K L EH1 R AH0 F AY2 D +CLARIFIES K L EH1 R AH0 F AY2 Z +CLARIFY K L EH1 R AH0 F AY2 +CLARIFYING K L EH1 R AH0 F AY2 IH0 NG +CLARIMOND K L AE1 R IH0 M AH0 N D +CLARINDA K L ER0 IH1 N D AH0 +CLARINE K L EH1 R IY0 N +CLARINET K L EH2 R AH0 N EH1 T +CLARINETIST K L EH2 R AH0 N EH1 T IH0 S T +CLARINETISTS K L EH2 R AH0 N EH1 T IH0 S T S +CLARINS K L EH1 R IH0 N Z +CLARION K L EH1 R IY0 AH0 N +CLARIS K L EH1 R IH0 S +CLARISSA K L ER0 IH1 S AH0 +CLARISSE K L AE1 R IH0 S +CLARISSE(1) K L AH0 R IY1 S +CLARITA K L AA0 R IY1 T AH0 +CLARITIN K L EH1 R IH0 T IH0 N +CLARITY K L EH1 R AH0 T IY0 +CLARITY(1) K L EH1 R IH0 T IY0 +CLARK K L AA1 R K +CLARK'S K L AA1 R K S +CLARKE K L AA1 R K +CLARKE'S K L AA1 R K S +CLARKEN K L AA1 R K EH0 N +CLARKIN K L AA1 R K IH0 N +CLARKS K L AA1 R K S +CLARKSBURG K L AA1 R K S B ER0 G +CLARKSON K L AA1 R K S AH0 N +CLARKSTON K L AA1 R K S T AH0 N +CLARKSVILLE K L AA1 R K S V IH2 L +CLARO K L AA1 R OW0 +CLAROSTAT K L EH1 R AH0 S T AE2 T +CLARRIDGE K L AE1 R IH0 JH +CLARRISSE K L AE1 R IH0 S +CLARY K L EH1 R IY0 +CLASBY K L AE1 S B IY0 +CLASEN K L EY1 S AH0 N +CLASH K L AE1 SH +CLASHED K L AE1 SH T +CLASHES K L AE1 SH IH0 Z +CLASHING K L AE1 SH IH0 NG +CLASON K L AE1 S AH0 N +CLASP K L AE1 S P +CLASPED K L AE1 S P T +CLASS K L AE1 S +CLASS'S K L AE1 S IH0 Z +CLASSACTION K L AE1 S AE1 K SH AH0 N +CLASSACTIONS K L AE1 S AE1 K SH AH0 N Z +CLASSED K L AE1 S T +CLASSEN K L AE1 S AH0 N +CLASSES K L AE1 S AH0 Z +CLASSES(1) K L AE1 S IH0 Z +CLASSIC K L AE1 S IH0 K +CLASSICAL K L AE1 S IH0 K AH0 L +CLASSICALLY K L AE1 S IH0 K L IY0 +CLASSICISM K L AE1 S IH0 S IH2 Z AH0 M +CLASSICIST K L AE1 S AH0 S AH0 S T +CLASSICS K L AE1 S IH0 K S +CLASSIER K L AE1 S IY0 ER0 +CLASSIFIABLE K L AE1 S AH0 F AY2 AH0 B AH0 L +CLASSIFICATION K L AE2 S AH0 F AH0 K EY1 SH AH0 N +CLASSIFICATIONS K L AE2 S AH0 F AH0 K EY1 SH AH0 N Z +CLASSIFIED K L AE1 S AH0 F AY2 D +CLASSIFIEDS K L AE1 S AH0 F AY2 D Z +CLASSIFIES K L AE1 S AH0 F AY2 Z +CLASSIFY K L AE1 S AH0 F AY2 +CLASSIFYING K L AE1 S AH0 F AY2 IH0 NG +CLASSING K L AE1 S IH0 NG +CLASSLESS K L AE1 S L AH0 S +CLASSMAN K L AE1 S M AH0 N +CLASSMATE K L AE1 S M EY2 T +CLASSMATES K L AE1 S M EY2 T S +CLASSMEN K L AE1 S M EH0 N +CLASSON K L AE1 S AH0 N +CLASSROOM K L AE1 S R UW2 M +CLASSROOMS K L AE1 S R UW2 M Z +CLASSY K L AE1 S IY0 +CLATTER K L AE1 T ER0 +CLATTERING K L AE1 T ER0 IH0 NG +CLAUD K L AO1 D +CLAUDE K L AO1 D +CLAUDET K L AO0 D EH1 T +CLAUDETTE K L OW0 D EH1 T +CLAUDIA K L AO1 D IY0 AH0 +CLAUDIAN K L AO1 D IY0 AH0 N +CLAUDIE K L AO1 D IY0 +CLAUDINA K L AO1 D IH0 N AH0 +CLAUDINA(1) K L AO0 D IY1 N AH0 +CLAUDINE K L AO0 D IY1 N +CLAUDIO K L AO1 D IY0 OW2 +CLAUDIUS K L AO1 D IY0 AH0 S +CLAUDSON K L AO1 D S AH0 N +CLAUNCH K L AO1 N CH +CLAUS K L AO1 Z +CLAUS' K L AO1 Z +CLAUSE K L AO1 Z +CLAUSELL K L AO1 Z AH0 L +CLAUSEN K L AW1 S AH0 N +CLAUSER K L AO1 Z ER0 +CLAUSES K L AO1 Z AH0 Z +CLAUSES(1) K L AO1 Z IH0 Z +CLAUSING K L AO1 Z IH0 NG +CLAUSON K L AO1 Z AH0 N +CLAUSS K L AO1 S +CLAUSSEN K L AO1 Z S AH0 N +CLAUSTROPHOBIA K L AO2 S T R AH0 F OW1 B IY0 AH0 +CLAUSTROPHOBIC K L AO2 S T R AH0 F OW1 B IH0 K +CLAVETTE K L AH0 V EH1 T +CLAVICHORD K L AE1 V AH0 K AO2 R D +CLAVICLE K L AE1 V AH0 K AH0 L +CLAVICLE(1) K L AE1 V IH0 K AH0 L +CLAVIN K L AE1 V IH0 N +CLAW K L AO1 +CLAWED K L AO1 D +CLAWING K L AO1 IH0 NG +CLAWS K L AO1 Z +CLAWSON K L AO1 S AH0 N +CLAXON K L AE1 K S AH0 N +CLAXTON K L AE1 K S T AH0 N +CLAY K L EY1 +CLAYBAUGH K L EY1 B AO2 +CLAYBORN K L EY1 B ER0 N +CLAYBORNE K L EY1 B ER0 N +CLAYBOURNE K L EY1 B ER0 N +CLAYBROOK K L EY1 B R UH2 K +CLAYBROOKS K L EY1 B R UH2 K S +CLAYBURN K L EY1 B ER2 N +CLAYCOMB K L EY1 K AH0 M +CLAYEY K L EY1 IY0 +CLAYMAN K L EY1 M AH0 N +CLAYMATION K L EY1 M EY2 SH AH0 N +CLAYMONT K L EY1 M AA2 N T +CLAYMORE K L EY1 M AO2 R +CLAYPOOL K L EY1 P UW2 L +CLAYPOOLE K L EY1 P UW2 L +CLAYS K L EY1 Z +CLAYSON K L EY1 Z AH0 N +CLAYTON K L EY1 T AH0 N +CLAYTON'S K L EY1 T AH0 N Z +CLAYTOR K L EY1 T ER0 +CLAYWELL K L EY1 W EH2 L +CLEAH K IY1 AH0 +CLEAN K L IY1 N +CLEANED K L IY1 N D +CLEANER K L IY1 N ER0 +CLEANERS K L IY1 N ER0 Z +CLEANEST K L IY1 N AH0 S T +CLEANING K L IY1 N IH0 NG +CLEANLINESS K L EH1 N L IY0 N IH0 S +CLEANLY K L IY1 N L IY0 +CLEANNESS K L IY1 N IH0 S +CLEANS K L IY1 N Z +CLEANSE K L EH1 N Z +CLEANSED K L EH1 N Z D +CLEANSER K L EH1 N Z ER0 +CLEANSERS K L EH1 N Z ER0 Z +CLEANSING K L EH1 N Z IH0 NG +CLEANTHA K L IY1 N TH AH0 +CLEANUP K L IY1 N AH2 P +CLEANUPS K L IY1 N AH2 P S +CLEAR K L IH1 R +CLEAR-CUT K L IH1 R K AH2 T +CLEARANCE K L IH1 R AH0 N S +CLEARANCES K L IH1 R AH0 N S IH0 Z +CLEARCUT K L IH1 R K AH2 T +CLEARCUTS K L IH1 R K AH2 T S +CLEARCUTTING K L IH1 R K AH2 T IH0 NG +CLEARED K L IH1 R D +CLEARER K L IH1 R ER0 +CLEAREST K L IH1 R IH0 S T +CLEARING K L IH1 R IH0 NG +CLEARINGHOUSE K L IH1 R IH0 NG HH AW2 S +CLEARINGHOUSES K L IY1 R IH0 NG HH AW2 S IH0 Z +CLEARLY K L IH1 R L IY0 +CLEARMAN K L IH1 R M AH0 N +CLEARNESS K L IH1 R N AH0 S +CLEARS K L IH1 R Z +CLEARWATER K L IH1 R W AO2 T ER0 +CLEARY K L IH1 R IY0 +CLEAT K L IY1 T +CLEATS K L IY1 T S +CLEAVAGE K L IY1 V AH0 JH +CLEAVAGE(1) K L IY1 V IH0 JH +CLEAVE K L IY1 V +CLEAVELAND K L IY1 V L AH0 N D +CLEAVENGER K L IY1 V IH0 N JH ER0 +CLEAVER K L IY1 V ER0 +CLEAVES K L IY1 V Z +CLECKLER K L EH1 K L ER0 +CLECKLEY K L EH1 K L IY0 +CLECKNER K L EH1 K N ER0 +CLEEK K L IY1 K +CLEERE K L IH1 R +CLEESE K L IY1 S +CLEETON K L IY1 T AH0 N +CLEF K L EH1 F +CLEFT K L EH1 F T +CLEGG K L EH1 G +CLEGHORN K L EH1 G HH ER0 N +CLELAND K L EH1 L AH0 N D +CLELL K L EH1 L +CLELLAND K L EH1 L AH0 N D +CLEM K L EH1 M +CLEMANS K L EH1 M AH0 N Z +CLEMATIS K L EH1 M AH0 T IH0 S +CLEMATIS(1) K L AH0 M AE1 T IH0 S +CLEMEN K L EH1 M AH0 N +CLEMENCE K L EH1 M AH0 N S +CLEMENCY K L EH1 M AH0 N S IY0 +CLEMENS K L EH1 M AH0 N Z +CLEMENSEN K L EH1 M AH0 N S AH0 N +CLEMENSON K L EH1 M IH0 N S AH0 N +CLEMENT K L EH1 M AH0 N T +CLEMENTE K L AH0 M EH1 N T EY0 +CLEMENTE(1) K L AH0 M EH1 N T IY0 +CLEMENTE'S K L AH0 M EH1 N T EY0 Z +CLEMENTE'S(1) K L AH0 M EH1 N T IY0 Z +CLEMENTES K L AH0 M EH1 N T EY0 Z +CLEMENTES(1) K L AH0 M EH1 N T IY0 Z +CLEMENTI K L EY0 M EY1 N T IY0 +CLEMENTIA K L EY0 M EY1 N SH AH0 +CLEMENTINE K L EH1 M AH0 N T AY2 N +CLEMENTINE(1) K L EH1 M AH0 N T IY2 N +CLEMENTS K L EH1 M AH0 N T S +CLEMENTSON K L EH1 M IH0 N T S AH0 N +CLEMENTZ K L EH1 M IH0 N T S +CLEMMER K L EH1 M ER0 +CLEMMIE K L EH1 M IY0 +CLEMMONS K L EH1 M AH0 N Z +CLEMMY K L EH1 M IY0 +CLEMO K L EY1 M OW0 +CLEMONS K L EH1 M AH0 N Z +CLEMSON K L EH1 M S AH0 N +CLENCH K L EH1 N CH +CLENCHED K L EH1 N CH T +CLENCHER K L EH1 N CH ER0 +CLENCHES K L EH1 N CH AH0 Z +CLENDANIEL K L EH1 N D AH0 N IY2 L +CLENDENEN K L EH1 N D AH0 N AH0 N +CLENDENIN K L EH1 N D IH0 N IH0 N +CLENDENING K L EH1 N D AH0 N IH0 NG +CLENDENNING K L EH2 N D EH1 N IH0 NG +CLENNEY K L EH1 N IY0 +CLENWAR K L EH1 N W ER0 +CLEO K L IY1 OW0 +CLEOPATRA K L IY2 AH0 P AE1 T R AH0 +CLEOPATRA'S K L IY2 AH0 P AE1 T R AH0 Z +CLEPHANE K L EH1 F EY2 N +CLEPPER K L EH1 P ER0 +CLERC K L ER1 K +CLERCQ K L ER1 K +CLERGY K L ER1 JH IY0 +CLERGYMAN K L ER1 JH IY0 M AH0 N +CLERGYMAN(1) K L ER1 JH IY0 M AE2 N +CLERGYMEN K L ER1 JH IY0 M IH0 N +CLERGYMEN(1) K L ER1 JH IY0 M EH2 N +CLERIC K L EH1 R IH0 K +CLERICAL K L EH1 R AH0 K AH0 L +CLERICAL(1) K L EH1 R IH0 K AH0 L +CLERICS K L EH1 R IH0 K S +CLERISSA K L EH2 R IY1 S AH0 +CLERK K L ER1 K +CLERK'S K L ER1 K S +CLERKIN K L ER1 K IH0 N +CLERKS K L ER1 K S +CLERKS' K L ER1 K S +CLERMONT K L EH1 R M AA2 N T +CLEVA K L IY1 V AH0 +CLEVE K L IY1 V +CLEVELAND K L IY1 V L AH0 N D +CLEVELAND'S K L IY1 V L AH0 N D Z +CLEVELANDER K L IY1 V L AH0 N D ER0 +CLEVELANDERS K L IY1 V L AH0 N D ER0 Z +CLEVEN K L IY1 V AH0 N +CLEVENGER K L EH1 V IH0 N JH ER0 +CLEVER K L EH1 V ER0 +CLEVERER K L EH1 V AH0 R ER2 +CLEVERLY K L EH1 V ER0 L IY0 +CLEVERNESS K L EH1 V ER0 N AH0 S +CLEVETRUST K L IY1 V T R AH1 S T +CLEVIE K L IY1 V IY0 +CLEVINGER K L EH1 V IH0 NG ER0 +CLEVITE K L EH0 V AY1 T +CLEVITE'S K L EH0 V AY1 T S +CLEWELL K L EH1 W EH0 L +CLEWIS K L UW1 IH0 S +CLEWISTON K L UW1 AH0 S T AH0 N +CLEWS K L UW1 Z +CLIANTHA K L IY0 AE1 N TH AH0 +CLIBURN K L AY1 B ER0 N +CLICHE K L IY0 SH EY1 +CLICHED K L IY2 SH EY1 D +CLICHES K L IY0 SH EY1 Z +CLICK K L IH1 K +CLICKBAIT K L IH1 K B EY2 T +CLICKED K L IH1 K T +CLICKER K L IH1 K ER0 +CLICKING K L IH1 K IH0 NG +CLICKNER K L IH1 K N ER0 +CLICKS K L IH1 K S +CLIENT K L AY1 AH0 N T +CLIENT'S K L AY1 AH0 N T S +CLIENTELE K L AY2 AH0 N T EH1 L +CLIENTS K L AY1 AH0 N T S +CLIENTS' K L AY1 AH0 N T S +CLIETT K L IY1 T +CLIF K L IH1 F +CLIFF K L IH1 F +CLIFF'S K L IH1 F S +CLIFFE K L IH1 F +CLIFFHANGER K L IH1 F HH AE2 NG ER0 +CLIFFHANGERS K L IH1 F HH AE2 NG ER0 Z +CLIFFORD K L IH1 F ER0 D +CLIFFORD'S K L IH1 F ER0 D Z +CLIFFS K L IH1 F S +CLIFFS' K L IH1 F S +CLIFT K L IH1 F T +CLIFTON K L IH1 F T AH0 N +CLIGGOTT K L IH1 G AH0 T +CLIM K L IH1 M +CLIMACO K L IH1 M AH0 K OW0 +CLIMACTIC K L AY0 M AE1 K T IH0 K +CLIMATE K L AY1 M AH0 T +CLIMATE(1) K L AY1 M IH0 T +CLIMATES K L AY1 M AH0 T S +CLIMATES(1) K L AY1 M IH0 T S +CLIMATIC K L AY0 M AE1 T IH0 K +CLIMATOLOGIST K L IH2 M AH0 T AA1 L AH0 JH IH0 S T +CLIMATOLOGIST(1) K L AY2 M AH0 T AA1 L AH0 JH IH0 S T +CLIMATOLOGISTS K L IH2 M AH0 T AA1 L AH0 JH IH0 S T S +CLIMATOLOGISTS(1) K L AY2 M AH0 T AA1 L AH0 JH IH0 S T S +CLIMATOLOGISTS(2) K L IH2 M AH0 T AA1 L AH0 JH IH0 S +CLIMATOLOGISTS(3) K L AY2 M AH0 T AA1 L AH0 JH IH0 S +CLIMAX K L AY1 M AE2 K S +CLIMAXED K L AY1 M AE2 K S T +CLIMAXES K L IH1 M AE0 K S IH0 Z +CLIMAXES(1) K L AY1 M AE0 K S IH0 Z +CLIMB K L AY1 M +CLIMBED K L AY1 M D +CLIMBER K L AY1 M ER0 +CLIMBERS K L AY1 M ER0 Z +CLIMBERS' K L AY1 M ER0 Z +CLIMBING K L AY1 M IH0 NG +CLIMBS K L AY1 M Z +CLIMER K L AY1 M ER0 +CLIMES K L AY1 M Z +CLINARD K L IH1 N ER0 D +CLINCH K L IH1 N CH +CLINCHED K L IH1 N CH T +CLINCHER K L IH1 N CH ER0 +CLINCHES K L IH1 N CH AH0 Z +CLINCHES(1) K L IH1 N CH IH0 Z +CLINCHING K L IH1 N CH IH0 NG +CLINE K L AY1 N +CLINES K L AY1 N Z +CLINES'S K L AY1 N Z IH0 Z +CLING K L IH1 NG +CLINGAN K L IH1 NG G AH0 N +CLINGENPEEL K L IH0 NG G EH1 N P IY0 L +CLINGER K L IH1 NG ER0 +CLINGER'S K L IH1 NG ER0 Z +CLINGERMAN K L IH1 NG ER0 M AH0 N +CLINGING K L IH1 NG IH0 NG +CLINGMAN K L IH1 NG M AH0 N +CLINGS K L IH1 NG Z +CLINI K L IY1 N IY0 +CLINIC K L IH1 N IH0 K +CLINIC'S K L IH1 N IH0 K S +CLINICAL K L IH1 N AH0 K AH0 L +CLINICAL(1) K L IH1 N IH0 K AH0 L +CLINICAL'S K L IH1 N IH0 K AH0 L Z +CLINICALLY K L IH1 N IH0 K AH0 L IY0 +CLINICALLY(1) K L IH1 N IH0 K L IY0 +CLINICIAN K L IH0 N IH1 SH AH0 N +CLINICIANS K L IH0 N IH1 SH AH0 N Z +CLINICS K L IH1 N IH0 K S +CLINIQUE K L AH0 N IY1 K +CLINK K L IH1 NG K +CLINKENBEARD K L IH0 NG K EH1 N B ER0 D +CLINKSCALE K L IH1 NG K S K EY2 L +CLINKSCALES K L IH1 NG K S K EY2 L Z +CLINT K L IH1 N T +CLINTON K L IH1 N T AH0 N +CLINTON'S K L IH1 N T AH0 N Z +CLINTONITE K L IH1 N T AH0 N AY2 T +CLINTONITES K L IH1 N T AH0 N AY2 T S +CLINTONOMICS K L IH2 N T AH0 N AA1 M IH0 K S +CLINTONS K L IH1 N T AH0 N Z +CLINTONS' K L IH1 N T AH0 N Z +CLIO K L IY1 OW0 +CLIP K L IH1 P +CLIPBOARD K L IH1 P B AO2 R D +CLIPPARD K L IH1 P ER0 D +CLIPPED K L IH1 P T +CLIPPER K L IH1 P ER0 +CLIPPERS K L IH1 P ER0 Z +CLIPPING K L IH1 P IH0 NG +CLIPPINGER K L IH1 P IH0 NG ER0 +CLIPPINGS K L IH1 P IH0 NG Z +CLIPS K L IH1 P S +CLIQUE K L IY1 K +CLIQUES K L IH1 K S +CLITES K L AY1 T S +CLITORIS K L AY0 T AO1 R IH0 S +CLIVE K L AY1 V +CLIVER K L AY1 V ER0 +CLO S IY2 EH2 L OW1 +CLOAK K L OW1 K +CLOAKED K L OW1 K T +CLOAKING K L OW1 K IH0 NG +CLOAKROOM K L OW1 K R UW2 M +CLOBBER K L AA1 B ER0 +CLOBBERED K L AA1 B ER0 D +CLOBBERING K L AA1 B ER0 IH0 NG +CLOCK K L AA1 K +CLOCK'S K L AA1 K S +CLOCKED K L AA1 K T +CLOCKER K L AA1 K ER0 +CLOCKERS K L AA1 K ER0 Z +CLOCKING K L AA1 K IH0 NG +CLOCKS K L AA1 K S +CLOCKWISE K L AA1 K W AY2 Z +CLOCKWORK K L AA1 K W ER2 K +CLODFELTER K L AA1 D F EH2 L T ER0 +CLODOVEO K L OW0 D OW1 V IY0 OW0 +CLOE K L OW1 +CLOER K L OW1 ER0 +CLOEY K L OW1 IY0 +CLOG K L AA1 G +CLOGGED K L AO1 G D +CLOGGING K L AA1 G IH0 NG +CLOGGING(1) K L AO1 G IH0 NG +CLOGS K L AA1 G Z +CLOGSTON K L AA1 G S T AH0 N +CLOHERTY K L AA1 HH ER0 T IY0 +CLOHESSY K L AA1 HH IH0 S IY0 +CLOISTER K L OY1 S T ER0 +CLOISTERED K L OY1 S T ER0 D +CLOISTERS K L OY1 S T ER0 Z +CLOKE K L OW1 K +CLOMIPRAMINE K L OW1 M IH0 P R AH0 M AY2 N +CLONCH K L AA1 N CH +CLONE K L OW1 N +CLONED K L OW1 N D +CLONES K L OW1 N Z +CLONES' K L OW1 N Z +CLONIDINE K L AA1 N IH0 D IY2 N +CLONING K L OW1 N IH0 NG +CLONINGER K L OW1 N IH0 NG ER0 +CLONTS K L AA1 N T S +CLONTZ K L AA1 N T S +CLOONAN K L UW1 N AH0 N +CLOONEY K L UW1 N IY0 +CLOOTIE K L UW1 T IY0 +CLOPPER K L AA1 P ER0 +CLOPTON K L AA1 P T AH0 N +CLORE K L AO1 R +CLORE'S K L AO1 R Z +CLORINDA K L AO0 R IY1 N D AH0 +CLOROX K L AO1 R AA0 K S +CLOS K L AA1 S +CLOSE K L OW1 S +CLOSE(1) K L OW1 Z +CLOSE-UP K L OW1 S AH2 P +CLOSED K L OW1 Z D +CLOSEDOWN K L OW1 Z D AW2 N +CLOSEDOWNS K L OW1 Z D AW2 N Z +CLOSELY K L OW1 S L IY0 +CLOSENESS K L OW1 S N IH0 S +CLOSER K L OW1 S ER0 +CLOSER(1) K L OW1 Z ER0 +CLOSES K L OW1 Z IH0 Z +CLOSEST K L OW1 S AH0 S T +CLOSET K L AA1 Z AH0 T +CLOSETED K L AA1 Z AH0 T IH0 D +CLOSETS K L AA1 Z AH0 T S +CLOSEUP K L OW1 S AH1 P +CLOSEUPS K L OW1 S AH1 P S +CLOSING K L OW1 Z IH0 NG +CLOSINGS K L OW1 Z IH0 NG Z +CLOSS K L AO1 S +CLOSSER K L AO1 S ER0 +CLOSSON K L AA1 S AH0 N +CLOSURE K L OW1 ZH ER0 +CLOSURES K L OW1 ZH ER0 Z +CLOT K L AA1 T +CLOTFELTER K L AA1 T F EH2 L T ER0 +CLOTH K L AO1 TH +CLOTHE K L OW1 DH +CLOTHED K L OW1 DH D +CLOTHES K L OW1 DH Z +CLOTHES(1) K L OW1 Z +CLOTHESHORSE K L OW1 Z HH AO2 R S +CLOTHESTIME K L OW1 DH Z T AY1 M +CLOTHIER K L OW1 DH Y ER0 +CLOTHIERS K L OW1 DH Y ER0 Z +CLOTHILDA K L AH0 TH IH1 L D AH0 +CLOTHILDE K L AA1 TH IH0 L D +CLOTHING K L OW1 DH IH0 NG +CLOTHS K L AO1 TH S +CLOTILDA K L AH0 T IH1 L D AH0 +CLOTS K L AA1 T S +CLOTT K L AA1 T +CLOTTED K L AA1 T AH0 D +CLOTTED(1) K L AA1 T IH0 D +CLOTTING K L AA1 T IH0 NG +CLOTURE K L OW1 CH ER0 +CLOUATRE K L AW1 AH0 T R +CLOUD K L AW1 D +CLOUDBURST K L AW1 D B ER2 S T +CLOUDED K L AW1 D IH0 D +CLOUDINESS K L AW1 D IY0 N IH0 S +CLOUDING K L AW1 D IH0 NG +CLOUDLESS K L AW1 D L AH0 S +CLOUDS K L AW1 D Z +CLOUDY K L AW1 D IY0 +CLOUGH K L AW1 +CLOUGHERTY K L AW1 ER0 T IY0 +CLOUSE K L AW1 S +CLOUSER K L AW1 S ER0 +CLOUT K L AW1 T +CLOUTHIER K L AW1 TH IY0 ER0 +CLOUTHIER(1) K L OW1 TH IY0 ER0 +CLOUTHIER(2) K L OW1 DH IY0 ER0 +CLOUTIER K L AW1 T IY0 ER0 +CLOVE K L OW1 V +CLOVER K L OW1 V ER0 +CLOVERLEAF K L OW1 V ER0 L IY2 F +CLOVES K L OW1 V Z +CLOVIS K L OW1 V IH0 S +CLOW K L OW1 +CLOWARD K L OW1 W ER0 D +CLOWDUS K L AW1 D IH0 S +CLOWER K L AW1 ER0 +CLOWERS K L AW1 ER0 Z +CLOWES K L AW1 Z +CLOWN K L AW1 N +CLOWNEY K L AW1 N IY0 +CLOWNING K L AW1 N IH0 NG +CLOWNS K L AW1 N Z +CLOY K L OY1 +CLOYD K L OY1 D +CLOYING K L OY1 IH0 NG +CLOZAPINE K L OW1 Z AH0 P AY2 N +CLUB K L AH1 B +CLUB'S K L AH1 B Z +CLUBB K L AH1 B +CLUBBED K L AH1 B D +CLUBBING K L AH1 B IH0 NG +CLUBBY K L AH1 B IY0 +CLUBHOUSE K L AH1 B HH AW2 S +CLUBHOUSES K L AH1 B HH AW2 S IH0 Z +CLUBS K L AH1 B Z +CLUCAS K L UW1 K AH0 Z +CLUCK K L AH1 K +CLUCKEY K L AH1 K IY0 +CLUCKING K L AH1 K IH0 NG +CLUCKS K L AH1 K S +CLUE K L UW1 +CLUED K L UW1 D +CLUELESS K L UW1 L AH0 S +CLUES K L UW1 Z +CLUETT K L UW1 IH0 T +CLUFF K L AH1 F +CLUGSTON K L AH1 G S T AH0 N +CLUJ K L UW1 JH +CLUJ(1) S IY1 EH1 L Y UW1 JH EY1 +CLUKEY K L UW1 K IY0 +CLUM K L AH1 M +CLUMP K L AH1 M P +CLUMPING K L AH1 M P IH0 NG +CLUMPS K L AH1 M P S +CLUMPY K L AH1 M P IY0 +CLUMSILY K L AH1 M S AH0 L IY0 +CLUMSINESS K L AH1 M Z IY0 N AH0 S +CLUMSY K L AH1 M Z IY0 +CLUNE K L UW1 N +CLUNG K L AH1 NG +CLUNK K L AH1 NG K +CLUNKER K L AH1 NG K ER0 +CLUNKERS K L AH1 NG K ER0 Z +CLUNKS K L AH1 NG K S +CLUNKY K L AH1 NG K IY0 +CLUNY K L UW1 N IY0 +CLUSTER K L AH1 S T ER0 +CLUSTERED K L AH1 S T ER0 D +CLUSTERING K L AH1 S T ER0 IH0 NG +CLUSTERS K L AH1 S T ER0 Z +CLUTCH K L AH1 CH +CLUTCHED K L AH1 CH T +CLUTCHES K L AH1 CH AH0 Z +CLUTCHES(1) K L AH1 CH IH0 Z +CLUTCHING K L AH1 CH IH0 NG +CLUTE K L UW1 T +CLUTTER K L AH1 T ER0 +CLUTTERED K L AH1 T ER0 D +CLUTTERING K L AH1 T ER0 IH0 NG +CLUTTS K L AH1 T S +CLYATT K L AY1 AH0 T +CLYBURN K L IH1 B ER0 N +CLYDE K L AY1 D +CLYDESDALE K L AY1 D Z D EY2 L +CLYMENE K L IH0 M IY1 N +CLYMER K L AY1 M ER0 +CLYNE K L AY1 N +CLYTE K L AY1 T +CLYTIE K L IH1 T IY0 +CLYVE K L AY1 V +CMOS S IY1 M OW0 S +CMOS(1) S IY1 EH1 M OW1 EH1 S +CMU S IY1 EH1 M Y UW1 +CMUDICT S IY2 EH2 M Y UW1 D IH2 K T +CMX K AH0 M EH1 K S +CNET S IY1 N EH2 T +CNN S IY1 EH1 N EH1 N +CNN'S S IY1 EH1 N EH1 N Z +CNN.COM S IY1 EH1 N EH1 N D AA1 T K AA1 M +CNNFN S IY1 EH1 N EH1 N EH1 F EH1 N +CO K OW1 +CO-OP K OW1 AA2 P +CO-OPERATIVE K OW2 AA1 P ER2 AH0 T IH0 V +CO-OPERATIVE(1) K OW2 AA1 P R AH0 T IH0 V +CO-OPT K OW0 AA1 P T +CO-OPTED K OW0 AA1 P T AH0 D +CO-WIFE K OW1 W AY1 F +CO-WORKER K OW1 W ER1 K ER0 +CO-WORKERS K OW1 W ER1 K ER0 Z +CO. K OW1 +CO.(1) K AH1 P AH0 N IY0 +CO2 S IY2 OW2 T UW1 +COACH K OW1 CH +COACH'S K OW1 CH IH0 Z +COACHED K OW1 CH T +COACHES K OW1 CH IH0 Z +COACHING K OW1 CH IH0 NG +COACHMAN K OW1 CH M AH0 N +COAD K OW1 D +COADY K OW1 D IY0 +COAGULATE K OW0 AE1 G Y AH0 L EY2 T +COAGULATING K OW0 AE1 G Y AH0 L EY2 T IH0 NG +COAGULATION K OW0 AE1 G Y AH0 L EY1 SH AH0 N +COAKLEY K OW1 K L IY0 +COAL K OW1 L +COAL'S K OW1 L Z +COALE K OW1 L +COALESCE K OW2 AH0 L EH1 S +COALESCED K OW2 AH0 L EH1 S T +COALESCENCE K OW2 AH0 L EH1 S AH0 N S +COALESCES K OW2 AH0 L EH1 S IH0 Z +COALESCING K OW2 AH0 L EH1 S IH0 NG +COALITION K OW2 AH0 L IH1 SH AH0 N +COALITION'S K OW2 AH0 L IH1 SH AH0 N Z +COALITIONS K OW2 AH0 L IH1 SH AH0 N Z +COALS K OW1 L Z +COALSON K OW1 L S AH0 N +COAN K OW1 N +COAR K AO1 R +COARSE K AO1 R S +COARSENING K AO1 R S IH0 N IH0 NG +COARSER K AO1 R S ER0 +COARTICULATE K OW2 AA0 R T IH1 K Y UW0 L EY0 T +COARTICULATED K OW2 AA0 R T IH1 K Y UW0 L EY0 T AH0 D +COARTICULATES K OW2 AA0 R T IH1 K Y UW0 L EY0 T S +COARTICULATING K OW2 AA0 R T IH1 K Y UW0 L EY0 T IH0 NG +COARTICULATION K OW2 AA0 R T IH1 K Y UW0 L EY0 SH AH0 N +COAST K OW1 S T +COAST'S K OW1 S T S +COASTAL K OW1 S T AH0 L +COASTAL'S K OW1 S T AH0 L Z +COASTAMERICA K OW2 S T AH0 M EH1 R IH0 K AH0 +COASTAMERICA'S K OW2 S T AH0 M EH1 R IH0 K AH0 Z +COASTED K OW1 S T IH0 D +COASTER K OW1 S T ER0 +COASTERS K OW1 S T ER0 Z +COASTING K OW1 S T IH0 NG +COASTLINE K OW1 S T L AY2 N +COASTLINES K OW1 S T L AY2 N Z +COASTS K OW1 S T S +COAT K OW1 T +COAT'S K OW1 T S +COATE K OW1 EY1 T +COATED K OW1 T AH0 D +COATED(1) K OW1 T IH0 D +COATES K OW1 EY1 T S +COATESVILLE K OW1 T S V IH2 L +COATING K OW1 T IH0 NG +COATINGS K OW1 T IH0 NG Z +COATNEY K OW1 T N IY0 +COATS K OW1 T S +COATTAIL K OW1 T T EY2 L +COATTAILS K OW1 T T EY2 L Z +COAUTHOR K OW1 AA1 TH ER0 +COAUTHORED K OW1 AA1 TH ER0 D +COAUTHORING K OW1 AA1 TH ER0 IH0 NG +COAUTHORS K OW1 AA1 TH ER0 Z +COAX K OW1 K S +COAXED K OW1 K S T +COAXES K OW1 K S IH0 Z +COAXIAL K OW1 AE1 K S IY0 AH0 L +COAXING K OW1 K S IH0 NG +COAXUM K OW1 K S AH0 M +COB K AA1 B +COBAIN K OW1 B EY2 N +COBAIN'S K OW1 B EY2 N Z +COBAINE K OW1 B EY2 N +COBALT K OW1 B AO2 L T +COBAUGH K AA1 B AO0 +COBB K AA1 B +COBBETT K AA1 B IH0 T +COBBINS K AA1 B IH0 N Z +COBBLE K AA1 B AH0 L +COBBLED K AA1 B AH0 L D +COBBLER K AA1 B L ER0 +COBBLER'S K AA1 B L ER0 Z +COBBLERS K AA1 B L ER0 Z +COBBLESTONE K AA1 B AH0 L S T OW2 N +COBBLESTONES K AA1 B AH0 L S T OW2 N Z +COBBS K AA1 B Z +COBE K OW1 B +COBEN K OW1 B AH0 N +COBEPA K OW0 B EY1 P AH0 +COBERLY K OW1 B ER0 L IY0 +COBERN K AA1 B ER0 N +COBERT K AA1 B ER0 T +COBEY K OW1 B IY0 +COBIA K OW1 B IY0 AH0 +COBIAN K OW1 B IY0 AH0 N +COBIN K OW1 B IH0 N +COBLE K OW1 B AH0 L +COBLEIGH K AA1 B L AH0 +COBLENTZ K AA1 B L IH0 N T S +COBLER K OW1 B AH0 L ER0 +COBLER(1) K OW1 B L ER0 +COBLINER K AA1 B L AY0 N ER0 +COBO K OW1 B OW0 +COBOL K OW1 B AO0 L +COBOS K OW1 B OW0 Z +COBRA K OW1 B R AH0 +COBRAS K OW1 B R AH0 Z +COBRE K AA1 B R AH0 +COBRIN K AA1 B R IH0 N +COBS K AA1 B Z +COBURN K OW1 B ER0 N +COBWEB K AA1 B W EH2 B +COBWEBS K AA1 B W EH2 B Z +COBY K OW1 B IY0 +COCA K OW1 K AH0 +COCA-COLA K OW2 K AH0 K OW1 L AA0 +COCAINE K OW0 K EY1 N +COCANINO K OW2 K AH0 N IY1 N OW0 +COCANOUGHER K AA1 K AH0 N AH2 F ER0 +COCCA K OW1 K AH0 +COCCARO K OW0 K AA1 R OW0 +COCCHI K OW1 K IY0 +COCCIA K OW1 CH AH0 +COCCO K OW1 K OW0 +COCCUS K AA1 K AH0 S +COCHAIRMAN K OW1 CH EH2 R M AH0 N +COCHENOUR K AA1 SH IH0 N UH0 R +COCHIN K OW1 CH IH0 N +COCHLEA K AA1 K L IY0 AH0 +COCHLEAR K AA1 K L IY0 ER0 +COCHLES K AA1 K AH0 L Z +COCHRAN K AA1 K R AH0 N +COCHRAN'S K AA1 K R AH0 N Z +COCHRANE K AA1 K R AH0 N +COCHRANTON K AA1 K R AH0 N T AH0 N +COCK K AA1 K +COCKAMAMIE K AO2 K AH0 M EY1 M IY0 +COCKATOO K AA1 K AH0 T UW2 +COCKATOOS K AA1 K AH0 T UW2 Z +COCKBURN K AA1 K B ER2 N +COCKBURN'S K OW1 B ER0 N Z +COCKBURN'S(1) K AA1 K B ER2 N Z +COCKE K OW1 K +COCKED K AA1 K T +COCKED(1) K AO1 K T +COCKER K AA1 K ER0 +COCKERELL K AA1 K ER0 EH2 L +COCKERHAM K AA1 K ER0 HH AE2 M +COCKERILL K AA1 K ER0 IH2 L +COCKEY K AA1 K IY0 +COCKEYED K AA1 K AY2 D +COCKFIELD K AA1 K F IY2 L D +COCKINESS K AA1 K IY0 N AH0 S +COCKING K AA1 K IH0 NG +COCKLE K AA1 K AH0 L +COCKLES K AA1 K AH0 L Z +COCKLIN K AA1 K L IH0 N +COCKMAN K AA1 K M AH0 N +COCKNEY K AA1 K N IY0 +COCKPIT K AA1 K P IH2 T +COCKPITS K AA1 K P IH2 T S +COCKRAN K AA1 K R AH0 N +COCKRELL K AA1 K R AH0 L +COCKRILL K AA1 K R AH0 L +COCKROACH K AA1 K R OW2 CH +COCKROACHES K AA1 K R OW2 CH IH0 Z +COCKROFT K AA1 K R AH0 F T +COCKRUM K AA1 K R AH0 M +COCKS K AA1 K S +COCKSUCKER K AA1 K S AH2 K ER0 +COCKSUCKER(1) K AA1 K S AH2 K ER0 Z +COCKTAIL K AA1 K T EY2 L +COCKTAILS K AA1 K T EY2 L Z +COCKWELL K AA1 K W EH2 L +COCKWELL'S K AA1 K W EH2 L Z +COCKY K AA1 K IY0 +COCO K OW1 K OW2 +COCOA K OW1 K OW0 +COCOANUTS K OW1 K OW0 N AH2 T S +COCOM K OW1 K AA1 M +COCONINO K OW2 K AH0 N IY1 N OW0 +COCONUT K OW1 K AH0 N AH2 T +COCONUTS K OW1 K AH0 N AH2 T S +COCOON K AH0 K UW1 N +COCOONING K AH0 K UW1 N IH0 NG +COCOONS K AH0 K UW1 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AA1 M ER0 Z B AE1 NG K S +COMMIE K AA1 M IY0 +COMMIES K AA1 M IY0 Z +COMMINGLE K AH0 M IH1 NG G AH0 L +COMMINGLE(1) K OW0 M IH1 NG G AH0 L +COMMINGLED K AA0 M IH1 NG G AH0 L D +COMMINGLED(1) K OW0 M IH1 NG G AH0 L D +COMMINGLING K AA0 M IH1 NG G AH0 L IH0 NG +COMMINGLING(1) K OW0 M IH1 NG G L IH0 NG +COMMINS K AA1 M IH0 N Z +COMMISERATE K AH0 M IH1 S ER0 EY2 T +COMMISERATES K AH0 M IH1 S ER0 EY2 T S +COMMISERATING K AH0 M IH1 S ER0 EY2 T IH0 NG +COMMISH K AH0 M IH1 SH +COMMISION K AH0 M IH1 Z AH0 N +COMMISION(1) K AH0 M IH1 SH AH0 N +COMMISSAR K AA1 M AH0 S AA2 R +COMMISSARIES K AA1 M AH0 S EH2 R IY0 Z +COMMISSARS K AA1 M IH0 S AA0 Z +COMMISSARY K AA1 M AH0 S EH2 R IY0 +COMMISSION K AH0 M IH1 SH AH0 N +COMMISSION'S K AH0 M IH1 SH AH0 N Z +COMMISSIONED K AH0 M IH1 SH AH0 N D +COMMISSIONER K AH0 M IH1 SH AH0 N ER0 +COMMISSIONER'S K AH0 M IH1 SH AH0 N ER0 Z +COMMISSIONERS K AH0 M IH1 SH AH0 N ER0 Z +COMMISSIONING K AH0 M IH1 SH AH0 N IH0 NG +COMMISSIONS K AH0 M IH1 SH AH0 N Z +COMMISSO K 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+COMPACTED K AH0 M P AE1 K T IH0 D +COMPACTNESS K AH0 M P AE1 K T N AH0 S +COMPACTOR K AH0 M P AE1 K T ER0 +COMPACTS K AH0 M P AE1 K T S +COMPACTS(1) K AA1 M P AE0 K T S +COMPAGNIE K AH1 M P AH0 N IY0 +COMPANERO K AA2 M P AH0 N Y EH1 R OW2 +COMPANHIA K AH0 M P AE1 NG Y AA2 +COMPANIA K AH0 M P EY1 N IY2 AA0 +COMPANIES K AH1 M P AH0 N IY2 Z +COMPANIES' K AH1 M P AH0 N IY2 Z +COMPANIES'S K AH1 M P AH0 N IY2 Z +COMPANION K AH0 M P AE1 N Y AH0 N +COMPANIONS K AH0 M P AE1 N Y AH0 N Z +COMPANIONSHIP K AH0 M P AE1 N Y AH0 N SH IH2 P +COMPANIONWAY K AH0 M P AE1 N Y AH0 N W EY2 +COMPANY K AH1 M P AH0 N IY2 +COMPANY'LL K AH1 M P AH0 N IY0 AH0 L +COMPANY'S K AH1 M P AH0 N IY0 Z +COMPANYWIDE K AH1 M P AH0 N IY0 W AY2 D +COMPAORE K AA2 M P AH0 AO1 R IY0 +COMPAQ K AA1 M P AE2 K +COMPAQ'S K AA1 M P AE2 K S +COMPARABILITY K AA2 M P ER0 AH0 B IH1 L IH0 T IY2 +COMPARABLE K AA1 M P R AH0 B AH0 L +COMPARABLE(1) K AH0 M P AE1 R AH0 B AH0 L +COMPARABLY K AA1 M P R AH0 B L IY2 +COMPARABLY(1) K AA0 M P AE1 R AH0 B L IY2 +COMPARATIVE K AH0 M P AE1 R AH0 T IH0 V +COMPARATIVELY K AH0 M P AE1 R AH0 T IH0 V L IY2 +COMPARATOR K AH0 M P AE1 R AH0 T ER2 +COMPARE K AH0 M P EH1 R +COMPARED K AH0 M P EH1 R D +COMPARES K AH0 M P EH1 R Z +COMPARING K AH0 M P EH1 R IH0 NG +COMPARISON K AH0 M P EH1 R AH0 S AH0 N +COMPARISONS K AH0 M P EH1 R AH0 S AH0 N Z +COMPARTMENT K AH0 M P AA1 R T M AH0 N T +COMPARTMENTAL K AH0 M P AA2 R T M EH1 N T AH0 L +COMPARTMENTALIZE K AH0 M P AA2 R T M EH1 N T AH0 L AY2 Z +COMPARTMENTALIZED K AA2 M P AA0 R T M EH1 N T AH0 L AY0 Z D +COMPARTMENTS K AH0 M P AA1 R T M AH0 N T S +COMPAS K AA1 M P AH0 S +COMPASS K AH1 M P AH0 S +COMPASSION K AH0 M P AE1 SH AH0 N +COMPASSIONATE K AH0 M P AE1 SH AH0 N AH0 T +COMPASSIONATELY K AH0 M P AE1 SH AH0 N AH0 T L IY2 +COMPATIBILITY K AH0 M P AE2 T AH0 B IH1 L AH0 T IY2 +COMPATIBLE K AH0 M P AE1 T AH0 B AH0 L +COMPATIBLES K AH0 M P AE1 T IH0 B AH0 L Z +COMPATRIOT K AH0 M P EY1 T R IY0 AH0 T +COMPATRIOTS K AH0 M P EY1 T R IY0 AH0 T S +COMPEAN K AA1 M P AH0 N +COMPEAU K AH0 M P OW1 +COMPEL K AH0 M P EH1 L +COMPELLED K AH0 M P EH1 L D +COMPELLING K AH0 M P EH1 L IH0 NG +COMPELLINGLY K AH0 M P EH1 L IH0 NG L IY0 +COMPELS K AH0 M P EH1 L Z +COMPENDIUM K AH0 M P EH1 N D IY0 AH0 M +COMPENSABLE K AH0 M P EH1 N S AH0 B AH0 L +COMPENSATE K AA1 M P AH0 N S EY2 T +COMPENSATED K AA1 M P AH0 N S EY2 T AH0 D +COMPENSATES K AA1 M P AH0 N S EY2 T S +COMPENSATING K AA1 M P AH0 N S EY2 T IH0 NG +COMPENSATION K AA2 M P AH0 N S EY1 SH AH0 N +COMPENSATIONS K AA2 M P AH0 N S EY1 SH AH0 N Z +COMPENSATORY K AH0 M P EH1 N S AH0 T AO2 R IY0 +COMPETE K AH0 M P IY1 T +COMPETED K AH0 M P IY1 T IH0 D +COMPETENCE K AA1 M P AH0 T IH0 N S +COMPETENCIES K AA1 M P AH0 T IH0 N S IY0 Z +COMPETENCY K AA1 M P AH0 T IH0 N S IY0 +COMPETENT K AA1 M P AH0 T IH0 N T +COMPETENTLY K AA1 M P AH0 T IH0 N T L IY0 +COMPETES K AH0 M P IY1 T S +COMPETING K AH0 M P IY1 T IH0 NG +COMPETITION K AA2 M P AH0 T IH1 SH AH0 N +COMPETITION'S K AA2 M P AH0 T IH1 SH AH0 N Z +COMPETITIONS K AA2 M P AH0 T IH1 SH AH0 N Z +COMPETITIVE K AH0 M P EH1 T AH0 T IH0 V +COMPETITIVE(1) K AH0 M P EH1 T IH0 T IH0 V +COMPETITIVELY K AH0 M P EH1 T IH0 T IH0 V L IY0 +COMPETITIVENESS K AH0 M P EH1 T IH0 T IH0 V N IH0 S +COMPETITOR K AH0 M P EH1 T AH0 T ER0 +COMPETITOR(1) K AH0 M P EH1 T IH0 T ER0 +COMPETITOR'S K AH0 M P EH1 T AH0 T ER0 Z +COMPETITORS K AH0 M P EH1 T AH0 T ER0 Z +COMPETITORS(1) K AH0 M P EH1 T IH0 T ER0 Z +COMPETITORS' K AH0 M P EH1 T IH0 T ER0 Z +COMPHER K AA1 M F ER0 +COMPILATION K AA2 M P AH0 L EY1 SH AH0 N +COMPILATIONS K AA2 M P AH0 L EY1 SH AH0 N Z +COMPILE K AH0 M P AY1 L +COMPILED K AH0 M P AY1 L D +COMPILER K AH0 M P AY1 L ER0 +COMPILERS K AH0 M P AY1 L ER0 Z +COMPILES K AH0 M P AY1 L Z +COMPILING K AH0 M P AY1 L IH0 NG +COMPLACENCY K AH0 M P L EY1 S AH0 N S IY0 +COMPLACENT K AH0 M P L EY1 S AH0 N T +COMPLACENTLY K AH0 M P L EY1 S AH0 N T L IY0 +COMPLAIN K AH0 M P L EY1 N +COMPLAINANT K AH0 M P L EY1 N AH0 N T +COMPLAINANT'S K AH0 M P L EY1 N AH0 N T S +COMPLAINANTS K AH0 M P L EY1 N AH0 N T S +COMPLAINED K AH0 M P L EY1 N D +COMPLAINER K AH0 M P L EY1 N ER0 +COMPLAINERS K AA1 M P L EY2 N ER0 Z +COMPLAINING K AH0 M P L EY1 N IH0 NG +COMPLAINS K AH0 M P L EY1 N Z +COMPLAINT K AH0 M P L EY1 N T +COMPLAINTS K AH0 M P L EY1 N T S +COMPLAISANT K AH0 M P L EY1 S AH0 N T +COMPLECTION K AH0 M P L EH1 K SH AH0 N +COMPLECTIONS K AH0 M P L EH1 K SH AH0 N Z +COMPLEMENT K AA1 M P L AH0 M AH0 N T +COMPLEMENTARY K AA2 M P L AH0 M EH1 N T R IY0 +COMPLEMENTARY(1) K AA2 M P L AH0 M EH1 N CH IY0 +COMPLEMENTED K AA1 M P L AH0 M EH2 N T IH0 D +COMPLEMENTING K AA1 M P L AH0 M EH2 N T IH0 NG +COMPLEMENTS K AA1 M P L AH0 M AH0 N T S +COMPLETE K AH0 M P L IY1 T +COMPLETED K AH0 M P L IY1 T AH0 D +COMPLETED(1) K AH0 M P L IY1 T IH0 D +COMPLETELY K AH0 M P L IY1 T L IY0 +COMPLETENESS K AH0 M P L IY1 T N AH0 S +COMPLETES K AH0 M P L IY1 T S +COMPLETING K AH0 M P L IY1 T IH0 NG +COMPLETION K AH0 M P L IY1 SH AH0 N +COMPLETIONS K AH0 M P L IY1 SH AH0 N Z +COMPLEX K AA1 M P L EH0 K S +COMPLEX(1) K AH0 M P L EH1 K S +COMPLEXES K AA1 M P L EH0 K S AH0 Z +COMPLEXION K AH0 M P L EH1 K SH AH0 N +COMPLEXIONS K AH0 M P L EH1 K SH AH0 N Z +COMPLEXITIES K AH0 M P L EH1 K S IH0 T IY0 Z +COMPLEXITY K AH0 M P L EH1 K S AH0 T IY0 +COMPLEXITY(1) K AH0 M P L EH1 K S IH0 T IY0 +COMPLIANCE K AH0 M P L AY1 AH0 N S +COMPLIANT K AH0 M P L AY1 AH0 N T +COMPLICATE K AA1 M P L AH0 K EY2 T +COMPLICATED K AA1 M P L AH0 K EY2 T AH0 D +COMPLICATES K AA1 M P L IH0 K EY2 T S +COMPLICATING K AA1 M P L AH0 K EY2 T IH0 NG +COMPLICATION K AA2 M P L AH0 K EY1 SH AH0 N +COMPLICATIONS K AA2 M P L AH0 K EY1 SH AH0 N Z +COMPLICIT K AH0 M P L IH1 S AH0 T +COMPLICITIES K AH0 M P L IH1 S IH0 T IY0 Z +COMPLICITY K AH0 M P L IH1 S AH0 T IY0 +COMPLICITY(1) K AH0 M P L IH1 S IH0 T IY0 +COMPLIED K AH0 M P L AY1 D +COMPLIES K AH0 M P L AY1 Z +COMPLIMENT K AA1 M P L AH0 M EH0 N T +COMPLIMENTARY K AA2 M P L AH0 M EH1 N T ER0 IY0 +COMPLIMENTED K AA1 M P L AH0 M EH2 N T IH0 D +COMPLIMENTING K AA1 M P L AH0 M EH2 N T IH0 NG +COMPLIMENTS K AA1 M P L AH0 M EH0 N T S +COMPLY K AH0 M P L AY1 +COMPLYING K AH0 M P L AY1 IH0 NG +COMPO K AA1 M P OW2 +COMPONENT K AH0 M P OW1 N AH0 N T +COMPONENTS K AH0 M P OW1 N AH0 N T S +COMPORT K AH0 M P AO1 R T +COMPORTED K AH0 M P AO1 R T AH0 D +COMPORTMENT K AH0 M P AO1 R T M AH0 N T +COMPOSE K AH0 M P OW1 Z +COMPOSED K AH0 M P OW1 Z D +COMPOSER K AH0 M P OW1 Z ER0 +COMPOSER'S K AH0 M P OW1 Z ER0 Z +COMPOSERS K AH0 M P OW1 Z ER0 Z +COMPOSES K AH0 M P OW1 Z IH0 Z +COMPOSING K AH0 M P OW1 Z IH0 NG +COMPOSITE K AH0 M P AA1 Z AH0 T +COMPOSITE(1) K AA0 M P AA1 Z AH0 T +COMPOSITE'S K AH0 M P AA1 Z AH0 T S +COMPOSITE'S(1) K AA0 M P AA1 Z AH0 T S +COMPOSITES K AH0 M P AA1 Z AH0 T S +COMPOSITES(1) K AA0 M P AA1 Z AH0 T S +COMPOSITION K AA2 M P AH0 Z IH1 SH AH0 N +COMPOSITIONAL K AA2 M P AH0 Z IH1 SH AH0 N AH0 L +COMPOSITIONS K AA2 M P AH0 Z IH1 SH AH0 N Z +COMPOST K AA1 M P OW0 S T +COMPOSTELA K AO2 M P AO0 S T EH1 L AH0 +COMPOSTING K AA1 M P OW2 S T IH0 NG +COMPOSTS K AA1 M P OW0 S T S +COMPOSURE K AH0 M P OW1 ZH ER0 +COMPOTE K AA1 M P OW0 T +COMPOUND K AA1 M P AW0 N D +COMPOUND(1) K AH0 M P AW1 N D +COMPOUNDED K AH0 M P AW1 N D AH0 D +COMPOUNDED(1) K AH0 M P AW1 N D IH0 D +COMPOUNDING K AH0 M P AW1 N D IH0 NG +COMPOUNDS K AA1 M P AW0 N D Z +COMPOUNDS(1) K AH0 M P AW1 N D Z +COMPREHEND K AA2 M P R IY0 HH EH1 N D +COMPREHENDED K AA2 M P R IH0 HH EH1 N D IH0 D +COMPREHENDING K AA2 M P R IH0 HH EH1 N D IH0 NG +COMPREHENDS K AA2 M P R IY0 HH EH1 N D Z +COMPREHENSIBILITY K AA2 M P R IY0 HH EH2 N S AH0 B IH1 L AH0 T IY0 +COMPREHENSIBLE K AA2 M P R IY0 HH EH1 N S AH0 B AH0 L +COMPREHENSION K AA2 M P R IY0 HH EH1 N SH AH0 N +COMPREHENSIVE K AA2 M P R IY0 HH EH1 N S IH0 V +COMPREHENSIVELY K AA2 M P R IH0 HH EH1 N S IH0 V L IY0 +COMPRESS K AA1 M P R EH0 S +COMPRESS(1) K AH0 M P R EH1 S +COMPRESSED K AH0 M P R EH1 S T +COMPRESSES K AA1 M P R EH0 S AH0 Z +COMPRESSES(1) K AH0 M P R EH1 S AH0 Z +COMPRESSES(2) K AH0 M P R EH1 S IH0 Z +COMPRESSING K AH0 M P R EH1 S IH0 NG +COMPRESSION K AH0 M P R EH1 SH AH0 N +COMPRESSOR K AH0 M P R EH1 S ER0 +COMPRESSORS K AH0 M P R EH1 S ER0 Z +COMPRINT K AA1 M P R IH2 N T +COMPRISE K AH0 M P R AY1 Z +COMPRISED K AH0 M P R AY1 Z D +COMPRISES K AH0 M P R AY1 Z AH0 Z +COMPRISES(1) K AH0 M P R AY1 Z IH0 Z +COMPRISING K AH0 M P R AY1 Z IH0 NG +COMPROMISE K AA1 M P R AH0 M AY2 Z +COMPROMISED K AA1 M P R AH0 M AY2 Z D +COMPROMISER K AA1 M P R AH0 M AY2 Z ER0 +COMPROMISES K AA1 M P R AH0 M AY2 Z IH0 Z +COMPROMISING K AA1 M P R AH0 M AY2 Z IH0 NG +COMPSTON K AA1 M P S T AH0 N +COMPTEK K AA1 M P T EH2 K +COMPTON K AA1 M P T AH0 N +COMPTON'S K AA1 M P T AH0 N Z +COMPTROLLER K AH0 M T R OW1 L ER0 +COMPTROLLER(1) K AA1 M T R OW2 L ER0 +COMPTROLLER'S K AH0 M T R OW1 L ER0 Z +COMPTROLLER'S(1) K AA1 M T R OW2 L ER0 Z +COMPTRONIX K AA2 M P T R AA1 N IH2 K S +COMPU K AA1 M P Y UW0 +COMPUADD K AA1 M P Y UW0 AE2 D +COMPUCHEM K AA1 M P Y UW0 K EH2 M +COMPUDYNE K AA1 M P Y UW0 D AY2 N +COMPUFUND K AA1 M P Y UW0 F AH2 N D +COMPUGRAPHIC K AA2 M P Y UW0 G R AE1 F IH0 K +COMPULSION K AH0 M P AH1 L SH AH0 N +COMPULSIONS K AH0 M P UH1 L SH AH0 N Z +COMPULSIVE K AH0 M P AH1 L S IH0 V +COMPULSIVELY K AH0 M P AH1 L S IH0 V L IY0 +COMPULSORY K AH0 M P AH1 L S ER0 IY0 +COMPUMAT K AA1 M P Y UW0 M AE2 T +COMPUNCTION K AH0 M P AH1 NG K SH AH0 N +COMPUS K AA1 M P Y UW0 Z +COMPUSA K AA1 M P Y UW1 EH1 S EY1 +COMPUSA'S K AA1 M P Y UW1 EH1 S EY1 Z +COMPUSERVE K AA1 M P Y UW0 S ER0 V +COMPUSERVE'S K AA1 M P Y UW0 S ER0 V Z +COMPUTALOG K AA1 M P Y UW0 T AE2 L AO0 G +COMPUTATION K AA2 M P Y AH0 T EY1 SH AH0 N +COMPUTATIONAL K AA2 M P Y UW0 T EY1 SH AH0 N AH0 L +COMPUTATIONS K AA2 M P Y UW0 T EY1 SH AH0 N Z +COMPUTE K AH0 M P Y UW1 T +COMPUTED K AH0 M P Y UW1 T AH0 D +COMPUTED(1) K AH0 M P Y UW1 T IH0 D +COMPUTER K AH0 M P Y UW1 T ER0 +COMPUTER'S K AH0 M P Y UW1 T ER0 Z +COMPUTER-GENERATED K AH0 M P Y UW1 T ER0 JH EH1 N ER0 EY2 T AH0 D +COMPUTERCRAFT K AH0 M P Y UW1 T ER0 K R AE2 F T +COMPUTERIZATION K AH0 M P Y UW2 T ER0 IH0 Z EY1 SH AH0 N +COMPUTERIZE K AH0 M P Y UW1 T ER0 AY2 Z +COMPUTERIZED K AH0 M P Y UW1 T ER0 AY2 Z D +COMPUTERIZING K AH0 M P Y UW1 T ER0 AY2 Z IH0 NG +COMPUTERLAND K AH0 M P Y UW1 T ER0 L AE2 N D +COMPUTERLAND'S K AH0 M P Y UW1 T ER0 L AE2 N D Z +COMPUTERLIKE K AH0 M P Y UW1 T ER0 L AY2 K +COMPUTERS K AH0 M P Y UW1 T ER0 Z +COMPUTERS' K AH0 M P Y UW1 T ER0 Z +COMPUTERVISION K AH0 M P Y UW1 T ER0 V IH2 ZH AH0 N +COMPUTERWORLD K AH0 M P Y UW1 T ER0 W ER2 L D +COMPUTES K AH0 M P Y UW1 T S +COMPUTING K AH0 M P Y UW1 T IH0 NG +COMPUTRAC K AA1 M P Y UW0 T R AE2 K +COMPUWARE K AA1 M P Y UW0 W EH2 R +COMRADE K AA1 M R AE2 D +COMRADES K AA1 M R AE2 D Z +COMRIE K AA1 M ER0 IY0 +COMS K AA1 M Z +COMSAT K AA1 M S AE0 T +COMSAT'S K AA1 M S AE0 T S +COMSTOCK K AA1 M S T AA2 K +COMTOIS K AH0 M T W AA1 +COMTREX K AA1 M T R EH2 K S +COMUNALE K OW0 M UW0 N AA1 L IY0 +CON K AA1 N +CONA K OW1 N AH0 +CONABLE K OW1 N AH0 B AH0 L +CONABLE'S K OW1 N AH0 B AH0 L Z +CONAGRA K AA2 N AE1 G R AH0 +CONAGRA'S K AA2 N AE1 G R AH0 Z +CONAHAN K AA1 N AH0 HH AE0 N +CONAIR K AA1 N EH2 R +CONAL K OW1 N AH0 L +CONAN K OW1 N AH0 N +CONANT K OW1 N AH0 N T +CONANT-PABLOS K OW1 N AH0 N T P AA1 B L OW0 S +CONARD K AA1 N ER0 D +CONASUPO K AA2 N AH0 S UW1 P OW0 +CONATSER K AA1 N AH0 T S ER0 +CONATY K AA1 N AH0 T IY0 +CONAWAY K AA1 N AH0 W EY0 +CONBOY K AA1 N B OY0 +CONCA K AA1 NG K AH0 +CONCANNON K AH0 N K AE1 N AH0 N +CONCATENATE K AH0 N K AE1 T AH0 N EY2 T +CONCATENATED K AH0 N K AE1 T AH0 N EY2 T AH0 D +CONCATENATES K AH0 N K AE1 T AH0 N EY2 T S +CONCATENATING K AH0 N K AE1 T AH0 N EY2 T IH0 NG +CONCATENATION K AH0 N K AE2 T AH0 N EY1 SH AH0 N +CONCAVE K AA0 N K EY1 V +CONCAVE(1) K AA1 N K EY0 V +CONCAVITY K AA0 N K AA1 V AH0 T IY2 +CONCEAL K AH0 N S IY1 L +CONCEALED K AH0 N S IY1 L D +CONCEALING K AH0 N S IY1 L IH0 NG +CONCEALMENT K AH0 N S IY1 L M AH0 N T +CONCEALS K AH0 N S IY1 L Z +CONCEDE K AH0 N S IY1 D +CONCEDED K AH0 N S IY1 D IH0 D +CONCEDES K AH0 N S IY1 D Z +CONCEDING K AH0 N S IY1 D IH0 NG +CONCEIT K AH0 N S IY1 T +CONCEITED K AH0 N S IY1 T AH0 D +CONCEIVABLE K AH0 N S IY1 V AH0 B AH0 L +CONCEIVABLY K AH0 N S IY1 V AH0 B L IY0 +CONCEIVE K AH0 N S IY1 V +CONCEIVED K AH0 N S IY1 V D +CONCEIVING K AH0 N S IY1 V IH0 NG +CONCENTRATE K AA1 N S AH0 N T R EY2 T +CONCENTRATED K AA1 N S AH0 N T R EY2 T AH0 D +CONCENTRATED(1) K AO1 N S AH0 N T R EY2 T IH0 D +CONCENTRATES K AA1 N S AH0 N T R EY2 T S +CONCENTRATING K AA1 N S AH0 N T R EY2 T IH0 NG +CONCENTRATION K AA2 N S AH0 N T R EY1 SH AH0 N +CONCENTRATIONS K AA2 N S AH0 N T R EY1 SH AH0 N Z +CONCENTRIC K AH0 N S EH1 N T R IH0 K +CONCEPCION K AH0 N S EH2 P S IY0 OW1 N +CONCEPT K AA1 N S EH0 P T +CONCEPTION K AH0 N S EH1 P SH AH0 N +CONCEPTIONS K AH0 N S EH1 P SH AH0 N Z +CONCEPTS K AA1 N S EH0 P T S +CONCEPTS(1) K AA1 N S EH0 P S +CONCEPTUAL K AH0 N S EH1 P CH UW0 AH0 L +CONCEPTUALIZATION K AH0 N S EH1 P CH W AH0 L IH0 Z EY2 SH AH0 N +CONCEPTUALIZE K AH0 N S EH1 P CH W AH0 L AY2 Z +CONCEPTUALIZES K AH0 N S EH1 P CH W AH0 L AY2 Z IH0 Z +CONCEPTUALLY K AH0 N S EH1 P CH UW0 AH0 L IY0 +CONCERN K AH0 N S ER1 N +CONCERN'S K AH0 N S ER1 N Z +CONCERNED K AH0 N S ER1 N D +CONCERNING K AH0 N S ER1 N IH0 NG +CONCERNS K AH0 N S ER1 N Z +CONCERNS' K AH0 N S ER1 N Z +CONCERT K AA1 N S ER0 T +CONCERT(1) K AH0 N S ER1 T +CONCERTED K AH0 N S ER1 T AH0 D +CONCERTED(1) K AH0 N S ER1 T IH0 D +CONCERTI K AH0 N CH EH1 R T IY0 +CONCERTINA K AA0 N S ER0 T IY1 N AH0 +CONCERTMASTER K AA1 N S ER0 T M AE2 S T ER0 +CONCERTO K AH0 N CH EH1 R T OW0 +CONCERTOS K AH0 N CH EH1 R T OW0 Z +CONCERTS K AA1 N S ER0 T S +CONCERTS(1) K AH0 N S ER1 T S +CONCESSION K AH0 N S EH1 SH AH0 N +CONCESSIONAIRE K AH0 N S EH2 SH AH0 N EH1 R +CONCESSIONAL K AH0 N S EH1 SH AH0 N AH0 L +CONCESSIONARY K AH0 N S EH1 SH AH0 N EH2 R IY0 +CONCESSIONS K AH0 N S EH1 SH AH0 N Z +CONCH K AA1 N CH +CONCH(1) K AA1 NG K +CONCHA K AA1 N CH AH0 +CONCHEMCO K AA2 N CH EH1 M K OW0 +CONCHITA K AH0 N CH IY1 T AH0 +CONCHOID K AA1 N CH OY0 D +CONCIERGE K AA2 N S IY0 EH1 R ZH +CONCILIATION K AH0 N S IH2 L IY0 EY1 SH AH0 N +CONCILIATOR K AH0 N S IH1 L IY0 EY2 T ER0 +CONCILIATOR'S K AH0 N S IH1 L IY0 EY2 T ER0 Z +CONCILIATORY K AH0 N S IH1 L IY2 AH0 T AO2 R IY0 +CONCILIATORY(1) K AH0 N S IH1 L Y AH0 T AO2 R IY0 +CONCISE K AH0 N S AY1 S +CONCISELY K AH0 N S AY1 S L IY0 +CONCLAVE K AA1 N K L EY2 V +CONCLUDE K AH0 N K L UW1 D +CONCLUDED K AH0 N K L UW1 D AH0 D +CONCLUDED(1) K AH0 N K L UW1 D IH0 D +CONCLUDES K AH0 N K L UW1 D Z +CONCLUDING K AH0 N K L UW1 D IH0 NG +CONCLUSION K AH0 N K L UW1 ZH AH0 N +CONCLUSIONS K AH0 N K L UW1 ZH AH0 N Z +CONCLUSIVE K AH0 N K L UW1 S IH0 V +CONCLUSIVELY K AH0 N K L UW1 S IH0 V L IY0 +CONCOCT K AH0 N K AA1 K T +CONCOCTED K AH0 N K AA1 K T AH0 D +CONCOCTING K AH0 N K AA1 K T IH0 NG +CONCOCTION K AH0 N K AA1 K SH AH0 N +CONCOCTIONS K AH0 N K AA1 K SH AH0 N Z +CONCOMITANT K AA2 N K AA1 M AH0 T AH0 N T +CONCOMITANT(1) K AA2 N K AH0 M IH1 T AH0 N T +CONCOMITANTLY K AA2 N K AA1 M AH0 T AH0 N T L IY0 +CONCOMITANTLY(1) K AA2 N K AH0 M IH1 T AH0 N T L IY0 +CONCORD K AA1 N K AO2 R D +CONCORD(1) K AA1 N K ER0 D +CONCORD'S K AA1 N K AO2 R D Z +CONCORD'S(1) K AA1 N K ER0 D Z +CONCORDE K AA1 N K AO2 R D +CONCOURSE K AA1 N K AO2 R S +CONCOURSES K AA1 N K AO2 R S IH0 Z +CONCRETE K AH0 N K R IY1 T +CONCRETE(1) K AA1 N K R IY0 T +CONCRETELY K AA1 N K R IY2 T L IY0 +CONCUBINAGE K AA0 N K Y UW1 B AH0 N AH0 JH +CONCUBINE K AA1 N K Y AH0 B AY2 N +CONCUBINES K AA1 N K Y AH0 B AY2 N Z +CONCUR K AH0 N K ER1 +CONCURRED K AH0 N K ER1 D +CONCURRENCE K AH0 N K ER1 AH0 N S +CONCURRENT K AH0 N K ER1 AH0 N T +CONCURRENTLY K AH0 N K ER1 AH0 N T L IY0 +CONCURRING K AH0 N K ER1 IH0 NG +CONCURS K AH0 N K ER1 Z +CONCUSSION K AH0 N K AH1 SH AH0 N +CONCUSSIONS K AH0 N K AH1 SH AH0 N Z +CONDE K AA1 N D +CONDELLO K AH0 N D EH1 L OW0 +CONDEMN K AH0 N D EH1 M +CONDEMNATION K AA2 N D AH0 M N EY1 SH AH0 N +CONDEMNATIONS K AA2 N D AH0 M N EY1 SH AH0 N Z +CONDEMNED K AH0 N D EH1 M D +CONDEMNING K AH0 N D EH1 M IH0 NG +CONDEMNS K AH0 N D EH1 M Z +CONDENSATE K AA1 N D AH0 N S EY2 T +CONDENSATES K AA1 N D AH0 N S EY2 T S +CONDENSATION K AA2 N D AH0 N S EY1 SH AH0 N +CONDENSE K AH0 N D EH1 N S +CONDENSED K AH0 N D EH1 N S T +CONDENSER K AH0 N D EH1 N S ER0 +CONDENSING K AH0 N D EH1 N S IH0 NG +CONDER K AA1 N D ER0 +CONDESCEND K AA2 N D IH0 S EH1 N D +CONDESCENDED K AA2 N D IH0 S EH1 N D IH0 D +CONDESCENDING K AA2 N D IH0 S EH1 N D IH0 NG +CONDESCENSION K AA2 N D AH0 S EH1 N SH AH0 N +CONDIE K AA1 N D IY0 +CONDIMENT K AA1 N D AH0 M AH0 N T +CONDIMENTS K AA1 N D AH0 M AH0 N T S +CONDIT K AA1 N D IH0 T +CONDITION K AH0 N D IH1 SH AH0 N +CONDITIONAL K AH0 N D IH1 SH AH0 N AH0 L +CONDITIONALITY K AH0 N D IH2 SH AH0 N AE1 L IH0 T IY0 +CONDITIONALLY K AH0 N D IH1 SH AH0 N AH0 L IY0 +CONDITIONALLY(1) K AH0 N D IH1 SH N AH0 L IY0 +CONDITIONED K AH0 N D IH1 SH AH0 N D +CONDITIONER K AH0 N D IH1 SH AH0 N ER0 +CONDITIONERS K AH0 N D IH1 SH AH0 N ER0 Z +CONDITIONING K AH0 N D IH1 SH AH0 N IH0 NG +CONDITIONS K AH0 N D IH1 SH AH0 N Z +CONDITT K AA1 N D IH0 T +CONDO K AA1 N D OW0 +CONDOLENCE K AH0 N D OW1 L AH0 N S +CONDOLENCES K AH0 N D OW1 L AH0 N S AH0 Z +CONDOM K AA1 N D AH0 M +CONDOMINIUM K AA2 N D AH0 M IH1 N IY0 AH0 M +CONDOMINIUMS K AA2 N D AH0 M IH1 N IY0 AH0 M Z +CONDOMS K AA1 N D AH0 M Z +CONDON K AA1 N D AH0 N +CONDONE K AH0 N D OW1 N +CONDONED K AH0 N D OW1 N D +CONDONES K AH0 N D OW1 N Z +CONDONING K AH0 N D OW1 N IH0 NG +CONDOR K AA1 N D ER0 +CONDORS K AA1 N D ER0 Z +CONDOS K AA1 N D OW0 Z +CONDRA K AA1 N D R AH0 +CONDRACKY K AA2 N D R AE1 K IY0 +CONDRACKY'S K AA2 N D R AE1 K IY0 Z +CONDRAY K AA1 N D R EY0 +CONDREN K AA1 N D ER0 AH0 N +CONDREY K AA1 N D R IY0 +CONDRON K AA1 N D R AH0 N +CONDRY K AA1 N D ER0 IY0 +CONDUCIVE K AH0 N D UW1 S IH0 V +CONDUCT K AA1 N D AH0 K T +CONDUCT(1) K AA0 N D AH1 K T +CONDUCTED K AH0 N D AH1 K T AH0 D +CONDUCTING K AH0 N D AH1 K T IH0 NG +CONDUCTION K AH0 N D AH1 K SH AH0 N +CONDUCTIVE K AH0 N D AH1 K T IH0 V +CONDUCTIVITY K AA2 N D AH2 K T IH1 V AH0 T IY0 +CONDUCTOR K AH0 N D 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AH0 N Z +CONFETTI K AH0 N F EH1 T IY0 +CONFIDANT K AA1 N F AH0 D AA2 N T +CONFIDANTE K AA1 N F AH0 D AE2 N T +CONFIDANTS K AA1 N F AH0 D AE2 N T S +CONFIDE K AH0 N F AY1 D +CONFIDED K AH0 N F AY1 D IH0 D +CONFIDENCE K AA1 N F AH0 D EH0 N S +CONFIDENCE'S K AA1 N F AH0 D EH2 N S IH0 Z +CONFIDENCES K AA1 N F AH0 D EH2 N S IH0 Z +CONFIDENT K AA1 N F AH0 D AH0 N T +CONFIDENTIAL K AA2 N F AH0 D EH1 N SH AH0 L +CONFIDENTIALITY K AA2 N F AH0 D EH2 N SH IY0 AE1 L AH0 T IY0 +CONFIDENTIALLY K AA2 N F AH0 D EH1 N SH AH0 L IY0 +CONFIDENTLY K AA1 N F AH0 D AH0 N T L IY0 +CONFIDES K AH0 N F AY1 D Z +CONFIDING K AH0 N F AY1 D IH0 NG +CONFIGURATION K AH0 N F IH2 G Y ER0 EY1 SH AH0 N +CONFIGURATIONS K AH0 N F IH2 G Y ER0 EY1 SH AH0 N Z +CONFIGURE K AH0 N F IH1 G Y ER0 +CONFIGURED K AH0 N F IH1 G Y ER0 D +CONFIGURING K AH0 N F IH1 G Y ER0 IH0 NG +CONFINDUSTRIA K AA0 N F IH2 N D UW1 S T R IY2 AH0 +CONFINE K AH0 N F AY1 N +CONFINED K AH0 N F AY1 N D +CONFINEMENT K AH0 N F AY1 N M AH0 N T +CONFINES K AA1 N 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ER0 AH0 T +CONGLOMERATE'S K AH0 N G L AA1 M ER0 AH0 T S +CONGLOMERATES K AH0 N G L AA1 M ER0 AH0 T S +CONGLOMERATION K AH0 N G L AA2 M ER0 EY1 SH AH0 N +CONGO K AA1 NG G OW0 +CONGO'S K AA1 NG G OW0 Z +CONGOLESE K AA2 N G AH0 L IY1 Z +CONGRATS K AH0 N G R AE1 T S +CONGRATULATE K AH0 N G R AE1 CH AH0 L EY2 T +CONGRATULATED K AH0 N G R AE1 CH AH0 L EY2 T IH0 D +CONGRATULATING K AH0 N G R AE1 CH AH0 L EY2 T IH0 NG +CONGRATULATION K AH0 N G R AE2 CH AH0 L EY1 SH AH0 N +CONGRATULATIONS K AH0 N G R AE2 CH AH0 L EY1 SH AH0 N Z +CONGRATULATORY K AH0 N G R AE1 CH AH0 L AH0 T AO2 R IY0 +CONGREGANT K AA1 NG G R AH0 G AH0 N T +CONGREGANTS K AA1 NG G R AH0 G AH0 N T S +CONGREGATE K AA1 NG G R AH0 G EY2 T +CONGREGATED K AA1 NG G R IH0 G EY2 T IH0 D +CONGREGATION K AA2 NG G R AH0 G EY1 SH AH0 N +CONGREGATION'S K AA2 NG G R AH0 G EY1 SH AH0 N Z +CONGREGATIONAL K AA2 NG G R AH0 G EY1 SH AH0 N AH0 L +CONGREGATIONS K AA2 NG G R AH0 G EY1 SH AH0 N Z +CONGRESS K AA1 NG G R AH0 S +CONGRESS' K AA1 N G R AH0 S IH0 Z +CONGRESS'(1) K AA1 NG G R AH0 S +CONGRESS'S K AA1 NG G R AH0 S IH0 Z +CONGRESSES K AA1 NG G R AH0 S IH0 Z +CONGRESSIONAL K AH0 N G R EH1 SH AH0 N AH0 L +CONGRESSIONALLY K AH0 N G R EH1 SH AH0 N AH0 L IY0 +CONGRESSIONALLY(1) K AH0 N G R EH1 SH N AH0 L IY0 +CONGRESSMAN K AA1 NG G R AH0 S M AH0 N +CONGRESSMAN'S K AA1 NG G R AH0 S M AH0 N Z +CONGRESSMEN K AA1 NG G R AH0 S M IH0 N +CONGRESSPEOPLE K AA1 NG G R AH0 S P IY2 P AH0 L +CONGRESSPERSON K AA1 NG G R AH0 S P ER2 S AH0 N +CONGRESSPERSONS K AA1 NG G R AH0 S P ER2 S AH0 N Z +CONGRESSWOMAN K AA1 NG G R AH0 S W UH2 M AH0 N +CONGRESSWOMAN'S K AA1 NG G R AH0 S W UH2 M AH0 N Z +CONGRESSWOMEN K AA1 NG G R AH0 S W IH2 M IH0 N +CONGROVE K AA1 NG G R AH0 V +CONGRUENCE K AO1 N G R UW0 AH0 N S +CONGRUENT K AO1 N G R UW0 EH2 N T +CONGRUITY K AH0 N G R UW1 AH0 T IY0 +CONIC K AA1 N IH0 K +CONIC(1) K OW1 N IH0 K +CONICAL K AA1 N IH0 K AH0 L +CONICAL(1) K OW1 N IH0 K AH0 L +CONICS K AA1 N IH0 K S +CONICS(1) K OW1 N IH0 K S +CONIFER K AA1 N AH0 F ER0 +CONIFER'S K AA1 N AH0 F ER0 Z +CONIFEROUS K AH0 N IH1 F ER0 AH0 S +CONIFERS K AA1 N AH0 F ER0 Z +CONIGLIARO K AH0 N IH2 G L IY0 AA1 R OW0 +CONIGLIO K AH0 N IH1 G L IY0 OW0 +CONISTON K AA1 N AH0 S T AH0 N +CONJECTURE K AH0 N JH EH1 K CH ER0 +CONJECTURE(1) K AH0 N JH EH1 K SH ER0 +CONJECTURES K AH0 N JH EH1 K CH ER0 Z +CONJECTURES(1) K AH0 N JH EH1 K SH ER0 Z +CONJOIN K AA2 N JH OY1 N +CONJOINED K AA2 N JH OY1 N D +CONJUGAL K AA1 N JH AH0 G AH0 L +CONJUGATE K AA2 N JH AH0 G EY1 T +CONJUGATE(1) K AA1 N JH AH0 G EY2 T +CONJUGATED K AA2 N JH AH0 G EY1 T IH0 D +CONJUGATED(1) K AA1 N JH AH0 G EY2 T IH0 D +CONJUGATES K AA2 N JH AH0 G EY1 T S +CONJUGATES(1) K AA1 N JH AH0 G EY2 T S +CONJUGATION K AA2 N JH AH0 G EY1 SH AH0 N +CONJUGATIONS K AA2 N JH AH0 G EY1 SH AH0 N Z +CONJUL K AA1 N JH AH0 L +CONJUNCTION K AH0 N JH AH1 NG K SH AH0 N +CONJUNCTIONS K AH0 N JH AH1 NG K SH AH0 N Z +CONJUNCTIVA K AA2 N JH AH0 NG K T AY1 V AH0 +CONJURE K AA1 N JH ER0 +CONJURED K AA1 N JH ER0 D +CONJURER K AA1 N JH AH0 R AH2 R +CONJURES K AA1 N JH ER0 Z +CONJURING K AA1 N JH ER0 IH0 NG +CONJUROR K AA1 N JH ER0 ER0 +CONK K AA1 NG K +CONKEL K AA1 NG K AH0 L +CONKEY K AA1 N K IY0 +CONKIN K AA1 NG K IH0 N +CONKLE K AA1 NG K AH0 L +CONKLIN K AA1 NG K L IH0 N +CONKLING K AA1 NG K L IH0 NG +CONKRIGHT K AA1 NG K R AY2 T +CONLAN K AA1 N L AH0 N +CONLEE K AA1 N L IY0 +CONLEY K AA1 N L IY0 +CONLIN K AA1 N L IH0 N +CONLON K AA1 N L AH0 N +CONLOW K AA1 N L OW0 +CONLY K AA1 N L IY0 +CONN K AA1 N +CONN. K AA1 N +CONN.(1) K AH0 N EH1 T AH0 K AH0 T +CONNALLY K AA1 N AH0 L IY0 +CONNALLY'S K AA1 N AH0 L IY0 Z +CONNAN K AA1 N AH0 N +CONNAUGHT K AA1 N AO0 T +CONNAUGHT'S K AA1 N AO0 T S +CONNAUGHTON K AA1 N AO0 T AA0 N +CONNAWAY K AA1 N AH0 W EY2 +CONNECT K AH0 N EH1 K T +CONNECTED K AH0 N EH1 K T IH0 D +CONNECTER K AH0 N EH1 K T ER0 +CONNECTICUT K AH0 N EH1 T AH0 K AH0 T +CONNECTICUT'S K AH0 N EH1 T AH0 K AH0 T S +CONNECTING K AH0 N EH1 K T IH0 NG +CONNECTION K AH0 N EH1 K SH AH0 N +CONNECTIONS K AH0 N EH1 K SH AH0 N Z +CONNECTIVE K AH0 N EH1 K T IH0 V +CONNECTIVITY K AH0 N EH0 K T IH1 V IH0 T IY0 +CONNECTOR K AH0 N EH1 K T ER0 +CONNECTORS K AH0 N EH1 K T ER0 Z +CONNECTS K AH0 N EH1 K T S +CONNED K AA1 N D +CONNEELY K AH0 N IY1 L IY0 +CONNELL K AA1 N AH0 L +CONNELLEY K AA1 N IH0 L IY0 +CONNELLY K AA1 N AH0 L IY0 +CONNELLY'S K AA1 N AH0 L IY0 Z +CONNELY K AA1 N L IY0 +CONNER K AA1 N ER0 +CONNER'S K AA1 N ER0 Z +CONNERLY K AA1 N ER0 L IY0 +CONNERS K AA1 N ER0 Z +CONNERY K AA1 N ER0 IY0 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R AH0 +COPROCESSOR K OW1 P R AA1 S EH0 S ER0 +COPROCESSORS K OW1 P R AA1 S EH0 S ER0 Z +COPS K AA1 P S +COPSEY K AA1 P S IY0 +COPTIC K AA1 P T IH0 K +COPULATE K AA1 P Y AH0 L EY2 T +COPUS K OW1 P AH0 S +COPY K AA1 P IY0 +COPYCAT K AA1 P IY0 K AE2 T +COPYCATS K AA1 P IY0 K AE2 T S +COPYCATTING K AA1 P IY0 K AE2 T IH0 NG +COPYCODE K AA1 P IY0 K OW2 D +COPYCODES K AA1 P IY0 K OW2 D Z +COPYING K AA1 P IY0 IH0 NG +COPYREADER K AA1 P IY0 R IY2 D ER0 +COPYREADERS K AA1 P IY0 R IY2 D ER0 Z +COPYRIGHT K AA1 P IY0 R AY2 T +COPYRIGHTABLE K AA1 P IY0 R AY2 T AH0 B AH0 L +COPYRIGHTED K AA1 P IY0 R AY2 T IH0 D +COPYRIGHTS K AA1 P IY0 R AY2 T S +COPYTELE K AA1 P IY0 T EH2 L AH0 +COPYWRITE K AA1 P IY0 R AY2 T +COPYWRITED K AA1 P IY0 R AY2 T IH0 D +COPYWRITER K AA1 P IY0 R AY2 T ER0 +COPYWRITERS K AA1 P IY0 R AY2 T ER0 Z +COR K AO1 R +CORA K AO1 R AH0 +CORA'S K AO1 R AH0 Z +CORABELLE K AO1 R AH0 B AH0 L +CORABELLE(1) K AO1 R AH0 B EH2 L +CORACLE K AO1 R AH0 K AH0 L +CORAL K AO1 R AH0 L +CORALIE K AO1 R AH0 L IY0 +CORALINE K AO1 R AH0 L AY2 N +CORALLO K AO2 R AE1 L OW0 +CORALS K AO1 R AH0 L Z +CORAM K AO1 R AE2 M +CORATH K AO1 R AE1 TH +CORAZON K AO1 R AH0 Z OW2 N +CORBAN K AO1 R B AH0 N +CORBEIL K AO1 R B AY2 L +CORBEL K AO1 R B AH0 L +CORBELL K AO1 R B EH0 L +CORBELLED K AO1 R B AH0 L D +CORBELLO K ER0 B EH1 L OW0 +CORBET K AO1 R B IH0 T +CORBETT K AO1 R B IH0 T +CORBIN K AO1 R B IH0 N +CORBIT K AO1 R B IH0 T +CORBITT K AO1 R B IH0 T +CORBO K AO1 R B OW0 +CORBRIDGE K AO1 R B R IH0 JH +CORBU K AO2 R B UW1 +CORBUSIER K AO2 R B Y UW1 S Y ER0 +CORBY K AO1 R B IY0 +CORCAP K AO1 R K AE2 P +CORCORAN K AO1 R K ER0 AH0 N +CORD K AO1 R D +CORDA K AO1 R D AH0 +CORDAGE K AO1 R D AH0 JH +CORDARO K ER0 D AA1 R OW0 +CORDASCO K ER0 D AA1 S K OW0 +CORDAY K AO1 R D EY2 +CORDED K AO1 R D AH0 D +CORDEIRO K ER0 D EH1 R OW0 +CORDELIA K AO2 R D IY1 L IY2 AH0 +CORDELL K AO2 R D EH1 L +CORDER K AO1 R D ER0 +CORDERO K ER0 D EH1 R OW0 +CORDES K AO1 R D Z +CORDESMAN K AO1 R D AH0 S M AH0 N +CORDIAL K AO1 R JH AH0 L +CORDIALLY K AO1 R JH AH0 L IY0 +CORDIALS K AO1 R JH AH0 L Z +CORDIANT K AO1 R D IY0 AH0 N T +CORDIANT'S K AO1 R D IY0 AH0 N T S +CORDIE K AO1 R D IY0 +CORDIER K AO1 R D IY0 ER0 +CORDILL K AO1 R D AH0 L +CORDING K AO1 R D IH0 NG +CORDIS K AO1 R D IH0 S +CORDLE K AO1 R D AH0 L +CORDLESS K AO1 R D L AH0 S +CORDNER K AO1 R D N ER0 +CORDOBA K AO2 R D OW1 B AH0 +CORDOBA'S K AO2 R D OW1 B AH0 Z +CORDOBAS K AO2 R D OW1 B AH0 Z +CORDON K AO1 R D AH0 N +CORDONE K AO1 R D AH0 N +CORDONED K AO1 R D AH0 N D +CORDOVA K AO2 R D OW1 V AH0 +CORDOVER K AO1 R D OW2 V ER0 +CORDOVEZ K AO2 R D OW1 V EH0 Z +CORDRAY K AO1 R D R EY2 +CORDREY K AO1 R D R IY0 +CORDRY K AO1 R D ER0 IY0 +CORDS K AO1 R D Z +CORDTS K AO1 R D T S +CORDUROY K AO1 R D ER0 OY2 +CORDY K AO1 R D IY0 +CORE K AO1 R +COREA K AO0 R IY1 AH0 +COREL K AO2 R EH1 L +CORELL K AO2 R EH1 L +CORELLA K ER0 EH1 L AH0 +COREN K AO1 R AH0 N +CORES K AO1 R Z +CORESPONDENT K AO2 R AH0 S P AA1 N D AH0 N T +CORESTATE K AO1 R S T EY2 T +CORESTATES K AO1 R S T EY2 T S +CORESTATES' K AO1 R AH0 S T EY2 T S +CORETECH K AO1 R T EH2 K +CORETTA K AO0 R EH1 T AH0 +CORETTE K AO1 R EH1 T +COREXIT K AO0 R EH1 K S IH0 T S +COREY K AO1 R IY0 +CORGI K AO1 R G IY0 +CORIA K AO1 R IY0 AH0 +CORIANDER K AO2 R IY0 AE1 N D ER0 +CORIELL K AO1 R IY0 L +CORIER K AO1 R IY0 ER0 +CORIGLIANO K ER0 IY0 G L IY0 AA1 N OW0 +CORINA K AO2 R IY1 N AH0 +CORINN K AO1 R IH0 N +CORINN'S K AO1 R IH0 N Z +CORINNA K AO2 R IH1 N AH0 +CORINNE K ER0 IY1 N +CORINTH K AO1 R AH0 N TH +CORINTHIAN K ER0 IH1 N TH IY0 AH0 N +CORINTHIANS K ER0 IH1 N TH IY0 AH0 N Z +CORINTO K AO2 R IH1 N T OW0 +CORIO K AO1 R IY0 OW0 +CORISA K ER0 IY1 S AH0 +CORISSA K AO2 R IH1 S AH0 +CORK K AO1 R K +CORKEN K AO1 R K AH0 N +CORKER K AO1 R K ER0 +CORKERN K AO1 R K ER0 N +CORKERY K AO1 R K ER0 IY0 +CORKILL K AO1 R K IH2 L +CORKING K AO1 R K IH0 NG +CORKINS K AO1 R K IH0 N Z +CORKRAN K AO1 R K R AH0 N +CORKS K AO1 R K S +CORKSCREW K AO1 R K S K R UW2 +CORKUM K AO1 R K AH0 M +CORKWOOD K AO1 R K W UH2 D +CORKY K AO1 R K IY0 +CORL K AO1 R L +CORLE K AO1 R AH0 L +CORLEONE K AO1 R L IY0 OW2 N +CORLEONE(1) K AO1 R L IY0 OW2 N IY0 +CORLESS K AO1 R L IH0 S +CORLETT K AO1 R L IH0 T +CORLEW K AO1 R L UW0 +CORLEY K AO1 R L IY0 +CORLISS K AO1 R L IH0 S +CORM K AO1 R M +CORMACK K AO1 R M AH0 K +CORMAN K AO1 R M AH0 N +CORMANY K AO1 R M AH0 N IY0 +CORMEN K AO1 R M AH0 N +CORMEN(1) K AO1 R M IH0 N +CORMICAN K AO1 R M IH0 K AH0 N +CORMICK K AO1 R M IH0 K +CORMIER K AO1 R M IY0 ER0 +CORMORANT K AO1 R M ER0 AH0 N T +CORMORANTS K AO1 R M ER0 AH0 N T S +CORN K AO1 R N +CORNA K AO1 R N AH0 +CORNACCHIA K ER0 N AA1 K IY0 AH0 +CORNALL K AO1 R N AH0 L +CORNBLUME K AO1 R N B L UW2 M +CORNBREAD K AO1 R N B R EH2 D +CORNCOB K AO1 R N K AA2 B +CORNCRIB K AO1 R N K R IH2 B +CORNE K AO1 R N +CORNEA K AO1 R N IY0 AH0 +CORNEAL K AO2 R N IY1 L +CORNEAS K AO1 R N IY0 AH0 Z +CORNEJO K ER0 N EY1 Y OW0 +CORNEL K AO1 R N AH0 L +CORNELA K ER0 N EH1 L AH0 +CORNELIA K AO0 R N IY1 L Y AH0 +CORNELIO K ER0 N EH1 L IY0 OW0 +CORNELIOUS K AO1 R N IH0 L IY0 IH0 S +CORNELIOUS(1) K AO0 R N IY1 L Y IH0 S +CORNELISON K ER0 N EH1 L IH0 S AH0 N +CORNELIUS K AO0 R N IY1 L Y AH0 S +CORNELIUSON K AO2 R N IH0 L IY0 UW1 S AH0 N +CORNELL K AO0 R N EH1 L +CORNELL'S K AO0 R N EH1 L Z +CORNELLE K ER0 N EH1 L +CORNER K AO1 R N ER0 +CORNERBACK K AO1 R N ER0 B AE2 K +CORNERED K AO1 R N ER0 D +CORNERING K AO1 R N ER0 IH0 NG +CORNERS K AO1 R N ER0 Z +CORNERSTONE K AO1 R N ER0 S T OW2 N +CORNERSTONES K AO1 R N ER0 S T OW2 N Z +CORNET K AO0 R N EH1 T +CORNETT K AO1 R N IH0 T +CORNETTE K ER0 N EH1 T +CORNETTIST K AO0 R N EH1 T AH0 S T +CORNEY K AO1 R N IY0 +CORNFELD K AO1 R N F EH2 L D +CORNFIELD K AO1 R N F IY2 L D +CORNFIELDS K AO1 R N F IY1 L D Z +CORNFLOWER K AO1 R N F L AW2 ER0 +CORNFLOWERS K AO1 R N F L AW2 ER0 Z +CORNFORTH K AO1 R N F ER0 TH +CORNHUSK K AO1 R N HH AH2 S K +CORNHUSKING K AO1 R N HH AH2 S K IH0 NG +CORNHUSKS K AO1 R N HH AH2 S K S +CORNIA K AO1 R N IY0 AH0 +CORNICHE K AO1 R N IH0 SH +CORNICK K AO1 R N IH0 K +CORNIE K AO1 R N IY0 +CORNIEL K AO2 R N IY1 L +CORNIEL'S K AO2 R N IY1 L Z +CORNING K AO1 R N IH0 NG +CORNING'S K AO1 R N IH0 NG Z +CORNISH K AO1 R N IH0 SH +CORNMAN K AO1 R N M AH0 N +CORNMEAL K AO1 R N M IY2 L +CORNS K AO1 R N Z +CORNSTALK K AO1 R N S T AO2 K +CORNSTALKS K AO1 R N S T AO2 K S +CORNSTARCH K AO1 R N S T AA2 R CH +CORNUCOPIA K AO2 R N AH0 K OW1 P IY0 AH0 +CORNWALL K AO1 R N W AO0 L +CORNWALL'S K AO1 R N W AO0 L Z +CORNWALLIS K AO0 R N W AO1 L AH0 S +CORNWELL K AO1 R N W EH2 L +CORNY K AO1 R N IY0 +COROLLA K ER0 AA1 L AH0 +COROLLARIES K AO1 R AH0 L EH2 R IY0 Z +COROLLARY K AO1 R AH0 L EH2 R IY0 +COROLOGIS K ER0 R AA1 L AH0 JH IH0 S +CORONA K ER0 OW1 N AH0 +CORONA'S K ER0 OW1 N AH0 Z +CORONADO K ER0 OW0 N AA1 D OW0 +CORONAL K ER0 OW1 N AH0 L +CORONARY K AO1 R AH0 N EH2 R IY0 +CORONATION K AO2 R AH0 N EY1 SH AH0 N +CORONER K AO1 R AH0 N ER0 +CORONER'S K AO1 R AH0 N ER0 Z +CORONERS K AO1 R AH0 N ER0 Z +CORONET K AO1 R AH0 N EH1 T +CORONETS K AO1 R AH0 N EH1 T S +CORP K AO1 R P 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K AO1 R P +CORP.(1) K AO1 R P ER0 EY1 SH AH0 N +CORP.'S K AO1 R P S +CORP.'S(1) K AO1 R P ER0 EY1 SH AH0 N Z +CORPENING K AO1 R P AH0 N IH0 NG +CORPORA K AO1 R P ER0 AH0 +CORPORACION K AO2 R P ER0 AA2 S IY0 OW1 N +CORPORAL K AO1 R P ER0 AH0 L +CORPORAL(1) K AO1 R P R AH0 L +CORPORATE K AO1 R P ER0 AH0 T +CORPORATE(1) K AO1 R P R AH0 T +CORPORATES K AO1 R P ER0 AH0 T S +CORPORATEWATCH K AO1 R P R AH0 T W AA2 CH +CORPORATEWIDE K AO1 R P ER0 IH0 T W AY2 D +CORPORATION K AO2 R P ER0 EY1 SH AH0 N +CORPORATION'S K AO2 R P ER0 EY1 SH AH0 N Z +CORPORATIONS K AO2 R P ER0 EY1 SH AH0 N Z +CORPORATIONS' K AO2 R P ER0 EY1 SH AH0 N Z +CORPORATISM K AO1 R P ER0 AH0 T IH2 Z AH0 M +CORPORATIST K AO1 R P ER0 AH0 T IH0 S T +CORPS K AO1 R +CORPS(1) K AO1 R Z +CORPS' K AO1 R Z +CORPSE K AO1 R P S +CORPSES K AO1 R P S AH0 Z +CORPSES(1) K AO1 R P S IH0 Z +CORPSMAN K AO1 R M AH0 N +CORPULANT K AO1 R P Y AH0 L AH0 N T +CORPUS K AO1 R P AH0 S +CORPUS-CHRISTI K AO1 R P AH0 S K R IH1 S T IY0 +CORPUZ K AO1 R P UW0 Z +CORR K AO1 R +CORRADI K ER0 AA1 D IY0 +CORRADINO K ER0 AA0 D IY1 N OW0 +CORRADO K ER0 AA1 D OW0 +CORRAL K ER0 AE1 L +CORRALES K ER0 AA1 L EH0 S +CORRALLED K ER0 AE1 L D +CORRALLING K ER0 AE1 L IH0 NG +CORRAO K AO1 R AW0 +CORREA K AO1 R IY0 AH0 +CORREALE K AO1 R IY0 AH0 L +CORRECT K ER0 EH1 K T +CORRECTED K ER0 EH1 K T AH0 D +CORRECTED(1) K ER0 EH1 K T IH0 D +CORRECTING K ER0 EH1 K T IH0 NG +CORRECTION K ER0 EH1 K SH AH0 N +CORRECTIONAL K ER0 EH1 K SH AH0 N AH0 L +CORRECTIONS K ER0 EH1 K SH AH0 N Z +CORRECTIVE K ER0 EH1 K T IH0 V +CORRECTLY K ER0 EH1 K T L IY0 +CORRECTNESS K ER0 EH1 K T N AH0 S +CORRECTS K ER0 EH1 K T S +CORREGIDOR K ER0 EH1 G AH0 D AO0 R +CORREIA K ER0 EY1 IY0 AH0 +CORREIRA K ER0 EH1 R AH0 +CORRELATE K AO1 R AH0 L EY2 T +CORRELATE(1) K AO1 R AH0 L AH0 T +CORRELATED K AO1 R AH0 L EY2 T AH0 D +CORRELATES K AO1 R AH0 L AH0 T S +CORRELATES(1) K AO1 R AH0 L EY0 T S +CORRELATING K AO1 R AH0 L EY0 T IH0 NG +CORRELATION K AO2 R AH0 L EY1 SH AH0 N +CORRELATIONS K AO2 R AH0 L EY1 SH AH0 N Z +CORRELL K ER0 EY1 L +CORRENE K AO1 R IY0 N +CORRENTE K ER0 EH1 N T IY0 +CORRENTI K ER0 EH1 N T IY0 +CORRESPOND K AO2 R AH0 S P AA1 N D +CORRESPONDED K AO2 R AH0 S P AA1 N D IH0 D +CORRESPONDENCE K AO2 R AH0 S P AA1 N D AH0 N S +CORRESPONDENT K AO2 R AH0 S P AA1 N D AH0 N T +CORRESPONDENTS K AO2 R AH0 S P AA1 N D AH0 N T S +CORRESPONDENTS' K AO2 R AH0 S P AA1 N D AH0 N T S +CORRESPONDING K AO2 R AH0 S P AA1 N D IH0 NG +CORRESPONDINGLY K AO2 R AH0 S P AA1 N D IH0 NG L IY0 +CORRESPONDS K AO2 R AH0 S P AA1 N D Z +CORRIB K AO1 R IH0 B +CORRICK K AO1 R IH0 K +CORRIDOR K AO1 R AH0 D ER0 +CORRIDOR(1) K AO1 R IH0 D ER0 +CORRIDORS K AO1 R IH0 D ER0 Z +CORRIDORS(1) K AO1 R AH0 D ER0 Z +CORRIE K AO1 R IY0 +CORRIERE K AO2 R Y EH1 R +CORRIGAN K AO1 R IH0 G AH0 N +CORRIGAN'S K AO1 R IH0 G AH0 N Z +CORRIGIBLE K AO1 R AH0 JH AH0 B AH0 L +CORRIHER K AO1 R IH0 HH ER0 +CORRIN K AO1 R IH0 N +CORRINA K ER0 IY1 N AH0 +CORRINGTON K AO1 R IH0 NG T AH0 N +CORRIVEAU K AO1 R IH0 V OW0 +CORROBORATE K ER0 AA1 B ER0 EY2 T +CORROBORATED K ER0 AA1 B ER0 EY2 T IH0 D +CORROBORATES K ER0 AO1 B ER0 EY2 T S +CORROBORATING K ER0 AA1 B ER0 EY2 T IH0 NG +CORROBORATION K ER0 AO2 B ER0 EY1 SH AH0 N +CORROBORATIVE K ER0 AA1 B ER0 AH0 T IH2 V +CORROBORATIVE(1) K ER0 AA1 B R AH0 T IH2 V +CORRODE K ER0 OW1 D +CORRODED K ER0 OW1 D IH0 D +CORRODES K ER0 OW1 D Z +CORRON K ER0 AO1 N +CORROON K AO0 R UW1 N +CORROSION K ER0 OW1 ZH AH0 N +CORROSIVE K ER0 OW1 S IH0 V +CORROW K AO1 R OW0 +CORRUGATE K AO1 R AH0 G EY2 T +CORRUGATED K AO1 R AH0 G EY2 T AH0 D +CORRUGATED(1) K AO1 R AH0 G EY2 T IH0 D +CORRUPT K ER0 AH1 P T +CORRUPTED K ER0 AH1 P T IH0 D +CORRUPTIBLE K ER0 AH1 P T IH0 B AH0 L +CORRUPTING K ER0 AH1 P T IH0 NG +CORRUPTION K ER0 AH1 P SH AH0 N +CORRUPTIONS K ER0 AH1 P SH AH0 N Z +CORRUPTIVE K ER0 AH1 P T IH0 V +CORRUPTLY K ER0 AH1 P T L IY0 +CORRUPTS K ER0 AH1 P T S +CORRY K AO1 R IY0 +CORSA K AO1 S AH0 +CORSAGE K AO0 R S AA1 ZH +CORSAIR K AO1 R S EH0 R +CORSARO K ER0 S AA1 R OW0 +CORSE K AO1 R S +CORSELLO K ER0 S EH1 L OW0 +CORSENTINO K ER0 S EH0 N T IY1 N OW0 +CORSER K AO1 R S ER0 +CORSET K AO1 R S AH0 T +CORSETTI K ER0 S EH1 T IY0 +CORSI K AO1 R S IY0 +CORSICA K AO1 R S IH0 K AH0 +CORSICAN K AO1 R S AH0 K AH0 N +CORSICAS K AO1 R S IH0 K AH0 Z +CORSIGLIA K ER0 S IY1 G L IY0 AH0 +CORSINI K ER0 S IY1 N IY0 +CORSO K AO1 R S OW0 +CORSON K AO1 R S AH0 N +CORT K AO1 R T +CORTE K AO1 R T +CORTEGE K AO0 R T EH1 ZH +CORTELAND K AO1 R T L AH0 N D +CORTELYOU K AO1 R T EH0 L Y UW2 +CORTEN K AO1 R T EH0 N +CORTENS K AO1 R T EH0 N Z +CORTENS' K AO1 R T EH0 N Z +CORTER K AO1 R T ER0 +CORTES K AO2 R T EH1 Z +CORTESE K ER0 T EY1 Z IY0 +CORTESI K ER0 T EH1 S IY0 +CORTEX K AO1 R T EH0 K S +CORTEZ K AO0 R T EH1 Z +CORTEZE K AO0 R T EH1 Z +CORTI K AO1 R T IY0 +CORTICAL K AO1 R T AH0 K AH0 L +CORTICOSTEROID K AO2 R T IH0 K OW0 S T EH1 R OY2 D +CORTICOSTEROIDS K AO2 R T IH0 K OW0 S T EH1 R OY2 D Z +CORTIN K AO1 R T IH0 N +CORTINA K ER0 T IY1 N AH0 +CORTINAS K AO1 R T IY0 N AH0 Z +CORTINE K AO0 R T IY1 N +CORTINES K AO0 R T IY1 N Z +CORTISOL K AO1 R T IH0 S AO2 L +CORTISONE K AO1 R T AH0 Z OW2 N +CORTLAND K AO1 R T L AH0 N D +CORTNER K AO1 R T N ER0 +CORTOPASSI K ER0 T OW0 P AA1 S IY0 +CORTRIGHT K AO1 R T R AY0 T +CORUM K AO1 R AH0 M +CORUNDUM K ER0 AH1 N D AH0 M +CORVA K AO1 R V AH0 +CORVALLIS K AO2 R V AE1 L IH0 S +CORVETTE K AO0 R V EH1 T +CORVETTES K AO2 R V EH1 T S +CORVIN K AO1 R V IH0 N +CORVINO K AO2 R V IY1 N OW0 +CORVO K AO1 R V OW0 +CORVUS K AO1 R V AH0 S +CORWIN K AO1 R W IH2 N +CORY K AO1 R IY2 +CORZINE K AO2 R Z IY1 N +CORZO K AO1 R Z OW0 +COS K AO1 S +COSA K OW1 S AA0 +COSATU K AH0 S AA1 T UW2 +COSATU'S K AH0 S AA1 T UW2 Z +COSBY K AO1 Z B IY0 +COSBY'S K AO1 Z B IY0 Z +COSCIA K OW1 S CH AA0 +COSE K OW1 Z +COSELL K OW0 S EH1 L +COSENS K OW1 S AH0 N Z +COSENTINO K OW2 S EH0 N T IY1 N OW0 +COSENZA K OW2 S EH1 N Z AH0 +COSERATZ K OW1 Z ER0 AE2 T S +COSETTE K AH0 S EH1 T +COSEY K OW1 Z IY0 +COSGRIFF K AA1 S G R IH0 F +COSGROVE K AA1 S G R AH0 V +COSI K OW1 S IY0 +COSIC K OW1 S IH0 K +COSIC(1) K OW1 Z IH0 K +COSIC(2) K AA1 S IH0 K +COSIMA K OW0 S IY1 M AH0 +COSIO K OW1 S IY0 OW0 +COSLETT K AA1 S L IH0 T +COSMA K OW1 Z M AH0 +COSMAIR K AO1 Z M EH2 R +COSMAN K AA1 S M AH0 N +COSME K OW1 Z M +COSMETIC K AA0 Z M EH1 T IH0 K +COSMETICALLY K AO2 Z M EH1 T IH0 K L IY0 +COSMETICS K AA0 Z M EH1 T IH0 K S +COSMETOLOGY K AA2 Z M AH0 T AA1 L AH0 JH IY0 +COSMIC K AA1 Z M IH0 K +COSMO K AO1 Z M OW0 +COSMO'S K AA1 Z M OW0 Z +COSMODROME K AO1 Z M AH0 D R OW2 M +COSMOLOGY K AO0 Z M AO1 L AH0 JH IY0 +COSMONAUT K AO1 Z M AH0 N AO2 T +COSMONAUTS K AO1 Z M AH0 N AO2 T S +COSMONAUTS' K AO1 Z M AH0 N AO2 T S +COSMOPOLITAN K AA2 Z M AH0 P AA1 L AH0 T AH0 N +COSMOPULOS K AO2 Z M AH0 P Y UW1 L OW0 S +COSMOS K AA1 Z M OW0 S +COSNER K AA1 S N ER0 +COSPER K AA1 S P ER0 +COSPONSOR K OW2 S P AO1 N S ER0 +COSPONSORS K OW2 S P AO1 N S ER0 Z +COSS K AO1 S +COSSA K AO1 S AH0 +COSSACK K AO1 S AH0 K +COSSACKS K AA1 S AE0 K S +COSSAIRT K AA1 S ER0 T +COSSAT K AA1 S AE0 T +COSSET K AA1 S 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V ER0 IH0 NG Z +COVERS K AH1 V ER0 Z +COVERSTONE K AH1 V ER0 S T OW2 N +COVERT K OW1 V ER0 T +COVERTLY K OW0 V ER1 T L IY0 +COVERUP K AH1 V ER0 AH2 P +COVERUPS K AH1 V ER0 AH2 P S +COVES K OW1 V Z +COVET K AH1 V AH0 T +COVETED K AH1 V AH0 T IH0 D +COVETS K AH1 V AH0 T S +COVEY K AH1 V IY0 +COVIA K OW1 V IY0 AH0 +COVIELLO K OW2 V IY0 EH1 L OW0 +COVILL K AA1 V AH0 L +COVILLE K OW1 V IH2 L +COVIN K OW1 V IH0 N +COVINA K OW0 V IY1 N AH0 +COVINGTON K AH1 V IH0 NG T AH0 N +COVINO K OW0 V IY1 N OW0 +COVITZ K OW1 V IH0 T S +COVY K AH1 V IY0 +COW K AW1 +COW'S K AW1 Z +COWABUNGA K AW2 AH0 B AH1 N G AH0 +COWAN K AW1 AH0 N +COWANS K AW1 AH0 N Z +COWARD K AW1 ER0 D +COWARD'S K AW1 ER0 D Z +COWARDICE K AW1 ER0 D AH0 S +COWARDLY K AW1 ER0 D L IY0 +COWARDS K AW1 ER0 D Z +COWART K AW1 AA0 R T +COWBELL K AW1 B EH2 L +COWBELLS K AW1 B EH2 L Z +COWBOY K AW1 B OY2 +COWBOY'S K AW1 B OY2 Z +COWBOYS K AW1 B OY2 Z +COWBOYS' K AW1 B OY2 Z +COWDEN K AW1 D AH0 N +COWDERY K AW1 D ER0 IY0 +COWDREY K AW1 D R IY0 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N +COXWELL K AA1 K S W EH2 L +COY K OY1 +COYE K OY1 +COYER K OY1 ER0 +COYKENDALL K OY0 K EH1 N D AH0 L +COYLE K OY1 L +COYLY K OY1 L IY0 +COYM K OY1 M +COYNE K OY1 N +COYNER K OY1 N ER0 +COYOTE K AY0 OW1 T IY0 +COYOTE(1) K AY1 OW0 T +COYOTES K AY0 OW1 T IY0 S +COYOTES(1) K AY1 OW0 T S +COZ K AA1 Z +COZAD K OW1 Z AH0 D +COZART K AA1 Z AA0 R T +COZBY K AA1 Z B IY0 +COZIER K OW1 Z IY0 ER0 +COZINE K OW0 Z IY1 N IY0 +COZINESS K OW1 Z IY0 N AH0 S +COZMAN K OW1 Z M AH0 N +COZY K OW1 Z IY0 +COZYING K OW1 Z IY0 IH0 NG +COZZA K OW1 T S AH0 +COZZENS K AA1 Z AH0 N Z +COZZI K OW1 T S IY0 +COZZOLINO K OW0 T S OW0 L IY1 N OW0 +CPS S IY1 P IY2 EH1 S +CPU S IY2 P IY2 Y UW1 +CR. K R EH1 S AH0 N T +CRAB K R AE1 B +CRABB K R AE1 B +CRABBE K R AE1 B +CRABBED K R AE1 B D +CRABBS K R AE1 B Z +CRABBY K R AE1 B IY0 +CRABEATER K R AE1 B IY2 T ER0 +CRABILL K R AE1 B AH0 L +CRABLE K R EY1 B AH0 L +CRABMEAT K R AE1 B M IY2 T +CRABS K R AE1 B Z +CRABTREE K R AE1 B T R IY2 +CRACCHIOLO K R AA0 K IY0 OW1 L OW0 +CRACE K R EY1 S +CRACK K R AE1 K +CRACKDOWN K R AE1 K D AW2 N +CRACKDOWNS K R AE1 K D AW2 N Z +CRACKED K R AE1 K T +CRACKEL K R AE1 K AH0 L +CRACKER K R AE1 K ER0 +CRACKERJACK K R AE1 K ER0 JH AE2 K +CRACKERS K R AE1 K ER0 Z +CRACKHEAD K R AE1 K HH EH2 D +CRACKHEADS K R AE1 K HH EH2 D Z +CRACKING K R AE1 K IH0 NG +CRACKLE K R AE1 K AH0 L +CRACKLED K R AE1 K AH0 L D +CRACKLES K R AE1 K AH0 L Z +CRACKLING K R AE1 K L IH0 NG +CRACKPOT K R AE1 K P AA2 T +CRACKPOTS K R AE1 K P AA2 T S +CRACKS K R AE1 K S +CRACRAFT K R AA1 K R AE0 F T +CRADDOCK K R AE1 D AH0 K +CRADER K R EY1 D ER0 +CRADIC K R AE1 D IH0 K +CRADLE K R EY1 D AH0 L +CRADLES K R EY1 D AH0 L Z +CRADLING K R EY1 D AH0 L IH0 NG +CRADLING(1) K R EY1 D L IH0 NG +CRADOCK K R AE1 D AH0 K +CRADY K R EY1 D IY0 +CRAFT K R AE1 F T +CRAFT'S K R AE1 F T S +CRAFTED K R AE1 F T IH0 D +CRAFTING K R AE1 F T IH0 NG +CRAFTON K R AE1 F T AH0 N +CRAFTS K R AE1 F T S +CRAFTS(1) K R AE1 F S +CRAFTSMAN K R AE1 F T S M AH0 N +CRAFTSMAN(1) K R AE1 F S M AH0 N +CRAFTSMANSHIP K R AE1 F T S M AH0 N SH IH2 P +CRAFTSMANSHIP(1) K R AE1 F S M AH0 N SH IH2 P +CRAFTSMEN K R AE1 F T S M EH0 N +CRAFTSMEN(1) K R AE1 F S M EH0 N +CRAFTSPEOPLE K R AE1 F T S P IY2 P AH0 L +CRAFTSPEOPLE(1) K R AE1 F S P IY2 P AH0 L +CRAFTY K R AE1 F T IY0 +CRAG K R AE1 G +CRAGER K R EY1 JH ER0 +CRAGG K R AE1 G +CRAGGS K R AE1 G Z +CRAGGY K R AE1 G IY0 +CRAGHEAD K R AE1 G HH EH2 D +CRAGIN K R AE1 JH IH0 N +CRAGLE K R EY1 G AH0 L +CRAGO K R AA1 G OW0 +CRAGS K R AE1 G Z +CRAGUN K R AE1 G AH0 N +CRAIB K R EY1 B +CRAIG K R EY1 G +CRAIG'S K R EY1 G Z +CRAIGHEAD K R EY1 G HH EH2 D +CRAIGIE K R EY1 G IY0 +CRAIGO K R EY1 G OW0 +CRAIGSLIST K R EY1 G Z L IH2 S T +CRAIL K R EY1 L +CRAIN K R EY1 N +CRAIN'S K R EY1 N Z +CRAINE K R EY1 N +CRAKER K R EY1 K ER0 +CRALL K R AO1 L +CRAM K R AE1 M +CRAMBLIT K R AE1 M B L IH0 T +CRAMER K R EY1 M ER0 +CRAMER'S K R EY1 M ER0 Z +CRAMES K R EY1 M Z +CRAMMED K R AE1 M D +CRAMMER K R AE1 M ER0 +CRAMMING K R AE1 M IH0 NG +CRAMP K R AE1 M P +CRAMPED K R AE1 M P T +CRAMPING K R AE1 M P IH0 NG +CRAMPON K R AE1 M P AO0 N +CRAMPONS K R AE1 M P AO0 N Z +CRAMPS K R AE1 M P S +CRAMPTON K R AE1 M P T AH0 N +CRAMS K R AE1 M Z +CRAMTON K R AE1 M T AH0 N +CRANBERRIES K R AE1 N B EH2 R IY0 Z +CRANBERRY K R AE1 N B EH2 R IY0 +CRANCE K R AE1 N S +CRANDALL K R AE1 N D AH0 L +CRANDALL'S K R AE1 N D AH0 L Z +CRANDELL K R AE1 N D AH0 L +CRANE K R EY1 N +CRANE'S K R EY1 N Z +CRANED K R EY1 N D +CRANER K R EY1 N ER0 +CRANES K R EY1 N Z +CRANESBILL K R EY1 N Z B IH2 L +CRANESBILLS K R EY1 N Z B IH2 L Z +CRANEY K R EY1 N IY0 +CRANFIELD K R AE1 N F IY2 L D +CRANFILL K R AE1 N F AH0 L +CRANFORD K R AE1 N F ER0 D +CRANIAL K R EY1 N IY2 AH0 L +CRANIUM K R EY1 N IY2 AH0 M +CRANK K R AE1 NG K +CRANKED K R AE1 NG K T +CRANKING K R AE1 NG K IH0 NG +CRANKS K R AE1 NG K S +CRANKSHAFT K R AE1 NG K SH AE2 F T +CRANKSHAFTS K R AE1 NG K SH AE2 F T S +CRANKY K R AE1 NG K IY0 +CRANLEY K R AE1 N L IY0 +CRANMER K R AE1 N M ER0 +CRANMORE K R AA1 N M AO0 R +CRANNELL K R AE1 N AH0 L +CRANNEY K R AE1 N IY0 +CRANNIES K R AE1 N IY0 Z +CRANNY K R AE1 N IY0 +CRANOR K R EY1 N ER0 +CRANS K R AE1 N Z +CRANSHAW K R AE1 N SH AO2 +CRANSTON K R AE1 N S T AH0 N +CRANSTON'S K R AE1 N S T AH0 N Z +CRAP K R AE1 P +CRAPO K R AA1 P OW2 +CRAPPIE K R AE1 P IY2 +CRAPPS K R AE1 P S +CRAPPY K R AE1 P IY2 +CRAPS K R AE1 P S +CRAPSER K R AE1 P S ER0 +CRAPSHOOT K R AE1 P SH UW2 T +CRARY K ER1 EH0 R IY2 +CRASE K R EY1 Z +CRASH K R AE1 SH +CRASH'S K R AE1 SH IH0 Z +CRASHED K R AE1 SH T +CRASHES K R AE1 SH IH0 Z +CRASHING K R AE1 SH IH0 NG +CRASNER K R AE1 Z N ER0 +CRASNIANSKI K R AE2 S N IY0 AE1 N S K IY0 +CRASS K R AE1 S +CRASSWELLER K R AE1 S W EH2 L ER0 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+CREATES K R IY0 EY1 T S +CREATH K R EH1 TH +CREATING K R IY0 EY1 T IH0 NG +CREATION K R IY0 EY1 SH AH0 N +CREATIONISM K R IY0 EY1 SH AH0 N IH2 Z AH0 M +CREATIONS K R IY0 EY1 SH AH0 N Z +CREATIVE K R IY0 EY1 T IH0 V +CREATIVELY K R IY0 EY1 T IH0 V L IY0 +CREATIVENESS K R IY0 EY1 T IH0 V N AH0 S +CREATIVITY K R IY2 EY0 T IH1 V AH0 T IY0 +CREATOLOGIST K R IY0 EY2 T AO1 L AH0 JH IH0 S T +CREATOLOGISTS K R IY0 EY2 T AO1 L AH0 JH IH0 S T S +CREATOR K R IY0 EY1 T ER0 +CREATORS K R IY0 EY1 T ER0 Z +CREATURE K R IY1 CH ER0 +CREATURES K R IY1 CH ER0 Z +CRECELIUS K R IH0 S IY1 L IY0 IH0 S +CRECHE K R EH1 SH +CRECHES K R EH1 SH AH0 Z +CREDENCE K R IY1 D AH0 N S +CREDENTIAL K R IH0 D EH1 N SH AH0 L +CREDENTIAL(1) K R AH0 D EH1 N SH AH0 L +CREDENTIALED K R AH0 D EH1 N SH AH0 L D +CREDENTIALS K R AH0 D EH1 N SH AH0 L Z +CREDENZA K R AH0 D EH1 N Z AH0 +CREDEUR K R IH0 D ER1 +CREDIBILITY K R EH2 D AH0 B IH1 L IH0 T IY0 +CREDIBLE K R EH1 D AH0 B AH0 L +CREDIBLY K R EH1 D AH0 B L IY0 +CREDIT K R EH1 D AH0 T +CREDIT(1) K R EH1 D IH0 T +CREDIT'S K R EH1 D IH0 T S +CREDITABLE K R EH1 D AH0 T AH0 B AH0 L +CREDITABLY K R EH1 D AH0 T AH0 B L IY0 +CREDITANSTALT K R EH2 D IH1 T AH0 N SH T AO2 L T +CREDITBANK K R EH1 D IH0 T B AE2 NG K +CREDITED K R EH1 D AH0 T AH0 D +CREDITED(1) K R EH1 D IH0 T IH0 D +CREDITHRIFT K R EH2 D IH0 TH R IH1 F T +CREDITING K R EH1 D AH0 T IH0 NG +CREDITO K R EH0 D IY1 T OW0 +CREDITOR K R EH1 D AH0 T ER0 +CREDITOR(1) K R EH1 D IH0 T ER0 +CREDITORS K R EH1 D IH0 T ER0 Z +CREDITORS' K R EH1 D IH0 T ER0 Z +CREDITS K R EH1 D IH0 T S +CREDITWATCH K R EH1 D IH0 T W AA2 CH +CREDITWORTHINESS K R EH1 D IH0 T W ER2 DH IY0 N AH0 S +CREDITWORTHY K R EH1 D IH0 T W ER2 DH IY0 +CREDLE K R EH1 D AH0 L +CREDO K R EY1 D OW0 +CREDO(1) K R IY1 D OW0 +CREDULITY K R IH0 D UW1 L AH0 T IY0 +CREDULOUS K R EH1 JH AH0 L AH0 S +CREE K R IY1 +CREECH K R IY1 CH +CREECY K R IY1 S IY0 +CREED K R IY1 D +CREEDEN K R IY1 D AH0 N +CREEDON K R IY1 D AH0 N +CREEDS K R IY1 D Z +CREEGAN K R IY1 G AH0 N +CREEK K R IY1 K +CREEK'S K R IY1 K S +CREEKMORE K R IY1 K M AO0 R +CREEKMUR K R IY1 K M ER0 +CREEKS K R IY1 K S +CREEL K R IY1 L +CREELMAN K R IY1 L M AH0 N +CREELY K R IY1 L IY0 +CREEP K R IY1 P +CREEPINESS K R IY1 P IY0 N IH0 S +CREEPING K R IY1 P IH0 NG +CREEPS K R IY1 P S +CREEPY K R IY1 P IY0 +CREER K R IH1 R +CREES K R IY1 Z +CREF K R EH1 F +CREF'S K R EH1 F S +CREGAN K R IY1 G AH0 N +CREGAR K R IY1 G ER0 +CREGER K R IY1 JH ER0 +CREGG K R EH1 G +CREGGER K R EH1 G ER0 +CREGO K R EH1 G OW0 +CREHAN K R EH1 HH AH0 N +CREIGHTON K R EY1 T AH0 N +CREKO K R EH1 K OW0 +CRELLIN K R EH1 L IH0 N +CREMATE K R IY1 M EY0 T +CREMATED K R IY1 M EY0 T IH0 D +CREMATION K R IY0 M EY1 SH AH0 N +CREMATORIA K R IY0 M AH0 T AO1 R IY0 AH0 +CREMATORIUM K R IY0 M AH0 T AO1 R IY0 AH0 M +CREME K R IY1 M +CREMEANS K R EH1 M AH0 N Z +CREMEENS K R IH0 M IY1 N Z +CREMER K R IY1 M ER0 +CREMIN K R EH1 M IH0 N +CRENELATE K R EH1 N AH0 L EY2 T +CRENELATED K R EH1 N AH0 L EY2 T AH0 D +CRENSHAW K R EH1 N SH AO2 +CRENWELGE K R EH1 N W IH0 L JH +CREOLE K R IY1 OW0 L +CREOLES K R IY0 OW1 L Z +CREOLIZE K R IY1 OW2 L AY2 Z +CREOLIZED K R IY1 OW2 L AY2 Z D +CREOSOTE K R IY1 AH0 S OW2 T +CREPE K R EY1 P +CREPEAU K R IH0 P OW1 +CREPES K R EY1 P S +CREPS K R EH1 P S +CREPT K R EH1 P T +CREQUE K R EH1 K +CRESAP K R EH1 S AH0 P +CRESAP(1) K R IY1 S AH0 P +CRESCENDO K R IH0 SH EH1 N D OW0 +CRESCENT K R EH1 S AH0 N T +CRESCENTS K R EH1 S AH0 N T S +CRESCENZI K R EH0 S CH EH1 N Z IY0 +CRESCENZO K R EH0 S CH EH1 N Z OW0 +CRESCI K R EH1 S IY0 +CRESCOTT K R EH1 S K AA0 T +CRESON K R EH1 S AH0 N +CRESPI K R EH1 S P IY0 +CRESPIN K R EH1 S P IH0 N +CRESPO K R EH1 S P OW0 +CRESS K R EH1 S +CRESSES K R EH1 S AH0 Z +CRESSES(1) K R EH1 S IH0 Z +CRESSEY K R EH1 S IY0 +CRESSLER K R EH1 S L ER0 +CRESSMAN K R EH1 S M AH0 N +CRESSON K R EH1 S AH0 N +CRESSWELL K R EH1 S W EH2 L +CRESSY K R EH1 S IY0 +CREST K R EH1 S T +CRESTAR K R EH1 S T AA2 R +CRESTED K R EH1 S T IH0 D +CRESTFALLEN K R EH1 S T F AO2 L AH0 N +CRESTING K R EH1 S T IH0 NG +CRESTMONT K R EH1 S T M AA2 N T +CRESTS K R EH1 S T S +CRESWELL K R EH1 S W EH2 L +CRETACEOUS K R IH0 T EY1 SH IH0 S +CRETCHEN K R EH1 CH AH0 N +CRETE K R IY1 T +CRETELLA K R EH0 T EH1 L AH0 +CRETIEN K R IY1 SH Y AH0 N +CRETIN K R IY1 T AH0 N +CRETSINGER K R EH1 T S IH0 N JH ER0 +CREUTZFELDT K R UH1 T S F EH0 L D +CREUTZFELDT(1) K R UH1 T S F EH0 L T +CREVASSE K R AH0 V AE1 S +CREVELING K R EH1 V AH0 L IH0 NG +CREVELING(1) K R EH1 V L IH0 NG +CREVICE K R EH1 V AH0 S +CREVICES K R EH1 V AH0 S IH0 Z +CREVIER K R IY1 V IY0 ER0 +CREVISTON K R EH1 V IH0 S T AA0 N +CREW K R UW1 +CREW'S K R UW1 Z +CREWE K R UW1 +CREWEL K R UW1 AH0 L +CREWES K R UW1 Z +CREWMAN K R UW1 M AH0 N +CREWMEN K R UW1 M IH0 N +CREWS K R UW1 Z +CRIB K R IH1 B +CRIBARI K R IY0 B AA1 R IY0 +CRIBB K R IH1 B +CRIBBAGE K R IH1 B AH0 JH +CRIBBING K R IH1 B IH0 NG +CRIBBS K R IH1 B Z +CRIBS K R IH1 B Z +CRICHLOW K R IH1 K L OW0 +CRICHTON K R IH1 CH T AH0 N +CRICK K R IH1 K +CRICKET K R IH1 K IH0 T +CRICKET'S K R IH1 K IH0 T S +CRICKETS K R IH1 K IH0 T S +CRIDDLE K R IH1 D AH0 L +CRIDER K R AY1 D ER0 +CRIED K R AY1 D +CRIER K R AY1 ER0 +CRIES K R AY1 Z +CRIGER K R AY1 JH ER0 +CRIGGER K R IH1 G ER0 +CRIGLER K R IH1 G L ER0 +CRIHFIELD K R IH1 F IY0 L D +CRILL K R IH1 L +CRILLEY K R IH1 L IY0 +CRILLY K R IH1 L IY0 +CRIM K R IH1 M +CRIME K R AY1 M +CRIME'S K R AY1 M Z +CRIMEA K R AY0 M IY1 AH0 +CRIMEAN K R IH0 M IY1 N +CRIMEAN(1) K R AY2 M IY1 AH0 N +CRIMES K R AY1 M Z +CRIMI K R IY1 M IY0 +CRIMINAL K R IH1 M AH0 N AH0 L +CRIMINAL'S K R IH1 M AH0 N AH0 L Z +CRIMINALIST K R IH1 M AH0 N AH0 L IH0 S T +CRIMINALIST'S K R IH1 M AH0 N AH0 L IH0 S T S +CRIMINALISTICS K R IH2 M AH0 N AH0 L IH1 S T IH0 K S +CRIMINALISTS K R IH1 M AH0 N AH0 L IH0 S T S +CRIMINALITY K R IH2 M AH0 N AE1 L IH0 T IY0 +CRIMINALIZATION K R IH2 M AH0 N AH0 L AH0 Z EY1 SH AH0 N +CRIMINALIZE K R IH1 M AH0 N AH0 L AY2 Z +CRIMINALIZED K R IH1 M AH0 N AH0 L AY2 Z D +CRIMINALIZING K R IH1 M AH0 N AH0 L AY2 Z IH0 NG +CRIMINALLY K R IH1 M AH0 N AH0 L IY0 +CRIMINALS K R IH1 M AH0 N AH0 L Z +CRIMINALS' K R IH1 M AH0 N AH0 L Z +CRIMINOLOGIST K R IH2 M IH0 N AA1 L AH0 JH IH0 S T +CRIMINOLOGISTS K R IH2 M IH0 N AA1 L AH0 JH IH0 S T S +CRIMINOLOGY K R IH2 M IH0 N AA1 L AH0 JH IY0 +CRIMM K R IH1 M +CRIMMINS K R IH1 M IH0 N Z +CRIMP K R IH1 M P +CRIMPED K R IH1 M P T +CRIMPING K R IH1 M P IH0 NG +CRIMPS K R IH1 M P S +CRIMSON K R IH1 M Z AH0 N +CRINER K R AY1 N ER0 +CRINGE K R IH1 N JH +CRINGED K R IH1 N JH D +CRINGES K R IH1 N JH IH0 Z +CRINGING K R IH1 N JH IH0 NG +CRIP K R IH1 P +CRIPE K R AY1 P +CRIPPEN K R IH1 P AH0 N +CRIPPLE K R IH1 P AH0 L +CRIPPLED K R IH1 P AH0 L D +CRIPPLES K R IH1 P AH0 L Z +CRIPPLING K R IH1 P AH0 L IH0 NG +CRIPPLING(1) K R IH1 P L IH0 NG +CRIPPS K R IH1 P S +CRIPS K R IH1 P S +CRIS K R IH1 S +CRISAFI K R IY0 S AA1 F IY0 +CRISAFULLI K R IY0 S AA0 F UW1 L IY0 +CRISANTI K R IH0 S AE1 N T IY0 +CRISCI K R IH1 S IY0 +CRISCIONE K R IY0 S CH OW1 N IY0 +CRISCO K R IY1 S K OW0 +CRISCUOLO K R IY0 S K W OW1 L OW0 +CRISE K R AY1 Z +CRISES K R AY1 S IY0 Z +CRISHMAN K R IH1 SH M AH0 N +CRISHMAN'S K R IH1 SH M AH0 N Z +CRISIS K R AY1 S AH0 S +CRISLER K R IH1 S AH0 L ER0 +CRISLER(1) K R IH1 S L ER0 +CRISLIP K R IH1 S L IH0 P +CRISMAN K R IH1 S M AH0 N +CRISMON K R IH1 Z M AH0 N +CRISOSTOMO K R IY0 S OW0 S T OW1 M OW0 +CRISP K R IH1 S P +CRISPELL K R IH1 S P AH0 L +CRISPEN K R IH1 S P AH0 N +CRISPER K R IH1 S P ER0 +CRISPIN K R IH1 S P IH0 N +CRISPINA K R IY0 S P IY1 N AH0 +CRISPINO K R IY0 S P IY1 N OW0 +CRISPLY K R IH1 S P L IY0 +CRISPNESS K R IH1 S P N AH0 S +CRISPO K R IY1 S P OW0 +CRISPY K R IH1 S P IY0 +CRISS K R IH1 S +CRISS-CROSS K R IH1 S K R AO1 S +CRISS-CROSSED K R IH1 S K R AO1 S T +CRISSCROSS K R IH1 S K R AO2 S +CRISSCROSSED K R IH1 S K R AO2 S T +CRISSCROSSING K R IH1 S K R AO2 S IH0 NG +CRISSEY K R IH1 S IY0 +CRISSINGER K R IH1 S IH0 N JH ER0 +CRISSLOW K R IH1 S L OW0 +CRISSMAN K R IH1 S M AH0 N +CRIST K R IH1 S T +CRISTA K R IH1 S T AH0 +CRISTABEL K R IH1 S T AH0 B EH0 L +CRISTAL K R IH1 S T AH0 L +CRISTIANI K R IH2 S T IY0 AA1 N IY0 +CRISTIANI(1) K R IH2 S CH IY0 AA1 N IY0 +CRISTIANI'S K R IH2 S T IY0 AA1 N IY0 Z +CRISTIANI'S(1) K R IH2 S CH IY0 AA1 N IY0 Z +CRISTIANO K R IY0 S T IY0 AA1 N OW0 +CRISTINA K R IH0 S T IY1 N AH0 +CRISTO K R IH1 S T OW2 +CRISTO'S K R IH1 S T OW2 Z +CRISTOBAL K R IH1 S T AH0 B AH0 L +CRISTOBEL K R IH1 S T AH0 B EH0 L +CRISTOBEL'S K R IH1 S T AH0 B EH0 L Z +CRISWELL K R IH1 S W EH0 L +CRITCHER K R IH1 CH ER0 +CRITCHFIELD K R IH1 CH F IY0 L D +CRITCHLEY K R IH1 CH L IY0 +CRITCHLOW K R IH1 CH L OW0 +CRITELLI K R IH0 T EH1 L IY0 +CRITERIA K R AY0 T IH1 R IY0 AH0 +CRITERION K R AY0 T IH1 R IY0 AH0 N +CRITES K R AY1 T S +CRITIC K R IH1 T IH0 K +CRITIC'S K R IH1 T IH0 K S +CRITICAL K R IH1 T IH0 K AH0 L +CRITICALITY K R IH2 T AH0 K AE1 L AH0 T IY0 +CRITICALLY K R IH1 T IH0 K AH0 L IY0 +CRITICALLY(1) K R IH1 T IH0 K L IY0 +CRITICISM K R IH1 T IH0 S IH2 Z AH0 M +CRITICISMS K R IH1 T IH0 S IH2 Z AH0 M Z +CRITICIZE K R IH1 T IH0 S AY2 Z +CRITICIZED K R IH1 T AH0 S AY2 Z D +CRITICIZES K R IH1 T IH0 S AY2 Z IH0 Z +CRITICIZING K R IH1 T IH0 S AY2 Z IH0 NG +CRITICS K R IH1 T IH0 K S +CRITICS' K R IH1 T IH0 K S +CRITIQUE K R AH0 T IY1 K +CRITIQUE(1) K R IH0 T IY1 K +CRITIQUED K R IH0 T IY1 K T +CRITIQUES K R IH0 T IY1 K S +CRITIQUING K R IH0 T IY1 K IH0 NG +CRITON K R AY1 T AH0 N +CRITSER K R IH1 T S ER0 +CRITTENDEN K R IH0 T EH1 N D AH0 N +CRITTENDON K R IH1 T AH0 N D IH0 N +CRITTER K R IH1 T ER0 +CRITTERS K R IH1 T ER0 Z +CRITZ K R IH1 T S +CRITZER K R IH1 T Z ER0 +CRIVARO K R IH0 V AE1 R OW0 +CRIVELLI K R IH0 V EH1 L IY0 +CRIVELLO K R IH0 V EH1 L OW0 +CRIVEN K R IH1 V AH0 N +CRNKOVICH S ER1 N AH0 V IH2 CH +CRO K R OW1 +CROAK K R OW1 K +CROAKER K R OW1 K ER0 +CROAKING K R OW1 K IH0 NG +CROAT K R OW1 AA2 T +CROAT'S K R OW1 AA2 T S +CROATIA K R OW0 EY1 SH AH0 +CROATIA'S K R OW0 EY1 SH AH0 Z +CROATIAN K R OW0 EY1 SH AH0 N +CROATIAN'S K R OW0 EY1 SH AH0 N Z +CROATIANS K R OW0 EY1 SH AH0 N Z +CROATIANS' K R OW0 EY1 SH AH0 N Z +CROATS K R OW1 AA2 T S +CROC K R AA1 K +CROCCO K R AA1 K OW0 +CROCE K R OW1 CH IY0 +CROCHET K R OW0 SH EY1 +CROCHETED K R OW0 SH EY1 D +CROCHETIERE K R OW2 SH AH0 T IH1 R +CROCHETING K R OW0 SH EY1 IH0 NG +CROCK K R AA1 K +CROCKER K R AA1 K ER0 +CROCKER'S K R AA1 K ER0 Z +CROCKERY K R AA1 K ER0 IY0 +CROCKETT K R AA1 K IH0 T +CROCKFORD K R AA1 K F ER0 D +CROCODILE K R AA1 K AH0 D AY2 L +CROCODILES K R AA1 K AH0 D AY2 L Z +CROCODILIAN K R AA2 K AH0 D IH1 L Y AH0 N +CROCUS K R OW1 K AH0 S +CROCUSES K R OW1 K Y UW0 S IH0 Z +CROFF K R AO1 F +CROFFORD K R AA1 F ER0 D +CROFOOT K R OW1 F UH0 T +CROFT K R AO1 F T +CROFTON K R AA1 F T AH0 N +CROFTS K R AO1 F T S +CROGAN K R OW1 G AH0 N +CROGHAN K R AA1 G AH0 N +CROISSANT K W AA2 S AA1 N T +CROISSANT(1) K R AH0 S AA1 N T +CROISSANTS K W AA2 S AA1 N T S +CROISSANTS(1) K R AH0 S AA1 N T S +CROITZER K R OY1 T S ER0 +CROIX K R OY1 +CROIX'S K R OY1 Z +CROKE K R OW1 K +CROKER K R OW1 K ER0 +CROLEY K R OW1 L IY0 +CROLL K R OW1 L +CROM K R AA1 M +CROMARTIE K R AA1 M AA0 R T IY0 +CROMBIE K R AA1 M B IY0 +CROMER K R OW1 M ER0 +CROMER'S K R OW1 M ER0 Z +CROMIE K R AA1 M IY0 +CROMLEY K R AA1 M L IY0 +CROMPTON K R AA1 M P T AH0 N +CROMWELL K R AA1 M W AH0 L +CROMWELL'S K R AA1 M W IH0 L Z +CRON K R AA1 N +CRONAN K R OW1 N AH0 N +CRONAUER K R AA1 N AW0 R +CRONCE K R AA1 N S +CRONE K R OW1 N +CRONEN K R OW1 N AH0 N +CRONER K R OW1 N ER0 +CRONEY K R OW1 N IY0 +CRONIES K R OW1 N IY0 Z +CRONIN K R OW1 N IH0 N +CRONK K R AA1 NG K +CRONKHITE K R AA1 NG K HH AY2 T +CRONKITE K R AA1 NG K AY2 T +CRONKRIGHT K R AA1 NG K R AY2 T +CRONQUIST K R AA1 N K W IH2 S T +CRONUS K R OW1 N AH0 S +CRONY K R OW1 N IY0 +CRONYISM K R OW1 N IY0 IH2 Z AH0 M +CROOK K R UH1 K +CROOKE K R UH1 K +CROOKED K R UH1 K AH0 D +CROOKED-LEG K R UH1 K AH0 D L EH2 G +CROOKEDNESS K R UH1 K AH0 D N AH0 S +CROOKER K R UH1 K ER0 +CROOKLYN K R UH1 K L IH2 N +CROOKLYN'S K R UH1 K L IH2 N Z +CROOKS K R UH1 K S +CROOKSHANK K R UH1 K SH AE2 NG K +CROOKSHANKS K R UH1 K SH AE2 NG K S +CROOKSTON K R UH1 K S T AH0 N +CROOM K R UW1 M +CROOMS K R UW1 M Z +CROON K R UW1 N +CROONER K R UW1 N ER0 +CROONING K R UW1 N IH0 NG +CROONS K R UW1 N Z +CROP K R AA1 P +CROP'S K R AA1 P S +CROPLAND K R AA1 P L AE2 N D +CROPLEY K R AA1 P L IY0 +CROPP K R AA1 P +CROPPED K R AA1 P T +CROPPER K R AA1 P ER0 +CROPPING K R AA1 P IH0 NG +CROPS K R AA1 P S +CROPSEY K R AA1 P S IY0 +CROQUET K R OW0 K EY1 +CROS K R AO1 S +CROSBEY K R AA1 S B IY0 +CROSBIE K R AO1 Z B IY0 +CROSBY K R AO1 Z B IY0 +CROSBY'S K R AO1 Z B IY0 Z +CROSE K R OW1 Z +CROSHAW K R AA1 SH AO0 +CROSKEY K R AA1 S K IY0 +CROSLAND K R AA1 S L AH0 N D +CROSLEY K R AA1 S L IY0 +CROSLIN K R AA1 S L IH0 N +CROSON K R OW1 S AH0 N +CROSS K R AO1 S +CROSS'S K R AO1 S IH0 Z +CROSS-COUNTRY K R AO1 S K AH2 N T R IY0 +CROSS-POLLINATE K R AO1 S P AA2 L AH0 N EY2 T +CROSS-REFERENCE K R AO1 S R EH2 F ER0 AH0 N S +CROSSAN K R AA1 S AH0 N +CROSSBILL K R AO1 S B IH2 L +CROSSBILLS K R AO1 S B IH2 L Z +CROSSBONES K R AO1 S B OW2 N Z +CROSSBORDER K R AO1 S B AO2 R D ER0 +CROSSBOW K R AO1 S B OW2 +CROSSBOWS K R AO1 S B OW2 Z +CROSSCURRENT K R AO1 S K ER2 AH0 N T +CROSSCURRENTS K R AO1 S K ER2 AH0 N T S +CROSSE K R AA1 S +CROSSED K R AO1 S T +CROSSEN K R AO1 S AH0 N +CROSSER K R AO1 S ER0 +CROSSES K R AO1 S IH0 Z +CROSSETT K R AA1 S IH0 T +CROSSFIELD K R AO1 S F IY2 L D +CROSSFIRE K R AO1 S F AY0 R +CROSSFIRE(1) K R AO1 S F AY2 R +CROSSFIRE'S K R AO1 S F AY0 R Z +CROSSIN K R AA1 S IH0 N +CROSSING K R AO1 S IH0 NG +CROSSINGS K R AO1 S IH0 NG Z +CROSSLAND K R AO1 S L AE2 N D +CROSSLEY K R AA1 S L IY0 +CROSSLIN K R AA1 S L IH0 N +CROSSMAN K R AO1 S M AH0 N +CROSSNINE K R AO1 S N AY2 N +CROSSNO K R OW1 S N OW0 +CROSSON K R AA1 S AH0 N +CROSSOVER K R AO1 S OW2 V ER0 +CROSSPIECE K R AO1 S P IY2 S +CROSSPIECES K R AO1 S P IY2 S AH0 Z +CROSSPIECES(1) K R AO1 S P IY2 S IH0 Z +CROSSROAD K R AO1 S R OW2 D +CROSSROADS K R AO1 S R OW2 D Z +CROSSTALK K R AO1 S T AO1 K +CROSSTOWN K R AO1 S T AW2 N +CROSSVILLE K R AA1 S V IH0 L +CROSSWALK K R AA1 S W AA2 K +CROSSWALKS K R AA1 S W AA2 K S +CROSSWHITE K R AA1 S W AY0 T +CROSSWISE K R AO1 S W AY2 Z +CROSSWORD K R AO1 S W ER2 D +CROSSWORDS K R AO1 S W ER2 D Z +CROSTHWAIT K R AA1 S TH W AH0 T +CROSTHWAITE K R AA1 S TH W AH0 T +CROSTON K R AA1 S T AH0 N +CROSWELL K R AA1 S W EH0 L +CROTCH K R AA1 CH +CROTCHETY K R AA1 CH AH0 T IY0 +CROTEAU K R AH0 T OW1 +CROTHERS K R AH1 DH ER0 Z +CROTONVILLE K R OW1 T AH0 N V IH2 L +CROTTEAU K R AH0 T OW1 +CROTTS K R AA1 T S +CROTTY K R AA1 T IY0 +CROTWELL K R AA1 T W EH2 L +CROTZER K R OW1 T Z ER0 +CROUCH K R AW1 CH +CROUCHED K R AW1 CH T +CROUCHER K R AW1 CH ER0 +CROUCHING K R AW1 CH IH0 NG +CROUGH K R AW1 +CROUNSE K R AW1 N S +CROUP K R UW1 P +CROUSE K R AW1 S +CROUSER K R AW1 S ER0 +CROUT K R AW1 T +CROUTHAMEL K R AW1 TH AH0 M EH0 L +CROVITZ K R OW1 V IH0 T S +CROVITZ'S K R OW1 V IH0 T S IH0 Z +CROVL K R OW1 V AH0 L +CROVLS K R OW1 V AH0 L Z +CROW K R OW1 +CROW'S K R OW1 Z +CROWBAR K R OW1 B AA2 R +CROWBOROUGH K R OW1 B ER0 OW0 +CROWD K R AW1 D +CROWD'S K R AW1 D Z +CROWDED K R AW1 D AH0 D +CROWDED(1) K R AW1 D IH0 D +CROWDEN K R AW1 D AH0 N +CROWDER K R AW1 D ER0 +CROWDING K R AW1 D IH0 NG +CROWDS K R AW1 D Z +CROWE K R OW1 +CROWED K R OW1 D +CROWELL K R OW1 AH0 L +CROWING K R OW1 IH0 NG +CROWKEEPER K R OW1 K IY2 P ER0 +CROWKEEPERS K R OW1 K IY2 P ER0 Z +CROWL K R AW1 L +CROWLE K R AW1 L +CROWLEY K R AW1 L IY0 +CROWLEY'S K R AW1 L IY0 Z +CROWN K R AW1 N +CROWN'S K R AW1 N Z +CROWNE K R AW1 N +CROWNED K R AW1 N D +CROWNER K R AW1 N ER0 +CROWNING K R AW1 N IH0 NG +CROWNLIKE K R AW1 N L AY2 K +CROWNOVER K R AW1 N OW2 V ER0 +CROWNS K R AW1 N Z +CROWNX K R AW1 N EH2 K S +CROWS K R OW1 Z +CROWSON K R AW1 S AH0 N +CROWTHER K R AW1 DH ER0 +CROWTHER'S K R OW1 TH ER0 Z +CROWTHERS K R OW1 TH ER0 Z +CROXTON K R AA1 K S T AH0 N +CROY K R OY1 +CROYLE K R OY1 L +CROZIER K R OW1 ZH ER0 +CRUCE K R UW1 S +CRUCES K R UW1 S IY0 Z +CRUCIAL K R UW1 SH AH0 L +CRUCIALLY K R UW1 SH AH0 L IY0 +CRUCIBLE K R UW1 S AH0 B AH0 L +CRUCIFIED K R UW1 S AH0 F 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AO2 R S EY1 +D'S D IY1 Z +D'SOUZA D IH0 S UW1 Z AH0 +D'SOUZA(1) D IY0 S UW1 Z AH0 +D. D IY1 +D.'S D IY1 Z +D.C. D IY2 S IY1 +D.S D IY1 Z +DA D AA1 +DA(1) D IY1 EY1 +DA'S D IY1 EY1 Z +DAANE D AA1 N +DAARMSTADT D AA1 R M S T AA0 D +DAAS D AA1 S +DAB D AE1 B +DABAH D AE1 B AH0 +DABAH(1) D AH0 B AA1 +DABBING D AE1 B IH0 NG +DABBLE D AE1 B AH0 L +DABBLED D AE1 B AH0 L D +DABBLES D AE1 B AH0 L Z +DABBLING D AE1 B AH0 L IH0 NG +DABBLING(1) D AE1 B L IH0 NG +DABBS D AE1 B Z +DABCHICK D AE1 B CH IH0 K +DABHOL D AE1 B OW0 L +DABKOWSKI D AH0 B K AO1 F S K IY0 +DABNEY D AE1 B N IY0 +DABROWSKI D AH0 B R AO1 F S K IY0 +DAC D AE1 K +DACE D EY1 S +DACEY D EY1 S IY0 +DACHA D AA1 CH AH0 +DACHAU D AE1 K AW0 +DACHSHUND D AA1 K S HH UH2 N D +DACHSHUNDS D AA1 K S HH UH2 N T S +DACIA D EY1 SH IY0 AH0 +DACK D AE1 K +DACOSTA D AA0 K OW1 S T AH0 +DACQUISTO D AE1 K W IH0 S T OW0 +DACRON D AE1 K R AA2 N +DACRUZ D AA1 K R UW0 Z +DACS D AE1 K S +DACTYL D AE1 K T IH0 L +DACUNHA D AH0 K AH1 N HH AH0 +DACUS D AE1 K IH0 S +DACY D EY1 S IY0 +DAD D AE1 D +DAD'S D AE1 D Z +DADA D AA1 D AA2 +DADAMO D AA0 D AA1 M OW0 +DADDARIO D AA0 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D EH0 G N OW1 +DAIGNEAULT D EH0 G N OW1 +DAIGRE D EY1 G ER0 +DAIGREPONT D EY1 G R IH0 P AA0 N T +DAIHATSU D AY2 HH AE1 T S UW0 +DAIICHI D AY2 IY1 CH IY0 +DAIKIN D EY1 K IH0 N +DAIKON D AY1 K AO2 N +DAIL D EY1 L +DAILE D EY1 L +DAILEY D EY1 L IY0 +DAILIES D EY1 L IY0 Z +DAILY D EY1 L IY0 +DAIMLER D EY1 M L ER0 +DAIMLER(1) D EH1 M L ER0 +DAIMLER'S D EY1 M L ER0 Z +DAIMONES D EY1 M OW2 N Z +DAIN D EY1 N +DAINES D EY1 N Z +DAINI D EY1 N IY0 +DAINIPPON D EY2 N IH0 P AA1 N +DAINS D EY1 N Z +DAINTILY D EY1 N T AH0 L IY2 +DAINTY D EY1 N T IY0 +DAIQUIRI D AE1 K ER0 IY0 +DAIRIES D EH1 R IY0 Z +DAIRY D EH1 R IY0 +DAIRYING D EH1 R IY0 IH0 NG +DAIRYMEN D EY1 R IY0 M AH0 N +DAIS D EY1 Z +DAISE D EY1 Z +DAISEY D EY1 S IY0 +DAISHOWA D EY2 SH AW1 AH0 +DAISIES D EY1 Z IY0 Z +DAISY D EY1 Z IY0 +DAISY'S D EY1 Z IY0 Z +DAIWA D EY1 W AH0 +DAIWA'S D EY1 W AH0 Z +DAJUN D EY1 JH AH0 N +DAK D AE1 K +DAK(1) D IY1 EY1 K EY1 +DAKAR D AA0 K AA1 R +DAKE D EY1 K +DAKIN D EY1 K IH0 N +DAKOTA D AH0 K OW1 T AH0 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IY0 +DALILA D AH0 L AY1 L AH0 +DALIS D AE1 L IH0 S +DALKE D EY1 L K +DALKON D AE1 L K AH0 N +DALL D AO1 L +DALLA D AE1 L AH0 +DALLAIRE D AA1 L EH0 R +DALLARA D AE2 L AA1 R AH0 +DALLAS D AE1 L AH0 S +DALLAS' D AE1 L AH0 S +DALLAS'S D AE1 L AH0 S IH0 Z +DALLEY D AE1 L IY0 +DALLHOLD D AO1 L HH OW2 L D +DALLIANCE D AE1 L IY0 AH0 N S +DALLIED D AE1 L IY0 D +DALLMAN D AO1 L M AH0 N +DALLMANN D AO1 L M AH0 N +DALLY D AE1 L IY0 +DALMA D AA1 L M AH0 +DALMAN D AE1 L M AH0 N +DALMATIAN D AE0 L M EY1 SH AH0 N +DALMATIANS D AE0 L M EY1 SH AH0 N Z +DALMO D AO1 L M OW0 +DALO D AA1 L OW0 +DALOIA D AA0 L OW1 Y AH0 +DALOISIO D AA0 L OY1 S IY0 OW0 +DALONZO D AH0 L AA1 N Z OW0 +DALPE D EY1 L P +DALPIAZ D AA0 L P IY1 AA0 Z +DALPORTO D AA0 L P AO1 R T OW0 +DALRYMPLE D AE1 L R IH0 M P AH0 L +DALTO D AA1 L T OW0 +DALTON D AO1 L T AH0 N +DALTON'S D AO1 L T AH0 N Z +DALTONS D AO1 L T AH0 N Z +DALY D EY1 L IY0 +DALZELL D AE1 L Z AH0 L +DALZIEL D AE1 L Z IY2 L +DAM D AE1 M +DAM'S D AE1 M Z +DAMA D AA1 M AH0 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AH1 K S +DELVALLE D EH2 L V AE1 L IY0 +DELVALLE'S D EH2 L V AE1 L IY0 Z +DELVE D EH1 L V +DELVECCHIO D EH2 L V EH1 K IY0 OW0 +DELVED D EH1 L V D +DELVES D EH1 L V Z +DELVIN D EH1 L V IH0 N +DELVING D EH1 L V IH0 NG +DELWIN D EH1 L W IH0 N +DELWIP D EH1 L W IH0 P +DELWYN D EH1 L W IH0 N +DELZELL D EH1 L Z AH0 L +DELZER D EH1 L Z ER0 +DEMAGGIO D IH0 M AA1 JH IY0 OW0 +DEMAGOGIC D EH2 M AH0 G AA1 JH IH0 K +DEMAGOGUE D EH1 M AH0 G AA2 G +DEMAGOGUERY D EH1 M AH0 G AA2 G ER0 IY0 +DEMAGOGUES D EH1 M AH0 G AA2 G Z +DEMAGOGUING D EH1 M AH0 G AA2 G IH0 NG +DEMAGOGY D EH1 M AH0 G AA2 JH IY0 +DEMAIN D IH0 M EY1 N +DEMAIO D IH0 M AA1 IY0 OW0 +DEMAIO(1) D IH0 M AA1 OW0 +DEMAN D IY1 M AH0 N +DEMAND D IH0 M AE1 N D +DEMANDED D IH0 M AE1 N D AH0 D +DEMANDED(1) D IH0 M AE1 N D IH0 D +DEMANDING D IH0 M AE1 N D IH0 NG +DEMANDINGLY D IH0 M AE1 N D IH0 NG L IY0 +DEMANDS D IH0 M AE1 N D Z +DEMAR D IH0 M AA1 R +DEMARAIS D EH1 M ER0 EY0 +DEMARAY D EH1 M ER0 EY0 +DEMARCATION D IY2 M AA0 R K EY1 SH AH0 N 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IY0 +DEMBY D EH1 M B IY0 +DEMCHAK D EH1 M CH AH0 K +DEMEAN D IH0 M IY1 N +DEMEANED D IH0 M IY1 N D +DEMEANING D IH0 M IY1 N IH0 NG +DEMEANOR D IH0 M IY1 N ER0 +DEMEANORS D IH0 M IY1 N ER0 Z +DEMEANOUR D IH0 M IY1 N ER0 +DEMEANOURS D IH0 M IY1 N ER0 Z +DEMEANS D IH0 M IY1 N Z +DEMEL D EH1 M AH0 L +DEMELLO D IH0 M EH1 L OW0 +DEMELO D IH0 M EH1 L OW0 +DEMENT D AH0 M EH1 N T +DEMENTED D IH0 M EH1 N T IH0 D +DEMENTIA D IH0 M EH1 N SH IY0 AH0 +DEMEO D IY1 M IY0 OW0 +DEMEREE D EH1 M ER0 IY0 +DEMERGER D IY0 M ER1 JH ER0 +DEMERIST D IH0 M ER1 IH0 S T +DEMERIST(1) D EH1 M ER0 IH0 S T +DEMERIST'S D IH0 M ER1 IH0 S T S +DEMERIT D IY0 M EH1 R AH0 T +DEMERITS D IY0 M EH1 R AH0 T S +DEMERITT D EH1 M ER0 IH0 T +DEMERS D IY1 M ER0 Z +DEMERSE D EH1 M ER0 S +DEMERY D IH0 M ER1 IY0 +DEMESNE D AH0 M EY1 N +DEMETER D IH0 M IY1 T ER0 +DEMETRE D EH0 M IY1 T ER0 +DEMETRIA D IH0 M EH1 T R IY0 AH0 +DEMETRIO D IH0 M EH1 T R IY0 OW0 +DEMETRIOU D IH0 M EH0 T R IY1 UW0 +DEMETRIUS D IH0 M IY1 T R IY0 AH0 S +DEMEYER D EH1 M AY0 ER0 +DEMI D EH1 M IY0 +DEMI'S D EH1 M IY0 Z +DEMICCO D IH0 M IY1 K OW0 +DEMICHAEL D EH1 M IH0 K EH0 L +DEMICHELE D EH1 M IH0 K AH0 L +DEMICK D EH1 M IH0 K +DEMILIO D IH0 M IY1 L IY0 OW0 +DEMILITARIZATION D IY0 M IH2 L AH0 T ER0 AH0 Z EY1 SH AH0 N +DEMILITARIZE D IY0 M IH1 L AH0 T ER0 AY2 Z +DEMILITARIZED D IY0 M IH1 L AH0 T ER0 AY2 Z D +DEMILITARIZES D IY0 M IH1 L AH0 T ER0 AY2 Z IH0 Z +DEMILITARIZING D IY0 M IH1 L AH0 T ER0 AY2 Z IH0 NG +DEMILLE D IH0 M IY1 L IY0 +DEMILLE(1) D IH0 M IH1 L +DEMILO D IH0 M IH1 L OW0 +DEMILO(1) D IH0 M AY1 L OW0 +DEMING D EH1 M IH0 NG +DEMINT D EY1 M IY0 N T +DEMIRAG D EY2 M IH0 R AA1 JH +DEMIREL D AH0 M IH1 R AH0 L +DEMIRJIAN D IH0 M ER1 JH IY0 AH0 N +DEMISCH D AH0 M IH1 SH +DEMISE D IH0 M AY1 Z +DEMISH D EH1 M IH0 SH +DEMJANJUK D EH0 M Y AA1 N Y UW0 K +DEMJANJUK(1) D EH0 M Y AE1 N Y UW0 K +DEMJANJUK'S D EH0 M Y AA1 N Y UW0 K S +DEMJANJUK'S(1) D EH0 M Y AE1 N Y UW0 K S +DEMKO D EH1 M K OW0 +DEMLER D EH1 M L ER0 +DEMMA D IY1 M AH0 +DEMME D EH1 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IY0 +DEPOSITARY(1) D IH0 P AA1 Z IH0 T EH2 R IY0 +DEPOSITED D AH0 P AA1 Z IH0 T IH0 D +DEPOSITED(1) D IH0 P AA1 Z AH0 T AH0 D +DEPOSITING D AH0 P AA1 Z IH0 T IH0 NG +DEPOSITION D EH2 P AH0 Z IH1 SH AH0 N +DEPOSITIONAL D EH2 P AH0 Z IH1 SH AH0 N AH0 L +DEPOSITIONS D EH2 P AH0 Z IH1 SH AH0 N Z +DEPOSITOR D AH0 P AA1 Z IH0 T ER0 +DEPOSITOR'S D AH0 P AA1 Z IH0 T ER0 Z +DEPOSITORS D AH0 P AA1 Z IH0 T ER0 Z +DEPOSITORS' D IH0 P AA1 Z IH0 T ER0 Z +DEPOSITORY D IH0 P AA1 Z AH0 T AO2 R IY0 +DEPOSITS D AH0 P AA1 Z IH0 T S +DEPOSITS(1) D IH0 P AA1 Z AH0 T S +DEPOT D IY1 P OW0 +DEPOT'S D IY1 P OW0 Z +DEPOTS D IY1 P OW0 Z +DEPOY D EH1 P OY0 +DEPP D EH1 P +DEPPE D EH1 P +DEPPEN D EH1 P AH0 N +DEPRAVATION D EH2 P R AH0 V EY1 SH AH0 N +DEPRAVE D IY0 P R EY1 V +DEPRAVED D IY0 P R EY1 V D +DEPRAVITY D IH0 P R AE1 V AH0 T IY0 +DEPRECATE D EH1 P R AH0 K EY2 T +DEPRECATED D EH1 P R AH0 K EY2 T AH0 D +DEPRECATES D EH1 P R AH0 K EY2 T S +DEPRECATING D EH1 P R AH0 K EY2 T IH0 NG +DEPRECIABLE D IH0 P R IH1 SH AH0 B AH0 L +DEPRECIATE D IH0 P R IY1 SH IY0 EY2 T +DEPRECIATED D IH0 P R IY1 SH IY0 EY2 T IH0 D +DEPRECIATES D IH0 P R IY1 SH IY0 EY2 T S +DEPRECIATING D IH0 P R IY1 SH IY0 EY2 T IH0 NG +DEPRECIATION D IH0 P R IY2 SH IY0 EY1 SH AH0 N +DEPRECIATIONS D IH0 P R IY2 SH IY0 EY1 SH AH0 N Z +DEPREDATION D EH2 P R AH0 D EY1 SH AH0 N +DEPREDATIONS D EH2 P R AH0 D EY1 SH AH0 N Z +DEPREE D IH0 P R IY1 +DEPRENYL D EH1 P R AH0 N IH2 L +DEPRESS D IH0 P R EH1 S +DEPRESSANT D IH0 P R EH1 S AH0 N T +DEPRESSANTS D IH0 P R EH1 S AH0 N T S +DEPRESSED D IH0 P R EH1 S T +DEPRESSES D IH0 P R EH1 S AH0 Z +DEPRESSES(1) D IH0 P R EH1 S IH0 Z +DEPRESSING D IH0 P R EH1 S IH0 NG +DEPRESSINGLY D IH0 P R EH1 S IH0 NG L IY0 +DEPRESSION D IH0 P R EH1 SH AH0 N +DEPRESSIONS D IH0 P R EH1 SH AH0 N Z +DEPRESSIVE D IH0 P R EH1 S IH0 V +DEPRESSURIZE D IH0 P R EH1 SH ER0 AY2 Z +DEPRESSURIZED D IH0 P R EH1 SH ER0 AY2 Z D +DEPRESSURIZES D IH0 P R EH1 SH ER0 AY2 Z IH0 Z +DEPRESSURIZING D IH0 P R EH1 SH ER0 AY2 Z IH0 NG +DEPREY 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D IH0 M IH1 N IH0 SH IH0 NG +DIMINISHMENT D IH0 M IH1 N IH0 SH M AH0 N T +DIMINO D IH0 M IY1 N OW2 +DIMINUTION D IH2 M AH0 N UW1 SH AH0 N +DIMINUTIVE D IH0 M IH1 N Y AH0 T IH0 V +DIMITRI D IH0 M IY1 T R IY0 +DIMITRIOS D IH0 M IY1 T R IY0 OW2 S +DIMITRIUS D IH0 M IY1 T R IY0 AH2 S +DIMITRIUS' D IH0 M IY1 T R IY0 AH2 S +DIMITRIUS'S D IH0 M IY1 T R IY0 AH2 S IH0 S +DIMITROFF D IH1 M IH0 T R AO0 F +DIMITRUK D IH0 M IY1 T R UH2 K +DIMLY D IH1 M L IY0 +DIMMED D IH1 M D +DIMMER D IH1 M ER0 +DIMMERS D IH1 M ER0 Z +DIMMICK D IH1 M IH0 K +DIMMING D IH1 M IH0 NG +DIMMITT D IH1 M IH0 T +DIMOCK D IH1 M AH0 K +DIMON D IH1 M AH0 N +DIMONA D IH0 M OW1 N AA2 +DIMOND D AY1 M AH0 N D +DIMORPHIC D AY0 M AO1 R F IH0 K +DIMORPHISM D AY0 M AO1 R F IH0 Z AH0 M +DIMPERIO D IH0 M P EH1 R IY0 OW2 +DIMPLE D IH1 M P AH0 L +DIMPLED D IH1 M P AH0 L D +DIMPLES D IH1 M P AH0 L Z +DIMRY D IH1 M R IY0 +DIMS D IH1 M Z +DIMSDALE D IH1 M Z D EY2 L +DIMUNITION D IH0 M Y UW0 N IH1 SH AH0 N +DIMURO D IH0 M UH1 R OW2 +DIMUZIO D IH0 M UW1 Z IY0 OW2 +DIN D IH1 N +DINA D IY1 N AH0 +DINAH D AY1 N AH0 +DINAN D IH1 N AH0 N +DINAPOLI D IH0 N AE1 P AH0 L IY2 +DINAR D IH0 N AA1 R +DINARDO D IH0 N AA1 R D OW2 +DINARS D AY1 N ER0 Z +DINARS(1) D IH2 N AA1 R Z +DINATALE D IH0 N AA0 T AA1 L IY2 +DINDA D IH1 N D AH0 +DINE D AY1 N +DINED D AY1 N D +DINEEN D IH0 N IY1 N +DINEHART D AY1 N HH AA2 R T +DINER D AY1 N ER0 +DINERS D AY1 N ER0 Z +DINES D AY1 N Z +DINESH D IH1 N EH0 SH +DING D IH1 NG +DING-DONG D IH1 NG D AO1 NG +DINGEE D IH1 NG G IY0 +DINGEL D IH1 NG G AH0 L +DINGELL D IH1 NG G AH0 L +DINGELL'S D IH1 NG G AH0 L Z +DINGER D IH1 NG ER0 +DINGES D IH1 N JH IH0 Z +DINGESS D IH1 NG G IH0 S +DINGHAM D IH1 NG AH0 M +DINGHY D IH1 NG IY0 +DINGLE D IH1 NG G AH0 L +DINGLEDINE D IH1 NG G AH0 L D AY0 N +DINGLER D IH1 NG G AH0 L ER0 +DINGLER(1) D IH1 NG G L ER0 +DINGLEY D IH1 NG G L IY0 +DINGMAN D IH1 NG M AH0 N +DINGO D IH1 NG G OW0 +DINGS D IH1 NG Z +DINGUS D IH1 NG G IH0 S +DINGWALL D IH1 NG G W AH0 L +DINGY D IH1 N JH IY0 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IY2 Z AH0 Z +DIODATI D IY2 OW0 D AA1 T IY2 +DIODATO D IY2 OW0 D AA1 T OW2 +DIODE D AY1 OW2 D +DIODES D AY1 OW2 D Z +DIOGUARDI D IY0 OW0 G AA1 R D IY2 +DION D AY1 AH0 N +DION(1) D IY1 AO2 N +DIONA D IY0 OW1 N AH0 +DIONE D IY1 AA0 N +DIONISIO D AY2 AH0 N IH1 S IY0 OW2 +DIONNE D IY1 AA0 N +DIONYSIAN D AY2 AH0 N IH1 S IY0 AH0 N +DIONYSIUS D AY2 AH0 N IH1 S IY0 AH0 S +DIOR D IY2 AO1 R +DIORIO D IY0 AO1 R IY0 OW2 +DIORITE D AY1 ER0 AY2 T +DIOS D IY1 OW0 S +DIOS' D IY1 OW0 S +DIOS'S D IY1 OW0 S IH0 Z +DIOXIDE D AY0 AA1 K S AY2 D +DIOXIDES D AY0 AA1 K S AY0 D Z +DIOXIN D AY2 AA1 K S IH0 N +DIOXINS D AY2 AA1 K S IH0 N Z +DIP D IH1 P +DIPALMA D IH0 P AA1 L M AH0 +DIPANJAN D AH0 P AA1 N JH AH2 N +DIPAOLA D IH0 P AA0 OW1 L AH0 +DIPAOLO D IH0 P AA0 OW1 L OW2 +DIPASQUALE D IH0 P AA0 S K W AA1 L IY2 +DIPASQUALE(1) D IY0 P AA0 S K W AA1 L EY2 +DIPERNA D IH0 P EH1 R N AH0 +DIPHTHERIA D IH0 F TH IH1 R IY0 AA0 +DIPHTHONG D IH1 F TH AO2 NG +DIPIAZZA D IH0 P IY0 AA1 T S AA2 +DIPIAZZA(1) D IY0 P IY0 AA1 T S AA2 +DIPIERO D IH0 P IH1 R OW2 +DIPIERRO D IH0 P IH1 R OW2 +DIPIETRO D IH0 P IY1 T R OW2 +DIPINTO D IH0 P IH1 N T OW2 +DIPIRRO D IH0 P IH1 R OW2 +DIPLOMA D IH0 P L OW1 M AA0 +DIPLOMACY D IH0 P L OW1 M AH0 S IY0 +DIPLOMAS D IH0 P L OW1 M AH0 Z +DIPLOMAT D IH1 P L AH0 M AE2 T +DIPLOMAT'S D IH1 P L AH0 M AE2 T S +DIPLOMATIC D IH2 P L AH0 M AE1 T IH0 K +DIPLOMATICALLY D IH2 P L AH0 M AE1 T IH0 K L IY0 +DIPLOMATS D IH1 P L AH0 M AE2 T S +DIPLOMATS' D IH1 P L AH0 M AE2 T S +DIPOLE D AY1 P OW2 L +DIPPED D IH1 P T +DIPPEL D IH1 P AH0 L +DIPPER D IH1 P ER0 +DIPPERS D IH1 P ER0 Z +DIPPING D IH1 P IH0 NG +DIPPLE D IH1 P AH0 L +DIPPOLD D IH1 P OW2 L D +DIPPOLITO D IH0 P OW0 L IY1 T OW2 +DIPPY D IH1 P IY0 +DIPRIMA D IH0 P R IY1 M AH0 +DIPS D IH1 P S +DIPSHIT D IH1 P SH IH2 T +DIPSTICK D IH1 P S T IH2 K +DIRCKS D ER1 K S +DIRE D AY1 R +DIRE(1) D AY1 ER0 +DIRECT D ER0 EH1 K T +DIRECT(1) D AY0 R EH1 K T +DIRECT(2) D IH0 R EH1 K T +DIRECTED D ER0 EH1 K T AH0 D +DIRECTED(1) D ER0 EH1 K T IH0 D +DIRECTED(2) D AY0 R EH1 K T IH0 D +DIRECTED(3) D IH0 R EH1 K T IH0 D +DIRECTING D ER0 EH1 K T IH0 NG +DIRECTING(1) D IY0 R EH1 K T IH0 NG +DIRECTING(2) D AY0 R EH1 K T IH0 NG +DIRECTING(3) D IH0 R EH1 K T IH0 NG +DIRECTION D ER0 EH1 K SH AH0 N +DIRECTION(1) D IY0 R EH1 K SH IH0 N +DIRECTION(2) D AY0 R EH1 K SH IH0 N +DIRECTION(3) D IH0 R EH1 K SH IH0 N +DIRECTIONAL D ER0 EH1 K SH AH0 N AH0 L +DIRECTIONAL(1) D IY0 R EH1 K SH IH0 N AH0 L +DIRECTIONAL(2) D AY0 R EH1 K SH IH0 N AH0 L +DIRECTIONAL(3) D IH0 R EH1 K SH IH0 N AH0 L +DIRECTIONLESS D ER0 EH1 K SH AH0 N L AH0 S +DIRECTIONLESS(1) D IY0 R EH1 K SH IH0 N L AH0 S +DIRECTIONLESS(2) D AY0 R EH1 K SH IH0 N L AH0 S +DIRECTIONLESS(3) D IH0 R EH1 K SH IH0 N L AH0 S +DIRECTIONS D ER0 EH1 K SH AH0 N Z +DIRECTIONS(1) D IY0 R EH1 K SH IH0 N Z +DIRECTIONS(2) D AY0 R EH1 K SH IH0 N Z +DIRECTIONS(3) D IH0 R EH1 K SH IH0 N Z +DIRECTIVE D ER0 EH1 K T IH0 V +DIRECTIVE(1) D IY0 R EH1 K T IH0 V +DIRECTIVE(2) D AY0 R EH1 K T IH0 V +DIRECTIVE(3) D IH0 R EH1 K T IH0 V +DIRECTIVES D AY0 R EH1 K T IH0 V Z +DIRECTIVES(1) D IY0 R EH1 K T IH0 V Z +DIRECTIVES(2) D ER0 EH1 K T IH0 V Z +DIRECTIVES(3) D IH0 R EH1 K T IH0 V Z +DIRECTLY D ER0 EH1 K T L IY0 +DIRECTLY(1) D IY0 R EH1 K L IY0 +DIRECTLY(2) D AY0 R EH1 K L IY0 +DIRECTLY(3) D IH0 R EH1 K L IY0 +DIRECTNESS D ER0 EH1 K T N AH0 S +DIRECTNESS(1) D IY0 R EH1 K N AH0 S +DIRECTNESS(2) D AY0 R EH1 K N AH0 S +DIRECTNESS(3) D IH0 R EH1 K N AH0 S +DIRECTOR D ER0 EH1 K T ER0 +DIRECTOR(1) D AY0 R EH1 K T ER0 +DIRECTOR(2) D IY0 R EH1 K T ER0 +DIRECTOR(3) D IH0 R EH1 K T ER0 +DIRECTOR'S D AY0 R EH1 K T ER0 Z +DIRECTOR'S(1) D ER0 EH1 K T ER0 Z +DIRECTOR'S(2) D IY0 R EH1 K T ER0 Z +DIRECTOR'S(3) D IH0 R EH1 K T ER0 Z +DIRECTORAL D ER0 EH1 K T ER0 AH0 L +DIRECTORATE D ER0 EH1 K T ER0 AH0 T +DIRECTORATE(1) D AY0 R EH1 K T ER0 AH0 T +DIRECTORATE(2) D IY0 R EH1 K T ER0 AH0 T +DIRECTORATE(3) D IH0 R EH1 K T ER0 AH0 T +DIRECTORIAL D ER0 EH0 K T AO1 R IY0 AH0 L +DIRECTORIAL(1) D AY0 R EH0 K T AO1 R IY0 AH0 L +DIRECTORIAL(2) D IY0 R EH0 K T AO1 R IY0 AH0 L +DIRECTORIAL(3) D IH0 R EH0 K T AO1 R IY0 AH0 L +DIRECTORIES D AY0 R EH1 K T ER0 IY0 Z +DIRECTORIES(1) D ER0 EH1 K T ER0 IY0 Z +DIRECTORIES(2) D IY0 R EH1 K T ER0 IY0 Z +DIRECTORIES(3) D IH0 R EH1 K T ER0 IY0 Z +DIRECTORS D ER0 EH1 K T ER0 Z +DIRECTORS(1) D AY0 R EH1 K T ER0 Z +DIRECTORS(2) D IY0 R EH1 K T ER0 Z +DIRECTORS(3) D IH0 R EH1 K T ER0 Z +DIRECTORS' D IH0 R EH1 K T ER0 Z +DIRECTORS'(1) D ER0 EH1 K T ER0 Z +DIRECTORS'(2) D IY0 R EH1 K T ER0 Z +DIRECTORSHIP D ER0 EH1 K T ER0 SH IH2 P +DIRECTORSHIP(1) D AY0 R EH1 K T ER0 SH IH2 P +DIRECTORSHIP(2) D IY0 R EH1 K T ER0 SH IH2 P +DIRECTORSHIP(3) D IH0 R EH1 K T ER0 SH IH2 P +DIRECTORSHIPS D ER0 EH1 K T ER0 SH IH2 P S +DIRECTORSHIPS(1) D AY0 R EH1 K T ER0 SH IH2 P S +DIRECTORSHIPS(2) D IY0 R EH1 K T ER0 SH IH2 P S +DIRECTORSHIPS(3) D IH0 R EH1 K T ER0 SH IH2 P S +DIRECTORY D ER0 EH1 K T ER0 IY0 +DIRECTORY(1) D AY0 R EH1 K T ER0 IY0 +DIRECTORY(2) D IY0 R EH1 K T ER0 IY0 +DIRECTORY(3) D IH0 R EH1 K T ER0 IY0 +DIRECTS D ER0 EH1 K T S +DIRECTS(1) D AY0 R EH1 K T S +DIRECTS(2) D IY0 R EH1 K T S +DIRECTS(3) D IH0 R EH1 K T S +DIRECTV D ER0 EH1 K T IY1 V IY1 +DIRECTV(1) D AY0 R EH1 K T IY1 V IY1 +DIRECTV(2) D IY0 R EH1 K T IY1 V IY1 +DIRECTV(3) D IH0 R EH1 K T IY1 V IY1 +DIRENZO D IH0 R EH1 N Z OW2 +DIREST D AY1 R AH0 S T +DIRGE D ER1 JH +DIRHAMS D ER1 AH0 M Z +DIRICKSON D IH1 R IH2 K S AH0 N +DIRIENZO D IH0 R IY1 N Z OW2 +DIRK D ER1 K +DIRKES D ER1 K S +DIRKS D ER1 K S +DIRKSE D ER1 K S +DIRKSEN D ER1 K S AH0 N +DIRLAM D ER0 L AE1 M +DIROCCO D IH0 R AA1 K OW2 +DIROSA D IH0 R OW1 S AA0 +DIRR D ER1 +DIRT D ER1 T +DIRT'S D ER1 T S +DIRTIER D ER1 T IY0 ER0 +DIRTIEST D ER1 T IY0 AH0 S T +DIRTY D ER1 T IY0 +DIRUSSO D IH0 R UW1 S OW2 +DIS D IH1 S +DISA D IH1 S AH0 +DISABATINO D IH0 S AA0 B AA0 T IY1 N OW0 +DISABATO D IH0 S AA0 B AA1 T OW0 +DISABILITIES D IH0 S AH0 B IH1 L AH0 T IY0 Z +DISABILITIES(1) D IH0 S AH0 B IH1 L IH0 T IY0 Z +DISABILITY D IH2 S AH0 B IH1 L IH0 T IY0 +DISABILITY(1) D IH0 S AH0 B IH1 L IH0 T IY0 Z +DISABLE D IH0 S EY1 B AH0 L +DISABLED D IH0 S EY1 B AH0 L D +DISABLES D IH0 S EY1 B AH0 L Z +DISABLING D IH0 S EY1 B AH0 L IH0 NG +DISABLING(1) D IH2 S EY1 B L IH0 NG +DISABUSE D IH0 S AH0 B Y UW1 S +DISABUSE(1) D IH0 S AH0 B Y UW1 Z +DISABUSED D IH0 S AH0 B Y UW1 Z D +DISABUSES D IH0 S AH0 B Y UW1 S IH0 Z +DISADVANTAGE D IH2 S AH0 D V AE1 N T IH0 JH +DISADVANTAGE(1) D IH2 S AH0 D V AE1 N IH0 JH +DISADVANTAGED D IH0 S AH0 D V AE1 N T IH0 JH D +DISADVANTAGED(1) D IH2 S AH0 D V AE1 N IH0 JH D +DISADVANTAGEOUS D IH2 S AE2 D V AE2 N T EY1 JH AH0 S +DISADVANTAGES D IH2 S AH0 D V AE1 N T IH0 JH IH0 Z +DISADVANTAGES(1) D IH2 S AH0 D V AE1 N IH0 JH Z +DISAFFECT D IH2 S AH0 F EH1 K T +DISAFFECTED D IH2 S AH0 F EH1 K T IH0 D +DISAFFECTION D IH2 S AH0 F EH1 K SH AH0 N +DISAGREE D IH0 S AH0 G R IY1 +DISAGREEABLE D IH2 S AH0 G R IY1 AH0 B AH0 L +DISAGREED D IH0 S AH0 G R IY1 D +DISAGREEING D IH0 S AH0 G R IY1 IH0 NG +DISAGREEMENT D IH0 S AH0 G R IY1 M AH0 N T +DISAGREEMENTS D IH2 S AH0 G R IY1 M AH0 N T S +DISAGREES D IH0 S AH0 G R IY1 Z +DISALLOW D IH2 S AH0 L AW1 +DISALLOWANCE D IH2 S AH0 L AW1 AH0 N S +DISALLOWANCES D IH2 S AH0 L AW1 AH0 N S IH0 Z +DISALLOWED D IH2 S AH0 L AW1 D +DISALLOWING D IH0 S AH0 L AW1 IH0 NG +DISALVO D IH0 S AA1 L V OW2 +DISANO D IH0 S AA1 N OW0 +DISANTI D IH0 S AE1 N T IY2 +DISANTIS D IH0 S AA1 N T IH0 S +DISANTO D IH0 S AE1 N T OW2 +DISAPPEAR D IH2 S AH0 P IH1 R +DISAPPEAR(1) D IH2 S AH0 P IY1 R +DISAPPEARANCE D IH2 S AH0 P IH1 R AH0 N S +DISAPPEARANCE(1) D IH2 S AH0 P IY1 R AH0 N S +DISAPPEARANCES D IH2 S AH0 P IH1 R AH0 N S IH0 Z +DISAPPEARANCES(1) D IH2 S AH0 P IY1 R AH0 N S IH0 Z +DISAPPEARED D IH2 S AH0 P IH1 R D +DISAPPEARED(1) D IH2 S AH0 P IY1 R D +DISAPPEARING D IH2 S AH0 P IH1 R IH0 NG +DISAPPEARING(1) D IH2 S AH0 P IY1 R IH0 NG +DISAPPEARS D IH2 S AH0 P IH1 R Z +DISAPPEARS(1) D IH2 S AH0 P IY1 R Z +DISAPPOINT D IH2 S AH0 P OY1 N T +DISAPPOINTED D IH2 S AH0 P OY1 N T IH0 D +DISAPPOINTED(1) D IH2 S AH0 P OY1 N IH0 D +DISAPPOINTING D IH2 S AH0 P OY1 N T IH0 NG +DISAPPOINTING(1) D IH2 S AH0 P OY1 N IH0 NG +DISAPPOINTINGLY D IH0 S AH0 P OY1 N T IH0 NG L IY0 +DISAPPOINTINGLY(1) D IH0 S AH0 P OY1 N IH0 NG L IY0 +DISAPPOINTMENT D IH2 S AH0 P OY1 N T M AH0 N T +DISAPPOINTMENTS D IH0 S AH0 P OY1 N T M AH0 N T S +DISAPPOINTS D IH2 S AH0 P OY1 N T S +DISAPPROVAL D IH0 S AH0 P R UW1 V AH0 L +DISAPPROVE D IH2 S AH0 P R UW1 V +DISAPPROVED D IH2 S AH0 P R UW1 V D +DISAPPROVES D IH0 S AH0 P R UW1 V Z +DISAPPROVING D IH0 S AH0 P R UW1 V IH0 NG +DISARM D IH0 S AA1 R M +DISARMAMENT D IH0 S AA1 R M AH0 M AH0 N T +DISARMED D IH0 S AA1 R M D +DISARMING D IH0 S AA1 R M IH0 NG +DISARMINGLY D IH0 S AA1 R M IH0 NG L IY0 +DISARRAY D IH2 S ER0 EY1 +DISARRAY(1) D IH2 S AH0 R EY1 +DISASSEMBLE D IH2 S AH0 S EH1 M B AH0 L +DISASSEMBLED D IH2 S AH0 S EH1 M B AH0 L D +DISASSOCIATE D IH2 S AH0 S OW1 SH IY0 EY0 T +DISASSOCIATE(1) D IH2 S AH0 S OW1 S IY0 EY0 T +DISASSOCIATED D IH2 S AH0 S OW1 SH IY0 EY0 T AH0 D +DISASSOCIATED(1) D IH2 S AH0 S OW1 S IY0 EY0 T AH0 D +DISASTER D IH0 Z AE1 S T ER0 +DISASTERS D IH0 Z AE1 S T ER0 Z +DISASTROUS D IH0 Z AE1 S T R AH0 S +DISASTROUSLY D IH0 Z AE1 S T R AH0 S L IY0 +DISAVOW D IH2 S AH0 V AW1 +DISAVOWED D IH2 S AH0 V AW1 D +DISAVOWING D IH0 S AH0 V AW1 IH0 NG +DISBAND D IH0 S B AE1 N D +DISBANDED D IH0 S B AE1 N D IH0 D +DISBANDING D IH0 S B AE1 N D IH0 NG +DISBAR D IH2 S B AA1 R +DISBARMENT D IH2 S B AA1 R M AH0 N T +DISBARRED D IH0 S B AA1 R D +DISBELIEF D IH2 S B IH0 L IY1 F +DISBELIEVE D IH0 S B IH0 L IY1 V +DISBELIEVING D IH0 S B IH0 L IY1 V IH0 NG +DISBRO D IH1 S B R OW0 +DISBROW D IH1 S B R AW0 +DISBURSE D IH0 S B ER1 S +DISBURSED D IH0 S B ER1 S T +DISBURSEMENT D IH0 S B ER1 S M AH0 N T +DISBURSEMENTS D IH0 S B ER1 S M AH0 N T S +DISBURSING D IH0 S B ER1 S IH0 NG +DISC D IH1 S K +DISCARD D IH0 S K AA1 R D +DISCARDED D IH0 S K AA1 R D IH0 D +DISCARDING D IH0 S K AA1 R D IH0 NG +DISCARDS D IH0 S K AA1 R D Z +DISCENZA D IH0 S CH EH1 N Z AA0 +DISCERN D IH0 S ER1 N +DISCERNABLY D IH0 S ER1 N AH0 B L IY0 +DISCERNED D IH0 S ER1 N D +DISCERNIBLE D IH0 S ER1 N AH0 B AH0 L +DISCERNING D IH0 S ER1 N IH0 NG +DISCERNMENT D IH0 S ER1 N M AH0 N T +DISCERNS D IH0 S ER1 N Z +DISCH D IH1 SH +DISCHARGE D IH0 S CH AA1 R JH +DISCHARGE(1) D IH1 S CH AA2 R JH +DISCHARGED D IH0 S CH AA1 R JH D +DISCHARGED(1) D IH1 S CH AA2 R JH D +DISCHARGES D IH0 S CH AA1 R JH AH0 Z +DISCHARGES(1) D IH1 S CH AA2 R JH AH0 Z +DISCHARGING D IH0 S CH AA1 R JH IH0 NG +DISCHARGING(1) D IH1 S CH AA2 R JH IH0 NG +DISCHER D IH1 SH ER0 +DISCHINGER D IH1 SH IH0 N JH ER0 +DISCIPLE D IH0 S AY1 P AH0 L +DISCIPLES D IH0 S AY1 P AH0 L Z +DISCIPLINARIAN D IH2 S IH0 P L IH0 N EH1 R IY0 AH0 N +DISCIPLINARIANS D IH2 S IH0 P L IH0 N EH1 R IY0 AH0 N Z +DISCIPLINARY D IH1 S AH0 P L AH0 N EH2 R IY0 +DISCIPLINE D IH1 S AH0 P L AH0 N +DISCIPLINED D IH1 S AH0 P L AH0 N D +DISCIPLINES D IH1 S AH0 P L AH0 N Z +DISCIPLINING D IH1 S AH0 P L AH0 N IH0 NG +DISCLAIM D IH0 S K L EY1 M +DISCLAIMED D IH0 S K L EY1 M D +DISCLAIMER D IH0 S K L EY1 M ER0 +DISCLAIMERS D IH0 S K L EY1 M ER0 Z +DISCLAIMING D IH0 S K L EY1 M IH0 NG +DISCLAIMS D IH0 S K L EY1 M Z +DISCLAND D IH1 S K L AE2 N D +DISCLOSE D IH0 S K L OW1 Z +DISCLOSED D IH0 S K L OW1 Z D +DISCLOSES D IH0 S K L OW1 Z IH0 Z +DISCLOSING D IH0 S K L OW1 Z IH0 NG +DISCLOSURE D IH0 S K L OW1 ZH ER0 +DISCLOSURES D IH0 S K L OW1 ZH ER0 Z +DISCO D IH1 S K OW0 +DISCOGRAPHY D IH0 S K AO1 G R AH0 F IY0 +DISCOLOR D IH0 S K AH1 L ER0 +DISCOLORATION D IH0 S K AH2 L ER0 EY1 SH AH0 N +DISCOLORATIONS D IH0 S K AH2 L ER0 EY1 SH AH0 N Z +DISCOLORED D IH0 S K AH1 L ER0 D +DISCOLORS D IH0 S K AH1 L ER0 Z +DISCOMBOBULATE D IH2 S K AH0 M B AO1 B Y UW0 L EY0 T +DISCOMBOBULATED D IH2 S K AH0 M B AO1 B Y UW0 L EY0 T AH0 D +DISCOMBOBULATES D IH2 S K AH0 M B AO1 B Y UW0 L EY0 T S +DISCOMBOBULATING D IH2 S K AH0 M B AO1 B Y UW0 L EY0 T IH0 NG +DISCOMFORT D IH0 S K AH1 M F ER0 T +DISCONCERT D IH2 S K AH0 N S ER1 T +DISCONCERTING D IH2 S K AH0 N S ER1 T IH0 NG +DISCONNECT D IH0 S K AH0 N EH1 K T +DISCONNECTED D IH2 S K AH0 N EH1 K T IH0 D +DISCONNECTING D IH2 S K AH0 N EH1 K T IH0 NG +DISCONNECTION D IH2 S K AH0 N EH1 K SH AH0 N +DISCONNECTS D IH0 S K AH0 N EH1 K T S +DISCONTENT D IH0 S K AH0 N T EH1 N T +DISCONTENTED D IH2 S K AH0 N T EH1 N T IH0 D +DISCONTENTEDLY D IH2 S K AH0 N T EH1 N T IH0 D L IY0 +DISCONTENTEDNESS D IH2 S K AH0 N T EH1 N T IH0 D N AH0 S +DISCONTENTS D IH2 S K AH0 N T EH1 N T S +DISCONTINUANCE D IH2 S K AH0 N T IH1 N Y UW0 AH0 N S +DISCONTINUATION D IH2 S K AH0 N T IH2 N Y UW0 EY1 SH AH0 N +DISCONTINUE D IH0 S K AH0 N T IH1 N Y UW0 +DISCONTINUED D IH0 S K AH0 N T IH1 N Y UW0 D +DISCONTINUING D IH0 S K AH0 N T IH1 N Y UW0 IH0 NG +DISCONTINUITY D IH0 S K AA2 N T IH0 N UW1 IH0 T IY0 +DISCORD D IH1 S K AO0 R D +DISCORDANT D IH0 S K AO1 R D AH0 N T +DISCOS D IH1 S K OW0 Z +DISCOTHEQUE D IH1 S K OW0 T EH2 K +DISCOTHEQUES D IH1 S K OW0 T EH2 K S +DISCOUNT D IH0 S K AW1 N T +DISCOUNT(1) D IH1 S K AW0 N T +DISCOUNTABLE D IH1 S K AW2 N T AH0 B AH0 L +DISCOUNTED D IH1 S K AW2 N T IH0 D +DISCOUNTED(1) D IH1 S K AW2 N IH0 D +DISCOUNTER D IH1 S K AW2 N T ER0 +DISCOUNTERS D IH0 S K AW1 N T ER0 Z +DISCOUNTERS(1) D IH1 S K AW2 N ER0 R Z +DISCOUNTING D IH1 S K AW2 N T IH0 NG +DISCOUNTING(1) D IH1 S K AW2 N IH0 NG +DISCOUNTS D IH0 S K AW1 N T S +DISCOUNTS(1) D IH1 S K AW2 N T S +DISCOURAGE D IH0 S K ER1 IH0 JH +DISCOURAGED D IH0 S K ER1 IH0 JH D +DISCOURAGEMENT D IH0 S K ER1 IH0 JH M AH0 N T +DISCOURAGES D IH0 S K ER1 IH0 JH IH0 Z +DISCOURAGING D IH0 S K ER1 IH0 JH IH0 NG +DISCOURSE D IH1 S K AO0 R S +DISCOURSES D IH0 S K AO1 R S IH0 Z +DISCOURSES(1) D IH1 S K AO0 R S IH0 Z +DISCOVER D IH0 S K AH1 V ER0 +DISCOVERABLE D IH0 S K AH1 V ER0 AH0 B AH0 L +DISCOVERABLE(1) D IH0 S K AH1 V R AH0 B AH0 L +DISCOVERED D IH0 S K AH1 V ER0 D +DISCOVERER D IH0 S K AH1 V AH0 R ER0 +DISCOVERERS D IH0 S K AH1 V AH0 R ER0 Z +DISCOVERIES D IH0 S K AH1 V ER0 IY0 Z +DISCOVERING D IH0 S K AH1 V ER0 IH0 NG +DISCOVERS D IH0 S K AH1 V ER0 Z +DISCOVERY D IH0 S K AH1 V ER0 IY0 +DISCOVERY(1) D IH0 S K AH1 V R IY0 +DISCOVERY(2) D IH2 S K AH1 V R IY0 +DISCOVERY'S D IH0 S K AH1 V ER0 IY0 Z +DISCOVERY'S(1) D IH0 S K AH1 V R IY0 Z +DISCREDIT D IH0 S K R EH1 D AH0 T +DISCREDITED D IH0 S K R EH1 D IH0 T IH0 D +DISCREDITING D IH0 S K R EH1 D AH0 T IH0 NG +DISCREDITS D IH0 S K R EH1 D AH0 T S +DISCREET D IH0 S K R IY1 T +DISCREETLY D IH0 S K R IY1 T L IY0 +DISCREPANCIES D IH0 S K R EH1 P AH0 N S IY0 Z +DISCREPANCY D IH0 S K R EH1 P AH0 N S IY0 +DISCRETE D IH0 S K R IY1 T +DISCRETION D IH0 S K R EH1 SH AH0 N +DISCRETIONARY D IH0 S K R EH1 SH AH0 N EH2 R IY0 +DISCRETIONS D IH0 S K R EH1 SH AH0 N Z +DISCRIMINATE D IH0 S K R IH1 M AH0 N EY2 T +DISCRIMINATED D IH0 S K R IH1 M AH0 N EY2 T AH0 D +DISCRIMINATED(1) D IH0 S K R IH1 M AH0 N EY2 T IH0 D +DISCRIMINATES D IH0 S K R IH1 M AH0 N EY2 T S +DISCRIMINATING D IH0 S K R IH1 M AH0 N EY2 T IH0 NG +DISCRIMINATION D IH0 S K R IH2 M AH0 N EY1 SH AH0 N +DISCRIMINATIVE D IH0 S K R IH1 M AH0 N AH0 T IH0 V +DISCRIMINATORY D IH0 S K R IH1 M AH0 N AH0 T AO2 R IY0 +DISCS D IH1 S K S +DISCURSIVE D IH0 S K ER1 S IH0 V +DISCUS D IH1 S K AH0 S +DISCUSS D IH0 S K AH1 S +DISCUSSED D IH0 S K AH1 S T +DISCUSSES D IH0 S K AH1 S AH0 Z +DISCUSSES(1) D IH0 S K AH1 S IH0 Z +DISCUSSING D IH0 S K AH1 S IH0 NG +DISCUSSION D IH0 S K AH1 SH AH0 N +DISCUSSIONS D IH0 S K AH1 SH AH0 N Z +DISDAIN D IH0 S D EY1 N +DISDAINED D IH0 S D EY1 N D +DISDAINFUL D IH0 S D EY1 N F AH0 L +DISDAINING D IH0 S D EY1 N IH0 NG +DISDAINS D IH0 S D EY1 N Z +DISE D AY1 S +DISE(1) D AY1 Z +DISEASE D IH0 Z IY1 Z +DISEASE'S D IH0 Z IY1 Z IH0 Z +DISEASED D IH0 Z IY1 Z D +DISEASES D IH0 Z IY1 Z AH0 Z +DISEASES(1) D IH0 Z IY1 Z IH0 Z +DISEMBARK D IH0 S EH0 M B AA1 R K +DISEMBARKATION D IH0 S EH2 M B AA0 R K EY1 SH AH0 N +DISEMBODIED D IH0 S IH0 B AA1 D IY0 D +DISEMBODY D IH0 S IH0 B AA1 D IY0 +DISENCHANTED D IH0 S IH0 N CH AE1 N T IH0 D +DISENCHANTED(1) D IH0 S IH0 N CH AE1 N IH0 D +DISENCHANTMENT D IH0 S IH0 N CH AE1 N T M AH0 N T +DISENFRANCHISE D IH0 S IH0 N F R AE1 N CH AY2 Z +DISENFRANCHISED D IH0 S IH0 N F R AE1 N CH AY2 Z D +DISENFRANCHISEMENT D IH0 S IH0 N F R AE1 N CH AY2 Z M AH0 N T +DISENGAGE D IH0 S IH0 N G EY1 JH +DISENGAGED D IH0 S IH0 N G EY1 JH D +DISENGAGEMENT D IH0 S IH0 N G EY1 JH M AH0 N T +DISENGAGING D IH0 S IH0 N G EY1 JH IH0 NG +DISENTANGLE D IH2 S AH0 N T AE1 NG G AH0 L +DISEQUILIBRIUM D IH0 S IY2 K W AH0 L IH1 B R IY0 AH0 M +DISESTABLISHMENT D IH0 S IH0 S T AE1 B L IH0 SH M AH0 N T +DISFAVOR D IH0 S F EY1 V ER0 +DISFAVORING D IH0 S F EY1 V ER0 IH0 NG +DISFIGURE D IH0 S F IH1 G Y ER0 +DISFIGURED D IH0 S F IH1 G Y ER0 D +DISFIGUREMENT D IH0 S F IH1 G Y ER0 M EH0 N T +DISFIGURING D IH0 S F IH1 G Y ER0 IH0 NG +DISGORGE D IH0 S G AO1 R JH +DISGORGED D IH0 S G AO1 R JH D +DISGORGEMENT D IH0 S G AO1 R JH M AH0 N T +DISGRACE D IH0 S G R EY1 S +DISGRACED D IH0 S G R EY1 S T +DISGRACEFUL D IH0 S G R EY1 S F AH0 L +DISGRUNTLED D IH0 S G R AH1 N T AH0 L D +DISGRUNTLED(1) D IH0 S G R AH1 N AH0 L D +DISGRUNTLEMENT D IH0 S G R AH1 N T AH0 L M AH0 N T +DISGRUNTLING D IH0 S G R AH1 N T AH0 L IH0 NG +DISGRUNTLING(1) D IH0 S G R AH1 N T L IH0 NG +DISGUISE D IH0 S G AY1 Z +DISGUISED D IH0 S G AY1 Z D +DISGUISES D IH0 S G AY1 Z IH0 Z +DISGUISING D IH0 S G AY1 Z IH0 NG +DISGUST D IH0 S G AH1 S T +DISGUSTED D IH0 S G AH1 S T AH0 D +DISGUSTED(1) D IH0 S G AH1 S T IH0 D +DISGUSTING D IH0 S G AH1 S T IH0 NG +DISGUSTS D IH0 S G AH1 S T S +DISH D IH1 SH +DISHARMONY D IH0 S HH AA1 R M AH0 N IY0 +DISHAROON D IH0 SH ER0 UW1 N +DISHAW D IH1 SH AO2 +DISHEARTENED D IH0 S HH AA1 R T AH0 N D +DISHEARTENING D IH0 S HH AA1 R T AH0 N IH0 NG +DISHEARTENING(1) D IH2 S HH AA1 R T N IH0 NG +DISHED D IH1 SH T +DISHER D IH1 SH ER0 +DISHES D IH1 SH AH0 Z +DISHES(1) D IH1 SH IH0 Z +DISHEVEL D IH0 SH EH1 V AH0 L +DISHEVELED D IH0 SH EH1 V AH0 L D +DISHING D IH1 SH IH0 NG +DISHMAN D IH1 SH M AH0 N +DISHNER D IH1 SH N ER0 +DISHON D IH1 S AH0 N +DISHONEST D IH0 S AA1 N AH0 S T +DISHONESTLY D 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D IH0 S K EH1 T +DISKETTES D IH0 S K EH1 T S +DISKIN D IH1 S K IH0 N +DISKLESS D IH1 S K L AH0 S +DISKS D IH1 S K S +DISLIKE D IH0 S L AY1 K +DISLIKED D IH0 S L AY1 K T +DISLIKES D IH0 S L AY1 K S +DISLIKING D IH0 S L AY1 K IH0 NG +DISLOCATE D IH1 S L OW0 K EY0 T +DISLOCATED D IH1 S L OW0 K EY0 T IH0 D +DISLOCATION D IH0 S L OW1 K EY1 SH AH0 N +DISLOCATIONS D IH0 S L OW1 K EY1 SH AH0 N Z +DISLODGE D IH0 S L AA1 JH +DISLODGED D IH0 S L AA1 JH D +DISLODGING D IH0 S L AA1 JH IH0 NG +DISLOYAL D IH0 S L OY1 AH0 L +DISLOYALTY D IH0 S L OY1 AH0 L T IY0 +DISMAL D IH1 Z M AH0 L +DISMALLY D IH1 Z M AH0 L IY0 +DISMANTLE D IH0 S M AE1 N T AH0 L +DISMANTLE(1) D IH0 S M AE1 N AH0 L +DISMANTLED D IH0 S M AE1 N T AH0 L D +DISMANTLED(1) D IH0 S M AE1 N AH0 L D +DISMANTLEMENT D IH0 S M AE1 N T AH0 L M AH0 N T +DISMANTLES D IH0 S M AE1 N T AH0 L Z +DISMANTLING D IH0 S M AE1 N T AH0 L IH0 NG +DISMANTLING(1) D IH0 S M AE1 N AH0 L IH0 NG +DISMANTLING(2) D IH2 S M AE1 N T L IH0 NG +DISMAY D IH0 S M EY1 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IH1 S AH0 N +DISORDER D IH0 S AO1 R D ER0 +DISORDERED D IH0 S AO1 R D ER0 D +DISORDERLY D IH0 S AO1 R D ER0 L IY0 +DISORDERS D IH0 S AO1 R D ER0 Z +DISORGANIZATION D IH0 S AO2 R G AH0 N AH0 Z EY1 SH AH0 N +DISORGANIZE D IH0 S AO1 R G AH0 N AY2 Z +DISORGANIZED D IH0 S AO1 R G AH0 N AY2 Z D +DISORIENT D IH0 S AO1 R IY0 EH2 N T +DISORIENTATION D IH0 S AO2 R IY0 AH0 N T EY1 SH AH0 N +DISORIENTED D IH0 S AO1 R IY0 EH2 N T IH0 D +DISORIENTING D IH0 S AO1 R IY0 EH2 N T IH0 NG +DISOWN D IH0 S OW1 N +DISOWNED D IH0 S OW1 N D +DISPAIR D IH0 S P EH1 R +DISPARAGE D IH0 S P EH1 R IH0 JH +DISPARAGED D IH0 S P EH1 R IH0 JH D +DISPARAGES D IH0 S P EH1 R IH0 JH IH0 Z +DISPARAGING D IH0 S P EH1 R IH0 JH IH0 NG +DISPARAGINGLY D IH0 S P EH1 R IH0 JH IH0 NG L IY0 +DISPARATE D IH1 S P ER0 IH0 T +DISPARATE(1) D IH0 S P EH1 R IH0 T +DISPARITIES D IH0 S P EH1 R AH0 T IY0 Z +DISPARITY D IH0 S P EH1 R AH0 T IY0 +DISPASSIONATE D IH0 S P AE1 SH AH0 N AH0 T +DISPASSIONATELY D IH0 S P AE1 SH AH0 N AH0 T L IY0 +DISPATCH D IH0 S P AE1 CH +DISPATCHED D IH0 S P AE1 CH T +DISPATCHER D IH0 S P AE1 CH ER0 +DISPATCHER(1) D IH1 S P AE2 CH ER0 +DISPATCHER'S D IH0 S P AE1 CH ER0 Z +DISPATCHER'S(1) D IH1 S P AE2 CH ER0 Z +DISPATCHERS D IH0 S P AE1 CH ER0 Z +DISPATCHES D IH0 S P AE1 CH IH0 Z +DISPATCHING D IH0 S P AE1 CH IH0 NG +DISPEL D IH0 S P EH1 L +DISPELL D IH0 S P EH1 L +DISPELLED D IH0 S P EH1 L D +DISPELLING D IH0 S P EH1 L IH0 NG +DISPELS D IH0 S P EH1 L Z +DISPENSABLE D IH0 S P EH1 N S AH0 B AH0 L +DISPENSARY D IH0 S P EH1 N S ER0 IY0 +DISPENSARY(1) D IH1 S P EH0 N S EH2 R IY0 +DISPENSATION D IH2 S P AH0 N S EY1 SH AH0 N +DISPENSE D IH0 S P EH1 N S +DISPENSED D IH0 S P EH1 N S T +DISPENSER D IH0 S P EH1 N S ER0 +DISPENSERS D IH0 S P EH1 N S ER0 Z +DISPENSES D IH0 S P EH1 N S IH0 Z +DISPENSING D IH0 S P EH1 N S IH0 NG +DISPENZA D IH0 S P EH1 N Z AH0 +DISPERSAL D IH0 S P ER1 S AH0 L +DISPERSANT D IH2 S P ER1 S AH0 N T +DISPERSANTS D IH2 S P ER1 S AH0 N T S +DISPERSE D IH0 S P ER1 S +DISPERSED D IH0 S P ER1 S T +DISPERSING D IH0 S P ER1 S IH0 NG +DISPERSION D IH0 S P ER1 ZH AH0 N +DISPERSIVE D IH0 S P ER1 S IH0 V +DISPIRITED D IH0 S P IH1 R AH0 T IH0 D +DISPIRITING D IH0 S P IH1 R IH0 T IH0 NG +DISPLACE D IH0 S P L EY1 S +DISPLACED D IH0 S P L EY1 S T +DISPLACEMENT D IH0 S P L EY1 S M AH0 N T +DISPLACEMENTS D IH0 S P L EY1 S M AH0 N T S +DISPLACES D IH0 S P L EY1 S IH0 Z +DISPLACING D IH0 S P L EY1 S IH0 NG +DISPLAY D IH0 S P L EY1 +DISPLAYED D IH0 S P L EY1 D +DISPLAYING D IH0 S P L EY1 IH0 NG +DISPLAYS D IH0 S P L EY1 Z +DISPLAYWRITE D IH0 S P L EY1 R AY2 T +DISPLAYWRITER D IH0 S P L EY1 R AY2 T ER0 +DISPLEASE D IH0 S P L IY1 Z +DISPLEASED D IH0 S P L IY1 Z D +DISPLEASURE D IH0 S P L EH1 ZH ER0 +DISPOSABLE D IH0 S P OW1 Z AH0 B AH0 L +DISPOSABLES D IH0 S P OW1 Z AH0 B AH0 L Z +DISPOSAL D IH0 S P OW1 Z AH0 L +DISPOSALS D IH0 S P OW1 Z AH0 L Z +DISPOSE D IH0 S P OW1 Z +DISPOSED D IH0 S P OW1 Z D +DISPOSER D IH0 S P OW1 Z ER0 +DISPOSES D IH0 S P OW1 Z IH0 Z +DISPOSING D IH0 S P OW1 Z IH0 NG +DISPOSITION D IH2 S P AH0 Z IH1 SH AH0 N +DISPOSITIONS D IH2 S P AH0 Z IH1 SH AH0 N Z +DISPOSITIVE D IH2 S P AA1 Z AH0 T IH0 V +DISPOSSESS D IH2 S P AH0 Z EH1 S +DISPOSSESSED D IH2 S P AH0 Z EH1 S T +DISPROPORTIONATE D IH2 S P R AH0 P AO1 R SH AH0 N IH0 T +DISPROPORTIONATELY D IH2 S P R AH0 P AO1 R SH AH0 N AH0 T L IY0 +DISPROVE D IH0 S P R UW1 V +DISPROVED D IH0 S P R UW1 V D +DISPROVEN D IH0 S P R UW1 V IH0 N +DISPROVES D IH0 S P R UW1 V Z +DISPUTABLE D IH0 S P Y UW1 T AH0 B AH0 L +DISPUTATION D IH0 S P Y UW1 T EY1 SH AH0 N +DISPUTE D IH0 S P Y UW1 T +DISPUTED D IH0 S P Y UW1 T AH0 D +DISPUTED(1) D IH0 S P Y UW1 T IH0 D +DISPUTES D IH0 S P Y UW1 T S +DISPUTING D IH0 S P Y UW1 T IH0 NG +DISQUALIFICATION D IH0 S K W AA2 L AH0 F AH0 K EY1 SH AH0 N +DISQUALIFIED D IH0 S K W AA1 L AH0 F AY2 D +DISQUALIFIES D IH0 S K W AA1 L AH0 F AY2 Z +DISQUALIFY D IH0 S K W AA1 L AH0 F AY2 +DISQUALIFYING D IH0 S K W AA1 L AH0 F AY2 IH0 NG +DISQUE D IH1 S K +DISQUIET D IH0 S K W AY1 AH0 T +DISQUIETING D IH0 S K W AY1 AH0 T IH0 NG +DISRAELI D IH0 Z R EY1 L IY0 +DISREGARD D IH2 S R IH0 G AA1 R D +DISREGARDED D IH2 S R IH0 G AA1 R D IH0 D +DISREGARDING D IH2 S R IH0 G AA1 R D IH0 NG +DISREGARDS D IH2 S R IH0 G AA1 R D Z +DISREPAIR D IH2 S R IH0 P EH1 R +DISREPUTABLE D IH0 S R EH1 P Y AH0 T AH0 B AH0 L +DISREPUTE D IH2 S R IH0 P Y UW1 T +DISRESPECT D IH2 S R IH0 S P EH1 K T +DISRESPECTED D IH2 S R IH0 S P EH1 K T IH0 D +DISRESPECTFUL D IH2 S R IH0 S P EH1 K T F AH0 L +DISRESPECTING D IH2 S R IH0 S P EH1 K T IH0 NG +DISRESPECTS D IH2 S R IH0 S P EH1 K T S +DISRUPT D IH0 S R AH1 P T +DISRUPTED D IH0 S R AH1 P T IH0 D +DISRUPTING D IH0 S R AH1 P T IH0 NG +DISRUPTION D IH0 S R AH1 P SH AH0 N +DISRUPTIONS D IH0 S R AH1 P SH AH0 N Z +DISRUPTIVE D IH0 S R AH1 P T IH0 V +DISRUPTS D IH0 S R AH1 P T S +DISS D IH1 S +DISSATISFACTION D IH2 S AE0 T IH0 S F AE1 K SH AH0 N +DISSATISFIED D IH0 S AE1 T AH0 S F AY2 D +DISSATISFY D IH0 S AE1 T AH0 S F AY2 +DISSECT D AY0 S EH1 K T +DISSECTED D AY0 S EH1 K T AH0 D +DISSECTING D AY0 S EH1 K T IH0 NG +DISSECTION D AY0 S EH1 K SH AH0 N +DISSECTION(1) D AY1 S EH0 K SH AH0 N +DISSECTIONS D AY0 S EH1 K SH AH0 N Z +DISSECTIONS(1) D AY1 S EH0 K SH AH0 N Z +DISSECTS D AY0 S EH1 K T S +DISSECTS(1) D AY0 S EH1 K S +DISSEMBLE D IH0 S EH1 M B AH0 L +DISSEMBLING D IH0 S EH1 M B L IH0 NG +DISSEMINATE D IH0 S EH1 M AH0 N EY2 T +DISSEMINATED D IH0 S EH1 M AH0 N EY2 T AH0 D +DISSEMINATES D IH0 S EH1 M AH0 N EY2 T S +DISSEMINATING D IH0 S EH1 M AH0 N EY2 T IH0 NG +DISSEMINATION D IH0 S EH2 M AH0 N EY1 SH AH0 N +DISSENSION D IH0 S EH1 N SH AH0 N +DISSENT D IH0 S EH1 N T +DISSENTED D IH0 S EH1 N T IH0 D +DISSENTED(1) D IH0 S EH1 N IH0 D +DISSENTER D IH0 S EH1 N T ER0 +DISSENTERS D IH0 S EH1 N T ER0 Z +DISSENTERS(1) D IH0 S EH1 N ER0 Z +DISSENTING D IH0 S EH1 N T IH0 NG +DISSENTING(1) D IH0 S EH1 N IH0 NG +DISSENTS D IH0 S EH1 N T S +DISSERTATION D IH2 S ER0 T EY1 SH AH0 N +DISSERVICE D IH0 S ER1 V AH0 S +DISSIDENCE D IH1 S AH0 D IH0 N S +DISSIDENT D IH1 S AH0 D IH0 N T +DISSIDENTS D IH1 S AH0 D AH0 N T S +DISSIDENTS' D IH1 S AH0 D AH0 N T S +DISSIMILAR D IH0 S IH1 M AH0 L ER0 +DISSIMILARITY D IH2 S IH2 M AH0 L AE1 R AH0 T IY0 +DISSING D IH1 S IH0 NG +DISSINGER D IH1 S IH0 N JH ER0 +DISSIPATE D IH1 S AH0 P EY2 T +DISSIPATED D IH1 S AH0 P EY2 T IH0 D +DISSIPATES D IH1 S AH0 P EY2 T S +DISSIPATING D IH1 S AH0 P EY2 T IH0 NG +DISSIPATION D IH2 S IH0 P EY1 SH AH0 N +DISSIPATIVE D IH1 S AH0 P EY2 T IH0 V +DISSOCIATE D IH0 S OW1 S IY0 EY0 T +DISSOCIATION D IH0 S OW2 S IY0 EY1 SH AH0 N +DISSOLUTION D IH2 S AH0 L UW1 SH AH0 N +DISSOLVE D IH0 Z AA1 L V +DISSOLVED D IH0 Z AA1 L V D +DISSOLVER D IH0 Z AA1 L V ER0 +DISSOLVERS D IH0 Z AA1 L V ER0 Z +DISSOLVES D IH0 Z AA1 L V Z +DISSOLVING D IH0 Z AO1 L V IH0 NG +DISSONANCE D IH1 S AH0 N AH0 N S +DISSONANT D IH1 S AH0 N AH0 N T +DISSUADE D IH0 S W EY1 D +DISSUADED D IH0 S W EY1 D IH0 D +DISSYMMETRIC D IH2 S IH0 M EH1 T R IH0 K +DISSYMMETRY D IH0 S IH1 M AH0 T R IY0 +DISTAD D IH1 S T AH0 D +DISTAL D IH1 S T AH0 L +DISTANCE D IH1 S T AH0 N S +DISTANCED D IH1 S T AH0 N S T +DISTANCES D IH1 S T AH0 N S AH0 Z +DISTANCES(1) D IH1 S T AH0 N S IH0 Z +DISTANCING D IH1 S T AH0 N S IH0 NG +DISTANT D IH1 S T AH0 N T +DISTASI D IH0 S T AA1 S IY0 +DISTASIO D IH0 S T AA1 S IY0 OW0 +DISTASTE D IH0 S T EY1 S T +DISTASTEFUL D IH0 S T EY1 S T F AH0 L +DISTEFANO D IH0 S T EH0 F AA1 N OW0 +DISTEL D IH1 S T AH0 L +DISTEMPER D IH0 S T EH1 M P ER0 +DISTEND D IH0 S T EH1 N D +DISTENDED D IH0 S T EH1 N D IH0 D +DISTIL D IH0 S T IH1 L +DISTILL D IH0 S T IH1 L +DISTILLATE D IH1 S T AH0 L EY2 T +DISTILLATE(1) D IH1 S T AH0 L AH0 T +DISTILLATES D IH1 S T AH0 L EY2 T S +DISTILLATION D IH2 S T AH0 L EY1 SH AH0 N +DISTILLED D IH0 S T IH1 L D +DISTILLER D IH0 S T IH1 L ER0 +DISTILLER'S D IH0 S T IH1 L ER0 Z +DISTILLERIES D IH0 S T IH1 L ER0 IY0 Z +DISTILLERS D IH0 S T IH1 L ER0 Z +DISTILLERS' D IH0 S T IH1 L ER0 Z +DISTILLERS'S D IH0 S T IH1 L ER0 Z IH0 Z +DISTILLERY D IH0 S T IH1 L ER0 IY0 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IH1 S T R IH0 K T S +DISTRICTING D IH1 S T R IH0 K T IH0 N G +DISTRICTS D IH1 S T R IH0 K T S +DISTRIGAS D IH0 S T R IY1 G AH0 S +DISTRON D IH1 S T R AA2 N +DISTRUST D IH0 S T R AH1 S T +DISTRUSTED D IH0 S T R AH1 S T AH0 D +DISTRUSTED(1) D IH0 S T R AH1 S T IH0 D +DISTRUSTFUL D IH0 S T R AH1 S T F AH0 L +DISTRUSTS D IH0 S T R AH1 S T S +DISTURB D IH0 S T ER1 B +DISTURBANCE D IH0 S T ER1 B AH0 N S +DISTURBANCES D IH0 S T ER1 B AH0 N S AH0 Z +DISTURBANCES(1) D IH0 S T ER1 B AH0 N S IH0 Z +DISTURBED D IH0 S T ER1 B D +DISTURBING D IH0 S T ER1 B IH0 NG +DISTURBINGLY D IH0 S T ER1 B IH0 NG L IY0 +DISTURBS D IH0 S T ER1 B Z +DISUNION D IH0 S Y UW1 N Y AH0 N +DISUNITY D IH0 S Y UW1 N AH0 T IY0 +DISUSE D IH0 S Y UW1 S +DITCH D IH1 CH +DITCHED D IH1 CH T +DITCHES D IH1 CH AH0 Z +DITCHES(1) D IH1 CH IH0 Z +DITCHING D IH1 CH IH0 NG +DITH D IH1 TH +DITHER D IH1 DH ER0 +DITHERING D IH1 DH ER0 IH0 NG +DITHERS D IH1 DH ER0 Z +DITHYRAMB D IH1 TH ER0 AE2 M +DITKA D IH1 T K AH0 +DITKA'S D IH1 T K AH0 Z 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AH0 N AH0 L +DIVISIONS D IH0 V IH1 ZH AH0 N Z +DIVISIONS' D IH0 V IH1 ZH AH0 N Z +DIVISIVE D IH0 V AY1 S IH0 V +DIVISIVENESS D IH0 V AY1 S IH0 V N AH0 S +DIVISON D IH0 V IH1 ZH AH0 N +DIVISON(1) D IH0 V IH1 S AH0 N +DIVISOR D IH0 V AY1 Z ER0 +DIVITA D IH0 V IY1 T AH0 +DIVITO D IH0 V IY1 T OW0 +DIVORCE D IH0 V AO1 R S +DIVORCED D IH0 V AO1 R S T +DIVORCEE D AH0 V AO1 R S IY2 +DIVORCEE(1) D AH0 V AO1 R S EY2 +DIVORCES D IH0 V AO1 R S IH0 Z +DIVORCING D IH0 V AO1 R S IH0 NG +DIVULGE D IH0 V AH1 L JH +DIVULGE(1) D AY0 V AH1 L JH +DIVULGED D IH0 V AH1 L JH D +DIVULGED(1) D AY0 V AH1 L JH D +DIVULGING D IH0 V AH1 L JH IH0 NG +DIVULGING(1) D AY0 V AH1 L JH IH0 NG +DIVVIED D IH1 V IY0 D +DIVVY D IH1 V IY0 +DIWA D IY1 W AH0 +DIWALI D IH0 W AA1 L IY0 +DIX D IH1 K S +DIXIE D IH1 K S IY0 +DIXIELAND D IH1 K S IY0 L AE2 N D +DIXON D IH1 K S AH0 N +DIXON'S D IH1 K S AH0 N Z +DIXONS D IH1 K S AH0 N Z +DIXSON D IH1 K S AH0 N +DIXVILLE D IH1 K S V IH0 L +DIXY D IH1 K S IY0 +DIZON D IH1 Z AH0 N 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B IH0 K +DOBER D OW1 B ER0 +DOBERMAN D OW1 B ER0 M AH0 N +DOBERSTEIN D OW1 B ER0 S T AY0 N +DOBERSTEIN(1) D OW1 B ER0 S T IY0 N +DOBESH D AA1 B IH0 SH +DOBEY D AA1 B IY0 +DOBIAS D OW0 B IY1 AH0 Z +DOBIE D AA1 B IY0 +DOBIES D OW1 B IY0 Z +DOBIS D OW1 B IH0 S +DOBKIN D AA1 B K IH0 N +DOBKINS D AA1 B K IH0 N Z +DOBLE D OW1 B AH0 L +DOBLER D OW1 B AH0 L ER0 +DOBLER(1) D OW1 B L ER0 +DOBMEIER D AA1 B M AY0 ER0 +DOBOJ D OW1 B AO2 JH +DOBOS D OW1 B OW0 Z +DOBOSZ D AA1 B AH0 SH +DOBRANSKY D AH0 B R AE1 N S K IY0 +DOBRATZ D AA1 B R AH0 T S +DOBRIMIR D AH0 B R IY1 M IH0 R +DOBRIN D AA1 B R IH0 N +DOBRINJA D AH0 B R IY1 N JH AH0 +DOBRINJA(1) D AH0 B R IY1 N Y AH0 +DOBRINS D AA1 B R IH0 N Z +DOBRINSKI D AH0 B R IH1 N S K IY0 +DOBRO D OW1 B R OW2 +DOBROWOLSKI D AH0 B R AW0 OW1 L S K IY0 +DOBROWSKI D AH0 B R AO1 F S K IY0 +DOBRY D AA1 B R IY0 +DOBRYNIN D AA1 B R IH0 N IH0 N +DOBRYNIN(1) D AH0 B R IY1 N IH0 N +DOBRZYNSKI D OW2 B R AH0 ZH IH1 N S K IY0 +DOBSON D AA1 B S AH0 N +DOBSON'S D AA1 B S AH0 N Z +DOBSONS D AA1 B S AH0 N Z +DOBY D OW1 B IY0 +DOBYNS D OW1 B IH0 N Z +DOC D AA1 K +DOCENT D OW1 S AH0 N T +DOCENTS D OW1 S AH0 N T S +DOCHERTY D AA1 CH ER0 T IY0 +DOCHOW D OW1 CH AW0 +DOCHTERMAN D AA1 K T ER0 M AH0 N +DOCIE D AA1 K IY0 +DOCILA D AA1 S IH0 L AH0 +DOCILE D AA1 S AH0 L +DOCILITY D AA0 S IH1 L AH0 T IY0 +DOCK D AA1 K +DOCK'S D AA1 K S +DOCKED D AA1 K T +DOCKEN D AA1 K AH0 N +DOCKENDORF D AA1 K IH0 N D AO0 R F +DOCKER D AA1 K ER0 +DOCKERS D AA1 K ER0 Z +DOCKERY D AA1 K ER0 IY0 +DOCKET D AA1 K AH0 T +DOCKETS D AA1 K AH0 T S +DOCKHAM D AA1 K HH AH0 M +DOCKIERS D AA1 K Y ER0 Z +DOCKING D AA1 K IH0 NG +DOCKINGS D AA1 K IH0 NG Z +DOCKINS D AA1 K IH0 N Z +DOCKLAND D AA1 K L AH0 N D +DOCKLANDS D AA1 K L AH0 N D Z +DOCKS D AA1 K S +DOCKSIDE D AA1 K S AY2 D +DOCKSON D AA1 K S AH0 N +DOCKSTADER D AA1 K S T AH0 D ER0 +DOCKTER D AA1 K T ER0 +DOCKWORKER D AA1 K W ER2 K ER0 +DOCKWORKERS D AA1 K W ER2 K ER0 Z +DOCKYARD D AA1 K Y AA2 R D +DOCS D AA1 K S +DOCTOR D AA1 K T ER0 +DOCTOR(1) D AO1 K T ER0 +DOCTOR'S D AA1 K T ER0 Z +DOCTORAL D AA1 K T ER0 AH0 L +DOCTORATE D AA1 K T ER0 AH0 T +DOCTORATES D AA1 K T ER0 AH0 T S +DOCTORED D AA1 K T ER0 D +DOCTORING D AA1 K T ER0 IH0 NG +DOCTORS D AA1 K T ER0 Z +DOCTORS' D AA1 K T ER0 Z +DOCTRINAIRE D AA2 K T R AH0 N EH1 R +DOCTRINAL D AA1 K T R AH0 N AH0 L +DOCTRINE D AA1 K T R AH0 N +DOCTRINE(1) D AO1 K T ER0 IH0 N +DOCTRINE'S D AA1 K T R AH0 N Z +DOCTRINES D AA1 K T R AH0 N Z +DOCUDRAMA D OW2 K AH0 D R AE1 M AH0 +DOCUMENT D AA1 K Y AH0 M EH0 N T +DOCUMENT(1) D AA1 K Y UW0 M EH0 N T +DOCUMENTA D AA2 K Y UW0 M EH1 N T AH0 +DOCUMENTARIES D AA2 K Y AH0 M EH1 N T ER0 IY0 Z +DOCUMENTARIES(1) D AA2 K Y AH0 M EH1 N ER0 IY0 Z +DOCUMENTARIES(2) D AA2 K Y UW0 M EH1 N T ER0 IY0 Z +DOCUMENTARIES(3) D AA2 K Y UW0 M EH1 N ER0 IY0 Z +DOCUMENTARY D AA2 K Y AH0 M EH1 N T ER0 IY0 +DOCUMENTARY(1) D AA2 K Y AH0 M EH1 N ER0 IY0 +DOCUMENTARY(2) D AA2 K Y UW0 M EH1 N T ER0 IY0 +DOCUMENTARY(3) D AA2 K Y UW0 M EH1 N ER0 IY0 +DOCUMENTATION D AA2 K Y AH0 M EH0 N T EY1 SH AH0 N +DOCUMENTATION(1) D AA2 K Y UW0 M EH0 N T EY1 SH AH0 N +DOCUMENTED D AA1 K Y AH0 M EH2 N T AH0 D +DOCUMENTED(1) D AA1 K Y AH0 M EH2 N AH0 D +DOCUMENTED(2) D AA1 K Y UW0 M EH2 N T AH0 D +DOCUMENTED(3) D AA1 K Y UW0 M EH2 N AH0 D +DOCUMENTING D AA1 K Y AH0 M AH0 N T IH0 NG +DOCUMENTING(1) D AA1 K Y AH0 M AH0 N IH0 NG +DOCUMENTING(2) D AA1 K Y UW0 M AH0 N T IH0 NG +DOCUMENTING(3) D AA1 K Y UW0 M AH0 N IH0 NG +DOCUMENTS D AA1 K Y AH0 M AH0 N T S +DOCUMENTS(1) D AA1 K Y UW0 M AH0 N T S +DODARO D OW0 D AA1 R OW0 +DODD D AA1 D +DODD'S D AA1 D Z +DODDERING D AA1 D ER0 IH0 NG +DODDINGTON D AA1 D IH0 N T AH0 N +DODDINGTON(1) D AA1 D IH0 NG T AH0 N +DODDRIDGE D AA1 D R IH0 JH +DODDS D AA1 D Z +DODGE D AA1 JH +DODGE'S D AA1 JH IH0 Z +DODGED D AA1 JH D +DODGEN D AA1 JH AH0 N +DODGER D AA1 JH ER0 +DODGER'S D AA1 JH ER0 Z +DODGERS D AA1 JH ER0 Z +DODGERS' D AA1 JH ER0 Z +DODGES D AA1 JH IH0 Z +DODGING D AA1 JH IH0 NG +DODI D OW1 D IY0 +DODI'S D OW1 D IY0 Z +DODO D OW1 D OW0 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T OW0 +DOTS D AA1 T S +DOTSON D AA1 T S AH0 N +DOTT D AA1 T +DOTTAVIO D OW0 T AA1 V IY0 OW0 +DOTTED D AA1 T AH0 D +DOTTED(1) D AA1 T IH0 D +DOTTER D AA1 T ER0 +DOTTERER D AA1 T ER0 ER0 +DOTTIE D AA1 T IY0 +DOTTING D AA1 T IH0 NG +DOTTS D AA1 T S +DOTTY D AA1 T IY0 +DOTY D OW1 T IY0 +DOTZLER D AA1 T S L ER0 +DOUB D AW1 B +DOUBEK D AW1 B IH0 K +DOUBET D AW1 B IH0 T +DOUBLE D AH1 B AH0 L +DOUBLE-CHECK D AH1 B AH0 L CH EH2 K +DOUBLE-ENTENDRE D AH1 B AH0 L AA0 N T AA1 N D R AH0 +DOUBLED D AH1 B AH0 L D +DOUBLEDAY D AH1 B AH0 L D EY2 +DOUBLEDECKER D AH2 B AH0 L D EH1 K ER0 +DOUBLES D AH1 B AH0 L Z +DOUBLESPEAK D AH1 B AH0 L S P IY2 K +DOUBLETHINK D AH1 B AH0 L TH IH2 NG K +DOUBLETREE D AH1 B AH0 L T R IY2 +DOUBLING D AH1 B AH0 L IH0 NG +DOUBLING(1) D AH1 B L IH0 NG +DOUBLY D AH1 B L IY0 +DOUBRAVA D AW1 B R AH0 V AH0 +DOUBT D AW1 T +DOUBTED D AW1 T IH0 D +DOUBTER D AW1 T ER0 +DOUBTERS D AW1 T ER0 Z +DOUBTFIRE D AW1 T F AY1 ER0 +DOUBTFIRE'S D AW1 T F AY1 ER0 Z +DOUBTFIRES D AW1 T F AY1 ER0 Z 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AH0 N +DOWER D AW1 R +DOWERS D AW1 R Z +DOWIE D AW1 IY0 +DOWIS D AW1 IH0 S +DOWLAND D AW1 L AH0 N D +DOWLEN D AW1 L AH0 N +DOWLER D AW1 L ER0 +DOWLESS D AW1 L AH0 S +DOWLING D AW1 L IH0 NG +DOWN D AW1 N +DOWN'S D AW1 N Z +DOWNARD D AW1 N ER0 D +DOWNBEAT D AW0 N B IY1 T +DOWNCAST D AW1 N K AE2 S T +DOWNDRAFT D AW1 N D R AE2 F T +DOWNE D AW1 N +DOWNED D AW1 N D +DOWNEN D AW1 N AH0 N +DOWNER D AW1 N ER0 +DOWNERS D AW1 N ER0 Z +DOWNES D AW1 N Z +DOWNES'S D AW1 N Z IH0 Z +DOWNEY D AW1 N IY0 +DOWNEY'S D AW1 N IY0 Z +DOWNFALL D AW1 N F AO2 L +DOWNGRADE D AW1 N G R EY1 D +DOWNGRADED D AW1 N G R EY1 D AH0 D +DOWNGRADES D AW1 N G R EY1 D Z +DOWNGRADING D AW1 N G R EY1 D IH0 NG +DOWNGRADINGS D AW1 N G R EY2 D IH0 NG Z +DOWNHAM D AW1 N HH AH0 M +DOWNHILL D AW1 N HH IH1 L +DOWNIE D AW1 N IY0 +DOWNING D AW1 N IH0 NG +DOWNINGTOWN D AW1 N IH0 NG T AW2 N +DOWNLOAD D AW1 N L OW2 D +DOWNLOADED D AW1 N L OW2 D IH0 D +DOWNLOADING D AW1 N L OW2 D IH0 NG +DOWNLOADS D AW1 N L OW2 D Z +DOWNPAYMENT D AW2 N P EY1 M AH0 N T +DOWNPAYMENTS D AW2 N P EY1 M AH0 N T S +DOWNPLAY D AW1 N P L EY2 +DOWNPLAYED D AW1 N P L EY2 D +DOWNPLAYING D AW1 N P L EY2 IH0 NG +DOWNPLAYS D AW1 N P L EY2 Z +DOWNPOUR D AW1 N P AO0 R +DOWNPOURS D AW1 N P AO2 R Z +DOWNRANGE D AW1 N R EY1 N JH +DOWNRIGHT D AW1 N R AY2 T +DOWNRIVER D AW2 N R IH1 V ER0 +DOWNS D AW1 N Z +DOWNSCALE D AW1 N S K EY2 L +DOWNSIDE D AW1 N S AY2 D +DOWNSIDES D AW1 N S AY2 D Z +DOWNSIZE D AW1 N S AY2 Z +DOWNSIZED D AW1 N S AY2 Z D +DOWNSIZES D AW1 N S AY2 Z IH0 Z +DOWNSIZING D AW1 N S AY2 Z IH0 NG +DOWNSIZINGS D AW1 N S AY2 Z IH0 NG Z +DOWNSTAGE D AW1 N S T EY2 JH +DOWNSTAIRS D AW1 N S T EH1 R Z +DOWNSTATE D AW1 N S T EY2 T +DOWNSTREAM D AW1 N S T R IY1 M +DOWNSWING D AW1 N S W IH2 NG +DOWNTIME D AW1 N T AY2 M +DOWNTOWN D AW1 N T AW1 N +DOWNTOWN'S D AW1 N T AW1 N Z +DOWNTOWNS D AW1 N T AW1 N Z +DOWNTREND D AW1 N T R EH2 N D +DOWNTRODDEN D AW2 N T R AA1 D AH0 N +DOWNTURN D AW1 N T ER2 N +DOWNTURNS D AW1 N T ER2 N Z +DOWNUM D AW1 N AH0 M +DOWNWARD D AW1 N W ER0 D +DOWNWARDLY D AW1 N W ER0 D L IY0 +DOWNWARDS D AW1 N W ER0 D Z +DOWNWIND D AW0 N W IH1 N D +DOWNY D AW1 N IY0 +DOWRY D AW1 R IY0 +DOWSE D AW1 S +DOWSING D AW1 S IH0 NG +DOWSMAN D AW1 Z M AH0 N +DOWTY D AW1 T IY0 +DOXEY D AA1 K S IY0 +DOXIE D AA1 K S IY0 +DOXOLOGIES D AA0 K S AA1 L AH0 JH IY0 Z +DOXOLOGY D AA0 K S AA1 L AH0 JH IY0 +DOXTATER D AA1 K S T EY0 T ER0 +DOXY D AA1 K S IY0 +DOYAL D OY0 AA1 L +DOYEL D OY1 AH0 L +DOYEN D OY1 IH0 N +DOYENNE D OY2 EH1 N +DOYLE D OY1 L +DOYLE'S D OY1 L Z +DOYON D OY1 AH0 N +DOZE D OW1 Z +DOZED D OW1 Z D +DOZEN D AH1 Z AH0 N +DOZENS D AH1 Z AH0 N Z +DOZES D OW1 Z IH0 Z +DOZIER D OW1 Z IY0 ER0 +DOZING D OW1 Z IH0 NG +DQALPHA D IY1 K Y UW1 AE1 L F AH0 +DR D R AY1 V +DR(1) D AA1 K T ER0 +DR. D R AY1 V +DR.(1) D AA1 K T ER0 +DRAB D R AE1 B +DRABBED D R AE1 B D +DRABBLE D R AE1 B AH0 L +DRABEK D R AE1 B IH0 K +DRABENSTOTT D R AH0 B EH1 N S T AH0 T +DRABIK D R AA1 B IH0 K +DRABINSKY D R AH0 B IH1 N S K IY0 +DRABKIN D R AE1 B K IH2 N +DRABS D R AE1 B Z +DRACE D R EY1 S +DRACH D R AE1 CH +DRACHENBERG D R AE1 K AH0 N B ER0 G +DRACHMA D R AE1 K M AH0 +DRACHMAS D R AA1 K M AH0 Z +DRACKETT D R AE1 K IH0 T +DRACO D R EY1 K OW0 +DRACO(1) D R AE1 K OW0 +DRACONIAN D R EY0 K OW1 N IY0 AH0 N +DRACONIAN(1) D R AH0 K OW1 N IY0 AH0 N +DRACULA D R AE1 K Y UW0 L AH0 +DRAEGER D R EH1 G ER0 +DRAFFEN D R AE1 F AH0 N +DRAFT D R AE1 F T +DRAFT'S D R AE1 F T S +DRAFTED D R AE1 F T IH0 D +DRAFTEE D R AE1 F T IY1 +DRAFTEES D R AE1 F T IY1 Z +DRAFTER D R AE1 F T ER0 +DRAFTERS D R AE1 F T ER0 Z +DRAFTING D R AE1 F T IH0 NG +DRAFTS D R AE1 F T S +DRAFTSMAN D R AE1 F T S M AH0 N +DRAFTSMANSHIP D R AE1 F T S M AH0 N SH IH2 P +DRAFTSMEN D R AE1 F T S M AH0 N +DRAFTY D R AE1 F T IY0 +DRAG D R AE1 G +DRAGAN D R AA1 G AH0 N +DRAGE D R EY1 JH +DRAGER D R EY1 G ER0 +DRAGGED D R AE1 G D +DRAGGING D R AE1 G IH0 NG +DRAGGY D R AE1 G IY0 +DRAGLINE D R AE1 G L AY2 N +DRAGNET D R AE1 G N EH2 T +DRAGNETS D R AE1 G N EH2 T S +DRAGO D R AA1 G OW0 +DRAGON D R AE1 G AH0 N +DRAGON'S D R AE1 G AH0 N Z +DRAGONAIR D R AE1 G AH0 N EH2 R +DRAGONE D R AH0 G OW1 N +DRAGONHEAD D R AE1 G AH0 N HH EH2 D +DRAGONHEART D R AE1 G AH0 N HH AA2 R T +DRAGONS D R AE1 G AH0 N Z +DRAGOO D R AA1 G UW0 +DRAGOVICH D R AE1 G AH0 V IH0 CH +DRAGS D R AE1 G Z +DRAHEIM D R AE1 HH AY0 M +DRAHOS D R EY1 HH OW0 Z +DRAHUSCHAK D R AE1 HH AH0 SH AE0 K +DRAHUSCHAK(1) D R AH0 HH UW1 SH AH0 K +DRAIN D R EY1 N +DRAINAGE D R EY1 N AH0 JH +DRAINAGE(1) D R EY1 N IH0 JH +DRAINE D R EY1 N +DRAINED D R EY1 N D +DRAINER D R EY1 N ER0 +DRAINERS D R EY1 N ER0 Z +DRAINING D R EY1 N IH0 NG +DRAINS D R EY1 N Z +DRAKE D R EY1 K +DRAKEFORD D R AE1 K F AO0 R D +DRAKES D R EY1 K S +DRAKOS D R EY1 K OW0 Z +DRALLE D R EY1 L +DRAM D R AE1 M +DRAM(1) D IY1 R AE2 M +DRAMA D R AA1 M AH0 +DRAMAMINE D R AE1 M AH0 M IY2 N +DRAMAS D R AA1 M AH0 Z +DRAMATIC D R AH0 M AE1 T IH0 K +DRAMATICALLY D R AH0 M AE1 T IH0 K L IY0 +DRAMATICALLY(1) D R AH0 M AE1 T IH0 K AH0 L IY0 +DRAMATICS D R AH0 M AE1 T IH0 K S +DRAMATIST D R AA1 M AH0 T IH0 S T +DRAMATIZATION D R AE2 M AH0 T AH0 Z EY1 SH AH0 N +DRAMATIZATIONS D R AE2 M AH0 T AH0 Z EY1 SH AH0 N Z +DRAMATIZE D R AA1 M AH0 T AY2 Z +DRAMATIZE(1) D R AE1 M AH0 T AY2 Z +DRAMATIZED D R AE1 M AH0 T AY2 Z D +DRAMATIZES D R AE1 M AH0 T AY2 Z IH0 Z +DRAMATIZING D R AE1 M AH0 T AY2 Z IH0 NG +DRAMATURGY D R AA1 M AH0 T ER0 JH IY0 +DRAMS D R AE1 M Z +DRAMS(1) D IY1 R AE2 M Z +DRANE D R EY1 N +DRANEY D R EY1 N IY0 +DRANG D R AE1 NG +DRANK D R AE1 NG K +DRANSFIELD D R AE1 N S F IY2 L D +DRAPE D R EY1 P +DRAPEAU D R AH0 P OW1 +DRAPED D R EY1 P T +DRAPER D R EY1 P ER0 +DRAPERIES D R EY1 P ER0 IY0 Z +DRAPERY D R EY1 P ER0 IY0 +DRAPES D R EY1 P S +DRAPING D R EY1 P IH0 NG +DRAPKIN D R AE1 P K IH0 N +DRASNER D R AE1 S N ER0 +DRASTIC D R AE1 S T IH0 K +DRASTICALLY D R AE1 S T IH0 K L IY0 +DRAUGHN D R AO1 N +DRAUGHON D R AO1 AH0 N +DRAUGHT D R AE1 F T +DRAUGHTS D R AE1 F T S +DRAUS D R AO1 Z +DRAVECKY D R AH0 V EH1 K IY0 +DRAVES D R EY1 V Z +DRAVIS D R AE1 V IH0 S +DRAVO D R AE1 V OW0 +DRAVO'S D R AE1 V OW0 Z +DRAW D R AO1 +DRAWBACK D R AO1 B AE2 K +DRAWBACKS D R AO1 B AE2 K S +DRAWBAUGH D R AO1 B AO2 +DRAWBRIDGE D R AO1 B R IH2 JH +DRAWDOWN D R AO1 D AW2 N +DRAWDOWNS D R AO1 D AW2 N Z +DRAWDY D R AO1 D IY0 +DRAWER D R AO1 R +DRAWERS D R AO1 R Z +DRAWING D R AO1 IH0 NG +DRAWINGS D R AO1 IH0 NG Z +DRAWL D R AO1 L +DRAWLED D R AO1 L D +DRAWLS D R AO1 L Z +DRAWN D R AO1 N +DRAWS D R AO1 Z +DRAY D R EY1 +DRAYER D R EY1 ER0 +DRAYTON D R EY1 T AH0 N +DRAYTON'S D R EY1 T AH0 N Z +DREAD D R EH1 D +DREADED D R EH1 D IH0 D +DREADFUL D R EH1 D F AH0 L +DREADFULLY D R EH1 D F AH0 L IY0 +DREADING D R EH1 D IH0 NG +DREADNOUGHT D R EH1 D N AO2 T +DREADS D R EH1 D Z +DREAM D R IY1 M +DREAMED D R IY1 M D +DREAMER D R IY1 M ER0 +DREAMERS D R IY1 M ER0 Z +DREAMING D R IY1 M IH0 NG +DREAMLAND D R IY1 M L AE2 N D +DREAMLIKE D R IY1 M L AY2 K +DREAMS D R IY1 M Z +DREAMT D R EH1 M T +DREAMWORKS D R IY1 M W ER2 K S +DREAMWORKS' D R IY1 M W ER2 K S +DREAMWORLD D R IY1 M W ER2 L D +DREAMY D R IY1 M IY0 +DREARINESS D R IY1 R IY0 N AH0 S +DREARY D R IH1 R IY0 +DREBSKY D R EH1 B S K IY0 +DRECHSEL D R EH1 K S AH0 L +DRECHSLER D R EH1 K S AH0 L ER0 +DRECHSLER(1) D R EH1 K S L ER0 +DRED D R EH1 D +DREDD D R EH1 D +DREDGE D R EH1 JH +DREDGED D R EH1 JH D +DREDGES D R EH1 JH AH0 Z +DREDGES(1) D R EH1 JH IH0 Z +DREDGING D R EH1 JH IH0 NG +DREES D R IY1 Z +DREESE D R IY1 Z +DREESSEN D R IY1 S AH0 N +DREGER D R EH1 G ER0 +DREGS D R EH1 G Z +DREHER D R EH1 R +DREIBELBIS D R AY1 B IH0 L B IH0 S +DREIER D R AY1 ER0 +DREIGHTON D R AY1 T IH0 N +DREILING D R AY1 L IH0 NG +DREIS D R IY1 Z +DREISBACH D R AY1 S B AA2 K +DREMAN D R IY1 M AH0 N +DRENCH D R EH1 N CH +DRENCHED D R EH1 N CH T +DRENCHES D R EH1 N CH AH0 Z +DRENCHING D R EH1 N CH IH0 NG +DRENNAN D R EH1 N AH0 N +DRENNEN D R EH1 N AH0 N +DRENNING D R EH1 N IH0 NG +DRENNON D R EH1 N AH0 N +DRENTH D R EH1 N TH +DREPUNG D R EY1 P AH2 NG +DREPUNG(1) D R EY2 P AO1 NG +DRESBACH D R EH1 S B AA2 K +DRESCH D R EH1 SH +DRESCHER D R EH1 SH ER0 +DRESDEN D R EH1 Z D IH0 N +DRESDNER D R EH1 Z D N ER0 +DRESDNER'S D R EH1 Z D N ER0 Z +DRESEN D R IY1 Z AH0 N +DRESHER D R EH1 SH ER0 +DRESNER D R EH1 Z N ER0 +DRESS D R EH1 S +DRESSAGE D R EH0 S AA1 ZH +DRESSED D R EH1 S T +DRESSEL D R EH1 S AH0 L +DRESSEN D R EH1 S AH0 N +DRESSER D R EH1 S ER0 +DRESSER'S D R EH1 S ER0 Z +DRESSERS D R EH1 S ER0 Z +DRESSES D R EH1 S AH0 Z +DRESSES(1) D R EH1 S IH0 Z +DRESSIER D R EH1 S IY0 ER0 +DRESSING D R EH1 S IH0 NG +DRESSINGS D R EH1 S IH0 NG Z +DRESSLER D R EH1 S L ER0 +DRESSMAKER D R EH1 S M EY2 K ER0 +DRESSMAKERS D R EH1 S M EY2 K ER0 Z +DRESSMAKING D R EH1 S M EY2 K IH0 NG +DRESSY D R EH1 S IY0 +DREW D R UW1 +DREWERY D R UW1 ER0 IY0 +DREWES D R UW1 Z +DREWETT D R UW1 IH0 T +DREWRY D R UW1 R IY0 +DREWS D R UW1 Z +DREXEL D R EH1 K S AH0 L +DREXEL'S D R EH1 K S AH0 L Z +DREXLER D R EH1 K S L ER0 +DREY D R EY1 +DREYER D R EY1 ER0 +DREYFUS D R AY1 F AH0 S +DREYFUS(1) D R EY1 F AH0 S +DREYFUS'S D R EY1 F AH0 S IH0 Z +DREYFUSS D R EY1 F AH0 S +DRIBBED D R IH1 B D +DRIBBLE D R IH1 B AH0 L +DRIBBLED D R IH1 B AH0 L D +DRIBBLES D R IH1 B AH0 L Z +DRIBBLING D R IH1 B AH0 L IH0 NG +DRIBBLING(1) D R IH1 B L IH0 NG +DRIBS D R IH1 B Z +DRIED D R AY1 D +DRIEHAUS D R IY1 HH AW2 S +DRIER D R AY1 ER0 +DRIES D R AY1 Z +DRIESSEN D R IY1 S AH0 N +DRIEST D R AY1 AH0 S T +DRIEVER D R IY1 V ER0 +DRIFT D R IH1 F T +DRIFTA D R IH1 F T AH0 +DRIFTED D R IH1 F T AH0 D +DRIFTED(1) D R IH1 F T IH0 D +DRIFTER D R IH1 F T ER0 +DRIFTERS D R IH1 F T ER0 Z +DRIFTING D R IH1 F T IH0 NG +DRIFTNET D R IH1 F T N EH2 T +DRIFTS D R IH1 F T S +DRIFTWOOD D R IH1 F T W UH2 D +DRIGGERS D R IH1 G ER0 Z +DRIGGS D R IH1 G Z +DRILL D R IH1 L +DRILLBIT D R IH1 L B IH2 T +DRILLED D R IH1 L D +DRILLER D R IH1 L ER0 +DRILLERS D R IH1 L ER0 Z +DRILLING D R IH1 L IH0 NG +DRILLING'S D R IH1 L IH0 NG Z +DRILLS D R IH1 L Z +DRINA D IY1 N AH0 +DRINA'S D IY1 N AH0 Z +DRINAS D IY1 N AH0 Z +DRING D R IH1 NG +DRINK D R IH1 NG K +DRINKABLE D R IH1 N K AH0 B AH0 L +DRINKARD D R IH1 NG K ER0 D +DRINKER D R IH1 NG K ER0 +DRINKER'S D R IH1 NG K ER0 Z +DRINKERS D R IH1 NG K ER0 Z +DRINKING D R IH1 NG K IH0 NG +DRINKS D R IH1 NG K S +DRINKWATER D R IH1 NG K W AO2 T ER0 +DRINKWINE D R IH1 NG K W AY2 N +DRINNON D R IH1 N AH0 N +DRIP D R IH1 P +DRIP-DRY D R IH1 P D R AY1 +DRIPPED D R IH1 P T +DRIPPING D R IH1 P IH0 NG +DRIPPS D R IH1 P S +DRIPS D R IH1 P S +DRISCOLL D R IH1 S K AH0 L +DRISKELL D R IH1 S K AH0 L +DRISKILL D R IH1 S K IH0 L +DRIVABLE D R AY1 V AH0 B AH0 L +DRIVE D R AY1 V +DRIVE'S D R AY1 V Z +DRIVE-BY D R AY1 V B AY1 +DRIVE-THRU D R AY1 V TH R UW1 +DRIVE-THRUS D R AY1 V TH R UW1 Z +DRIVEL D R IH1 V AH0 L +DRIVEN D R IH1 V AH0 N +DRIVER D R AY1 V ER0 +DRIVER'S D R AY1 V ER0 Z +DRIVERLESS D R AY1 V ER0 L IH0 S +DRIVERS D R AY1 V ER0 Z +DRIVERS' D R AY1 V ER0 Z +DRIVES D R AY1 V Z +DRIVEWAY D R AY1 V W EY2 +DRIVEWAYS D R AY1 V W EY2 Z +DRIVING D R AY1 V IH0 NG +DRIZZLE D R IH1 Z AH0 L +DRIZZLING D R IH1 Z AH0 L IH0 NG +DRIZZLING(1) D R IH1 Z L IH0 NG +DRIZZLY D R IH1 Z L IY0 +DROBKOV D R AO1 B K AO0 V +DROBKOV(1) D R AO1 B K AO0 F +DROBNY D R AA1 B N IY0 +DRODDY D R AA1 D IY0 +DROEGE D R OW1 JH +DROESSLER D R OW1 S AH0 L ER0 +DROESSLER(1) D R OW1 S L ER0 +DROGE D R OW1 JH +DROGOUL D R OW0 G UW1 L +DROGOUL'S D R OW0 G UW1 L Z +DROGUE D R OW1 G +DROHAN D R OW1 AH0 N +DROID D R OY1 D +DROIDS D R OY1 D Z +DROKE D R OW1 K +DROLET D R OW1 L IH0 T +DROLL D R OW1 L +DROLLINGER D R OW1 L IH0 NG ER0 +DROMEDARY D R AA1 M AH0 D EH2 R IY0 +DROMER D R OW1 M ER0 +DROMEY D R OW1 M IY0 +DROMGOOLE D R AA1 M G UW2 L +DROMGOOLES D R AA0 M G UW1 L Z +DROMI D R AA1 M IY0 +DROMOMANIA D R OW2 M OW0 M EY1 N IY0 AH0 +DROMOMANIA(1) D R OW2 M OW0 M EY1 N Y AH0 +DROMON D R OW1 M AH0 N +DRONE D R OW1 N +DRONED D R OW1 N D +DRONES D R OW1 N Z +DRONET D R OW1 N IH0 T +DRONEY D R OW1 N IY0 +DRONING D R OW1 N IH0 NG +DROOL D R UW1 L +DROOLED D R UW1 L D +DROOLING D R UW1 L IH0 NG +DROOP D R UW1 P +DROOPED D R UW1 P T +DROOPING D R UW1 P IH0 NG +DROOPY D R UW1 P IY0 +DROP D R AA1 P +DROP(1) D R AO1 P +DROP-OFF D R AA1 P AO2 F +DROP-OFFS D R AA1 P AO2 F S +DROPKIN D R AA1 P K IH0 N +DROPLET D R AA1 P L AH0 T +DROPLETS D R AA1 P L AH0 T S +DROPOFF D R AA1 P AO2 F +DROPOFFS D R AA1 P AO2 F S +DROPOUT D R AA1 P AW2 T +DROPOUTS D R AA1 P AW2 T S +DROPPED D R AA1 P T +DROPPER D R AA1 P ER0 +DROPPERS D R AA1 P ER0 Z +DROPPING D R AA1 P IH0 NG +DROPPINGS D R AA1 P IH0 NG Z +DROPS D R AA1 P S +DROPSY D R AA1 P S IY0 +DROSER D R OW1 Z ER0 +DROSS D R AO1 S +DROST D R AA1 S T +DROSTE D R OW1 S T +DROSTE(1) D R AA1 S T +DROSTE(2) D R AA1 S T AH0 +DROTAR D R OW1 T ER0 +DROUGHT D R AW1 T +DROUGHT'S D R AW1 T S +DROUGHTS D R AW1 T S +DROUILLARD D R W IY0 L AA1 R D +DROUIN D R W IY1 N +DROVE D R OW1 V +DROVER D R OW1 V ER0 +DROVES D R OW1 V Z +DROWN D R AW1 N +DROWNED D R AW1 N D +DROWNING D R AW1 N IH0 NG +DROWNINGS D R AW1 N IH0 NG Z +DROWNS D R AW1 N Z +DROWSINESS D R AW1 Z IY0 N AH0 S +DROWSY D R AW1 Z IY0 +DROZ D R AA1 Z +DROZD D R AA1 Z D +DROZDA D R AA1 Z D AH0 +DROZDOWSKI D R AH0 Z D AO1 F S K IY0 +DRU D R UW1 +DRUB D R AH1 B +DRUBBED D R AH1 B D +DRUBBING D R AH1 B IH0 NG +DRUCE D R UW1 S +DRUCIE D R AH1 K IY0 +DRUCK D R AH1 K +DRUCKENMILLER D R AH1 K IH0 N M IH2 L ER0 +DRUCKER D R AH1 K ER0 +DRUCKMAN D R AH1 K M AH0 N +DRUDGE D R AH1 JH +DRUDGERY D R AH1 JH ER0 IY0 +DRUELLA D R UW2 EH1 L AH0 +DRUG D R AH1 G +DRUG'S D R AH1 G Z +DRUGAN D R UW1 G AH0 N +DRUGGED D R AH1 G D +DRUGGING D R AH1 G IH0 NG +DRUGGIST D R AH1 G IH0 S T +DRUGGIST'S D R AH1 G AH0 S T S +DRUGGIST'S(1) D R AH1 G IH0 S T S +DRUGGISTS D R AH1 G AH0 S T S +DRUGGISTS(1) D R AH1 G IH0 S T S +DRUGMAKER D R AH1 G M EY2 K ER0 +DRUGMAKERS D R AH1 G M EY2 K ER0 Z +DRUGS D R AH1 G Z +DRUGS' D R AH1 G Z +DRUGSTORE D R AH1 G S T AO2 R +DRUGSTORES D R AH1 G S T AO2 R Z +DRUID D R UW1 IH0 D +DRUIDISM D R UW1 AH0 D IH2 Z AH0 M +DRUIDS D R UW1 IH0 D Z +DRUISILLA D R IH0 S IH1 L AH0 +DRUM D R AH1 M +DRUMBEAT D R AH1 M B IY2 T +DRUMHEAD D R AH1 M HH EH2 D +DRUMHELLER D R AH1 M HH EH2 L ER0 +DRUMLIN'S D R AH1 M L IH0 N Z +DRUMM D R AH1 M +DRUMMED D R AH1 M D +DRUMMER D R AH1 M ER0 +DRUMMERS D R AH1 M ER0 Z +DRUMMEY D R AH1 M IY0 +DRUMMING D R AH1 M IH0 NG +DRUMMOND D R AH1 M AH0 N D +DRUMMONDS D R AH1 M AH0 N D Z +DRUMRIGHT D R AH1 M R AY2 T +DRUMS D R AH1 M Z +DRUMSTICK D R AH1 M S T IH0 K +DRUMWRIGHT D R AH1 M R AY2 T +DRUNK D R AH1 NG K +DRUNKARD D R AH1 NG K ER0 D +DRUNKARDS D R AH1 NG K ER0 D Z +DRUNKEN D R AH1 NG K AH0 N +DRUNKENNESS D R AH1 NG K AH0 N N AH0 S +DRUNKS D R AH1 NG K S +DRUPE D R UW1 P +DRUPES D R UW1 P S +DRURY D R UW1 R IY0 +DRUSA D R UW1 S AH0 +DRUSE D R UW1 Z +DRUSIE D R AH1 S IY0 +DRUSILLA D R UW2 S IH1 L AH0 +DRUTHERS D R AH1 DH ER0 Z +DRUZE D R UW1 Z +DRY D R AY1 +DRYCLEAN D R AY1 K L IY2 N +DRYCLEANER D R AY1 K L IY2 N ER0 +DRYCLEANING D R AY1 K L IY2 N IH0 NG +DRYDEN D R AY1 D AH0 N +DRYE D R AY1 +DRYER D R AY1 ER0 +DRYERS D R AY1 ER0 Z +DRYING D R AY1 IH0 NG +DRYLY D R AY1 L IY0 +DRYNESS D R AY1 N AH0 S +DRYPERS D R AY1 P ER0 Z +DRYPOINT D R AY1 P OY2 N T +DRYSDALE D R AY1 Z D EY2 L +DRYSER D R AY1 S ER0 +DRYWALL D R AY1 W AA2 L +DRZEWIECKI JH UW0 IY1 T S K IY0 +DSOUZA D AH0 S UW1 Z AH0 +DSS D IY1 EH1 S EH1 S +DSV D IY1 EH1 S V IY1 +DU D UW1 +DU(1) D AH0 +DU-BOIS D UW1 B OY1 S +DUAL D UW1 AH0 L +DUAL(1) D UW1 L +DUALISM D UW1 AH0 L IH2 Z AH0 M +DUALISMS D UW1 AH0 L IH2 Z AH0 M Z +DUALIST D UW1 AH0 L IH0 S T +DUALISTIC D UW2 AH0 L IH1 S T IH0 K +DUALITY D UW0 AE1 L AH0 T IY0 +DUALS D UW1 AH0 L Z +DUAN D W AE1 N +DUAN(1) D W EY1 N +DUANA D UW0 AE1 N AH0 +DUANE D W EY1 N +DUARTE D W AA1 R T EY2 +DUARTE'S D W AA1 R T EY2 Z +DUB D AH1 B +DUBA D UW1 B AH0 +DUBACH D AH1 B AA0 K +DUBAI D UW0 B AY1 +DUBARRY D UW1 B EH2 R IY0 +DUBAS D UW1 B AH0 Z +DUBAY D AH1 B EY0 +DUBBED D AH1 B D +DUBBERLY D AH1 B ER0 L IY0 +DUBBING D AH1 B IH0 NG +DUBBS D AH1 B Z +DUBCEK D AH1 B CH EH2 K +DUBCEK(1) D UW1 B CH EH2 K +DUBE D UW1 B +DUBEAU D AH0 B OW1 +DUBERSTEIN D UW1 B ER0 S T AY2 N +DUBERSTEIN(1) D UW1 B ER0 S T IY2 N +DUBERSTEIN'S D UW1 B ER0 S T AY2 N Z +DUBERSTEIN'S(1) D UW1 B ER0 S T IY2 N Z +DUBEY D AH1 B IY0 +DUBHI D UW1 B IY0 +DUBICKI D AH0 B IH1 T S K IY0 +DUBIE D AH1 B IY0 +DUBIEL D AH1 B IY0 L +DUBILIER D UW2 B AH0 L IH1 R +DUBILIER(1) D UW2 B AH0 L AY1 ER0 +DUBIN D UW1 B IH0 N +DUBININ D UW0 B IH1 N IH0 N +DUBINSKY D AH0 B IH1 N S K IY0 +DUBIOUS D UW1 B IY0 AH0 S +DUBIOUSLY D UW1 B IY0 AH0 S L IY2 +DUBIS D UW1 B IH0 S +DUBLIN D AH1 B L IH0 N +DUBLIN'S D AH1 B L IH0 N Z +DUBOFF D AH1 B AO2 F +DUBOIS D UW0 B OY1 S +DUBOIS(1) D UW0 B W AA1 +DUBOISE D UW0 B OY1 S +DUBOISE(1) D UW0 B W AA1 +DUBORD D AH0 B AO1 R D +DUBOSE D UW0 B OW1 Z +DUBOW D UW1 B OW0 +DUBRAWSKI D UW0 B R AW1 S K IY0 +DUBRAY D AH1 B R EY2 +DUBREE D AH0 B R IY1 +DUBREUIL D AH1 B R UW0 L +DUBROC D AH1 B R AO0 K +DUBROFF D UW1 B R AO0 F +DUBROVNIK D UW0 B R AA1 V N IH0 K +DUBROVNIK'S D UW0 B R AA1 V N IH0 K Z +DUBROVNIKS D UW0 B R AA1 V N IH0 K Z +DUBROVSKY D UW0 B R AO1 F S K IY0 +DUBROVSKY(1) D UW0 B R AO1 V S K IY0 +DUBROW D AH1 B R OW2 +DUBS D AH1 B Z +DUBUC D UW1 B AH0 K +DUBUISSON D AH1 B IH0 S AH0 N +DUBUQUE D AH0 B Y UW1 K +DUBUQUE'S D AH0 B Y UW1 K S +DUBY D UW1 B IY0 +DUC D AH1 K +DUCA D UW1 K AH0 +DUCAL D UW1 K AH0 L +DUCE D UW1 S +DUCE(1) D UW1 CH EY2 +DUCEY D UW1 S IY0 +DUCH D AH1 CH +DUCHAINE D AH0 SH EY1 N +DUCHAMP D UW0 SH AA1 M P +DUCHAMP'S D UW0 SH AA1 M P S +DUCHARME D AH0 SH AA1 R M +DUCHEMIN D AH1 SH IH0 M AE0 N +DUCHENE D AH1 K IY0 N +DUCHENNE D UW0 SH EH1 N +DUCHESNEAU D AH1 SH IH0 S N OW0 +DUCHESS D AH1 CH AH0 S +DUCHIN D UW1 CH IH0 N +DUCHON D AH1 CH AH0 N +DUCHOSSOIS D UW0 CH AO1 S W AA2 +DUCHOW D AH1 CH OW0 +DUCHY D AH1 CH IY0 +DUCK D AH1 K +DUCK'S D AH1 K S +DUCKED D AH1 K T +DUCKER D AH1 K ER0 +DUCKETT D AH1 K IH0 T +DUCKIES D AH1 K IH2 Z +DUCKING D AH1 K IH0 NG +DUCKLING D AH1 K L IH0 NG +DUCKLINGS D AH1 K L IH0 NG Z +DUCKS D AH1 K S +DUCKS' D AH1 K S +DUCKSWORTH D AH1 K S W ER2 TH +DUCKWALL D AH1 K W AO2 L +DUCKWEED D AH1 K W IY2 D +DUCKWORTH D AH1 K W ER2 TH +DUCKY D AH1 K IY2 +DUCLOS D AH0 K L OW1 Z +DUCOMMUN D UW0 K AA1 M AH0 N +DUCOMMUN(1) D UW0 K AA1 M UW1 N +DUCOTE D AH0 K OW1 T +DUCT D AH1 K T +DUCTILE D AH1 K T AH0 L +DUCTILITY D AH0 K T IH1 L AH0 T IY0 +DUCTLESS D AH1 K T L AH0 S +DUCTS D AH1 K T S +DUD D AH1 D +DUDA D UW1 D AH0 +DUDACK D UW1 D AE0 K +DUDAR D UW1 D ER0 +DUDAS D UW1 D AH0 Z +DUDASH D AH1 D AH0 SH +DUDAYEV D UW0 D AY1 EH2 V +DUDAYEV'S D UW0 D AY1 EH2 V Z +DUDD D AH1 D +DUDDING D AH1 D IH0 NG +DUDDY D AH1 D IY0 +DUDE D UW1 D +DUDECK D UW1 D EH0 K +DUDECK'S D UW1 D EH0 K S +DUDEK D UW1 D IH0 K +DUDEN D UW1 D AH0 N +DUDENHOEFFER D AH1 D IH0 N HH OW0 F ER0 +DUDES D Y UW1 D Z +DUDGEON D AH1 JH AH0 N +DUDIK D UW1 D IH0 K +DUDLEY D AH1 D L IY0 +DUDMAN D AH1 D M AH0 N +DUDNEY D AH1 D N IY0 +DUDS D AH1 D Z +DUDZIAK D AH1 JH IY0 AE0 K +DUDZIK D AH1 D Z IH0 K +DUDZINSKI D AH0 JH IH1 N S K IY0 +DUE D UW1 +DUE(1) D Y UW1 +DUECKER D UW1 K ER0 +DUEITT D UW1 AH0 T +DUEKER D UW1 K ER0 +DUEL D UW1 AH0 L +DUELED D UW1 AH0 L D +DUELING D UW1 L IH0 NG +DUELIST D UW1 AH0 L IH0 S T +DUELL JH UW1 L +DUELL(1) D UW1 L +DUELS D UW1 AH0 L Z +DUENA D UW0 EH1 N AH0 +DUENA(1) D W EY1 N Y AH0 +DUENAS D UW0 EH1 N AH0 S +DUENAS(1) D W EY1 N Y AH0 S +DUENEZ D W EH0 N EH1 Z +DUENOW D UW1 N OW0 +DUENSING D UH1 N S IH0 NG +DUER D UW1 ER0 +DUERKSEN D UH1 R K S AH0 N +DUERR D UH1 R +DUERSON D UH1 R S AH0 N +DUERST D UH1 R S T +DUES D UW1 Z +DUESBERG D UW1 Z B ER0 G +DUESING D UW1 S IH0 NG +DUESLER D UW1 S AH0 L ER0 +DUESLER(1) D UW1 S L ER0 +DUESSELDORF D UW1 S AH0 L D AO2 R F +DUET D UW0 EH1 T +DUET(1) D Y UW0 EH1 T +DUETS D UW0 EH1 T S +DUETS(1) D Y UW0 EH1 T S +DUEY D UW1 IY0 +DUEY(1) D Y UW1 IY0 +DUFAULT D AH0 F OW1 +DUFEK D UW1 F IH0 K +DUFF D AH1 F +DUFFALA D AH0 F AE1 L AH0 +DUFFEE D AH1 F IY0 +DUFFEK D AH1 F IH0 K +DUFFEL D AH1 F AH0 L +DUFFELL D AH1 F AH0 L +DUFFER D AH1 F ER0 +DUFFETT D AH1 F IH0 T +DUFFEY D AH1 F IY0 +DUFFIE D AH1 F IY0 +DUFFIELD D AH1 F IY2 L D +DUFFIN D AH1 F IH0 N +DUFFNER D AH1 F N ER0 +DUFFORD D AH1 F ER0 D +DUFFOUR D AH1 F AO0 R +DUFFUS D AH1 F AH0 S +DUFFY D AH1 F IY0 +DUFFY'S D AH1 F IY0 Z +DUFNER D AH1 F N ER0 +DUFORD D AH1 F ER0 D +DUFORT D AH1 F ER0 T +DUFOUR D AH0 F UH1 R +DUFRANE D AH0 F R EY1 N +DUFRENE D AH0 F R IY1 N +DUFRESNE D AH0 F R EH1 N +DUFUR D AH0 F ER1 +DUG D AH1 G +DUGAL D UW1 JH AH0 L +DUGALD D AH1 G AH0 L D +DUGAN D AH1 G AH0 N +DUGAR D UW1 G ER0 +DUGAS D UW1 G AH0 Z +DUGDALE D AH1 G D EY2 L +DUGGAN D AH1 G AH0 N +DUGGAR D AH1 G ER0 +DUGGER D AH1 G ER0 +DUGGIN D AH1 G IH0 N +DUGGINS D AH1 G IH0 N Z +DUGO D UW1 G OW0 +DUGOUT D AH1 G AW2 T +DUGOUTS D AH1 G AW2 T S +DUGUAY D AH1 G EY0 +DUGUID D AH1 G W IH0 D +DUH D AH1 +DUHAIME D UW1 AY0 M +DUHAMEL D UW2 HH AE1 M AH0 L +DUHART D AH1 HH AA0 R T +DUHE D UW1 HH +DUHON D UW1 HH AH0 N +DUHR D ER1 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L +DULLEA D AH1 L IY0 AH0 +DULLED D AH1 L D +DULLER D AH1 L ER0 +DULLES D AH1 L AH0 S +DULLEST D AH1 L AH0 S T +DULLING D AH1 L IH0 NG +DULLNESS D AH1 L N AH0 S +DULMAGE D AH1 L M AH0 JH +DULONG D Y UW1 L AO0 NG +DULSKI D AH1 L S K IY0 +DULUDE D Y UW1 L UW2 D +DULUTH D AH0 L UW1 TH +DULWICH D AH1 L W IH2 CH +DULWORTH D AH1 L W ER0 TH +DULY D UW1 L IY0 +DUM D AH1 M +DUMA D UW1 M AH0 +DUMA'S D UW1 M AH0 Z +DUMAINE D AH0 M EY1 N +DUMAIS D AH0 M EY1 +DUMAN D UW1 M AH0 N +DUMAS D UW1 M AH0 Z +DUMAS(1) D UW2 M AA1 +DUMB D AH1 M +DUMB-ASS D AH1 M AE2 S +DUMBASS D AH1 M AE2 S +DUMBBELL D AH1 M B EH2 L +DUMBBELLS D AH1 M B EH2 L Z +DUMBER D AH1 M ER0 +DUMBEST D AH1 M AH0 S T +DUMBFOUND D AH1 M F AW0 N D +DUMBFOUNDED D AH1 M F AW0 N D IH0 D +DUMBFOUNDING D AH1 M F AW0 N D IH0 NG +DUMBFOUNDS D AH1 M F AW0 N D Z +DUMBING D AH1 M IH0 NG +DUMBLEDORE D AH1 M B AH0 L D AO2 R +DUMBO D AH1 M B OW0 +DUMBSTRUCK D AH1 M S T R AH2 K +DUMENIL D UW1 M AH0 N IH2 L +DUMEZ D UW1 M EH0 Z +DUMFORD D AH1 M F ER0 D 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Z +DUPRE D AH1 P R EY0 +DUPREE D AH0 P R IY1 +DUPREY D AH1 P R EY0 +DUPRIEST D UW2 P R IY1 S T +DUPUIS D AH0 P W IY1 +DUPUY D AH0 P W IY1 +DUQUE D UW1 K +DUQUESNE D UW0 K EY1 N +DUQUESNE'S D UW0 K EY1 N Z +DUQUETTE D AH0 K EH1 T +DURA D UH1 R AH0 +DURABILITY D ER0 AH0 B IH1 L IH0 T IY0 +DURABLE D UH1 R AH0 B AH0 L +DURABLES D UH1 R AH0 B AH0 L Z +DURACELL D UH1 R AH0 S EH2 L +DURAKON D UH1 R AH0 K IH0 N +DURALL D Y UW1 R AH0 L +DURAMED D UH1 R AH0 M EH2 D +DURAN D ER0 AE1 N +DURAN'S D ER0 AE1 N S +DURAND D UH0 R AA1 N D +DURANDO D UH0 R AA1 N D OW0 +DURANG D ER0 AE1 NG +DURANGO D ER0 AE1 NG G OW0 +DURANT D UH1 R AH0 N T +DURANT'S D ER0 AE1 N T S +DURANTE D UH0 R AA1 N T IY0 +DURATION D UH1 R EY1 SH AH0 N +DURATIONS D UH1 R EY1 SH AH0 N Z +DURAY D UH1 R EY0 +DURAZO D UH0 R AA1 Z OW0 +DURBAN D ER1 B AH0 N +DURBEN D ER1 B AH0 N +DURBIN D ER1 B IH0 N +DURCH D ER1 CH +DURCHHOLZ D ER1 CH OW2 L T S +DURDEN D ER1 D AH0 N +DURDIN D ER1 D IH0 N +DUREE D UH1 R IY1 +DURELL D Y UW1 R AH0 L +DUREN D UH1 R AH0 N +DURENBERGER D UH1 R AH0 N B ER0 G ER0 +DURENE D Y UW1 R IY0 N +DURER D UH1 R ER0 +DURESS D UH1 R EH0 S +DURETTE D ER0 EH1 T +DURFEE D ER1 F IY0 +DURFEY D ER1 F IY0 +DURFLINGER D ER1 F AH0 L IH0 NG ER0 +DURFLINGER(1) D ER1 F L IH0 NG ER0 +DURGAN D ER1 G AH0 N +DURGIN D ER1 JH IH0 N +DURHAM D ER1 AH0 M +DURHAM(1) D UH1 R HH AE1 M +DURHAM(2) D UH1 R AH0 M +DURI D UH1 R IY0 +DURICK D Y UW1 R IH0 K +DURIE D UH1 R IY0 +DURING D UH1 R IH0 NG +DURING(1) D Y UH1 R IH0 NG +DURING(2) D ER1 IH0 NG +DURIO D UH1 R IY0 OW0 +DURIRON D UW0 R IH1 R AH0 N +DURIS D Y UW1 R IH0 S +DURKEE D ER1 K IY0 +DURKHEIM D ER1 K HH AY2 M +DURKHEIM'S D ER1 K HH AY2 M Z +DURKIN D ER1 K IH0 N +DURLAND D ER1 L AH0 N D +DURLEY D ER1 L IY0 +DURLING D ER1 L IH0 NG +DURN D ER1 N +DURNELL D ER1 N AH0 L +DURNEY D ER1 N IY0 +DURNIL D ER1 N AH0 L +DURNIN D ER1 N IH0 N +DURNING D ER1 N IH0 NG +DURO D UH1 R OW2 +DUROCHER D Y UW1 R AH0 K ER0 +DURON D Y UW1 R AH0 N +DUROSS D Y UW1 R AH0 S +DURR D ER1 +DURRAH D UH1 R AH0 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IY2 N +ELEFANTE EH0 L EH0 F AA1 N T EH2 +ELEGANCE EH1 L AH0 G AH0 N S +ELEGANT EH1 L AH0 G AH0 N T +ELEGANTLY EH1 L IH0 G AH0 N T L IY2 +ELEGY EH1 L AH0 JH IY2 +ELEK EH1 L IH0 K +ELEKTRA EH0 L EH1 K T R AH0 +ELEKTRISK IH0 L EH2 K T R IH1 S K +ELEKTRIZITAETSWERK EH2 L IH0 K T R IH1 Z IH0 T AE2 T S W ER0 K +ELEKTRON IH0 L EH1 K T R AA0 N +ELEMENT EH1 L AH0 M AH0 N T +ELEMENTAL EH2 L AH0 M EH1 N T AH0 L +ELEMENTAL(1) EH2 L AH0 M EH1 N AH0 L +ELEMENTARY EH2 L AH0 M EH1 N T R IY0 +ELEMENTARY(1) EH2 L AH0 M EH1 N T ER0 R IY0 +ELEMENTARY(2) EH2 L AH0 M EH1 N CH R IY0 +ELEMENTS EH1 L AH0 M AH0 N T S +ELENA EH1 L AH0 N AA0 +ELENA(1) EH2 L EY1 N AA0 +ELENA'S EH1 L AH0 N AA0 Z +ELENBAAS EH1 L IH0 N B AA0 Z +ELENE EH1 L IY0 N +ELENORE EH1 L IH0 N ER0 +ELEONORE EH0 L IY0 AH0 N AO1 R IY0 +ELEPHANT EH1 L AH0 F AH0 N T +ELEPHANT'S EH1 L AH0 F AH0 N T S +ELEPHANTIASIS EH2 L IH0 F AH0 N T AY1 AH0 S IH0 S +ELEPHANTINE EH2 L AH0 F AE1 N T IY2 N +ELEPHANTS EH1 L AH0 F AH0 N T S +ELEPHANTS' EH1 L AH0 F AH0 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JH IY1 +G.'S JH IY1 Z +G.S JH IY1 Z +GA G AA1 +GA(1) JH IY1 EY1 +GA(2) JH AO1 R JH AH0 +GAAL G AA1 L +GAAR G AA1 R +GAARDER G AA1 R D ER0 +GAB G AE1 B +GABA G AA1 B AH0 +GABALDON G AA0 B AA0 L D AO1 N +GABARDINE G AE1 B ER0 D IY2 N +GABARDINES G AE1 B ER0 D IY2 N Z +GABAY G AE1 B EY0 +GABBARD G AH0 B AA1 R D +GABBERT G AE1 B ER0 T +GABBING G AE1 B IH0 NG +GABBRO G AE1 B R OW0 +GABBROIC G AE0 B R OW1 IH0 K +GABBY G AE1 B IY0 +GABE G EY1 B +GABEHART G EY1 B HH AA2 R T +GABEIRA G AH0 B EY1 R AH0 +GABEL G AH0 B EH1 L +GABELE G AH0 B EH1 L EY0 +GABELLI G AH0 B EH1 L IY0 +GABER G EY1 B ER0 +GABERT G AE1 B ER0 T +GABHART G AE1 B HH AA2 R T +GABIE G AE1 B IY0 +GABLE G EY1 B AH0 L +GABLED G EY1 B AH0 L D +GABLER G EY1 B AH0 L ER0 +GABLER(1) G EY1 B L ER0 +GABLES G EY1 B AH0 L Z +GABON G AH0 B AA1 N +GABOR G AH0 B AO1 R +GABORIAULT G AE1 B OW0 R IY2 OW2 +GABOURY G AE1 B UH0 R IY0 +GABRALL G EY1 B R AH0 L +GABRALL'S G EY1 B R AH0 L Z +GABRIEL G EY1 B R IY0 AH0 L +GABRIEL'S G EY1 B R IY0 AH0 L Z +GABRIELA G AA2 B R IY0 EH1 L AA2 +GABRIELE G AA2 B R IY0 EH1 L AH0 +GABRIELLA G AA2 B R IY0 EH1 L AA2 +GABRIELLE G AA2 B R IY0 EH1 L +GABRIELLI G AA2 B R IY0 EH1 L IY2 +GABRIELSEN G AE1 B R IY0 L S AH0 N +GABRIELSEN(1) G EY1 B R IY0 EH0 L S AH0 N +GABRIELSON G AE1 B R IY0 L S AH0 N +GABRIELSON(1) G EY1 B R IY0 EH0 L S AH0 N +GABROWNY G AA0 B R AW1 N IY2 +GABRYS G AE1 B ER0 IY0 Z +GABY G AE1 B IY0 +GACCIONE G AA0 K CH OW1 N IY2 +GACEK G AA1 CH EH2 K +GACH G AE1 CH +GACY G EY1 S IY2 +GACY'S G EY1 S IY2 Z +GAD G AE1 D +GADBERRY G AE1 D B EH2 R IY2 +GADBOIS G AE1 D B W AA2 +GADD G AE1 D +GADDIE G AE1 D IY0 +GADDING G AE1 D IH0 NG +GADDIS G AE1 D IH0 S +GADDUM G AE1 D AH0 M +GADDY G AE1 D IY0 +GADE G EY1 D +GADFLIES G AE1 D F L AY2 Z +GADFLY G AE1 D F L AY2 +GADGET G AE1 JH AH0 T +GADGET'S G AE1 JH AH0 T S +GADGETRY G AE1 JH AH0 T R IY0 +GADGETS G AE1 JH AH0 T S +GADHAFI G AH0 D AA1 F IY0 +GADHAFI(1) G AH0 D HH AA1 F IY0 +GADHAFI'S G AH0 D AA1 F IY0 Z +GADHAFI'S(1) G AH0 D HH AA1 F IY0 Z +GADOMSKI G AH0 D AA1 M S K IY0 +GADOURY G AE1 D UH0 R IY0 +GADS G AE1 D Z +GADSBY G AE1 D Z B IY0 +GADSDEN G AE1 D Z D AH0 N +GADSON G AE1 D S AH0 N +GADWAY G AE1 D W EY2 +GADZINSKI G AH0 JH IH1 N S K IY0 +GAE G AY1 +GAEA G IY1 AH0 +GAEBEL G EH1 B AH0 L +GAEDE G IY1 D +GAEL G EY1 L +GAELIC G EY1 L IH0 K +GAERTNER G EH1 R T N ER0 +GAETA G IY1 T AH0 +GAETANO G AY0 T AA1 N OW0 +GAETH G IY1 TH +GAETZ G IY1 T S +GAF G AE1 F +GAFF G AE1 F +GAFFE G AE1 F +GAFFES G AE1 F S +GAFFEY G AE1 F IY0 +GAFFIN G AE1 F IH0 N +GAFFNEY G AE1 F N IY0 +GAFFORD G AE1 F ER0 D +GAG G AE1 G +GAGA G AA1 G AH2 +GAGAN G EY1 G AH0 N +GAGAN(1) G AA2 G AA1 N +GAGARIN G AH0 G AE1 R AH0 N +GAGE G EY1 JH +GAGEL G AE1 G AH0 L +GAGEN G AE1 G AH0 N +GAGER G EY1 G ER0 +GAGGED G AE1 G D +GAGGLE G AE1 G AH0 L +GAGLIANO G AA0 G L IY0 AA1 N OW0 +GAGLIANO(1) G AE0 G L IY0 AA1 N OW0 +GAGLIARDI G AA0 G L IY0 AA1 R D IY0 +GAGLIARDI(1) G AE0 G L IY0 AA1 R D IY0 +GAGLIARDO G AA0 G L IY0 AA1 R D OW0 +GAGLIARDO(1) G AE0 G L IY0 AA1 R D OW0 +GAGLIO G AE1 G L IY0 OW0 +GAGLIONE G AA0 G L IY0 OW1 N IY0 +GAGLIONE(1) G AE0 G L IY0 OW1 N IY0 +GAGNE G EY1 N IY0 +GAGNE(1) G AE1 G N IY0 +GAGNER G AE1 G N ER0 +GAGNIER G AE1 G N IY0 ER0 +GAGNON G AE1 N Y AH0 N +GAGS G AE1 G Z +GAHAGAN G AA0 HH AA1 G AA0 N +GAHAN G AE1 HH AH0 N +GAHLI G AA1 L IY0 +GAHM G AE1 M +GAHN G AE1 N +GAHR G AA1 R +GAI G EY1 +GAIA G AY1 AH0 +GAIDAR G AY1 D AA2 R +GAIDAR'S G AY1 D AA2 R Z +GAIER G EY1 ER0 +GAIGE G EY1 JH +GAIL G EY1 L +GAIL'S G EY1 L Z +GAILE G EY1 L +GAILEY G EY1 L IY0 +GAILLARD G EY1 L ER0 D +GAILY G EY1 L IY0 +GAIN G EY1 N +GAINED G EY1 N D +GAINER G EY1 N ER0 +GAINERS G EY1 N ER0 Z +GAINES G EY1 N Z +GAINESVILLE G EY1 N Z V IH2 L +GAINEY G EY1 N IY0 +GAINFUL G EY1 N F AH0 L +GAINFULLY G EY1 N F AH0 L IY0 +GAINING G EY1 N IH0 NG +GAINOR G EY1 N ER0 +GAINOUS G EY1 N AH0 S +GAINS G EY1 N Z +GAINSAY G EY1 N S EY2 +GAINSBORO G EY1 N Z B ER0 OW0 +GAINSCO G EY1 N S K OW0 +GAIR G EH1 R +GAISER G EY1 Z ER0 +GAIT G EY1 T +GAITAN G AY2 T AA1 N +GAITER G EY1 T ER0 +GAITHER G EY1 TH ER0 +GAITHERSBURG G EY1 TH ER0 Z B ER0 G +GAITSKILL G EY1 T S K IH1 L +GAJDA G AY1 D AH0 +GAJEWSKI G AY0 EH1 F S K IY0 +GAL G AE1 L +GALA G AE1 L AH0 +GALA(1) G EY1 L AH0 +GALACTIC G AH0 L AE1 K T IH0 K +GALACTICA G AH0 L AE1 K T IH2 K AH0 +GALACTOSE G AH0 L AE1 K T OW0 S +GALAHAD G AE1 L AH0 HH AE2 D +GALAMBOS G AA0 L AA1 M B OW0 Z +GALAN G EY1 L AH0 N +GALANE G AH0 L EY1 N +GALANG G AE1 L AH0 NG +GALANIS G AH0 L AA1 N IH0 S +GALANOS G AH0 L AA1 N OW0 S +GALANT G AA1 L AH0 N T +GALANTE G AA0 L AA1 N T IY0 +GALANTER G AH0 L AE1 N T ER0 +GALANTI G AH0 L AE1 N T IY0 +GALAPAGOS G AH0 L AA1 P AH0 G OW0 Z +GALARNEAU G AE1 L AA0 R N OW2 +GALARZA G AH0 L AA1 R Z AH0 +GALAS G EY1 L AH0 Z +GALASIE G AE1 L AH0 S IY0 +GALASSI G AA0 L AA1 S IY0 +GALASSO G AA0 L AA1 S OW0 +GALATAS G AA0 L AA1 T AA0 Z +GALATEA G AE2 L AH0 T IY1 AH0 +GALATI G AA0 L AA1 T IY0 +GALAVIZ G AE1 L AH0 V IH0 Z +GALAX G AE1 L AE2 K S +GALAXIES G AE1 L AH0 K S IY0 Z +GALAXY G AE1 L AH0 K S IY0 +GALAXY'S G AE1 L AH0 K S IY0 Z +GALBAN G AE1 L B AH0 N +GALBO G AE1 L B OW0 +GALBRAITH G AE1 L B R EY2 TH +GALBREATH G AE1 L B R EH2 TH +GALE G EY1 L +GALE'S G EY1 L Z +GALEA G EY1 L IY0 AH0 +GALEANO G AA0 L IY1 N OW0 +GALEB G AE1 L AH0 B +GALEB(1) G EY1 L AH0 B +GALEBS G AE1 L AH0 B Z +GALEBS(1) G EY1 L AH0 B Z +GALEF G AE1 L AH0 F +GALEN G EY1 L AH0 N +GALEN'S G EY1 L AH0 N Z +GALENA G AH0 L IY1 N AH0 +GALENICAL G AH0 L EH1 N IH0 K AH0 L +GALENTINE G AA0 L EH0 N T IY1 N IY0 +GALER G EY1 L ER0 +GALERIA G AE2 L ER0 IY1 AH0 +GALERIAS G AE2 L ER0 IY1 AH0 Z +GALERIES G AE1 L ER0 IY0 Z +GALERNTER G AH0 L ER1 N T ER0 +GALES G EY1 L Z +GALESBURG G EY1 L Z B ER0 G +GALESI G AH0 L EH1 S IY0 +GALEY G EY1 L IY0 +GALFORD G AE1 L F ER0 D +GALGANO G AA0 L G AA1 N OW0 +GALI G AA1 L IY0 +GALI'S G AA1 L IY0 Z +GALIANO G AA0 L IY0 AA1 N OW0 +GALICIA G AH0 L IH1 SH IY0 AH0 +GALIE G EY1 L IY0 +GALIENA G AA0 L IY1 N AH0 +GALIK G AE1 L IH0 K +GALILEAN G AE2 L AH0 L IY1 AH0 N +GALILEE G AE1 L AH0 L IY2 +GALILEO G AE2 L AH0 L IY1 OW0 +GALILEO(1) G AE2 L AH0 L EY1 OW0 +GALILEO'S G AE2 L AH0 L IY1 OW0 Z +GALILEO'S(1) G AE2 L AH0 L EY1 OW0 Z +GALIN G AE1 L IH0 N +GALINA G AH0 L IY1 N AH0 +GALINDO G AA0 L IY1 N D OW0 +GALINSKI G AH0 L IH1 N S K IY0 +GALINSKY G AH0 L IH1 N S K IY0 +GALIOTO G AA0 L IY0 OW1 T OW0 +GALIPAULT G AE1 L IH0 P AO2 L T +GALIPAULT(1) G AE1 L IH0 P OW2 +GALIPEAU G AE1 L IH0 P OW2 +GALITSIN G AH0 L IH1 T S IH0 N +GALKA G AE1 L K AH0 +GALL G AO1 L +GALLA G AE1 L AH0 +GALLACHER G AE1 L AH0 K ER0 +GALLAGER G AO1 L IH0 JH ER0 +GALLAGHER G AE1 L AH0 G ER0 +GALLAHAN G AE1 L AH0 HH AE0 N +GALLAHER G AE1 L AH0 HH ER0 +GALLAMORE G AA0 L AA1 M AO0 R +GALLAND G AE1 L AH0 N D +GALLANT G AE1 L AH0 N T +GALLANTLY G AE1 L AH0 N T L IY0 +GALLANTRY G AE1 L AH0 N T R IY0 +GALLARD G AH0 L AA1 R D +GALLARDO G AA0 L AA1 R D OW0 +GALLAS G AE1 L AH0 Z +GALLATIN G AE1 L AH0 T IH0 N +GALLAUDET G AE1 L AH0 D EH0 T +GALLAWAY G AO1 L AH0 W EY2 +GALLBLADDER G AO1 L B L AE2 D ER0 +GALLE G EY1 L +GALLE(1) G AE2 L EY1 +GALLEGO G AA0 L EH1 G OW0 +GALLEGOS G AE1 L IH0 G OW0 Z +GALLEMORE G AA0 L EH1 M AO0 R +GALLEN G AO1 L AH0 N +GALLENTINE G AA0 L EH0 N T IY1 N IY0 +GALLEON G AE1 L IY0 AH0 N +GALLEONS G AE1 L IY0 AH0 N Z +GALLER G AO1 L ER0 +GALLERANI G AA0 L ER0 AA1 N IY0 +GALLERIA G AE2 L ER0 IY1 AH0 +GALLERIES G AE1 L ER0 IY0 Z +GALLERY G AE1 L ER0 IY0 +GALLERY'S G AE1 L ER0 IY0 Z +GALLES G EY1 L Z +GALLET G AE1 L IH0 T +GALLETTI G AA0 L EH1 T IY0 +GALLEY G AE1 L IY0 +GALLEYS G AE1 L IY0 Z +GALLI G AE1 L IY0 +GALLIA G AE1 L Y AH0 +GALLIANO G AA0 L IY0 AA1 N OW0 +GALLIC G AE1 L IH0 K +GALLICK G AE1 L IH0 K +GALLIEN G AH0 L IY1 N +GALLIER G AE1 L IY0 ER0 +GALLIGAN G AE1 L IH0 G AH0 N +GALLIHER G AE1 L IH0 HH ER0 +GALLIK G AE1 L IH0 K +GALLIMARD G AE1 L IH0 M ER0 D +GALLIMORE G AA0 L IY1 M AO0 R +GALLINA G AA0 L IY1 N AH0 +GALLING G AO1 L IH0 NG +GALLINGER G AO1 L IH0 NG ER0 +GALLINSKY G AH0 L IH1 N S K IY0 +GALLION G AE1 L Y AH0 N +GALLIUM G AE1 L IY0 AH0 M +GALLIVAN G AE1 L IH0 V AH0 N +GALLMAN G AO1 L M AH0 N +GALLO G AE1 L OW0 +GALLO'S G AE1 L OW0 Z +GALLOGLY G AE1 L AH0 G L IY0 +GALLON G AE1 L AH0 N +GALLONS G AE1 L AH0 N Z +GALLOON G AH0 L UW1 N +GALLOP G AE1 L AH0 P +GALLOPED G AE1 L AH0 P T +GALLOPING G AE1 L AH0 P IH0 NG +GALLOS G AE1 L OW0 Z +GALLOW G AE1 L OW0 +GALLOWAY G AE1 L OW0 W EY2 +GALLOWAYS G AE1 L OW0 W EY2 Z +GALLOWS G AE1 L OW0 Z +GALLS G AO1 L Z +GALLSTONE G AO1 L S T OW2 N +GALLSTONES G AA1 L S T OW2 N Z +GALLSTONES(1) G AO1 L S T OW2 N Z +GALLUCCI G AA0 L UW1 CH IY0 +GALLUCCIO G AA0 L UW1 CH IY0 OW0 +GALLUP G AE1 L AH0 P +GALLUS G AE1 L AH0 S +GALLUZZO G AA0 L UW1 Z OW0 +GALLWAY G AO1 L W EY2 +GALOOB G AH0 L UW1 B +GALOOB'S G AH0 L UW1 B Z +GALORE G AH0 L AO1 R +GALOSH G AH0 L AA1 SH +GALOSHES G AH0 L AA1 SH AH0 Z +GALOSHES(1) G AH0 L AA1 SH IH0 Z +GALOTTI G AH0 L AA1 T IY0 +GALPIN G AE1 L P IH0 N +GALS G AE1 L Z +GALSTER G AE1 L S T ER0 +GALSWORTHY G AE1 L Z W ER2 DH IY0 +GALT G AO1 L T +GALTON G AE1 L T AH0 N +GALUDET G AE2 L AH0 D EH1 T +GALUS G AE1 L IH0 S +GALUSHA G AE1 L AH0 SH AH0 +GALUSKA G AH0 L AH1 S K AH0 +GALVAN G AA0 L V AA1 N +GALVANIC G AE0 L V AE1 N IH0 K +GALVANIZE G AE1 L V AH0 N AY2 Z +GALVANIZED G AE1 L V AH0 N AY2 Z D +GALVANIZES G AE1 L V AH0 N AY2 Z AH0 Z +GALVANIZING G AE1 L V AH0 N AY2 Z IH0 NG +GALVEN G AA1 L V AH0 N +GALVESTON G AE1 L V AH0 S T AH0 N +GALVEZ G AA0 L V EH1 Z +GALVIN G AE1 L V IH0 N +GALVIN'S G AE1 L V IH0 N Z +GALWAY G AA1 L W EY0 +GALYEAN G AE1 L IY0 AH0 N +GALYEN G AE1 L IY0 EH0 N +GALYON G AE1 L IY0 AA0 N +GAMA G AA1 M AH0 +GAMACHE G AA1 M EY0 K +GAMAGE G AE1 M IH0 JH +GAMAL G AH0 M AA1 L +GAMBA G AE1 M B AH0 +GAMBALE G AA0 M B AA1 L IY0 +GAMBARDELLA G AA0 M B AA0 R D EH1 L AH0 +GAMBER G AE1 M B ER0 +GAMBIA G AE1 M B IY0 AH0 +GAMBILL G AH0 M B IH1 L +GAMBINO G AE0 M B IY1 N OW0 +GAMBIT G AE1 M B IH0 T +GAMBITS G AE1 M B AH0 T S +GAMBLE G AE1 M B AH0 L +GAMBLE'S G AE1 M B AH0 L Z +GAMBLED G AE1 M B AH0 L D +GAMBLER G AE1 M B L ER0 +GAMBLER'S G AE1 M B L ER0 Z +GAMBLERS G AE1 M B L ER0 Z +GAMBLES G AE1 M B AH0 L Z +GAMBLIN G AE1 M B L IH0 N +GAMBLING G AE1 M B AH0 L IH0 NG +GAMBLING(1) G AE1 M B L IH0 NG +GAMBLING'S G AE1 M B L IH0 NG Z +GAMBOA G AA0 M B OW1 AH0 +GAMBONE G AA1 M B OW0 N +GAMBREL G AE1 M B R AH0 L +GAMBRELL G AE1 M B R AH0 L +GAMBRILL G AE1 M B R IH0 L +GAMBRO G AE1 M B R OW0 +GAMCO G AE1 M K OW0 +GAME G EY1 M +GAME'S G EY1 M Z +GAMECOCK G EY1 M K AO2 K +GAMECOCKS G EY1 M K AO2 K S +GAMEKEEPER G EY1 M K IY2 P ER0 +GAMEKEEPERS G EY1 M K IY2 P ER0 S +GAMEL G AA1 M AH0 L +GAMELIN G AE1 M IH0 L IH0 N +GAMELIN(1) G AE1 M L IH0 N +GAMELLO G AH0 M EH1 L OW0 +GAMELY G EY1 M L IY0 +GAMEPLAY G EY1 M P L EY2 +GAMER G EY1 M ER0 +GAMERS G EY1 M ER0 Z +GAMES G EY1 M Z +GAMES' G EY1 M Z +GAMESHOW G EY1 M SH OW2 +GAMESHOWS G EY1 M SH OW2 Z +GAMESMAN G EY1 M Z M AE2 N +GAMESMANSHIP G EY1 M Z M AH0 N SH IH2 P +GAMEST G EY1 M AH0 S T +GAMET G AE1 M IH0 T +GAMETANGIA G AE2 M AH0 T AE1 N JH IY0 AH0 +GAMETE G AE1 M IY0 T +GAMETE(1) G AH0 M IY1 T +GAMETOPHYTE G AH0 M IY1 T AH0 F AY2 T +GAMEZ G AA0 M EH1 Z +GAMING G EY1 M IH0 NG +GAMING'S G EY1 M IH0 NG Z +GAMINO G AA0 M IY1 N OW0 +GAMM G AE1 M +GAMMA G AE1 M AH0 +GAMMAGE G AE1 M IH0 JH +GAMMAL G AH0 M AA1 L +GAMMEL G AE1 M AH0 L +GAMMELL G AE1 M AH0 L +GAMMILL G AE1 M IH0 L +GAMMON G AE1 M AH0 N +GAMMONS G AE1 M AH0 N Z +GAMONS G AE1 M AH0 N Z +GAMP G AE1 M P +GAMPER G AE1 M P ER0 +GAMSAKHURDIA G AE0 M S AH0 K ER1 D IY0 AH0 +GAMSAKHURDIA(1) G AE0 M S AH0 K ER1 D Y AH0 +GAMUNDE G AH0 M UW1 N D +GAMUNDE'S G AH0 M UW1 N D Z +GAMUT G AE1 M AH0 T +GAN G AE1 N +GANANOQUE G AH0 N AE1 N AH0 K +GANAS G AE1 N AH0 Z +GANATIEUGANAUF G AH0 N EY1 SH AH0 G AE2 N AH0 L F +GANAWAY G AE1 N AH0 W EY0 +GANCARZ G AA1 N K AA0 R Z +GANCI G AE1 N S IY0 +GANDA G AE1 N D AH0 +GANDALF G AE1 N D AO0 L F +GANDALF'S G AE1 N D AO0 L F S +GANDARA G AA0 N D AA1 R AH0 +GANDEE G AE1 N D IY0 +GANDER G AE1 N D ER0 +GANDERS G AE1 N D ER0 Z +GANDHI G AA1 N D IY0 +GANDHI'S G AA1 N D IY0 Z +GANDOLFI G AA0 N D OW1 L F IY0 +GANDOLFO G AA0 N D OW1 L F OW0 +GANDY G AE1 N D IY0 +GANEM G AE1 N IH0 M +GANES G EY1 N Z +GANEY G EY1 N IY0 +GANG G AE1 NG +GANG'S G AE1 NG Z +GANGBANGER G AE1 NG B AE0 NG G ER0 +GANGBANGERS G AE1 NG B AE0 NG G ER0 Z +GANGBUSTER G AE1 NG B AH2 S T ER0 +GANGBUSTERS G AE1 NG B AH2 S T ER0 Z +GANGE G AE1 N JH +GANGEMI G AA0 NG G EH1 M IY0 +GANGER G AE1 NG ER0 +GANGES G AE1 N JH IY0 Z +GANGI G AE1 N JH IY0 +GANGING G AE1 NG IH0 NG +GANGL G AE1 NG G AH0 L +GANGLIA G AE1 NG G L IY0 AA0 +GANGLION G AE1 NG G L IY0 AA0 N +GANGLIONIC G AE2 NG G L IY0 AA1 N IH0 K +GANGLOFF G AE1 NG G L AO0 F +GANGLY G AE1 NG L IY0 +GANGPLANK G AE1 NG P L AE2 NG K +GANGRENE G AE1 N G R IY0 N +GANGS G AE1 NG Z +GANGSTA G AE1 NG S T AH0 +GANGSTER G AE1 NG S T ER0 +GANGSTERS G AE1 NG S T ER0 Z +GANGWER G AE1 NG W ER0 +GANIC G AE1 N IH0 K +GANIM G AE1 N IH0 M +GANIS G AE1 N IH0 S +GANLEY G AE1 N L IY0 +GANN G AE1 N +GANNAWAY G AE1 N AH0 W EY0 +GANNETT G AE1 N IH0 T +GANNETT'S G AE1 N AH0 T S +GANNON G AE1 N AH0 N +GANO G AA1 N OW0 +GANOE G AE1 N OW0 +GANONG G AE1 N AO0 NG +GANS G AE1 N Z +GANSEN G AE1 N S AH0 N +GANSER G AE1 N S ER0 +GANSKE G AE1 N S K +GANSON G AE1 N S AH0 N +GANSTER G AE1 N S T ER0 +GANT G AE1 N T +GANTENBEIN G AE1 N T IH0 N B AY0 N +GANTER G AE1 N T ER0 +GANTLET G AO1 N T L AH0 T +GANTNER G AE1 N T N ER0 +GANTOS G AE1 N T OW0 S +GANTRY G AE1 N T R IY0 +GANTT G AE1 N T +GANTZ G AE1 N T S +GANUS G EY1 N IH0 S +GANYMEDE G AE1 N AH0 M IY2 D +GANZ G AE1 N Z +GANZEL G AE1 N Z AH0 L +GANZER G AE1 N Z ER0 +GAO G AW1 +GAONA G AA0 OW1 N AH0 +GAP G AE1 P +GAP'S G AE1 P S +GAPE G EY1 P +GAPING G EY1 P IH0 NG +GAPINSKI G AH0 P IH1 N S K IY0 +GAPP G AE1 P +GAPPA G AE1 P AH0 +GAPS G AE1 P S +GAR G AA1 R +GARA G AE1 R AH0 +GARABEDIAN G AE2 R AH0 B IY1 D IY0 AH0 N +GARAFALO G AA0 R AA0 F AA1 L OW0 +GARAFOLA G AA0 R AA0 F OW1 L AH0 +GARAGE G ER0 AA1 ZH +GARAGES G ER0 AA1 ZH IH0 Z +GARAGIOLA G ER0 AE2 JH IY0 OW1 L AH0 +GARAGIOLA(1) G EH2 R AH0 JH IY0 OW1 L AH0 +GARAJDA G ER0 AA1 ZH D AH0 +GARAJDA(1) G AO0 R AA1 ZH D AH0 +GARAJDA'S G ER0 AA1 ZH D AH0 Z +GARAJDA'S(1) G AO0 R AA1 ZH D AH0 Z +GARAMENDI G EH2 R AH0 M EH1 N D IY0 +GARAMENDI'S G EH2 R AH0 M EH1 N D IY0 Z +GARAND G AE1 R AH0 N D +GARANT G AA1 R AH0 N T +GARARD G ER0 AA1 R D +GARAVAGLIA G AA0 R AA0 V AA1 G L IY0 AH0 +GARAY G AE1 R EY0 +GARB G AA1 R B +GARBACZ G AA1 R B AH0 CH +GARBAGE G AA1 R B IH0 JH +GARBARINI G AA0 R B AA0 R IY1 N IY0 +GARBARINO G AA0 R B AA0 R IY1 N OW0 +GARBE G AA1 R B +GARBED G AA1 R B D +GARBER G AA1 R B ER0 +GARBERS G AA1 R B ER0 Z +GARBETT G AA1 R B IH0 T +GARBLE G AA1 R B AH0 L +GARBLED G AA1 R B AH0 L D +GARBLES G AA1 R B AH0 L Z +GARBLING G AA1 R B L IH0 NG +GARBO G AA1 R B OW0 +GARBUTT G AA1 R B AH0 T +GARCEAU G AA0 R S OW1 +GARCES G AA1 R S EH0 S +GARCETTI G AA2 R CH EH1 T IY0 +GARCETTI'S G AA2 R CH EH1 T IY0 Z +GARCIA G AA2 R S IY1 AH0 +GARCIA'S G AA0 R S IY1 AH0 Z +GARCIAS G AA0 R S IY1 AH0 Z +GARCZYNSKI G ER0 CH IH1 N S K IY0 +GARD G AA1 R D +GARDA G AA1 R D AH0 +GARDE G AA1 R D +GARDEA G AA1 R D IY0 AH0 +GARDELLA G AA2 R D EH1 L AH0 +GARDEN G AA1 R D AH0 N +GARDEN'S G AA1 R D AH0 N Z +GARDENA G AA0 R D IY1 N AH0 +GARDENAMERICA G AA2 R D AH0 N AH0 M EH1 R IH0 K AH0 +GARDENED G AA1 R D AH0 N D +GARDENER G AA1 R D AH0 N ER0 +GARDENER'S G AA1 R D AH0 N ER0 Z +GARDENERS G AA1 R D AH0 N ER0 Z +GARDENERS(1) G AA1 R D N ER0 Z +GARDENHIRE G AA1 R D AH0 N HH AY2 R +GARDENIA G AA0 R D IY1 N Y AH0 +GARDENIAS G AA0 R D IY1 N Y AH0 Z +GARDENING G AA1 R D AH0 N IH0 NG +GARDENING(1) G AA1 R D N IH0 NG +GARDENS G AA1 R D AH0 N Z +GARDIN G AA1 R D IH0 N +GARDINER G AA1 R D N ER0 +GARDINI G AA0 R D IY1 N IY0 +GARDINI'S G AA0 R D IY1 N IY0 Z +GARDINIER G AA1 R D IH0 N IY0 ER0 +GARDINIER(1) G AA1 R D IH0 N Y ER0 +GARDNER G AA1 R D N ER0 +GARDNER'S G AA1 R D N ER0 Z +GARDOLIN G AA1 R D OW0 L IH0 N +GARDOLIN'S G AA1 R D OW0 L IH0 N Z +GARDUNO G AA0 R D UW1 N OW0 +GARDYNE G AA1 R D AY2 N +GARE G EH1 R +GAREAU G ER0 OW1 +GARED G AE1 R AH0 D +GARELICK G AE1 R IH0 L IH0 K +GARETH G EH1 R IH0 TH +GARETT G AE1 R IH0 T +GAREY G AE1 R IY0 +GARFIELD G AA1 R F IY2 L D +GARFINKEL G AA1 R F IH0 NG K AH0 L +GARFINKLE G AA1 R F IH2 NG K AH0 L +GARFUNKEL G AA1 R F AH0 NG K AH0 L +GARG G AA1 R G +GARGAN G AA1 R G AH0 N +GARGANO G AA0 R G AA1 N OW0 +GARGANTUAN G AA0 R G AE1 N CH UW0 AH0 N +GARGER G AA1 R G ER0 +GARGES G AA1 R JH IH0 Z +GARGILL G AA1 R JH IH0 L +GARGIS G AA1 R G IH0 S +GARGIULO G AA1 R JH UW0 L OW0 +GARGOYLE G AA1 R G OY2 L +GARGOYLES G AA1 R G OY2 L Z +GARGUILO G AA0 R G W IY1 L OW0 +GARGUS G AA1 R G AH0 S +GARI G AA1 R IY0 +GARIBALDI G AE2 R AH0 B AO1 L D IY0 +GARIBAY G AE1 R IH0 B EY0 +GARIEPY G ER0 IY1 P IY0 +GARIN G EH1 R IH0 N +GARING G EH1 R IH0 NG +GARINGER G EH1 R IH0 NG ER0 +GARIS G AE1 R IH0 S +GARISH G EH1 R IH0 SH +GARISSA G AH0 R IH1 S AH0 +GARITY G AE1 R IH0 T IY0 +GARL G AA1 R L +GARLAN G AA1 R L AH0 N +GARLAND G AA1 R L AH0 N D +GARLIC G AA1 R L IH0 K +GARLICK G AA1 R L IH0 K +GARLICKY G AA1 R L IH0 K IY0 +GARLING G AA1 R L IH0 NG +GARLINGER G AA1 R L IH0 NG ER0 +GARLINGHOUSE G AA1 R L IH0 NG HH AW2 S +GARLINGTON G AA1 R L IH0 NG T AH0 N +GARLITZ G AA1 R L IH0 T S +GARLOCK G AA1 R L AH0 K +GARLOW G AA1 R L OW0 +GARMAN G AA1 R M AH0 N +GARMANY G ER0 M AO1 N IY0 +GARMENT G AA1 R M AH0 N T +GARMENTS G AA1 R M AH0 N T S +GARMON G AA1 R M AH0 N +GARMOND G AA1 R M AH0 N D +GARMS G AA1 R M Z +GARMUND G AA1 R M AH0 N D +GARN G AA1 R N +GARNEAU G AA0 R N OW1 +GARNELL G AA0 R N EH1 L +GARNER G AA1 R N ER0 +GARNERED G AA1 R N ER0 D +GARNERING G AA1 R N ER0 IH0 NG +GARNERS G AA1 R N ER0 Z +GARNES G AA1 R N Z +GARNET G AA1 R N AH0 T +GARNETT G AA1 R N IH0 T +GARNETTE G AA0 R N EH1 T +GARNEY G AA1 R N IY0 +GARNICA G AA0 R N IY1 K AH0 +GARNIER G AA1 R N IY0 ER0 +GARNISH G AA1 R N IH0 SH +GARNISHED G AA1 R N IH0 SH T +GARNISHES G AA1 R N IH0 SH AH0 Z +GARNISHMENT G AA1 R N IH0 SH M AH0 N T +GARNO G AA1 R N OW0 +GARNOCK G AA1 R N AH0 K +GARNSEY G AA1 R N S IY0 +GARO G EH1 R OW0 +GAROFALO G AA0 R OW0 F AA1 L OW0 +GAROFANO G AA0 R OW0 F AA1 N OW0 +GAROFOLO G EH0 R AH0 F OW1 L AH0 +GAROLS G AE1 R AO0 L Z +GARON G AA0 R AO1 N +GARONE G ER0 OW1 N +GARONZIK G AH0 R AO1 N Z IH0 K +GAROUTTE G ER0 UW1 T +GARP G AA1 R P +GARP'S G AA1 R P S +GARPS G AA1 R P S +GARR G AE1 R +GARRABRANT G AA0 R AA1 B R AH0 N T +GARRAHAN G AE1 R AH0 HH AE0 N +GARRAMONE G AE1 R AH0 M OW2 N +GARRARD G AE1 R ER0 D +GARRATT G EH1 R AH0 T +GARRAWAY G AE1 R AH0 W EY0 +GARRELL G AA0 R EH1 L +GARRELS G AE1 R EH0 L Z +GARRELTS G AE1 R IH0 L T S +GARREN G AA1 R AH0 N +GARRET G EH1 R IH0 T +GARRET'S G EH1 R AH0 T S +GARRETS G EH1 R AH0 T S +GARRETSON G AE1 R IH0 T S AH0 N +GARRETT G AE1 R IH0 T +GARRETT(1) G EH1 R IH0 T +GARRETT'S G AE1 R IH0 T Z +GARRETT'S(1) G EH1 R IH0 T Z +GARRETTE G ER0 EH1 T +GARREY G AE1 R IY0 +GARRICK G EH1 R IH0 K +GARRIDO G AA0 R IY1 D OW0 +GARRIDO-LUNA G AA0 R IY1 D OW0 L UW1 N AH0 +GARRIGA G AE1 R IH0 G AH0 +GARRIGAN G AE1 R IH0 G AH0 N +GARRIGUES G AA0 R IY1 G EH0 S +GARRIGUS G AA0 R IY1 G IH0 S +GARRINGER G AE1 R IH0 NG ER0 +GARRIOTT G AE1 R IY0 AH0 T +GARRIS G AE1 R IH0 S +GARRISON G AE1 R IH0 S AH0 N +GARRISONED G AE1 R AH0 S AH0 N D +GARRITANO G AA0 R IY0 T AA1 N OW0 +GARRITT G AE1 R IH0 T +GARRITY G EH1 R IH0 T IY0 +GARRO G AA1 R OW0 +GARROD G AE1 R AH0 D +GARROL G AE1 R AH0 L +GARROLS G AE1 R AH0 L Z +GARRON G AE1 R AH0 N +GARRON'S G EH1 R AH0 N Z +GARROS G EH1 R OW0 S +GARROTT G AE1 R AH0 T +GARROW G EH1 R OW0 +GARROWAY G AE1 R OW0 W EY2 +GARROZ G AE1 R AH0 Z +GARRULOUS G EH1 R AH0 L AH0 S +GARRY G AE1 R IY0 +GARRY(1) G EH1 R IY0 +GARS G AA1 R Z +GARSIDE G AA1 R S AY2 D +GARSKE G AA1 R S K +GARSON G AA1 R S AH0 N +GARST G AA1 R S T +GARSTEN G AA1 R S T EH0 N +GARSTEN'S G AA1 R S T EH0 N Z +GARSTIN G AA1 R S T AH0 N +GARSTKA G AA1 R S T K AH0 +GARSTON G AA1 R S T AH0 N +GARTEN G AA1 R T AH0 N +GARTENBERG G AA1 R T AH0 N B ER0 G +GARTER G AA1 R T ER0 +GARTERS G AA1 R T ER0 Z +GARTH G AA1 R TH +GARTHWAITE G AA1 R TH W EY2 T +GARTIN G AA1 R T IH0 N +GARTLAND G AA1 R T L AH0 N D +GARTLEY G AA1 R T L IY0 +GARTMAN G AA1 R T M AH0 N +GARTMORE G AA1 R T M AO2 R +GARTNER G AA1 R T N ER0 +GARTON G AA1 R T AH0 N +GARTRELL G AA1 R T R AH0 L +GARTSIDE G AA1 R T S AY2 D +GARTZKE G AA1 R T S K +GARTZKE(1) G AA1 R T S K IY0 +GARUDA G AH0 R UW1 D AH0 +GARUDA'S G AH0 R UW1 D AH0 Z +GARVER G AA1 R V ER0 +GARVER'S G AA1 R V ER0 Z +GARVERICK G AA1 R V ER0 IH0 K +GARVEY G AA1 R V IY0 +GARVIE G AA1 R V IY0 +GARVIN G AA1 R V IH0 N +GARWIN G AA1 R W IH0 N +GARWOOD G AA1 R W UH2 D +GARY G EH1 R IY0 +GARY(1) G AE1 R IY0 +GARY'S G EH1 R IY0 Z +GARY'S(1) G AE1 R IY0 Z +GARZA G AA1 R Z AH0 +GARZARELLI G AA1 R Z ER0 EH2 L IY0 +GARZON G AA1 R Z AH0 N +GAS G AE1 S +GAS'S G AE1 S IH0 Z +GASAWAY G AE1 S AH0 W EY2 +GASBARRO G AA0 S B AA1 R OW0 +GASCA G AA1 S K AH0 +GASCON G AE1 S K AH0 N +GASCONS G AE1 S K AH0 N Z +GASE G EY1 Z +GASEOUS G AE1 S IY0 AH0 S +GASES G AE1 S AH0 Z +GASES(1) G AE1 S IH0 Z +GASH G AE1 SH +GASHED G AE1 SH T +GASHES G AE1 SH AH0 Z +GASICH G AE1 S IH0 K +GASICH(1) G EY1 Z IH0 K +GASIFICATION G AE2 S AH0 F AH0 K EY1 SH AH0 N +GASIFY G AE2 S AH0 F AY2 +GASIOR G AE1 S IY0 ER0 +GASIOROWSKI G AH0 S IY0 AO0 R AO1 F S K IY0 +GASKA G AA1 S K AH0 +GASKAMP G AE1 S K AE2 M P +GASKELL G AE1 S K AH0 L +GASKET G AE1 S K AH0 T +GASKETS G AE1 S K AH0 T S +GASKEY G AE1 S K IY2 +GASKILL G AE1 S K IH2 L +GASKIN G AE1 S K IH0 N +GASKINS G AE1 S K IH0 N Z +GASLIGHT G AE1 S L AY0 T +GASNER G AE1 S N ER0 +GASOHOL G AE1 S AH0 HH AO2 L +GASOLINE G AE1 S AH0 L IY2 N +GASOLINES G AE2 S AH0 L IY1 N Z +GASP G AE1 S P +GASPAR G AE1 S P ER0 +GASPARA G AH0 S P AA1 R AH0 +GASPARD G AH0 S P AA1 R D +GASPARI G AA0 S P AA1 R IY0 +GASPARINI G AA0 S P AA0 R IY1 N IY0 +GASPARRO G AA0 S P AA1 R OW0 +GASPE G AE1 S P IY0 +GASPED G AE1 S P T +GASPER G AE1 S P ER0 +GASPERINI G AA0 S P ER0 IY1 N IY0 +GASPING G AE1 S P IH0 NG +GASPS G AE1 S P S +GASQUE G EY1 S K +GASS G AE1 S +GASSAWAY G AE1 S AH0 W EY0 +GASSED G AE1 S T +GASSEE G AE1 S IY1 +GASSEN G AE1 S AH0 N +GASSER G AE1 S ER0 +GASSERT G AE1 S ER0 T +GASSES G AE1 S IH0 Z +GASSETT G AE1 S IH0 T +GASSING G AE1 S IH0 NG +GASSMAN G AE1 S M AH0 N +GASSMANN G AE1 S M AH0 N +GASSNER G AE1 S N ER0 +GAST G AE1 S T +GASTELLI G AH0 S T EH1 L IY0 +GASTER G AE1 S T ER0 +GASTILUM G EY1 S T IH0 L AH0 M +GASTINEAU G AE1 S T IH0 N OW2 +GASTON G AE1 S T AH0 N +GASTON'S G AE1 S T AH0 N Z +GASTONIA G AH0 S T OW1 N IY0 AH0 +GASTRIC G AE1 S T R IH0 K +GASTRITIS G AE0 S T R AY1 T AH0 S +GASTRO G AE1 S T R OW0 +GASTROINTESTINAL G AE2 S T R OW0 IH0 N T EH1 S T AH0 N AH0 L +GASTRONOMIC G AH0 S T R AA2 N AA1 M IH0 K +GASTRONOMY G AE0 S T R AA1 N AH0 M IY0 +GASTROSCOPE G AE1 S T R AH0 S K OW2 P +GASTROVASCULAR G AE2 S T R OW0 V AE1 S K Y AH0 L ER0 +GASTRULATE G AE1 S T R AH0 L EY2 T +GASTRULATION G AE2 S T R AH0 L EY1 SH AH0 N +GAT G AE1 T +GATCH G AE1 CH +GATCHEL G AE1 CH AH0 L +GATCHELL G AE1 CH AH0 L +GATE G EY1 T +GATEAU G AA0 T OW1 +GATED G EY1 T IH0 D +GATEKEEPER G EY1 T K IY2 P ER0 +GATEKEEPERS G EY1 T K IY2 P ER0 Z +GATELEY G AE1 T IH0 L IY0 +GATELEY(1) G EY1 T L IY0 +GATELY G EY1 T L IY0 +GATES G EY1 T S +GATES' G EY1 T S +GATES'S G EY1 T S IH0 Z +GATES'S(1) G EY1 T S +GATEWAY G EY1 T W EY2 +GATEWAY'S G EY1 T W EY2 Z +GATEWAYS G EY1 T W EY2 Z +GATEWOOD G EY1 T W UH2 D +GATH G AE1 TH +GATHER G AE1 DH ER0 +GATHERED G AE1 DH ER0 D +GATHERER G AE1 DH ER0 ER0 +GATHERERS G AE1 DH ER0 ER0 Z +GATHERING G AE1 DH ER0 IH0 NG +GATHERINGS G AE1 DH ER0 IH0 NG Z +GATHERS G AE1 DH ER0 Z +GATHINGS G AE1 TH IH0 NG Z +GATHMAN G AE1 TH M AH0 N +GATHRIGHT G AE1 TH R AY2 T +GATIEN G EY1 T Y EH0 N +GATING G EY1 T IH0 NG +GATLEY G AE1 T L IY0 +GATLIFF G AE1 T L IH0 F +GATLIN G AE1 T L IH0 N +GATLING G AE1 T L IH0 NG +GATLING'S G AE1 T L IH0 NG Z +GATOIL G AH0 T OY1 L +GATOR G EY1 T ER0 +GATORADE G AE1 T ER0 EY2 D +GATORS G EY1 T ER0 Z +GATOS G AA1 T OW2 S +GATOS(1) G AE1 T OW2 S +GATOS(2) G EY1 T OW2 S +GATOS(3) G EY1 T OW0 S +GATRELL G AE1 T R AH0 L +GATSBY G AE1 T S B IY0 +GATSON G AE1 T S AH0 N +GATT G AE1 T +GATTEN G AE1 T AH0 N +GATTI G AE1 T IY0 +GATTING G AE1 T IH0 NG +GATTIS G AE1 T IH0 S +GATTIS(1) G AE1 T IY0 Z +GATTON G AE1 T AH0 N +GATTUSO G AA0 T UW1 S OW0 +GATTY G AE1 T IY0 +GATWARD G AE1 T W ER0 D +GATWICK G AE1 T W IH2 K +GATWICK(1) G EY1 T W IH2 K +GATX G AE1 T EH2 K S +GATZ G AE1 T S +GATZA G AA1 T Z AH0 +GATZKE G AE1 T S K +GATZKE(1) G AE1 T S K IY0 +GAU G OW1 +GAUB G AO1 B +GAUBATZ G AW1 B AH0 T S +GAUBERT G AW1 B ER0 T +GAUBERT(1) G AW0 B EH1 R T +GAUBERT'S G AW1 B ER0 T S +GAUBERT'S(1) G AW0 B EH1 R T S +GAUCH G AO1 CH +GAUCHE G OW1 SH +GAUCHER G OW1 SH ER0 +GAUCHO G AW1 CH OW0 +GAUCHOS G AW1 CH OW0 Z +GAUDET G OW0 D EH1 T +GAUDETTE G OW0 D EH1 T +GAUDIER G AO2 D IY0 EY1 +GAUDIN G OW0 D AE1 N +GAUDINO G AO2 D IY1 N OW0 +GAUDIO G AO1 D IY0 OW0 +GAUDIOSO G AO0 D IY0 OW1 S OW0 +GAUDREAU G OW0 D R OW1 +GAUDY G AO1 D IY0 +GAUER G AW1 ER0 +GAUERKE G AW1 ER0 K +GAUFMAN G AO1 F M AH0 N +GAUFMAN'S G AO1 F M AH0 N Z +GAUGE G EY1 JH +GAUGED G EY1 JH D +GAUGER G EY1 JH ER0 +GAUGES G EY1 JH AH0 Z +GAUGES(1) G EY1 JH IH0 Z +GAUGH G AO1 +GAUGHAN G AO1 AH0 N +GAUGHMAN G AO1 M AH0 N +GAUGHRAN G AO1 R AH0 N +GAUGING G EY1 JH IH0 NG +GAUGLER G AO1 G L ER0 +GAUGUIN G AO1 G W IH0 N +GAUGUIN(1) G OW1 G AE2 N +GAUL G AO1 L +GAULAN G AO1 L AH0 N +GAULDEN G AW1 D AH0 N +GAULDING G AO1 L D IH0 NG +GAULIN G OW0 L AE1 N +GAULKE G AO1 L K +GAULLE G AO1 L +GAULLIST G AO1 L IH0 S T +GAULS G AO1 L Z +GAULT G AO1 L T +GAULTIER G OW1 L T Y EY0 +GAULTIER(1) G AA1 L T Y ER0 +GAULTNEY G AO1 L T N IY0 +GAUMER G AW1 M ER0 +GAUMOND G OW0 M AA1 N D +GAUNA G AO1 N AH0 +GAUNCE G AO1 N S +GAUNT G AO1 N T +GAUNTLET G AO1 N T L AH0 T +GAUNTNESS G AO1 N T N AH0 S +GAUNTT G AO1 N T +GAUS G AO1 Z +GAUSE G AO1 Z +GAUSMAN G AW1 S M AH0 N +GAUSS G AW1 S +GAUSSIAN G AW1 S IY0 AH0 N +GAUSTAD G AW1 S T AH0 D +GAUT G AO1 T +GAUTHIER G AW1 TH IY0 ER0 +GAUTHREAUX G OW0 TH R OW1 +GAUTIER G AW1 T IY0 ER0 +GAUTNEY G AO1 T N IY0 +GAUTREAU G OW0 T R OW1 +GAUTREAUX G OW0 T R OW1 +GAUVAIN G OW0 V AE1 N +GAUVIN G OW0 V AE1 N +GAUVREAU G OW0 V R OW1 +GAUZE G AO1 Z 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D +GAYMAN G EY0 M AE1 N +GAYMON G EY1 M AH0 N +GAYNATIE G EY1 N AH0 T IY0 +GAYNER G EY1 N ER0 +GAYNESS G EY1 N AH0 S +GAYNOR G EY1 N ER0 +GAYS G EY1 Z +GAYSHILL G EY2 Z HH IH1 L +GAYSHILL(1) G EY0 SH IH1 L +GAYTAN G EY1 T AH0 N +GAYTON G EY1 T AH0 N +GAZ G AA1 Z +GAZ(1) G AE1 Z +GAZA G AA1 Z AH0 +GAZA'S G AA1 Z AH0 Z +GAZANS G AA1 Z AH0 N Z +GAZAWAY G AA1 Z AH0 W EY0 +GAZDA G AE1 Z D AH0 +GAZDIK G AE1 Z D IH0 K +GAZE G EY1 Z +GAZED G EY1 Z D +GAZELLA G AH0 Z EH1 L AH0 +GAZELLE G AH0 Z EH1 L +GAZELLES G AH0 Z EH1 L Z +GAZES G EY1 Z AH0 Z +GAZES(1) G EY1 Z IH0 Z +GAZETA G AH0 Z EY1 T AH0 +GAZETA(1) G AH0 Z EH1 T AH0 +GAZETTE G AH0 Z EH1 T +GAZING G EY1 Z IH0 NG +GAZONSKY G AH0 Z AA1 N S K IY0 +GAZONSKY'S G AH0 Z AA1 N S K IY0 Z +GAZPROM G AE1 Z P R AA2 M +GAZZOLA G AA0 T S OW1 L AH0 +GDANSK G D AE1 N S K +GDP JH IY2 D IY2 P IY1 +GEAC G IY1 K +GEAC(1) JH IY1 IY1 EY1 S IY1 +GEAGEA JH IY1 AH0 JH IY1 AH0 +GEAN JH IY1 N +GEAR G IH1 R +GEAR'S G IH1 R Z +GEARAN G IH1 R AH0 N +GEARAN'S G IH1 R 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+GIRL G ER1 L +GIRL'S G ER1 L Z +GIRLFRIEND G ER1 L F R EH2 N D +GIRLFRIEND'S G ER1 L F R EH2 N D Z +GIRLFRIENDS G ER1 L F R EH2 N D Z +GIRLHOOD G ER1 L HH UH2 D +GIRLIE G ER1 L IY0 +GIRLISH G ER1 L IH0 SH +GIRLISHLY G ER1 L IH0 SH L IY0 +GIRLS G ER1 L Z +GIRLS' G ER1 L Z +GIROBANK G IH1 R OW0 B AE2 NG K +GIROD ZH ER0 AA1 D +GIROIR ZH AY0 R W AA1 R +GIROLAMO JH IH0 R OW0 L AA1 M OW0 +GIROLDI G IH0 R OW1 L D IY0 +GIROLDI'S G IH0 R OW1 L D IY0 Z +GIRON ZH IH1 R AH0 N +GIRONDE JH ER0 AO1 N D +GIROUARD ZH AY1 R UW0 ER0 D +GIROUX ZH IH0 R UW1 +GIROZENTRALE G IH0 R OW1 Z EH0 N T R AA2 L +GIRSKY G ER1 S K IY0 +GIRT G ER1 T +GIRTEN G ER1 T AH0 N +GIRTH G ER1 TH +GIRTMAN G ER1 T M AH0 N +GIRTON G ER1 T AH0 N +GIRVAN G ER1 V AH0 N +GIRVEN G ER1 V AH0 N +GIRVIN G ER1 V IH0 N +GISBERT JH IH1 S B ER0 T +GISBERT(1) G IH1 S B ER0 T +GISCARD G IH0 S K AA1 R D +GISCARD(1) ZH IH0 S K AA1 R +GISCLAIR ZH IH0 S K L EH1 R +GISELA G IY1 Z AH0 L AH0 +GISELLA JH IH0 S EH1 L AH0 +GISELLE ZH IH0 S EH1 L +GISENYI JH IH0 S EH1 N IY0 +GISENYI(1) JH IH0 S EH1 N Y IY0 +GISH JH IH1 SH +GISH(1) G IH1 SH +GISI JH IY1 S IY0 +GISLER G IH1 S AH0 L ER0 +GISLER(1) G IH1 S L ER0 +GISMONDI JH IY0 S M OW1 N D IY0 +GISSENDANNER G IH1 S IH0 N D AH0 N ER0 +GISSI G IH1 S IY0 +GIST JH IH1 S T +GISU JH IH1 S UW0 +GIT G IH1 T +GITANA JH IY0 T AE1 N AH0 +GITANO G IH0 T AA1 N OW0 +GITANO'S G IH0 T AA1 N OW0 Z +GITCHELL JH IH1 CH AH0 L +GITHA JH IH1 DH AH0 +GITHENS G IH1 TH AH0 N Z +GITHUB G IH1 T HH AH0 B +GITLIN JH IH1 T L IH0 N +GITTELMAN G IH1 T AH0 L M AH0 N +GITTENS G IH1 T AH0 N Z +GITTER G IH1 T ER0 +GITTINGS JH IH1 T IH0 NG Z +GITTINS JH IH1 T IH0 N Z +GITTIS JH IH1 T AH0 S +GITTIS(1) G IH1 T IH0 S +GITTLEMAN G IH1 T AH0 L M AH0 N +GITTLEMAN'S G IH1 T AH0 L M AH0 N Z +GITTLER G IH1 T L ER0 +GITTO JH IY1 T OW0 +GIUDICE JH UW1 D IH0 S IY0 +GIUDICI JH UW1 D IH0 CH IY0 +GIUFFRE JH UW1 F R IY0 +GIUFFRE'S JH UW1 F R IY0 Z +GIUFFRIDA JH UW1 F R IY0 D AH0 +GIULIANI JH UW2 L IY0 AA1 N IY0 +GIULIANI'S JH UW2 L IY0 AA1 N IY0 Z +GIULIANO JH UW2 L IY0 AA1 N OW0 +GIULIO JH UW1 L IY0 OW0 +GIUNTA JH UW1 N T AH0 +GIURESCU JH UW2 R EH1 S K UW0 +GIUSEPPE JH IH0 S EH1 P IY0 +GIUSTI JH UW1 S T IY0 +GIUSTO JH UW1 S T OW0 +GIVAN G IH1 V AH0 N +GIVE G IH1 V +GIVEAWAY G IH1 V AH0 W EY2 +GIVEAWAYS G IH1 V AH0 W EY2 Z +GIVEBACK G IH1 V B AE2 K +GIVEBACKS G IH1 V B AE2 K S +GIVEN G IH1 V AH0 N +GIVEN(1) G IH1 V IH0 N +GIVENCHY G IH0 V EH1 N CH IY0 +GIVENNESS G IH1 V AH0 N AH0 S +GIVENS G IH1 V AH0 N Z +GIVENS'S G IH1 V AH0 N Z IH0 Z +GIVER G IH1 V ER0 +GIVERS G IH1 V ER0 Z +GIVES G IH1 V Z +GIVETH G IH1 V EH0 TH +GIVHAN G IH1 V HH AH0 N +GIVIN' G IH1 V IH0 N +GIVING G IH1 V IH0 NG +GIVING-FEAST G IH1 V IH0 NG F IY2 S T +GIVINS G IH1 V IH0 N Z +GIVLER G IH1 V L ER0 +GIZA G IH1 Z AH0 +GIZA(1) G IY1 Z AH0 +GIZBERT G IH1 Z B ER0 T +GIZBERT'S G IH1 Z B ER0 T S +GIZMO G IH1 Z M OW2 +GIZMOS G IH1 Z M OW0 Z +GIZZARD G IH1 Z ER0 D +GIZZI JH IY1 T S IY0 +GJELTEN JH EH1 L T AH0 N +GJELTEN'S JH EH1 L T AH0 N Z +GJERDE JH ER1 D +GLAAB G L AA1 B +GLAB G L AE1 B +GLACE G L EY1 S +GLACIAL G L EY1 SH AH0 L +GLACIATE G L EY1 SH IY0 EY2 T +GLACIATE(1) G L EY1 S IY0 EY2 T +GLACIATED G L EY1 SH IY0 EY2 T AH0 D +GLACIATED(1) G L EY1 S IY0 EY2 T AH0 D +GLACIATION G L EY2 SH IY0 EY1 SH AH0 N +GLACIER G L EY1 SH ER0 +GLACIER'S G L EY1 SH ER0 Z +GLACIERS G L EY1 SH ER0 Z +GLACIS G L EY1 S AH0 S +GLACKEN G L AE1 K AH0 N +GLACKIN G L AE1 K IH0 N +GLAD G L AE1 D +GLADD G L AE1 D +GLADDEN G L AE1 D AH0 N +GLADDING G L AE1 D IH0 NG +GLADDOCK G L AE1 D AH0 K +GLADE G L EY1 D +GLADES G L EY1 D Z +GLADFELTER G L AE1 D F EH2 L T ER0 +GLADHILL G L AE1 D HH IH2 L +GLADIATOR G L AE1 D IY0 EY2 T ER0 +GLADIATORS G L AE1 D IY0 EY2 T ER0 Z +GLADIEUX G L AE1 D IY0 OW0 +GLADIOLUS G L AE2 D IY0 OW1 L AH0 S +GLADIS G L AE1 D IH0 S +GLADISH G L AE1 D IH0 SH +GLADJE G L AE1 D JH IY2 +GLADLY G L AE1 D L IY0 +GLADMAN G L AE1 D M AH0 N +GLADNEY G L AE1 D N IY0 +GLADSON G L AE1 D S AH0 N +GLADSTEIN G L AE1 D S T AY2 N +GLADSTEIN(1) G L AE1 D S T IY2 N +GLADSTONE G L AE1 D S T OW2 N +GLADSTONES G L AE1 D S T OW2 N Z +GLADU G L EY1 D UW0 +GLADWELL G L AE1 D W EH2 L +GLADWIN G L AE1 D W IH0 N +GLADYS G L AE1 D IH0 S +GLADYS' G L AE1 D IH0 S +GLAESER G L EY1 Z ER0 +GLAHN G L AE1 N +GLAM G L AE1 M +GLAMOR G L AE1 M ER0 +GLAMORIZE G L AE1 M ER0 AY2 Z +GLAMORIZED G L AE1 M ER0 AY0 Z D +GLAMORIZING G L AE1 M ER0 AY0 Z IH0 NG +GLAMOROUS G L AE1 M ER0 AH0 S +GLAMOUR G L AE1 M ER0 +GLANCE G L AE1 N S +GLANCED G L AE1 N S T +GLANCES G L AE1 N S IH0 Z +GLANCING G L AE1 N S IH0 NG +GLANCY G L AE1 N S IY0 +GLAND G L AE1 N D +GLANDER G L AE1 N D ER0 +GLANDON G L AE1 N D AH0 N +GLANDS G L AE1 N D Z +GLANDULAR G L AE1 N JH AH0 L ER0 +GLANTON G L AE1 N T AH0 N +GLANTZ G L AE1 N T S +GLANVILLE G L AE1 N V IH2 L +GLANZ G L AE1 N Z +GLANZER G L AE1 N Z ER0 +GLANZMAN G L AE1 N Z M AH0 N +GLARE G L EH1 R +GLARED G L EH1 R D +GLARES G L EH1 R Z +GLARING G L EH1 R IH0 NG +GLARIS G L EH1 R IH0 S +GLAS G L AE1 S +GLASBY G L AE1 S B IY0 +GLASCO G L AA1 S K OW0 +GLASCOCK G L AE1 S K AH0 K +GLASCOE G L AE1 S K OW0 +GLASER G L EY1 Z ER0 +GLASGOW G L AE1 S K OW2 +GLASGOW(1) G L AE1 S G OW2 +GLASHEEN G L AH0 SH IY1 N +GLASHOW G L AE1 SH AW0 +GLASNER G L AE1 S N ER0 +GLASNOST G L AE1 S N AA0 S T +GLASNOST(1) G L AO1 S T N OW2 S T +GLASNOST(2) G L AO1 S N OW2 S T +GLASOW G L EY1 Z OW0 +GLASPER G L AE1 S P ER0 +GLASPIE G L AE1 S P IY0 +GLASPY G L AE1 S P IY0 +GLASS G L AE1 S +GLASS'S G L AE1 S IH0 Z +GLASSBERG G L AE1 S B ER0 G +GLASSBLOWER G L AE1 S B L OW2 ER0 +GLASSBLOWERS G L AE1 S B L OW2 ER0 Z +GLASSBLOWING G L AE1 S B L OW2 IH0 NG +GLASSBURN G L AE1 S B ER2 N +GLASSCO G L AE1 S K OW0 +GLASSCOCK G L AE1 S K AA2 K +GLASSED G L AE1 S T +GLASSER G L AE1 S ER0 +GLASSES G L AE1 S AH0 Z +GLASSES(1) G L AE1 S IH0 Z +GLASSEY G L AE1 S IY0 +GLASSFORD G L AE1 S F AO0 R D +GLASSLIKE G L AE1 S L AY2 K +GLASSMAKER G L AE1 S M EY2 K ER0 +GLASSMAKING G L AE1 S M EY2 K IH0 NG +GLASSMAN G L AE1 S M AE2 N +GLASSMAN(1) G L AE1 S M AH0 N +GLASSMEYER G L AE1 S M AY0 ER0 +GLASSNER G L AE1 S N ER0 +GLASSON G L AE1 S AH0 N +GLASSWARE G L AE1 S W EH2 R +GLASSY G L AE1 S IY0 +GLASTETTER G L AE1 S T IH0 T ER0 +GLATFELTER G L AE1 T F IH0 L T ER0 +GLATT G L AE1 T +GLATZ G L AE1 T S +GLATZER G L EY1 T Z ER0 +GLAUB G L AO1 B +GLAUBER G L AW1 B ER0 +GLAUCOMA G L AO0 K OW1 M AH0 +GLAUDE G L AO1 D +GLAUS G L AO1 Z +GLAUSER G L AW1 S ER0 +GLAVAN G L EY1 V AH0 N +GLAVIN G L AE1 V IH0 N +GLAVINE G L AE0 V IH1 N +GLAVINE(1) G L AE0 V IY1 N +GLAWE G L AO1 +GLAXO G L AE1 K S OW0 +GLAXO'S G L AE1 K S OW0 Z +GLAZA G L AA1 Z AH0 +GLAZE G L EY1 Z +GLAZEBROOK G L EY1 Z B R UH2 K +GLAZED G L EY1 Z D +GLAZENER G L AE1 Z IY0 N ER0 +GLAZER G L EY1 Z ER0 +GLAZES G L EY1 Z AH0 Z +GLAZES(1) G L EY1 Z IH0 Z +GLAZIER G L EY1 Z IY0 ER0 +GLAZING G L EY1 Z IH0 NG +GLAZNER G L AE1 Z N ER0 +GLAZUNOV G L AE1 Z UW0 N AA0 V +GLEACHER G L IY1 CH ER0 +GLEAM G L IY1 M +GLEAMED G L IY1 M D +GLEAMING G L IY1 M IH0 NG +GLEAMS G L IY1 M Z +GLEAN G L IY1 N +GLEANED G L IY1 N D +GLEASON G L IY1 S AH0 N +GLEASON'S G L IY1 S AH0 N Z +GLEATON G L IY1 T AH0 N +GLEAVE G L IY1 V +GLEAVES G L IY1 V Z +GLEBA G L IY1 B AH0 +GLECKLER G L EH1 K L ER0 +GLEDA G L EY1 D AH0 +GLEDHILL G L EH1 D HH IH2 L +GLEE G L IY1 +GLEEFUL G L IY1 F AH0 L +GLEEFULLY G L IY1 F AH0 L IY0 +GLEESON G L IY1 Z AH0 N +GLEGHORN G L EH1 G HH ER0 N +GLEICH G L AY1 K +GLEICHAUF G L AY1 K AO0 F +GLEIM G L IY1 M +GLEISNER G L AY1 S N ER0 +GLEMP G L EH1 M P +GLEN G L EH1 N +GLENAYRE G L EH2 N EH1 R +GLENAYRE(1) G L EH2 N AY1 R +GLENBROOK G L EH1 N B R UH2 K +GLENDA G L EH1 N D AH0 +GLENDALE G L EH1 N D EY2 L +GLENDENING G L EH1 N D AH0 N IH0 NG +GLENDENNING G L EH1 N D IH0 N IH0 NG +GLENDINNING G L EH1 N D IH0 N IH0 NG +GLENDON G L EH1 N D OW0 N +GLENFED G L EH1 N F EH2 D +GLENFED'S G L EH1 N F EH2 D Z +GLENGARRY G L EH2 N G EH1 R IY0 +GLENHAM G L EH1 N HH AH0 M +GLENHAM(1) G L EH1 N AH0 M +GLENMORE G L EH1 N M AO2 R +GLENN G L EH1 N +GLENN'S G L EH1 N Z +GLENNA G L EH1 N AH0 +GLENNIE G L EH1 N IY0 +GLENNON G L EH1 N AH0 N +GLENNY G L EH1 N IY0 +GLENORA G L AH0 N AO1 R AH0 +GLENS G L EH1 N Z +GLENVIEW G L EH1 N V Y UW2 +GLENVILLE G L EH1 N V IH0 L +GLENWOOD G L EH1 N W UH2 D +GLENWOOD'S G L EH1 N W UH2 D Z +GLESS G L EH1 S +GLESSNER G L EH1 S N ER0 +GLEW G L UW1 +GLIB G L IH1 B +GLIBLY G L IH1 B L IY0 +GLICK G L IH1 K +GLICKENHAUS G L IH1 K AH0 N HH AW2 S +GLICKMAN G L IH1 K M AH0 N +GLICKMAN'S G L IH1 K S M AH0 N Z +GLICKSMAN G L IH1 K S M AH0 N +GLICKSTEIN G L IH1 K S T IY2 N +GLICKSTEIN(1) G L IH1 K S T AY2 N +GLIDDEN G L IH1 D AH0 N +GLIDE G L AY1 D +GLIDED G L AY1 D IH0 D +GLIDER G L AY1 D ER0 +GLIDERS G L AY1 D ER0 Z +GLIDES G L AY1 D Z +GLIDEWELL G L AY1 D W EH2 L +GLIDING G L AY1 D IH0 NG +GLIMCHER G L IH1 M CH ER0 +GLIMMER G L IH1 M ER0 +GLIMMERING G L IH1 M ER0 IH0 NG +GLIMMERS G L IH1 M ER0 Z +GLIMPSE G L IH1 M P S +GLIMPSED G L IH1 M P S T +GLIMPSES G L IH1 M P S IH0 Z +GLINES G L AY1 N Z +GLINKA G L IH1 NG K AH0 +GLINSKI G L IH1 N S K IY0 +GLINT G L IH1 N T +GLINTING G L IH1 N T IH0 NG +GLISSANDI G L AH0 S AA1 N D IY0 +GLISSON G L IH1 S AH0 N +GLISTEN G L IH1 S AH0 N +GLISTENED G L IH1 S AH0 N D +GLISTENING G L IH1 S AH0 N IH0 NG +GLISTENING(1) G L IH1 S N IH0 NG +GLITCH G L IH1 CH +GLITCHES G L IH1 CH IH0 Z +GLITTER G L IH1 T ER0 +GLITTERED G L IH1 T ER0 D +GLITTERING G L IH1 T ER0 IH0 NG +GLITTERS G L IH1 T ER0 Z +GLITTERY G L IH1 T ER0 IY0 +GLITZ G L IH1 T S +GLITZY G L IH1 T S IY0 +GLO G L OW1 +GLOAM G L OW1 M +GLOAMING G L OW1 M IH0 NG +GLOAT G L OW1 T +GLOATED G L OW1 T IH0 D +GLOATING G L OW1 T IH0 NG +GLOATS G L OW1 T S +GLOB G L AA1 B +GLOBAL G L OW1 B AH0 L +GLOBAL'S G L OW1 B AH0 L Z +GLOBALIZATION G L OW2 B AH0 L IH0 Z EY1 SH AH0 N +GLOBALIZE G L OW1 B AH0 L AY2 Z +GLOBALIZED G L OW1 B AH0 L AY2 Z D +GLOBALLY G L OW1 B AH0 L IY0 +GLOBALSTAR G L OW1 B AH0 L S T AA2 R +GLOBCOM G L AA1 B K AA0 M +GLOBE G L OW1 B +GLOBE'S G L OW1 B Z +GLOBES G L OW1 B Z +GLOBETROTTER G L OW1 B T R AO0 T ER0 +GLOBETROTTERS G L OW1 B T R AO0 T ER0 Z +GLOBEX G L OW1 B AH0 K S +GLOBO G L OW1 B OW0 +GLOBS G L AA1 B Z +GLOBULAR G L AA1 B Y AH0 L ER0 +GLOBULIN G L AA1 B Y AH0 L IH0 N +GLOBULINS G L AA1 B Y AH0 L IH0 N Z +GLOBUS G L OW1 B AH0 S +GLOCESTER G L AW1 S T ER0 +GLOCK G L AA1 K +GLOCKENSPIEL G L AA1 K AH0 N S P IY2 L +GLOCKNER G L AA1 K N ER0 +GLOD G L AA1 D +GLODOWSKI G L AH0 D AO1 F S K IY0 +GLOE G L OW1 +GLOECKNER G L OW1 K N ER0 +GLOEDE G L OW1 D +GLOGOWSKI G L AH0 G AO1 F S K IY0 +GLOMAR G L OW1 M AA0 R +GLOMB G L AA1 M +GLOMSKI G L AA1 M S K IY2 +GLONASS G L AA1 N AH0 S +GLOOM G L UW1 M +GLOOMIER G L UW1 M IY0 ER0 +GLOOMILY G L UW1 M AH0 L IY0 +GLOOMY G L UW1 M IY0 +GLOOR G L UH1 R +GLOP G L AA1 P +GLOPPY G L AA1 P IY0 +GLOR G L AO1 R +GLORE G L AO1 R +GLORI G L AO1 R IY0 +GLORIA G L AO1 R IY0 AH0 +GLORIANA G L AO2 R IY0 AE1 N AH0 +GLORIANE G L AO2 R IY0 AE1 N +GLORIES G L AO1 R IY0 Z +GLORIFICATION G L AO2 R AH0 F IH0 K EY1 SH AH0 N +GLORIFICATION(1) G L AO2 R IH0 F IH0 K EY1 SH AH0 N +GLORIFIED G L AO1 R AH0 F AY2 D +GLORIFIES G L AO1 R AH0 F AY2 Z +GLORIFY G L AO1 R AH0 F AY2 +GLORIFYING G L AO1 R AH0 F AY2 IH0 NG +GLORIOSO G L AO0 R IY0 OW1 S OW0 +GLORIOUS G L AO1 R IY0 AH0 S +GLORIOUSLY G L AO1 R IY0 AH0 S L IY0 +GLORY G L AO1 R IY0 +GLOSS G L AO1 S +GLOSSARY G L AO1 S ER0 IY0 +GLOSSED G L AO1 S T +GLOSSER G L AO1 S ER0 +GLOSSES G L AO1 S IH0 Z +GLOSSIER G L AO1 S IY0 ER0 +GLOSSMAN G L AO1 S M AH0 N +GLOSSON G L AA1 S AH0 N +GLOSSY G L AO1 S IY0 +GLOSTER G L AA1 S T ER0 +GLOTFELTY G L AA1 T F IH0 L T IY0 +GLOTTAL G L AA1 T AH0 L +GLOTTIS G L AA1 T AH0 S +GLOTZBACH G L AA1 T S B AA0 K +GLOUCESTER G L AO1 S T ER0 +GLOVE G L AH1 V +GLOVED G L AH1 V D +GLOVER G L AH1 V ER0 +GLOVES G L AH1 V Z +GLOW G L OW1 +GLOWACKI G L AW0 AA1 T S K IY0 +GLOWED G L OW1 D +GLOWER G L AW1 ER0 +GLOWERED G L AW1 ER0 D +GLOWERING G L AW1 ER0 IH0 NG +GLOWING G L OW1 IH0 NG +GLOWINGLY G L OW1 IH0 NG L IY0 +GLOWS G L OW1 Z +GLOYD G L OY1 D +GLUCK G L AH1 K +GLUCK'S G L AH1 K S +GLUCKMAN G L AH1 K M AH0 N +GLUCKSMAN G L AH1 K S M AH0 N +GLUCOSAMATE G L UW0 K AA1 S AH0 M EY2 T +GLUCOSAMINE G L UW0 K AA1 S AH0 M IY2 N +GLUCOSE G L UW1 K OW2 S +GLUCOSIDE G L UW1 K AH0 S AY2 D +GLUCOSIDES G L UW1 K AH0 S AY2 D Z +GLUE G L UW1 +GLUECK G L UW1 K +GLUED G L UW1 D +GLUES G L UW1 Z +GLUM G L AH1 M +GLUMLY G L AH1 M L IY0 +GLUMMER G L AH1 M ER0 +GLUNT G L AH1 N T +GLUNTZ G L AH1 N T S +GLUNZ G L AH1 N Z +GLUSKIN G L AH1 S K IH0 N +GLUT G L AH1 T +GLUTAMATE G L UW1 T AH0 M EY2 T +GLUTAMIC G L UW0 T AE1 M IH0 K +GLUTARIC G L UW0 T AE1 R IH0 K +GLUTEN G L UW1 T AH0 N +GLUTH G L UW1 TH +GLUTS G L AH1 T S +GLUTTED G L AH1 T IH0 D +GLUTTONOUS G L AH1 T AH0 N AH0 S +GLUTTONS G L AH1 T AH0 N Z +GLUTTONY G L AH1 T AH0 N IY0 +GLYCEL G L IH1 S AH0 L +GLYCEMIC G L AY0 S EH1 M IH0 K +GLYCEROL G L IH1 S ER0 OW2 L +GLYCINE G L AY1 S IY2 N +GLYCINE(1) G L AY1 S AH0 N +GLYCOGEN G L AY1 K AH0 JH IH0 N +GLYCOL G L AY1 K AO2 L +GLYCOL(1) G L AY1 K OW2 L +GLYCOLIC G L AY0 K AO1 L AH0 K +GLYCOMED G L AY1 K OW2 M D +GLYCOMED(1) G L AY1 K OW0 M EH2 D +GLYCOSIDE G L AY1 K AH0 S AY2 D +GLYMPH G L IH1 M F +GLYN G L IH1 N +GLYNDEBOURNE G L IH1 N D B AO2 R N +GLYNIS G L IH1 N IH0 S +GLYNN G L IH1 N +GLYNNIE G L IH1 N IY0 +GLYNNIS G L IH1 N IH0 S +GM JH IY2 EH1 M +GMBH G IY1 EH2 M B IY2 HH AA2 +GNAGEY N AE1 JH IY0 +GNAIZDA N EY1 Z D AH0 +GNANN N AE1 N +GNARL N AA1 R L +GNARLE N AA1 R L +GNARLED N AA1 R L D +GNARLING N AA1 R L IH0 NG +GNARLS N AA1 R L Z +GNARLY N AA1 R L IY0 +GNASH N AE1 SH +GNASHING N AE1 SH IH0 NG +GNAT N AE1 T +GNATCATCHER N AE1 T K AE2 CH ER0 +GNATCATCHERS N AE1 T K AE2 CH ER0 Z +GNATS N AE1 T S +GNAU N AW1 +GNAW N AO1 +GNAWED N AO1 D +GNAWING N AO1 IH0 NG +GNAWS N AO1 Z +GNC JH IY1 EH1 N S IY1 +GNEISS N AY1 S +GNOCCHI N OW1 K IY0 +GNOME N OW1 M +GNOMES N OW1 M Z +GNOMIC N OW1 M IH0 K +GNOMONIC N OW0 M AA1 N IH0 K +GNOSTICISM N AA1 S T IH0 S IH2 Z AH0 M +GNP JH IY2 EH2 N P IY1 +GNU N UW1 +GO G OW1 +GO-CART G OW1 K AA2 R T +GOA G OW1 AH0 +GOAD G OW1 D +GOADED G OW1 D IH0 D +GOADING G OW1 D IH0 NG +GOAL G OW1 L +GOALIE G OW1 L IY0 +GOALKEEPER G OW1 L K IY2 P ER0 +GOALPOST G OW1 L P OW2 S T +GOALS G OW1 L Z +GOAN G OW1 N +GOANS G OW1 N Z +GOAR G AO1 R +GOARD G AO1 R D +GOAT G OW1 T +GOAT'S G OW1 T S +GOATEE G OW1 T IY1 +GOATES G OW1 EY0 T S +GOATLEY G OW1 T L IY0 +GOATS G OW1 T S +GOB G AA1 B +GOBAIN G OW1 B IH0 N +GOBBLE G AA1 B AH0 L +GOBBLED G AA1 B AH0 L D +GOBBLEDYGOOK G AA2 B AH0 L D IY0 G UH1 K +GOBBLER G AA1 B AH0 L ER0 +GOBBLER(1) G AA1 B L ER0 +GOBBLERS G AA1 B AH0 L ER0 Z +GOBBLERS(1) G AA1 B L ER0 Z +GOBBLES G AA1 B AH0 L Z +GOBBLING G AA1 B AH0 L IH0 NG +GOBBLING(1) G AA1 B L IH0 NG +GOBEL G OW1 B AH0 L +GOBEN G AA1 B AH0 N +GOBER G OW1 B ER0 +GOBERSTEIN G OW1 B ER0 S T IY2 N +GOBERSTEIN(1) G OW1 B ER0 S T AY2 N +GOBERT G AA1 B ER0 T +GOBI G OW1 B IY0 +GOBIE G OW1 B IY0 +GOBIN G OW1 B IH0 N +GOBINOT G OW1 B IH0 N AA0 T +GOBIOFF G OW1 B IY0 AO0 F +GOBLE G OW1 B AH0 L +GOBLET G AA1 B L AH0 T +GOBLIN G AA1 B L IH0 N +GOBLINS G AA1 B L IH0 N Z +GOBLIRSCH G AA1 B L ER0 SH +GOBS G AA1 B Z 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G AH1 V ER0 N M AH0 N T +GOVERNMENT'S G AH1 V ER0 N M AH0 N T S +GOVERNMENTAL G AH1 V ER0 M EH2 N T AH0 L +GOVERNMENTAL(1) G AH2 V ER0 N M EH1 N T AH0 L +GOVERNMENTALLY G AH1 V ER0 M EH2 N T AH0 L IY0 +GOVERNMENTS G AH1 V ER0 N M AH0 N T S +GOVERNMENTS' G AH1 V ER0 N M AH0 N T S +GOVERNOR G AH1 V ER0 N ER0 +GOVERNOR'S G AH1 V ER0 N ER0 Z +GOVERNORS G AH1 V ER0 N ER0 Z +GOVERNORS' G AH1 V ER0 N ER0 Z +GOVERNORSHIP G AH1 V ER0 N ER0 SH IH2 P +GOVERNORSHIPS G AH1 V ER0 N ER0 SH IH2 P S +GOVERNS G AH1 V ER0 N Z +GOVETT G AH1 V AH0 T +GOVIER G OW1 V IY0 ER0 +GOVONI G OW0 V OW1 N IY0 +GOVPX G AH1 V P IY2 EH1 K S +GOVS G AA1 V Z +GOVS(1) G AA1 V ER0 N ER0 Z +GOW G AW1 +GOWAN G AW1 AH0 N +GOWANS G AW1 AH0 N Z +GOWARD G OW1 W ER0 D +GOWDY G AW1 D IY0 +GOWELL G AA1 W EH0 L +GOWEN G AW1 AH0 N +GOWENS G AW1 AH0 N Z +GOWER G AW1 ER0 +GOWIN G AW1 IH0 N +GOWING G AW1 IH0 NG +GOWINS G AW1 IH0 N Z +GOWN G AW1 N +GOWNS G AW1 N Z +GOY G OY1 +GOYA G OY1 AH0 +GOYA'S G OY1 AH0 Z +GOYER G OY1 ER0 +GOYETTE G OY2 EH1 T +GOYIM G OY1 IH0 M +GOYKO G OY1 K OW0 +GOYNE G OY1 N +GOYNES G OY1 N Z +GOZA G OW1 Z AH0 +GOZO G OW1 Z OW0 +GOZO'S G OW1 Z OW0 Z +GOZOFSKY G AH0 Z AO1 F S K IY0 +GPS G IY1 P IY0 EH1 S +GRAB G R AE1 B +GRABAU G R AE1 B AW0 +GRABBE G R AE1 B +GRABBED G R AE1 B D +GRABBER G R AE1 B ER0 +GRABBERS G R AE1 B ER0 Z +GRABBING G R AE1 B IH0 NG +GRABE G R EY1 B +GRABEL G R AE1 B AH0 L +GRABEN G R AE1 B AH0 N +GRABENS G R AA1 B AH0 N Z +GRABENSTEIN G R AE1 B AH0 N S T AY2 N +GRABENSTEIN(1) G R AE1 B AH0 N S T IY2 N +GRABER G R EY1 B ER0 +GRABERT G R AE1 B ER0 T +GRABILL G R AH0 B IH1 L +GRABINSKI G R AH0 B IH1 N S K IY0 +GRABLE G R EY1 B AH0 L +GRABNER G R AE1 B N ER0 +GRABOSKI G R AH0 B AW1 S K IY0 +GRABOW G R AE1 B OW0 +GRABOWSKI G R AH0 B AO1 F S K IY0 +GRABOY G R EY1 B OY0 +GRABS G R AE1 B Z +GRABSKI G R AE1 B S K IY2 +GRACE G R EY1 S +GRACE'S G R EY1 S IH0 Z +GRACED G R EY1 S T +GRACEFFA G R AH0 S EH1 F AH0 +GRACEFUL G R EY1 S F AH0 L +GRACEFULLY G R EY1 S F AH0 L IY0 +GRACELAND G 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IY0 AH0 N T +GRADIENTS G R EY1 D IY0 AH0 N T S +GRADING G R EY1 D IH0 NG +GRADISON G R AE1 D IH0 S AH0 N +GRADNEY G R AE1 D N IY0 +GRADO G R AA1 D OW0 +GRADOV G R EY1 D AO0 F +GRADOVS G R EY1 D AO0 F S +GRADS G R AE1 D Z +GRADSTEIN G R AE1 D S T IY0 N +GRADSTEIN(1) G R AE1 D S T AY0 N +GRADSTEIN'S G R AE1 D S T IY0 N Z +GRADSTEIN'S(1) G R AE1 D S T AY0 N Z +GRADUAL G R AE1 JH UW0 AH0 L +GRADUALISM G R AE1 JH AH0 W AH0 L IH2 Z AH0 M +GRADUALIST G R AE1 JH AH0 W AH0 L IH0 S T +GRADUALLY G R AE1 JH UW0 AH0 L IY0 +GRADUALLY(1) G R AE1 JH UW0 L IY0 +GRADUATE G R AE1 JH AH0 W AH0 T +GRADUATE(1) G R AE1 JH AH0 W EY2 T +GRADUATE(2) G R AE1 JH UW0 W AH0 T +GRADUATE(3) G R AE1 JH UW0 EY2 T +GRADUATED G R AE1 JH UW0 EY2 T IH0 D +GRADUATED(1) G R AE1 JH AH0 W EY2 T IH0 D +GRADUATES G R AE1 JH AH0 W AH0 T S +GRADUATES(1) G R AE1 JH AH0 W EY2 T S +GRADUATES(2) G R AE1 JH UW0 W AH0 T S +GRADUATES(3) G R AE1 JH UW0 EY2 T S +GRADUATING G R AE1 JH AH0 W EY2 T IH0 NG +GRADUATING(1) G R AE1 JH UW0 EY2 T IH0 NG +GRADUATION G R AE2 JH UW0 EY1 SH AH0 N +GRADUATION(1) G R AE2 JH AH0 W EY1 SH AH0 N +GRADUATIONS G R AE2 JH UW0 EY1 SH AH0 N Z +GRADUATIONS(1) G R AE2 JH AH0 W EY1 SH AH0 N Z +GRADUS G R EY1 D AH0 S +GRADY G R EY1 D IY0 +GRAEBER G R EH1 B ER0 +GRAEBNER G R EH1 B N ER0 +GRAEF G R IY1 F +GRAEF(1) G R AE1 F +GRAEFE G R IY1 F +GRAEFE(1) G R AE1 F +GRAEFF G R IY1 F +GRAEFF(1) G R AE1 F +GRAEME G R EY1 M +GRAEME(1) G R AE1 M +GRAESER G R EY1 Z ER0 +GRAESSLE G R EH1 S AH0 L +GRAETZ G R IY1 T S +GRAF G R AE1 F +GRAFE G R EY1 F +GRAFF G R AE1 F +GRAFFAM G R AE1 F AH0 M +GRAFFEO G R AA1 F IY0 OW0 +GRAFFITI G R AH0 F IY1 T IY0 +GRAFFIUS G R AE1 F IY0 IH0 S +GRAFT G R AE1 F T +GRAFTED G R AE1 F T IH0 D +GRAFTING G R AE1 F T IH0 NG +GRAFTON G R AE1 F T AH0 N +GRAFTS G R AE1 F T S +GRAGE G R EY1 JH +GRAGERT G R EY1 G ER0 T +GRAGG G R AE1 G +GRAHAM G R EY1 AH0 M +GRAHAM(1) G R AE1 M +GRAHAM'S G R EY1 AH0 M Z +GRAHAM'S(1) G R AE1 M Z +GRAHAMS G R AE1 M Z +GRAHAMS(1) G R EY1 AH0 M Z +GRAHEK G R AE1 HH IH0 K +GRAHL G R AA1 L +GRAHN G R AE1 N +GRAICHEN G R AY1 K AH0 N +GRAIL G R EY1 L +GRAIN G R EY1 N +GRAINED G R EY1 N D +GRAINERY G R EY1 N ER0 IY0 +GRAINGER G R EY1 NG JH ER0 +GRAINS G R EY1 N Z +GRAINY G R EY1 N IY0 +GRAJEDA G R AY0 IY1 D AH0 +GRALEY G R AE1 L IY0 +GRALL G R AO1 L +GRAM G R AE1 M +GRAMA G R AE1 M AH0 +GRAMAPHONE G R AE1 M AH0 F OW2 N +GRAMBLING G R AE1 M B L IH0 NG +GRAMBLING(1) G R AE1 M B AH0 L IH0 NG +GRAMER G R EY1 M ER0 +GRAMERCY G R AH0 M ER1 S IY0 +GRAMERSEY G R AH0 M ER1 S IY0 +GRAMES G R EY1 M Z +GRAMLEY G R AE1 M L IY0 +GRAMLICH G R AE1 M L IH0 K +GRAMLING G R AE1 M L IH0 NG +GRAMM G R AE1 M +GRAMM'S G R AE1 M Z +GRAMMAR G R AE1 M ER0 +GRAMMATICAL G R AH0 M AE1 T AH0 K AH0 L +GRAMMATICAL(1) G R AH0 M AE1 T IH0 K AH0 L +GRAMMATICO G R AA0 M AA0 T IY1 K OW0 +GRAMMER G R AE1 M ER0 +GRAMMIES G R AE1 M IY2 Z +GRAMMOPHON G R AE1 M AH0 F AA0 N +GRAMMS G R AE1 M Z +GRAMMY G R AE1 M IY0 +GRAMMY'S G R AE1 M IY0 Z +GRAMMYS G R AE1 M IY0 Z +GRAMS G R AE1 M Z 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AH0 N Z +GRANDCHILDREN'S(1) G R AE1 N D CH IH2 L D R AH0 N Z +GRANDDAD G R AE1 N D AE2 D +GRANDDADDY G R AE1 N D AE2 D IY0 +GRANDDAUGHTER G R AE1 N D AO2 T ER0 +GRANDDAUGHTER'S G R AE1 N D AO2 T ER0 Z +GRANDDAUGHTERS G R AE1 N D AO2 T ER0 Z +GRANDE G R AE1 N D +GRANDER G R AE1 N D ER0 +GRANDERSON G R AE1 N D ER0 S AH0 N +GRANDEST G R AE1 N D AH0 S T +GRANDEUR G R AE0 N D UW1 R +GRANDFATHER G R AE1 N D F AA2 DH ER0 +GRANDFATHER(1) G R AE1 N F AA2 DH ER0 +GRANDFATHER'S G R AE1 N D F AA2 DH ER0 Z +GRANDFATHER'S(1) G R AE1 N F AA2 DH ER0 Z +GRANDFATHERED G R AE1 N D F AA2 DH ER0 D +GRANDFATHERED(1) G R AE1 N F AA2 DH ER0 D +GRANDFATHERING G R AE1 N D F AA2 DH ER0 IH0 NG +GRANDFATHERING(1) G R AE1 N F AA2 DH ER0 IH0 NG +GRANDFATHERLY G R AE1 N D F AA2 DH ER0 L IY0 +GRANDFATHERLY(1) G R AE1 N F AA2 DH ER0 L IY0 +GRANDFATHERS G R AE1 N D F AA2 DH ER0 Z +GRANDFATHERS(1) G R AE1 N F AA2 DH ER0 Z +GRANDFIELD G R AE1 N D F IY2 L D +GRANDI G R AE1 N D IY0 +GRANDILLO G R AE0 N D IH1 L OW0 +GRANDILOQUENT G R AE0 N D IH1 L AH0 K W AH0 N T +GRANDIN G R AE1 N D IH2 N +GRANDINETTI G R AE0 N D IY0 N EH1 T IY0 +GRANDIOSE G R AE2 N D IY0 OW1 S +GRANDIOSE(1) G R AE1 N D IY0 OW2 S +GRANDIS G R AE1 N D IH0 S +GRANDISON G R AE1 N D IH0 S AH0 N +GRANDKID G R AE1 N D K IH2 D +GRANDKID(1) G R AE1 N K IH2 D +GRANDKIDS G R AE1 N D K IH2 D Z +GRANDKIDS(1) G R AE1 N K IH2 D Z +GRANDLY G R AE1 N D L IY0 +GRANDMA G R AE1 N D M AA0 +GRANDMA'S G R AE1 N D M AA2 Z +GRANDMAISON G R AE1 N D M AY2 Z AA1 N +GRANDMAISON(1) G R AE1 N D M EY1 S AH0 N +GRANDMAS G R AE1 N D M AA2 Z +GRANDMASTER G R AE1 N D M AE1 S T ER0 +GRANDMET G R AE1 N D M EH2 T +GRANDMOTHER G R AE1 N D M AH2 DH ER0 +GRANDMOTHER'S G R AE1 N D M AH2 DH ER0 Z +GRANDMOTHERLY G R AE1 N D M AH2 DH ER0 L IY0 +GRANDMOTHERS G R AE1 N D M AH2 DH ER0 Z +GRANDNEPHEW G R AE1 N D N EH1 F Y UW0 +GRANDNEPHEWS G R AE1 N D N EH1 F Y UW0 Z +GRANDON G R AE1 N D AA0 N +GRANDPA G R AE1 N D P AA2 +GRANDPA'S G R AE1 N P AA2 Z +GRANDPARENT G R AE1 N D P EH2 R AH0 N T +GRANDPARENTS G R AE1 N D P EH2 R AH0 N T S +GRANDPARENTS' G R AE1 N D P EH2 R AH0 N T S +GRANDPAS G R AE1 N D P AA2 Z +GRANDPRE G R AE1 N D P R EY2 +GRANDS G R AE1 N D Z +GRANDSON G R AE1 N D S AH2 N +GRANDSON'S G R AE1 N D S AH2 N Z +GRANDSONS G R AE1 N D S AH2 N Z +GRANDSTAFF G R AE1 N D S T AE2 F +GRANDSTAFF(1) G R AE1 N S T AE2 F +GRANDSTAND G R AE1 N D S T AE2 N D +GRANDSTANDING G R AE1 N D S T AE2 N D IH0 NG +GRANDT G R AE1 N T +GRANDUNCLE G R AE1 N D AH1 NG K AH0 L +GRANDUNCLES G R AE1 N D AH1 NG K AH0 L Z +GRANDVIEW G R AE1 N D V Y UW2 +GRANDY G R AE1 N D IY0 +GRANER G R EY1 N ER0 +GRANESE G R AE1 N IY0 Z +GRANEY G R EY1 N IY0 +GRANFIELD G R AE1 N F IY2 L D +GRANGE G R EY1 N JH +GRANGER G R EY1 N JH ER0 +GRANGERS G R EY1 N JH ER0 Z +GRANGES G R EY1 N JH IH0 Z +GRANHOLM G R AE1 N HH OW2 L M +GRANIER G R EY1 N IY0 ER0 +GRANIERI G R AA0 N IH2 EH1 R IY0 +GRANILLO G R AH0 N IH1 L OW0 +GRANINGEVERKEN G R AE2 N IH0 NG G EH1 V ER0 K AH0 N +GRANINGEVERKEN'S G R AE2 N IH0 NG G EH1 V ER0 K AH0 N Z +GRANITE G R AE1 N IH0 T +GRANITIC G R AH0 N IH1 T IH0 K +GRANITO G R AA0 N IY1 T OW0 +GRANLUND G R AE1 N L AH0 N D +GRANNAN G R AE1 N AH0 N +GRANNIES G R AE1 N IY0 Z +GRANNIS G R AE1 N IH0 S +GRANNY G R AE1 N IY0 +GRANO G R AA1 N OW0 +GRANOFF G R AE1 N AO0 F +GRANOLA G R AH0 N OW1 L AH0 +GRANQUIST G R AE1 N K W IH2 S T +GRANSTROM G R AE1 N S T R AH0 M +GRANT G R AE1 N T +GRANT'S G R AE1 N T S +GRANTED G R AE1 N T AH0 D +GRANTED(1) G R AE1 N T IH0 D +GRANTED(2) G R AE1 N AH0 D +GRANTED(3) G R AE1 N IH0 D +GRANTHAM G R AE1 N TH AH0 M +GRANTING G R AE1 N T IH0 NG +GRANTING(1) G R AE1 N IH0 NG +GRANTLAND G R AE1 N T L AH0 N D +GRANTOR G R AE1 N T ER0 +GRANTORS G R AE1 N T ER0 Z +GRANTREE G R AE1 N T R IY2 +GRANTREE'S G R AE1 N T R IY2 Z +GRANTS G R AE1 N T S +GRANTZ G R AE1 N T S +GRANULAR G R AE1 N Y AH0 L ER0 +GRANULATION G R AE2 N Y AH0 L EY1 SH AH0 N +GRANULE G R AE1 N Y AH0 L +GRANULES G R AE1 N Y AH0 L Z +GRANULOCYTE G R AH0 N UW1 L OW0 S AY2 T +GRANUM G R AE1 N AH0 M +GRANVILLE G R AE1 N V IH0 L +GRANVILLE'S G R AE1 N V IH0 L Z +GRANZ G R AE1 N T S +GRANZOW G R AE1 N Z OW0 +GRAPAGE G R EY1 P AH0 JH +GRAPE G R EY1 P +GRAPEFRUIT G R EY1 P F R UW2 T +GRAPEFRUITS G R EY1 P F R UW2 T S +GRAPER G R EY1 P ER0 +GRAPES G R EY1 P S +GRAPESHOT G R EY1 P SH AA2 T +GRAPEVINE G R EY1 P V AY2 N +GRAPEVINES G R EY1 P V AY2 N Z +GRAPH G R AE1 F +GRAPHIC G R AE1 F IH0 K +GRAPHICAL G R AE1 F IH0 K AH0 L +GRAPHICALLY G R AE1 F IH0 K L IY0 +GRAPHICS G R AE1 F IH0 K S +GRAPHICS' G R AE1 F IH0 K S +GRAPHITE G R AE1 F AY2 T +GRAPHOLOGY G R AH0 F AA1 L AH0 JH IY0 +GRAPHS G R AE1 F S +GRAPPLE G R AE1 P AH0 L +GRAPPLED G R AE1 P AH0 L D +GRAPPLES G R AE1 P AH0 L Z +GRAPPLING G R AE1 P L IH0 NG +GRAPPLING(1) G R AE1 P AH0 L IH0 NG +GRAS G R AE1 S +GRAS(1) G R AA1 +GRASER G R EY1 Z ER0 +GRASMICK G R AE1 Z M IH0 K +GRASP G R AE1 S P +GRASPED G R AE1 S P T +GRASPING G R AE1 S P IH0 NG +GRASPS G R AE1 S P S +GRASS G R AE1 S +GRASSE G R AE1 S +GRASSED G R AE1 S T 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+GRATIFY G R AE1 T AH0 F AY2 +GRATIFYING G R AE1 T AH0 F AY2 IH0 NG +GRATING G R EY1 T IH0 NG +GRATIS G R AE1 T AH0 S +GRATITUDE G R AE1 T AH0 T UW2 D +GRATTAN G R AE1 T AH0 N +GRATTON G R AE1 T AH0 N +GRATUITIES G R AH0 T UW1 IH0 T IY0 Z +GRATUITOUS G R AH0 T UW1 AH0 T AH0 S +GRATUITOUSLY G R AH0 T UW1 AH0 T AH0 S L IY0 +GRATUITY G R AH0 T UW1 IH0 T IY0 +GRATZ G R AE1 T S +GRATZER G R EY1 T Z ER0 +GRAU G R AW1 +GRAUBERGER G R AW1 B ER0 G ER0 +GRAUE G R AW1 +GRAUE(1) G R UW1 +GRAUEL G R AW1 AH0 L +GRAUEL(1) G R UW1 AH0 L +GRAUER G R AW1 ER0 +GRAUER(1) G R UW1 ER0 +GRAUL G R AO1 L +GRAUMAN G R AO1 M AH0 N +GRAUMANN G R AO1 M AH0 N +GRAUNKE G R AO1 NG K +GRAVAMEN G R AA0 V EY1 M AH0 N +GRAVANO G R AH0 V AA1 N OW0 +GRAVANO(1) G R AH0 V AE1 N OW0 +GRAVATT G R AE1 V AH0 T +GRAVE G R EY1 V +GRAVEL G R AE1 V AH0 L +GRAVELINE G R EY1 V L AY2 N +GRAVELL G R AE1 V AH0 L +GRAVELLE G R AH0 V EH1 L +GRAVELLY G R AE1 V AH0 L IY0 +GRAVELY G R EY1 V L IY0 +GRAVEN G R EY1 V AH0 N +GRAVER G R EY1 V ER0 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G R IH1 F IH0 NG +GRIFFIS G R IH1 F IH0 S +GRIFFITH G R IH1 F AH0 TH +GRIFFITH(1) G R IH1 F IH0 TH +GRIFFITH'S G R IH1 F IH0 TH S +GRIFFITHS G R IH1 F IH0 TH S +GRIFFITTS G R IH1 F IH0 T S +GRIFFO G R IH1 F OW0 +GRIFFON G R IH1 F AH0 N +GRIFFY G R IH1 F IY0 +GRIGAS G R AY1 G AH0 Z +GRIGG G R IH1 G +GRIGGS G R IH1 G Z +GRIGGY G R IH1 G IY0 +GRIGNON G R IH1 G N AH0 N +GRIGOLI G R IH0 G OW1 L IY0 +GRIGOROVICH G R IH0 G AO1 R AH0 V IH0 CH +GRIGORY G R EH1 G ER0 IY0 +GRIGORY(1) G R IY1 G ER0 IY0 +GRIGORYANT G R IH0 G AO1 R Y AE0 N T +GRIGORYANTS G R IH0 G AO1 R Y AE0 N T S +GRIGSBY G R IH1 G Z B IY0 +GRIJALVA G R IY0 Y AA1 L V AH0 +GRILL G R IH1 L +GRILLE G R IH1 L +GRILLED G R IH1 L D +GRILLI G R IH1 L IY0 +GRILLING G R IH1 L IH0 NG +GRILLIOT G R IH1 L IY0 AH0 T +GRILLO G R IH1 L OW0 +GRILLOT G R IH1 L AH0 T +GRILLS G R IH1 L Z +GRIM G R IH1 M +GRIMA G R IY1 M AH0 +GRIMACE G R IH1 M AH0 S +GRIMACED G R IH1 M AH0 S T +GRIMACES G R IH1 M AH0 S IH0 Z +GRIMACING G R IH1 M AH0 S IH0 NG 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D S T OW2 N +GRINE G R AY1 N +GRINER G R AY1 N ER0 +GRING G R IH1 NG +GRINGO G R IH1 NG G OW0 +GRINGOS G R IH1 NG G OW0 Z +GRINNED G R IH1 N D +GRINNELL G R IH0 N EH1 L +GRINNING G R IH1 N IH0 NG +GRINS G R IH1 N Z +GRINSTEAD G R IH1 N S T EH2 D +GRINSTEIN G R IH1 N S T IY2 N +GRINSTEIN(1) G R IH1 N S T AY2 N +GRIP G R IH1 P +GRIPE G R AY1 P +GRIPED G R AY1 P T +GRIPES G R AY1 P S +GRIPING G R AY1 P IH0 NG +GRIPP G R IH1 P +GRIPPED G R IH1 P T +GRIPPER G R IH1 P ER2 +GRIPPI G R IH1 P IY0 +GRIPPING G R IH1 P IH0 NG +GRIPPO G R IH1 P OW0 +GRIPS G R IH1 P S +GRISANTI G R IH0 S AE1 N T IY0 +GRISBY G R IH1 S B IY0 +GRISCOM G R IH1 S K AH0 M +GRISE G R AY1 Z +GRISHAM G R IH1 SH AH0 M +GRISHAM'S G R IH1 SH AH0 M Z +GRISHILDA G R IH0 SH IH1 L D AH0 +GRISHMAN G R IH1 SH M AH0 N +GRISLY G R IH1 Z L IY0 +GRISMER G ER1 IH0 Z AH0 M ER0 +GRISMER(1) G R IH1 S M ER0 +GRISMORE G R IY1 S M AO0 R +GRISSETT G R IH1 S IH0 T +GRISSINGER G R IH1 S IH0 NG ER0 +GRISSO G R IH1 S OW0 +GRISSOM G R IH1 S AH0 M 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AA1 SH AO0 NG +GROSJEAN G R AH0 S ZH IY1 N +GROSKOPF G R AA1 S K AO0 P F +GROSKOPF(1) G R OW1 S K AO0 F +GROSS G R OW1 S +GROSS'S G R OW1 S IH0 Z +GROSSBARD G R OW1 S B AA2 R D +GROSSBERG G R OW1 S B ER0 G +GROSSE G R AA1 S +GROSSED G R OW1 S T +GROSSENBACHER G R AA1 S IH0 N B AA0 K ER0 +GROSSER G R OW1 S ER0 +GROSSES G R OW1 S IH0 Z +GROSSFELD G R OW1 S F EH2 L D +GROSSHANS G R AA1 SH AH0 N Z +GROSSI G R OW1 S IY0 +GROSSING G R OW1 S IH0 NG +GROSSKOPF G R OW1 S K AO0 P F +GROSSKOPF(1) G R OW1 S K AO0 F +GROSSLY G R OW1 S L IY0 +GROSSMAN G R OW1 S M AH0 N +GROSSMAN'S G R OW1 S M AH0 N Z +GROSSMANN G R AO1 S M AH0 N +GROSSNICKLE G R AA1 S N IH0 K AH0 L +GROSSO G R OW1 S OW0 +GROSVENOR G R OW1 V N ER0 +GROSZ G R OW1 S +GROTE G R OW1 T +GROTESQUE G R OW0 T EH1 S K +GROTESQUELY G R OW0 T EH1 S K L IY0 +GROTH G R AA1 TH +GROTHAUS G R AA1 T HH AW2 S +GROTHE G R OW1 DH +GROTHEER G R AO1 TH IH0 R +GROTON G R AA1 T AH0 N +GROTTO G R AA1 T OW2 +GROTZ G R AA1 T S +GROUCH G R AW1 CH +GROUCHO G R 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AH1 N F AY2 ER0 +GUNFIRE(1) G AH1 N F AY2 R +GUNFLINT G AH1 N F L IH0 N T +GUNG G AH1 NG +GUNHILDA G UW0 N HH IY1 L D AH0 +GUNIA G UW1 N IY0 AH0 +GUNKEL G AH1 NG K AH0 L +GUNLICK G AH1 N L IH0 K +GUNLICKS G AH1 N L IH0 K S +GUNMAN G AH1 N M AH0 N +GUNMAN'S G AH1 N M AH0 N Z +GUNMEN G AH1 N M EH2 N +GUNN G AH1 N +GUNN'S G AH1 N Z +GUNNAR G AH1 N ER0 +GUNNARSON G AH1 N AA0 R S AH0 N +GUNNED G AH1 N D +GUNNELL G AH1 N AH0 L +GUNNELLS G AH1 N AH0 L Z +GUNNELS G AH1 N AH0 L Z +GUNNER G AH1 N ER0 +GUNNERS G AH1 N ER0 Z +GUNNERSON G AH1 N ER0 S AH0 N +GUNNERY G AH1 N ER0 IY0 +GUNNING G AH1 N IH0 NG +GUNNISON G AH1 N IH0 S AH0 N +GUNNOE G AH1 N OW0 +GUNNY G AH1 N IY0 +GUNNYSACK G AH1 N IY0 S AE2 K +GUNNYSACKS G AH1 N IY0 S AE2 K S +GUNPOINT G AH1 N P OY2 N T +GUNPOWDER G AH1 N P AW2 D ER0 +GUNRUNNER G AH1 N R AH2 N ER0 +GUNS G AH1 N Z +GUNSALUS G AH0 N S AA1 L AH0 S +GUNSHIP G AH1 N SH IH2 P +GUNSHIPS G AH1 N SH IH2 P S +GUNSHOT G AH1 N SH AA2 T +GUNSHOTS G AH1 N SH AA2 T S +GUNSLINGER G AH1 N S L IH2 NG ER0 +GUNSLINGERS G AH1 N S L IH2 NG ER0 Z +GUNSMOKE G AH1 N S M OW2 K +GUNST G AH1 N S T +GUNTER G AH1 N T ER0 +GUNTHER G AH1 N TH ER0 +GUNTUR G AH1 N T ER0 +GUNTY G AH1 N T IY0 +GUPPIES G AH1 P IY0 Z +GUPPY G AH1 P IY0 +GUPTA G UH1 P T AH0 +GUPTILL G AH1 P T IH0 L +GUPTON G AH1 P T AH0 N +GURA G UH1 R AH0 +GURAL G Y UH1 R AH0 L +GUREVICH G Y UW1 R IH0 V IH0 CH +GURGANIOUS G ER1 G AH0 N IY0 IH0 S +GURGANUS G ER1 G AH0 N IH0 S +GURGLE G ER1 G AH0 L +GURGLING G ER1 G AH0 L IH0 NG +GURGLING(1) G ER1 G L IH0 NG +GURIAN G Y UH1 R IY0 AH0 N +GURION G Y UH1 R IY0 AH0 N +GURIT G Y UH1 R IH0 T +GURIT(1) G UH1 R IH0 T +GURKA G ER1 K AH0 +GURKIN G ER1 K IH0 N +GURLEY G ER1 L IY0 +GURNARDS G ER1 N ER0 D Z +GURNEE G ER0 N IY1 +GURNEY G ER1 N IY0 +GURNEY'S G ER1 N IY0 Z +GURNSEY G ER1 N S IY0 +GURR G ER1 +GURRIA G ER1 IY0 AH0 +GURROLA G UH0 R OW1 L AH0 +GURRY G ER1 IY0 +GURSKI G ER1 S K IY0 +GURSKY G ER1 S K IY0 +GURTLER G ER1 T AH0 L ER0 +GURTLER(1) G ER1 T L ER0 +GURTNER G ER1 T N ER0 +GURTZ G ER1 T S +GURU G UW1 R UW2 +GURU'S G UW1 R UW2 Z +GURULE G ER0 UW1 L +GURUS G UW1 R UW2 Z +GUS G AH1 S +GUSCIORA G UW2 S IY0 AO1 R AH0 +GUSE G Y UW1 Z +GUSELLA G Y UW2 S EH1 L AH0 +GUSEMAN G UW1 S M AH0 N +GUSES G Y UW1 Z IH0 Z +GUSES(1) G AH1 S AH0 Z +GUSH G AH1 SH +GUSHED G AH1 SH T +GUSHER G AH1 SH ER0 +GUSHERS G AH1 SH ER0 Z +GUSHES G AH1 SH IH0 Z +GUSHING G AH1 SH IH0 NG +GUSINSKY G AH0 S IH1 N S K IY0 +GUSKY G AH1 S K IY0 +GUSLAN G UW1 Z L AA2 N +GUSLER G AH1 S AH0 L ER0 +GUSLER(1) G AH1 S L ER0 +GUSMAN G AH1 S M AH0 N +GUSS G AH1 S +GUSSIE G AH1 S IY0 +GUSSIED G AH1 S IY0 D +GUSSMAN G AH1 S M AH0 N +GUSSY G AH1 S IY0 +GUST G AH1 S T +GUSTAF G UW1 S T AA0 F +GUSTAFSON G AH1 S T AH0 F S AH0 N +GUSTAFSSON G UW1 S T AA0 F S AH0 N +GUSTAV G UH1 S T AA0 F +GUSTAVA G UW0 S T AA1 V AH0 +GUSTAVE G UW0 S T AA1 V IY0 +GUSTAVESON G UW0 S T AA0 V EY1 S AH0 N +GUSTAVO G AH0 S T AA1 V OW0 +GUSTAVSON G AH1 S T AH0 V S AH0 N +GUSTAVUS G AH1 S T AH0 V AH0 S +GUSTE G AH1 S T +GUSTED G AH1 S T IH0 D +GUSTER G AH1 S T ER0 +GUSTIN G AH1 S T IH0 N +GUSTING G AH1 S T IH0 NG +GUSTO G AH1 S T OW2 +GUSTON G AH1 S T AH0 N +GUSTS G AH1 S T S +GUSTUS G AH1 S T AH0 S +GUSTY G AH1 S T IY0 +GUT G AH1 T +GUTEKUNST G AH1 T IH0 K AH0 N S T +GUTENBERG G UW1 T AH0 N B ER0 G +GUTERMAN G Y UW1 T ER0 M AH0 N +GUTERMUTH G AH1 T ER0 M UW0 TH +GUTFELD G AH1 T F EH2 L D +GUTFREUND G UH1 T F R EH2 N D +GUTH G UW1 TH +GUTHERIE G AH1 TH ER0 IY0 +GUTHERY G AH1 TH ER0 IY0 +GUTHMILLER G AH1 TH M IH0 L ER0 +GUTHRIDGE G AH1 TH R IH0 JH +GUTHRIE G AH1 TH R IY0 +GUTHRIE'S G AH1 TH R IY0 Z +GUTIEREZ G UW0 T IH1 R EH0 Z +GUTIERRES G UW0 T Y EH1 R EH0 Z +GUTIERREZ G UW0 T Y EH1 R EH0 Z +GUTKNECHT G UW1 T N EH0 K T +GUTKOWSKI G AH0 T K AO1 F S K IY0 +GUTLESS G AH1 T L EH0 S +GUTMAN G AH1 T M AH0 N +GUTMANN G AH1 T M AH0 N +GUTOWSKI G AH0 T AO1 F S K IY0 +GUTRIDGE G AH1 T R IH2 JH +GUTS G AH1 T S +GUTSHALL G AH1 CH AH0 L +GUTSY G AH1 T S IY1 +GUTT G AH1 T +GUTTED G AH1 T IH0 D +GUTTENBERG G AH1 T AH0 N B ER0 G +GUTTER G AH1 T ER0 +GUTTERED G AH1 T ER0 D +GUTTERING G AH1 T ER0 IH0 NG +GUTTERMAN G AH1 T ER0 M AH0 N +GUTTERS G AH1 T ER0 Z +GUTTING G AH1 T IH0 NG +GUTTMACHER G AH1 T M AA2 K ER0 +GUTTMAN G AH1 T M AH0 N +GUTTMANN G AH1 T M AH0 N +GUTTURAL G AH1 T ER0 AH0 L +GUTWAKS G AH1 T W AA2 K S +GUTWEIN G AH1 T W AY2 N +GUTZMAN G AH1 T S M AH0 N +GUTZMER G AH1 T S M ER0 +GUTZWILLER G AH1 T S W IH2 L ER0 +GUY G AY1 +GUY'S G AY1 Z +GUYANA G AY2 AA1 N AH0 +GUYER G AY1 ER0 +GUYETT G AY2 EH1 T +GUYETTE G AY2 EH1 T +GUYMON G AY1 M AH0 N +GUYNES G AY1 N Z +GUYNN G AY1 N +GUYON G AY1 AH0 N +GUYOT G AY1 AH0 T +GUYS G AY1 Z +GUYS' G AY1 Z +GUYTON G AY1 T AH0 N +GUZA G Y UW1 Z AH0 +GUZEK G UW1 Z EH0 K +GUZIK G Y UW1 Z IH0 K +GUZMAN G AH1 Z M AH0 N +GUZMAN(1) G UW1 Z M AA2 N +GUZOWSKI G AH0 Z AO1 F S K IY0 +GUZY G Y UW1 Z IY0 +GUZZARDO G UW0 T S AA1 R D OW0 +GUZZETTA G UW0 T S EH1 T AH0 +GUZZETTI G Y UW0 Z EH1 T IY0 +GUZZI G UW1 T S IY0 +GUZZLE G AH1 Z AH0 L +GUZZLER G AH1 Z L ER0 +GUZZLER'S G AH1 Z AH0 L ER0 Z +GUZZLER'S(1) G AH1 Z L ER0 Z +GUZZLERS G AH1 Z AH0 L ER0 Z +GUZZLERS(1) G AH1 Z L ER0 Z +GUZZLES G AH1 Z AH0 L Z +GUZZLING G AH1 Z AH0 L IH0 NG +GUZZLING(1) G AH1 Z L IH0 NG +GUZZO G UW1 Z OW0 +GVARYAHU G AH0 V EH0 R Y AA1 HH UW0 +GWALTNEY G W AO1 L T N IY0 +GWARTNEY G W AO1 R T N IY0 +GWAY G W EY1 +GWAY(1) JH IY1 W EY2 +GWEN G W EH1 N +GWENDA G W EH1 N D AH0 +GWENDOLYN G W EH1 N D AH0 L IH0 N +GWENNIE G W EH1 N IY0 +GWENORE G W EH1 N ER0 +GWIN G W IH1 N +GWINN G W IH1 N +GWINN'S G W IH1 N Z +GWINNER G W IH1 N ER0 +GWINNETT G W IH0 N EH1 T +GWIZDALA G W IH0 Z D AA1 L AH0 +GWOZDZ G W AA1 Z D Z +GWYN G W IH1 N +GWYNETH G W IH1 N AH0 TH +GWYNETH'S G W IH1 N AH0 TH S +GWYNETHS G W IH1 N AH0 TH S +GWYNN G W IH1 N +GWYNNE G W IH1 N +GYGER G AY1 G ER0 +GYI G IY1 +GYI(1) JH IY1 W AY1 AY1 +GYLES JH AY1 L Z +GYLLENHAMMAR JH IH1 L EH0 N HH AE2 M ER0 +GYM JH IH1 M +GYM'S JH IH1 M Z +GYMBOREE JH IH2 M B AO0 R IY1 +GYMNASIA JH IH0 M N EY1 Z IY0 AH0 +GYMNASIUM JH IH0 M N EY1 Z IY0 AH0 M +GYMNASIUMS JH IH0 M N EY1 Z IY0 AH0 M Z +GYMNAST JH IH1 M N AH0 S T +GYMNASTIC JH IH0 M N AE1 S T IH0 K +GYMNASTICS JH IH0 M N AE1 S T IH0 K S +GYMNASTS JH IH1 M N AE0 S T S +GYMS JH IH1 M Z +GYN G IH1 N +GYN(1) G AY1 N +GYNECOLOGIC G AY2 N AH0 K AH0 L AA1 JH IH0 K +GYNECOLOGICAL G AY2 N AH0 K AH0 L AA1 JH IH0 K AH0 L +GYNECOLOGIST G AY2 N AH0 K AA1 L AH0 JH AH0 S T +GYNECOLOGISTS G AY2 N AH0 K AA1 L AH0 JH AH0 S T S +GYNECOLOGY G AY2 N AH0 K AA1 L AH0 JH IY0 +GYNEX JH IH1 N AH0 K S +GYOHTEN G Y OW1 T AH0 N +GYOSAI G Y OW1 S EY2 +GYP JH IH1 P +GYPPED JH IH1 P T +GYPSIES JH IH1 P S IY0 Z +GYPSUM JH IH1 P S AH0 M +GYPSUM'S JH IH1 P S AH0 M Z +GYPSY JH IH1 P S IY0 +GYR JH AY1 R +GYRATE JH AY1 R EY2 T +GYRATED JH AY1 R EY2 T IH0 D +GYRATES JH AY1 R EY2 T S +GYRATING JH AY1 R EY2 T IH0 NG +GYRATION JH AY0 R EY1 SH AH0 N +GYRATIONS JH AY0 R EY1 SH AH0 N Z +GYRO JH AY1 R OW2 +GYROCOMPASS JH AY1 R OW0 K AH2 M P AH0 S +GYRODYNE JH IH1 R AH0 D AY0 N +GYRODYNES JH IH1 R AH0 D AY0 N Z +GYROPILOT JH AY1 R OW0 P AY2 L AH0 T +GYROS JH AY1 R OW2 Z +GYROSCOPE JH AY1 R AH0 S K OW2 P +GYROSCOPES JH AY1 R AH0 S K OW2 P S +GYROSCOPIC JH AY2 R AH0 S K AA1 P IH0 K +GYTHA JH AY1 DH AH0 +GYUHAMA G Y UW2 HH AA1 M AH0 +H EY1 CH +H'S EY1 CH IH0 Z +H. EY1 CH +H.'S EY1 CH IH0 Z +HA HH AA1 +HA'ARETZ HH AA1 R EH0 T S +HA'ARETZ(1) HH AH0 AA1 R EH0 T S +HA'ETZNI HH AH0 EH1 T S N IY0 +HA-HA HH AA2 HH AA1 +HA-HA-HA HH AA2 HH AA2 HH AA1 +HAAB HH AA1 B +HAACK HH AA1 K +HAACKE HH AA1 K +HAAF HH AA1 F +HAAG HH AA1 G +HAAGEN HH AA1 G AH0 N +HAAGENSON HH AA1 G IH0 N S AH0 N +HAAK HH AA1 K +HAAKE HH AA1 K +HAAKENSON HH AA1 K IH0 N S AH0 N +HAALAND HH AA1 L AH0 N D +HAAN HH AA1 N +HAAPALA HH AA2 P AA1 L AH0 +HAAR HH AA1 R +HAAS HH AA1 S +HAASE HH AA1 S +HAASS HH AA1 S +HAAVELMO HH AA2 V EH1 L M OW0 +HABBEN HH AE1 B AH0 N +HABEAS HH AE1 B IY0 AH0 S +HABECK HH AA1 B EH0 K +HABECKER HH AE1 B EH0 K ER0 +HABEEB HH AE1 B IY0 B +HABEGGER HH AE1 B IH0 G ER0 +HABEL HH AE1 B AH0 L +HABENICHT HH AE1 B IH0 N IH0 K T +HABER HH EY1 B ER0 +HABERDASHERY HH AE1 B ER0 D AE2 SH ER0 IY0 +HABERER HH AE1 B ER0 ER0 +HABERKORN HH AE1 B ER0 K ER0 N +HABERL HH AE1 B ER0 L +HABERLAND HH AE1 B ER0 L AH0 N D +HABERLE HH AE1 B ER0 AH0 L +HABERMAN HH EY1 B ER0 M AH0 N +HABERMANN HH EY1 B ER0 M AH0 N +HABERMAS HH AA1 B ER0 M AA2 S +HABERMEHL HH AE1 B ER0 M AH0 L +HABERSON HH EY1 B ER0 S IH0 N +HABERSON(1) HH AE1 B ER0 S IH0 N +HABERSTROH HH AA0 B EH1 R S T R OW0 +HABIB HH AH0 B IY1 B +HABIBI HH AH0 B IY1 B IY0 +HABIBIE HH AH0 B IY1 B IY0 +HABICH HH AE1 B IH0 K +HABICHT HH AE1 B IH0 K T +HABIG HH AE1 B IH0 G +HABIGER HH AE1 B IH0 G ER0 +HABIT HH AE1 B AH0 T +HABITABLE HH AE1 B AH0 T AH0 B AH0 L +HABITAT HH AE1 B AH0 T AE2 T +HABITAT'S HH AE1 B AH0 T AE2 T S +HABITATION HH AE2 B AH0 T EY1 SH AH0 N +HABITATS HH AE1 B AH0 T AE2 T S +HABITS HH AE1 B AH0 T S +HABITUAL HH AH0 B IH1 CH UW0 AH0 L +HABITUALLY HH AH0 B IH1 CH UW0 AH0 L IY0 +HABITUALLY(1) HH AH0 B IH1 CH UW0 L IY0 +HABITUES HH AE1 B IH0 CH UW0 Z +HABLE HH EY1 B AH0 L +HABS HH AE1 B Z +HABSBURG HH AE1 P S B ER0 G +HABY HH EY1 B IY0 +HABYARIMANA HH AE2 B Y AA0 R IY0 M AA1 N AA2 +HACH HH AE1 CH +HACHETTE HH AH0 SH EH1 T +HACHEY HH AE1 CH IY0 +HACHTEL HH AE1 K T AH0 L +HACIENDA HH AE2 S IY0 EH1 N D AH0 +HACK HH AE1 K +HACKATHON HH AE1 K AH0 TH AO2 N +HACKATHORN HH AE1 K AH0 TH ER2 N +HACKBART HH AE1 K B AA2 R T +HACKBARTH HH AE1 K B AA2 R TH +HACKBERRY HH AE1 K B EH2 R IY0 +HACKE HH AE1 K +HACKED HH AE1 K T +HACKEL HH AE1 K AH0 L +HACKENBERG HH AE1 K AH0 N B ER0 G +HACKENSACK HH AE1 K AH0 N S AE2 K +HACKER HH AE1 K ER0 +HACKER'S HH AE1 K ER0 Z +HACKERS HH AE1 K ER0 Z +HACKERT HH AE1 K ER0 T +HACKETT HH AE1 K IH0 T +HACKFORD HH AE1 K F ER0 D +HACKING HH AE1 K IH0 NG +HACKL HH AE1 K AH0 L +HACKLE HH AE1 K AH0 L +HACKLEMAN HH AE1 K AH0 L M AH0 N +HACKLER HH AE1 K AH0 L ER0 +HACKLER(1) HH AE1 K L ER0 +HACKLES HH AE1 K AH0 L Z +HACKLEY HH AE1 K L IY0 +HACKMAN HH AE1 K M AE2 N +HACKMAN(1) HH AE1 K M AH0 N +HACKMANN HH AE1 K M AH0 N +HACKMATACK HH AE1 K M AH0 T AE2 K +HACKNEY HH AE1 K N IY0 +HACKNEYED HH AE1 K N IY0 D +HACKS HH AE1 K S +HACKSAW HH AE1 K S AO2 +HACKSTAFF HH AE1 K S T AE2 F +HACKWORTH HH AE1 K W ER2 TH +HAD HH AE1 D +HADA HH AA1 D AH0 +HADAD HH AE1 D AH0 D +HADAR HH AE1 D ER2 +HADAWAY HH AA1 D AH0 W EY0 +HADD HH AE1 D +HADDAD HH AE1 D AH0 D +HADDAN HH AE1 D AH0 N +HADDAWAY HH AE1 D AH0 W EY0 +HADDEN HH AE1 D AH0 N +HADDOCK HH AE1 D AH0 K +HADDON HH AE1 D AH0 N +HADDONFIELD HH AE1 D AH0 N F IY0 L D +HADDOW HH AE1 D OW0 +HADE HH EY1 D +HADEN HH EY1 D AH0 N +HADER HH EY1 D ER0 +HADES HH EY1 D IY0 Z +HADFIELD HH AE1 D F IY2 L D +HADID HH AA0 D IY1 D +HADLEIGH HH AE1 D L AH0 +HADLER HH EY1 D AH0 L ER0 +HADLER(1) HH EY1 D L ER0 +HADLEY HH AE1 D L IY0 +HADLINE HH AE1 D L AY0 N +HADLOCK HH AE1 D L AH0 K +HADN'T HH AE1 D AH0 N T +HADN'T(1) HH AE1 D AH0 N +HADNOT HH AE1 D N AH0 T +HADOYA HH AH0 D OY1 AH0 +HADRIA HH AE1 D R IY0 AH0 +HADRIAN HH AE1 D R IY0 AH0 N +HADRIAN(1) HH EY1 D R IY0 AH0 N +HADRIAN'S HH EY1 D R IY0 AH0 N Z +HADRON HH AE1 D R AO2 N +HADSALL HH AE1 D S AH0 L +HADSELL HH AE1 D S AH0 L +HADSON HH AE1 D S AH0 N +HADWIN HH AE1 D W IH0 N +HAEBERLE HH EH1 B ER0 AH0 L +HAECKER HH EH1 K ER0 +HAEFELE HH EH1 F AH0 L +HAEFFNER HH EH1 F N ER0 +HAEFNER HH EH1 F N ER0 +HAEGELE HH EH1 G AH0 L +HAEGER HH EH1 G ER0 +HAEN HH IY1 N +HAENEL HH EH1 N AH0 L +HAERING HH AA1 ER0 IH0 NG +HAERTEL HH EH1 R T AH0 L +HAESE HH IY1 S +HAESSLY HH AE1 S L IY0 +HAEUSSLER HH AW1 S L ER0 +HAFELE HH AE1 F AH0 L +HAFEMAN HH EY1 F M AH0 N +HAFEN HH AE1 F AH0 N +HAFER HH EY1 F ER0 +HAFEY HH EY1 F IY0 +HAFEZ HH AA1 F EH0 Z +HAFF HH AE1 F +HAFFEY HH AE1 F IY0 +HAFFEZ HH AA1 F EH0 Z +HAFFNER HH AE1 F N ER0 +HAFFORD HH AE1 F ER0 D +HAFIF HH AA0 F IY1 F +HAFIF'S HH AA0 F IY1 F S +HAFLEY HH AE1 F L IY0 +HAFNER HH AE1 F N ER0 +HAFNIA HH AE1 F N IY0 AH0 +HAFNIUM HH AE1 F N IY0 AH0 M +HAFT HH AE1 F T +HAFT'S HH AE1 F T S +HAFT'S(1) HH AE1 F S +HAFTA HH AE1 F T AH0 +HAFTS HH AE1 F T S +HAFTS(1) HH AE1 F S +HAFTS' HH AE1 F T S +HAFTS'(1) HH AE1 F S +HAG HH AE1 G +HAGA HH AA1 G AH0 +HAGADORN HH AE1 G AH0 D AO0 R N +HAGAMAN HH AE1 G AH0 M AH0 N +HAGAN HH EY1 G AH0 N +HAGANS HH EY1 G AH0 N Z +HAGAR HH EY1 G AA0 R +HAGAR(1) HH EY1 G ER0 +HAGARTY HH AE1 G AA0 R T IY0 +HAGBERG HH AE1 G B ER0 G +HAGE HH EY1 JH +HAGEDORN HH AE1 G IH0 D ER0 N +HAGEE HH AE1 JH IY0 +HAGEL HH AE1 G AH0 L +HAGELIN HH AE1 G IH0 L IH0 N +HAGEMAN HH EY1 JH M AH0 N +HAGEMANN HH EY1 JH M AH0 N +HAGEMEIER HH AE1 G IH0 M AY0 ER0 +HAGEMEISTER HH AE1 G IH0 M AY0 S T ER0 +HAGEMEYER HH AE1 G IH0 M AY0 ER0 +HAGEN HH EY1 G AH0 N +HAGENBUCH HH AE1 G IH0 N B AH0 K +HAGENLOCKER HH EY1 G AH0 N L AA2 K ER0 +HAGENOW HH AE1 JH IH0 N OW0 +HAGENS HH EY1 G AH0 N Z +HAGER HH EY1 G ER0 +HAGERMAN HH EY1 G ER0 M AH0 N +HAGERSTOWN HH EY1 G ER0 Z T AW2 N +HAGERTY HH AE1 JH ER0 T IY0 +HAGEWOOD HH EY1 JH W UH0 D +HAGEY HH AE1 JH IY0 +HAGFISH HH AE1 G F IH0 SH +HAGG HH AE1 G +HAGGADAH HH AH0 G AH1 D AH0 +HAGGAN HH AE1 G AH0 N +HAGGAR HH AE1 G ER0 +HAGGARD HH AE1 G ER0 D +HAGGART HH AE1 G ER0 T +HAGGARTY HH AE1 G AA2 R T IY0 +HAGGE HH AE1 G +HAGGERTY HH AE1 G ER0 T IY0 +HAGGETT HH AE1 G IH0 T +HAGGINS HH AE1 G IH0 N Z +HAGGLE HH AE1 G AH0 L +HAGGLED HH AE1 G AH0 L D +HAGGLING HH AE1 G AH0 L IH0 NG +HAGGLING(1) HH AE1 G L IH0 NG +HAGGLUND HH AE1 G L AH0 N D +HAGGSTROM HH AE1 G S T R AH0 M +HAGIN HH AE1 JH IH0 N +HAGIN(1) HH AE1 G IH2 N +HAGINS HH AE1 G IH0 N Z +HAGINS(1) HH AE1 JH IH2 N Z +HAGIOGRAPHY HH AE2 G IY0 AA1 G R AH0 F IY0 +HAGIWARA HH AA2 G IH0 W AA1 R AH0 +HAGLE HH EY1 G AH0 L +HAGLER HH AE1 G L ER0 +HAGLEY HH AE1 G L IY0 +HAGLUND HH AE1 G L AH0 N D +HAGMAN HH AE1 G M AH0 N +HAGMANN HH AE1 G M AH0 N +HAGNER HH AE1 G N ER0 +HAGOOD HH AE1 G UH0 D +HAGOPIAN HH AH0 G OW1 P IY0 AH0 N +HAGSTROM HH AE1 G S T R AH0 M +HAGUE HH EY1 G +HAGWOOD HH AE1 G W UH2 D +HAGY HH EY1 G IY0 +HAH HH AA1 +HAHL HH AA1 L +HAHM HH AE1 M +HAHN HH AA1 N +HAHNE HH EY1 N +HAHNER HH AA1 N ER0 +HAHS HH AA1 S +HAID HH EY1 D +HAIDA HH AY1 D AH0 +HAIDEE HH EY1 D IY0 +HAIDER HH EY1 D ER0 +HAIDET HH EY1 D IH0 T +HAIFA HH AY1 F AH0 +HAIFONG HH AY1 F AO0 NG +HAIG HH EY1 G +HAIG'S HH EY1 G Z +HAIGH HH EY1 +HAIGHT HH EY1 T +HAIGLER HH EY1 G L ER0 +HAIK HH EY1 K +HAIKU HH AY1 K UW0 +HAIKUS HH AY1 K UW0 Z +HAIL HH EY1 L +HAILAND HH EY1 L AH0 N D +HAILE HH EY1 L +HAILE(1) HH AY1 L IY0 +HAILED HH EY1 L D +HAILES HH EY1 L Z +HAILES(1) HH AY1 L IY0 Z +HAILEY HH EY1 L IY0 +HAILING HH EY1 L IH0 NG +HAILS HH EY1 L Z +HAILSTONE HH EY1 L S T OW2 N +HAILSTONES HH EY1 L S T OW2 N Z +HAILSTORM HH EY1 L S T AO2 R M +HAIM HH AY1 M +HAIM(1) HH EY1 M +HAIMES HH EY1 M Z +HAIMOVITCH HH EY1 M AH0 V IH0 CH +HAIMOVITZ HH EY1 M AH0 V IH0 T S +HAIMOWITZ HH AY1 M AH0 W IH0 T S +HAIN HH EY1 N +HAINAN HH EY1 N AH0 N +HAINER HH EY1 N ER0 +HAINES HH EY1 N Z +HAINEY HH EY1 N IY0 +HAINLEY HH EY1 N L IY0 +HAINLINE HH EY1 N L AY2 N +HAINS HH EY1 N Z +HAINSWORTH HH EY1 N S W ER0 TH +HAIR HH EH1 R +HAIR'S HH EH1 R Z +HAIRCUT HH EH1 R K AH2 T +HAIRCUTS HH EH1 R K AH2 T S +HAIRDO HH EH1 R D UW2 +HAIRDOS HH EH1 R D UW2 Z +HAIRDRESSER HH EH1 R D R EH2 S ER0 +HAIRDRESSERS HH EH1 R D R EH2 S ER0 Z +HAIRDRESSING HH EH1 R D R EH2 S IH0 NG +HAIRE HH EH1 R +HAIRED HH EH1 R D +HAIRFIELD HH EH1 R F IY2 L D +HAIRGROVE HH AY1 R G R AH0 V +HAIRINESS HH EH1 R IY0 N AH0 S +HAIRLESS HH EH1 R L AH0 S +HAIRLINE HH EH1 R L AY2 N +HAIRR HH EH1 R +HAIRS HH EH1 R Z +HAIRSPRAY HH EH1 R S P R EY2 +HAIRSTON HH AY1 R S T AH0 N +HAIRSTYLE HH EH1 R S T AY2 L +HAIRY HH EH1 R IY0 +HAISLEY HH EY1 Z L IY0 +HAISLIP HH AY1 S L IH0 P +HAIST HH AA1 IH0 S T +HAIT HH EY1 T +HAITH HH EY1 TH +HAITHCOCK HH EY1 TH K AA2 K +HAITI HH EY1 T IY0 +HAITI'S HH EY1 T IY0 Z +HAITIAN HH EY1 SH AH0 N +HAITIANS HH EY1 SH AH0 N Z +HAITIEN HH EY1 SH AH0 N +HAITIENS HH EY1 SH AH0 N Z +HAITIS HH EY1 T IY0 Z +HAIZLIP HH EY1 Z L IH0 P +HAJDU HH AA1 Y D UW0 +HAJDUK HH AY1 D AH0 K +HAJEK HH AY1 EH0 K +HAJIME HH AA0 JH IY1 M IY0 +HAJJ HH AE1 JH +HAJJAR HH AA0 Y AA1 R +HAKALA HH AH0 K AA1 L AH0 +HAKAN HH EY1 K AH0 N +HAKAN(1) HH AA1 K AH0 N +HAKANSON HH AE1 K AH0 N S AH0 N +HAKE HH EY1 K +HAKEEM HH AA0 K IY1 M +HAKEEM'S HH AA0 K IY1 M Z +HAKES HH EY1 K S +HAKIM HH AA0 K IY1 M +HAKIM(1) AA0 K IY1 M +HAKIM'S HH AA0 K IY1 M Z +HAKIM'S(1) AA0 K IY1 M Z +HAKKI HH AE1 K IY0 +HAKKO HH AE1 K OW0 +HAKON HH AE1 K AH0 N +HAKUHODO HH AA2 K UW2 HH OW1 D OW0 +HAL HH AE1 L +HAL'S HH AE1 L Z +HALAMA HH AA0 L AA1 M AH0 +HALAMANDARIS HH AE2 L AH0 M AE1 N D ER0 IH0 S +HALAS HH AA1 L AH0 Z +HALASZ HH AA1 L AH0 SH +HALBACH HH AE1 L B AA0 K +HALBERG HH AE1 L B ER0 G +HALBERSTADT HH AE1 L B ER0 SH T AE0 T +HALBERSTAM HH AE1 L B ER0 S T AE0 M +HALBERT HH AE1 L B ER0 T +HALBIG HH AE1 L B IH0 G +HALBROOK HH AE1 L B R UH0 K +HALBROOKS HH AE1 L B R UH0 K S +HALBUR HH AE1 L B ER0 +HALBUTOGULLARI HH AE0 L B UW2 T OW2 G UW0 L AA1 R IY0 +HALCION HH AE1 L S IY0 AH0 N +HALCION'S HH AE1 L S IY0 AH0 N Z +HALCOMB HH AE1 L K AH0 M +HALCYON HH AE1 L S IY0 AH0 N +HALCYONE HH AE1 L S IY0 OW0 N +HALD HH AO1 L D +HALDAN HH AE1 L D AH0 N +HALDANA HH AH0 L D AE1 N AH0 +HALDEMAN HH AA1 L D M AH0 N +HALDEMAN(1) HH AA1 L D AH0 M AH0 N +HALDEMAN'S HH AA1 L D M AH0 N Z +HALDEMAN'S(1) HH AA1 L D AH0 M AH0 N Z +HALDEN HH AO1 L D AH0 N +HALDER HH AO1 L D ER0 +HALDERMAN HH AO1 L D ER0 M AH0 N +HALE HH EY1 L +HALE'S HH EY1 L Z +HALEBOPP HH AY0 L B AO1 P +HALEN HH EY1 L EH0 N +HALES HH EY1 L Z +HALEVI HH AH0 L EY1 V IY0 +HALEVI(1) HH AH0 L IY1 V IY0 +HALEY HH EY1 L IY0 +HALEY'S HH EY1 L IY0 Z +HALF HH AE1 F +HALF'S HH AE1 F S +HALF-BAKED HH AE1 F B EY2 K T +HALF-COCK HH AE1 F K AA2 K +HALF-COCKED HH AE1 F K AA2 K T +HALF-DOZEN HH AE1 F D AH2 Z AH0 N +HALF-HEARTED HH AE1 F HH AA2 R T IH0 D +HALF-HOUR HH AE1 F AW2 ER0 +HALF-TIME HH AE1 F T AY2 M +HALFACRE HH AE1 F EY2 K ER0 +HALFBACK HH AE1 F B AE2 K +HALFBACKS HH AE1 F B AE2 K S +HALFDAN HH AE1 L F D AH0 N +HALFERTY HH AE1 F ER0 T IY0 +HALFHEARTED HH AE1 F HH AA2 R T IH0 D +HALFHILL HH AE1 F HH IH2 L +HALFMAN HH AE1 F M AH0 N +HALFMANN HH AE1 F M AH0 N +HALFORD HH AE1 F ER0 D +HALFRIDA HH AE1 F R IH0 D AH0 +HALFTIME HH AE1 F T AY2 M +HALFTIMES HH AE1 F T AY2 M Z +HALFTONE HH AE1 F T OW2 N +HALFTONES HH AE1 F T OW2 N Z +HALFWAY HH AE1 F W EY1 +HALFWIT HH AE1 F W IH0 T +HALFWITS HH AE1 F W IH0 T S +HALGREN HH AE1 L G R EH0 N +HALIBURTON HH AE1 L IH0 B ER2 T AH0 N +HALIBUT HH AE1 L AH0 B AH0 T +HALIDE HH AE1 L AY2 D +HALIFA HH AH0 L IY1 F AH0 +HALIFAX HH AE1 L IH0 F AE2 K S +HALIK HH AE1 L IH0 K +HALIMA HH AH0 L IY1 M AH0 +HALIMEDA HH AA0 L IY0 M EY1 D AH0 +HALITE HH AE1 L AY0 T +HALKO HH AE1 L K OW0 +HALL HH AO1 L +HALL'S HH AO1 L Z +HALLA HH AE1 L AH0 +HALLADAY HH AE1 L AH0 D EY2 +HALLAHAN HH AE1 L AH0 HH AE0 N +HALLAM HH AE1 L AH0 M +HALLANAN HH AE1 L AH0 N AH0 N +HALLANDALE HH AE1 L AH0 N D EY2 L +HALLAS HH AE1 L AH0 Z +HALLAUER HH AE1 L AW0 ER0 +HALLBAUER HH AO1 L B AW2 R +HALLBERG HH AO1 L B ER0 G +HALLE HH AE1 L +HALLE(1) HH AE1 L IY0 +HALLECK HH AE1 L IH0 K +HALLELUJAH HH AE2 L AH0 L UW1 Y AH0 +HALLEN HH AO1 L AH0 N +HALLENBECK HH AO1 L AH0 N B EH2 K +HALLER HH AO1 L ER0 +HALLERAN HH AE1 L ER0 AE0 N +HALLET HH AE1 L IH0 T +HALLETT HH AE1 L IH0 T +HALLEY HH AE1 L IY0 +HALLEY(1) HH EY1 L IY0 +HALLFORD HH AE1 L F ER0 D +HALLGARTEN HH AO1 L G AA2 R T AH0 N +HALLGREN HH AE1 L G R EH0 N +HALLIBURTON HH AE1 L IH0 B ER2 T AH0 N +HALLIBURTON'S HH AE1 L IH0 B ER2 T AH0 N Z +HALLICIFORN HH AH0 L IH1 S IH0 F AO0 R N +HALLIDAY HH AE1 L IH0 D EY2 +HALLIE HH AO1 L IY0 +HALLIGAN HH AE1 L IH0 G AH0 N +HALLIN HH AE1 L IH0 N +HALLINAN HH AE1 L IH0 N AH0 N +HALLING HH AO1 L IH0 NG +HALLINGBY HH AO1 L IH0 NG B IY0 +HALLISEY HH AE1 L IH0 S IY0 +HALLMAN HH AO1 L M AH0 N +HALLMARK HH AA1 L M AA2 R K +HALLMARK'S HH AO1 L M AA2 R K S +HALLMARKS HH AO1 L M AA2 R K S +HALLOCK HH AE1 L AH0 K +HALLORAN HH AE1 L ER0 AH0 N +HALLOW HH AE1 L OW0 +HALLOWAY HH AE1 L OW0 W EY2 +HALLOWE'EN HH AE2 L AH0 W IY1 N +HALLOWED HH AE1 L OW0 D +HALLOWEEN HH AE2 L AH0 W IY1 N +HALLOWELL HH AE1 L AH0 W EH0 L +HALLOWS HH AE1 L OW0 Z +HALLQUIST HH AE1 L K W IH0 S T +HALLS HH AO1 L Z +HALLSTROM HH AE1 L S T R AH0 M +HALLUCINATE HH AH0 L UW1 S AH0 N EY0 T +HALLUCINATED HH AH0 L UW1 S AH0 N EY0 T IH0 D +HALLUCINATES HH AH0 L UW1 S AH0 N EY0 T S +HALLUCINATING HH AH0 L UW1 S AH0 N EY0 T IH0 NG +HALLUCINATING(1) HH AH0 L UW1 S IH0 N EY0 T IH0 NG +HALLUCINATION HH AH0 L UW2 S AH0 N EY1 SH AH0 N +HALLUCINATIONS HH AH0 L UW2 S AH0 N EY1 SH AH0 N Z +HALLUCINATORY HH AH0 L UW1 S AH0 N AH0 T AO2 R IY0 +HALLUCINOGENIC HH AH0 L UW2 S AH0 N AH0 JH EH1 N IH0 K +HALLUM HH AE1 L AH0 M +HALLUMS HH AE1 L AH0 M Z +HALLWARD HH AO1 L W ER0 D +HALLWAY HH AO1 L W EY2 +HALLWAYS HH AO1 L W EY2 Z +HALLWOOD HH AO1 L W UH2 D +HALLY HH AE1 L IY0 +HALM HH AA1 M +HALMI HH AO1 L M IY0 +HALMOS HH AO1 L M OW0 S +HALMSTAD HH AA1 L M S T AE2 D +HALO HH EY1 L OW0 +HALOGEN HH AE1 L AH0 JH AH0 N +HALOGENATE HH AE1 L AH0 JH AH0 N EY2 T +HALOGENATED HH AE1 L AH0 JH AH0 N EY2 T IH0 D +HALON HH EY1 L AA2 N +HALOPHYTIC HH AE2 L AH0 F IH1 T IH0 K +HALOS HH EY1 L OW0 Z +HALPER HH AE1 L P ER0 +HALPERIN HH AE1 L P ER0 IH0 N +HALPERIN(1) HH AE1 L P R IH0 N +HALPERN HH AE1 L P ER0 N +HALPERSTANT HH AE1 L P ER0 S T AH0 N T +HALPERT HH AE1 L P ER0 T +HALPIN HH AE1 L P IH0 N +HALPRIN HH AE1 L P R IH0 N +HALSELL HH AE1 L S AH0 L +HALSETH HH AE1 L S IH0 TH +HALSEY HH AE1 L S IY0 +HALSTEAD HH AE1 L S T EH0 D +HALSTED HH AE1 L S T IH0 D +HALSTON HH AO1 L S T AH0 N +HALSTON'S HH AO1 L S T AH0 N Z +HALT HH AO1 L T +HALTED HH AO1 L T AH0 D +HALTED(1) HH AO1 L T IH0 D +HALTEMAN HH EY1 L T M AH0 N +HALTER HH AO1 L T ER0 +HALTER'S HH AO1 L T ER0 Z +HALTERMAN HH AO1 L T ER0 M AH0 N +HALTERS HH AO1 L T ER0 Z +HALTING HH AO1 L T IH0 NG +HALTINGLY HH AO1 L T IH0 NG L IY0 +HALTIWANGER HH AE1 L T IH0 W AH0 NG ER0 +HALTOM HH AE1 L T AH0 M +HALTON HH AE1 L T AH0 N +HALTS HH AO1 L T S +HALUSKA HH AH0 L AH1 S K AH0 +HALVE HH AE1 V +HALVED HH AE1 V D +HALVERSON HH AE1 L V ER0 S AH0 N +HALVES HH AE1 V Z +HALVING HH AE1 V IH0 NG +HALVORSEN HH AE0 L V AO1 R S AH0 N +HALVORSON HH AE1 L V ER0 S AH0 N +HAM HH AE1 M +HAMA HH AA1 M AH0 +HAMACHER HH AE1 M AH0 K ER0 +HAMAD HH AE1 M AH0 D +HAMADA HH AA0 M AA1 D AH0 +HAMADEI HH AE1 M AH0 D EY2 +HAMADI HH AH0 M AA1 D IY0 +HAMAKER HH AA1 M EY0 K ER0 +HAMAL HH EY1 M AH0 L +HAMAMOTO HH AA0 M AA0 M OW1 T OW0 +HAMAN HH EY1 M AH0 N +HAMANAKA HH AH0 M AH0 N AA1 K AH0 +HAMANN HH AA1 M AH0 N +HAMAR HH AH0 M AA1 R +HAMAS HH AA2 M AA1 S +HAMAS' HH AA2 M AA1 S +HAMASAKI HH AA2 M AA0 S AA1 K IY0 +HAMBELTON HH AH0 M B EH1 L T AH0 N +HAMBERG HH AE1 M B ER0 G +HAMBERGER HH AE1 M B ER0 G ER0 +HAMBLEN HH AE1 M B AH0 L AH0 N +HAMBLET HH AE1 M B L IH0 T +HAMBLETON HH AE1 M B AH0 L T AA0 N +HAMBLEY HH AE1 M B L IY0 +HAMBLIN HH AE1 M B L IH0 N +HAMBLY HH AE1 M B L IY0 +HAMBRECHT HH AE1 M B R EH2 K T +HAMBRICK HH AE1 M B R IH2 K +HAMBRIGHT HH AE1 M B R AY2 T +HAMBRO HH AE1 M B R OW0 +HAMBROS HH AE1 M B R OW0 S +HAMBURG HH AE1 M B ER0 G +HAMBURGER HH AE1 M B ER0 G ER0 +HAMBURGERS HH AE1 M B ER0 G ER0 Z +HAMBY HH AE1 M B IY0 +HAMDAN HH AE1 M D AH0 N +HAMDOON HH AE0 M D UW1 N +HAMDUN HH AE1 M D AH0 N +HAMED HH AE1 M D +HAMEISTER HH AE1 M AY0 S T ER0 +HAMEL HH AE1 M AH0 L +HAMELIN HH AE1 M AH0 L IH0 N +HAMELIN(1) HH AE1 M L IH2 N +HAMER HH AE1 M ER0 +HAMES HH EY1 M Z +HAMID HH AH0 M IY1 D +HAMIEL HH AE1 M IY0 L +HAMIL HH AE1 M AH0 L +HAMILL HH AE1 M AH0 L +HAMILTON HH AE1 M AH0 L T AH0 N +HAMILTON'S HH AE1 M AH0 L T AH0 N Z +HAMILTONIAN HH AE1 M AH0 L T OW2 N Y AH0 N +HAMILTONS HH AE1 M AH0 L T AH0 N Z +HAMISH HH AE1 M IH0 SH +HAMITER HH AE1 M AY0 T ER0 +HAMITIC HH AE0 M IH1 T IH0 K +HAMLER HH AE1 M AH0 L ER0 +HAMLER(1) HH AE1 M L ER0 +HAMLET HH AE1 M L AH0 T +HAMLET(1) HH AE1 M L IH0 T +HAMLETS HH AE1 M L AH0 T S +HAMLETT HH AE1 M L IH0 T +HAMLEY HH AE1 M L IY0 +HAMLEY'S HH AE1 M L IY0 Z +HAMLIN HH AE1 M L IH0 N +HAMLING HH AE1 M L IH0 NG +HAMLISCH HH AE1 M L IH0 SH +HAMLISCH'S HH AE1 M L IH0 SH AH0 Z +HAMM HH AE1 M +HAMMAC HH AE1 M AH0 K +HAMMACHER HH AE1 M AA2 K ER0 +HAMMACK HH AE1 M AH0 K +HAMMAKER HH AE1 M EY2 K ER0 +HAMMAN HH AE1 M AH0 N +HAMMANN HH AE1 M AH0 N +HAMMAR HH AE1 M ER0 +HAMMAS HH AH0 M AA1 S +HAMMAS' HH AH0 M AA1 S +HAMMAS'S HH AH0 M AA1 S IH0 S +HAMME HH AE1 M +HAMMEL HH AE1 M AH0 L +HAMMELL HH AE1 M AH0 L +HAMMEN HH AE1 M AH0 N +HAMMER HH AE1 M ER0 +HAMMER'S HH AE1 M ER0 Z +HAMMERED HH AE1 M ER0 D +HAMMERING HH AE1 M ER0 IH0 NG +HAMMERLE HH AE1 M ER0 AH0 L +HAMMERLOCK HH AE1 M ER0 L AA2 K +HAMMERMAN HH AE1 M ER0 M AH0 N +HAMMERMEISTER HH AE1 M ER0 M AY2 S T ER0 +HAMMERMILL HH AE1 M ER0 M IH2 L +HAMMERS HH AE1 M ER0 Z +HAMMERSCHMIDT HH AE1 M ER0 SH M IH2 T +HAMMERSLEY HH AE1 M ER0 S L IY0 +HAMMERSMITH HH AE1 M ER0 S M IH2 TH +HAMMERSON HH AE1 M ER0 S AH0 N +HAMMERSTEIN HH AE1 M ER0 S T IY2 N +HAMMERSTEIN(1) HH AE1 M ER0 S T AY2 N +HAMMERSTEIN'S HH AE1 M ER0 S T IY2 N Z +HAMMERSTEIN'S(1) HH AE1 M ER0 S T AY2 N Z +HAMMERSTROM HH AE1 M ER0 S T R AH0 M +HAMMES HH AE1 M Z +HAMMETT HH AE1 M IH0 T +HAMMILL HH AE1 M AH0 L +HAMMITT HH AE1 M IH0 T +HAMMOCK HH AE1 M AH0 K +HAMMOCKS HH AE1 M AH0 K S +HAMMON HH AE1 M AH0 N +HAMMOND HH AE1 M AH0 N D +HAMMONDS HH AE1 M AH0 N D Z +HAMMONS HH AE1 M AH0 N Z +HAMMONTREE HH AE0 M AH0 N T R IY1 +HAMMURABI HH AE1 M AH0 R AA2 B IY2 +HAMNER HH AE1 M N ER0 +HAMON HH AE1 M AH0 N +HAMOR HH AE1 M ER0 +HAMP HH AE1 M P +HAMPE HH AE1 M P +HAMPEL HH AE1 M P AH0 L +HAMPER HH AE1 M P ER0 +HAMPERED HH AE1 M P ER0 D +HAMPERING HH AE1 M P ER0 IH0 NG +HAMPERS HH AE1 M P ER0 Z +HAMPLE HH AE1 M P AH0 L +HAMPSHIRE HH AE1 M P SH ER0 +HAMPSHIRE(1) HH AE1 M SH ER0 +HAMPSHIRE(2) HH AE1 M P SH AY0 ER0 +HAMPSHIRE(3) HH AE1 M SH AY0 ER0 +HAMPSHIRE'S HH AE1 M P SH ER0 Z +HAMPSHIRE'S(1) HH AE1 M SH ER0 Z +HAMPSHIRE'S(2) HH AE1 M P SH AY0 ER0 Z +HAMPSHIRE'S(3) HH AE1 M SH AY0 ER0 Z +HAMPSHIRITES HH AE1 M P SH ER0 AY2 T S +HAMPSON HH AE1 M P S AH0 N +HAMPSTEAD HH AE1 M P S T EH2 D +HAMPTON HH AE1 M P T AH0 N +HAMPTON'S HH AE1 M P T AH0 N Z +HAMPTONS HH AE1 M P T AH0 N Z +HAMPTONSHIRE HH AE1 M P T AH0 N SH ER0 +HAMPTONSHIRE'S HH AE1 M P T AH0 N SH ER0 Z +HAMRE HH AE1 M ER0 +HAMRIC HH AE1 M R IH0 K +HAMRICK HH AE1 M R IH0 K +HAMROCK HH AE1 M R AA2 K +HAMS HH AE1 M Z +HAMSHER HH AE1 M SH ER0 +HAMSON HH AE1 M S AH0 N +HAMSPHIRE HH AE1 M S F AY2 R +HAMSTER HH AE1 M S T ER0 +HAMSTERS HH AE1 M S T ER0 Z +HAMSTRA HH AE1 M S T R AH0 +HAMSTRING HH AE1 M S T R IH2 NG +HAMSTRINGS HH AE1 M S T R IH2 NG Z +HAMSTRUNG HH AE1 M S T R AH0 NG +HAMTRAMCK HH AE0 M T R AE1 M IH0 K +HAN HH AA1 N +HAN(1) HH AE1 N +HAN'S HH AA1 N Z +HAN'S(1) HH AE1 N Z +HANA HH AE1 N AH0 +HANAFIN HH AE1 N AH0 F IH0 N +HANAGAN HH AA0 N AA1 G AA0 N +HANAHAN HH AE1 N AH0 HH AE0 N +HANAK HH AA1 N AH0 K +HANAN HH EY1 N AH0 N +HANAS HH AE1 N AH0 Z +HANAUER HH AE1 N AW0 ER0 +HANAWALT HH AE1 N AH0 W AO2 L T +HANAWAY HH AE1 N AH0 W EY0 +HANBACK HH AE1 N B AE2 K +HANBERRY HH AE1 N B EH2 R IY0 +HANBO HH AE1 N B OW0 +HANBURY HH AE1 N B EH2 R IY0 +HANBY HH AE1 N B IY0 +HANCE HH AE1 N S +HANCHER HH AE1 N CH ER0 +HANCHETT HH AE1 N CH IH0 T +HANCHEY HH AE1 N CH IY0 +HANCOCK HH AE1 N K AA2 K +HANCOCK'S HH AE1 N K AA2 K S +HANCOX HH AE1 N K AA0 K S +HAND HH AE1 N D +HAND'S HH AE1 N D Z +HAND-HELD HH AE1 N D HH EH2 L D +HANDA HH AE1 N D AH0 +HANDBAG HH AE1 N D B AE2 G +HANDBAGS HH AE1 N D B AE2 G Z +HANDBALL HH AE1 N D B AO2 L +HANDBALLS HH AE1 N D B AO2 L Z +HANDBILL HH AE1 N D B IH2 L +HANDBILLS HH AE1 N D B IH2 L Z +HANDBOOK HH AE1 N D B UH2 K +HANDBOOKS HH AE1 N D B UH2 K S +HANDCLASP HH AE1 N D K L AE2 S P +HANDCRAFT HH AE1 N D K R AE2 F T +HANDCRAFTED HH AE1 N D K R AE2 F T IH0 D +HANDCRAFTS HH AE1 N D K R AE2 F T S +HANDCUFF HH AE1 N D K AH2 F +HANDCUFFED HH AE1 N D K AH2 F T +HANDCUFFING HH AE1 N D K AH2 F IH0 NG +HANDCUFFS HH AE1 N D K AH2 F S +HANDED HH AE1 N D AH0 D +HANDED(1) HH AE1 N D IH0 D +HANDEDLY HH AE1 N D IH0 D L IY0 +HANDEDNESS HH AE1 N D AH0 D N AH0 S +HANDEL HH AE1 N D AH0 L +HANDEL'S HH AE1 N D AH0 L Z +HANDELAND HH AE1 N D IH0 L AH0 N D +HANDELMAN HH AE1 N D AH0 L M AH0 N +HANDELS HH AE1 N D AH0 L Z +HANDELSBANK HH AE1 N D AH0 L Z B AE2 NG K +HANDELSBANKEN HH AE2 N D AH0 L S B AE1 NG K AH0 N +HANDELSMAN HH AE1 N D IH0 L S M AH0 N +HANDER HH AE1 N D ER0 +HANDERS HH AE1 N D ER0 Z +HANDFORD HH AE1 N D F ER0 D +HANDFUL HH AE1 N D F UH2 L +HANDFULS HH AE1 N D F UH2 L Z +HANDGUN HH AE1 N D G AH2 N +HANDGUNS HH AE1 N D G AH2 N Z +HANDHELD HH AE1 N D HH EH1 L D +HANDHOLD HH AE1 N D HH OW2 L D +HANDHOLDING HH AE1 N D HH OW2 L D IH0 NG +HANDICAP HH AE1 N D IY0 K AE2 P +HANDICAPPED HH AE1 N D IY0 K AE2 P T +HANDICAPPER HH AE1 N D IY0 K AE2 P ER0 +HANDICAPPERS HH AE1 N D IY0 K AE2 P ER0 Z +HANDICAPPING HH AE1 N D IY0 K AE2 P IH0 NG +HANDICAPS HH AE1 N D IY0 K AE2 P S +HANDICRAFT HH AE1 N D IY0 K R AE2 F T +HANDICRAFTS HH AE1 N D IY0 K R AE2 F T S +HANDIER HH AE1 N D IY0 ER0 +HANDIEST HH AE1 N D IY0 AH0 S T +HANDILY HH AE1 N D AH0 L IY0 +HANDING HH AE1 N D IH0 NG +HANDIWORK HH AE1 N D IY0 W ER2 K +HANDKE HH AE1 N D K IY0 +HANDKERCHIEF HH AE1 NG K ER0 CH IH0 F +HANDKERCHIEF(1) HH AE1 NG K ER0 CH IY0 F +HANDKERCHIEFS HH AE1 NG K ER0 CH AH0 F S +HANDKERCHIEFS(1) HH AE1 NG K ER0 CH IY0 F S +HANDLE HH AE1 N D AH0 L +HANDLEBAR HH AE1 N D AH0 L B AA2 R +HANDLEBARS HH AE1 N D AH0 L B AA2 R Z +HANDLED HH AE1 N D AH0 L D +HANDLER HH AE1 N D L ER0 +HANDLER(1) HH AE1 N D AH0 L ER0 +HANDLERS HH AE1 N D L ER0 Z +HANDLERS(1) HH AE1 N D AH0 L ER0 Z +HANDLES HH AE1 N D AH0 L Z +HANDLEY HH AE1 N D L IY0 +HANDLIN HH AE1 N D L IH0 N +HANDLING HH AE1 N D L IH0 NG +HANDLING(1) HH AE1 N D AH0 L IH0 NG +HANDLON HH AE1 N D L AH0 N +HANDLOOM HH AE1 N D L UW2 M +HANDLOOMS HH AE1 N D L UW2 M Z +HANDLY HH AE1 N D L IY0 +HANDMADE HH AE1 N D M EY1 D +HANDMADE(1) HH AE1 N M EY1 D +HANDOUT HH AE1 N D AW2 T +HANDOUTS HH AE1 N D AW2 T S +HANDOVER HH AE1 N D OW0 V ER0 +HANDPICK HH AE1 N D P IH1 K +HANDPICKED HH AE1 N D P IH1 K T +HANDRAIL HH AE1 N D R EY2 L +HANDRAILS HH AE1 N D R EY2 L Z +HANDRICH HH AE1 N D R IH0 K +HANDROS HH AE1 N D R OW0 S +HANDS HH AE1 N D Z +HANDS(1) HH AE1 N Z +HANDS-ON HH AE2 N Z AO1 N +HANDSAW HH AE1 N D S AO2 +HANDSAWS HH AE1 N D S AO2 Z +HANDSET HH AE1 N D S EH2 T +HANDSETS HH AE1 N D S EH2 T S +HANDSHAKE HH AE1 N D SH EY2 K +HANDSHAKES HH AE1 N D SH EY2 K S +HANDSHAKING HH AE1 N D SH EY2 K IH0 NG +HANDSOME HH AE1 N S AH0 M +HANDSOMELY HH AE1 N S AH0 M L IY0 +HANDSTAND HH AE1 N D S T AE2 N D +HANDSTANDS HH AE1 N D S T AE2 N D Z +HANDWERK HH AE1 N D W ER0 K +HANDWERKER HH AE1 N D W ER0 K ER0 +HANDWOVEN HH AE1 N D W OW1 V AH0 N +HANDWOVEN(1) HH AE1 N W OW1 V AH0 N +HANDWRITING HH AE1 N D R AY2 T IH0 NG +HANDWRITTEN HH AE1 N D R IH2 T AH0 N +HANDY HH AE1 N D IY0 +HANDYMAN HH AE1 N D IY0 M AE2 N +HANDYMEN HH AE1 N D IY0 M EH1 N +HANE HH EY1 N +HANEDA HH AH0 N EY1 D AH0 +HANEL HH AE1 N AH0 L +HANELINE HH AE1 N IH0 L AY2 N +HANEMANN HH EY1 N M AH0 N +HANER HH EY1 N ER0 +HANES HH EY1 N Z +HANEY HH EY1 N IY0 +HANF HH AE1 N F +HANFORD HH AE1 N F ER0 D +HANFT HH AE1 N F T +HANG HH AE1 NG +HANGAR HH AE1 NG ER0 +HANGARS HH AE1 NG ER0 Z +HANGARTNER HH AE1 NG G AA0 R T N ER0 +HANGED HH AE1 NG D +HANGEN HH AE1 NG AH0 N +HANGER HH AE1 NG ER0 +HANGERS HH AE1 NG ER0 Z +HANGIN' HH AE1 NG G IH0 N +HANGING HH AE1 NG IH0 NG +HANGING(1) HH AE1 NG G IH0 NG +HANGINGS HH AE1 NG G IH0 NG Z +HANGMAN HH AE1 NG M AH0 N +HANGOUT HH AE1 NG AW2 T +HANGOUTS HH AE1 NG AW2 T S +HANGOVER HH AE1 NG OW2 V ER0 +HANGOVERS HH AE1 NG OW2 V ER0 Z +HANGS HH AE1 NG Z +HANGSANG HH AE1 NG S AE2 NG +HANGSANG'S HH AE1 NG S AE2 NG Z +HANGUL HH AE1 N G UH2 L +HANGUP HH AE1 NG G AH2 P +HANGUPS HH AE1 NG G AH2 P S +HANI HH AE1 N IY0 +HANI'S HH AE1 N IY0 Z +HANIFEN HH AE1 N IH0 F AH0 N +HANIFIN HH AE1 N IH0 F IH0 N +HANIGAN HH AE1 N IH0 G AH0 N +HANING HH EY1 N IH0 NG +HANISCH HH AE1 N IH0 SH +HANISEE HH AE1 N IH0 S IY0 +HANISH HH AE1 N IH0 SH +HANJIN HH AE1 N JH IH0 N +HANK HH AE1 NG K +HANK'S HH AE1 N K S +HANKE HH AE1 NG K +HANKEL HH AE1 NG K AH0 L +HANKEN HH AE1 NG K AH0 N +HANKER HH AE1 NG K ER0 +HANKERING HH AE1 NG K ER0 IH0 NG +HANKERSON HH AE1 NG K ER0 S AH0 N +HANKES HH AE1 NG K S +HANKEY HH AE1 NG K IY0 +HANKIN HH AE1 NG K IH0 N +HANKINS HH AE1 NG K IH0 N Z +HANKINSON HH AE1 NG K IH0 N S AH0 N +HANKLA HH AE1 NG K L AH0 +HANKO HH AE1 NG K OW0 +HANKS HH AE1 NG K S +HANKY HH AE1 NG K IY0 +HANLEY HH AE1 N L IY0 +HANLEY'S HH AE1 N L IY0 Z +HANLIN HH AE1 N L IH0 N +HANLON HH AE1 N L AH0 N +HANLY HH AE1 N L IY0 +HANMER HH AE1 N M ER0 +HANN HH AE1 N +HANNA HH AE1 N AH0 +HANNA'S HH AE1 N AH0 Z +HANNAFORD HH AE1 N AH0 F ER0 D +HANNAGAN HH AE1 N AH0 G AE0 N +HANNAH HH AE1 N AH0 +HANNAHS HH AE1 N AH0 Z +HANNAM HH AE1 N AH0 M +HANNAMAN HH AE1 N AH0 M AH0 N +HANNAN HH AE1 N AH0 N +HANNAY HH AE1 N EY0 +HANNEKEN HH AE1 N IH0 K AH0 N +HANNEMAN HH AE1 N M AH0 N +HANNEMANN HH AE1 N M AH0 N +HANNEN HH AE1 N AH0 N +HANNER HH AE1 N ER0 +HANNERS HH AE1 N ER0 Z +HANNES HH AE1 N Z +HANNESSON HH AE1 N AH0 S AH0 N +HANNEY HH AE1 N IY0 +HANNI HH AE1 N IY0 +HANNIBAL HH AE1 N IH0 B AH0 L +HANNIE HH AE1 N IY0 +HANNIFIN HH AE1 N IH0 F IH0 N +HANNIG HH AE1 N IH0 G +HANNIGAN HH AE1 N IH0 G AH0 N +HANNING HH AE1 N IH0 NG +HANNIS HH AE1 N IH0 S +HANNITY HH AE1 N IH0 T IY0 +HANNOCH HH AE1 N AH0 K +HANNOLD HH AE1 N OW2 L D +HANNON HH AE1 N AH0 N +HANNULA HH AE1 N UW0 L AH0 +HANNUM HH AE1 N AH0 M +HANNY HH AE1 N IY0 +HANO HH AA1 N OW0 +HANOI HH AE1 N OY0 +HANOI'S HH AH0 N OY1 Z +HANOLD HH AE1 N OW0 L D +HANOVER HH AE1 N OW0 V ER0 +HANOVER'S HH AE1 N OW0 V ER0 Z +HANOVERIAN HH AE2 N OW0 V IH1 R IY0 AH0 N +HANRAHAN HH AE1 N R AH0 HH AE0 N +HANRATTY HH AE1 N R AH0 T IY0 +HANS HH AA1 N S +HANS(1) HH AE1 N Z +HANSA HH AE1 N S AH0 +HANSARD HH AE1 N S ER0 D +HANSBERGER HH AE1 N S B ER0 G ER0 +HANSBERRY HH AE1 N S B EH2 R IY0 +HANSBROUGH HH AE1 N S B R AW0 +HANSBURY HH AE1 N S B EH0 R IY0 +HANSCHE HH AE1 N SH IY0 +HANSCOM HH AE1 N S K AH0 M +HANSEATIC HH AE2 N S IY0 AE1 T IH0 K +HANSEL HH AE1 N S AH0 L +HANSELL HH AE1 N S AH0 L +HANSELMAN HH AE1 N S AH0 L M AH0 N +HANSEN HH AE1 N S AH0 N +HANSEN'S HH AE1 N S AH0 N Z +HANSER HH AA1 N S ER0 +HANSFORD HH AE1 N S F ER0 D +HANSHAW HH AE1 N SH AO2 +HANSHEW HH AE1 N SH UW0 +HANSHIN HH AE1 N SH IH0 N +HANSLEY HH AE1 N S L IY0 +HANSMA HH AE1 N S M AH0 +HANSMAN HH AE1 N S M AH0 N +HANSMANN HH AE1 N S M AH0 N +HANSOM HH AE1 N S AH0 M +HANSON HH AE1 N S AH0 N +HANSON'S HH AE1 N S AH0 N Z +HANSSEN HH AE1 N S AH0 N +HANSSON HH AE1 N S AH0 N +HANTA HH AE1 N T AH0 +HANTA(1) HH AA1 N T AH0 +HANTAVIRUS HH AE1 N T AH0 V AY2 R AH0 S +HANTEN HH AE1 N T AH0 N +HANTHORN HH AE1 N TH ER0 N +HANTMAN HH AE1 N T M AH0 N +HANTZ HH AE1 N T S +HANUKKAH HH AA1 N AH0 K AH0 +HANUKKAH'S HH AA1 N AH0 K AH0 Z +HANUKKAHS HH AA1 N AH0 K AH0 Z +HANUS HH EY1 N IH0 S +HANVEY HH AE1 N V IY0 +HANWA HH AE1 N W AH0 +HANWA'S HH AE1 N W AH0 Z +HANWAY HH AE1 N W EY2 +HANY HH EY1 N IY0 +HANY'S HH EY1 N IY0 Z +HANZEL HH AE1 N Z AH0 L +HANZLIK HH AE1 N Z L IH0 K +HAO HH AW1 +HAO-CHI HH AW1 CH IY1 +HAP HH AE1 P +HAPAG HH EY1 P AE2 G +HAPEMAN HH EY1 P M AH0 N +HAPGOOD HH AE1 P G UH2 D +HAPHAZARD HH AE0 P HH AE1 Z ER0 D +HAPHAZARDLY HH AE1 F AH0 Z ER0 D L IY0 +HAPHAZARDLY(1) HH AE0 P HH AE1 Z ER0 D L IY0 +HAPKE HH EY1 P K IY0 +HAPLESS HH AE1 P L AH0 S +HAPLOID HH AE1 P L OY0 D +HAPNER HH AE1 P N ER0 +HAPOALIM HH AH0 P OW1 AH0 L IY0 M +HAPOALIM(1) HH AH0 P OW2 AH0 L IY1 M +HAPP HH AE1 P +HAPPE HH AE1 P +HAPPEL HH AE1 P AH0 L +HAPPEN HH AE1 P AH0 N +HAPPENED HH AE1 P AH0 N D +HAPPENING HH AE1 P AH0 N IH0 NG +HAPPENING(1) HH AE1 P N IH0 NG +HAPPENINGS HH AE1 P AH0 N IH0 NG Z +HAPPENINGS(1) HH AE1 P N IH0 NG Z +HAPPENS HH AE1 P AH0 N Z +HAPPENSTANCE HH AE1 P AH0 N S T AE2 N S +HAPPIER HH AE1 P IY0 ER0 +HAPPIEST HH AE1 P IY0 AH0 S T +HAPPILY HH AE1 P AH0 L IY0 +HAPPINESS HH AE1 P IY0 N AH0 S +HAPPY HH AE1 P IY0 +HAPSBURG HH AE1 P S B ER0 G +HAQ HH AE1 K +HAQ'S HH AE1 K S +HAQUE HH AE1 K +HAR HH AA1 R +HARA HH EH1 R AH0 +HARA-KIRI HH AA1 R IH0 K IH1 R IY0 +HARADA HH AA0 R AA1 D AH0 +HARADIM HH AH0 R AE1 D IH2 M +HARADIM(1) HH AH0 R AE2 D IY1 M +HARAHAN HH AE1 R AH0 HH AE2 N +HARALD HH AA1 R AH0 L D +HARALDA HH AA0 R AA1 L D AH0 +HARALSON HH AE1 R AH0 L S AH0 N +HARAN HH AE1 R AH0 N +HARANGUE HH ER0 AE1 NG +HARANGUED HH ER0 AE1 NG D +HARANGUES HH ER0 AE1 NG Z +HARANGUING HH ER0 AE1 NG IH0 NG +HARARE HH ER0 AA1 R IY0 +HARASS HH ER0 AE1 S +HARASSED HH ER0 AE1 S T +HARASSER HH ER0 AE1 S ER0 +HARASSERS HH ER0 AE1 S ER0 Z +HARASSES HH ER0 AE1 S IH0 Z +HARASSING HH ER0 AE1 S IH0 NG +HARASSMENT HH ER0 AE1 S M AH0 N T +HARASZTI HH ER0 AE1 S T IY0 +HARAWAY HH AA1 R AH0 W EY0 +HARB HH AA1 R B +HARBACH HH AA1 R B AA2 K +HARBAUGH HH AA1 R B AO2 +HARBECK HH AA1 R B EH2 K +HARBER HH AA1 R B ER0 +HARBERT HH AA1 R B ER0 T +HARBERTS HH AA1 R B ER0 T S +HARBESON HH AA1 R B IH0 S AH0 N +HARBIN HH AA1 R B IH0 N +HARBINGER HH AA1 R B IH0 N JH ER0 +HARBINGERS HH AA1 R B IH0 NG ER0 Z +HARBINSON HH AA1 R B IH0 N S AH0 N +HARBISON HH AA1 R B IH0 S AH0 N +HARBOLD HH AA1 R B OW2 L D +HARBOR HH AA1 R B ER0 +HARBOR'S HH AA1 R B ER0 Z +HARBORED HH AA1 R B ER0 D +HARBORING HH AA1 R B ER0 IH0 NG +HARBORS HH AA1 R B ER0 Z +HARBORSIDE HH AA1 R B ER0 S AY2 D +HARBORY HH AA1 R B AH0 R IY0 +HARBOUR HH AA1 R B ER0 +HARBUCK HH AA1 R B AH0 K +HARBURY HH AA1 R B ER0 IY0 +HARC HH AA1 R K +HARCLERODE HH AA1 R K AH0 L ER0 OW0 D +HARCLERODE(1) HH AA1 R K L ER0 OW0 D +HARCOURT HH AA1 R K AO2 R T +HARCOURT'S HH AA1 R K ER0 T S +HARCROW HH AA1 R K R OW0 +HARCUM HH AA1 R K AH0 M +HARD HH AA1 R D +HARD-ASS HH AA2 R D AE2 S +HARD-WORKING HH AA2 R D W ER1 K IH0 NG +HARDACRE HH AA1 R D EY2 K ER0 +HARDAGE HH AA1 R D IH0 JH +HARDART HH AA1 R D AA2 R T +HARDAWAY HH AA1 R D AH0 W EY2 +HARDBACK HH AA1 R D B AE2 K +HARDBALL HH AA1 R D B AO2 L +HARDBOARD HH AA1 R D B AO2 R D +HARDCASTLE HH AA1 R D K AE2 S AH0 L +HARDCASTLE'S HH AA1 R D K AE2 S AH0 L Z +HARDCORE HH AA1 R D K AO1 R +HARDCOVER HH AA1 R D K AH2 V ER0 +HARDCOVERS HH AA1 R D K AH2 V ER0 Z +HARDEBECK HH AA1 R D B EH0 K +HARDEE HH AA1 R D IY1 +HARDEE'S HH AA1 R D IY1 Z +HARDEGREE HH AA0 R D IH0 G R IY1 +HARDEMAN HH AA1 R D M AH0 N +HARDEN HH AA1 R D AH0 N +HARDEN'S HH AA1 R D AH0 N Z +HARDENBROOK HH AA1 R D AH0 N B R UH2 K +HARDENED HH AA1 R D AH0 N D +HARDENER HH AA1 R D AH0 N ER0 +HARDENERS HH AA1 R D AH0 N ER0 Z +HARDENING HH AA1 R D AH0 N IH0 NG +HARDENING(1) HH AA1 R D N IH0 NG +HARDENS HH AA1 R D AH0 N Z +HARDER HH AA1 R D ER0 +HARDERS HH AA1 R D ER0 Z +HARDEST HH AA1 R D AH0 S T +HARDESTY HH AA1 R D AH0 S T IY0 +HARDEY HH AA1 R D IY0 +HARDGOOD HH AA1 R D G UH2 D +HARDGOODS HH AA1 R D G UH2 D Z +HARDGRAVE HH AA1 R D G R EY2 V +HARDGROVE HH AA1 R D G R OW2 V +HARDHEAD HH AA1 R D HH EH2 D +HARDHEADED HH AA1 R D HH EH2 D IH0 D +HARDICK HH AA1 R D IH0 K +HARDIE HH AA1 R D IY0 +HARDIER HH AA1 R D IY0 ER0 +HARDIEST HH AA1 R D IY0 AH0 S T +HARDIGREE HH AA0 R D IH0 G R IY1 +HARDIMAN HH AA1 R D IH0 M AH0 N +HARDIMON HH AA1 R D IH0 M AA0 N +HARDIN HH AA1 R D IH0 N +HARDING HH AA1 R D IH0 NG +HARDING'S HH AA1 R D IH0 NG S +HARDINGER HH AA1 R D IH0 NG ER0 +HARDISON HH AA1 R D IH0 S AH0 N +HARDISTER HH AA1 R D IH0 S T ER0 +HARDISTY HH AA1 R D IH0 S T IY0 +HARDLINE HH AA1 R D L AY2 N +HARDLINER HH AA1 R D L AY2 N ER0 +HARDLINERS HH AA1 R D L AY2 N ER0 Z +HARDLY HH AA1 R D L IY0 +HARDMAN HH AA1 R D M AH0 N +HARDNESS HH AA1 R D N AH0 S +HARDNETT HH AA1 R D N IH0 T +HARDPRESSED HH AA1 R D P R EH2 S T +HARDRICK HH AA1 R D R IH0 K +HARDS HH AA1 R D Z +HARDSCRABBLE HH AA1 R D S K R AE2 B AH0 L +HARDSHIP HH AA1 R D SH IH0 P +HARDSHIPS HH AA1 R D SH IH0 P S +HARDT HH AA1 R T +HARDTKE HH AA1 R D K IY0 +HARDWARE HH AA1 R D W EH2 R +HARDWAY HH AA1 R D W EY2 +HARDWICK HH AA1 R D W IH2 K +HARDWICKE HH AA1 R D W IH0 K +HARDWIN HH AA1 R D W IH0 N +HARDWIRED HH AA2 R D W AY1 ER0 D +HARDWOOD HH AA1 R D W UH2 D +HARDWOODS HH AA1 R D W UH2 D Z +HARDWORK HH AA1 R D W ER2 K +HARDWORKING HH AA1 R D W ER2 K IH0 NG +HARDY HH AA1 R D IY0 +HARDY'S HH AA1 R D IY0 Z +HARDYMON HH AA1 R D IY0 M AA2 N +HARE HH EH1 R +HARE'S HH EH1 R Z +HAREBRAINED HH EH1 R B R EY2 N D +HARELSON HH AE1 R IH0 L S AH0 N +HAREM HH EH1 R AH0 M +HAREN HH EH1 R AH0 N +HARER HH EH1 R ER0 +HARES HH EH1 R Z +HAREWOOD HH EH1 R W UH2 D +HARFF HH AA1 R F +HARFORD HH AA1 R F ER0 D +HARGADON HH AA0 R G AA0 D AO1 N +HARGAN HH AA1 R G AH0 N +HARGARTEN HH AA1 R G AA0 R T AH0 N +HARGENS HH AA1 R G AH0 N Z +HARGER HH AA1 R G ER0 +HARGETT HH AA1 R JH IH0 T +HARGIS HH AA1 R G IH0 S +HARGRAVE HH AA1 R G R EY2 V +HARGRAVES HH AA1 R G R EY2 V Z +HARGREAVES HH AA1 R G R IY2 V Z +HARGROVE HH AA1 R G R OW2 V +HARGUS HH AA1 R G AH0 S +HARI HH AA1 R IY0 +HARIG HH AE1 R IH0 G +HARIMA HH EH0 R IY1 M AH0 +HARING HH EH1 R IH0 NG +HARIRI HH ER0 IH1 R IY0 +HARIS HH AA1 R IY0 S +HARIS(1) HH EH1 R IH0 S +HARITOS HH EH0 R IY1 T OW0 S +HARIZ HH EH1 R IH0 Z +HARJO HH AA1 R JH OW0 +HARJU HH AA1 R Y UW0 +HARK HH AA1 R K +HARKAVY HH AA1 R K AH0 V IY0 +HARKE HH AA1 R K +HARKEN HH AA1 R K AH0 N +HARKENS HH AA1 R K AH0 N Z +HARKER HH AA1 R K ER0 +HARKEY HH AA1 R K IY0 +HARKIN HH AA1 R K IH0 N +HARKIN'S HH AA1 R K IH0 N Z +HARKING HH AA1 R K IH0 NG +HARKINS HH AA1 R K IH0 N Z +HARKLEROAD HH AA1 R K L ER0 OW0 D +HARKLESS HH AA1 R K L AH0 S +HARKNESS HH AA1 R K N AH0 S +HARKRADER HH AA1 R K R AH0 D ER0 +HARKRIDER HH AA1 R K R AY2 D ER0 +HARKS HH AA1 R K S +HARL HH AA1 R L +HARLACHER HH AA1 R L AH0 K ER0 +HARLAN HH AA1 R L AH0 N +HARLAND HH AA1 R L AH0 N D +HARLE HH AA1 R AH0 L +HARLEM HH AA1 R L AH0 M +HARLEM'S HH AA1 R L AH0 M Z +HARLEMAN HH AA1 R AH0 L M AH0 N +HARLEQUIN HH AA1 R L AH0 K W AH0 N +HARLESS HH AA1 R L IH0 S +HARLEY HH AA1 R L IY0 +HARLEY'S HH AA1 R L IY0 Z +HARLEYSVILLE HH AA1 R L IY0 Z V IH2 L +HARLIN HH AA1 R L IH0 N +HARLIN'S HH AA1 R L IH0 N Z +HARLING HH AA1 R L IH0 NG +HARLINGEN HH AA1 R L IH0 NG AH0 N +HARLISON HH AA1 R L IH0 S AH0 N +HARLOFF HH AA1 R L AO0 F +HARLOT HH AA1 R L AH0 T +HARLOW HH AA1 R L OW0 +HARM HH AA1 R M +HARM'S HH AA1 R M Z +HARMAN HH AA1 R M AH0 N +HARMATA HH AA0 R M AA1 T AH0 +HARMATTAN HH AA2 R M AH0 T AE1 N +HARMED HH AA1 R M D +HARMEL HH AA1 R M AH0 L +HARMEN HH AA1 R M AH0 N +HARMENING HH AA1 R M AH0 N IH0 NG +HARMER HH AA1 R M ER0 +HARMES HH AA1 R M Z +HARMETZ HH AA1 R M EH2 T S +HARMEYER HH AA1 R M AY2 ER0 +HARMFUL HH AA1 R M F AH0 L +HARMFULLY HH AA1 R M F AH0 L IY0 +HARMFULNESS HH AA1 R M F AH0 L N AH0 S +HARMING HH AA1 R M IH0 NG +HARMISON HH AA1 R M IH0 S AH0 N +HARMLESS HH AA1 R M L AH0 S +HARMLESSLY HH AA1 R M L AH0 S L IY0 +HARMON HH AA1 R M AH0 N +HARMON'S HH AA1 R M AH0 N Z +HARMONIA HH AA0 R M OW1 N IY0 AH0 +HARMONIC HH AA0 R M AA1 N IH0 K +HARMONICA HH AA0 R M AA1 N IH0 K AH0 +HARMONICS HH AA0 R M AA1 N IH0 K S +HARMONIE HH AA1 R M AH0 N IY0 +HARMONIES HH AA1 R M AH0 N IY0 Z +HARMONIOUS HH AA0 R M OW1 N IY0 AH0 S +HARMONIOUSLY HH AA0 R M OW1 N IY0 AH0 S L IY0 +HARMONIUM HH AA0 R M OW1 N IY0 AH0 M +HARMONIZATION HH AA2 R M AH0 N IH0 Z EY1 SH AH0 N +HARMONIZE HH AA1 R M AH0 N AY2 Z +HARMONIZED HH AA1 R M AH0 N AY2 Z D +HARMONIZES HH AA1 R M AH0 N AY2 Z IH0 Z +HARMONIZING HH AA1 R M AH0 N AY2 Z IH0 NG +HARMONY HH AA1 R M AH0 N IY0 +HARMS HH AA1 R M Z +HARMSEN HH AA1 R M S AH0 N +HARN HH AA1 R N +HARNACK HH AA1 R N AH0 K +HARNAGE HH AA1 R N IH0 JH +HARNDEN HH AA1 R N D AH0 N +HARNE HH AA1 R N +HARNED HH AA1 R N D +HARNER HH AA1 R N ER0 +HARNESS HH AA1 R N AH0 S +HARNESS(1) HH AA1 R N IH0 S +HARNESSED HH AA1 R N AH0 S T +HARNESSES HH AA1 R N AH0 S AH0 Z +HARNESSES(1) HH AA1 R N AH0 S IH0 Z +HARNESSING HH AA1 R N AH0 S IH0 NG +HARNETT HH AA1 R N IH0 T +HARNEY HH AA1 R N IY0 +HARNISCH HH AA1 R N IH0 SH +HARNISCHFEGER HH AA1 R N IH0 SH F EH2 G ER0 +HARNISCHFEGER'S HH AA1 R N IH0 SH F EH2 G ER0 Z +HARNISH HH AA1 R N IH0 SH +HARNOIS HH AA0 R N W AA1 +HARO HH AA1 R OW0 +HAROLD HH EH1 R AH0 L D +HAROLD'S HH EH1 R AH0 L D Z +HAROLDSON HH AE1 R OW0 L D S AH0 N +HARP HH AA1 R P +HARPE HH AA1 R P +HARPED HH AA1 R P T +HARPEL HH AA0 R P EH1 L +HARPENAU HH AA1 R P IH0 N OW0 +HARPER HH AA1 R P ER0 +HARPER'S HH AA1 R P ER0 Z +HARPERCOLLINS HH AA1 R P ER0 K AO1 L IH0 N Z +HARPERS HH AA1 R P ER0 Z +HARPHAM HH AA1 R F AH0 M +HARPIN HH AA0 R P AE1 N +HARPING HH AA1 R P IH0 NG +HARPIST HH AA1 R P IH0 S T +HARPISTS HH AA1 R P IH0 S T S +HARPLEY HH AA1 R P L IY0 +HARPO HH AA1 R P OW0 +HARPOLD HH AA1 R P OW2 L D +HARPOLE HH AA1 R P OW2 L +HARPOON HH AA0 R P UW1 N +HARPOONS HH AA0 R P UW1 N Z +HARPOOTLIAN HH AA0 R P UW1 T L IY0 AH0 N +HARPS HH AA1 R P S +HARPSICHORD HH AA1 R P S AH0 K AO2 R D +HARPST HH AA1 R P S T +HARPSTER HH AA1 R P S T ER0 +HARQUEBUS HH AA1 R K W AH0 B AH0 S +HARR HH AE1 R +HARRA HH AA1 R AH0 +HARRAH HH AE1 R AH0 +HARRAH'S HH EH1 R AH0 Z +HARRAL HH AE1 R AH0 L +HARRALSON HH AE1 R AH0 L S AH0 N +HARRE HH AE1 R +HARREL HH AE1 R AH0 L +HARRELD HH AE1 R IH0 L D +HARRELL HH EH1 R AH0 L +HARRELL'S HH AE1 R AH0 L Z +HARRELSON HH EH1 R IH0 L S AH0 N +HARREN HH AE1 R AH0 N +HARRER HH AA1 R ER0 +HARRIED HH EH1 R IY0 D +HARRIER HH EH1 R IY0 ER0 +HARRIES HH EH1 R IY0 Z +HARRIET HH EH1 R IY0 AH0 T +HARRIETTE HH AE1 R IY0 EH0 T +HARRIGAN HH EH1 R IH0 G AH0 N +HARRIGER HH AE1 R IH0 G ER0 +HARRILL HH AE1 R AH0 L +HARRIMAN HH EH1 R IH0 M AH0 N +HARRING HH AE1 R IH0 NG +HARRINGTON HH EH1 R IH0 NG T AH0 N +HARRIOTT HH AE1 R IY0 AH0 T +HARRIS HH EH1 R IH0 S +HARRIS' HH EH1 R IH0 S +HARRIS'S HH EH1 R IH0 S IH0 Z +HARRISBURG HH AE1 R IH0 S B ER0 G +HARRISBURG(1) HH EH1 R IH0 S B ER0 G +HARRISBURG'S HH AE1 R IH0 S B ER0 G Z +HARRISBURG'S(1) HH EH1 R IH0 S B ER0 G Z +HARRISBURGH HH AE1 R IH0 S B ER0 G +HARRISBURGH(1) HH EH1 R IH0 S B ER0 G +HARRISBURGH'S HH AE1 R IH0 S B ER0 G Z +HARRISBURGH'S(1) HH EH1 R IH0 S B ER0 G Z +HARRISES HH AE1 R IH0 S IH0 Z +HARRISON HH EH1 R IH0 S AH0 N +HARRISON'S HH EH1 R IH0 S AH0 N Z +HARRISS HH AE1 R IH0 S +HARRITY HH AE1 R IH0 T IY0 +HARROD HH EH1 R AH0 D +HARROD'S HH EH1 R AH0 D Z +HARRODS HH EH1 R AH0 D Z +HARROLD HH EH1 R AH0 L D +HARRON HH AE1 R AH0 N +HARROP HH EH1 R AH0 P +HARROUN HH ER0 UW1 N +HARROW HH AE1 R OW0 +HARROWER HH AE1 R OW0 W ER0 +HARROWING HH EH1 R OW0 IH0 NG +HARRY HH EH1 R IY0 +HARRY'S HH EH1 R IY0 Z +HARRYMAN HH AE1 R IY0 M AH0 N +HARSCH HH AA1 R SH +HARSCO HH AA1 R S K OW0 +HARSH HH AA1 R SH +HARSHA HH AA1 R SH AH0 +HARSHAM HH AA1 R SH AH0 M +HARSHAW HH AA1 R SH AO2 +HARSHBARGER HH AA1 R SH B AA2 R G ER0 +HARSHBERGER HH AA1 R SH B ER0 G ER0 +HARSHER HH AA1 R SH ER0 +HARSHEST HH AA1 R SH AH0 S T +HARSHFIELD HH AA1 R SH F IY2 L D +HARSHLY HH AA1 R SH L IY0 +HARSHMAN HH AA1 R SH M AH0 N +HARSHNESS HH AA1 R SH N AH0 S +HARSTAD HH AA1 R S T AH0 D +HARSTON HH AA1 R S T AH0 N +HART HH AA1 R T +HART'S HH AA1 R T S +HARTE HH AA1 R T +HARTEL HH AA1 R T AH0 L +HARTELL HH AA1 R T AH0 L +HARTEN HH AA1 R T AH0 N +HARTENSTEIN HH AA1 R T AH0 N S T AY2 N +HARTENSTEIN(1) HH AA1 R T AH0 N S T IY2 N +HARTER HH AA1 R T ER0 +HARTFIEL HH AA1 R T F IY2 L +HARTFIELD HH AA1 R T F IY2 L D +HARTFORD HH AA1 R T F ER0 D +HARTFORD'S HH AA1 R T F ER0 D Z +HARTGRAVES HH AA1 R T G R EY2 V Z +HARTGROVE HH AA1 R T G R OW2 V +HARTH HH AA1 R TH +HARTIG HH AA1 R T IH0 G +HARTIGAN HH AA1 R T IH0 G AH0 N +HARTIN HH AA1 R T IH0 N +HARTING HH AA1 R T IH0 NG +HARTINGER HH AA1 R T IH0 NG ER0 +HARTIS HH AA1 R T IH0 S +HARTJE HH AA1 R T JH EY0 +HARTKE HH AA1 R T K IY0 +HARTKOPF HH AA1 R T K AO0 F +HARTL HH AA1 R T AH0 L +HARTLAGE HH AA1 R T L IH0 JH +HARTLAND HH AA1 R T L AH0 N D +HARTLAUB HH AA1 R T L AW2 B +HARTLE HH AA1 R T AH0 L +HARTLESS HH AA1 R T L AH0 S +HARTLEY HH AA1 R T L IY0 +HARTLIEB HH AA1 R T L IY2 B +HARTLINE HH AA1 R T L AY2 N +HARTLING HH AA1 R T L IH0 NG +HARTMAN HH AA1 R T M AH0 N +HARTMANN HH AA1 R T M AH0 N +HARTMARX HH AA1 R T M AA2 R K S +HARTNELL HH AA1 R T N AH0 L +HARTNER HH AA1 R T N ER0 +HARTNESS HH AA1 R T N AH0 S +HARTNETT HH AA1 R T N IH0 T +HARTNEY HH AA1 R T N IY0 +HARTOG HH AA1 R T AH0 G +HARTON HH AA1 R T AH0 N +HARTONG HH AA1 R T AO0 NG +HARTRANFT HH AA1 R T R AH2 N F T +HARTS HH AA1 R T S +HARTSELL HH AA1 R T S AH0 L +HARTSFIELD HH AA1 R T S F IY2 L D +HARTSHORN HH AA1 R T S HH AO2 R N +HARTSHORNE HH AA1 R CH ER0 N +HARTSOCK HH AA1 R T S AH0 K +HARTSOE HH AA1 R T S OW0 +HARTSON HH AA1 R T S AH0 N +HARTSOOK HH AA1 R T S UH0 K +HARTSOUGH HH AA1 R T S AW0 +HARTSTEIN HH AA1 R T S T AY2 N +HARTSTEIN(1) HH AA1 R T S T IY2 N +HARTSVILLE HH AA1 R T S V IH0 L +HARTT HH AA1 R T +HARTTER HH AA1 R T ER0 +HARTUNG HH AA1 R T AH0 NG +HARTWELL HH AA1 R T W EH2 L +HARTWICK HH AA1 R T W IH2 K +HARTWIG HH AA1 R T W IH0 K +HARTWOOD HH AA1 R T W UH2 D +HARTY HH AA1 R T IY0 +HARTZ HH AA1 R T S +HARTZEL HH AA1 R T Z AH0 L +HARTZELL HH AA1 R T Z AH0 L +HARTZLER HH AA1 R T S L ER0 +HARTZOG HH AA1 R T Z AH0 G +HARUO HH AA0 R UW1 OW0 +HARV HH AA1 R V +HARVARD HH AA1 R V ER0 D +HARVARD'S HH AA1 R V ER0 D Z +HARVATH HH AA1 R V AH0 TH +HARVE HH AA1 R V +HARVEL HH AA1 R V AH0 L +HARVELL HH AA1 R V AH0 L +HARVEST HH AA1 R V AH0 S T +HARVESTABLE HH AA1 R V AH0 S T AH0 B AH0 L +HARVESTED HH AA1 R V AH0 S T IH0 D +HARVESTER HH AA1 R V AH0 S T ER0 +HARVESTERS HH AA1 R V AH0 S T ER0 Z +HARVESTING HH AA1 R V AH0 S T IH0 NG +HARVESTS HH AA1 R V AH0 S T S +HARVEY HH AA1 R V IY0 +HARVEY'S HH AA1 R V IY0 Z +HARVIE HH AA1 R V IY0 +HARVILL HH AA1 R V IH0 L +HARVILLE HH AA1 R V IH2 L +HARVIN HH AA1 R V IH0 N +HARVISON HH AA1 R V IH0 S AH0 N +HARWARD HH AA1 R W ER0 D +HARWELL HH AA1 R W EH2 L +HARWICK HH AA1 R W IH0 K +HARWOOD HH AA1 R W UH2 D +HARYANA HH EH0 R Y AA1 N AH0 +HAS HH AE1 Z +HAS(1) HH AH0 Z +HAS-BEEN HH AE1 Z B IH2 N +HAS-BEENS HH AE1 Z B IH2 N Z +HASAN HH AA2 S AA1 N +HASBRO HH AE1 Z B R OW0 +HASBRO'S HH AE1 Z B R OW2 Z +HASBROOK HH AE1 S B R UH0 K +HASBROUCK HH AE1 Z B R UH2 K +HASCALL HH AE1 S K AH0 L +HASCH HH AE1 SH +HASCHKE HH AE1 SH K +HASE HH EY1 Z +HASEGAWA HH AA2 S EY0 G AA1 W AH0 +HASEK HH AA1 S EH0 K +HASELDEN HH AE1 S IH0 L D AH0 N +HASELEY HH AE1 S IH0 L IY0 +HASELHORST HH AE1 S IH0 L HH AO0 R S T +HASELTINE HH AE1 S IH0 L T IY0 N +HASELTON HH AH0 S EH1 L T AH0 N +HASEMAN HH EY1 S M AH0 N +HASENAUER HH AE1 S IH0 N AW0 ER0 +HASENFUS HH EY1 Z AH0 N F AH2 S +HASER HH EH1 Z ER0 +HASH HH AE1 SH +HASHAGEN HH AE1 SH AH0 G AH0 N +HASHED HH AE1 SH T +HASHEM HH AE1 SH IH0 M +HASHEMI HH AH0 SH EY1 M IY0 +HASHEMITE HH AE1 SH AH0 M AY2 T +HASHER HH AE1 SH ER0 +HASHER'S HH AE1 SH ER0 Z +HASHERS HH AE1 SH ER0 Z +HASHES HH AE1 SH AH0 Z +HASHI HH AE1 SH IY2 +HASHIM HH AE1 SH IH0 M +HASHIMOTO HH AA0 SH IY0 M OW1 T OW0 +HASHING HH AE1 SH IH0 NG +HASHISH HH AE0 SH IY1 SH +HASHMAN HH AE1 SH M AH0 N +HASHMARK HH AE1 SH M AA2 R K +HASHMI HH AE1 SH M IY0 +HASHMI(1) HH AA1 SH M IY0 +HASHTAG HH AE1 SH T AE2 G +HASID HH AH0 S IH1 D +HASIDIC HH AH0 S IH1 D IH0 K +HASIDIC(1) HH AH0 S IY1 D IH0 K +HASIDIM HH AH0 S IH1 D IH0 M +HASIDIM(1) HH AH0 S IY1 D IH0 M +HASIDS HH AH0 S IH1 D Z +HASKE HH EY1 S K +HASKELL HH AE1 S K AH0 L +HASKETT HH AE1 S K IH0 T +HASKEW HH AE1 S K Y UW0 +HASKIN HH AE1 S K IH0 N +HASKINS HH AE1 S K IH0 N Z +HASLAM HH AE1 S L AH0 M +HASLER HH AE1 S AH0 L ER0 +HASLER(1) HH AE1 S L ER0 +HASLETT HH AE1 S L IH0 T +HASLEY HH AE1 Z L IY0 +HASMAN HH AE1 S M AH0 N +HASN'T HH AE1 Z AH0 N T +HASO HH AA1 S OW2 +HASO'S HH AA1 S OW2 Z +HASPEL HH AE1 S P AH0 L +HASS HH AE1 S +HASSAN HH AH0 S AA1 N +HASSE HH AA1 S +HASSEBROCK HH AE1 S IH0 B R AA1 K +HASSEL HH AE1 S AH0 L +HASSELBACH HH AE1 S IH0 L B AA0 K +HASSELBRING HH AE1 S IH0 L B R IH0 NG +HASSELL HH AE1 S AH0 L +HASSELMAN HH AE1 S AH0 L M AH0 N +HASSEN HH AE1 S AH0 N +HASSENBERG HH AE1 S AH0 N B ER0 G +HASSENFELD HH AE1 S AH0 N F EH2 L D +HASSETT HH AE1 S IH0 T +HASSEY HH AE1 S IY0 +HASSIG HH AE1 S IH0 G +HASSING HH AE1 S IH0 NG +HASSINGER HH AE1 S IH0 N JH ER0 +HASSLE HH AE1 S AH0 L +HASSLED HH AE1 S AH0 L D +HASSLER HH AE1 S L ER0 +HASSLES HH AE1 S AH0 L Z +HASSLING HH AE1 S AH0 L IH0 NG +HASSLING(1) HH AE1 S L IH0 NG +HASSMAN HH AE1 S M AH0 N +HASSON HH AE1 S AH0 N +HAST HH AE1 S T +HASTA HH AE1 S T AH0 +HASTA(1) AA1 S T AH0 +HASTE HH EY1 S T +HASTEN HH EY1 S AH0 N +HASTENED HH EY1 S AH0 N D +HASTENING HH EY1 S AH0 N IH0 NG +HASTENING(1) HH EY1 S N IH0 NG +HASTENS HH EY1 S AH0 N Z +HASTERT HH AE1 S T ER0 T +HASTEY HH EY1 S T IY0 +HASTIE HH EY1 S T IY0 +HASTILY HH EY1 S T AH0 L IY0 +HASTING HH EY1 S T IH0 NG +HASTINGS HH EY1 S T IH0 NG Z +HASTON HH AE1 S T AH0 N +HASTY HH EY1 S T IY0 +HASWELL HH AE1 S W EH0 L +HASZ HH AA1 SH +HAT HH AE1 T +HAT'S HH AE1 T S +HATA HH AA1 T AH0 +HATALA HH AE1 T AH0 L AH0 +HATAWAY HH AE1 T AH0 W EY2 +HATCH HH AE1 CH +HATCH'S HH AE1 CH IH0 Z +HATCHBACK HH AE1 CH B AE2 K +HATCHED HH AE1 CH T +HATCHEL HH AE1 CH AH0 L +HATCHELL HH AE1 CH AH0 L +HATCHER HH AE1 CH ER0 +HATCHERIES HH AE1 CH ER0 IY0 Z +HATCHERY HH AE1 CH ER0 IY0 +HATCHES HH AE1 CH IH0 Z +HATCHET HH AE1 CH AH0 T +HATCHETS HH AE1 CH AH0 T S +HATCHETT HH AE1 CH IH0 T +HATCHING HH AE1 CH IH0 NG +HATE HH EY1 T +HATED HH EY1 T AH0 D +HATED(1) HH EY1 T IH0 D +HATEFUL HH EY1 T F AH0 L +HATEM HH AE1 T IH0 M +HATER HH EY1 T ER0 +HATERS HH EY1 T ER0 Z +HATES HH EY1 T S +HATFIELD HH AE1 T F IY2 L D +HATFIELD'S HH AE1 T F IY2 L D Z +HATH HH AE1 TH +HATHAWAY HH AE1 TH AH0 W EY2 +HATHAWAY'S HH AE1 TH AH0 W EY2 Z +HATHCOAT HH AE1 TH K OW2 T +HATHCOCK HH AE1 TH K AH0 K +HATHEWAY HH EY1 DH W EY0 +HATHORN HH AA1 TH AO0 R N +HATHORNE HH AE1 TH ER0 N +HATING HH EY1 T IH0 NG +HATLER HH EY1 T AH0 L ER0 +HATLER(1) HH EY1 T L ER0 +HATLESTAD HH AE1 T AH0 L S T AH0 D +HATLEY HH AE1 T L IY0 +HATMAKER HH AE1 T M EY2 K ER0 +HATON HH AE1 T AO0 N +HATON(1) AE2 T AO1 N +HATRED HH EY1 T R AH0 D +HATREDS HH EY1 T R AH0 D Z +HATRICK HH AE1 T R IH0 K +HATS HH AE1 T S +HATT HH AE1 T +HATTABAUGH HH AE1 T AH0 B AO0 +HATTAN HH AE1 T AH0 N +HATTAWAY HH AE1 T AH0 W EY0 +HATTEN HH AE1 T AH0 N +HATTENDORF HH AE1 T IH0 N D AO0 R F +HATTER HH AE1 T ER0 +HATTERAS HH AE1 T ER0 AH0 S +HATTERSLEY HH AE1 T ER0 Z L IY0 +HATTERY HH AE1 T ER0 IY0 +HATTIE HH AE1 T IY0 +HATTON HH AE1 T AH0 N +HATTORI HH AA0 T AO1 R IY0 +HATTUSAS HH AH0 T UW1 S AH0 S +HATTY HH AE1 T IY0 +HATZ HH AE1 T S +HAU HH AW1 +HAUB HH AO1 B +HAUBER HH AW1 B ER0 +HAUBERT HH AW1 B ER0 T +HAUBNER HH AW1 B N ER0 +HAUBRICH HH AW1 B R IH0 K +HAUCH HH AO1 CH +HAUCK HH AO1 K +HAUENSTEIN HH AW1 AH0 N S T AY0 N +HAUENSTEIN(1) HH AW1 AH0 N S T IY0 N +HAUER HH AW1 ER0 +HAUETER HH AW1 T ER0 +HAUF HH AO1 F +HAUFER HH AO1 F ER0 +HAUFF HH AO1 F +HAUG HH AO1 G +HAUGAN HH AO1 G AH0 N +HAUGE HH AO1 JH +HAUGEN HH AW1 G AH0 N +HAUGER HH AW1 G ER0 +HAUGH HH AO1 +HAUGHEY HH AO1 K IY0 +HAUGHN HH AO1 N +HAUGHT HH AO1 T +HAUGHTILY HH AO1 T IH0 L IY0 +HAUGHTON HH AO1 T AH0 N +HAUGHTY HH AO1 T IY0 +HAUGLAND HH AO1 G L AH0 N D +HAUK HH AO1 K +HAUKE HH AO1 K +HAUL HH AO1 L +HAULAGE HH AO1 L AH0 JH +HAULED HH AO1 L D +HAULER HH AO1 L ER0 +HAULERS HH AO1 L ER0 Z +HAULING HH AO1 L IH0 NG +HAULS HH AO1 L Z +HAULSEY HH AO1 L S IY0 +HAUN HH AO1 N +HAUNT HH AO1 N T +HAUNTED HH AO1 N T IH0 D +HAUNTING HH AO1 N T IH0 NG +HAUNTINGLY HH AO1 N T IH0 NG L IY0 +HAUNTS HH AO1 N T S +HAUPERT HH AW1 P ER0 T +HAUPPAUGE HH AW1 P AO0 JH +HAUPT HH AO1 P T +HAUPTFUHRER HH AW1 P T F Y UH2 R ER0 +HAUPTMAN HH AW1 P T M AH0 N +HAUPTMANN HH AW1 P T M AH0 N +HAURY HH AO1 R IY0 +HAUS HH AW1 S +HAUSA HH AW1 S AH0 +HAUSAUER HH AW1 S AW0 ER0 +HAUSCH HH AW1 SH +HAUSCHILD HH AW1 S CH AY2 L D +HAUSCHILDT HH AW1 SH IH0 L T +HAUSE HH AW1 S +HAUSEN HH AW1 Z AH0 N +HAUSER HH AW1 Z ER0 +HAUSERMAN HH AW1 Z ER0 M AH0 N +HAUSFELD HH AW1 S F EH2 L D +HAUSKY HH AO1 S K IY0 +HAUSLER HH AW1 S AH0 L ER0 +HAUSLER(1) HH AW1 S L ER0 +HAUSMAN HH AW1 S M AH0 N +HAUSMANN HH AW1 S M AH0 N +HAUSNER HH AW1 S N ER0 +HAUSS HH AW1 S +HAUSSER HH AW1 S ER0 +HAUSSLER HH AW1 S AH0 L ER0 +HAUSSLER(1) HH AW1 S L ER0 +HAUSSMANN HH AW1 S M AH0 N +HAUSUMMI HH AW0 S UW1 M IY0 +HAUSWIRTH HH AW1 S W ER0 TH +HAUT HH AO1 T +HAUTALA HH AO1 T AH0 L AH0 +HAUTE HH OW1 T +HAUTE(1) HH AH1 T +HAUTER HH AW1 T ER0 +HAUTH HH AO1 TH +HAUVER HH AW1 V ER0 +HAVANA HH AH0 V AE1 N AH0 +HAVANA'S HH AH0 V AE1 N AH0 Z +HAVARD HH AE1 V ER0 D +HAVAS HH AA1 V AA0 Z +HAVE HH AE1 V +HAVEL HH AE1 V AH0 L +HAVELKA HH AH0 V EH1 L K AH0 +HAVELOCK HH AE1 V L AA2 K +HAVEMAN HH EY1 V M AH0 N +HAVEMANN HH AE1 V AH0 M AH0 N +HAVEN HH EY1 V AH0 N +HAVEN'T HH AE1 V AH0 N T +HAVEN'T(1) HH AE1 V AH0 N +HAVENER HH AE1 V IY0 N ER0 +HAVENS HH EY1 V AH0 N Z +HAVER HH EH1 V ER0 +HAVERFIELD HH AE1 V ER0 F IY2 L D +HAVERFORD HH AE1 V ER0 F ER0 D +HAVERKAMP HH AE1 V ER0 K AE2 M P +HAVERLAND HH AE1 V ER0 L AH0 N D +HAVERLY HH EY1 V ER0 L IY0 +HAVERSTICK HH EY1 V ER0 S T IH0 K +HAVERSTOCK HH EY1 V ER0 S T AA0 K +HAVERTY HH AE1 V ER0 T IY0 +HAVES HH AE1 V Z +HAVEY HH EY1 V IY0 +HAVIER HH AE1 V Y ER0 +HAVILAND HH EY1 V IY0 L AH0 N D +HAVILL HH AA0 V IY1 L +HAVILLAND HH AE1 V AH0 L AH0 N D +HAVIN' HH AE1 V IH0 N +HAVING HH AE1 V IH0 NG +HAVINGTON HH AE1 V IH0 NG T AH0 N +HAVINGTON'S HH AE1 V IH0 NG T AH0 N Z +HAVINS HH AE1 V IH0 N Z +HAVIS HH AE1 V IH0 S +HAVLICEK HH AA1 V L IH0 CH EH0 K +HAVLIK HH AE1 V L IH0 K +HAVLIN HH AE1 V L IH0 N +HAVNER HH AE1 V N ER0 +HAVOC HH AE1 V AH0 K +HAVRAN HH AE1 V R AH0 N +HAVRANEK HH AH0 V R AE1 N EH0 K +HAVRILLA HH AE2 V R IH1 L AH0 +HAVRON HH AE1 V R AH0 N +HAW HH AO1 +HAWAII HH AH0 W AY1 IY2 +HAWAII'S HH AH0 W AY1 IY2 Z +HAWAIIAN HH AH0 W AY1 AH0 N +HAWAIIANS HH AH0 W AY1 AH0 N Z +HAWASS HH AE1 W AA0 S +HAWBAKER HH AO1 B EY2 K ER0 +HAWE HH AO1 +HAWES HH AO1 Z +HAWING HH AO1 IH0 NG +HAWK HH AO1 K +HAWKBILL HH AO1 K B IH2 L +HAWKBILL'S HH AO1 K B IH2 L Z +HAWKE HH AO1 K +HAWKE'S HH AO1 K S +HAWKED HH AO1 K T +HAWKEN HH AO1 K AH0 N +HAWKER HH AO1 K ER0 +HAWKERS HH AO1 K ER0 Z +HAWKES HH AO1 K S +HAWKEY HH AO1 K IY2 +HAWKEYE HH AO1 K AY2 +HAWKEYE'S HH AO1 K AY2 Z +HAWKINESS HH AO1 K N AH0 S +HAWKING HH AO1 K IH0 NG +HAWKINS HH AO1 K IH0 N Z +HAWKINS' HH AO1 K IH0 N Z +HAWKINSON HH AO1 K IH0 N S AH0 N +HAWKISH HH AO1 K IH0 SH +HAWKS HH AO1 K S +HAWKSLEY HH AO1 K S L IY0 +HAWLEY HH AO1 L IY0 +HAWLEY'S HH AO1 L IY0 Z +HAWN HH AO1 N +HAWORTH HH AE1 W ER0 TH +HAWS HH AO1 Z +HAWTHORN HH AO1 TH AO2 R N +HAWTHORNE HH AO1 TH AO0 R N +HAWTHORNE'S HH AO1 TH AO0 R N Z +HAWTHORNS HH AO1 TH AO2 R N Z +HAWVER HH AO1 V ER0 +HAXTON HH AE1 K S T AH0 N +HAY HH EY1 +HAYASHI HH AA0 Y AA1 SH IY0 +HAYASHIDA HH AA0 Y AA0 SH IY1 D AH0 +HAYCOCK HH EY1 K AA2 K +HAYCRAFT HH EY1 K R AE2 F T +HAYDEL HH EY1 D AH0 L +HAYDEN HH EY1 D AH0 N +HAYDN HH AY1 D AH0 N +HAYDN'S HH AY1 D AH0 N Z +HAYDOCK HH EY1 D AA2 K +HAYDON HH EY1 D AH0 N +HAYDU HH EY1 D UW0 +HAYDUK HH EY1 D AH0 K +HAYE HH EY1 +HAYEK HH EY1 IH0 K +HAYEN HH EY1 AH0 N +HAYENGA HH EY0 EY1 NG G AH0 +HAYER HH EY1 ER0 +HAYES HH EY1 Z +HAYFIELD HH EY1 F IY2 L D +HAYFIELDS HH EY1 F IY2 L D Z +HAYFORD HH EY1 F ER0 D +HAYGOOD HH EY1 G UH2 D +HAYHURST HH EY1 HH ER0 S T +HAYING HH EY1 IH0 NG +HAYLES HH EY1 L Z +HAYLEY HH EY1 L IY0 +HAYLOFT HH EY1 L AO2 F T +HAYLOFTS HH EY1 L AO2 F T S +HAYMAKER HH EY1 M EY2 K ER0 +HAYMAKERS HH EY1 M EY2 K ER0 Z +HAYMAN HH EY1 M AH0 N +HAYMARKET HH EY1 M AA2 R K IH0 T +HAYMARKETS HH EY1 M AA2 R K IH0 T S +HAYMES HH EY1 M Z +HAYMON HH EY1 M AH0 N +HAYMOND HH EY1 M AH0 N D +HAYMORE HH EY1 M AO0 R +HAYN HH EY1 N +HAYNE HH EY1 N +HAYNER HH EY1 N ER0 +HAYNES HH EY1 N Z +HAYNESWORTH HH EY1 N Z W ER0 TH +HAYNIE HH EY1 N IY0 +HAYNSWORTH HH EY1 N Z W ER0 TH +HAYS HH EY1 Z +HAYSE HH EY1 Z +HAYSLETT HH EY1 S L IH0 T +HAYSLIP HH EY1 S L IH0 P +HAYSTACK HH EY1 S T AE2 K +HAYSTACKS HH EY1 S T AE2 K S +HAYTER HH EY1 T ER0 +HAYTON HH EY1 T AH0 N +HAYWARD HH EY1 W ER0 D +HAYWARD'S HH EY1 W ER0 D Z +HAYWIRE HH EY1 W AY2 R +HAYWOOD HH EY1 W UH2 D +HAYWORTH HH EY1 W ER2 TH +HAZAN HH EY1 Z AH0 N +HAZARD HH AE1 Z ER0 D +HAZARDOUS HH AE1 Z ER0 D AH0 S +HAZARDS HH AE1 Z ER0 D Z +HAZE HH EY1 Z +HAZEL HH EY1 Z AH0 L +HAZELBAKER HH EY1 Z AH0 L B EY2 K ER0 +HAZELETT HH AE1 Z IH0 L EH0 T +HAZELETT(1) HH AE1 Z L EH0 T +HAZELIP HH AE1 Z IH0 L IH0 P +HAZELL HH AE1 Z AH0 L +HAZELNUT HH EY1 Z AH0 L N AH2 T +HAZELNUTS HH EY1 Z AH0 L N AH2 T S +HAZELRIGG HH AH0 Z EH1 L R IH0 G +HAZELRIGG(1) HH EY1 Z EH0 L R IH0 G +HAZELTINE HH EY1 Z AH0 L T AY2 N +HAZELTON HH EY1 Z AH0 L T AH0 N +HAZELWOOD HH EY1 Z AH0 L W UH2 D +HAZELWOOD'S HH EY1 Z AH0 L W UH2 D Z +HAZEN HH EY1 Z AH0 N +HAZIER HH EY1 Z IY0 ER0 +HAZING HH EY1 Z IH0 NG +HAZLE HH EY1 Z AH0 L +HAZLETON HH EY1 Z AH0 L T AH0 N +HAZLETT HH AE1 Z L IH0 T +HAZLEWOOD HH EY1 Z AH0 L W UH2 D +HAZY HH EY1 Z IY0 +HAZZARD HH AE1 Z ER0 D +HBO EY1 CH B IY0 OW1 +HBOX EY1 CH B AO1 K S +HCES EY1 CH S IY1 IY1 EH1 S +HE HH IY1 +HE'D HH IY1 D +HE'LL HH IY1 L +HE'S HH IY1 Z +HEABERLIN HH IY1 B ER0 L IH0 N +HEACOCK HH IY1 K AH0 K +HEACOX HH IY1 K AA0 K S +HEAD HH EH1 D +HEAD'S HH EH1 D Z +HEADACHE HH EH1 D EY2 K +HEADACHES HH EH1 D EY2 K S +HEADBAND HH EH1 D B AE2 N D +HEADBANDS HH EH1 D B AE2 N D Z +HEADBOARD HH EH1 D B AO2 R D +HEADBOARDS HH EH1 D B AO2 R D Z +HEADCHEESE HH EH1 D CH IY2 Z +HEADCOUNT HH EH1 D K AW2 N T +HEADCOUNTS HH EH1 D K AW2 N T S +HEADDRESS HH EH1 D R EH2 S +HEADDRESSES HH EH1 D D R EH2 S AH0 Z +HEADED HH EH1 D AH0 D +HEADED(1) HH EH1 D IH0 D +HEADEN HH EH1 D AH0 N +HEADER HH EH1 D ER0 +HEADERS HH EH1 D ER0 Z +HEADFIRST HH EH1 D F ER1 S T +HEADGEAR HH EH1 D G IH2 R +HEADHUNTER HH EH1 D HH AH2 N T ER0 +HEADHUNTERS HH EH1 D HH AH2 N T ER0 Z +HEADING HH EH1 D IH0 NG +HEADINGS HH EH1 D IH0 NG Z +HEADINGTON HH EH1 D IH0 NG T AH0 N +HEADLEE HH EH1 D L IY2 +HEADLESS HH EH1 D L AH0 S +HEADLEY HH EH1 D L IY0 +HEADLIGHT HH EH1 D L AY2 T +HEADLIGHTS HH EH1 D L AY2 T S +HEADLINE HH EH1 D L AY2 N +HEADLINED HH EH1 D L AY2 N D +HEADLINER HH EH1 D L AY2 N ER0 +HEADLINERS HH EH1 D L AY2 N ER0 Z +HEADLINES HH EH1 D L AY2 N Z +HEADLINING HH EH1 D L AY2 N IH0 NG +HEADLONG HH EH1 D L AO2 NG +HEADLUND HH EH1 D L AH0 N D +HEADMAN HH EH1 D M AH0 N +HEADMASTER HH EH1 D M AE1 S T ER0 +HEADMASTERS HH EH1 D M AE1 S T ER0 Z +HEADMISTRESS HH EH1 D M IH2 S T R AH0 S +HEADMISTRESSES HH EH1 D M IH2 S T R AH0 S AH0 Z +HEADPHONE HH EH1 D F OW2 N +HEADPHONES HH EH1 D F OW2 N Z +HEADQUARTER HH EH1 D K W AO2 R T ER0 +HEADQUARTER(1) HH EH1 D K AO2 R T ER0 +HEADQUARTERED HH EH1 D K AO2 R T ER0 D +HEADQUARTERED(1) HH EH1 D K W AO2 R T ER0 D +HEADQUARTERS HH EH1 D K W AO2 R T ER0 Z +HEADQUARTERS(1) HH EH1 D K AO2 R T ER0 Z +HEADREST HH EH1 D R EH2 S T +HEADRESTS HH EH1 D R EH2 S T S +HEADRICK HH EH1 D R IH0 K +HEADROOM HH EH1 D R UW2 M +HEADS HH EH1 D Z +HEADS-UP HH EH1 D Z AH2 P +HEADSET HH EH1 D S EH2 T +HEADSETS HH EH1 D S EH2 T S +HEADSHIP HH EH1 D SH IH2 P +HEADSMAN HH EH1 D Z M AH0 N +HEADSTART HH EH1 D S T AA2 R T +HEADSTARTS HH EH1 D S T AA2 R T S +HEADSTONE HH EH1 D S T OW2 N +HEADSTONES HH EH1 D S T OW2 N Z +HEADSTRONG HH EH1 D S T R AO2 NG +HEADWATER HH EH1 D W AO2 T ER0 +HEADWATERS HH EH1 D W AO2 T ER0 Z +HEADWAY HH EH1 D W EY2 +HEADWIND HH EH1 D W IH2 N D +HEADWINDS HH EH1 D W IH2 N D Z +HEADY HH EH1 D IY0 +HEAFNER HH IY1 F N ER0 +HEAGLE HH IY1 G AH0 L +HEAGNEY HH IY1 G N IY0 +HEAGY HH IY1 JH IY0 +HEAL HH IY1 L +HEALD HH IY1 L D +HEALED HH IY1 L D +HEALER HH IY1 L ER0 +HEALERS HH IY1 L ER0 Z +HEALEY HH IY1 L IY0 +HEALING HH IY1 L IH0 NG +HEALS HH IY1 L Z +HEALTH HH EH1 L TH +HEALTH'S HH EH1 L TH S +HEALTHAMERICA HH IY2 L TH AH0 M EH1 R IH0 K AH0 +HEALTHCARE HH EH1 L TH K EH2 R +HEALTHCARE'S HH EH1 L TH K EH2 R Z +HEALTHCORP HH EH1 L TH K AO2 R P +HEALTHCORP(1) HH EH1 L TH K AO2 R +HEALTHDYNE HH EH1 L TH D AY2 N +HEALTHFUL HH EH1 L TH F AH0 L +HEALTHIER HH EH1 L TH IY0 ER0 +HEALTHIEST HH EH1 L TH IY0 IH0 S T +HEALTHINESS HH EH1 L TH IY0 N AH0 S +HEALTHSOURCE HH EH1 L TH S AO2 R S +HEALTHSOUTH HH EH1 L TH S AW2 TH +HEALTHTRUST HH EH1 L TH T R AH2 S T +HEALTHTRUST'S HH EH1 L TH T R AH2 S T S +HEALTHVEST HH EH1 L TH V EH2 S T +HEALTHWEEK HH EH1 L TH W IY2 K +HEALTHWORK HH EH1 L TH W ER0 K +HEALTHWORKS HH EH1 L TH W ER0 K S +HEALTHY HH EH1 L TH IY0 +HEALY HH IY1 L IY0 +HEALY'S HH IY1 L IY0 Z +HEANEY HH IY1 N IY0 +HEAP HH IY1 P +HEAPE HH IY1 P +HEAPED HH IY1 P T +HEAPHY HH IY1 F IY0 +HEAPING HH IY1 P IH0 NG +HEAPS HH IY1 P S +HEAR HH IY1 R +HEARD HH ER1 D +HEARER HH IY1 R ER0 +HEARERS HH IY1 R ER0 Z +HEARIN HH IH1 R IH0 N +HEARING HH IY1 R IH0 NG +HEARING'S HH IY1 R IH0 NG Z +HEARINGS HH IY1 R IH0 NG Z +HEARKENS HH AA1 R K AH0 N Z +HEARL HH ER1 L +HEARN HH ER1 N +HEARNE HH ER1 N +HEARNS HH ER1 N Z +HEARON HH IH1 R AH0 N +HEARRON HH AO1 R AH0 N +HEARS HH IY1 R Z +HEARSAY HH IY1 R S EY2 +HEARSE HH ER1 S +HEARST HH ER1 S T +HEARST'S HH ER1 S T S +HEART HH AA1 R T +HEART'S HH AA1 R T S +HEARTACHE HH AA1 R T EY2 K +HEARTBEAT HH AA1 R T B IY2 T +HEARTBEATS HH AA1 R T B IY2 T S +HEARTBREAK HH AA1 R T B R EY2 K +HEARTBREAKING HH AA1 R T B R EY2 K IH0 NG +HEARTBREAKS HH AA1 R T B R EY2 K S +HEARTBROKEN HH AA1 R T B R OW2 K AH0 N +HEARTBURN HH AA1 R T B ER2 N +HEARTED HH AA1 R T AH0 D +HEARTED(1) HH AA1 R T IH0 D +HEARTEDLY HH AA1 R T IH0 D L IY0 +HEARTEN HH AA1 R T AH0 N +HEARTENED HH AA1 R T AH0 N D +HEARTENING HH AA1 R T AH0 N IH0 NG +HEARTENING(1) HH AA1 R T N IH0 NG +HEARTFELT HH AA1 R T F EH2 L T +HEARTH HH AA1 R TH +HEARTHS HH AA1 R TH S +HEARTIER HH AA1 R T IY0 ER0 +HEARTIEST HH AA1 R T IY0 AH0 S T +HEARTILY HH AA1 R T AH0 L IY0 +HEARTLAND HH AA1 R T L AE2 N D +HEARTLESS HH AA1 R T L AH0 S +HEARTS HH AA1 R T S +HEARTSCAN HH AA1 R T S K AE2 N +HEARTTHROB HH AA1 R T TH R AA2 B +HEARTTHROBS HH AA1 R T TH R AA2 B Z +HEARTWARMING HH AA1 R T W AO2 R M IH0 NG +HEARTWISE HH AA1 R T W AY2 Z +HEARTWOOD HH AA1 R T W UH2 D +HEARTY HH AA1 R T IY0 +HEASLEY HH IY1 Z L IY0 +HEASLIP HH IY1 S L IH0 P +HEASTON HH IY1 S T AH0 N +HEAT HH IY1 T +HEAT'S HH IY1 T S +HEATED HH IY1 T AH0 D +HEATED(1) HH IY1 T IH0 D +HEATEDLY HH IY1 T IH0 D L IY0 +HEATER HH IY1 T ER0 +HEATERS HH IY1 T ER0 Z +HEATH HH IY1 TH +HEATH'S HH IY1 TH S +HEATHCLIFF HH EH1 TH K L IH0 F +HEATHCOCK HH EH1 TH K AH0 K +HEATHCOTE HH EH1 TH K AH0 T +HEATHEN HH IY1 DH AH0 N +HEATHER HH EH1 DH ER0 +HEATHER'S HH EH1 DH ER0 Z +HEATHERINGTON HH EH1 DH ER0 IH0 NG T AH0 N +HEATHERLY HH EH1 DH ER0 L IY0 +HEATHERS HH EH1 DH ER0 Z +HEATHMAN HH IY1 TH M AH0 N +HEATHROW HH IY1 TH R OW0 +HEATHROW'S HH IY1 TH R OW0 Z +HEATHWOOD HH IY1 TH W UH2 D +HEATING HH IY1 T IH0 NG +HEATLEY HH IY1 T L IY0 +HEATON HH IY1 T AH0 N +HEATS HH IY1 T S +HEATWOLE HH IY1 T W OW2 L +HEAVE HH IY1 V +HEAVED HH IY1 V D +HEAVEN HH EH1 V AH0 N +HEAVEN'S HH EH1 V AH0 N Z +HEAVENER HH EH1 V AH0 N ER0 +HEAVENLY HH EH1 V AH0 N L IY0 +HEAVENS HH EH1 V AH0 N Z +HEAVES HH IY1 V Z +HEAVEY HH IY1 V IY0 +HEAVIER HH EH1 V IY0 ER0 +HEAVIES HH EH1 V IY0 Z +HEAVIEST HH EH1 V IY0 AH0 S T +HEAVILY HH EH1 V AH0 L IY0 +HEAVIN HH EH1 V IH0 N +HEAVING HH IY1 V IH0 NG +HEAVNER HH IY1 V N ER0 +HEAVRIN HH IY1 V R IH0 N +HEAVY HH EH1 V IY0 +HEAVYHANDED HH EH1 V IY0 HH AE2 N D IH0 D +HEAVYSET HH EH1 V IY0 S EH2 T +HEAVYWEIGHT HH EH1 V IY0 W EY2 T +HEAVYWEIGHTS HH EH1 V IY0 W EY2 T S +HEBARD HH EH1 B ER0 D +HEBB HH EH1 B +HEBDA HH EH1 B D AH0 +HEBDING HH EH1 B D IH0 NG +HEBE HH IY1 B +HEBEI HH IY1 B IY0 +HEBEL HH EH1 B AH0 L +HEBELER HH EH1 B AH0 L ER0 +HEBENSTREIT HH EH1 B IH0 N S T R AY0 T +HEBER HH IY1 B ER0 +HEBERER HH EH1 B ER0 ER0 +HEBERLE HH EH1 B ER0 AH0 L +HEBERLEIN HH EH1 B ER0 L AY2 N +HEBERLING HH EH1 B ER0 L IH0 NG +HEBERT HH EH1 B ER0 T +HEBNER HH EH1 B N ER0 +HEBREW HH IY1 B R UW0 +HEBREWS HH IY1 B R UW0 Z +HEBRIDES HH EH1 B R IH0 D IY0 Z +HEBRON HH EH1 B R AH0 N +HEBRON(1) HH EH1 B R AO2 N +HECCO HH EH1 K OW0 +HECHINGER HH EH1 K IH0 N JH ER0 +HECHLER HH EH1 K L ER0 +HECHT HH EH1 K T +HECHT'S HH EH1 K T S +HECHTMAN HH EH1 K T M AH0 N +HECK HH EH1 K +HECK'S HH EH1 K S +HECKAMAN HH EH1 K AH0 M AH0 N +HECKARD HH EH1 K ER0 D +HECKART HH EH1 K ER0 T +HECKATHORN HH EH1 K AH0 TH ER0 N +HECKBERT HH EH1 K B ER0 T +HECKEL HH EH1 K AH0 L +HECKENDORN HH EH1 K EH0 N D AO0 R N +HECKER HH EH1 K ER0 +HECKERT HH EH1 K ER0 T +HECKLE HH EH1 K AH0 L +HECKLED HH EH1 K AH0 L D +HECKLER HH EH1 K L ER0 +HECKLERS HH EH1 K L ER0 Z +HECKLING HH EH1 K L IH0 NG +HECKMAN HH EH1 K M AH0 N +HECKMANN HH EH1 K M AH0 N +HECKUVA HH EH0 K Y UW1 V AH0 +HECKUVA(1) HH EH1 K AH0 V AH0 +HECLA HH EH1 K L AH0 +HECLA'S HH EH1 K L AH0 Z +HECOX HH EH1 K AA0 K S +HECTARE HH EH1 K T AA2 R +HECTARES HH EH1 K T AA2 R Z +HECTIC HH EH1 K T IH0 K +HECTOGRAPH HH EH1 K T AH0 G R AE2 F +HECTOR HH EH1 K T ER0 +HECTOR'S HH EH1 K T ER0 Z +HECTORING HH EH1 K T ER0 IH0 NG +HECUBA HH EH1 K Y AH0 B AH0 +HECUBA(1) HH EH1 K Y UW0 B AH0 +HEDA HH EY1 D AH0 +HEDBERG HH EH1 D B ER0 G +HEDDA HH EH1 D AH0 +HEDDEN HH EH1 D AH0 N +HEDDING HH EH1 D IH0 NG +HEDDY HH EH1 D IY0 +HEDEEN HH EH1 D IY0 N +HEDGE HH EH1 JH +HEDGECOCK HH EH1 JH K AA2 K +HEDGED HH EH1 JH D +HEDGEHOG HH EH1 JH HH AA2 G +HEDGEHOGS HH EH1 JH HH AA2 G Z +HEDGEPATH HH EH1 JH P AE2 TH +HEDGEPETH HH EH1 JH IH0 P EH0 TH +HEDGER HH EH1 JH ER0 +HEDGERS HH EH1 JH ER0 Z +HEDGES HH EH1 JH IH0 Z +HEDGING HH EH1 JH IH0 NG +HEDGLIN HH EH1 JH L IH0 N +HEDGPETH HH EH1 JH P IH0 TH +HEDI HH EH1 D IY0 +HEDIGER HH EH1 D IH0 G ER0 +HEDIN HH EH1 D IH0 N +HEDINGER HH EH1 D IH0 N G ER0 +HEDINGER(1) HH EH1 D IH0 N JH ER0 +HEDLEY HH EH1 D L IY0 +HEDLUND HH EH1 D L AH0 N D +HEDMAN HH EH1 D M AH0 N +HEDONIC HH AH0 D AA1 N IH0 K +HEDONISM HH IY1 D AH0 N IH2 Z AH0 M +HEDONISTIC HH IY2 D AH0 N IH1 S T IH0 K +HEDQUIST HH EH1 D K W IH2 S T +HEDRICH HH EH1 D R IH0 K +HEDRICK HH EH1 D R IH0 K +HEDSTROM HH EH1 D S T R AH0 M +HEDTKE HH EH1 D K IY0 +HEDWIG HH EH1 D W IH0 G +HEDWIGA HH EH1 D W IH0 G AH0 +HEDY HH IY1 D IY0 +HEE HH IY1 +HEEB HH IY1 B +HEEBNER HH IY1 B N ER0 +HEED HH IY1 D +HEEDED HH IY1 D AH0 D +HEEDED(1) HH IY1 D IH0 D +HEEDING HH IY1 D IH0 NG +HEEDS HH IY1 D Z +HEEFNER HH IY1 F N ER0 +HEEG HH IY1 G +HEEHAW HH IY1 HH AW2 +HEEKE HH IY1 K +HEEKIN HH IY1 K IH0 N +HEEL HH IY1 L +HEELAN HH IY1 L AH0 N +HEELED HH IY1 L D +HEELING HH IY1 L IH0 NG +HEELS HH IY1 L Z +HEEMSTRA HH IY1 M S T R AH0 +HEENAN HH IY1 N AH0 N +HEENEY HH IY1 N IY0 +HEER HH IY1 ER0 +HEEREN HH IH1 R AH0 N +HEERMANN HH IH1 R M AH0 N +HEES HH IY1 Z +HEESCH HH IY1 SH +HEESE HH IY1 Z +HEETER HH IY1 T ER0 +HEFEI HH AH0 F EY1 +HEFFEL HH EH1 F AH0 L +HEFFELFINGER HH EH1 F IH0 L F IH0 NG ER0 +HEFFERAN HH EH1 F ER0 AH0 N +HEFFERMAN HH EH1 F ER0 M AH0 N +HEFFERN HH EH1 F ER0 N +HEFFERNAN HH EH1 F ER0 N AH0 N +HEFFERON HH EH1 F ER0 AH0 N +HEFFINGTON HH EH1 F IH0 NG T AH0 N +HEFFLER HH EH1 F L ER0 +HEFFLEY HH EH1 F L IY0 +HEFFNER HH EH1 F N ER0 +HEFFRON HH EH1 F R AH0 N +HEFLER HH EH1 F L ER0 +HEFLEY HH EH1 F L IY0 +HEFLIN HH EH1 F L IH0 N +HEFNER HH EH1 F N ER0 +HEFNER'S HH EH1 F N ER0 Z +HEFT HH EH1 F T +HEFTER HH EH1 F T ER0 +HEFTI HH EH1 F T IY0 +HEFTIER HH EH1 F T IY0 ER0 +HEFTIEST HH EH1 F T IY0 AH0 S T +HEFTY HH EH1 F T IY0 +HEGADORN HH EH1 G AH0 D AO2 R N +HEGARTY HH EH1 G AA0 R T IY0 +HEGE HH IY1 JH +HEGEDUS HH EH1 G IH0 D IH0 S +HEGEL HH EH1 G AH0 L +HEGELIAN HH IY0 JH IY1 L IY0 AH0 N +HEGEMAN HH IY1 G M AH0 N +HEGEMONIC HH EH2 G AH0 M AA1 N IH0 K +HEGEMONY HH IY0 JH EH1 M AH0 N IY0 +HEGENNA HH EH0 G EH1 N AH0 +HEGER HH IY1 G ER0 +HEGG HH EH1 G +HEGGE HH EH1 G +HEGGEN HH EH1 G AH0 N +HEGGIE HH EH1 G IY0 +HEGLAND HH EH1 G L AH0 N D +HEGLER HH EH1 G L ER0 +HEGLUND HH EH1 G L AH0 N D +HEGNA HH EH1 G N AH0 +HEGNER HH EH1 G N ER0 +HEGSTROM HH EH1 G S T R AH0 M +HEGWOOD HH EH1 G W UH2 D +HEGYI HH EY1 G Y IY0 +HEH HH EH1 +HEHIR HH EH1 HH IH0 R +HEHL HH EH1 L +HEHMAN HH EH1 M AH0 N +HEHMEYER HH EH1 M AY2 R +HEHN HH EH1 N +HEHR HH EH1 R +HEIBEL HH AY1 B AH0 L +HEIBERG HH AY1 B ER0 G +HEIBERGER HH AY1 B ER0 G ER0 +HEICHEL HH AY1 K AH0 L +HEICHELBECH HH AY1 K IH0 L B IH0 K +HEICK HH AY1 K +HEICO HH AY1 K OW0 +HEICO'S HH AY1 K OW0 Z +HEID HH AY1 D +HEIDBREDER HH AY1 D B R IH0 D ER0 +HEIDBRINK HH AY1 D B R IH0 NG K +HEIDE HH AY1 D +HEIDECKER HH AY1 D IH0 K ER0 +HEIDEGGER HH AY1 D IH0 G ER0 +HEIDEL HH AY1 D AH0 L +HEIDELBERG HH AY1 D AH0 L B ER0 G +HEIDELBERG'S HH AY1 D AH0 L B ER0 G Z +HEIDELBERGER HH AY1 D AH0 L B ER0 G ER0 +HEIDEMAN HH AY1 D M AH0 N +HEIDEMANN HH AY1 D M AH0 N +HEIDEN HH AY1 D AH0 N +HEIDENREICH HH AY1 D IH0 N R AY0 K +HEIDER HH AY1 D ER0 +HEIDI HH AY1 D IY0 +HEIDI'S HH AY1 D IY0 S +HEIDINGER HH AY1 D IH0 NG ER0 +HEIDIWEAR HH AY1 D IY0 W EH2 R +HEIDLER HH AY1 D AH0 L ER0 +HEIDLER(1) HH AY1 D L ER0 +HEIDORN HH AY1 D ER0 N +HEIDRICH HH AY1 D R IH0 K +HEIDRICK HH AY1 D R IH0 K +HEIDSTRA HH AY1 D S T R AH0 +HEIDT HH AY1 D T +HEIER HH AY1 ER0 +HEIFER HH AY1 F ER0 +HEIFER(1) HH EH1 F ER0 +HEIFERS HH EH1 F ER0 Z +HEIFERS(1) HH AY1 F ER0 Z +HEIFETZ HH AY1 F IH0 T S +HEIFNER HH IY1 F N ER0 +HEIGES HH AY1 JH IH0 Z +HEIGHT HH AY1 T +HEIGHTEN HH AY1 T AH0 N +HEIGHTENED HH AY1 T AH0 N D +HEIGHTENING HH AY1 T AH0 N IH0 NG +HEIGHTENING(1) HH AY1 T N IH0 NG +HEIGHTENS HH AY1 T AH0 N Z +HEIGHTH HH AY1 TH +HEIGHTS HH AY1 T S +HEIGL HH AY1 G AH0 L +HEIKEN HH AY1 K AH0 N +HEIKES HH AY1 K AH0 Z +HEIKKILA HH AY1 K IH0 L AH0 +HEIKKINEN HH AY1 K IH0 N AH0 N +HEIKO HH AY1 K OW0 +HEIKO(1) HH EY1 K OW0 +HEIL HH AY1 L +HEILAND HH AY1 L AH0 N D +HEILBRUN HH AY1 L B R AH0 N +HEILEMAN HH AY1 L M AH0 N +HEILEMAN'S HH AY1 L M AH0 N Z +HEILER HH AY1 L ER0 +HEILIG HH AY1 L IH0 G +HEILMAN HH AY1 L M AH0 N +HEILMANN HH AY1 L M AH0 N +HEIM HH AY1 M +HEIMAN HH AY1 M AH0 N +HEIMANN HH AY1 M AH0 N +HEIMBACH HH AY1 M B AA2 K +HEIMBERGER HH AY1 M B ER0 G ER0 +HEIMBIGNER HH AY1 M B AY0 G N ER0 +HEIMBUCH HH AY1 M B AH0 K +HEIMBURGER HH AY1 M B ER0 G ER0 +HEIMER HH AY1 M ER0 +HEIMERL HH AY1 M ER0 L +HEIMLICH HH AY1 M L IH0 K +HEIMS HH AY1 M Z +HEIMSOTH HH AY1 M S AH0 TH +HEIN HH AY1 N +HEINBACH HH AY1 N B AA2 K +HEINBAUGH HH AY1 N B AW0 +HEINBURGER HH AY1 N B ER0 G ER0 +HEINDEL HH AY1 N D AH0 L +HEINDL HH AY1 N D AH0 L +HEINE HH AY1 N +HEINECKE HH AY1 N IH0 K +HEINEKEN HH AY1 N AH0 K AH0 N +HEINEMAN HH AY1 N M AH0 N +HEINEMANN HH AY1 N M AH0 N +HEINEN HH AY1 N AH0 N +HEINER HH AY1 N ER0 +HEINES HH AY1 N Z +HEINEY HH AY1 N IY0 +HEINI HH AY1 N IY0 +HEINICKE HH AY1 N IH0 K +HEINIG HH AY1 N IH0 G +HEININGER HH AY1 N IH0 NG ER0 +HEINISCH HH AY1 N IH0 SH +HEINKE HH AY1 NG K +HEINKEL HH AY1 NG K AH0 L +HEINL HH AY1 N AH0 L +HEINLE HH AY1 N AH0 L +HEINLEIN HH AY1 N L AY2 N +HEINLEN HH AY1 N AH0 L AH0 N +HEINLY HH AY1 N L IY0 +HEINO HH AY1 N OW0 +HEINOLD HH AY1 N OW0 L D +HEINONEN HH AY1 N AH0 N AH0 N +HEINOUS HH EY1 N AH0 S +HEINRICH HH AY1 N R IH0 K +HEINRICHS HH AY1 N R IH0 K S +HEINS HH AY1 N Z +HEINSOHN HH AY1 N S AH0 N +HEINTZ HH AY1 N T S +HEINTZE HH AY1 N T S +HEINTZELMAN HH AY1 N T Z AH0 L M AH0 N +HEINTZMAN HH AY1 N T S M AH0 N +HEINY HH AY1 N IY0 +HEINZ HH AY1 N Z +HEINZ'S HH AY1 N Z IH0 Z +HEINZE HH AY1 N Z +HEINZEL HH AY1 N Z AH0 L +HEINZELMAN HH AY1 N Z AH0 L M AH0 N +HEINZEN HH AY1 N Z AH0 N +HEINZMAN HH AY1 N Z M AH0 N +HEINZMANN HH AY1 N Z M AH0 N +HEIPLE HH AY1 P AH0 L +HEIR EH1 R +HEIRESS EH1 R AH0 S +HEIRESSES EH1 R AH0 S IH0 Z +HEIRLOOM EH1 R L UW2 M +HEIRLOOMS EH1 R L UW2 M Z +HEIRONIMUS EH1 R AA0 N IH0 M UW0 S +HEIRONIMUS(1) HH AY0 R AA1 N IH0 M AH0 S +HEIRS EH1 R Z +HEISBOURG HH AY1 S B AO2 R G +HEISE HH AY1 S +HEISEL HH AY1 S AH0 L +HEISER HH AY1 S ER0 +HEISERMAN HH AY1 S ER0 M AH0 N +HEISEY HH AY1 S IY0 +HEISHMAN HH IY1 IH0 SH M AH0 N +HEISINGER HH AY1 S IH0 N JH ER0 +HEISKELL HH AY1 S K AH0 L +HEISLER HH AY1 S AH0 L ER0 +HEISLER(1) HH AY1 S L ER0 +HEISMAN HH AY1 S M AH0 N +HEISMAN'S HH AY1 S M AH0 N Z +HEISNER HH AY1 S N ER0 +HEISS HH AY1 S +HEIST HH AY1 S T +HEISTAND HH AY1 S T AH0 N D +HEISTER HH AY1 S T ER0 +HEIT HH AY1 T +HEITKAMP HH AY1 T K AE2 M P +HEITMAN HH AY1 T M AH0 N +HEITMANN HH AY1 T M AH0 N +HEITMEYER HH AY1 T M AY0 ER0 +HEITNER HH AY1 T N ER0 +HEITZ HH AY1 T S +HEITZENRATER HH AY1 T Z IH0 N R EY0 T ER0 +HEITZMAN HH AY1 T S M AH0 N +HEIWA HH AY1 W AH0 +HEIZER HH AY1 Z ER0 +HEJL HH EH1 JH L +HEJNA HH EH1 JH N AH0 +HEKKER HH EH1 K ER0 +HEKMATYAR HH EH2 K M AH0 T Y AA1 R +HEKMATYAR'S HH EH2 K M AH0 T Y AA1 R Z +HELABA HH EH0 L AA1 B AH0 +HELANDER HH EH1 L AH0 N D ER0 +HELANE HH AH0 L EY1 N +HELBER HH EH1 L B ER0 +HELBERG HH EH1 L B ER0 G +HELBERT HH EH1 L B ER0 T +HELBIG HH EH1 L B IH0 G +HELBING HH EH1 L B IH0 NG +HELBLING HH EH1 L B AH0 L IH0 NG +HELBLING(1) HH EH1 L B L IH0 NG +HELD HH EH1 L D +HELDENBRAND HH EH1 L D IH0 N B R AH0 N D +HELDENBRAND(1) HH EH1 L D IH0 N B R AE0 N D +HELDENTENOR HH EH1 L D EH0 N T EH2 N ER0 +HELDER HH EH1 L D ER0 +HELDERMAN HH EH1 L D ER0 M AH0 N +HELDMAN HH EH1 L D M AH0 N +HELDOR HH EH1 L D ER0 +HELDRETH HH EH1 L D R IH0 TH +HELDRING HH EH1 L D R IH0 NG +HELDS HH EH1 L D Z +HELDT HH EH1 L T +HELEN HH EH1 L AH0 N +HELEN'S HH EH1 L IH0 N Z +HELENA HH EH1 L AH0 N AH0 +HELENA'S HH EH1 L IH0 N AH0 Z +HELENE HH AH0 L IY1 N +HELENS HH EH1 L AH0 N Z +HELF HH EH1 L F +HELFAND HH EH1 L F AH0 N D +HELFER HH EH1 L F ER0 +HELFGOTT HH EH1 L F G AA2 T +HELFMAN HH EH1 L F M AH0 N +HELFRICH HH EH1 L F R IH0 K +HELGA HH EH1 L G AH0 +HELGERSON HH EH1 L G ER0 S AH0 N +HELGESEN HH EH1 L G IY0 Z AH0 N +HELGESON HH EH1 L G IH0 S AH0 N +HELGET HH EH1 L G IH0 T +HELGREN HH EH1 L G R EH0 N +HELICAL HH EH1 L IH0 K AH0 L +HELICE HH EH1 L IH0 S +HELICON HH EH1 L IH0 K AA2 N +HELICONS HH EH1 L IH0 K AA2 N Z +HELICOPTER HH EH1 L IH0 K AA2 P T ER0 +HELICOPTER'S HH EH1 L AH0 K AA2 P T ER0 Z +HELICOPTERS HH EH1 L IH0 K AA2 P T ER0 Z +HELIE HH EH1 L IY0 +HELIN HH EH1 L IH0 N +HELING HH IY1 L IH0 NG +HELINSKI HH IH0 L IH1 N S K IY0 +HELIONETIC HH IY2 L IY0 OW0 N EH1 T IH0 K +HELIONETICS HH IY2 L IY0 OW0 N EH1 T IH0 K S +HELIOPOLIS HH IY2 L IY0 AA1 P AH0 L AH0 S +HELIOS HH IY1 L IY0 AA2 S +HELIOTROPE HH IY1 L IY0 AH0 T R OW2 P +HELIUM HH IY1 L IY0 AH0 M +HELIX HH IY1 L IH0 K S +HELKE HH EH1 L K +HELL HH EH1 L +HELL'S HH EH1 L Z +HELLACIOUS HH EH2 L EY1 SH AH0 S +HELLACIOUSLY HH EH2 L EY1 SH AH0 S L IY0 +HELLACIOUSNESS HH EH2 L EY1 SH AH0 S N AH0 S +HELLAMS HH EH1 L AH0 M Z +HELLAND HH EH1 L AH0 N D +HELLARD HH EH1 L ER0 D +HELLBERG HH EH1 L B ER0 G +HELLBUSCH HH EH1 L B AH0 SH +HELLBUSCH(1) HH EH1 L B UH0 SH +HELLE HH EH1 L +HELLEN HH EH1 L AH0 N +HELLENBRAND HH EH1 L AH0 N B R AE2 N D +HELLENIC HH AH0 L EH1 N IH0 K +HELLENISM HH EH1 L AH0 N IH2 Z AH0 M +HELLENISTIC HH EH2 L AH0 N IH1 S T IH0 K +HELLENIZE HH EH1 L AH0 N AY2 Z +HELLENIZED HH EH1 L AH0 N AY2 Z D +HELLENIZES HH EH1 L AH0 N AY2 Z IH0 Z +HELLENIZING HH EH1 L AH0 N AY2 Z IH0 NG +HELLER HH EH1 L ER0 +HELLER'S HH EH1 L ER0 Z +HELLERMAN HH EH1 L ER0 M AH0 N +HELLFIRE HH EH1 L F AY2 R +HELLICKSON HH EH1 L IH0 K S AH0 N +HELLIER HH EH1 L Y ER0 +HELLING HH EH1 L IH0 NG +HELLINGER HH EH1 L IH0 NG ER0 +HELLISH HH EH1 L IH0 SH +HELLMAN HH EH1 L M AH0 N +HELLMANN HH EH1 L M AH0 N +HELLMER HH EH1 L M ER0 +HELLMUTH HH EH1 L M UW2 TH +HELLNER HH EH1 L N ER0 +HELLO HH AH0 L OW1 +HELLO(1) HH EH0 L OW1 +HELLRAISER HH EH1 L R EY2 Z ER0 +HELLSTROM HH EH1 L S T R AH0 M +HELLUMS HH EH1 L AH0 M Z +HELLUVA HH EH2 L UW1 V AH0 +HELLWIG HH EH1 L W IH0 G +HELLYER HH EH1 L IY0 ER0 +HELM HH EH1 L M +HELMA HH EH1 L M AH0 +HELMAN HH EH1 L M AH0 N +HELMBRECHT HH EH1 L M B R IH0 K T +HELME HH EH1 L M +HELMER HH EH1 L M ER0 +HELMERICH HH EH1 L M ER0 IH0 K +HELMERS HH EH1 L M ER0 Z +HELMES HH EH1 L M Z +HELMET HH EH1 L M AH0 T +HELMETED HH EH1 L M AH0 T IH0 D +HELMETS HH EH1 L M AH0 T S +HELMICH HH EH1 L M IH0 K +HELMICK HH EH1 L M IH0 K +HELMIG HH EH1 L M IH0 G +HELMING HH EH1 L M IH0 NG +HELMINIAK HH EH1 L M IH0 N IY0 AE0 K +HELMINSKI HH IH0 L M IH1 N S K IY0 +HELMINTH HH EH1 L M IH0 N TH +HELMKAMP HH EH1 L M K AE2 M P +HELMKE HH EH1 L M K +HELMONT HH EH1 L M AA2 N T +HELMS HH EH1 L M Z +HELMS' HH EH1 L M Z +HELMS'S HH EH1 L M Z IH0 Z +HELMSBURTON HH EH1 L M Z B ER0 T AH0 N +HELMSLEY HH EH1 L M Z L IY0 +HELMSLEY'S HH EH1 L M Z L IY0 Z +HELMSLEYS HH EH1 L M Z L IY0 Z +HELMSMAN HH EH1 L M Z M AE2 N +HELMSTETTER HH EH1 L M S T IH0 T ER0 +HELMUT HH EH1 L M AH0 T +HELMUTH HH EH1 L M UW2 TH +HELOT HH EH1 L AH0 T +HELOTISM HH EH1 L AH0 T IH2 Z AH0 M +HELOTRY HH EH1 L AH0 T R IY0 +HELOTS HH EH1 L AH0 T S +HELP HH EH1 L P +HELPED HH EH1 L P T +HELPER HH EH1 L P ER0 +HELPERS HH EH1 L P ER0 Z +HELPFUL HH EH1 L P F AH0 L +HELPFULLY HH EH1 L P F AH0 L IY0 +HELPING HH EH1 L P IH0 NG +HELPINGS HH EH1 L P IH0 NG Z +HELPLESS HH EH1 L P L AH0 S +HELPLESSLY HH EH1 L P L AH0 S L IY0 +HELPLESSNESS HH EH1 L P L AH0 S N AH0 S +HELPRIN HH EH1 L P R IH0 N +HELPS HH EH1 L P S +HELSEL HH EH1 L S AH0 L +HELSER HH EH1 L S ER0 +HELSETH HH EH1 L S IH0 TH +HELSINKI HH EH1 L S IH0 NG K IY0 +HELSLEY HH EH1 L S L IY0 +HELSTROM HH EH1 L S T R AH0 M +HELT HH EH1 L T +HELTER HH EH1 L T ER0 +HELTER-SKELTER HH EH2 L T ER0 S K EH1 L T ER0 +HELTON HH EH1 L T AH0 N +HELTSLEY HH EH1 L T S L IY0 +HELTZEL HH EH1 L T Z AH0 L +HELVETICA HH EH2 L V EH1 T IH0 K AH0 +HELVEY HH EH1 L V IY0 +HELVIE HH EH1 L V IY0 +HELWIG HH EH1 L W IH0 G +HELZER HH EH1 L Z ER0 +HEM HH EH1 M +HEMAN HH IY1 M AH0 N +HEMANI HH AH0 M AA1 N IY0 +HEMANN HH EH1 M AH0 N +HEMANT HH EH1 M AH0 N T +HEMATITE HH EH1 M AH0 T AY2 T +HEMATOLOGY HH EH2 M AH0 T AA1 L AH0 JH IY0 +HEMATOLOGY(1) HH IY2 M AH0 T AA1 L AH0 JH IY0 +HEMBERGER HH EH1 M B ER0 G ER0 +HEMBREE HH IH0 M B R IY1 +HEMBRICK HH EH1 M B R IH2 K +HEMBY HH EH1 M B IY0 +HEMDALE HH EH1 M D EY2 L +HEMDALE'S HH EH1 M D EY2 L Z +HEMEL HH EH1 M AH0 L +HEMENWAY HH EH1 M AH0 N W EY2 +HEMIMORPHITE HH EH2 M AH0 M AO1 R F AY2 T +HEMING HH EH1 M IH0 NG +HEMINGER HH EH1 M IH0 NG ER0 +HEMINGWAY HH EH1 M IH0 NG W EY2 +HEMINGWAY'S HH EH1 M IH0 NG W EY2 Z +HEMIPLEGIA HH EH2 M AH0 P L IY1 JH IY0 AH0 +HEMIPLEGIA(1) HH EH2 M AH0 P L IY1 JH Y AH0 +HEMISPHERE HH EH1 M IH0 S F IH2 R +HEMISPHERIC HH EH2 M AH0 S F IH1 R IH0 K +HEMKER HH EH1 M K ER0 +HEMLER HH EH1 M L ER0 +HEMLINE HH EH1 M L AY2 N +HEMLINES HH EH1 M L AY2 N Z +HEMLO HH EH1 M L OW0 +HEMLOCK HH EH1 M L AA2 K +HEMM HH EH1 M +HEMME HH EH1 M +HEMMED HH EH1 M D +HEMMELGARN HH EH1 M IH0 L G AA0 R N +HEMMEN HH EH1 M AH0 N +HEMMER HH EH1 M ER0 +HEMMERICH HH EH1 M ER0 IH0 K +HEMMERLE HH EH1 M ER0 L IY0 +HEMMERLING HH EH1 M ER0 L IH0 NG +HEMMERT HH EH1 M ER0 T +HEMMETER HH EH1 M IH0 T ER0 +HEMMING HH EH1 M IH0 NG +HEMMINGER HH EH1 M IH0 NG ER0 +HEMMINGHAUS HH EH1 M IH0 NG HH AW2 S +HEMMINGS HH EH1 M IH0 NG Z +HEMMINGSEN HH EH1 M IH0 NG S AH0 N +HEMMINGSON HH EH1 M IH0 NG S AH0 N +HEMO HH IY1 M OW0 +HEMOCYANIN HH IY2 M AH0 S AY1 AH0 N AH0 N +HEMODYNAMIC HH EH2 M OW0 D AY0 N AE1 M IH0 K +HEMODYNAMICS HH EH2 M OW0 D AY0 N AE1 M IH0 K S +HEMOGLOBIN HH IY2 M AH0 G L OW1 B AH0 N +HEMOLYTIC HH IY2 M AH0 L IH1 T IH0 K +HEMOND HH EH1 M AH0 N D +HEMOPHILIA HH IY2 M AH0 F IY1 L IY0 AH0 +HEMOPHILIAC HH IY0 M AH0 F IH1 L IY0 AE0 K +HEMOPHILIAC(1) HH IY0 M OW0 F IH1 L IY0 AE0 K +HEMOPHILIAC(2) HH IY0 M AH0 F IH1 L Y AE0 K +HEMOPHILIAC(3) HH IY0 M OW0 F IH1 L Y AE0 K +HEMOPHILIACS HH IY2 M AH0 F IH1 L IY0 AE2 K S +HEMORRHAGE HH EH1 M ER0 IH0 JH +HEMORRHAGE(1) HH EH1 M R AH0 JH +HEMORRHAGED HH EH1 M ER0 IH0 JH D +HEMORRHAGIC HH EH2 M ER0 AE1 G IH0 K +HEMORRHAGING HH EH1 M ER0 IH0 JH IH0 NG +HEMORRHOID HH EH1 M ER0 OY2 D +HEMORRHOIDS HH EH1 M ER0 OY2 D Z +HEMOTEC HH EH1 M OW0 T EH2 K +HEMP HH EH1 M P +HEMPEL HH EH1 M P AH0 L +HEMPEN HH EH1 M P AH0 N +HEMPFLING HH EH1 M P F AH0 L IH0 NG +HEMPFLING(1) HH EH1 M P F L IH0 NG +HEMPHILL HH EH1 M P HH IH2 L +HEMPSTEAD HH EH1 M P S T EH0 D +HEMRIC HH EH1 M R IH0 K +HEMRICK HH EH1 M R IH0 K +HEMRY HH EH1 M R IY0 +HEMS HH EH1 M Z +HEMSLEY HH EH1 M Z L IY0 +HEMSTREET HH EH1 M S T R IY2 T +HEMY HH EH1 M IY0 +HEN HH EH1 N +HEN'S HH EH1 N Z +HENAO HH EY1 N AW0 +HENARD HH EH1 N ER0 D +HENAULT HH EH1 N AW0 L T +HENBANE HH EH1 N B EY2 N +HENCE HH EH1 N S +HENCEFORTH HH EH1 N S F AO1 R TH +HENCH HH EH1 N CH +HENCHMAN HH EH1 N CH M AH0 N +HENCHMEN HH EH1 N CH M AH0 N +HENCKEL HH EH1 N K AH0 L +HENDEE HH EH1 N D IY0 +HENDEL HH EH1 N D AH0 L +HENDERSHOT HH EH1 N D ER0 SH AH0 T +HENDERSHOTT HH EH1 N D ER0 SH AH0 T +HENDERSON HH EH1 N D ER0 S AH0 N +HENDLER HH EH1 N D L ER0 +HENDLEY HH EH1 N D L IY0 +HENDON HH EH1 N D OW0 N +HENDRA HH EH1 N D R AH0 +HENDREN HH EH1 N D ER0 AH0 N +HENDRICH HH EH1 N D R IH0 K +HENDRICK HH EH1 N D R IH0 K +HENDRICKS HH EH1 N D R IH0 K S +HENDRICKSEN HH EH1 N D R IH0 K S AH0 N +HENDRICKSON HH EH1 N D R IH0 K S AH0 N +HENDRIE HH EH1 N D ER0 IY0 +HENDRIK HH EH1 N D R IH0 K +HENDRIKS HH EH1 N D R IH0 K S +HENDRIKSEN HH EH1 N D R IH0 K S AH0 N +HENDRIX HH EH1 N D R IH0 K S +HENDRIXSON HH EH1 N D R IH0 K S AH0 N +HENDRON HH EH1 N D R AH0 N +HENDRY HH EH1 N D R IY0 +HENDRY'S HH EH1 N D R IY0 Z +HENDRYX HH EH1 N D R IH0 K S +HENDY HH EH1 N D IY0 +HENEGAR HH EH1 N IH0 G ER0 +HENEGHAN HH IH0 N EH1 G AH0 N +HENEHAN HH EH1 N IH0 HH AE0 N +HENERY HH EH1 N ER0 IY0 +HENES HH IY1 N Z +HENEY HH EH1 N IY0 +HENG HH EH1 NG +HENGEL HH EH1 NG G AH0 L +HENGST HH EH1 NG G S T +HENHOUSE HH EH1 N HH AW2 S +HENIE HH EH1 N IY0 +HENIGAN HH EH1 N IH0 G AH0 N +HENIN HH EH1 N IH0 N +HENINGER HH EH1 N IH0 NG ER0 +HENION HH EH1 N Y AH0 N +HENK HH EH1 NG K +HENKE HH EH1 NG K +HENKEL HH EH1 NG K AH0 L +HENKELMAN HH EH1 NG K AH0 L M AH0 N +HENKELS HH EH1 NG K AH0 L Z +HENKEN HH EH1 NG K AH0 N +HENKES HH EH1 NG K S +HENKIN HH EH1 NG K IH0 N +HENKLE HH EH1 NG K AH0 L +HENLE HH EH1 N AH0 L +HENLEY HH EH1 N L IY0 +HENLEY'S HH EH1 N L IY0 Z +HENLEYS HH EH1 N L IY0 Z +HENLINE HH EH1 N L AY2 N +HENLY HH EH1 N L IY0 +HENMAN HH EH1 N M AH0 N +HENN HH EH1 N +HENNA HH EH1 N AH0 +HENNAN HH EH1 N AH0 N +HENNE HH EH1 N +HENNE(1) HH EH1 N IY0 +HENNEBERGER HH EH1 N B ER0 G ER0 +HENNEBERRY HH EH1 N B EH0 R IY0 +HENNEKE HH EH1 N IH0 K +HENNELLY HH EH1 N AH0 L IY0 +HENNEMAN HH EH1 N M AH0 N +HENNEN HH EH1 N AH0 N +HENNEPIN HH EH1 N IH0 P IH0 N +HENNER HH EH1 N ER0 +HENNES HH EH1 N Z +HENNESS HH EH1 N IH0 S +HENNESSEE HH EH1 N IH0 S IY0 +HENNESSEY HH EH1 N AH0 S IY0 +HENNESSEY'S HH EH1 N AH0 S IY0 Z +HENNESSY HH EH1 N AH0 S IY0 +HENNEY HH EH1 N IY0 +HENNICK HH EH1 N IH0 K +HENNIG HH EH1 N IH0 G +HENNIGAN HH EH1 N IH0 G AH0 N +HENNIGAR HH EH1 N IH0 G ER0 +HENNING HH EH1 N IH0 NG +HENNINGER HH EH1 N IH0 NG ER0 +HENNINGS HH EH1 N IH0 NG Z +HENNINGSEN HH EH1 N IH0 NG S AH0 N +HENNINGTON HH EH1 N IH0 NG T AH0 N +HENNIS HH EH1 N IH0 S +HENNON HH EH1 N AH0 N +HENPECK HH EH1 N P EH2 K +HENPECKED HH EH1 N P EH2 K T +HENRI HH EH1 N R IY0 +HENRI(1) AO2 R IY1 +HENRI(2) AA2 N R IY1 +HENRICH HH EH1 N R IH0 K +HENRICHS HH EH1 N R IH0 K S +HENRICHSEN HH EH1 N R IH0 K S AH0 N +HENRICK HH EH1 N R IH0 K +HENRICKS HH EH1 N R IH0 K S +HENRICKSEN HH EH1 N R IH0 K S AH0 N +HENRICKSON HH EH1 N R IH0 K S AH0 N +HENRIE HH EH1 N ER0 IY0 +HENRIETTA HH EH2 N R IY0 EH1 T AH0 +HENRIETTE HH EH2 N R IY0 EH1 T +HENRIK HH EH1 N R IH0 K +HENRIKA HH EH1 N R IH0 K AH0 +HENRIKSEN HH EH1 N R IH0 K S AH0 N +HENRIKSON HH EH1 N R IH0 K S AH0 N +HENRIQUE AA0 N R IY1 K +HENRIQUES HH EH0 N R IY1 K EH0 Z +HENRIQUES(1) AA0 N R IY1 K +HENRIQUEZ HH EH0 N R IY1 K EH0 Z +HENRIQUEZ(1) AA0 N R IY1 K +HENRY HH EH1 N R IY0 +HENRY'S HH EH1 N R IY0 Z +HENS HH EH1 N Z +HENSARLING HH EH1 N S AA0 R L IH0 NG +HENSCH HH EH1 N SH +HENSCHEL HH EH1 N SH AH0 L +HENSCHEN HH EH1 N SH AH0 N +HENSE HH EH1 N S +HENSEL HH EH1 N S AH0 L +HENSEN HH EH1 N S AH0 N +HENSHAW HH EH1 N SH AO2 +HENSIL HH EH1 N S AH0 L +HENSKE HH EH1 N S K IY0 +HENSLEE HH EH1 N Z L IY2 +HENSLER HH EH1 N S AH0 L ER0 +HENSLER(1) HH EH1 N S L ER0 +HENSLEY HH EH1 N Z L IY0 +HENSON HH EH1 N S AH0 N +HENTGES HH EH1 N T JH IH0 Z +HENTHORN HH EH1 N TH AO2 R N +HENTHORNE HH EH1 N TH AO2 R N +HENTIC HH EH1 N T IH0 K +HENTOFF HH EH1 N T AO0 F +HENTON HH EH1 N T AH0 N +HENTSCHEL HH EH1 N CH AH0 L +HENTZ HH EH1 N T S +HENWOOD HH EH1 N W UH2 D +HENZE HH EH1 N Z +HENZEL HH EH1 N Z AH0 L +HENZLER HH EH1 N Z L ER0 +HEON HH IY1 AH0 N +HEOROICO HH IY2 AH0 R OW1 AH0 K OW0 +HEP HH EH1 P +HEPARIN HH EH1 P ER0 IH0 N +HEPATIC HH AH0 P AE1 T IH0 K +HEPATITIS HH EH2 P AH0 T AY1 T AH0 S +HEPBURN HH EH1 P B ER0 N +HEPBURN'S HH EH1 P B ER0 N Z +HEPFER HH EH1 P F ER0 +HEPKER HH EH1 P K ER0 +HEPLER HH EH1 P L ER0 +HEPNER HH EH1 P N ER0 +HEPP HH EH1 P +HEPPE HH EH1 P +HEPPER HH EH1 P ER0 +HEPPLER HH EH1 P L ER0 +HEPPNER HH EH1 P N ER0 +HEPTATHLON HH EH0 P T AE1 TH L AA0 N +HEPWORTH HH EH1 P W ER0 TH +HER HH ER1 +HER'S HH ER1 Z +HERA HH IH1 R AH0 +HERADIA HH ER0 AA1 D IY0 AH0 +HERALD HH EH1 R AH0 L D +HERALD'S HH EH1 R AH0 L D Z +HERALDED HH EH1 R AH0 L D IH0 D +HERALDIC HH EH0 R AE1 L D IH0 K +HERALDING HH EH1 R AH0 L D IH0 NG +HERALDRY HH EH1 R AH0 L D R IY0 +HERALDS HH EH1 R AH0 L D Z +HERB ER1 B +HERB(1) HH ER1 B +HERB'S ER1 B Z +HERB'S(1) HH ER1 B Z +HERBACEOUS ER0 B EY1 SH AH0 S +HERBAL ER1 B AH0 L +HERBAL(1) HH ER1 B AH0 L +HERBALIFE ER1 B AH0 L AY2 F +HERBALIFE(1) HH ER1 B AH0 L AY2 F +HERBALIST ER1 B AH0 L IH2 S T +HERBALIST(1) HH ER1 B AH0 L IH2 S T +HERBALIST'S ER1 B AH0 L IH2 S T S +HERBALIST'S(1) HH ER1 B AH0 L IH2 S T S +HERBALISTS ER1 B AH0 L IH2 S T S +HERBALISTS(1) HH ER1 B AH0 L IH2 S T S +HERBALISTS' ER1 B AH0 L IH2 S T S +HERBALISTS'(1) HH ER1 B AH0 L IH2 S T S +HERBARIUM HH ER0 B EH1 R IY2 AH0 M +HERBARIUM(1) ER0 B EH1 R IY2 AH0 M +HERBARIUMS HH ER0 B EH1 R IY2 AH0 M Z +HERBARIUMS(1) ER0 B EH1 R IY2 AH0 M Z +HERBECK HH ER1 B EH0 K +HERBEL HH ER1 B AH0 L +HERBER HH ER1 B ER0 +HERBERG HH ER1 B ER0 G +HERBERGER HH ER1 B ER0 G ER0 +HERBERS HH ER1 B ER0 Z +HERBERT HH ER1 B ER0 T +HERBERT'S HH ER1 B ER0 T S +HERBICIDE HH ER1 B IH0 S AY2 D +HERBICIDE(1) ER1 B IH0 S AY2 D +HERBICIDES ER1 B AH0 S AY2 D Z +HERBICIDES(1) HH ER1 B AH0 S AY2 D Z +HERBIE HH ER1 B IY0 +HERBIG HH ER1 B IH0 G +HERBIN HH ER1 B IH0 N +HERBISON HH ER1 B IH0 S AH0 N +HERBIVORE HH ER1 B IH0 V AO2 R +HERBIVORE(1) ER1 B IH0 V AO2 R +HERBIVOROUS HH ER0 B IH1 V AO2 R AH0 S +HERBIVOROUS(1) ER0 B IH1 V AO2 R AH0 S +HERBOLD HH ER1 B OW0 L D +HERBS ER1 B Z +HERBST HH ER1 B S T +HERBSTER HH ER1 B S T ER0 +HERCEG HH ER1 S IH0 G +HERCEGOVINA HH EH2 R T S AH0 G OW0 V IY1 N AH0 +HERCEGOVINA(1) HH ER2 R T S AH0 G OW0 V IY1 N AH0 +HERCEGOVINA'S HH EH2 R T S AH0 G OW0 V IY1 N AH0 Z +HERCEGOVINA'S(1) HH ER2 R T S AH0 G OW0 V IY1 N AH0 Z +HERCULEAN HH ER0 K Y UW1 L IY0 AH0 N +HERCULES HH ER1 K Y AH0 L IY2 Z +HERCZEG HH ER1 CH IH0 G +HERD HH ER1 D +HERDA HH EH1 R D AH0 +HERDAL HH EH1 R D AH0 L +HERDED HH ER1 D IH0 D +HERDER HH EH1 R D ER0 +HERDER(1) HH ER1 D ER0 +HERDERS HH ER1 D ER0 Z +HERDING HH ER1 D IH0 NG +HERDMAN HH ER1 D M AH0 N +HERDS HH ER1 D Z +HERDSMEN HH ER1 D Z M IH0 N +HERDT HH ER1 T +HERE HH IY1 R +HERE'S HH IH1 R Z +HEREABOUT HH IH1 R AH0 B AW2 T +HEREABOUTS HH IH1 R AH0 B AW2 T S +HEREAFTER HH IH0 R AE1 F T ER0 +HEREBY HH IH0 R B AY1 +HEREDIA HH ER0 EH1 D IY0 AH0 +HEREDITARY HH ER0 EH1 D AH0 T EH2 R IY0 +HEREDITY HH ER0 EH1 D AH0 T IY0 +HEREFORD HH EH1 R AH0 F ER0 D +HEREIN HH IH0 R IH1 N +HERENDEEN HH IH1 R N D IY0 N +HERESY HH EH1 R AH0 S IY0 +HERETIC HH EH1 R AH0 T IH0 K +HERETICAL HH EH0 R EH1 T IH0 K AH0 L +HERETICS HH EH1 R EH0 T IH0 K S +HERETOFORE HH IH2 R T AH0 F AO1 R +HEREWITH HH IH1 R W IH1 TH +HERFORD HH ER1 F ER0 D +HERFURTH HH ER1 F ER0 TH +HERGERT HH ER1 G ER0 T +HERGET HH ER1 G IH0 T +HERGOTT HH ER1 G AH0 T +HERIN HH EH1 R IH0 N +HERING HH ER1 IH0 NG +HERINGER HH EH1 R IH0 N JH ER0 +HERINGTON HH EH1 R IH0 NG T AH0 N +HERITABLE HH EH1 R AH0 T AH0 B AH0 L +HERITAGE HH EH1 R AH0 T AH0 JH +HERITAGE(1) HH EH1 R IH0 T IH0 JH +HERITAGE'S HH EH1 R AH0 T IH0 JH IH0 Z +HERITAGES HH EH1 R IH0 T IH0 JH AH0 Z +HERK HH ER1 K +HERKERT HH ER1 K ER0 T +HERL HH ER1 L +HERLIHY HH ER1 L IH0 HH IY0 +HERLING HH ER1 L IH0 NG +HERLONG HH ER1 L AO0 NG +HERM HH ER1 M +HERMAN HH ER1 M AH0 N +HERMAN'S HH ER1 M AH0 N Z +HERMANCE HH ER1 M AH0 N S +HERMANN HH ER1 M AH0 N +HERMANNS HH ER1 M AA0 N Z +HERMANS HH ER1 M AH0 N Z +HERMANSEN HH ER1 M AH0 N S AH0 N +HERMANSON HH ER1 M AH0 N S AH0 N +HERMAPHRODITE HH ER0 M AE1 F R AH0 D AY2 T +HERMAPHRODITIC HH ER0 M AE2 F R AH0 D IH1 T IH0 K +HERMENIO HH ER0 M EH1 N IY0 OW0 +HERMES HH ER1 M IY0 Z +HERMETICALLY HH ER0 M EH1 T IH0 K AH0 L IY0 +HERMETICALLY(1) HH ER0 M EH1 T IH0 K L IY0 +HERMIA HH ER1 M IY0 AH0 +HERMIAS HH ER1 M IY0 AH0 Z +HERMIDA HH EH0 R M IY1 D AH0 +HERMIE HH ER1 M IY0 +HERMINA HH ER1 M IH0 N AH0 +HERMINA(1) HH ER0 M IY1 N AH0 +HERMINE HH ER1 M IH0 N +HERMINIA HH EH0 R M IY1 N IY0 AH0 +HERMINIE HH ER2 M IH1 N IY0 +HERMIONE HH ER2 M AY1 N IY0 +HERMIT HH ER1 M AH0 T +HERMITAGE HH ER1 M AH0 T AH0 JH +HERMITS HH ER1 M AH0 T S +HERMON HH ER1 M AH0 N +HERMOSA HH EH0 R M OW1 S AH0 +HERMOSILLO HH ER0 M AH0 S IH1 L OW0 +HERMS HH ER1 M Z +HERMSEN HH ER1 M S AH0 N +HERN HH ER1 N +HERNAN HH ER1 N AH0 N +HERNANDES HH ER1 N IH0 N D Z +HERNANDES(1) HH ER0 N AE1 N D EH0 Z +HERNANDEZ HH ER0 N AE1 N D EH0 Z +HERNANDEZ'S HH ER0 N AE1 N D EH0 Z AH0 Z +HERNANDO HH ER0 N AA1 N D OW0 +HERNDON HH ER1 N D AH0 N +HERNE HH ER1 N +HERNER HH ER1 N ER0 +HERNIA HH ER1 N IY0 AH0 +HERNIATE HH ER1 N IY0 EY2 T +HERNIATES HH ER1 N IY0 EY2 T S +HERNON HH ER1 N AH0 N +HERO HH IH1 R OW0 +HERO(1) HH IY1 R OW0 +HERO'S HH IH1 R OW0 Z +HERO'S(1) HH IY1 R OW0 Z +HEROD HH EH1 R AH0 D +HEROES HH IH1 R OW0 Z +HEROES(1) HH IY1 R OW0 Z +HEROIC HH IH0 R OW1 IH0 K +HEROICALLY HH IH2 R OW1 IH0 K L IY0 +HEROICS HH IH0 R OW1 IH0 K S +HEROIN HH EH1 R OW0 AH0 N +HEROIN'S HH EH1 R OW0 AH0 N Z +HEROINE HH EH1 R OW0 AH0 N +HEROINES HH EH1 R OW2 AH0 N Z +HEROISM HH EH1 R OW0 IH2 Z AH0 M +HEROIZE HH IY1 R OW0 AY2 Z +HEROIZED HH IY1 R OW0 AY2 Z D +HEROLD HH EH1 R AH0 L D +HERON HH EH1 R AH0 N +HERON'S HH EH1 R AH0 N Z +HERONS HH EH1 R AH0 N Z +HEROS HH IH1 R OW0 Z +HEROUX HH ER0 UW1 +HERPES HH ER1 P IY0 Z +HERR HH EH1 R +HERRE HH EH1 R +HERRE(1) HH AH1 R IY0 +HERREID HH EH1 R AY0 D +HERRELL HH EH1 R AH0 L +HERREN HH EH1 R AH0 N +HERRERA HH ER0 EH1 R AH0 +HERRERO HH EH0 R EH1 R OW0 +HERRHAUSEN HH EH1 R HH AW2 Z AH0 N +HERRIAGE HH EH1 R IY0 IH0 JH +HERRICK HH EH1 R IH0 K +HERRIDGE HH EH1 R IH0 JH +HERRIG HH EH1 R IH0 G +HERRIMAN HH EH1 R IH0 M AH0 N +HERRIN HH EH1 R IH0 N +HERRING HH EH1 R IH0 NG +HERRINGS HH EH1 R IH0 NG Z +HERRINGSHAW HH EH1 R IH0 NG SH AO2 +HERRINGTON HH EH1 R IH0 NG T AH0 N +HERRINGTON'S HH EH1 R IH0 NG T AH0 N Z +HERRIOTT HH EH1 R IY0 AA0 T +HERRIOTT(1) HH EH1 R IY0 AH0 T +HERRLE HH EH1 R AH0 L +HERRLINGER HH EH1 R L IH2 NG ER0 +HERRLINGER(1) HH EH1 R L IH2 NG G ER0 +HERRMAN HH EH1 R M AH0 N +HERRMANN HH EH1 R M AH0 N +HERRO HH EH1 R OW0 +HERROD HH EH1 R AH0 D +HERROLD HH EH1 R OW2 L D +HERRON HH EH1 R AH0 N +HERRONIMO HH ER0 AA1 N AH0 M OW0 +HERRONIMO'S HH ER0 AA1 N AH0 M OW0 Z +HERS HH ER0 Z +HERS(1) HH ER1 Z +HERSANT HH ER1 S AH0 N T +HERSCH HH ER1 SH +HERSCHEL HH ER1 SH AH0 L +HERSCHEL'S HH ER1 SH AH0 L Z +HERSCHELL HH ER1 SH AH0 L +HERSCHENSOHN HH ER1 SH AH0 N S AH0 N +HERSCU HH ER0 S K UW1 +HERSELF HH ER0 S EH1 L F +HERSEY HH ER1 S IY0 +HERSH HH ER1 SH +HERSHBERGER HH ER1 SH B ER0 G ER0 +HERSHEY HH ER1 SH IY0 +HERSHEY'S HH ER1 SH IY0 Z +HERSHISER HH ER1 SH AY0 Z ER0 +HERSHKOWITZ HH ER1 SH K AH0 W IH0 T S +HERSHMAN HH ER1 SH M AH0 N +HERSHNER HH ER1 SH N ER0 +HERSKOVITZ HH ER1 S K AH0 V IH0 T S +HERSKOWITZ HH ER1 S K AH0 W IH0 T S +HERSMAN HH ER1 S M AH0 N +HERSOM HH ER1 S AH0 M +HERSON HH ER1 S AH0 N +HERST HH ER1 S T +HERT HH ER1 T +HERTA HH ER1 T AH0 +HERTEL HH ER1 T AH0 L +HERTENSTEIN HH ER1 T AH0 N S T AY0 N +HERTENSTEIN(1) HH ER1 T AH0 N S T IY0 N +HERTER HH ER1 T ER0 +HERTHA HH ER1 TH AH0 +HERTIG HH ER1 T IH0 G +HERTING HH ER1 T IH0 NG +HERTLEIN HH ER1 T L AY0 N +HERTOG HH ER1 T AA0 G +HERTZ HH EH1 R T S +HERTZ(1) HH ER1 T S +HERTZBERG HH ER1 T S B ER0 G +HERTZENLEBEN HH ER1 T AH0 N L EY2 B AH0 N +HERTZENLEBEN'S HH ER1 T AH0 N L EY2 B AH0 N Z +HERTZLER HH ER1 T Z AH0 L ER0 +HERTZLER(1) HH ER1 T Z L ER0 +HERTZOG HH ER1 T Z AH0 G +HERTZOG(1) HH ER1 T Z AA2 G +HERVE HH ER1 V +HERVE(1) HH ER1 V EY0 +HERVEY HH ER0 V EY1 +HERWICK HH ER1 W IH2 K +HERWIG HH ER1 W IH0 G +HERWITZ HH ER1 W IH0 T S +HERYANA HH ER0 Y AE1 N AH0 +HERZ HH ER1 Z +HERZBERG HH ER1 Z B ER0 G +HERZBERGER HH ER1 Z B ER0 G ER0 +HERZEGOVINA HH EH2 R T S AH0 G OW0 V IY1 N AH0 +HERZEGOVINA(1) HH ER2 T S AH0 G OW0 V IY1 N AH0 +HERZEGOVINA'S HH EH2 R T S AH0 G OW0 V IY1 N AH0 Z +HERZEGOVINA'S(1) HH ER2 T S AH0 G OW0 V IY1 N AH0 Z +HERZER HH ER1 Z ER0 +HERZFELD HH ER1 Z F EH0 L D +HERZIG HH ER1 Z IH0 G +HERZING HH ER1 Z IH0 NG +HERZLINGER HH ER1 Z L IH2 NG ER0 +HERZOG HH ER1 Z AA0 G +HESCH HH EH1 SH +HESELTINE HH EH1 S AH0 L T IY2 N +HESELTINE(1) HH EH1 S AH0 L T AY2 N +HESELTON HH IH0 S EH1 L T AH0 N +HESHENG HH EH1 SH EH1 NG +HESIK HH EH1 S IH0 K +HESIK(1) HH EY1 S IH0 K +HESIOD HH IY1 S IY0 AH0 D +HESITANCY HH EH1 Z IH0 T AH0 N S IY0 +HESITANT HH EH1 Z IH0 T AH0 N T +HESITANTLY HH EH1 Z IH0 T AH0 N T L IY0 +HESITATE HH EH1 Z AH0 T EY2 T +HESITATED HH EH1 Z IH0 T EY2 T IH0 D +HESITATES HH EH1 Z AH0 T EY2 T S +HESITATING HH EH1 Z AH0 T EY2 T IH0 NG +HESITATION HH EH2 Z AH0 T EY1 SH AH0 N +HESITATIONS HH EH2 Z AH0 T EY1 SH AH0 N Z +HESKETH HH EH1 S K IH0 TH +HESKETT HH EH1 S K IH0 T +HESLEP HH EH1 S L IH0 P +HESLER HH EH1 S AH0 L ER0 +HESLER(1) HH EH1 S L ER0 +HESLIN HH EH1 Z L IH0 N +HESLIN'S HH EH1 Z L IH0 N Z +HESLOP HH EH1 S L AH0 P +HESPER HH EH1 S P ER0 +HESPERA HH EY0 S P EH1 R AH0 +HESS HH EH1 S +HESSE HH EH1 S +HESSE'S HH EH1 S IH0 Z +HESSEL HH EH1 S AH0 L +HESSELTINE HH EH1 S IH0 L T IY0 N +HESSER HH EH1 S ER0 +HESSIAN HH EH1 SH AH0 N +HESSING HH EH1 S IH0 NG +HESSINGER HH EH1 S IH0 N JH ER0 +HESSION HH EH1 SH IH0 N +HESSITE HH EH1 S AY0 T +HESSLER HH EH1 S L ER0 +HESSLING HH EH1 S AH0 L IH0 NG +HESSLING(1) HH EH1 S L IH0 NG +HESSON HH EH1 S AH0 N +HESSTON HH EH1 S T AH0 N +HESSTON'S HH EH1 S T AH0 N Z +HESTAND HH EH1 S T AH0 N D +HESTER HH EH1 S T ER0 +HESTHER HH EH1 S DH ER0 +HESTIA HH EH1 S T IY0 AH0 +HESTON HH EH1 S T AH0 N +HETEROCERCAL HH EH2 T ER0 OW0 S ER1 K AH0 L +HETERODOX HH EH1 T ER0 AH0 D AA2 K S +HETERODOXY HH EH1 T ER0 AH0 D AA2 K S IY0 +HETERODYNE HH EH1 T ER0 AH0 D AY2 N +HETEROGENEITY HH EH2 T ER0 AH0 JH IH0 N IY1 AH0 T IY0 +HETEROGENEITY(1) HH EH2 T ER0 AH0 JH IH0 N EY1 AH0 T IY0 +HETEROGENEOUS HH EH2 T ER0 AH0 JH IY1 N Y AH0 S +HETEROSEXUAL HH EH2 T ER0 OW0 S EH1 K SH UW2 AH0 L +HETEROSEXUALITY HH EH2 T ER0 OW0 S EH2 K SH UW0 AE1 L IH0 T IY0 +HETEROSEXUALS HH EH2 T ER0 OW0 S EH1 K SH UW2 AH0 L Z +HETEROSIS HH EH2 T ER0 OW1 S AH0 S +HETEROSPOROUS HH EH2 T ER0 AA1 S P ER0 AH0 S +HETEROTROPHIC HH EH2 T ER0 AH0 T R AA1 F IH0 K +HETEROZYGOUS HH EH2 T ER0 AH0 Z AY1 G AH0 S +HETH HH EH1 TH +HETHERINGTON HH EH1 DH ER0 IH0 NG T AH0 N +HETLAND HH EH1 T L AH0 N D +HETMAN HH EH1 T M AH0 N +HETRICK HH EH1 T R IH0 K +HETT HH EH1 T +HETTEL HH EH1 T AH0 L +HETTI HH EH1 T IY0 +HETTICK HH EH1 T IH0 K +HETTIE HH EH1 T IY0 +HETTLER HH EH1 T L ER0 +HETTRICK HH EH1 T R IH0 K +HETTY HH EH1 T IY0 +HETU HH IY1 CH UW0 +HETZ HH EH1 T S +HETZEL HH EH1 T Z AH0 L +HETZER HH EH1 T Z ER0 +HETZLER HH EH1 T S L ER0 +HEUBERGER HH OY1 B ER0 G ER0 +HEUBLEIN HH Y UW1 B L AY2 N +HEUER HH Y UW1 ER0 +HEUER'S HH Y UW1 ER0 Z +HEUERMAN HH OY1 ER0 M AH0 N +HEUERMANN HH OY1 ER0 M AH0 N +HEUMAN HH Y UW1 M AH0 N +HEUMANN HH Y UW1 M AH0 N +HEUN HH Y UW1 N +HEUNG-YEUNG HH UW1 NG Y UW1 NG +HEUPEL HH OY1 P AH0 L +HEURING HH ER1 IH0 NG +HEURISTIC HH Y UH0 R IH1 S T IH0 K +HEURISTICS HH Y UH0 R IH1 S T IH0 K S +HEUSEN HH Y UW1 S AH0 N +HEUSER HH OY1 S ER0 +HEUSSER HH Y UW1 S ER0 +HEVENER HH EH1 V IY0 N ER0 +HEVERLY HH EH1 V ER0 L IY0 +HEVEY HH IH0 V EY1 +HEVIA HH EY1 V IY0 AH0 +HEVNER HH EH1 V N ER0 +HEW HH Y UW1 +HEWARD HH Y UW1 ER0 D +HEWE HH Y UW1 +HEWELL HH EH1 W EH0 L +HEWELL(1) HH Y UW1 W EH0 L +HEWER HH Y UW1 ER0 +HEWES HH Y UW1 Z +HEWETT HH Y UW1 IH0 T +HEWEY HH Y UW1 IY0 +HEWING HH Y UW1 IH0 NG +HEWINS HH Y UW1 IH0 N Z +HEWITT HH Y UW1 IH0 T +HEWITT'S HH Y UW1 IH0 T S +HEWLER HH Y UW1 L ER0 +HEWLER'S HH Y UW1 L ER0 Z +HEWLETT HH Y UW1 L IH0 T +HEWN HH Y UW1 N +HEWS HH Y UW1 Z +HEWSON HH Y UW1 S AH0 N +HEX HH EH1 K S +HEXACHLOROPHENE HH EH2 K S AH0 K L AO1 R AH0 F IY2 N +HEXAGON HH EH1 K S AH0 G AA2 N +HEXAGONAL HH EH0 K S AE1 G AH0 N AH0 L +HEXANE HH EH1 K S EY0 N +HEXCEL HH EH1 K S AH0 L +HEXT HH EH1 K S T +HEY HH EY1 +HEYBOER HH EY1 B OW0 ER0 +HEYD HH EY1 D +HEYDAY HH EY1 D EY2 +HEYDE HH EY1 D +HEYDEN HH EY1 D AH0 N +HEYDON HH EY1 D AH0 N +HEYDT HH EY1 D T +HEYE HH AY1 +HEYEN HH AY1 N +HEYER HH EY1 ER0 +HEYING HH EY1 IH0 NG +HEYL HH EY1 L +HEYMAN HH EY1 M AH0 N +HEYMAN'S HH EY1 M AH0 N Z +HEYMANN HH EY1 M AH0 N +HEYMANN'S HH EY1 M AH0 N Z +HEYN HH EY1 N +HEYNE HH EY1 N +HEYS HH EY1 Z +HEYSE HH EY1 S +HEYSER HH EY1 Z ER0 +HEYWARD HH EY1 W ER0 D +HEYWOOD HH EY1 W UH2 D +HEZBOLLAH HH EH1 Z B AA0 L AH2 +HEZBOLLAH(1) HH EH2 Z B AA0 L AH1 +HEZBOLLAH'S HH EH1 Z B AA0 L AH2 Z +HEZBULLAH HH EH2 Z B AA0 L AH1 +HEZBULLAH(1) HH EH1 Z B AA0 L AH2 +HEZBULLAH'S HH EH1 Z B AA0 L AH2 Z +HFDF EY1 CH EH1 F D IY1 EH1 F +HGH EY1 CH JH IY1 EY1 CH +HI HH AY1 +HI-FI HH AY1 F AY1 +HIAA EY1 CH AY1 EY1 EY1 +HIAASEN HH AY1 AA0 S IH0 N +HIALEAH HH AY2 AH0 L IY1 AH0 +HIAM HH AY1 AH0 M +HIATT HH AY1 AH0 T +HIATT'S HH AY1 AH0 T S +HIATUS HH AY0 EY1 T AH0 S +HIAWATHA HH AY2 AH0 W AA1 TH AH0 +HIBAAQ HH AY1 B AE2 K +HIBACHI HH IY0 B AA1 CH IY2 +HIBBARD HH IH1 B ER0 D +HIBBEN HH IH1 B AH0 N +HIBBERD HH IH1 B ER0 D +HIBBERT HH IH1 B ER0 T +HIBBETT HH IH1 B IH0 T +HIBBING HH IH1 B IH0 NG +HIBBITTS HH IH1 B IH0 T S +HIBBLER HH IH1 B L ER0 +HIBBS HH IH1 B Z +HIBDON HH IH1 B D AH0 N +HIBERNATE HH AY1 B ER0 N EY2 T +HIBERNATION HH AY2 B ER0 N EY1 SH AH0 N +HIBERNIA HH AY2 B ER1 N IY0 AH0 +HIBERNIA'S HH AY2 B ER1 N IY0 AH0 Z +HIBLER HH IH1 B L ER0 +HIBMA HH IH1 B M AH0 +HIBNER HH IH1 B N ER0 +HIBOR HH AY1 B ER0 +HIBSHMAN HH IH1 B SH M AH0 N +HICCOUGH HH IH1 K AH0 P +HICCOUGHS HH IH1 K AH0 P S +HICCUP HH IH1 K AH0 P +HICCUPS HH IH1 K AH0 P S +HICE HH AY1 S +HICFA HH IH1 K F AH0 +HICHENS HH IH1 K AH0 N Z +HICK HH IH1 K +HICKAM HH IH1 K AH0 M +HICKCOX HH IH1 K AA0 K S +HICKEL HH IH1 K AH0 L +HICKEN HH IH1 K AH0 N +HICKERSON HH IH1 K ER0 S AH0 N +HICKEY HH IH1 K IY0 +HICKLE HH IH1 K AH0 L +HICKLIN HH IH1 K L IH0 N +HICKLING HH IH1 K L IH0 NG +HICKMAN HH IH1 K M AH0 N +HICKMON HH IH1 K M AH0 N +HICKOK HH IH1 K AH0 K +HICKORIES HH IH1 K ER0 IY0 Z +HICKORY HH IH1 K ER0 IY0 +HICKORY(1) HH IH1 K R IY0 +HICKOX HH IH1 K AA0 K S +HICKS HH IH1 K S +HICKSON HH IH1 K S AH0 N +HICKSVILLE HH IH1 K S V IH2 L +HID HH IH1 D +HIDALGO HH AH0 D AE1 L G OW2 +HIDDEN HH IH1 D AH0 N +HIDE HH AY1 D +HIDEAKI HH IY2 D EY0 AA1 K IY0 +HIDEAWAY HH AY1 D AH0 W EY2 +HIDEBOUND HH AY1 D B AW2 N D +HIDEO HH IH0 D EY1 OW0 +HIDEOUS HH IH1 D IY0 AH0 S +HIDEOUSLY HH IH1 D IY0 AH0 S L IY0 +HIDEOUT HH AY1 D AW2 T +HIDEOUTS HH AY1 D AW2 T S +HIDER HH AY1 D ER0 +HIDES HH AY1 D Z +HIDING HH AY1 D IH0 NG +HIDY HH AY1 D IY0 +HIEB HH IY1 B +HIEBER HH IY1 B ER0 +HIEBERT HH IY1 B ER0 T +HIEGEL HH IY1 G AH0 L +HIEMS HH IY1 M Z +HIEMSTRA HH IY1 M S T R AH0 +HIER HH AY1 ER0 +HIERARCHICAL HH AY2 R AA1 R K AH0 K AH0 L +HIERARCHIES HH AY1 R AA2 R K IY0 Z +HIERARCHY HH AY1 ER0 AA2 R K IY0 +HIERARCHY(1) HH AY1 R AA2 R K IY0 +HIERHOLZER HH AY1 R HH OW0 L Z ER0 +HIEROGLYPH HH AY2 R OW0 G L IH1 F +HIEROGLYPHIC HH AY2 R OW0 G L IH1 F IH0 K +HIEROGLYPHICS HH AY2 R OW0 G L IH1 F IH0 K S +HIEROGLYPHS HH AY2 R OW0 G L IH1 F S +HIERS HH IY1 R Z +HIESTAND HH IY1 S T AH0 N D +HIESTER HH AY1 IH0 S T ER0 +HIETALA HH AY1 T AH0 L AH0 +HIETPAS HH AY1 T P AH0 Z +HIETT HH AY1 T +HIGA HH IY1 G AH0 +HIGASHI HH IY0 G AA1 SH IY0 +HIGBEE HH IH1 G B IY2 +HIGBIE HH IH1 G B IY0 +HIGBY HH IH1 G B IY0 +HIGDON HH IH1 G D AH0 N +HIGGASON HH IH1 G AH0 S AH0 N +HIGGENBOTHAM HH IH1 G IH0 N B AH0 TH AH0 M +HIGGENS HH IH1 G AH0 N Z +HIGGERSON HH IH1 G ER0 S AH0 N +HIGGINBOTHAM HH IH0 G IH0 N B AA1 TH AH0 M +HIGGINBOTTOM HH IH0 G IH0 N B AA1 T AH0 M +HIGGINS HH IH1 G IH0 N Z +HIGGINSON HH IH1 G IH0 N S AH0 N +HIGGS HH IH1 G Z +HIGH HH AY1 +HIGH-END HH AY2 EH1 N D +HIGH-LEVEL HH AY2 L EH1 V AH0 L +HIGH-MINDED HH AY2 M AY1 N D IH0 D +HIGH-POWERED HH AY2 P AW1 ER0 D +HIGH-PROFILE HH AY2 P R OW1 F AY0 L +HIGH-QUALITY HH AY2 K W AA1 L AH0 T IY0 +HIGH-SCHOOL HH AY1 S K UW2 L +HIGH-SPEED HH AY1 S P IY2 D +HIGH-SPIRITED HH AY2 S P IH1 R IH0 D IH0 D +HIGH-SPIRITEDNESS HH AY2 S P IH1 R IH0 D IH0 D N AH0 S +HIGH-TECH HH AY2 T EH1 K +HIGHAM HH AY1 AH0 M +HIGHAM(1) HH IH1 G AH0 M +HIGHBERGER HH AY1 B ER2 G ER0 +HIGHBOY HH AY1 B OY2 +HIGHBROW HH AY1 B R AW2 +HIGHBROWS HH AY1 B R AW2 Z +HIGHER HH AY1 ER0 +HIGHEST HH AY1 AH0 S T +HIGHFALUTIN HH AY2 F AH0 L UW1 T IH0 N +HIGHFIELD HH AY1 F IY2 L D +HIGHFILL HH AY1 F IH2 L +HIGHFLIER HH AY1 F L AY2 ER0 +HIGHFLIERS HH AY1 F L AY2 ER0 Z +HIGHFLYING HH AY1 F L AY2 IH0 NG +HIGHLAND HH AY1 L AH0 N D +HIGHLANDER HH AY1 L AE2 N D ER0 +HIGHLANDERS HH AY1 L AE2 N D ER0 Z +HIGHLANDS HH AY1 L AH0 N D Z +HIGHLEY HH AY1 L IY0 +HIGHLIGHT HH AY1 L AY2 T +HIGHLIGHTED HH AY1 L AY2 T IH0 D +HIGHLIGHTING HH AY1 L AY2 T IH0 NG +HIGHLIGHTS HH AY1 L AY2 T S +HIGHLY HH AY1 L IY0 +HIGHMAN HH AY1 M AH0 N +HIGHNESS HH AY1 N AH0 S +HIGHOSIN HH AY1 OW0 S IH0 N +HIGHRISE HH AY1 R AY2 Z +HIGHRISES HH AY1 R AY2 Z IH0 Z +HIGHS HH AY1 Z +HIGHSCHOOL HH AY1 S K UW2 L +HIGHSCHOOLS HH AY1 S K UW2 L Z +HIGHSMITH HH AY1 S M IH2 TH +HIGHSPEED HH AY1 S P IY2 D +HIGHT HH AY1 T +HIGHTECH HH AY1 T EH2 K +HIGHTOWER HH AY1 T AW2 ER0 +HIGHTOWER'S HH AY1 T AW2 ER0 Z +HIGHWAY HH AY1 W EY2 +HIGHWAY'S HH AY1 W EY2 Z +HIGHWAYS HH AY1 W EY2 Z +HIGHYIELD HH AY1 Y IY1 L D +HIGINBOTHAM HH IH1 G IH0 N B AH0 TH AH0 M +HIGLEY HH IH1 G L IY0 +HIGMAN HH IH1 G M AH0 N +HIGNIGHT HH IH1 G N AY2 T +HIGNITE HH IH1 G N AY2 T +HIGUCHI HH IY0 G UW1 CH IY0 +HIGUERA HH IY0 G EH1 R AH0 +HIJACK HH AY1 JH AE2 K +HIJACKED HH AY1 JH AE2 K T +HIJACKER HH AY1 JH AE2 K ER0 +HIJACKERS HH AY1 JH AE2 K ER0 Z +HIJACKING HH AY1 JH AE2 K IH0 NG +HIJACKINGS HH AY1 JH AE2 K IH0 NG Z +HIJINKS HH IH1 JH IH0 NG K S +HIKE HH AY1 K +HIKED HH AY1 K T +HIKER HH AY1 K ER0 +HIKERS HH AY1 K ER0 Z +HIKES HH AY1 K S +HIKING HH AY1 K IH0 NG +HILAND HH IH1 L AH0 N D +HILARIA HH IY0 L AA1 R IY0 AH0 +HILARIO HH IY0 L AA1 R IY0 OW0 +HILARIOUS HH IH0 L EH1 R IY0 AH0 S +HILARIOUSLY HH IH0 L EH1 R IY0 AH0 S L IY0 +HILARITY HH IH0 L EH1 R AH0 T IY0 +HILARY HH IH1 L ER0 IY0 +HILB HH IH1 L B +HILBERG HH IH1 L B ER0 G +HILBERT HH IH1 L B ER0 T +HILBORN HH IH1 L B ER0 N +HILBUN HH IH1 L B AH0 N +HILBURN HH IH1 L B ER0 N +HILD HH IH1 L D +HILDA HH IH1 L D AH0 +HILDE HH IH1 L D +HILDEBRAN HH IH1 L D IH0 B R AH0 N +HILDEBRAND HH IH1 L D IH0 B R AE2 N D +HILDEBRANDT HH IH1 L D IH0 B R AH0 N T +HILDEBRANT HH IH1 L D IH0 B R AH0 N T +HILDEGARD HH IH1 L D AH0 G AA2 R D +HILDEGARDE HH IH1 L D IH0 G AA2 R D +HILDEGARDES HH IH1 L D AH0 G AA2 R D Z +HILDEMAR HH IH1 L D IH0 M ER0 +HILDEN HH AY1 L D AH0 N +HILDENBRAND HH IH1 L D IH0 N B R AH0 N D +HILDENBRAND(1) HH IH1 L D AH0 N B R AE0 N D +HILDER HH IH1 L D ER0 +HILDERBRAND HH IH1 L D ER0 B R AH0 N D +HILDERBRANDT HH IH1 L D ER0 B R AH0 N T +HILDIE HH AY1 L D IY0 +HILDITCH HH IH1 L D IH0 CH +HILDRETH HH IH1 L D R IH0 TH +HILDUM HH IH1 L D AH0 M +HILDY HH IH1 L D IY0 +HILE HH AY1 L +HILEMAN HH AY1 L M AH0 N +HILEMON HH AY1 L M AH0 N +HILEMON'S HH AY1 L M AH0 N Z +HILER HH AY1 L ER0 +HILES HH AY1 L Z +HILEY HH IH1 L IY0 +HILFIGER HH IH1 L F AY0 G ER0 +HILFIGER(1) HH IH1 L F IH0 G ER0 +HILFIKER HH IH1 L F IH0 K ER0 +HILGART HH IH1 L G AA2 R T +HILGEMAN HH IH1 L G M AH0 N +HILGENBERG HH IH1 L G AH0 N B ER0 G +HILGENDORF HH IH1 L G IH0 N D AO0 R F +HILGER HH IH1 L G ER0 +HILGERS HH IH1 L G ER0 Z +HILGERT HH IH1 L G ER0 T +HILINSKI HH IH0 L IH1 N S K IY0 +HILKE HH IH1 L K AH0 +HILKER HH IH1 L K ER0 +HILL HH IH1 L +HILL'S HH IH1 L Z +HILLA HH IH1 L AH0 +HILLARD HH IH1 L ER0 D +HILLARD'S HH IH1 L ER0 D Z +HILLARY HH IH1 L ER0 IY0 +HILLARY'S HH IH1 L ER0 IY0 Z +HILLAS HH IH1 L AH0 S +HILLBILLIES HH IH1 L B IH2 L IY0 Z +HILLBILLY HH IH1 L B IH0 L IY0 +HILLCREST HH IH1 L K R EH0 S T +HILLE HH IH1 L +HILLEARY HH IH1 L ER0 IY0 +HILLEBRAND HH IH1 L IH0 B R AH0 N D +HILLEGAS HH IH1 L IH0 G AH0 Z +HILLEGASS HH IH1 L IH0 G AH0 S +HILLEL HH IH2 L EH1 L +HILLEN HH IH1 L AH0 N +HILLENBRAND HH IH1 L AH0 N B R AE2 N D +HILLENBRAND'S HH IH1 L AH0 N B R AE2 N D Z +HILLENBURG HH IH1 L AH0 N B ER0 G +HILLER HH IH1 L ER0 +HILLERMAN HH IH1 L ER0 M AH0 N +HILLERY HH IH1 L ER0 IY0 +HILLESHEIM HH IH1 L IH0 S HH AY0 M +HILLESTAD HH IH1 L IH0 S T AH0 D +HILLEY HH IH1 L IY0 +HILLHAVEN HH IH1 L HH EY2 V AH0 N +HILLHAVEN'S HH IH1 L HH EY2 V AH0 N Z +HILLHOUSE HH IH1 L HH AW2 S +HILLIAN HH IH1 L Y AH0 N +HILLIANS HH IH1 L Y AH0 N Z +HILLIARD HH IH1 L Y AA0 R D +HILLIER HH IH1 L IY0 ER0 +HILLIGOSS HH IH1 L IH0 G AA0 S +HILLIKER HH IH1 L AY0 K ER0 +HILLIKER(1) HH IH1 L IH0 K ER0 +HILLIN HH IH1 L IH0 N +HILLING HH IH1 L IH0 NG +HILLIS HH IH1 L IH0 S +HILLMAN HH IH1 L M AE2 N +HILLMANN HH IH1 L M AH0 N +HILLMER HH IH1 L M ER0 +HILLOCK HH IH1 L AH0 K +HILLS HH IH1 L Z +HILLS' HH IH1 L Z +HILLSBORO HH IH1 L Z B ER0 OW0 +HILLSBOROUGH HH IH1 L Z B ER0 OW0 +HILLSDALE HH IH1 L Z D EY2 L +HILLSDOWN HH IH1 L Z D AW2 N +HILLSIDE HH IH1 L S AY2 D +HILLSIDES HH IH1 L S AY2 D Z +HILLSMAN HH IH1 L S M AH0 N +HILLSON HH IH1 L S AH0 N +HILLSTROM HH IH1 L S T R AH0 M +HILLTOP HH IH1 L T AA2 P +HILLTOPS HH IH1 L T AA2 P S +HILLY HH IH1 L IY0 +HILLYARD HH IH1 L Y AA2 R D +HILLYER HH IH1 L IY0 ER0 +HILMA HH IH1 L M AH0 +HILMER HH IH1 L M ER0 +HILMES HH IH1 L M Z +HILO HH IY1 L OW0 +HILPERT HH IH1 L P ER0 T +HILSABECK HH IH1 L S AH0 B EH2 K +HILSCHER HH IH1 L SH ER0 +HILSINGER HH IH1 L S IH0 NG ER0 +HILSMAN HH IH1 L Z M AH0 N +HILSON HH IH1 L S AH0 N +HILT HH IH1 L T +HILTNER HH IH1 L T N ER0 +HILTON HH IH1 L T AH0 N +HILTON'S HH IH1 L T AH0 N Z +HILTONS HH IH1 L T AH0 N Z +HILTON_HEAD HH IH1 L T AH0 N HH EH1 D +HILTS HH IH1 L T S +HILTUNEN HH IH1 L T AH0 N AH0 N +HILTY HH IH1 L T IY0 +HILTZ HH IH1 L T S +HILYARD HH AH0 L Y AA1 R D +HILYER HH IH1 L IY0 ER0 +HIM HH IH1 M +HIM(1) IH0 M +HIMALAYA HH IH2 M AH0 L AY1 AH0 +HIMALAYA(1) HH IH2 M AH0 L EY1 AH0 +HIMALAYAN HH IH2 M AH0 L EY1 AH0 N +HIMALAYAN(1) HH IH2 M AH0 L AY1 AH0 N +HIMALAYAS HH IH2 M AH0 L AY1 AH0 S +HIMALAYAS(1) HH IH2 M AH0 L EY1 AH0 S +HIME HH AY1 M +HIMEBAUGH HH IH1 M IH0 B AO0 +HIMEL HH IH1 M AH0 L +HIMES HH AY1 M Z +HIMMEL HH IH1 M AH0 L +HIMMELBERGER HH IH1 M AH0 L B ER0 G ER0 +HIMMELFARB HH IH1 M AH0 L F AA2 R B +HIMMELSBACH HH IH1 M IH0 L S B AA0 K +HIMMELSTEIN HH IH1 M AH0 L S T AY0 N +HIMMELSTEIN(1) HH IH1 M AH0 L S T IY0 N +HIMMLER HH IH1 M L ER0 +HIMONT HH IH1 M AH0 N T +HIMONT(1) HH AY1 M AH0 N T +HIMSELF HH IH0 M S EH1 L F +HINCH HH IH1 N CH +HINCHCLIFF HH IH1 N CH K L IH0 F +HINCHCLIFFE HH IH1 N CH K L IH0 F +HINCHEY HH IH1 N CH IY0 +HINCHLIFFE HH IH1 N K L IH0 F +HINCHMAN HH IH1 NG K M AH0 N +HINCK HH IH1 NG K +HINCKLEY HH IH1 NG K L IY0 +HIND HH AY1 N D +HINDE HH IH1 N D +HINDELONG HH IH1 N D AH0 L AO0 NG +HINDER HH IH1 N D ER0 +HINDERED HH IH1 N D ER0 D +HINDERER HH IH1 N D ER0 ER0 +HINDERING HH IH1 N D ER0 IH0 NG +HINDERLITER HH IH1 N D ER0 L IY0 T ER0 +HINDERMAN HH AY1 N D ER0 M AH0 N +HINDERS HH IH1 N D ER0 Z +HINDES HH IH1 N D Z +HINDI HH IH1 N D IY0 +HINDLE HH IH1 N D AH0 L +HINDLEY HH IH1 N D L IY0 +HINDMAN HH AY1 N D M AH0 N +HINDQUARTER HH AY1 N D K W AO2 R T ER0 +HINDQUARTERS HH AY1 N D K W AO2 R T ER0 Z +HINDRANCE HH IH1 N D R AH0 N S +HINDRANCES HH IH1 N D R AH0 N S IH0 Z +HINDS HH AY1 N D Z +HINDSIGHT HH AY1 N D S AY2 T +HINDSIGHT(1) HH AY1 N S AY2 T +HINDSIGHT'S HH AY1 N D S AY2 T S +HINDSIGHT'S(1) HH AY1 N S AY2 T S +HINDU HH IH1 N D UW2 +HINDUISM HH IH1 N JH UW0 IH2 Z AH0 M +HINDUS HH IH1 N D UW2 Z +HINDUSTAN HH IH1 N D UW0 S T AE2 N +HINE HH AY1 N +HINEBAUGH HH IH1 N IH0 B AO0 +HINELINE HH IH1 N IH0 L AY2 N +HINELY HH AY1 N L IY0 +HINEMAN HH AY1 N M AH0 N +HINER HH AY1 N ER0 +HINERMAN HH AY1 N ER0 M AH0 N +HINES HH AY1 N Z +HINESLEY HH IH1 N IH0 S L IY0 +HINESLEY(1) HH AY1 N Z L IY0 +HINEY HH IH1 N IY0 +HING HH IH1 NG +HINGE HH IH1 N JH +HINGED HH IH1 N JH D +HINGER HH IH1 N JH ER0 +HINGES HH IH1 N JH IH0 Z +HINGHAM HH IH1 NG AH0 M +HINGIS HH IH1 NG G AH0 S +HINGLE HH IH1 NG G AH0 L +HINGST HH IH1 NG S T +HINGSTON HH IH1 NG S T AH0 N +HINK HH IH1 NG K +HINKEL HH IH1 NG K AH0 L +HINKELMAN HH IH1 NG K AH0 L M AH0 N +HINKLE HH IH1 NG K AH0 L +HINKLEY HH IH1 NG K L IY0 +HINKSON HH IH1 NG K S AH0 N +HINMAN HH IH1 N M AH0 N +HINMEN HH IH1 N M EH0 N +HINN HH IH1 N +HINNANT HH IH1 N AH0 N T +HINNENKAMP HH IH1 N IH0 N K AE0 M P +HINNERS HH IH1 N ER0 Z +HINNY HH IH1 N IY0 +HINO HH IY1 N OW0 +HINOJOS HH IY0 N OW1 Y OW0 Z +HINOJOSA HH IY0 N OW0 JH OW1 S AH0 +HINOTE HH IH0 N OW1 T +HINRICHS HH IH1 N R IH0 K S +HINRICHSEN HH IH1 N R IH0 K S AH0 N +HINSCH HH IH1 N SH +HINSDALE HH IH1 N S D EY2 L +HINSHAW HH IH1 N SH AO2 +HINSLEY HH IH1 N S L IY0 +HINSON HH IH1 N S AH0 N +HINT HH IH1 N T +HINTED HH IH1 N T AH0 D +HINTED(1) HH IH1 N T IH0 D +HINTED(2) HH IH1 N IH0 D +HINTERLAND HH IH1 N T ER0 L AE2 N D +HINTERLANDS HH IH1 N T ER0 L AE2 N D Z +HINTING HH IH1 N T IH0 NG +HINTON HH IH1 N T AH0 N +HINTS HH IH1 N T S +HINTZ HH IH1 N T S +HINTZE HH IH1 N T Z +HINZ HH IH1 N Z +HINZACK HH IH1 N Z AE0 K +HINZE HH IH1 N Z +HINZMAN HH IH1 N Z M AH0 N +HIOTT HH AY1 AH0 T +HIP HH IH1 P +HIP-HOP HH IH1 P HH AO2 P +HIP-POCKET HH IH1 P P AA1 K AH0 T +HIPBONE HH IH1 P B OW1 N +HIPBONES HH IH1 P B OW1 N Z +HIPKINS HH IH1 P K IH0 N Z +HIPOLITO IY1 P OW0 L IY1 T OW0 +HIPP HH IH1 P +HIPPE HH IH1 P +HIPPEN HH IH1 P AH0 N +HIPPENSTEEL HH IH1 P IH0 N S T IY0 L +HIPPER HH IH1 P ER0 +HIPPERT HH IH1 P ER0 T +HIPPEST HH IH1 P AH0 S T +HIPPIE HH IH1 P IY0 +HIPPIES HH IH1 P IY0 Z +HIPPLE HH IH1 P AH0 L +HIPPLER HH IH1 P L ER0 +HIPPO HH IH1 P OW0 +HIPPOCAMPUS HH IH2 P OW0 K AE1 M P AH0 S +HIPPOCRATES HH IH1 P AH0 K R EY2 T S +HIPPOCRATES(1) HH IH0 P AO1 K R AH0 T IY0 Z +HIPPOCRATIC HH IH0 P AH0 K R AE1 T IH0 K +HIPPODROME HH IH1 P AH0 D R OW2 M +HIPPOLYTUS HH AH0 P AA1 L AH0 T AH0 S +HIPPOPOTAMUS HH IH2 P AH0 P AA1 T AH0 M AH0 S +HIPPOPOTAMUSES HH IH2 P AH0 P AA1 T AH0 M AH0 S IH0 Z +HIPPOS HH IH1 P OW0 Z +HIPPS HH IH1 P S +HIPS HH IH1 P S +HIPSHER HH IH1 P SH ER0 +HIPSKIND HH IH1 P S K IH0 N D +HIPSTER HH IH1 P S T ER0 +HIPSTERS HH IH1 P S T ER0 Z +HIPWELL HH IH1 P W EH2 L +HIRABAYASHI HH IH0 R AH0 B AY0 AA1 SH IY0 +HIRADIN HH IH0 R AA1 D IH0 N +HIRAI HH IH0 R AA1 IY0 +HIRAM HH AY1 R AH0 M +HIRANO HH IH0 R AA1 N OW0 +HIRATA HH IH0 R AA1 T AH0 +HIRAYAMA HH IH0 R AA0 Y AA1 M AH0 +HIRD HH ER1 D +HIRE HH AY1 ER0 +HIRE(1) HH AY1 R +HIRED HH AY1 ER0 D +HIRES HH AY1 ER0 Z +HIRES(1) HH AY1 R Z +HIRIART HH IH1 R IY0 AA0 R T +HIRING HH AY1 R IH0 NG +HIRINGS HH AY1 R IH0 NG Z +HIRN HH ER1 N +HIRO HH IH1 R OW0 +HIROAKI HH IH2 R OW0 AA1 K IY0 +HIROHITO HH IH2 R OW0 HH IY1 T OW2 +HIROHITO(1) HH IH2 R AH0 HH IY1 T OW2 +HIROHITO'S HH IH2 R OW0 HH IY1 T OW2 Z +HIROHITO'S(1) HH IH2 R AH0 HH IY1 T OW2 Z +HIROMASA HH IH2 R OW0 M AA1 S AH0 +HIRONS HH AY1 R AH0 N Z +HIROSAKAMOKI HH IH2 R AH0 S AE0 K AH0 M OW1 K IY0 +HIROSAKIMA HH IH2 R AH0 S AH0 K IY1 M AH0 +HIROSE HH IH0 R OW1 S EY0 +HIROSHI HH IH0 R OW1 SH IY0 +HIROSHIMA HH IH2 R OW0 SH IY1 M AH0 +HIROSHIMA(1) HH IH2 R OW1 SH IH0 M AH0 +HIROTA HH IH0 R OW1 T AH0 +HIROYUKI HH IH2 R OW0 Y UW1 K IY0 +HIRSCH HH ER1 SH +HIRSCH'S HH ER1 SH IH0 Z +HIRSCHBERG HH ER1 SH B ER0 G +HIRSCHFELD HH ER1 SH F EH0 L D +HIRSCHFIELD HH ER1 S K F IY0 L D +HIRSCHHORN HH ER1 SH HH ER0 N +HIRSCHI HH IH1 R S K IY0 +HIRSCHMAN HH ER1 SH M AH0 N +HIRSCHMANN HH ER1 SH M AH0 N +HIRSCHY HH ER1 SH IY0 +HIRSH HH ER1 SH +HIRSHBERG HH ER1 SH B ER0 G +HIRSHFIELD HH ER1 SH F IY0 L D +HIRSHHORN HH ER1 SH HH AO2 R N +HIRSHHORN(1) HH ER1 SH AO2 R N +HIRSHMAN HH ER1 SH M AH0 N +HIRST HH ER1 S T +HIRST'S HH ER1 S T S +HIRSUTE HH ER0 S UW1 T +HIRT HH ER1 T +HIRTH HH ER1 TH +HIRTLE HH ER1 T AH0 L +HIRTZ HH ER1 T S +HIRULOG HH IH1 R UW2 L AA2 G +HIRZEL HH ER1 Z AH0 L +HIS HH IH1 Z +HIS(1) HH IH0 Z +HISADA HH IH0 S AA1 D AH0 +HISAO HH IH0 S AA1 OW0 +HISAW HH AY1 S AO0 +HISCOCK HH IH1 S K AH0 K +HISCOX HH IH1 S K AA0 K S +HISE HH AY1 Z +HISEL HH IH1 S AH0 L +HISER HH AY1 Z ER0 +HISEY HH IH1 S IY0 +HISHAM HH IH1 SH AH0 M +HISLE HH AY1 AH0 L +HISLOP HH IH1 S L AH0 P +HISPANIC HH IH0 S P AE1 N IH0 K +HISPANICS HH IH0 S P AE1 N IH0 K S +HISPANIOLA HH IH0 S P AA2 NG OW1 L AH0 +HISPANO HH IH0 S P AA1 N OW0 +HISPANOIL HH IH1 S P AH0 N OY2 L +HISS HH IH1 S +HISS'S HH IH1 S IH0 Z +HISSED HH IH1 S T +HISSELF HH IH2 S EH1 L F +HISSES HH IH1 S IH0 Z +HISSING HH IH1 S IH0 NG +HISSONG HH IH1 S AO2 NG +HISTADRUT HH IH1 S T AH0 D R AH0 T +HISTAMINE HH IH1 S T AH0 M IY2 N +HISTIDINE HH IH1 S T AH0 D IY2 N +HISTOGRAM HH IH1 S T AH0 G R AE2 M +HISTOGRAMS HH IH1 S T AH0 G R AE2 M Z +HISTOLOGY HH IH0 S T AA1 L AH0 JH IY0 +HISTORIAN HH IH0 S T AO1 R IY0 AH0 N +HISTORIANS HH IH0 S T AO1 R IY0 AH0 N Z +HISTORIC HH IH0 S T AO1 R IH0 K +HISTORICAL HH IH0 S T AO1 R IH0 K AH0 L +HISTORICALLY HH IH0 S T AO1 R IH0 K AH0 L IY0 +HISTORICALLY(1) HH IH0 S T AO1 R IH0 K L IY0 +HISTORIES HH IH1 S T ER0 IY0 Z +HISTORIES(1) HH IH1 S T R IY0 Z +HISTORIOGRAPHY HH IH0 S T AO2 R IY0 AA1 G R AH0 F IY0 +HISTORY HH IH1 S T ER0 IY0 +HISTORY(1) HH IH1 S T R IY0 +HISTORY'S HH IH1 S T ER0 IY0 Z +HISTORY'S(1) HH IH1 S T R IY0 Z +HISTRIONIC HH IH2 S T R IY0 AA1 N IH0 K +HISTRIONICS HH IH2 S T R IY0 AA1 N IH0 K S +HIT HH IH1 T +HIT-AND-RUN HH IH1 T AE0 N R AH2 N +HITACHI HH IH0 T AA1 CH IY0 +HITCH HH IH1 CH +HITCHCOCK HH IH1 CH K AA2 K +HITCHCOCK'S HH IH1 CH K AA2 K S +HITCHED HH IH1 CH T +HITCHENS HH IH1 CH AH0 N Z +HITCHES HH IH1 CH IH0 Z +HITCHHIKE HH IH1 CH HH AY2 K +HITCHHIKED HH IH1 CH HH AY2 K T +HITCHHIKER HH IH1 CH HH AY2 K ER0 +HITCHHIKERS HH IH1 CH HH AY2 K ER0 Z +HITCHHIKES HH IH1 CH HH AY2 K S +HITCHHIKING HH IH1 CH HH AY2 K IH0 NG +HITCHING HH IH1 CH IH0 NG +HITCHINGS HH IH1 CH IH0 NG Z +HITCHINS HH IH1 CH IH0 N Z +HITCHMAN HH IH1 CH M AH0 N +HITCHNER HH IH1 CH N ER0 +HITE HH AY1 T +HITES HH AY1 T S +HITHER HH IH1 DH ER0 +HITHERTO HH IH1 DH ER2 T UW1 +HITLER HH IH1 T L ER0 +HITLER'S HH IH1 T L ER0 Z +HITMAN HH IH1 T M AE2 N +HITOSHI HH IH0 T OW1 SH IY0 +HITS HH IH1 T S +HITSCHLER HH IH1 T S L ER0 +HITSCHLER(1) HH IH1 CH L ER0 +HITSMAN HH IH1 T S M AH0 N +HITSON HH IH1 T S AH0 N +HITT HH IH1 T +HITTER HH IH1 T ER0 +HITTER'S HH IH1 T ER0 Z +HITTERS HH IH1 T ER0 Z +HITTING HH IH1 T IH0 NG +HITTITE HH IH1 T AY2 T +HITTLE HH IH1 T AH0 L +HITTNER HH IH1 T N ER0 +HITTY HH IH1 T IY0 +HITZ HH IH1 T S +HITZEMAN HH IH1 T S M AH0 N +HIV EY2 CH AY2 V IY1 +HIVE HH AY1 V +HIVELY HH AY1 V L IY0 +HIVES HH AY1 V Z +HIWAY HH AY1 W EY2 +HIX HH IH1 K S +HIXENBAUGH HH IH0 G Z EH1 N B AO0 +HIXON HH IH1 K S AH0 N +HIXSON HH IH1 K S AH0 N +HIZBOLLAH HH IH0 Z B OW1 L AH0 +HIZER HH AY1 Z ER0 +HJELM HH Y EH1 L M +HJERPE HH Y ER1 P +HJORT HH AH0 Y AO1 R T +HLAD HH L AE1 D +HLADIK HH L AE1 D IH0 K +HLADKY HH L AE1 D K IY0 +HLAVAC HH L AA1 V AH0 K +HLAVACEK HH L AA1 V AH0 CH EH0 K +HLAVATY HH L AH0 V AA1 T IY0 +HM HH AH0 M +HMM HH AH0 M +HMONG M AO1 NG +HMONG(1) HH M AO1 NG +HMONG(2) HH AH0 M AO1 NG +HNAT HH N AE1 T +HO HH OW1 +HO'S HH OW1 Z +HOADLEY HH OW1 D L IY0 +HOAG HH OW1 G +HOAGIE HH OW1 G IY0 +HOAGLAND HH OW1 G L AH0 N D +HOAGLIN HH OW1 G L IH0 N +HOAGLUND HH OW1 G L AH0 N D +HOAGY HH OW1 G IY0 +HOAK HH OW1 K +HOANG HH OW1 NG +HOAR HH AO1 R +HOARD HH AO1 R D +HOARDED HH AO1 R D IH0 D +HOARDING HH AO1 R D IH0 NG +HOARDS HH AO1 R D Z +HOARE HH AO1 R +HOARSE HH AO1 R S +HOARSENESS HH AO1 R S N AH0 S +HOARY HH AO1 R IY0 +HOAX HH OW1 K S +HOAXES HH OW1 K S IH0 Z +HOB HH AA1 B +HOBACK HH OW1 B AE2 K +HOBAN HH OW1 B AH0 N +HOBART HH OW1 B AA2 R T +HOBAUGH HH AA1 B AO0 +HOBBES HH AA1 B IY0 Z +HOBBES(1) HH AA1 B Z +HOBBIE HH AA1 B IY0 +HOBBIES HH AA1 B IY0 Z +HOBBING HH AA1 B IH0 NG +HOBBINS HH AA1 B IH0 N Z +HOBBIT HH AO1 B IH0 T +HOBBITS HH AO1 B IH0 T S +HOBBLE HH AA1 B AH0 L +HOBBLED HH AA1 B AH0 L D +HOBBLES HH AA1 B AH0 L Z +HOBBLING HH AA1 B AH0 L IH0 NG +HOBBLING(1) HH AA1 B L IH0 NG +HOBBS HH AA1 B Z +HOBBY HH AA1 B IY0 +HOBBYIST HH AA1 B IY0 IH0 S T +HOBBYISTS HH AA1 B IY0 IH0 S T S +HOBDAY HH AA1 B D EY2 +HOBDY HH AA1 B D IY0 +HOBEN HH AA1 B AH0 N +HOBERG HH OW1 B ER0 G +HOBERMAN HH OW1 B ER0 M AH0 N +HOBERT HH AA1 B ER0 T +HOBGOOD HH AA1 B G UH2 D +HOBIN HH OW1 B IH0 N +HOBLIT HH AA1 B L IH0 T +HOBNAIL HH AA1 B N EY2 L +HOBNOB HH AA1 B N AA2 B +HOBNOBBING HH AA1 B N AA2 B IH0 NG +HOBO HH OW1 B OW0 +HOBOES HH OW1 B OW0 Z +HOBOKEN HH OW1 B OW0 K AH0 N +HOBS HH AA1 B Z +HOBSBAWM HH AA0 B S B AO1 M +HOBSON HH AA1 B S AH0 N +HOBSON'S HH AA1 B S AH0 N Z +HOC HH AA1 K +HOCEVAR HH OW0 S EY0 V AA1 R +HOCH HH AA1 K +HOCHBERG HH AA1 K B ER0 G +HOCHBRUECKNER HH AA1 K B R AH2 K N ER0 +HOCHENHEIM HH AO1 K AH0 N HH AY2 M +HOCHHALTER HH AA1 K HH AH0 L T ER0 +HOCHHAUSER HH AA1 K HH AW2 Z ER0 +HOCHMAN HH AA1 K M AH0 N +HOCHMUTH HH AA1 K M UW2 TH +HOCHSTATTER HH AA1 K S T AH0 T ER0 +HOCHSTEDLER HH AA1 K S T IH0 D AH0 L ER0 +HOCHSTEDLER(1) HH AA1 K S T EH0 D L ER0 +HOCHSTEIN HH AA1 K S T AY0 N 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IH0 M AH0 +HOEKSTRA HH OW1 K S T R AH0 +HOEL HH OW1 L +HOELL HH OW1 L +HOELLE HH OW1 L +HOELSCHER HH OW1 L SH ER0 +HOELTER HH OW1 L T ER0 +HOELTERHOFF HH OW1 L T ER0 HH AO2 F +HOELTERHOFF'S HH OW1 L T ER0 HH AO2 F S +HOELTING HH OW1 L T IH0 NG +HOELZEL HH OW1 L Z AH0 L +HOELZER HH OW1 L Z ER0 +HOEN HH OW1 N +HOENE HH AA1 IY0 N +HOENER HH OW1 N ER0 +HOENIG HH OW1 N IH0 G +HOEPER HH OW1 P ER0 +HOEPFNER HH OW1 P F N ER0 +HOEPFNER(1) HH OW1 P N ER0 +HOEPNER HH OW1 P N ER0 +HOEPPNER HH OW1 P N ER0 +HOERIG HH AO1 R IH0 G +HOERNER HH AO1 R N ER0 +HOERR HH AO1 R +HOES HH OW1 Z +HOESCH HH OW1 SH +HOESCHEN HH OW1 SH AH0 N +HOESLY HH OW1 S L IY0 +HOEVELER HH OW1 V L ER0 +HOEVET HH OW1 V EH2 T +HOEVET'S HH OW1 V EH2 T S +HOEY HH OW1 IY0 +HOF HH AA1 F +HOFACKER HH AA1 F AH0 K ER0 +HOFBAUER HH AA1 F B AW0 ER0 +HOFER HH OW1 F ER0 +HOFF HH AO1 F +HOFFA HH AO1 F AH0 +HOFFA'S HH AO1 F AH0 Z +HOFFACKER HH AO1 F AH0 K ER0 +HOFFART HH AO1 F AA0 R T +HOFFARTH HH AO1 F AA0 R TH +HOFFECKER HH AO1 F IH0 K ER0 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AA2 R T IY0 +HOGBERG HH AA1 G B ER0 G +HOGE HH OW1 JH +HOGELAND HH AA1 G IH0 L AH0 N D +HOGELAND(1) HH OW1 G L AH0 N D +HOGEN HH AA1 G AH0 N +HOGENSON HH AA1 JH IH0 N S AH0 N +HOGER HH OW1 G ER0 +HOGG HH AA1 G +HOGGAN HH AA1 G AH0 N +HOGGARD HH AA1 G ER0 D +HOGGART HH AA1 G ER0 T +HOGGATT HH AA1 G AH0 T +HOGGE HH AA1 G +HOGGING HH AO1 G IH0 NG +HOGLAND HH AA1 G L AH0 N D +HOGLE HH OW1 G AH0 L +HOGLUND HH AO1 G L AH0 N D +HOGLUND'S HH AO1 G L AH0 N D Z +HOGLUNDS HH AO1 G L AH0 N D Z +HOGNOSE HH AA1 G N OW2 Z +HOGREFE HH AA1 G R IH0 F +HOGS HH AA1 G Z +HOGSED HH OW1 G S T +HOGSETT HH AA1 G S IH0 T +HOGSTON HH AA1 G S T AH0 N +HOGUE HH OW1 G +HOGWARTS HH AA1 G W AO2 R T S +HOGWASH HH AA1 G W AA2 SH +HOGWOOD HH AO1 G W UH2 D +HOH HH OW1 +HOHEISEL HH OW1 AY0 S AH0 L +HOHENBERGER HH OW1 AH0 N B ER0 G ER0 +HOHENSEE HH AA0 HH IH0 N S IY1 +HOHENSTEIN HH OW1 AH0 N S T AY0 N +HOHENSTEIN(1) HH OW1 AH0 N S T IY0 N +HOHL HH OW1 L +HOHLER HH OW1 L ER0 +HOHLT HH OW1 L T +HOHMAN HH OW1 M AH0 N +HOHMANN HH OW1 M AH0 N +HOHN HH AA1 N +HOHNER HH OW1 N ER0 +HOHNSTEIN HH OW1 N S T AY0 N +HOHNSTEIN(1) HH OW1 N S T IY0 N +HOHO HH OW1 HH OW1 +HOHORST HH OW1 HH AO2 R S T +HOHOS HH OW1 HH OW1 Z +HOHUM HH OW1 HH AH1 M +HOI HH OY1 +HOILAND HH OY0 L AE1 N D +HOILMAN HH OY1 L M AH0 N +HOISINGTON HH OY1 Z IH0 NG T AH0 N +HOIST HH OY1 S T +HOISTED HH OY1 S T AH0 D +HOISTED(1) HH OY1 S T IH0 D +HOISTING HH OY1 S T IH0 NG +HOISTS HH OY1 S T S +HOIT HH OY1 T +HOITY HH OY1 T IY0 +HOIUM HH AA1 IY0 AH0 M +HOJNACKI HH AH0 Y N AA1 T S K IY0 +HOK HH AO1 K +HOKANSON HH AA1 K AH0 N S AH0 N +HOKE HH OW1 K +HOKENSON HH AA1 K IH0 N S AH0 N +HOKEY HH OW1 K IY0 +HOKKAIDO HH OW0 K AY1 D OW0 +HOKUM HH OW1 K AH0 M +HOKURIKU HH AA2 K ER0 IY1 K UW2 +HOLA HH OW1 L AH0 +HOLADAY HH OW1 L AH0 D EY0 +HOLAHAN HH AA1 L AH0 HH AE0 N +HOLAN HH OW1 L AH0 N +HOLAWAY HH OW1 L AH0 W EY0 +HOLBEIN HH OW1 L B AY0 N +HOLBEN HH OW1 L B AH0 N +HOLBERG HH OW1 L B ER0 G +HOLBERT HH OW1 L B ER0 T +HOLBROOK HH OW1 L B R UH2 K +HOLBROOKE HH OW1 L B R UH0 K +HOLBROOKE'S HH OW1 L B R UH0 K S +HOLBROOKS HH OW1 L B R UH0 K S +HOLCK HH OW1 L K +HOLCOMB HH OW1 L K AH0 M +HOLCOMBE HH OW1 L K AH0 M +HOLD HH OW1 L D +HOLDA HH OW1 L D AH0 +HOLDAWAY HH OW1 L D AH0 W EY2 +HOLDE HH OW1 L D +HOLDEMAN HH OW1 L D M AH0 N +HOLDEN HH OW1 L D AH0 N +HOLDEN'S HH OW1 L D AH0 N Z +HOLDER HH OW1 L D ER0 +HOLDER'S HH OW1 L D ER0 Z +HOLDERBANK HH OW1 L D ER0 B AE2 NG K +HOLDERBAUM HH OW1 L D ER0 B AW0 M +HOLDERBY HH OW1 L D ER0 B IY0 +HOLDERFIELD HH OW1 L D ER0 F IY2 L D +HOLDERMAN HH OW1 L D ER0 M AH0 N +HOLDERNESS HH OW1 L D ER0 N AH0 S +HOLDERS HH OW1 L D ER0 Z +HOLDERS' HH OW1 L D ER0 Z +HOLDFAST HH OW1 L F AE2 S T +HOLDING HH OW1 L D IH0 NG +HOLDING'S HH OW1 L D IH0 NG Z +HOLDINGS HH OW1 L D IH0 NG Z +HOLDINGS' HH OW1 L D IH0 NG Z +HOLDMAN HH OW1 L D M AH0 N +HOLDORF HH OW1 L D AO0 R F +HOLDOUT HH OW1 L D AW2 T +HOLDOUTS HH OW1 L D AW2 T S +HOLDOVER HH OW1 L D OW2 V ER0 +HOLDOVERS HH OW1 L D OW2 V ER0 Z +HOLDREN HH OW1 L D ER0 AH0 N 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N +HOLLOW HH AA1 L OW0 +HOLLOW'S HH AA1 L OW0 Z +HOLLOWAY HH AA1 L OW0 W EY2 +HOLLOWED HH AA1 L OW0 D +HOLLOWELL HH AA1 L AH0 W EH0 L +HOLLOWING HH AA1 L OW0 IH0 NG +HOLLOWS HH AA1 L OW0 Z +HOLLSTEIN HH AA1 L S T AY0 N +HOLLSTEIN(1) HH AA1 L S T IY0 N +HOLLY HH AA1 L IY0 +HOLLY'S HH AA1 L IY0 Z +HOLLYFIELD HH AA1 L IH0 F IY2 L D +HOLLYFIELD(1) HH AA1 L IY0 F IY2 L D +HOLLYHEAD HH AO1 L IY0 HH EH2 D +HOLLYHOCK HH AA1 L IY0 HH AA2 K +HOLLYHOCKS HH AA1 L IY0 HH AA2 K S +HOLLYWOOD HH AA1 L IY0 W UH2 D +HOLLYWOOD'S HH AA1 L IY0 W UH2 D Z +HOLM HH OW1 M +HOLMAN HH AA1 L M AH0 N +HOLMBERG HH OW1 L M B ER0 G +HOLMDALE HH OW1 L M D EY2 L +HOLME HH OW1 L M +HOLMEN HH AA1 L M EH0 N +HOLMER HH OW1 L M ER0 +HOLMES HH OW1 M Z +HOLMES(1) HH OW1 L M Z +HOLMES'S HH OW1 M Z IH0 Z +HOLMES'S(1) HH OW1 L M Z IH0 Z +HOLMGREN HH OW1 L M G R EH0 N +HOLMIUM HH OW1 L M IY0 AH0 M +HOLMLUND HH OW1 L M L AH0 N D +HOLMQUEST HH OW1 L M K W EH2 S T +HOLMQUIST HH OW1 L M K W IH2 S T +HOLMSTROM HH OW1 L M S T R AH0 M 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HH OW1 P L AH0 S L IY0 +HOPELESSNESS HH OW1 P L AH0 S N AH0 S +HOPES HH OW1 P S +HOPEWELL HH OW1 P W EH2 L +HOPF HH AA1 P F +HOPFENSPERGER HH AA1 P F IH0 N S P ER0 G ER0 +HOPFENSPERGER(1) HH AA1 F IH0 N S P ER0 G ER0 +HOPFER HH AA1 P F ER0 +HOPFINGER HH AA1 P F IH0 NG ER0 +HOPGOOD HH AA1 P G UH2 D +HOPI HH OW1 P IY0 +HOPING HH OW1 P IH0 NG +HOPKE HH OW1 P K +HOPKIN HH AA1 P K IH0 N +HOPKIN'S HH AA1 P K IH0 N Z +HOPKINS HH AA1 P K IH0 N Z +HOPKINS' HH AA1 P K IH0 N Z +HOPKINSON HH AA1 P K IH0 N S AH0 N +HOPKINTON HH AA1 P K IH0 N T AH0 N +HOPKYNS HH AA1 P K IH0 N Z +HOPMAN HH AA1 P M AH0 N +HOPP HH AA1 P +HOPPA HH AA1 P AH0 +HOPPE HH AA1 P +HOPPED HH AA1 P T +HOPPEL HH AA1 P AH0 L +HOPPER HH AA1 P ER0 +HOPPER'S HH AA1 P ER0 Z +HOPPERS HH AA1 P ER0 Z +HOPPERT HH AA1 P ER0 T +HOPPES HH AA1 P S +HOPPING HH AA1 P IH0 NG +HOPPLE HH AA1 P AH0 L +HOPPS HH AA1 P S +HOPPY HH AO1 P IY0 +HOPS HH AA1 P S +HOPSCOTCH HH AA1 P S K AA2 CH +HOPSCOTCHED HH AA1 P S K AA2 CH T +HOPSON HH AA1 P S AH0 N 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IH0 B ER0 +HULLINGER HH AH1 L IH0 NG ER0 +HULLINGER(1) HH AH1 L IH0 N JH ER0 +HULLS HH AH1 L Z +HULLUM HH AH1 L AH0 M +HULME HH AH1 L M +HULON HH Y UW1 L AH0 N +HULON'S HH Y UW1 L AH0 N Z +HULOND HH Y UW1 L AH0 N D +HULOND'S HH Y UW1 L AH0 N D Z +HULS HH AH1 L Z +HULSE HH AH1 L S +HULSEBUS HH AH1 L S IH0 B IH0 S +HULSEY HH AH1 L S IY0 +HULSIZER HH AH1 L S AY2 Z ER0 +HULSLANDER HH AH1 L S L AH0 N D ER0 +HULSMAN HH AH1 L S M AH0 N +HULST HH AH1 L S T +HULT HH AH1 L T +HULT'S HH AH1 L T S +HULTBERG HH AH1 L T B ER0 G +HULTGREN HH AH1 L T G R EH0 N +HULTMAN HH AH1 L T M AH0 N +HULTON HH AH1 L T AH0 N +HULTQUIST HH AH1 L T K W IH0 S T +HULTS HH AH1 L T S +HULTZ HH AH1 L T S +HULVEY HH AH1 L V IY0 +HUM HH AH1 M +HUMAN HH Y UW1 M AH0 N +HUMAN(1) Y UW1 M AH0 N +HUMAN'S HH Y UW1 M AH0 N Z +HUMANA HH Y UW0 M AE1 N AH0 +HUMANA'S HH Y UW0 M AE1 N AH0 Z +HUMANE HH Y UW0 M EY1 N +HUMANELY HH Y UW0 M EY1 N L IY0 +HUMANISM HH Y UW1 M AH0 N IH2 Z AH0 M +HUMANIST HH Y UW1 M AH0 N IH0 S T +HUMANISTIC HH Y UW2 M AH0 N IH1 S T IH0 K +HUMANISTS HH Y UW1 M AH0 N IH0 S T S +HUMANITARIAN HH Y UW2 M AE2 N AH0 T EH1 R IY0 AH0 N +HUMANITARIAN(1) Y UW2 M AE2 N AH0 T EH1 R IY0 AH0 N +HUMANITARIANS HH Y UW2 M AE2 N AH0 T EH1 R IY0 AH0 N Z +HUMANITARIANS(1) Y UW2 M AE2 N AH0 T EH1 R IY0 AH0 N Z +HUMANITIES HH Y UW0 M AE1 N IH0 T IY0 Z +HUMANITIES(1) Y UW0 M AE1 N IH0 T IY0 Z +HUMANITY HH Y UW0 M AE1 N IH0 T IY0 +HUMANITY(1) Y UW0 M AE1 N IH0 T IY0 +HUMANITY'S HH Y UW0 M AE1 N IH0 T IY0 Z +HUMANITY'S(1) Y UW0 M AE1 N IH0 T IY0 Z +HUMANIZE HH Y UW1 M AH0 N AY2 Z +HUMANIZED HH Y UW1 M AH0 N AY2 Z D +HUMANIZES HH Y UW1 M AH0 N AY2 Z IH0 Z +HUMANIZING HH Y UW1 M AH0 N AY2 Z IH0 NG +HUMANKIND HH Y UW1 M AH0 N K AY2 N D +HUMANKIND'S HH Y UW1 M AH0 N K AY2 N D Z +HUMANLY HH Y UW1 M AH0 N L IY0 +HUMANN HH Y UW1 M AH0 N +HUMANNESS HH Y UW1 M AH0 N N AH0 S +HUMANOID HH Y UW1 M AH0 N OY2 D +HUMANS HH Y UW1 M AH0 N Z +HUMANS(1) Y UW1 M AH0 N Z +HUMBARGER HH AH1 M B AA2 R G ER0 +HUMBER HH AH1 M B ER0 +HUMBERT HH AH1 M B ER0 T +HUMBERTO HH AH0 M B ER1 T OW2 +HUMBERTO(1) UW2 M B EH1 R T OW2 +HUMBLE HH AH1 M B AH0 L +HUMBLED HH AH1 M B AH0 L D +HUMBLER HH AH1 M B AH0 L ER0 +HUMBLER(1) HH AH1 M B L ER0 +HUMBLES HH AH1 M B AH0 L Z +HUMBLEST HH AH1 M B AH0 L AH0 S T +HUMBLING HH AH1 M B AH0 L IH0 NG +HUMBLING(1) HH AH1 M B L IH0 NG +HUMBLY HH AH1 M B L IY0 +HUMBOLDT HH AH1 M B OW2 L T +HUMBUG HH AH1 M B AH2 G +HUMBURG HH AH1 M B ER0 G +HUMDINGER HH AH1 M D IH0 NG ER0 +HUMDRUM HH AH1 M D R AH2 M +HUME HH Y UW1 M +HUMENIK HH Y UW1 M IH0 N IH0 K +HUMEROUS HH Y UW1 M ER0 AH0 S +HUMEROUS(1) Y UW1 M ER0 AH0 S +HUMERUS HH Y UW1 M ER0 AH0 S +HUMES HH Y UW1 M Z +HUMFREY HH AH1 M F R IY0 +HUMFRY HH AH1 M F ER0 IY0 +HUMI HH Y UW1 M IY0 +HUMID HH Y UW1 M AH0 D +HUMID(1) HH Y UW1 M IH0 D +HUMID(2) Y UW1 M AH0 D +HUMID(3) Y UW1 M IH0 D +HUMIDIFIER HH Y UW0 M IH1 D AH0 F AY2 ER0 +HUMIDIFIERS HH Y UW0 M IH1 D AH0 F AY2 ER0 Z +HUMIDITY HH Y UW0 M IH1 D AH0 T IY0 +HUMIDITY'S HH Y UW0 M IH1 D AH0 T IY0 Z +HUMIDOR HH Y UW1 M IH0 D AO2 R +HUMILIATE HH Y UW0 M IH1 L IY0 EY2 T +HUMILIATED HH Y UW0 M IH1 L IY0 EY2 T IH0 D +HUMILIATES HH Y UW0 M IH1 L IY0 EY2 T S +HUMILIATING HH Y UW0 M IH1 L IY0 EY2 T IH0 NG +HUMILIATION HH Y UW0 M IH2 L IY0 EY1 SH AH0 N +HUMILIATIONS HH Y UW2 M IH2 L IY0 EY1 SH AH0 N Z +HUMILITY HH Y UW0 M IH1 L IH0 T IY0 +HUMISTON HH Y UW1 M IH0 S T AA0 N +HUMKE HH AH1 M K IY0 +HUML HH AH1 M AH0 L +HUMM HH AH1 M +HUMMEL HH AH1 M AH0 L +HUMMELL HH AH1 M AH0 L +HUMMER HH AH1 M ER0 +HUMMING HH AH1 M IH0 NG +HUMMINGBIRD HH AH1 M IH0 NG B ER2 D +HUMMINGBIRDS HH AH1 M IH0 NG B ER2 D Z +HUMMUS HH UH1 M AH0 S +HUMONGOUS HH Y UW0 M AO1 NG G AH0 S +HUMOR HH Y UW1 M ER0 +HUMORAL HH Y UW1 M ER0 AH0 L +HUMORED HH Y UW1 M ER0 D +HUMORIST HH Y UW1 M ER0 AH0 S T +HUMORIST(1) HH Y UW1 M ER0 IH0 S T +HUMORISTS HH Y UW1 M ER0 IH0 S T S +HUMORLESS HH Y UW1 M ER0 L AH0 S +HUMOROUS HH Y UW1 M ER0 AH0 S +HUMOROUSLY HH Y UW1 M ER0 AH0 S L IY0 +HUMOUR HH Y UW1 M ER0 +HUMP HH AH1 M P +HUMPAL HH AH1 M P AH0 L +HUMPBACK HH AH1 M P B AE2 K +HUMPED HH AH1 M P T +HUMPERT HH AH1 M P ER2 T +HUMPH HH AH1 M F +HUMPHERY HH AH1 M F ER0 IY0 +HUMPHERY(1) HH AH1 M F R IY0 +HUMPHERYS HH AH1 M F ER0 IY0 Z +HUMPHERYS(1) HH AH1 M F R IY0 Z +HUMPHREY HH AH1 M F R IY0 +HUMPHREY'S HH AH1 M F R IY0 Z +HUMPHREYS HH AH1 M F R IY0 Z +HUMPHRIES HH AH1 M F ER0 IY0 Z +HUMPHRY HH AH1 M F R IY0 +HUMPTY HH AH1 M P T IY0 +HUMS HH AH1 M Z +HUMULIN HH Y UW2 M Y UW1 L IH0 N +HUMUS HH Y UW1 M AH0 S +HUMVEE HH AH1 M V IY2 +HUMVEE'S HH AH1 M V IY2 Z +HUMVEES HH AH1 M V IY2 Z +HUN HH AH1 N +HUNAN HH UW1 N AA0 N +HUNCH HH AH1 N CH +HUNCHBACK HH AH1 N CH B AE2 K +HUNCHED HH AH1 N CH T +HUNCHES HH AH1 N CH IH0 Z +HUNCHINE HH AH0 CH IY1 N +HUND HH AH1 N D +HUNDAI HH AH1 N D EY0 +HUNDERTMARK HH AH1 N D ER0 T M AA2 R K +HUNDLEY HH AH1 N D L IY0 +HUNDRED HH AH1 N D R AH0 D +HUNDRED(1) HH AH1 N D R IH0 D +HUNDRED(2) HH AH1 N ER0 D +HUNDRED(3) HH AH1 N D ER0 D +HUNDRED'S HH AH1 N D R IH0 D Z +HUNDREDS HH AH1 N D R AH0 D Z +HUNDREDS(1) HH AH1 N D ER0 D Z +HUNDREDS(2) HH AH1 N ER0 D Z +HUNDREDTH HH AH1 N D R AH0 D TH +HUNDREDTHS HH AH1 N D R AH0 D TH S +HUNDREDWEIGHT HH AH1 N D R AH0 D W EY2 T +HUNDT HH AH1 N T +HUNEKE HH AH1 N IH0 K +HUNEYCUTT HH AH1 N IY0 K AH0 T +HUNG HH AH1 NG +HUNGARIAN HH AH0 NG G EH1 R IY0 AH0 N +HUNGARIANS HH AH0 NG G EH1 R IY0 AH0 N Z +HUNGARY HH AH1 NG G ER0 IY0 +HUNGARY'S HH AH1 NG G ER0 IY0 Z +HUNGATE HH AH1 NG EY0 T +HUNGER HH AH1 NG G ER0 +HUNGERFORD HH AH1 NG G ER0 F ER0 D +HUNGERFORDS HH AH1 NG G ER0 F ER0 D Z +HUNGERING HH AH1 NG G ER0 IH0 NG +HUNGRIER HH AH1 NG G R IY0 ER0 +HUNGRILY HH AH1 NG G R AH0 L IY0 +HUNGRY HH AH1 NG G R IY0 +HUNK HH AH1 NG K +HUNKE HH AH1 NG K +HUNKELE HH AH1 NG K AH0 L +HUNKER HH AH1 NG K ER0 +HUNKERED HH AH1 NG K ER0 D +HUNKERING HH AH1 NG K ER0 IH0 NG +HUNKINS HH AH1 NG K IH0 N Z +HUNKS HH AH1 NG K S +HUNKY HH AH1 NG K IY0 +HUNLEY HH AH1 N L IY0 +HUNN HH AH1 N +HUNNELL HH AH1 N AH0 L +HUNNEWELL HH AH1 N IH0 W EH0 L +HUNNICUTT HH AH1 N IH0 K AH0 T +HUNSAKER HH AH1 N S AH0 K ER0 +HUNSBERGER HH AH1 N S B ER0 G ER0 +HUNSICKER HH AH1 N S IH0 K ER0 +HUNSINGER HH AH1 N S IH0 NG ER0 +HUNSLEY HH AH1 N S L IY0 +HUNSUCKER HH AH1 N S AH0 K ER0 +HUNT HH AH1 N T +HUNT'S HH AH1 N T S +HUNTCO HH AH1 N T K OW0 +HUNTE HH AH1 N T +HUNTED HH AH1 N T AH0 D +HUNTED(1) HH AH1 N T IH0 D +HUNTED(2) HH AH1 N AH0 D +HUNTED(3) HH AH1 N IH0 D +HUNTER HH AH1 N T ER0 +HUNTER'S HH AH1 N T ER0 Z +HUNTERS HH AH1 N T ER0 Z +HUNTING HH AH1 N T IH0 NG +HUNTINGDON HH AH1 N T IH0 NG D IH0 N +HUNTINGTON HH AH1 N T IH0 NG T AH0 N +HUNTINGTON'S HH AH1 N T IH0 NG T AH0 N Z +HUNTLEY HH AH1 N T L IY0 +HUNTLY HH AH1 N T L IY0 +HUNTON HH AH1 N T AH0 N +HUNTOON HH AH0 N T UW1 N +HUNTRESS HH AH1 N T R IH0 S +HUNTS HH AH1 N T S +HUNTS' HH AH1 N T S +HUNTSINGER HH AH1 N T S IH0 N JH ER0 +HUNTSMAN HH AH1 N T S M AH0 N +HUNTSVILLE HH AH1 N T S V IH0 L +HUNTWAY HH AH1 N T W EY2 +HUNTZINGER HH AH1 N T Z IH0 NG ER0 +HUNZA HH AH1 N Z AH0 +HUNZEKER HH AH1 N Z IH0 K ER0 +HUNZIKER HH AH1 N Z IH0 K ER0 +HUOT HH Y UW1 AH0 T +HUPE HH Y UW1 P +HUPFER HH AH1 P F ER0 +HUPP HH AH1 P +HUPPERT HH AH1 P ER0 T +HUR HH ER1 +HURCO HH ER1 K OW2 +HURD HH ER1 D +HURDLE HH ER1 D AH0 L +HURDLER HH ER1 D AH0 L ER0 +HURDLER(1) HH ER1 D L ER0 +HURDLES HH ER1 D AH0 L Z +HURDLING HH ER1 D AH0 L IH0 NG +HURDLING(1) HH ER1 D L IH0 NG +HURDMAN HH ER1 D M AH0 N +HURFORD HH ER1 F ER0 D +HURL HH ER1 L +HURLBERT HH ER1 L B ER0 T +HURLBURT HH ER1 L B ER0 T +HURLBUT HH ER1 L B AH0 T +HURLBUTT HH ER1 L B AH0 T +HURLED HH ER1 L D +HURLESS HH ER1 L AH0 S +HURLEY HH ER1 L IY0 +HURLING HH ER1 L IH0 NG +HURLOCK HH ER1 L AH0 K +HURLY HH ER1 L IY0 +HURM HH ER1 M +HURN HH ER1 N +HURNEY HH ER1 N IY0 +HURON HH Y UW1 R AA2 N +HURON(1) HH Y UH1 R AA2 N +HURRAH HH UH0 R AA1 +HURRAY HH AH0 R EY1 +HURRELL HH AO1 R AH0 L +HURRI HH ER1 IY0 +HURRICANE HH ER1 AH0 K EY2 N +HURRICANE(1) HH AH1 R AH0 K EY2 N Z +HURRICANE'S HH ER1 AH0 K EY2 N Z +HURRICANES HH ER1 AH0 K EY2 N Z +HURRIED HH ER1 IY0 D +HURRIEDLY HH ER1 IY0 D L IY0 +HURRIES HH ER1 IY0 Z +HURRY HH ER1 IY0 +HURRYING HH ER1 IY0 IH0 NG +HURSEY HH ER1 S IY0 +HURSH HH ER1 SH +HURST HH ER1 S T +HURSTON HH ER1 S T AH0 N +HURT HH ER1 T +HURTA HH ER1 T AH0 +HURTADO HH ER0 T AA1 D OW0 +HURTEAU HH ER0 T OW1 +HURTFUL HH ER1 T F AH0 L +HURTIG HH ER1 T IH0 G +HURTING HH ER1 T IH0 NG +HURTLE HH ER1 T AH0 L +HURTLING HH ER1 T L IH0 NG +HURTS HH ER1 T S +HURTT HH ER1 T +HURTUBISE HH ER1 T AH0 B AY0 Z +HURVEY HH ER1 V IY0 +HURVITZ HH ER1 V IH0 T S +HURWITZ HH ER1 W IH0 T S +HUSAIN HH AH1 S AY0 N +HUSAK HH UW1 S AH0 K +HUSAR HH UW1 S ER0 +HUSBAND HH AH1 Z B AH0 N D +HUSBAND'S HH AH1 Z B AH0 N D Z +HUSBANDRY HH AH1 Z B AH0 N D R IY0 +HUSBANDS HH AH1 Z B AH0 N D Z +HUSBANDS' HH AH1 S B AH0 N D Z +HUSBY HH AH1 S B IY0 +HUSCHKA HH AH1 SH K AH0 +HUSE HH Y UW1 Z +HUSEBY HH AH1 S IH0 B IY0 +HUSEMAN HH UW1 S M AH0 N +HUSEN HH UW1 S AH0 N +HUSER HH Y UW1 Z ER0 +HUSH HH AH1 SH +HUSHED HH AH1 SH T +HUSIC HH Y UW1 Z IH0 K +HUSK HH AH1 S K +HUSKA HH AH1 S K AH0 +HUSKEY HH AH1 S K IY0 +HUSKINS HH AH1 S K IH0 N Z +HUSKS HH AH1 S K S +HUSKY HH AH1 S K IY0 +HUSKY'S HH AH1 S K IY0 Z +HUSMAN HH AH1 S M AH0 N +HUSMANN HH AH1 S M AH0 N +HUSON HH UW1 S AH0 N +HUSS HH AH1 S +HUSSAIN HH UW0 S EY1 N +HUSSAR HH AH1 S ER0 +HUSSEIN HH UW0 S EY1 N +HUSSEIN'S HH UW0 S EY1 N Z +HUSSEINI HH Y UW0 S EY1 N IY0 +HUSSEINI(1) HH UW0 S EY1 N IY0 +HUSSER HH AH1 S ER0 +HUSSEY HH AH1 S IY0 +HUSSITE HH AH1 S AY2 T +HUSSMAN HH AH1 S M AH0 N +HUSSON HH AH1 S AH0 N +HUSSONG HH AH1 S AO2 NG +HUSSY HH AH1 S IY0 +HUST HH AH1 S T +HUSTAD HH AH1 S T AH0 D +HUSTEAD HH AH1 S T EH0 D +HUSTED HH AH1 S T IH0 D +HUSTER HH AH1 S T ER0 +HUSTINGS HH AH1 S T IH0 NG Z +HUSTLE HH AH1 S AH0 L +HUSTLED HH AH1 S AH0 L D +HUSTLER HH AH1 S AH0 L ER0 +HUSTLER(1) HH AH1 S L ER0 +HUSTLERS HH AH1 S AH0 L ER0 Z +HUSTLERS(1) HH AH1 S L ER0 Z +HUSTLES HH AH1 S AH0 L Z +HUSTLING HH AH1 S AH0 L IH0 NG +HUSTLING(1) HH AH1 S L IH0 NG +HUSTON HH AH1 S T AH0 N +HUT HH AH1 T +HUT'S HH AH1 T S +HUTA HH UW1 T AH0 +HUTCH HH AH1 CH +HUTCHCRAFT HH AH1 CH K R AE2 F T +HUTCHENS HH AH1 CH AH0 N Z +HUTCHEON HH AH1 CH IY0 AH0 N +HUTCHERSON HH AH1 CH ER0 S AH0 N +HUTCHESON HH AH1 CH IH0 S AH0 N +HUTCHINGS HH AH1 CH IH0 NG Z +HUTCHINS HH AH1 T CH IH2 N Z +HUTCHINSON HH AH1 CH IH0 N S AH0 N +HUTCHISON HH AH1 CH IH0 S AH0 N +HUTCHISON'S HH AH1 CH IH0 S AH0 N Z +HUTH HH UW1 TH +HUTMACHER HH AH1 T M AH0 K ER0 +HUTNICK HH AH1 T N IH0 K +HUTO HH UW1 T OW2 +HUTS HH AH1 T S +HUTSELL HH AH1 T S AH0 L +HUTSON HH AH1 T S AH0 N +HUTT HH AH1 T +HUTTER HH AH1 T ER0 +HUTTNER HH AH1 T N ER0 +HUTTO HH UW1 T OW0 +HUTTON HH AH1 T AH0 N +HUTTON'S HH AH1 T AH0 N Z +HUTU HH UW1 T UW2 +HUTU'S HH UW1 T UW2 Z +HUTUS HH UW1 T UW2 Z +HUTZEL HH AH1 T Z AH0 L +HUTZELL HH AH1 T Z AH0 L +HUTZELMAN HH AH1 T S AH0 L M AH0 N +HUTZLER HH AH1 T S L ER0 +HUVAL HH UW0 V AE1 L +HUWE HH UW1 W +HUX HH AH1 K S +HUXFORD HH AH1 K S F ER0 D +HUXLEY HH AH1 K S L IY0 +HUXTABLE HH AH1 K S T AH0 B AH0 L +HUXTABLES HH AH1 K S T AH0 B AH0 L Z +HUYCK HH AY1 K +HUYETT HH AY1 IH0 T +HUYLER HH AY1 L ER0 +HUYNH HH AY1 N +HUYSER HH AY1 S ER0 +HUZZAH HH UH2 Z AA1 +HWA HH W AA1 +HWAN HH W AA1 N +HWAN'S HH W AA1 N Z +HWANG HH W AE1 NG +HWANG(1) HH W AA1 NG +HWANG-HO HH W AE1 NG HH OW1 +HWANG-HO(1) HH W AA1 NG HH OW1 +HWE HH W EY1 +HY HH AY1 +HYACINTH HH AY1 AH0 S IH2 N TH +HYACINTHA HH AY2 AH0 S IH1 N TH AH0 +HYACINTHE HH AY1 AH0 S IH0 N TH +HYACINTHIA HH AY2 AH0 S IH1 N TH IY0 AH0 +HYACINTHIE HH AY1 AH0 S IH2 N TH IY0 +HYACINTHS HH AY1 AH0 S IH0 N TH S +HYADES HH AY1 AH0 D IY2 Z +HYAKUTAKE HH AY1 AH0 K UW0 T AA2 K IY0 +HYAKUTAKE(1) HH AY1 AH0 K Y UW0 T AA2 K IY0 +HYALURONIC HH AY2 AH0 L ER0 AA1 N IH0 K +HYAMS HH AY1 AH0 M Z +HYANNIS HH AY0 AE1 N IH0 S +HYANNISPORT HH AY0 AE1 N IH0 S P AO0 R T +HYATT HH AY1 AH0 T +HYATT'S HH AY1 AH0 T S +HYBL HH IH1 B AH0 L +HYBL'S HH IH1 B AH0 L Z +HYBRID HH AY1 B R AH0 D +HYBRID(1) HH AY1 B R IH0 D +HYBRIDIZATION HH AY2 B R AH0 D AH0 Z EY1 SH AH0 N +HYBRIDIZE HH AY1 B R AH0 D AY2 Z +HYBRIDS HH AY1 B R AH0 D Z +HYBRIENKO HH AY1 B R IY0 EH2 N K OW0 +HYBRITECH HH AY1 B R IH0 T EH2 K +HYCHE HH AY1 CH +HYCOR HH AY1 K AO2 R +HYCROFT HH AY1 K R AO2 F T +HYDE HH AY1 D +HYDE'S HH AY1 D Z +HYDEA HH AY2 D IY1 AH0 +HYDEA(1) HH AY2 D EY1 AH0 +HYDEIA HH AY1 D EY1 AH0 +HYDEN HH AY1 D AH0 N +HYDER HH AY1 D ER0 +HYDERABAD HH AY0 D EH1 R AH0 B AE2 D +HYDERABAD(1) HH AY1 D ER0 AH0 B AE2 D +HYDOCK HH AY1 D AH0 K +HYDRA HH AY1 D R AH0 +HYDRANT HH AY1 D R AH0 N T +HYDRANTS HH AY1 D R AH0 N T S +HYDRAS HH AY1 D R AH0 Z +HYDRATE HH AY1 D R EY2 T +HYDRATED HH AY1 D R EY2 T AH0 D +HYDRATES HH AY1 D R EY2 T S +HYDRATION HH AY0 D R EY1 SH AH0 N +HYDRAULIC HH AY0 D R AO1 L IH0 K +HYDRAULICS HH AY0 D R AO1 L IH0 K S +HYDRAZINE HH AY1 D R AH0 Z IY2 N +HYDRICK HH IH1 D R IH0 K +HYDRIDE HH AY1 D R AY2 D +HYDRO HH AY1 D R OW2 +HYDRO'S HH AY1 D R OW2 Z +HYDROCARBON HH AY2 D R OW0 K AA1 R B AH0 N +HYDROCARBONS HH AY2 D R OW0 K AA1 R B AH0 N Z +HYDROCEPHALIC HH AY2 D R OW0 S EH0 F AA1 L IH0 K +HYDROCEPHALUS HH AY2 D R OW0 S EH1 F AH0 L AH0 S +HYDROELECTRIC HH AY2 D R OW0 IH0 L EH1 K T R IH0 K +HYDROENCEPHALUS HH AY2 D R OW0 AH0 N S EH1 F AH0 L AH0 S +HYDROFOIL HH AY1 D R AH0 F OY2 L +HYDROGEN HH AY1 D R AH0 JH AH0 N +HYDROGENATE HH AY1 D R AH0 JH AH0 N EY2 T +HYDROGENATED HH AY1 D R AH0 JH AH0 N EY2 T IH0 D +HYDROGENATED(1) HH AY0 D R AA1 JH AH0 N EY2 T IH0 D +HYDROGENATES HH AY1 D R AH0 JH AH0 N EY2 T S +HYDROGENATING HH AY1 D R AH0 JH AH0 N EY2 T IH0 NG +HYDROGENATION HH AY2 D R AA2 JH AH0 N EY1 SH AH0 N +HYDROGENS HH AY1 D R AH0 JH AH0 N Z +HYDROGRAPHIC HH AY2 D R AH0 G R AE1 F IH0 K +HYDROLYSIS HH AY0 D R AA1 L AH0 S AH0 S +HYDROLYZE HH AY1 D R AH0 L AY2 Z +HYDROLYZED HH AY1 D R AH0 L AY2 Z D +HYDROLYZING HH AY1 D R AH0 L AY2 Z IH0 NG +HYDROMETER HH AY0 D R AA1 M AH0 T ER0 +HYDRON HH AY1 D R AH0 N +HYDROPHILIC HH AY2 D R AH0 F IH1 L IH0 K +HYDROPIC HH AY2 D R AO1 P IH0 K +HYDROPONIC HH AY2 D R AH0 P AA1 N IH0 K +HYDROPOWER HH AY1 D R OW0 P AW2 R +HYDROSOL HH AY1 D R AH0 S AA2 L +HYDROSULFIDE HH AY2 D R OW0 S AH1 L F AY2 D +HYDROTHERAPY HH AY2 D R OW0 TH EH1 R AH0 P IY0 +HYDROTHERMAL HH AY2 D R OW0 TH ER1 M AH0 L +HYDROUS HH AY1 D R AH0 S +HYDROX HH AY1 D R AO2 K S +HYDROXIDE HH AY0 D R AA1 K S AY0 D +HYDROXIDES HH AY0 D R AA1 K S AY0 D Z +HYDROXY HH AY2 D R AO1 K S IY0 +HYDSTRA HH AY1 D S T R AH0 +HYE HH AY0 +HYENA HH AY0 IY1 N AH0 +HYENAS HH AY0 IY1 N AH0 Z +HYER HH AY1 ER0 +HYERS HH AY1 ER0 Z +HYGEIA HH AY2 JH EY1 AH0 +HYGIENE HH AY1 JH IY2 N +HYGIENIST HH AY2 G IY1 N IH0 S T +HYGIENIST(1) HH AY2 G EH1 N IH0 S T +HYGIENISTS HH AY2 G IY1 N IH0 S T S +HYGIENISTS(1) HH AY2 G IY1 N IH0 S +HYGIENISTS(2) HH AY2 G EH1 N IH0 S T S +HYGIENISTS(3) HH AY2 G EH1 N IH0 S +HYGROMETER HH AY0 G R AA1 M AH0 T ER0 +HYKES HH AY1 K S +HYLAND HH AY1 L AH0 N D +HYLE HH AY1 L +HYLER HH AY1 L ER0 +HYLSA HH AY1 L S AH0 +HYLTON HH IH1 L T AH0 N +HYMAN HH AY1 M AH0 N +HYMANS HH AY1 M AH0 N Z +HYMAS HH AY1 M AH0 Z +HYMEL HH AY1 M AH0 L +HYMEN HH AY1 M AH0 N +HYMENEAL HH IH2 M AH0 N IY1 AH0 L +HYMER HH AY1 M ER0 +HYMES HH AY1 M Z +HYMIE HH AY1 M IY0 +HYMIES HH AY1 M IY0 Z +HYMN HH IH1 M +HYMNAL HH IH1 M N AH0 L +HYMNALS HH IH1 M N AH0 L Z +HYMNOLOGY HH IH0 M N AA1 L AH0 JH IY0 +HYMNS HH IH1 M Z +HYMOWITZ HH IH1 M AH0 W IH0 T S +HYMOWITZ(1) HH AY1 M AH0 W IH0 T S +HYND HH IH1 N D +HYNDMAN HH IH1 N D M AH0 N +HYNDS HH IH1 N D Z +HYNEK HH AY1 N IH0 K +HYNES HH AY1 N Z +HYNES'S HH AY1 N Z IH0 Z +HYNSON HH IH1 N S AH0 N +HYOGO HH Y OW1 G OW0 +HYOTAN HH Y OW1 T AE2 N +HYPE HH AY1 P +HYPED HH AY1 P T +HYPER HH AY1 P ER0 +HYPERACTIVE HH AY2 P ER0 AE1 K T IH0 V +HYPERACTIVITY HH AY2 P ER0 AE0 K T IH1 V IH0 T IY0 +HYPERBARIC HH AY0 P ER0 B AA1 R IH0 K +HYPERBARIC(1) HH AY0 P ER1 B AE1 R IH0 K +HYPERBOLA HH AY0 P ER1 B AH0 L AH0 +HYPERBOLE HH AY0 P ER1 B AH0 L IY2 +HYPERBOLIC HH AY2 P ER0 B AA1 L IH0 K +HYPERBOREAN HH AY2 P ER0 B AO1 R IY0 AH0 N +HYPERCARD HH AY2 P ER0 K AA1 R D +HYPERCHROMATIC HH AY2 P ER0 K R OW0 M AE1 T IH0 K +HYPERCRITICAL HH AY2 P ER0 K R IH1 T IH0 K AH0 L +HYPERDRIVE HH AY1 P ER0 D R AY2 V +HYPERINFLATION HH AY2 P ER0 IH0 N F L EY1 SH AH0 N +HYPERION HH AY0 P IH1 R IY0 AH0 N +HYPERKINETIC HH AY2 P ER0 K IH0 N EH1 T IH0 K +HYPERLINK HH AY1 P ER0 L IH0 NG K +HYPERLINKS HH AY1 P ER0 L IH0 NG K S +HYPERMARKET HH AY1 P ER0 M AA2 R K IH0 T +HYPERMARKETS HH AY1 P ER0 M AA2 R K IH0 T S +HYPEROPIA HH AY2 P ER0 OW1 P IY2 AA0 +HYPERPLASIA HH AY2 P ER0 P L EY1 ZH IY2 AA0 +HYPERSENSITIVE HH AY2 P ER0 S EH1 N S IH0 T IH0 V +HYPERSENSITIVITY HH AY2 P ER0 S EH1 N S IH0 T IH2 V IH0 T IY2 +HYPERSONIC HH AY2 P ER0 S AA1 N IH0 K +HYPERSPACE HH AY2 P ER0 S P EY1 S +HYPERTENSION HH AY2 P ER0 T EH1 N SH AH0 N +HYPERTENSIVE HH AY2 P ER0 T EH1 N S IH0 V +HYPERTEXT HH AY1 P ER0 T EH2 K S T +HYPERTONIC HH AY2 P ER0 T AA1 N IH0 K +HYPERTROPHIC HH AY2 P ER0 T R OW1 F IH0 K +HYPERTROPHY HH AY1 P ER0 T R OW2 F IY0 +HYPES HH AY1 P S +HYPHAE HH AY1 F IY2 +HYPHEN HH AY1 F AH0 N +HYPHENATE HH AY1 F AH0 N EY2 T +HYPHENATED HH AY1 F AH0 N EY2 T IH0 D +HYPHENATES HH AY1 F AH0 N EY2 T S +HYPHENATING HH AY1 F AH0 N EY2 T IH0 NG +HYPHENATION HH AY2 F AH0 N EY1 SH AH0 N +HYPING HH AY1 P IH0 NG +HYPNOSIS HH IH0 P N OW1 S AH0 S +HYPNOTIC HH IH0 P N AA1 T IH0 K +HYPNOTICS HH IH0 P N AA1 T IH0 K S +HYPNOTISM HH IH1 P N AH0 T IH2 Z AH0 M +HYPNOTISM'S HH IH1 P N AH0 T IH2 Z AH0 M Z +HYPNOTIST HH IH1 P N AH0 T IH0 S T +HYPNOTISTS HH IH1 P N AH0 T IH0 S T S +HYPNOTIZE HH IH1 P N AH0 T AY2 Z +HYPNOTIZED HH IH1 P N AH0 T AY2 Z D +HYPNOTIZES HH IH1 P N AH0 T AY2 Z AH0 Z +HYPO HH AY1 P OW0 +HYPOCHONDRIA HH AY2 P AH0 K AA1 N D R IY0 AH0 +HYPOCHONDRIAC HH AY2 P AH0 K AA1 N D R IY0 AE0 K +HYPOCRISY HH IH0 P AA1 K R AH0 S IY0 +HYPOCRITE HH IH1 P AH0 K R IH2 T +HYPOCRITES HH IH1 P AH0 K R IH2 T S +HYPOCRITICAL HH IH2 P AH0 K R IH1 T IH0 K AH0 L +HYPODERMIC HH AY2 P AH0 D ER1 M IH0 K +HYPOGLYCEMIA HH AY2 P OW0 G L AY0 S IY1 M IY0 AH0 +HYPOGLYCEMIC HH AY2 P OW0 G L AY0 S IY1 M IH0 K +HYPOLITE HH AY1 P AH0 L AY0 T +HYPONEX HH AY1 P OW0 N EH2 K S +HYPOTENSION HH AY2 P OW0 T EH1 N SH AH0 N +HYPOTHALAMIC HH AY2 P OW0 TH AA0 L AE1 M IH0 K +HYPOTHALAMUS HH AY2 P OW0 TH AA1 L AH0 M AH0 S +HYPOTHEKEN HH AY2 P AA1 TH AH0 K AH0 N +HYPOTHERMIA HH AY2 P AH0 TH ER1 M IY0 AH0 +HYPOTHESES HH AY0 P AA1 TH AH0 S IY2 Z +HYPOTHESIS HH AY0 P AA1 TH AH0 S AH0 S +HYPOTHESIZE HH AY0 P AA1 TH AH0 S AY2 Z +HYPOTHESIZED HH AY0 P AA1 TH AH0 S AY2 Z D +HYPOTHETICAL HH AY2 P AH0 TH EH1 T AH0 K AH0 L +HYPOTHETICAL(1) HH AY2 P AH0 TH EH1 T IH0 K AH0 L +HYPOTHETICALLY HH AY2 P AH0 TH EH1 T IH0 K L IY0 +HYPOTHETICALS HH AY2 P AH0 TH EH1 T AH0 K AH0 L Z +HYPOXIA HH AY0 P AA1 K S IY0 AH0 +HYRAXES HH AY1 R AE0 K S AH0 Z +HYRE HH AY1 R +HYSELL HH AY1 S AH0 L +HYSER HH AY1 Z ER0 +HYSLOP HH AY1 S L AH0 P +HYSON HH AY1 S AH0 N +HYSONG HH AY1 S AO2 NG +HYSSOP HH IH1 S AH0 P +HYSTER HH IH1 S T ER0 +HYSTERECTOMIES HH IH2 S T ER0 EH1 K T AH0 M IY0 +HYSTERECTOMY HH IH2 S T ER0 EH1 K T AH0 M IY0 +HYSTERIA HH IH0 S T EH1 R IY0 AH0 +HYSTERIC HH IH2 S T EH1 R IH0 K +HYSTERICAL HH IH0 S T EH1 R IH0 K AH0 L +HYSTERICALLY HH IH2 S T EH1 R IH0 K L IY0 +HYSTERICS HH IH2 S T EH1 R IH0 K S +HYUN HH AY1 AH0 N +HYUN(1) HH Y AH1 N +HYUNDAE HH Y AH1 N D EY2 +HYUNDAI HH Y AH1 N D EY2 +HYUNDAI(1) HH AH1 N D EY2 +HYUNDAI'S HH AH1 N D EY2 Z +HYUNDAIS HH Y AH1 N D EY2 Z +HYWELL HH AY1 W EH0 L +HZ HH ER1 T Z +I AY1 +I'D AY1 D +I'ERS AY1 ER0 Z +I'LL AY1 L +I'M AY1 M +I'M(1) AH0 M +I'S AY1 Z +I'VE AY1 V +I. 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IH1 M P IH0 SH +IMPLACABLE IH2 M P L AE1 K AH0 B AH0 L +IMPLANT IH2 M P L AE1 N T +IMPLANT(1) IH1 M P L AE2 N T +IMPLANTABLE IH1 M P L AE2 N T AH0 B AH0 L +IMPLANTATION IH2 M P L AE0 N T EY1 SH AH0 N +IMPLANTED IH2 M P L AE1 N T IH0 D +IMPLANTING IH2 M P L AE1 N T IH0 NG +IMPLANTS IH2 M P L AE1 N T S +IMPLANTS(1) IH1 M P L AE2 N T S +IMPLAUSIBLE IH2 M P L AO1 Z AH0 B AH0 L +IMPLAUSIBLY IH2 M P L AO1 Z AH0 B L IY0 +IMPLEMENT IH1 M P L AH0 M AH0 N T +IMPLEMENTATION IH2 M P L AH0 M EH0 N T EY1 SH AH0 N +IMPLEMENTATIONS IH2 M P L AH0 M EH0 N T EY1 SH AH0 N Z +IMPLEMENTED IH1 M P L AH0 M EH2 N T AH0 D +IMPLEMENTED(1) IH1 M P L AH0 M EH2 N AH0 D +IMPLEMENTING IH1 M P L AH0 M EH2 N T IH0 NG +IMPLEMENTING(1) IH1 M P L AH0 M EH2 N IH0 NG +IMPLEMENTS IH1 M P L AH0 M AH0 N T S +IMPLICATE IH1 M P L IH0 K EY2 T +IMPLICATED IH1 M P L IH0 K EY2 T IH0 D +IMPLICATES IH1 M P L IH0 K EY2 T S +IMPLICATING IH1 M P L IH0 K EY2 T IH0 NG +IMPLICATION IH2 M P L AH0 K EY1 SH AH0 N +IMPLICATIONS IH2 M P L AH0 K EY1 SH AH0 N Z +IMPLICIT IH2 M P L IH1 S AH0 T +IMPLICITLY IH2 M P L IH1 S AH0 T L IY0 +IMPLIED IH2 M P L AY1 D +IMPLIES IH2 M P L AY1 Z +IMPLODE IH2 M P L OW1 D +IMPLODED IH2 M P L OW1 D IH0 D +IMPLODES IH2 M P L OW1 D Z +IMPLODING IH2 M P L OW1 D IH0 NG +IMPLORE IH2 M P L AO1 R +IMPLORED IH2 M P L AO1 R D +IMPLORES IH2 M P L AO1 R Z +IMPLORING IH2 M P L AO1 R IH0 NG +IMPLOSION IH2 M P L OW1 ZH AH0 N +IMPLY IH2 M P L AY1 +IMPLYING IH2 M P L AY1 IH0 NG +IMPOLITE IH2 M P AH0 L AY1 T +IMPOLITIC IH2 M P AO0 L IH1 T IH2 K +IMPONDERABLE IH2 M P AA1 N D ER0 AH0 B AH0 L +IMPONDERABLES IH2 M P AA1 N D ER0 AH0 B AH0 L Z +IMPORT IH2 M P AO1 R T +IMPORT(1) IH1 M P AO2 R T +IMPORTANCE IH2 M P AO1 R T AH0 N S +IMPORTANT IH2 M P AO1 R T AH0 N T +IMPORTANTLY IH2 M P AO1 R T AH0 N T L IY0 +IMPORTATION IH2 M P AO0 R T EY1 SH AH0 N +IMPORTED IH2 M P AO1 R T IH0 D +IMPORTER IH2 M P AO1 R T ER0 +IMPORTERS IH2 M P AO1 R T ER0 Z +IMPORTERS' IH2 M P AO1 R T ER0 Z +IMPORTING IH2 M P AO1 R T IH0 NG +IMPORTS IH2 M P AO1 R T S +IMPORTS(1) IH1 M P AO2 R T S +IMPORTS' IH1 M P AO0 R T S +IMPOSE IH2 M P OW1 Z +IMPOSED IH2 M P OW1 Z D +IMPOSES IH2 M P OW1 Z IH0 Z +IMPOSING IH2 M P OW1 Z IH0 NG +IMPOSITION IH2 M P AH0 Z IH1 SH AH0 N +IMPOSSIBILITY IH2 M P AO2 S IH0 B IH1 L IH0 T IY0 +IMPOSSIBLE IH2 M P AA1 S AH0 B AH0 L +IMPOSSIBLE'S IH2 M P AA1 S AH0 B AH0 L Z +IMPOSSIBLY IH2 M P AA1 S AH0 B L IY0 +IMPOSTER IH2 M P AO1 S T ER0 +IMPOSTOR IH2 M P AO1 S T ER0 +IMPOSTORS IH2 M P AO1 S T ER0 Z +IMPOTENCE IH1 M P AH0 T AH0 N S +IMPOTENT IH1 M P AH0 T AH0 N T +IMPOUND IH2 M P AW1 N D +IMPOUNDED IH2 M P AW1 N D IH0 D +IMPOUNDING IH2 M P AW1 N D IH0 NG +IMPOUNDMENT IH2 M P AW1 N D M AH0 N T +IMPOUNDMENTS IH2 M P AW1 N D M AH0 N T S +IMPOUNDS IH2 M P AW1 N D Z +IMPOVERISH IH2 M P AA1 V R IH0 SH +IMPOVERISHED IH2 M P AA1 V R IH0 SH T +IMPOVERISHES IH2 M P AA1 V R IH0 SH AH0 Z +IMPOVERISHING IH2 M P AA1 V R IH0 SH IH0 NG +IMPOVERISHMENT IH2 M P AA1 V R IH0 SH M AH0 N T +IMPRACTICABLE IH2 M P R AE1 K T IH0 K AH0 B AH0 L +IMPRACTICAL IH2 M P R AE1 K T AH0 K AH0 L +IMPRACTICAL(1) IH2 M P R AE1 K T IH0 K AH0 L +IMPRECISE IH1 M P R AH0 S AY2 S +IMPREGNABLE IH2 M P R EH1 G N AH0 B AH0 L +IMPREGNATE IH2 M P R EH1 G N EY2 T +IMPREGNATED IH2 M P R EH1 G N EY2 T AH0 D +IMPREGNATES IH2 M P R EH1 G N EY2 T S +IMPREGNATING IH2 M P R EH1 G N EY2 T IH0 NG +IMPREGNATION IH2 M P R EH1 G N EY1 SH AH0 N +IMPRESARIO IH2 M P R IH0 S AA1 R IY0 OW2 +IMPRESS IH2 M P R EH1 S +IMPRESS(1) IH1 M P R EH2 S +IMPRESSED IH2 M P R EH1 S T +IMPRESSES IH2 M P R EH1 S IH0 Z +IMPRESSING IH2 M P R EH1 S IH0 NG +IMPRESSION IH2 M P R EH1 SH AH0 N +IMPRESSIONABLE IH2 M P R EH1 SH AH0 N AH0 B AH0 L +IMPRESSIONISM IH2 M P R EH1 SH AH0 N IH2 Z AH0 M +IMPRESSIONIST IH2 M P R EH1 SH AH0 N AH0 S T +IMPRESSIONIST(1) IH2 M P R EH1 SH AH0 N IH0 S T +IMPRESSIONISTIC IH2 M P R EH2 SH AH0 N IH1 S T IH0 K +IMPRESSIONISTS IH2 M P R EH1 SH AH0 N IH0 S T S +IMPRESSIONS IH2 M P R EH1 SH AH0 N Z +IMPRESSIVE IH2 M P R EH1 S IH0 V +IMPRESSIVELY IH2 M P R EH1 S IH0 V L IY0 +IMPRESSMENT IH2 M P R EH1 S M AH0 N T +IMPRIMATUR IH2 M P R IH0 M AA1 T ER0 +IMPRIMIS IH2 M P R IY1 M IH0 S +IMPRINT IH2 M P R IH1 N T +IMPRINT(1) IH1 M P R IH0 N T +IMPRINTED IH2 M P R IH1 N T IH0 D +IMPRINTED(1) IH2 M P R IH1 N IH0 D +IMPRINTING IH2 M P R IH1 N T IH0 NG +IMPRINTING(1) IH2 M P R IH1 N IH0 NG +IMPRINTS IH2 M P R IH1 N T S +IMPRISON IH2 M P R IH1 Z AH0 N +IMPRISONED IH2 M P R IH1 Z AH0 N D +IMPRISONING IH2 M P R IH1 Z AH0 N IH0 NG +IMPRISONMENT IH2 M P R IH1 Z AH0 N M AH0 N T +IMPRISONS IH2 M P R IH1 Z AH0 N Z +IMPROBABLE IH2 M P R AA1 B AH0 B AH0 L +IMPROBABLY IH2 M P R AA1 B AH0 B L IY0 +IMPROMPTU IH2 M P R AA1 M P T UW0 +IMPROPER IH2 M P R AA1 P ER0 +IMPROPERLY IH2 M P R AA1 P ER0 L IY0 +IMPROPRIETIES IH2 M P R AH0 P R AY1 AH0 T IY0 Z +IMPROPRIETY IH2 M P R AH0 P R AY1 AH0 T IY0 +IMPROV IH1 M P R AA2 V +IMPROVE IH2 M P R UW1 V +IMPROVED IH2 M P R UW1 V D +IMPROVEMENT IH2 M P R UW1 V M AH0 N T +IMPROVEMENTS IH2 M P R UW1 V M AH0 N T S +IMPROVES IH2 M P R UW1 V Z +IMPROVING IH2 M P R UW1 V IH0 NG +IMPROVISATION IH2 M P R AA0 V IH0 Z EY1 SH AH0 N +IMPROVISATIONAL IH2 M P R AA0 V IH0 Z EY1 SH AH0 N AH0 L +IMPROVISATIONS IH2 M P R AA0 V IH0 Z EY1 SH AH0 N Z +IMPROVISE IH1 M P R AH0 V AY2 Z +IMPROVISE(1) IH2 M P R AH0 V AY1 Z +IMPROVISED IH1 M P R AH0 V AY2 Z D +IMPROVISES IH1 M P R AH0 V AY2 Z AH0 Z +IMPROVISES(1) IH2 M P R AH0 V AY1 Z AH0 Z +IMPROVISING IH1 M P R AH0 V AY2 Z IH0 NG +IMPRUDENCE IH2 M P R UW1 D AH0 N S +IMPRUDENT IH2 M P R UW1 D AH0 N T +IMPRUDENTLY IH2 M P R UW1 D AH0 N T L IY0 +IMPSON IH1 M P S AH0 N +IMPUGN IH2 M P Y UW1 N +IMPUGNED IH2 M P Y UW1 N D +IMPUGNING IH2 M P Y UW1 N IH0 NG +IMPUGNS IH2 M P Y UW1 N Z +IMPULSE IH1 M P AH0 L S +IMPULSE(1) IH2 M P AH1 L S +IMPULSES IH1 M P AH0 L S IH0 Z +IMPULSES(1) IH2 M P AH1 L S IH0 Z +IMPULSIVE IH2 M P AH1 L S IH0 V +IMPULSIVELY IH2 M P AH1 L S IH0 V L IY0 +IMPUNITY IH2 M P Y UW1 N IH0 T IY0 +IMPURE IH2 M P Y UH1 R +IMPURITIES IH2 M P Y UH1 R AH0 T IY0 Z +IMPURITY IH2 M P Y UH1 R AH0 T IY0 +IMPUTATION IH2 M P Y AH0 T EY1 SH AH0 N +IMPUTE IH2 M P Y UW1 T +IMPUTED IH2 M P Y UW1 T IH0 D +IMRE IH1 M R AH0 +IMREG IH2 M R EH1 G +IMREG'S IH2 M R EH1 G Z +IMRIE IH1 M ER0 IY0 +IMUS AY1 M AH0 S +IN IH0 N +IN(1) IH1 N +IN'S IH0 N Z +IN'S(1) IH1 N Z +IN-HOUSE IH2 N HH AW1 S +IN-LAW IH2 N L AO1 +IN-LAWS IH2 N L AO1 Z +IN. 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IH1 NG K +INC.'S IH1 NG K S +INCA IH1 NG K AH0 +INCALCULABLE IH2 N K AE1 L K Y AH0 L AH0 B AH0 L +INCANDESCENT IH2 N K AH0 N D EH1 S AH0 N T +INCANT IH2 N K AE1 N T +INCANTATION IH2 N K AE1 N T EY1 SH AH0 N +INCANTATORY IH2 N K AE1 N T AH0 T AO2 R IY0 +INCAPABLE IH2 N K EY1 P AH0 B AH0 L +INCAPACITATE IH2 N K AH0 P AE1 S IH0 T EY2 T +INCAPACITATED IH2 N K AH0 P AE1 S IH0 T EY2 T IH0 D +INCAPACITATING IH2 N K AH0 P AE1 S IH0 T EY2 T IH0 NG +INCAPACITATION IH2 N K AH0 P AE2 S IH0 T EY1 SH AH0 N +INCAPACITY IH2 N K AH0 P AE1 S AH0 T IY0 +INCARCERATE IH2 N K AA1 R S ER0 EY2 T +INCARCERATED IH2 N K AA1 R S ER0 EY2 T IH0 D +INCARCERATES IH2 N K AA1 R S ER0 EY2 T S +INCARCERATING IH2 N K AA1 R S ER0 EY2 T IH0 NG +INCARCERATION IH2 N K AA2 R S ER0 EY1 SH AH0 N +INCARNATE IH2 N K AA1 R N AH0 T +INCARNATE(1) IH2 N K AA1 R N EY2 T +INCARNATION IH2 N K AA1 R N EY1 SH AH0 N +INCARNATIONS IH2 N K AA0 R N EY1 SH AH0 N Z +INCAS IH1 NG K AH0 Z +INCASE IH2 N K EY1 S +INCATA IH2 NG K AA1 T AH0 +INCATA'S 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AH1 S T AH0 F AY2 AH0 B L IY0 +JUSTIFICATION JH AH2 S T AH0 F AH0 K EY1 SH AH0 N +JUSTIFICATIONS JH AH2 S T IH0 F IH0 K EY1 SH AH0 N Z +JUSTIFIED JH AH1 S T AH0 F AY2 D +JUSTIFIES JH AH1 S T AH0 F AY2 Z +JUSTIFY JH AH1 S T AH0 F AY2 +JUSTIFYING JH AH1 S T AH0 F AY2 IH0 NG +JUSTIN JH AH1 S T AH0 N +JUSTIN(1) JH AH1 S T IH0 N +JUSTIN'S JH AH1 S T AH0 N Z +JUSTIN'S(1) JH AH1 S T IH0 N Z +JUSTINA Y UW0 S T IY1 N AH0 +JUSTINE JH AH0 S T IY1 N +JUSTINIANO JH UW0 S T IY0 N IY0 AA1 N OW0 +JUSTINO JH AH0 S T IY1 N OW0 +JUSTIS Y UW1 S T IH0 S +JUSTISS Y UW1 S T IY0 S +JUSTLY JH AH1 S T L IY0 +JUSTMAN JH AH1 S T M AH0 N +JUSTO JH AH1 S T OW0 +JUSTUS JH AH1 S T AH0 S +JUSTY JH AH1 S T IY0 +JUT JH AH1 T +JUTE JH UW1 T +JUTLAND JH AH1 T L AH0 N D +JUTRAS Y UW1 T R AA0 Z +JUTS JH AH1 T S +JUTTING JH AH1 T IH0 NG +JUUL JH UW1 AH0 L +JUVE JH UW1 V +JUVENILE JH UW1 V AH0 N AH0 L +JUVENILE(1) JH UW1 V AH0 N AY2 L +JUVENILE'S JH UW1 V AH0 N AH0 L Z +JUVENILE'S(1) JH UW1 V AH0 N AY2 L Z +JUVENILES JH UW1 V AH0 N AH0 L Z +JUVENILES(1) JH UW1 V AH0 N AY2 L Z +JUWAN JH UW1 AA0 N +JUXTAPOSE JH AH2 K S T AH0 P OW1 Z +JUXTAPOSED JH AH2 K S T AH0 P OW1 Z D +JUXTAPOSES JH AH2 K S T AH0 P OW1 Z IH0 Z +JUXTAPOSING JH AH2 K S T AH0 P OW1 Z IH0 NG +JUXTAPOSITION JH AH2 K S T AH0 P AH0 Z IH1 SH AH0 N +JUXTAPOSITIONS JH AH2 K S T AH0 P AH0 Z IH1 SH AH0 N Z +JWAN JH W AA1 N +JYISHANE JH IY1 SH EY1 N +JYNX JH IH1 NG K S +K K EY1 +K'S K EY1 Z +K-MART K EY1 M AA1 R T +K-MART'S K EY1 M AA1 R T S +K. K EY1 +K.'S K EY1 Z +KA K AA1 +KAAS K AA1 S +KAATZ K AA1 T S +KABART K AH0 B AA1 R T +KABAT K AE1 B AH0 T +KABBAH K AH0 B AH1 +KABBALAH K AH0 B AA1 L AH0 +KABBANI K AH0 B AA1 N IY0 +KABEL K AE1 B AH0 L +KABI K AE1 B IY0 +KABI(1) K AA1 B IY0 +KABILA K AH0 B IH1 L AH0 +KABILA'S K AH0 B IH1 L AH0 Z +KABIVITRUM K AH0 B IH1 V IH0 T R AH0 M +KABLE K EY1 B AH0 L +KABLER K EY1 B AH0 L ER0 +KABLER(1) K EY1 B L ER0 +KABOOM K AH0 B UW1 M +KABRAL K AH0 B R AA1 L +KABUKI K AH0 B UW1 K IY2 +KABUL K AA1 B UH0 L +KACER K EY1 S ER0 +KACH K AE1 CH +KACHEL K AE1 K AH0 L +KACHIGIAN K AH0 SH IY1 G IY2 AH0 N +KACHMAR K AE1 K M ER0 +KACHUCK K AH0 CH AH1 K +KACHUR K AE1 CH ER0 +KACKLEY K AE1 K L IY0 +KACZMARCZYK K AA1 CH M ER0 CH IH0 K +KACZMAREK K AH0 CH M AA1 R EH0 K +KACZMARSKI K AH0 CH M AA1 R S K IY0 +KACZOR K AA1 CH ER0 +KACZOROWSKI K AH0 CH ER0 AO1 F S K IY0 +KACZYNSKI K AH0 CH IH1 N S K IY0 +KACZYNSKI(1) K AH0 Z IH1 N S K IY0 +KACZYNSKI'S K AH0 CH IH1 N S K IY0 Z +KACZYNSKI'S(1) K AH0 Z IH1 N S K IY0 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G L ER0 +KAGY K EY1 G IY0 +KAH K AA1 +KAHALANI K AA2 HH AH0 L AA1 N IY0 +KAHAN K AH0 HH AA1 N +KAHAN'S K AH0 HH AA1 N Z +KAHANE K AH0 HH AA1 N EY2 +KAHANE(1) K AH0 HH EY1 N +KAHL K AA1 L +KAHLE K AA1 L +KAHLER K AA1 L ER0 +KAHLEY K AA1 L IY0 +KAHN K AA1 N +KAHN'S K AA1 N Z +KAHNG K AA1 NG +KAHR K AA1 R +KAHR'S K AA1 R Z +KAHRE K EH1 R +KAHRE(1) K AA1 R +KAHRS K AA1 R Z +KAHULUI K AH0 HH UW1 L W IY0 +KAHUNA K AH0 HH UW1 N AH0 +KAI K AY1 +KAIFU K AY1 F UW2 +KAIGLER K EY1 G L ER0 +KAIL K EY1 L +KAILASH K EY1 L AH0 SH +KAILUA K AY0 L UW1 AH0 +KAIM K EY1 M +KAIN K EY1 N +KAINE K EY1 N +KAINER K EY1 N ER0 +KAINZ K EY1 N Z +KAIRAMO K EH2 R AA1 M OW0 +KAIREY K EH1 R IY0 +KAISER K AY1 Z ER0 +KAISER'S K AY1 Z ER0 Z +KAISERAUGST K AY1 Z ER0 AO0 G S T +KAISERTECH K AY1 Z ER0 T EH2 K +KAISERTECH'S K AY1 Z ER0 T EH2 K S +KAISHA K EY1 SH AH0 +KAJI K AA1 JH IY0 +KAJIMA K AA2 JH IY1 M AH0 +KAJUAHAR K AH0 JH UW1 AH0 HH AA0 R +KAKADU K AA2 K AA1 D UW0 +KAKIMOTO K AA2 K IH0 M OW1 T OW0 +KAKOS K EY1 K OW0 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L T AH0 N B AA2 K ER0 +KALTER K AO1 L T ER0 +KALTHOFF K AE1 L TH +KALUGIN K AH0 L UW1 G AH0 N +KALUZA K AH0 L UW1 Z AH0 +KALUZNY K AH0 L AH1 Z N IY0 +KALVAR K AE1 L V AA0 R +KAM K AE1 M +KAMA K AA1 M AH0 +KAMAKAU K AA2 M AH0 K AA1 UW0 +KAMAKAU'S K AA2 M AH0 K AA1 UW0 Z +KAMAL K EY1 M AH0 L +KAMALI K AH0 M AA1 L IY0 +KAMAN K EY1 M AH0 N +KAMBER K AE1 M B ER0 +KAMCHATKA K AE2 M CH AE1 T K AH0 +KAMCHATKA(1) K AA2 M CH AA1 T K AH0 +KAMEHAMEHA K AH0 M EY1 AH0 M EY1 AH0 +KAMEHAMEHA'S K AH0 M EY1 AH0 M EY1 AH0 Z +KAMEI K AE1 M IY0 +KAMEI(1) K AA2 M EY1 +KAMEL K AA1 M AH0 L +KAMEN K AA1 M EH0 N +KAMEN(1) K EY1 M EH0 N +KAMENAR K AE1 M AH0 N ER0 +KAMENS K AA1 M EH0 N Z +KAMENS(1) K EY1 M EH0 N Z +KAMENSKY K AH0 M EH1 N S K IY0 +KAMENTSEV K AH0 M EH1 N T S AA2 V +KAMER K EY1 M ER0 +KAMERER K AE1 M ER0 ER0 +KAMIKAZE K AA2 M AH0 K AA1 Z IY0 +KAMIN K AA1 M IY0 N +KAMIN(1) K EY1 M IH2 N +KAMIN(2) K AE1 M IH2 N +KAMINER K AE1 M IH0 N ER0 +KAMINS K AE1 M IH0 N Z +KAMINS(1) K EY1 M IH2 N Z +KAMINSKI K AH0 M IH1 N S K IY0 +KAMINSKY K AH0 M IH1 N S K IY0 +KAMIR K AH0 M IH1 R +KAMKE K AE1 M K IY0 +KAMLER K AE1 M AH0 L ER0 +KAMLER(1) K AE1 M L ER0 +KAMM K AE1 M +KAMMAN K AE1 M AH0 N +KAMMER K AE1 M ER0 +KAMMERER K AE1 M ER0 ER0 +KAMMERZELL K AE1 M ER0 Z AH0 L +KAMMEYER K AE1 M AY0 ER0 +KAMNEVA K AE2 M N EY1 V AH0 +KAMP K AE1 M P +KAMP'S K AE1 M P S +KAMPA K AE1 M P AH0 +KAMPALA K AH0 M P AA1 L AH0 +KAMPE K AE1 M P +KAMPELMAN K AE1 M P AH0 L M AH0 N +KAMPEN K AE1 M P AH0 N +KAMPER K AE1 M P ER0 +KAMPF K AE1 M P F +KAMPFER K AE1 M P F ER0 +KAMPHAUS K AE1 M P HH AW2 S +KAMPMAN K AE1 M P M AH0 N +KAMPMANN K AE1 M P M AH0 N +KAMPS K AE1 M P S +KAMPSCHULTE K AE1 M P SH UH2 L T IY0 +KAMRA K AE1 M R AH0 +KAMRADT K AE1 M R AH0 T +KAMRAN K AE1 M R AH0 N +KAMRATH K AE1 M R AH0 TH +KAMSTRA K AE1 M S T R AH0 +KAN K AE1 N +KANA K AE1 N AH0 +KANADE K AH0 N AA1 D EY2 +KANADY K AE1 N AH0 D IY0 +KANAGY K AE1 N AH0 JH IY0 +KANAI K AH0 N AY1 +KANAK K AE1 N AH0 K +KANAN K EY1 N AH0 N +KANAREK K AE1 N ER0 IH0 K +KANAWA K AA2 N AA1 W AH0 +KANAWHA K AH0 N AO1 HH AH0 +KANAZAWA K AA2 N AA0 Z AA1 W AH0 +KANDA K AE1 N D AH0 +KANDAHAR K AE1 N D AH0 HH AA0 R +KANDEL K AE1 N D AH0 L +KANDLER K AE1 N D L ER0 +KANDT K AE1 N T +KANE K EY1 N +KANE'S K EY1 N Z +KANEB K AE1 N AH0 B +KANEGSBERG K AE1 N AH0 G Z B ER0 G +KANEKO K AA0 N EY1 K OW0 +KANELL K AH0 N EH1 L +KANELL(1) K AE1 N AH0 L +KANEMARU K AE2 N EH0 M AA1 R UW0 +KANEMARU'S K AA2 N EY0 M AA1 R UW0 Z +KANER K EY1 N ER0 +KANESHIRO K AA0 N EY0 SH IH1 R OW0 +KANEY K EY1 N IY0 +KANG K AE1 NG +KANG(1) K AA1 NG +KANGAROO K AE2 NG G ER0 UW1 +KANGAROOS K AE2 NG G ER0 UW1 Z +KANGAS K AE1 NG G AH0 Z +KANGHUA K AE1 NG HH Y UW0 AH0 +KANGYO K AE1 N JH Y OW0 +KANIA K AA0 N IY1 AH0 +KANIEWSKI K AA0 N IY0 EH1 F S K IY0 +KANIEWSKI(1) K AA0 N IY0 UW1 S K IY0 +KANIPE K AE1 N IH0 P +KANIS K AE1 N IH0 S +KANITZ K AE1 N IH0 T S +KANJI K AE1 N JH IY0 +KANJORSKI K AH0 N JH AO1 R S K IY0 +KANKA K AE1 N K AH0 +KANKA(1) K AE1 NG K AH0 +KANKAKEE K AE1 NG K IH0 K IY0 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AA1 D AH0 SH EY2 N Z +KARDELL K AA1 R D AH0 L +KARDOS K AA1 R D OW0 Z +KAREEM K ER0 IY1 M +KAREEM'S K ER0 IY1 M Z +KAREL K EH1 R AH0 L +KARELIAN K ER0 IY1 L IY0 AH0 N +KARELS K EH1 R AH0 L Z +KAREMA K AH0 R EH1 M AH0 +KAREMA'S K AH0 R EH1 M AH0 Z +KAREN K EH1 R AH0 N +KAREN'S K EH1 R AH0 N Z +KARENINA K EH2 R EH0 N IY1 N AH0 +KARENINA(1) K AH0 R EH1 N IH0 N AH0 +KARET K EH1 R AH0 T +KARG K AA1 R G +KARGER K AA1 R G ER0 +KARGES K AA1 R JH IH0 Z +KARGONAOV K AA1 R G AH0 N AO2 V +KARI K EH1 R IY0 +KARIBU K EH2 R IY1 B UW0 +KARIM K ER0 IY1 M +KARIMI K AA0 R IY1 M IY0 +KARIN K EH1 R IH0 N +KARINA K AA0 R IY1 N AH0 +KARINO K EH2 R IY1 N OW0 +KARIOTIS K AA2 R IY0 OW1 T IH0 S +KARIS K EH1 R IY0 Z +KARL K AA1 R L +KARL'S K AA1 R L Z +KARLA K AA1 R L AH0 +KARLE K AA1 R AH0 L +KARLEN K AA1 R L AH0 N +KARLHEINZ K AA1 R L HH AY1 N Z +KARLIK K AA1 R L IH0 K +KARLIN K AA1 R L IH0 N +KARLINE K AA1 R L AY2 N +KARLOW K AA1 R L OW0 +KARLS K AA1 R L Z +KARLSEN K AA1 R L S AH0 N +KARLSON K AA1 R L S AH0 N 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IY0 +KARSH K AA1 R SH +KARSHNER K AA1 R SH N ER0 +KARSON K AA1 R S AH0 N +KARST K AA1 R S T +KARSTADT K AA1 R S T AE2 T +KARSTEN K AA1 R S T AH0 N +KARSTENS K AA1 R S T AH0 N Z +KARSTETTER K AA1 R S T IH0 T ER0 +KARTASASMITA K AA0 R T AE2 S AH0 S M IY1 T AH0 +KARTCHNER K AA1 R CH N ER0 +KARTER K AA1 R T ER0 +KARTES K AA1 R T S +KARUN K ER0 UW1 N +KARVONEN K AA1 R V AH0 N AH0 N +KARWOSKI K ER0 V AW1 S K IY0 +KARWOWSKI K ER0 V AO1 F S K IY0 +KARY K EH1 R IY0 +KARYDAKIS K EH2 R IY0 D AE1 K IH0 S +KARYN K AE1 R IH0 N +KARYRRHEXIS K EH2 R IY0 R EH1 K S IH0 S +KASABIAN K AH0 S EY1 B IY0 AH0 N +KASAGIC K AH0 S AA1 G IH0 K +KASAL K EY1 S AH0 L +KASBROL K AE1 Z B R AO0 L +KASBROLS K AE1 Z B R AO0 L Z +KASCH K AE1 SH +KASCHAK K AE1 SH AH0 K +KASDORF K AE1 S D AO0 R F +KASE K EY1 Z +KASEL K AE1 S AH0 L +KASELL K AE1 S AH0 L +KASEMAN K EY1 S M AH0 N +KASER K EY1 Z ER0 +KASESE K AH0 S IY1 Z IY0 +KASEY K AE1 S IY0 +KASH K AE1 SH +KASHA K AA1 SH AH0 +KASHIWAGI K AE2 SH IH0 W AE1 G IY0 +KASHIWAHARA K AA2 SH IY0 W AH0 HH AA1 R AH0 +KASHIWAHARA'S K AA2 SH IY0 W AH0 HH AA1 R AH0 Z +KASHIYAMA K AA2 SH IY0 Y AA1 M AH0 +KASHMIR K AE1 SH M IH0 R +KASHMIR(1) K AE1 SH M IY0 R +KASHMIRI K AE0 SH M IY1 R IY0 +KASHNER K AE1 SH N ER0 +KASHOGGI K AH0 SH AA1 JH IY0 +KASHUBA K AH0 SH UW1 B AH0 +KASI K AA1 Z IY0 +KASICH K AA1 S IH0 CH +KASICH'S K AA1 S IH0 CH IH0 Z +KASICK K AA1 S IH0 K +KASIK K AA1 S IH0 K +KASINGA K AH0 S IH1 NG G AH0 +KASINGA'S K AH0 S IH1 NG G AH0 Z +KASINGER K AE1 S IH0 N JH ER0 +KASKA K AA1 S K AH0 +KASKE K AE1 S K IY0 +KASKEL K AE1 S K AH0 L +KASLER K AE1 S AH0 L ER0 +KASLER(1) K AE1 S L ER0 +KASMER K AE1 S AH0 M ER0 +KASMIRA K AH0 S M AY1 R AH0 +KASNER K AE1 S N ER0 +KASPAR K AE1 S P ER0 +KASPAREK K AE1 S P ER0 IH0 K +KASPARIAN K AH0 S P EH1 R IY0 AH0 N +KASPAROV K AE1 S P ER0 AA0 V +KASPAROV(1) K AH0 S P AA1 R AA2 V +KASPER K AE1 S P ER0 +KASPEREK K AE1 S P ER0 IH0 K +KASPERSKI K AH0 S P ER1 S K IY0 +KASPROWICZ K AA1 S P R AH0 V IH0 CH +KASPRZAK K AA1 S P ER0 Z AH0 K 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ER0 IY1 N AH0 Z +KATASHIBA K AE2 T AH0 SH IY1 B AH0 +KATAYAMA K AA0 T AA0 Y AA1 M AH0 +KATAYAN K AA1 T AH0 Y AA0 N +KATCHER K AE1 CH ER0 +KATE K EY1 T +KATE'S K EY1 T S +KATEN K EY1 T AH0 N +KATER K EY1 T ER0 +KATES K EY1 T S +KATEY K EY1 T IY0 +KATH K AE1 TH +KATHA K AE1 TH AH0 +KATHALENE K AE0 TH AH0 L IY1 N +KATHAN K AE1 TH AH0 N +KATHARINA K AE2 TH EH0 R IY1 N AH0 +KATHARINE K AE1 TH R IH0 N +KATHERINE K AE1 TH ER0 IH0 N +KATHERINE(1) K AE1 TH R IH0 N +KATHI K AE1 TH IY0 +KATHIE K AE1 TH IY0 +KATHLEEN K AE0 TH L IY1 N +KATHLEEN'S K AE0 TH L IY1 N Z +KATHLENE K AE1 TH L IY2 N +KATHLINE K AE1 TH L AY2 N +KATHMAN K AE1 TH M AH0 N +KATHRYN K AE1 TH R IH0 N +KATHY K AE1 TH IY0 +KATHY'S K AE1 TH IY0 Z +KATI K EY1 T IY0 +KATIA K AA1 T IY0 AH0 +KATIE K EY1 T IY0 +KATIE'S K EY1 T IY0 Z +KATJA K AA1 T Y AH0 +KATMANDU K AE2 T M AE0 N D UW1 +KATO K EY1 T OW0 +KATO'S K EY1 T OW0 Z +KATONA K AA0 T OW1 N AH0 +KATRAGADDA K AA2 T R AH0 G AA1 D AH0 +KATRINA K AH0 T R IY1 N AH0 +KATS K AE1 T S 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AH0 D IY0 +KENNEDY'S K EH1 N AH0 D IY0 Z +KENNEDYS K EH1 N AH0 D IY0 Z +KENNEDYS' K EH1 N AH0 D IY0 Z +KENNEL K EH1 N AH0 L +KENNELL K EH1 N AH0 L +KENNELLY K EH1 N AH0 L IY0 +KENNELS K EH1 N AH0 L Z +KENNEMER K EH1 N IY0 M ER0 +KENNEMORE K EH1 N M AO0 R +KENNER K EH1 N ER0 +KENNER'S K EH1 N ER0 Z +KENNERLY K EH1 N ER0 L IY0 +KENNERSON K EH1 N ER0 S AH0 N +KENNESAW K EH1 N AH0 S AO2 +KENNETH K EH1 N IH0 TH +KENNETT K EH1 N AH0 T +KENNEY K EH1 N IY0 +KENNING K EH1 N IH0 NG +KENNINGTON K EH1 N IH0 NG T AH0 N +KENNISON K EH1 N IH0 S AH0 N +KENNON K EH1 N AH0 N +KENNY K EH1 N IY2 +KENNY'S K EH1 N IY2 Z +KENO K IY1 N OW0 +KENOBI K AH0 N OW1 B IY2 +KENOSHA K IH0 N OW1 SH AH0 +KENOYER K EH1 N OY0 ER0 +KENRICK K EH1 N R IH0 K +KENSINGER K EH1 N S IH0 N JH ER0 +KENSINGTON K EH1 N Z IH0 NG T AH0 N +KENSLER K EH1 N S AH0 L ER0 +KENSLER(1) K EH1 N S L ER0 +KENT K EH1 N T +KENT'S K EH1 N T S +KENTE K EH1 N T EY0 +KENTNER K EH1 N T N ER0 +KENTON K EH1 N T AH0 N +KENTUCKIAN K EH2 N T AH1 K IY0 AH0 N 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K EH1 P T +KEPT(1) K AE1 P T +KER K ER1 +KERA K EH1 R AH0 +KERALA K EH2 R AA1 L AH0 +KERANEN K EH1 R AH0 N AH0 N +KERATIN K EH1 R AH0 T AH0 N +KERATIN(1) K EH1 R AH0 T IH0 N +KERATOCONUS K EH2 R AH0 T AH0 K OW1 N AH0 S +KERATOTOMY K EH2 R AH0 T AO1 T AH0 M IY0 +KERB K ER1 B +KERBEL K ER1 B AH0 L +KERBER K ER1 B ER0 +KERBOW K ER1 B OW0 +KERBS K ER1 B Z +KERBY K ER1 B IY0 +KERCE K ER1 S +KERCHER K ER1 K ER0 +KERCHEVAL K ER1 CH IH0 V AH0 L +KERCHIEF K ER1 CH AH0 F +KERCHIEFS K ER1 CH AH0 F S +KERCHNER K ER1 K N ER0 +KEREKES K EH1 R IH0 K S +KEREN K EH1 R EH2 N +KERESTES K EH1 R IH0 S T S +KERESZTES K EH1 R AH0 S T IY0 Z +KERFOOT K ER1 F UH0 T +KERFUFFLE K ER0 F AH1 F AH0 L +KERIEN K EH1 R IY0 AH0 N +KERIN K EH1 R IH0 N +KERINS K EH1 R IH0 N Z +KERKER K ER1 K ER0 +KERKHOFF K ER1 K HH AO0 F +KERKMAN K ER1 K M AH0 N +KERKORIAN K ER0 K AO1 R IY0 AH0 N +KERKORIAN'S K ER0 K AO1 R IY0 AH0 N Z +KERL K ER1 L +KERLEY K ER1 L IY0 +KERLIN K ER1 L IH0 N +KERMAN K ER1 M AH0 N +KERMIT K ER1 M IH0 T 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AH0 +KIKATTE K IH1 K AE0 T +KIKER K AY1 K ER0 +KIKI K IY1 K IY0 +KIKKOMAN K IY1 K OW0 M AA0 N +KIKTA K IH1 K T AH0 +KIKUCHI K IY0 K UW1 CH IY0 +KIKUMURA K IY2 K UW2 M UW1 R AH0 +KIKWIT K IH1 K W IH0 T +KILA K IH1 L AH0 +KILAUEA K IY2 L AW2 EY1 AH0 +KILBANE K IH1 L B AH0 N +KILBORN K IH1 L B ER0 N +KILBORNE K IH1 L B AO2 R N +KILBOURN K IH1 L B ER0 N +KILBOURNE K IH1 L B ER0 N +KILBRIDE K IH1 L B R AY2 D +KILBURG K IH1 L B ER0 G +KILBURN K IH1 L B ER0 N +KILBURY K IH1 L B EH2 R IY0 +KILBY K IH1 L B IY0 +KILBY'S K IH1 L B IY0 Z +KILCOIN K IH1 L K OY0 N +KILCOYNE K IH1 L K OY0 N +KILCREASE K IH0 L K R IY1 S +KILCREASE(1) K IH1 L K R IY0 S +KILCULLEN K IH0 L K AH1 L AH0 N +KILDAY K IH1 L D EY2 +KILDEE K IH1 L D IY0 +KILDOW K IH1 L D OW0 +KILDUFF K IH1 L D AH0 F +KILE K AY1 L +KILEN K IH1 L AH0 N +KILEY K AY1 L IY0 +KILGO K IH1 L G OW0 +KILGORE K IH1 L G AO0 R +KILGOUR K IH1 L G ER0 +KILGUS K IH1 L G AH0 S +KILIAN K IH1 L IY0 AH0 N +KILIMANJARO K IH0 L IY2 M AH0 N JH AA1 R OW0 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IH0 L M AA1 R T IH0 N +KILMER K IH1 L M ER0 +KILN K IH1 L N +KILNS K IH1 L N Z +KILO K IH1 L OW2 +KILOBIT K IH1 L AH0 B IH0 T +KILOBYTE K IH1 L OW0 B AY2 T +KILOBYTES K IH1 L OW0 B AY2 T S +KILOGRAM K IH1 L AH0 G R AE2 M +KILOGRAMS K IH1 L AH0 G R AE2 M Z +KILOMETER K AH0 L AA1 M AH0 T ER0 +KILOMETER(1) K IH1 L AH0 M IY2 T ER0 +KILOMETERS K AH0 L AA1 M AH2 T ER0 Z +KILOMETERS(1) K IH1 L AH0 M IY2 T ER0 Z +KILOMETRE K IH2 L AO1 M AH2 T ER0 +KILOMETRE(1) K IH2 L AH0 M IY1 T ER0 +KILOMETRES K IH2 L AO1 M AH2 T ER0 Z +KILOMETRES(1) K IH2 L AH0 M IY1 T ER0 Z +KILOS K IY1 L OW2 Z +KILOWATT K IH1 L AH0 W AA2 T +KILOWATTS K IH1 L AH0 W AA2 T S +KILPATRICK K IH2 L P AE1 T R IH0 K +KILROY K IH1 L R OY2 +KILT K IH1 L T +KILTER K IH1 L T ER0 +KILTON K IH1 L T AH0 N +KILTS K IH1 L T S +KILTY K IH1 L T IY0 +KILZER K IH1 L Z ER0 +KIM K IH1 M +KIM'S K IH1 M Z +KIMBA K IH1 M B AH0 +KIMBALL K IH1 M B AH0 L +KIMBALL'S K IH1 M B AH0 L Z +KIMBEL K IH1 M B AH0 L +KIMBELL K IH1 M B EH0 L +KIMBER K IH1 M B ER0 +KIMBERLEY K IH1 M B ER0 L IY0 +KIMBERLIN K IH1 M B ER0 L IH0 N +KIMBERLING K IH1 M B ER0 L IH0 NG +KIMBERLY K IH1 M B ER0 L IY0 +KIMBERLY'S K IH1 M B ER0 L IY0 Z +KIMBLE K IH1 M B AH0 L +KIMBLER K IH1 M B L ER0 +KIMBLEY K IH1 M B L IY0 +KIMBREL K IH1 M B R AH0 L +KIMBRELL K IH1 M B R AH0 L +KIMBRIEL K IH1 M B R IY0 AH0 L +KIMBRO K IH1 M B R OW0 +KIMBROUGH K IH1 M B R AW0 +KIMCHE K IH1 M CH IY0 +KIMCHEE K IH1 M CH IY0 +KIMCHI K IH1 M CH IY0 +KIMCO K IH1 M K OW0 +KIME K AY1 M +KIMEL K IH1 M AH0 L +KIMERY K IH1 M ER0 IY0 +KIMES K AY1 M Z +KIMLER K IH1 M AH0 L ER0 +KIMLER(1) K IH1 M L ER0 +KIMM K IH1 M +KIMMEL K IH1 M AH0 L +KIMMELL K IH1 M AH0 L +KIMMELMAN K IH1 M AH0 L M AH0 N +KIMMER K IH1 M ER0 +KIMMERLE K IH1 M ER0 AH0 L +KIMMET K IH1 M IH0 T +KIMMEY K IH1 M IY0 +KIMMICH K IH1 M IH0 CH +KIMMINS K IH1 M IH0 N Z +KIMMITT K IH1 M IH0 T +KIMMONS K IH1 M AH0 N Z +KIMONO K AH0 M OW1 N AH0 +KIMONOS K AH0 M OW1 N AH0 Z +KIMOTO K IY0 M OW1 T OW0 +KIMPEL K IH1 M P AH0 L +KIMPLE K IH1 M P AH0 L +KIMPO K IH1 M P OW0 +KIMPTON K IH1 M P T AH0 N +KIMREY K IH1 M R IY0 +KIMS K IH1 M Z +KIMSEY K IH1 M Z IY0 +KIMURA K IY0 M UH1 R AH0 +KIMWIPE K IH1 M W AY0 P +KIMWIPES K IH1 M W AY0 P S +KIMZEY K IH1 M Z IY0 +KIN K IH1 N +KIN'S K IH1 N Z +KINARD K IH1 N ER0 D +KINARK K IH1 N AA0 R K +KINASE K AY1 N EY2 Z +KINBURN K IH1 N B ER2 N +KINCADE K IH2 N K EY1 D +KINCAID K IH2 N K EY1 D +KINCAID'S K IH2 N K EY1 D Z +KINCANNON K IH2 N K AE1 N AH0 N +KINCER K IH1 N S ER0 +KINCH K IH1 N CH +KINCHELOE K IH1 N CH IH0 L OW0 +KINCHEN K IH1 NG K AH0 N +KINCY K IH1 N S IY0 +KIND K AY1 N D +KINDA K IH1 N D AH0 +KINDALL K IH1 N D AH0 L +KINDEL K IH1 N D AH0 L +KINDELL K IH1 N D AH0 L +KINDER K AY1 N D ER0 +KINDERGARTEN K IH1 N D ER0 G AA2 R T AH0 N +KINDERGARTENS K IH1 N D ER0 G AA2 R T AH0 N Z +KINDERGARTNER K IH1 N D ER0 G AA2 R T N ER0 +KINDERGARTNERS K IH1 N D ER0 G AA2 R T N ER0 Z +KINDERMAN K AY1 N D ER0 M AH0 N +KINDEST K AY1 N D AH0 S T +KINDIG K IH1 N D IH0 G +KINDLE K IH1 N D AH0 L 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AH0 L +KINKER K IH1 NG K ER0 +KINKLE K IH1 NG K AH0 L +KINKO K IH1 NG K OW2 +KINKO'S K IH1 NG K OW2 Z +KINKS K IH1 NG K S +KINKY K IH1 NG K IY0 +KINLAW K IH1 N L AO2 +KINLEY K IH1 N L IY0 +KINLOCH K IH1 N L AH0 K +KINMAN K IH1 N M AH0 N +KINMEN K IH1 N M EH0 N +KINN K IH1 N +KINNAIRD K IH1 N ER0 D +KINNAMAN K IH1 N AH0 M AH0 N +KINNAMON K IH1 N AH0 M AH0 N +KINNAN K IH1 N AH0 N +KINNARD K IH1 N ER0 D +KINNE K IH1 N +KINNEAR K IH1 N IH2 R +KINNEBREW K IH1 N IH0 B R UW0 +KINNELL K IH1 N AH0 L +KINNER K IH1 N ER0 +KINNETT K IH1 N IH0 T +KINNEY K IH1 N IY0 +KINNICK K IH1 N IH0 K +KINNIE K IH1 N IY0 +KINNISON K IH1 N IH0 S AH0 N +KINNOCK K IH1 N AH0 K +KINNOCK'S K IH1 N AH0 K S +KINNUNEN K IH0 N AH1 N AH0 N +KINNY K IH1 N IY0 +KINOSHITA K IY0 N OW0 SH IY1 T AH0 +KINSEL K IH1 N S AH0 L +KINSELL K IH1 N S AH0 L +KINSELLA K IY0 N S EH1 L AH0 +KINSER K IH1 N S ER0 +KINSEY K IH1 N Z IY0 +KINSHASA K IH0 N SH AA1 S AH0 +KINSHASA(1) K IH0 N SH AE1 S AH0 +KINSHIP K IH1 N SH IH2 P +KINSINGER K IH1 N S IH0 N JH ER0 +KINSLER K IH1 N S AH0 L ER0 +KINSLER(1) K IH1 N S L ER0 +KINSLEY K IH1 N Z L IY0 +KINSLEY'S K IH1 N Z L IY0 Z +KINSLOW K IH1 N S L OW2 +KINSMAN K IH1 N Z M AE2 N +KINST K IH1 N S T +KINSTLER K IH1 N S T L ER0 +KINSTON K IH1 N S T AH0 N +KINT K IH1 N T +KINTER K IH1 N T ER0 +KINTIGH K IH1 N T AY0 +KINTNER K IH1 N T N ER0 +KINTON K IH1 N T AH0 N +KINTZ K IH1 N T S +KINTZEL K IH1 N T Z AH0 L +KINYON K IH1 N Y AH0 N +KINZEL K IH1 N Z AH0 L +KINZER K IH1 N Z ER0 +KINZEY K IH1 N Z IY0 +KINZIE K IH1 N Z IY0 +KINZLER K IH1 N Z L ER0 +KINZLMAIER K IH1 N Z AH0 L M AY2 ER0 +KIOSK K IY1 AO2 S K +KIOSKS K IY1 AO2 S K S +KIOUS K AY1 AH0 S +KIP K IH1 P +KIPER K AY1 P ER0 +KIPFER K IH1 P F ER0 +KIPLING K IH1 P L IH0 NG +KIPLINGER K IH1 P AH0 L IH0 NG ER0 +KIPLINGER(1) K IH1 P L IH0 NG ER0 +KIPLINGER'S K IH1 P L IH2 NG ER0 Z +KIPNIS K IH1 P N IH0 S +KIPP K IH1 P +KIPPER K IH1 P ER0 +KIPPERMAN K IH1 P ER0 M AH0 N +KIPPERS K IH1 P ER0 Z +KIPPES K IH1 P S +KIPPUR K IH1 P ER0 +KIR K IH1 R +KIRA K IY1 R AA0 +KIRACOFE K IH1 R AH0 K OW2 F +KIRALY K IH1 R AH0 L IY0 +KIRBY K ER1 B IY0 +KIRBY'S K ER1 B IY0 Z +KIRCH K ER1 K +KIRCHBERG K ER1 K B ER0 G +KIRCHBERG(1) K ER1 CH B ER0 G +KIRCHBERGER K ER1 CH B ER0 G ER0 +KIRCHEN K ER1 K AH0 N +KIRCHER K ER1 K ER0 +KIRCHGESSNER K ER1 K G IH0 S N ER0 +KIRCHHOFER K ER1 K HH AH0 F ER0 +KIRCHHOFF K ER1 K HH AO0 F +KIRCHMAN K ER1 K M AH0 N +KIRCHNER K ER1 K N ER0 +KIRCHNERS K ER1 K N ER0 Z +KIRCHOFF K ER1 K HH AO0 F +KIRGAN K ER1 G AH0 N +KIRGIZ K IH1 R G IH0 Z +KIRI K IH1 R IY0 +KIRIBATI K IH2 R IH1 B AA1 T IY0 +KIRIN K IH1 R IH0 N +KIRK K ER1 K +KIRK'S K ER1 K S +KIRKBRIDE K ER1 K B R AY0 D +KIRKBY K ER1 K B IY0 +KIRKEBY K ER1 K IH0 B IY0 +KIRKENDALL K ER0 K EH1 N D AH0 L +KIRKENDOLL K ER0 K EH1 N D OW0 L +KIRKER K ER1 K ER0 +KIRKEY K ER1 K IY0 +KIRKHAM K ER1 K HH AH0 M +KIRKHART K ER1 K HH AA0 R T +KIRKLAND K ER1 K L AH0 N D +KIRKLAND'S K ER1 K L AH0 N D Z +KIRKLEY K ER1 K L IY0 +KIRKLIN K ER1 K L IH0 N +KIRKMAN K ER1 K M AH0 N +KIRKNER K ER1 K N ER0 +KIRKPATRICK K ER0 K P AE1 T R IH0 K +KIRKPATRICK(1) K ER0 P AE1 T R IH0 K +KIRKS K ER1 K S +KIRKSEY K ER1 K S IY0 +KIRKUK K IH2 R K UH1 K +KIRKUM K IH1 R K AH0 M +KIRKWOOD K ER1 K W UH0 D +KIRLEY K ER1 L IY0 +KIRLIN K ER1 L IH0 N +KIRMSE K ER1 M S IY0 +KIRN K ER1 N +KIRNAN K ER1 N AH0 N +KIRNER K ER1 N ER0 +KIROUAC K AY1 R AW0 AE0 K +KIROV K IH1 R AA0 V +KIRSCH K ER1 SH +KIRSCHBAUM K ER1 SH B AW0 M +KIRSCHENBAUM K ER1 SH AH0 N B AW0 M +KIRSCHENMANN K ER1 SH AH0 N M AH0 N +KIRSCHMAN K ER1 SH M AH0 N +KIRSCHNER K ER1 SH N ER0 +KIRSH K ER1 SH +KIRSHBAUM K ER1 SH B AW2 M +KIRSHENBAUM K ER1 SH AH0 N B AW0 M +KIRSHFINK K ER1 SH F IH0 NG K +KIRSHNER K ER1 SH N ER0 +KIRST K ER1 S T +KIRSTEIN K ER1 S T AY0 N +KIRSTEIN(1) K ER1 S T IY0 N +KIRSTEN K ER1 S T AH0 N +KIRSTIE K ER1 S T IY0 +KIRSTIN K ER1 S T IH0 N +KIRT K ER1 T +KIRTLAND K ER1 T L AH0 N D +KIRTLEY K ER1 T L IY0 +KIRTON K ER1 T AH0 N +KIRTS K ER1 T S +KIRVEN K ER1 V AH0 N +KIRWAN K ER1 W AO0 N +KIRWIN K ER1 W IH0 N +KIRYAS K IH1 R Y AH0 S +KIRYAS(1) K IH2 R Y AA1 S +KIRYAT K IH1 R Y AH0 T +KIRYAT(1) K IH2 R Y AA1 T +KIS K IH1 S +KISAMORE K IY0 S AA1 M AO0 R +KISAN K IH1 Z AH0 N +KISCH K IH1 SH +KISCHELL K IH1 SH AH0 L +KISCO K IH1 S K OW0 +KISE K AY1 Z +KISER K AY1 Z ER0 +KISH K IH1 SH +KISHA K IH1 SH AH0 +KISHBAUGH K IH1 SH B AW0 +KISHI K IY1 SH IY0 +KISHORE K IY1 SH AO2 R +KISIEL K IH1 S IY0 L +KISKA K IH1 S K AH0 +KISKA'S K IH1 S K AH0 Z +KISLER K IH1 S AH0 L ER0 +KISLER(1) K IH1 S L ER0 +KISLING K IH1 S AH0 L IH0 NG +KISLING(1) K IH1 S L IH0 NG +KISMAYU K IH0 S M AA1 Y UW0 +KISMAYU(1) K IH0 Z M AA1 Y UW0 +KISMET K IH1 Z M IH0 T +KISMETS K IH1 Z M IH0 T S +KISNER K IH1 S N ER0 +KISOR K AY1 Z ER0 +KISS K IH1 S +KISSACK K IH1 S AH0 K +KISSAM K IH1 S AH0 M +KISSANE K IH1 S AH0 N +KISSED K IH1 S T +KISSEE K IH1 S IY1 +KISSEL K IH1 S AH0 L +KISSELL K IH1 S AH0 L +KISSER K IH1 S ER0 +KISSES K IH1 S AH0 Z +KISSES(1) K IH1 S IH0 Z +KISSICK K IH1 S IH0 K +KISSIMMEE K IH0 S IH1 M IY0 +KISSING K IH1 S IH0 NG +KISSINGER K IH1 S IH0 N JH ER0 +KISSINGER'S K IH1 S IH0 N JH ER0 Z +KISSLER K IH1 S L ER0 +KISSLING K IH1 S L IH0 NG +KISSNER K IH1 S N ER0 +KIST K IH1 S T +KISTER K IH1 S T ER0 +KISTLER K IH1 S T L ER0 +KISTNER K IH1 S T N ER0 +KISZCZAK K IH1 Z AE0 K +KISZCZAK(1) K IH1 SH AE0 K +KIT K IH1 T +KITA K IY1 T AH0 +KITAGAWA K IY0 T AA0 G AA1 W AH0 +KITAJIMA K IY2 T AH0 JH IY1 M AH0 +KITAMURA K IY0 T AA0 M UH1 R AH0 +KITCAT K IH1 T K AE2 T +KITCH K IH1 CH +KITCHEL K IH1 CH AH0 L +KITCHELL K IH1 CH AH0 L +KITCHEN K IH1 CH AH0 N +KITCHEN'S K IH1 CH AH0 N Z +KITCHENAID K IH1 CH AH0 N EY2 D +KITCHENER K IH1 CH AH0 N ER0 +KITCHENER(1) K IH1 CH N ER0 +KITCHENETTE K IH2 CH AH0 N EH1 T +KITCHENS K IH1 CH AH0 N Z +KITCHENWARE K IH1 CH AH0 N W EH2 R +KITCHIN K IH1 CH IH0 N +KITCHING K IH1 CH IH0 NG +KITCHINGS K IH1 CH IH0 NG Z +KITE K AY1 T +KITES K AY1 T S +KITHCART K IH1 TH K AA2 R T +KITIMAT K IH1 T IH0 M AE0 T +KITING K AY1 T IH0 NG +KITMAN K IH1 T M AH0 N +KITNER K IH1 T N ER0 +KITOWSKI K IH0 T AO1 F S K IY0 +KITS K IH1 T S +KITSCH K IH1 CH +KITSON K IH1 T S AH0 N +KITT K IH1 T +KITTANEH K IH0 T AA1 N EH2 +KITTEL K IH1 T AH0 L +KITTELL K IH1 T AH0 L +KITTELSON K IH1 T IH0 L S AH0 N +KITTEN K IH1 T AH0 N +KITTENS K IH1 T AH0 N Z +KITTERMAN K IH1 T ER0 M AH0 N +KITTINGER K IH1 T IH0 NG ER0 +KITTIWAKE K IH1 T IH0 W EY2 K +KITTLE K IH1 T AH0 L +KITTLER K IH1 T AH0 L ER0 +KITTLES K IH1 T AH0 L Z +KITTLESON K IH1 T AH0 L S AH0 N +KITTMAN K IH1 T M AH0 N +KITTNER K IH1 T N ER0 +KITTREDGE K IH1 T R IH0 JH +KITTRELL K IH1 T R AH0 L +KITTS K IH1 T S +KITTY K IH1 T IY0 +KITZ K IH1 T S +KITZHABER K IH1 T S HH EY2 B ER0 +KITZHABER(1) K IH1 T S HH AA2 B ER0 +KITZMAN K IH1 T S M AH0 N +KITZMILLER K IH1 T S M IH2 L ER0 +KIVELA K IH1 V IH0 L AH0 +KIVETT K IH1 V IH0 T +KIVI K IH1 V IY0 +KIWANI K IH0 W AA1 N IH0 +KIWANIS K IH0 W AA1 N IH0 S +KIWI K IY1 W IY0 +KIWI'S K IY1 W IY0 Z +KIWIS K IY1 W IY0 Z +KIYOHIDA K IY2 OW0 HH IY1 D AH0 +KIYOSHI K IY0 OW1 SH IY0 +KIYOTAKA K IY2 OW0 T AA1 K AH0 +KIZER K AY1 Z ER0 +KIZZIAH K IH1 Z IY0 AH0 +KJAR K Y AA1 R +KJAR(1) K EY1 JH EY1 EY1 AA1 R +KJELL K Y EH1 L +KJELLBERG K Y EH1 L B ER0 G +KJELLBERG(1) JH EH1 L B ER0 G +KJENSTAD K Y EH1 N S T AE2 D +KJOS K Y AO1 S +KKK K EY1 K EY1 K EY1 +KLAAS K L AA1 S +KLAASSEN K L AA1 S AH0 N +KLABUNDE K L AE1 B AH0 N D +KLADSTRUP K L AE1 D S T R AH0 P +KLADSTRUP'S K L AE1 D S T R AH0 P S +KLAGES K L EY1 JH IH0 Z +KLAHN K L AE1 N +KLAHR K L AE1 R +KLAIBER K L EY1 B ER0 +KLAMATH_FALLS K L AE1 M AH0 TH F AO1 L Z +KLAMER K L EY1 M ER0 +KLAMM K L AE1 M +KLAMMER K L AE1 M ER0 +KLAMON K L EY1 M AH0 N +KLAN K L AE1 N +KLAN'S K L AE1 N Z +KLANG K L AE1 NG +KLANN K L AE1 N +KLANS K L AE1 N Z +KLANSMAN K L AE1 N Z M AH0 N +KLANSMEN K L AE1 N Z M EH0 N +KLANWATCH K L AE1 N W AA2 CH +KLAPP K L AE1 P +KLAPPER K L AE1 P ER0 +KLAPPERICH K L AE1 P ER0 IH0 K +KLAR K L AA1 R +KLARE K L EH1 R +KLARICH K L AE1 R IH0 K +KLARMAN K L AA1 R M AH0 N +KLAS K L AE1 S +KLASE K L EY1 Z +KLASEN K L EY1 S AH0 N +KLASS K L AE1 S +KLASSEN K L AE1 S AH0 N +KLATSKY K L AE1 T S K IY0 +KLATT K L AE1 T +KLAUBER K L AW1 B ER0 +KLAUER K L AW1 ER0 +KLAUS K L AW1 S +KLAUSER K L AW1 S ER0 +KLAUSING K L AW1 S IH0 NG +KLAUSNER K L AW1 S N ER0 +KLAVER K L EY1 V ER0 +KLAWITTER K L AO1 IH0 T ER0 +KLAY K L EY1 +KLAYMAN K L EY1 M AH0 N +KLEBAN K L EH1 B AH0 N +KLEBBA K L EH1 B AH0 +KLEBE K L IY1 B +KLEBER K L IY1 B ER0 +KLECK K L EH1 K +KLECKA K L EH1 K AH0 +KLECKER K L EH1 K ER0 +KLECKNER K L EH1 K N ER0 +KLECZKA K L EH1 K S K AH0 +KLEE K L IY1 +KLEE'S K L IY1 Z +KLEEMAN K L IY1 M AH0 N +KLEEN K L IY1 N +KLEENEX K L IY1 N AH0 K S +KLEER K L IH1 R +KLEES K L IY1 Z +KLEFFNER K L EH1 F N ER0 +KLEIBER K L AY1 B ER0 +KLEIER K L AY1 ER0 +KLEIMAN K L AY1 M AH0 N +KLEIN K L AY1 N +KLEIN'S K L AY1 N Z +KLEINBERG K L AY1 N B ER0 G +KLEINDIENST K L AY1 N D IY2 N S T +KLEINE K L AY1 N +KLEINER K L AY1 N ER0 +KLEINERT K L AY1 N ER0 T +KLEINFELD K L AY1 N F EH2 L D +KLEINFELTER K L AY1 N F IH0 L T ER0 +KLEINHANS K L AY1 N HH AH0 N Z +KLEINHENZ K L AY1 N HH IH0 N S +KLEINKNECHT K L AY1 NG K N IH0 K T +KLEINMAN K L AY1 N M AH0 N +KLEINPASTE K L AY1 N P EY2 S T +KLEINPETER K L AY1 N P IY0 T ER0 +KLEINSASSER K L AY1 N S AH0 S ER0 +KLEINSCHMIDT K L AY1 N SH M IH2 T +KLEINSMITH K L AY1 N S M IH0 TH +KLEINWORT K L AY1 N W ER0 T +KLEIS K L AY1 Z +KLEISS K L AY1 S +KLEIST K L AY1 S T +KLEJNA K L EY1 N ER0 +KLEM K L EH1 M +KLEMA K L EH1 M AH0 +KLEMAN K L EH1 M AH0 N +KLEMANN K L EH1 M AH0 N +KLEMENS K L EH1 M AH0 N S +KLEMENT K L EH1 M AH0 N T +KLEMM K L EH1 M +KLEMME K L EH1 M +KLEMMER K L EH1 M ER0 +KLEMP K L EH1 M P +KLEMPNER K L EH1 M P N ER0 +KLEMZ K L EH1 M Z +KLENGE K L EH1 N JH +KLENK K L EH1 NG K +KLENKE K L EH1 NG K +KLENSCH K L EH1 N SH +KLEPAC K L EH1 P AH0 K +KLEPFER K L EH1 P F ER0 +KLEPPE K L EH1 P +KLEPPER K L EH1 P ER0 +KLEPPINGER K L EH1 P IH0 NG G ER0 +KLEPTOCRAT K L EH1 P T AH0 K R AE0 T +KLEPTOMANIAC K L EH2 P T AH0 M EY1 N IY0 AE0 K +KLERK K L ER1 K +KLERK'S K L ER1 K S +KLESCH K L EH1 SH +KLESKEN K L EH1 S K AH0 N +KLESS K L EH1 S +KLETT K L EH1 T +KLEUBECK K L UW1 B EH0 K +KLEVE K L IY1 V +KLEVEN K L IY1 V AH0 N +KLEVER K L EH1 V ER0 +KLEY K L EY1 +KLEZMATIC K L EH0 Z M AE1 T IH0 K +KLEZMATICS K L EH0 Z M AE1 T IH0 K S +KLEZMER K L EH1 Z M ER0 +KLICH K L IH1 CH +KLICK K L IH1 K +KLICKOVIC K L IH1 K AH0 V IH2 K +KLIEBERT K L IY1 B ER0 T +KLIEG K L IY1 G +KLIEMAN K L AY1 M AH0 N +KLIER K L AY1 ER0 +KLIETHERMES K L IY1 TH ER0 M Z +KLIEWER K L IY1 W ER0 +KLIGMAN K L IH1 G M AH0 N +KLIM K L IH1 M +KLIMA K L AY1 M AH0 +KLIMAS K L AY1 M AH0 Z +KLIMASZEWSKI K L IH0 M AH0 SH EH1 F S K IY0 +KLIMCZAK K L IH1 M CH AE0 K +KLIMEK K L IH1 M IH0 K +KLIMENT K L AY1 M AH0 N T +KLIMER K L IH1 M ER0 +KLIMER(1) K L AY1 M ER0 +KLIMOWICZ K L IH1 M AH0 V IH0 CH +KLINCK K L IH1 NG K +KLINDT K L IH1 N T +KLINDWORTH K L IH1 N D W ER0 TH +KLINE K L AY1 N +KLINEDINST K L IH1 N IH0 D IH0 N S T +KLINEDINST(1) K L AY1 N D IH0 N S T +KLINEFELTER K L IH1 N IH0 F IH0 L T ER0 +KLINEFELTER(1) K L AY1 N F IH0 L T ER0 +KLING K L IH1 NG +KLINGAMAN K L IH1 NG G AH0 M AH0 N +KLINGBEIL K L IH1 NG B AY0 L +KLINGBERG K L IH1 NG B ER0 G +KLINGE K L IH1 N JH +KLINGEL K L IH1 NG G AH0 L +KLINGENBERG K L IH1 NG AH0 N B ER0 G +KLINGENSMITH K L IH1 NG G IH0 N S M IH0 TH +KLINGER K L IH1 NG ER0 +KLINGER'S K L IH1 NG ER0 Z +KLINGERMAN K L IH1 NG ER0 M AH0 N +KLINGHOFFER K L IH1 NG HH AO2 F ER0 +KLINGLER K L IH1 NG G AH0 L ER0 +KLINGLER(1) K L IH1 NG G L ER0 +KLINGMAN K L IH1 NG M AH0 N +KLINGON K L IH1 NG G AO2 N +KLINGONS K L IH1 NG G AO2 N Z +KLINK K L IH1 NG K +KLINKE K L IH1 NG K +KLINKER K L IH1 NG K ER0 +KLINKHAMMER K L IH1 NG K HH AE0 M ER0 +KLINKHAMMER'S K L IH1 NG K HH AE0 M ER0 Z +KLINKNER K L IH1 NG K N ER0 +KLINT K L IH1 N T +KLINTWORTH K L IH1 N T W ER0 TH +KLINZING K L IH1 N Z IH0 NG +KLIPFEL K L IH1 P F AH0 L +KLIPP K L IH1 P +KLIPPEL K L IH1 P AH0 L +KLISH K L IH1 SH +KLITZ K L IH1 T S +KLITZKE K L IH1 T S K IY0 +KLIXSHAVICH K L IH0 K S AE1 V IH0 CH +KLOBERDANZ K L AA1 B ER0 D AH0 N S +KLOC K L AA1 K +KLOCEK K L OW1 S IH0 K +KLOCK K L AA1 K +KLOCKE K L AA1 K +KLOECKNER K L OW1 K N ER0 +KLOEHN K L OW1 N +KLOEPFER K L OW1 P F ER0 +KLOEPPEL K L OW1 P AH0 L +KLOEPPER K L OW1 P ER0 +KLOIBER K L OY1 B ER0 +KLOM K L AO1 M +KLOMP K L AA1 M P +KLONDIKE K L AA1 N D AY2 K +KLONOWSKI K L AH0 N AO1 F S K IY0 +KLONTZ K L AA1 N T S +KLOOS K L UW1 Z +KLOOSTER K L UW1 S T ER0 +KLOOSTERMAN K L UW1 S T ER0 M AH0 N +KLOPF K L AA1 P F +KLOPFENSTEIN K L AA1 P F AH0 N S T AY0 N +KLOPFENSTEIN(1) K L AA1 P F AH0 N S T IY0 N +KLOPFER K L AA1 P F ER0 +KLOPP K L AA1 P +KLOPPENBURG K L AA1 P AH0 N B ER0 G +KLOS K L AO1 S +KLOSE K L OW1 Z +KLOSINSKI K L AH0 S IH1 N S K IY0 +KLOSOWSKI K L AH0 S AO1 F S K IY0 +KLOSS K L AO1 S +KLOSSNER K L AA1 S N ER0 +KLOSTER K L AO1 S T ER0 +KLOSTERMAN K L AA1 S T ER0 M AH0 N +KLOSTERMANN K L AA1 S T ER0 M AH0 N +KLOTH K L AA1 TH +KLOTZ K L AA1 T S +KLOTZBACH K L AA1 T S B AA0 K +KLU K L UW1 +KLU(1) K EY2 EH2 L Y UW1 +KLUCEVSEK K L UW0 S EH1 V S EH0 K +KLUCK K L AH1 K +KLUDT K L AH1 D T +KLUENDER K L UH1 N D ER0 +KLUESNER K L UH1 S N ER0 +KLUEVER K L UH1 V ER0 +KLUG K L AH1 G +KLUGE K L UW1 JH +KLUGE'S K L UW1 JH IH0 Z +KLUGER K L UW1 G ER0 +KLUGH K L AH1 +KLUGMAN K L AH1 G M AH0 N +KLUGT K L AH1 T +KLUKAS K L UW1 K AH0 Z +KLUMB K L AH1 M +KLUMP K L AH1 M P +KLUMPP K L AH1 M P +KLUNDER K L AH1 N D ER0 +KLUNDT K L AH1 N T +KLUNK K L AH1 NG K +KLUS K L AH1 S +KLUSMAN K L AH1 S M AH0 N +KLUTE K L UW1 T +KLUTH K L UW1 TH +KLUTTS K L AH1 T S +KLUTTZ K L AH1 T S +KLUTZ K L AH1 T S +KLUTZNICK K L AH1 T S N IH0 K +KLUVER K L UW1 V ER0 +KLUWER K L UW1 W ER0 +KLUX K L AH1 K S +KLYM K L IH1 M +KLYNVELD K L IH1 N V EH2 L D +KMART K EY1 M AA2 R T +KMART'S K EY1 M AA2 R T S +KMETZ K AH0 M EH1 T S +KMIEC K AH0 M IY1 K +KMIECIK K AH0 M IY1 CH IH0 K +KNAACK N AA1 K +KNAAK N AA1 K +KNAB N AE1 B +KNABB N AE1 B +KNABE N EY1 B +KNABLE N EY1 B AH0 L +KNACK N AE1 K +KNACKS N AE1 K S +KNACKSTEDT N AE1 K S T IH0 T +KNAGGS N AE1 G Z +KNAPE N EY1 P +KNAPIK N AE1 P IH0 K +KNAPKE N EY1 P K +KNAPP N AE1 P +KNAPP'S N AE1 P S +KNAPPENBERGER N AE1 P AH0 N B ER0 G ER0 +KNAPPER N AE1 P ER0 +KNAPSACK N AE1 P S AE2 K +KNAPTON N AE1 P T AH0 N +KNARR N AE1 R +KNAUB N AO1 B +KNAUER N AW1 ER0 +KNAUF N AO1 F +KNAUFF N AO1 F +KNAUP N AO1 P +KNAUS N AO1 Z +KNAUSS N AO1 S +KNAVE N EY1 V +KNAVES N EY1 V Z +KNBC K EY1 EH1 N B IY1 S IY1 +KNEAD N IY1 D +KNEADING N IY1 D IH0 NG +KNEAFSEY N IY1 F S IY0 +KNEALE N IY1 L +KNEBEL N EH1 B AH0 L +KNECHT N EH1 K T +KNECHTEL N EH1 K T AH0 L +KNEE N IY1 +KNEEBONE N IY1 B OW2 N +KNEECAP N IY1 K AE2 P +KNEECAPS N IY1 K AE2 P S +KNEECE N IY1 S +KNEED N IY1 D +KNEEING N IY1 IH0 NG +KNEEL N IY1 L +KNEELAND N IY1 L AH0 N D +KNEELING N IY1 L IH0 NG +KNEER N IH1 R +KNEES N IY1 Z +KNEIP N IY1 P +KNEISEL N AY1 S AH0 L +KNEISLEY N IY1 S L IY0 +KNELL N EH1 L +KNELLER N EH1 L ER0 +KNELT N EH1 L T +KNEPP N EH1 P +KNEPPER N EH1 P ER0 +KNERR N EH1 R +KNESS N EH1 S +KNESSET N EH1 S AH0 T +KNESSET(1) K N EH1 S AH0 T +KNESSET(2) K AH0 N EH1 S AH0 T +KNEW N UW1 +KNEW(1) N Y UW1 +KNEZEVICH N EH1 Z IH0 V IH0 CH +KNICELY N AY1 S L IY0 +KNICK N IH1 K +KNICK-KNACK N IH1 K N AE1 K +KNICK-KNACKS N IH1 K N AE1 K S +KNICKER N IH1 K ER0 +KNICKERBOCKER N IH1 K ER0 B AA2 K ER0 +KNICKERBOCKERED N IH1 K ER0 B AA2 K ER0 D +KNICKERBOCKERS N IH1 K ER0 B AA2 K ER0 Z +KNICKERS N IH1 K ER0 Z +KNICKKNACK N IH1 K N AE2 K +KNICKKNACKS N IH1 K N AE2 K S +KNICKS N IH1 K S +KNICKS' N IH1 K S +KNIEF N IY1 F +KNIEP N IY1 P +KNIERIEM N IY1 R IY2 M +KNIERIM N IH1 R IH0 M +KNIES N AY1 Z +KNIESS N IY1 S +KNIEVEL K AH0 N IY1 V AH0 L +KNIEVEL(1) N IY1 V AH0 L +KNIFE N AY1 F +KNIFED N AY1 F T +KNIFELIKE N AY1 F L AY2 K +KNIFEPOINT N AY1 F P OY2 N T +KNIFFEN N IH1 F AH0 N +KNIFFIN N IH1 F IH0 N +KNIFING N AY1 F IH0 NG +KNIFINGS N AY1 F IH0 NG Z +KNIGGE N IH1 G +KNIGHT N AY1 T +KNIGHT'S N AY1 T S +KNIGHTED N AY1 T IH0 D +KNIGHTEN N AY1 T AH0 N +KNIGHTHOOD N AY1 T HH UH2 D +KNIGHTLY N AY1 T L IY0 +KNIGHTON N AY1 T AH0 N +KNIGHTS N AY1 T S +KNILL N IH1 L +KNIN K EY1 EH1 N AY1 EH1 N +KNIN(1) K N IH1 N +KNIN(2) N IH1 N +KNIPE N AY1 P +KNIPFER N IH1 P F ER0 +KNIPL N IH1 P AH0 L +KNIPP N IH1 P +KNIPPA N IH1 P AH0 +KNIPPEL N IH1 P AH0 L +KNIPPENBERG N IH1 P AH0 N B ER0 G +KNIPPER N IH1 P ER0 +KNIPPLE N IH1 P AH0 L +KNISELY N AY1 Z L IY0 +KNISKERN N IH1 S K ER0 N +KNISLEY N IH1 S L IY0 +KNISPEL N IH1 S P AH0 L +KNISS N IH1 S +KNIT N IH1 T +KNITS N IH1 T S +KNITTED N IH1 T AH0 D +KNITTED(1) N IH1 T IH0 D +KNITTEL N IH1 T AH0 L +KNITTER N IH1 T ER0 +KNITTING N IH1 T IH0 NG +KNITTLE N IH1 T AH0 L +KNITWEAR N IH1 T W EH2 R +KNIVES N AY1 V Z +KNIVETON N AY1 V T AH0 N +KNOB N AA1 B +KNOBBE N AA1 B +KNOBBY N AA1 B IY0 +KNOBEL N OW1 B AH0 L +KNOBLAUCH N AA1 B L AW0 K +KNOBLE N OW1 B AH0 L +KNOBLOCH N AA1 B L AH0 K +KNOBLOCK N AA1 B L AA0 K +KNOBS N AA1 B Z +KNOCH N AA1 K +KNOCHE N AA1 CH +KNOCHEL N AA1 K AH0 L +KNOCK N AA1 K +KNOCKDOWN N AA1 K D AW2 N +KNOCKED N AA1 K T +KNOCKING N AA1 K IH0 NG +KNOCKOFF N AA1 K AO2 F +KNOCKOFFS N AA1 K AO2 F S +KNOCKOUT N AA1 K AW2 T +KNOCKOUTS N AA1 K AW2 T S +KNOCKS N AA1 K S +KNODE N OW1 D +KNODEL N OW1 D AH0 L +KNODLE N OW1 D AH0 L +KNOEBEL N OW1 B AH0 L +KNOEDLER N OW1 D AH0 L ER0 +KNOEDLER(1) N OW1 D L ER0 +KNOELL N OW1 L +KNOFF N AO1 F +KNOGO N OW1 G OW0 +KNOKE N OW1 K +KNOLES N OW1 L Z +KNOLL N OW1 L +KNOLL'S N OW1 L Z +KNOOP N UW1 P +KNOP N AA1 P +KNOPE N OW1 P +KNOPF N AA1 P F +KNOPF(1) N AA1 F +KNOPP N AA1 P +KNORR N AO1 R +KNOST N AA1 S T +KNOT N AA1 T +KNOTEK N OW1 T IH0 K +KNOTH N AA1 TH +KNOTS N AA1 T S +KNOTT N AA1 T +KNOTT'S N AA1 T S +KNOTTED N AA1 T IH0 D +KNOTTS N AA1 T S +KNOTTY N AA1 T IY0 +KNOUFF N OW1 F +KNOUS N AO1 S +KNOUSE N AW1 S +KNOW N OW1 +KNOW-HOW N OW1 HH AW2 +KNOWED N OW1 D +KNOWER N OW1 ER0 +KNOWING N OW1 IH0 NG +KNOWINGLY N OW1 IH0 NG L IY0 +KNOWLEDGE N AA1 L AH0 JH +KNOWLEDGE(1) N AA1 L IH0 JH +KNOWLEDGEABLE N AA1 L AH0 JH AH0 B AH0 L +KNOWLEDGEABLY N AA1 L IH0 JH AH0 B L IY0 +KNOWLEDGEWARE N AA1 L IH0 JH W EH2 R +KNOWLES N OW1 L Z +KNOWLTON N OW1 L T AH0 N +KNOWN N OW1 N +KNOWNS N OW1 N Z +KNOWS N OW1 Z +KNOX N AA1 K S +KNOX'S N AA1 K S IH0 Z +KNOXVILLE N AA1 K S V IH0 L +KNOY N OY1 +KNUCKLE N AH1 K AH0 L +KNUCKLED N AH1 K AH0 L D +KNUCKLES N AH1 K AH0 L Z +KNUDSEN K N UW1 D S AH0 N +KNUDSEN'S K N UW1 D S AH0 N Z +KNUDSON K N UW1 D S AH0 N +KNUDTSON K N UW1 T S AH0 N +KNUEPPEL K N UW1 P AH0 L +KNUPP K N AH1 P +KNUST K N AH1 S T +KNUT K N AH1 T +KNUTE K N UW1 T +KNUTH K N UW1 TH +KNUTS K N AH1 T S +KNUTSEN N AH1 T S AH0 N +KNUTSON N UW1 T S AH0 N +KNUTZEN N AH1 T Z AH0 N +KO K OW1 +KOALA K OW0 AA1 L AH0 +KOALAS K OW0 AA1 L AH0 Z +KOBA K OW1 B AA0 +KOBACKER K OW1 B AE2 K ER0 +KOBAK K OW1 B AH0 K +KOBAYASHI K OW2 B AA0 Y AA1 SH IY0 +KOBE K OW1 B EY0 +KOBE'S K OW1 B EY0 Z +KOBEL K OW1 B AH0 L +KOBER K OW1 B ER0 +KOBERSTEIN K OW1 B ER0 S T AY0 N +KOBERSTEIN(1) K OW1 B ER0 S T IY0 N +KOBES K OW1 B Z +KOBLE K OW1 B AH0 L +KOBLER K OW1 B AH0 L ER0 +KOBLER(1) K OW1 B L ER0 +KOBREN K AA1 B R AH0 N +KOBRIN K AA1 B R IH0 N +KOBRIN'S K AA1 B R IH0 N Z +KOBS K AA1 B Z +KOBUS K OW1 B AH0 S +KOBY K OW1 B IY0 +KOBYLARZ K AH0 B IH1 L ER0 Z +KOBYLINSKI K AH0 B IH0 L IH1 N S K IY0 +KOBZA K AA1 B Z AH0 +KOCAK K OW1 K AH0 K +KOCH K AO1 CH +KOCH(1) K OW1 K +KOCHAN K AA1 K AH0 N +KOCHANEK K AA1 K AH0 N IH0 K +KOCHANOWSKI K AH0 HH AH0 N AO1 F S K IY0 +KOCHANSKI K AH0 HH AE1 N S K IY0 +KOCHEL K AA1 K AH0 L +KOCHENDORFER K AA1 K IH0 N D AO0 R F ER0 +KOCHER K AO1 CH ER0 +KOCHEVAR K AH0 HH EH1 V ER0 +KOCHIS K AA1 K IH0 S +KOCHMAN K AA1 K M AH0 N +KOCI K OW1 S IY0 +KOCIAN K OW1 SH AH0 N +KOCIEMBA K OW2 S IY0 EH1 M B AH0 +KOCINSKI K AH0 CH IH1 N S K IY0 +KOCIOLEK K OW2 S IY0 OW1 L EH0 K +KOCIS K OW1 S IH0 S +KOCK K AA1 K +KOCOUREK K AH0 K UH1 R EH0 K +KOCSIS K AA1 K S IH0 S +KOCUR K OW1 K ER0 +KOCUR'S K OW1 K ER0 Z +KOCUREK K AH0 K Y UW1 R EH0 K +KODACOLOR K OW1 D AH0 K AH2 L ER0 +KODAK K OW1 D AE2 K +KODAK'S K OW1 D AE2 K S +KODAMA K OW0 D AA1 M AH0 +KODIAK K OW1 D IY0 AE2 K +KODO K OW1 D OW0 +KOEBEL K OW1 B AH0 L +KOEDINGER K OW1 D IH0 NG ER0 +KOEGEL K OW1 G AH0 L +KOEGLER K OW1 G AH0 L ER0 +KOEGLER(1) K OW1 G L ER0 +KOEHL K OW1 L +KOEHLER K OW1 L ER0 +KOEHN K OW1 N +KOEHNE K OW1 N +KOEHNEN K OW1 N AH0 N +KOEKI K OW1 K IY0 +KOELLE K OW1 L +KOELLER K OW1 L ER0 +KOELLING K OW1 L IH0 NG +KOELSCH K OW1 L SH +KOELZER K OW1 L Z ER0 +KOEN K OW1 N +KOENEMAN K AA1 IY0 N M AH0 N +KOENEN K OW1 N AH0 N +KOENIG K ER1 N IH0 G +KOENIGS K ER1 N IH0 G Z +KOENIGSBERG K OW1 N IH0 G Z B ER0 G +KOENIGSFELD K OW1 N IH0 G Z F EH2 L D +KOEP K OW1 P +KOEPKE K OW1 P K +KOEPP K OW1 P +KOEPPE K OW1 P +KOEPPEL K OW1 P AH0 L +KOEPPEN K OW1 P AH0 N +KOEPSEL K OW1 P S EH0 L +KOEPSELL K OW1 P S EH0 L +KOERBER K AO1 R B ER0 +KOERNER K AO1 R N ER0 +KOERNKE K AO1 R N AH0 K IY0 +KOESTER K AO1 S T ER0 +KOESTERS K AO1 S T ER0 Z +KOESTLER K OW1 S T L ER0 +KOESTNER K OW1 S T N ER0 +KOETHER K OW1 DH ER0 +KOETJE K OW1 JH AH0 +KOETTER K OW1 T ER0 +KOETTING K OW1 T IH0 NG +KOFF K AO1 F +KOFFLER K AA1 F AH0 L ER0 +KOFFLER(1) K AA1 F L ER0 +KOFFMAN K AO1 F M AH0 N +KOFI K OW1 F IY0 +KOFLER K OW1 F AH0 L ER0 +KOFLER(1) K OW1 F L ER0 +KOFOED K OW1 F OW0 D +KOFRON K AA1 F R AH0 N +KOFU K OW1 F UW0 +KOGA K OW1 G AH0 +KOGAN K OW1 G AH0 N +KOGEL K OW1 G AH0 L +KOGER K OW1 G ER0 +KOGI K OW1 G IY0 +KOGLER K OW1 G AH0 L ER0 +KOGLER(1) K OW1 G L ER0 +KOGLIN K AA1 G L IH0 N +KOGUT K OW1 G AH0 T +KOGYO K OW1 JH Y OW0 +KOH K OW1 +KOHAN K OW1 HH AA0 N +KOHEN K OW1 AH0 N +KOHL K OW1 L +KOHL'S K OW1 L Z +KOHLBECK K OW1 L B EH2 K +KOHLBERG K OW1 L B ER0 G +KOHLBERG'S K OW1 L B ER0 G Z +KOHLENBERG K OW1 L AH0 N B ER0 G +KOHLER K OW1 L ER0 +KOHLES K OW1 HH AH0 L Z +KOHLHEPP K OW1 L HH IH0 P +KOHLHOFF K OW1 L HH AO2 F +KOHLI K OW1 L IY0 +KOHLMAN K OW1 L M AH0 N +KOHLMANN K OW1 L M AH0 N +KOHLMEIER K OW1 L M AY0 ER0 +KOHLMEYER K OW1 L M AY0 ER0 +KOHLRABI K AO0 L R AA1 B IY0 +KOHLS K OW1 L Z +KOHN K AA1 N +KOHNE K OW1 N +KOHNEN K OW1 N AH0 N +KOHNER K OW1 N ER0 +KOHNKE K AA1 NG K +KOHOUT K OW1 AW0 T +KOHR K AO1 R +KOHRING K AO1 R IH0 NG +KOHRS K AO1 R Z +KOHTARO K OW0 T AA1 R OW0 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K AO1 R IY0 +KORF K AO1 R F +KORFF K AO1 R F +KORFHAGE K AO1 R F HH IH0 JH +KORHONEN K AO1 R HH AH0 N AH0 N +KORINEK K AO1 R IH0 N IH0 K +KORMAN K AO1 R M AH0 N +KORMOS K AO1 R M OW0 Z +KORN K AO1 R N +KORNACKI K ER0 N AA1 T S K IY0 +KORNBERG K AO1 R N B ER0 G +KORNBLUM K AO1 R N B L AH0 M +KORNBLUTH K AO1 R N B L UW0 TH +KORNEGAY K AO1 R N IH0 G EY0 +KORNER K AO1 R N ER0 +KORNFELD K AO1 R N F EH0 L D +KORNHAUSER K AO1 R N HH AW0 Z ER0 +KORNREICH K AO1 R N R AY0 K +KORNS K AO1 N Z +KOROL K AO1 R AO0 L +KOROLOGOS K AO0 R AA2 L OW1 G OW0 S +KORONA K ER0 OW1 N AH0 +KOROTICH K AO1 R AH0 T IH0 CH +KORPELA K ER0 P IY1 L AH0 +KORPI K AO1 R P IY0 +KORRY K AO1 R IY0 +KORRY'S K AO1 R IY0 Z +KORSON K AO1 R S AH0 N +KORT K AO1 R T +KORTE K AO1 R T +KORTEN K AO1 R T AH0 N +KORTH K AO1 R TH +KORTHALS K AO1 R TH AH0 L Z +KORTMAN K AO1 R T M AH0 N +KORTUM K AO1 R T AH0 M +KORTZ K AO1 R T S +KORUNA K AO0 R UW1 N AA2 +KORVA K AO1 R V AA2 +KORVER K AO1 R V ER2 +KORY K AO1 R IY2 +KORYAGIN K AO2 R Y AA1 G IH0 N +KORZENIEWSKI K ER0 Z IH2 N IY0 EH1 F S K IY0 +KORZENIEWSKI(1) K AO2 R Z AH0 N UW1 F S K IY0 +KOS K AA1 S +KOSA K OW1 S AA2 +KOSAK K OW1 S AH0 K +KOSAKOWSKI K AH0 S AH0 K AO1 F S K IY2 +KOSAN K OW1 Z AH0 N +KOSANKE K AA1 S AH0 NG K +KOSANOVICH K AH0 S AE1 N AH0 V IH0 CH +KOSAR K OW1 S ER0 +KOSBERG K AO1 Z B ER0 G +KOSBIE K AA1 Z B IY0 +KOSCH K AO1 SH +KOSCHECK K AO1 S CH EH0 K +KOSCHECK'S K AO1 S CH EH0 K S +KOSCIELNIAK K AH0 S CH IY1 L N IY0 AE0 K +KOSCINSKI K AH0 S CH IH1 N S K IY0 +KOSCO K OW1 S K OW0 +KOSECOFF K OW1 S AH0 K AO0 F +KOSEK K OW1 S EH0 K +KOSEL K OW1 S AH0 L +KOSER K OW1 Z ER0 +KOSH K AA1 SH +KOSHER K OW1 SH ER0 +KOSHERED K OW1 SH ER0 D +KOSHERING K OW1 SH ER0 IH0 NG +KOSHERS K OW1 SH ER0 S +KOSIBA K OW0 S IY1 B AH0 +KOSIER K OW1 S IY0 ER0 +KOSIK K OW1 S IH0 K +KOSIN K OW1 S IH0 N +KOSINSKI K AH0 S IH1 N S K IY0 +KOSKA K OW1 S K AH0 +KOSKELA K AH0 S K IY1 L AH0 +KOSKEY K AA1 S K IY0 +KOSKI K AW1 S K IY0 +KOSKINEN K AA1 S K IH0 N AH0 N +KOSKO K OW1 S K OW0 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R AH0 Z EH1 W AH0 +KOSTRZEWSKI K AO2 S T ER0 Z EH1 W S K IY0 +KOSUB K OW1 S AH0 B +KOSY K OW1 S IY0 +KOSYAKOV K OW1 S Y AA0 K AO0 V +KOSYGIN K OW1 S IH0 G IH0 N +KOSYGIN(1) K OW1 S IY0 G IH0 N +KOT K AA1 T +KOTARA K OW0 T AA1 R AH0 +KOTARSKI K AH0 T AA1 R S K IY0 +KOTAS K OW1 T AH0 Z +KOTCH K AA1 CH +KOTE K OW1 T +KOTECKI K AH0 T EH1 T S K IY0 +KOTEK K OW1 T EH2 K +KOTELES K AA1 T EH0 L EH0 Z +KOTH K AA1 TH +KOTHARI K AA1 TH ER0 IY0 +KOTHE K OW1 DH +KOTILA K AH0 T AY1 L AH0 +KOTLARZ K AA1 T L ER0 Z +KOTLER K OW1 T AH0 L ER0 +KOTLER(1) K AA1 T L ER0 +KOTLOWITZ K AA1 T L AH0 W IH0 T S +KOTO K OW1 T OW0 +KOTOWSKI K AH0 T AO1 F S K IY0 +KOTSONIS K AE2 T S OW1 N AH0 S +KOTSONIS(1) K OW0 T S OW1 N AH0 S +KOTSONIS' K AE2 T S OW1 N AH0 S +KOTSONIS'(1) K OW0 T S OW1 N AH0 S +KOTSONIS'S K AE2 T S OW1 N AH0 S IH0 Z +KOTSONIS'S(1) K OW0 T S OW1 N AH0 S IH0 Z +KOTT K AA1 T +KOTTER K AA1 T ER0 +KOTTKE K AA1 T K IY0 +KOTTLER K AA1 T L ER0 +KOTTWITZ K AA1 T W IH0 T S +KOTULA K AH0 T UW1 L AH0 +KOTZ K AA1 T S +KOTZEBUE K AA1 T S AH0 B Y UW2 +KOUBA K UW1 B AH0 +KOUDELKA K AW0 D EH1 L K AH0 +KOUGH K AW1 +KOUNS K AW1 N Z +KOUNTZ K AW1 N T S +KOURI K OW0 UH1 R IY0 +KOURIL K UW1 R AH0 L +KOUROU K UW1 R UW2 +KOURY K AW1 R IY0 +KOUYATE K AW2 Y AA1 T EY2 +KOVAC K OW1 V AH0 K +KOVACEVIC K AH0 V AH0 CH EH1 V IH0 K +KOVACEVICH K AH0 V AA1 CH IH0 V IH0 CH +KOVACH K OW1 V AA0 K +KOVACH'S K OW1 V AA0 K S +KOVACIC K AH0 V AA1 K IH0 K +KOVACICH K AH0 V AA1 CH IH0 HH +KOVACIK K AA1 V AH0 CH IH0 K +KOVACK K AA1 V AH0 K +KOVACS K OW1 V AE0 K S +KOVAKS K OW1 V AE0 K S +KOVAL K OW1 V AH0 L +KOVALCHIK K AH0 V AA1 L HH IH0 K +KOVALCIK K AA1 V AH0 L CH IH0 K +KOVALESKI K AH0 V AH0 L EH1 S K IY0 +KOVALIK K AH0 V AA1 L IH0 K +KOVALSKY K AH0 V AA1 L S K IY0 +KOVALYOV K OW1 V AA0 L Y AH0 V +KOVAR K OW1 V ER0 +KOVARIK K AH0 V AA1 R IH0 K +KOVATCH K AA1 V AH0 CH +KOVATS K OW1 V AH0 T S +KOVEN K OW1 V AH0 N +KOVER K OW1 V ER0 +KOVERSADA K AH2 V ER0 S AA1 T AH0 +KOVICH K AA1 V IH0 CH +KOWABUNGA K AW2 AH0 B AH1 NG G AH0 +KOWAL K AW1 AH0 L +KOWALCHUK K AW0 AA1 L HH AH0 K +KOWALCZYK K AW1 AH0 L CH IH0 K +KOWALESKI K AW0 AH0 L EH1 S K IY0 +KOWALEWSKI K AW0 AH0 L EH1 F S K IY0 +KOWALIK K AW0 AA1 L IH0 K +KOWALKE K AA1 W AO2 K +KOWALKOWSKI K AA1 W AO0 K AO2 F S K IY0 +KOWALL K AW1 AH0 L +KOWALSKI K AH0 W AA1 L S K IY0 +KOWALSKY K AW0 AA1 L S K IY0 +KOWITZ K AA1 W IH0 T S +KOWNACKI K AW2 N AA1 K IY0 +KOWTOW K AW1 T AW1 +KOWTOW(1) K OW1 T OW1 +KOYAMA K OW0 Y AA1 M AH0 +KOYO K OY1 OW0 +KOZA K OW1 Z AH0 +KOZAK K OW1 Z AH0 K +KOZAKIEWICZ K AH0 Z AA1 K AH0 V IH0 CH +KOZAR K OW1 Z ER0 +KOZBERG K AA1 Z B ER0 G +KOZEL K OW1 Z AH0 L +KOZEMCHAK K OW2 Z EH1 M CH AE2 K +KOZICKI K AH0 Z IH1 T S K IY0 +KOZIEL K AA1 Z IY0 L +KOZIK K OW1 Z IH0 K +KOZIKOWSKI K AH0 Z IH0 K AO1 F S K IY0 +KOZINSKI K AH0 Z IH1 N S K IY0 +KOZIOL K AA1 Z IY0 AO0 L +KOZLIK K AA1 Z L IH0 K +KOZLOFF K AA1 Z L AO0 F +KOZLOSKI K AH0 Z L AW1 S K IY0 +KOZLOW K AA1 Z L OW0 +KOZLOWSKI K AH0 Z L AO1 F S K IY0 +KOZMA K OW1 Z M AH0 +KOZMINSKI K AH0 Z M IH1 N S K IY0 +KOZNOVSKY K AA2 Z N AA1 F S K IY0 +KOZNOVSKY'S K AA2 Z N AA1 F S K IY0 Z +KOZO K OW1 Z OW0 +KOZOL K OW1 Z AH0 L +KOZUB K OW1 Z AH0 B +KOZUCH K AA1 Z AH0 HH +KOZYREV K AA1 Z ER0 EH2 V +KOZYREV'S K AA1 Z ER0 EH2 V Z +KRAAI K R AA1 IY0 +KRAATZ K R AA1 T S +KRABBE K R AE1 B +KRABBENHOFT K R AE1 B IH0 N HH AH0 F T +KRABILL K R AE1 B AH0 L +KRACH K R AE1 CH +KRACHT K R AE1 K T +KRACK K R AE1 K +KRACKE K R AE1 K +KRAEGER K R EH1 G ER0 +KRAEMER K R EH1 M ER0 +KRAEUTLER K R AW1 T L ER0 +KRAFFT K R AE1 F T +KRAFT K R AE1 F T +KRAFT'S K R AE1 F T S +KRAFTWERK K R AE1 F T W ER0 K +KRAGE K R EY1 JH +KRAGER K R EY1 G ER0 +KRAGH K R AE1 G +KRAGT K R AE1 G T +KRAH K R AA1 +KRAHENBUHL K R AA1 IH0 N B AH0 L +KRAHL K R AA1 L +KRAHN K R AE1 N +KRAIN K R EY1 N +KRAJEWSKI K R AY0 EH1 F S K IY0 +KRAJICEK K R AY1 IH0 CH EH0 K +KRAJINA K R AY1 N AH0 +KRAJINA(1) K R AY0 IY1 N AH0 +KRAJINA'S K R AY1 N AH0 Z +KRAJINA'S(1) K R AY0 IY1 N AH0 Z +KRAKER K R EY1 K ER0 +KRAKOW K R AA1 K AW0 +KRAKOW(1) K R AA1 K AA0 V +KRAKOW(2) K R AE1 K AW0 +KRAKOWER K R AE1 K OW0 ER0 +KRAKOWSKI K R AH0 K AO1 F S K IY0 +KRAL K R AE1 L +KRALICEK K R AA1 L IH0 CH EH0 K +KRALIK K R AA1 L IH0 K +KRALL K R AO1 L +KRAM K R AE1 M +KRAMAR K R AE1 M ER0 +KRAMER K R EY1 M ER0 +KRAMER'S K R EY1 M ER0 Z +KRAMLICH K R AE1 M L IH0 K +KRAMM K R AE1 M +KRAMME K R AE1 M +KRAMMER K R AE1 M ER0 +KRAMMES K R AE1 M Z +KRAMP K R AE1 M P +KRAMPE K R AE1 M P +KRANDALL K R AE1 N D AH0 L +KRANE K R EY1 N +KRANER K R EY1 N ER0 +KRANICH K R AE1 N IH0 CH +KRANS K R AE1 N Z +KRANTZ K R AE1 N T S +KRANZ K R AE1 N Z +KRANZLER K R AE1 N Z L ER0 +KRAPELS K R AE1 P AH0 L Z +KRAPF K R AE1 P F +KRAPP K R AE1 P +KRAPRAYOON K R AE1 P R AA0 Y UW0 N +KRAS K R AE1 S +KRASINSKI K R AH0 S IH1 N S K IY0 +KRASKA K R AA1 S K AH0 +KRASNER K R AE1 S N ER0 +KRASNOFF K R AE1 S N AO0 F +KRASNOW K R AA1 S N OW0 +KRASNOYARSK K R AE2 S N AO0 Y AA1 R S K +KRASNY K R AE1 Z N IY0 +KRASOWSKI K R AH0 S AO1 F S K IY0 +KRASS K R AE1 S +KRASZEWSKI K R AH0 SH EH1 F S K IY0 +KRAT K R AE1 T +KRATKY K R AE1 T K IY0 +KRATOCHVIL K R AE1 T AH0 K V AH0 L +KRATOS K R AE1 T AO2 S +KRATT K R AE1 T +KRATZ K R AE1 T S +KRATZER K R EY1 T Z ER0 +KRATZKE K R AE1 T S K IY0 +KRAUER K R AW1 R +KRAUS K R AW1 S +KRAUSE K R AO1 S +KRAUSER K R AW1 S ER0 +KRAUSHAAR K R AW1 SH AA2 R +KRAUSKOPF K R AW1 S K AO0 F +KRAUSS K R AW1 S +KRAUSSE K R AO1 S +KRAUSZ K R AW1 SH +KRAUT K R AW1 T +KRAUTER K R AW1 T ER0 +KRAUTH K R AO1 TH +KRAUTHAMMER K R AW1 T HH AE2 M ER0 +KRAUZE K R AW1 Z +KRAVCHUK K R AA1 V CH UH2 K +KRAVCHUK'S K R AA1 V CH UH2 K Z +KRAVETZ K R AE1 V IH0 T S +KRAVIS K R AE1 V IH0 S +KRAVITZ K R AE1 V IH0 T S +KRAWCCYKIEWI K R AW2 CH IH0 K UW1 IY0 +KRAWCHUK K R AO1 CH AH0 K +KRAWCZAK K R AA1 V CH AE0 K +KRAWCZYK K R AA1 V CH IH0 K +KRAWIEC K R AA1 V IY0 K +KRAWITZ K R AA1 W IH0 T S +KRAY K R EY1 +KRAYNAK K R EY1 N AH0 K +KREAGER K R IY1 G ER0 +KREAMER K R IY1 M ER0 +KREBBS K R EH1 B Z +KREBS K R EH1 B Z +KREBS'S K R EH1 B Z IH0 Z +KREBSBACH K R EH1 B Z B AA0 K +KRECH K R EH1 K +KRECKO K R EH1 K OW0 +KREDIETBANK K R EH0 D IY0 T B AE1 NG K +KREDIT K R EH1 T IH0 T +KREDITANSTALT K R EH0 D IH1 T AH2 N S T AO2 L T +KREEGER K R IY1 G ER0 +KREFT K R EH1 F T +KREG K R EH1 G +KREGEL K R EH1 G AH0 L +KREGER K R IY1 G ER0 +KREH K R EH1 +KREHBIEL K R EH1 B IY0 L +KREHER K R EH1 R +KREICHER K R AY1 K ER0 +KREIDER K R AY1 D ER0 +KREIDLER K R AY1 D AH0 L ER0 +KREIDLER(1) K R AY1 D L ER0 +KREIFELS K R AY1 F AH0 L Z +KREIG K R IY1 G +KREIGER K R AY1 G ER0 +KREILING K R AY1 L IH0 NG +KREIMER K R AY1 M ER0 +KREIN K R EY1 N +KREINER K R AY1 N ER0 +KREIS K R IY1 Z +KREISBERG K R AY1 S B ER0 G +KREISCHER K R AY1 SH ER0 +KREISEL K R AY1 S AH0 L +KREISER K R AY1 S ER0 +KREISHER K R IY1 IH0 SH ER0 +KREISLER K R AY1 S L ER0 +KREISMAN K R AY1 S M AH0 N +KREISS K R AY1 S +KREITER K R AY1 T ER0 +KREITMAN K R AY1 T M AH0 N +KREITNER K R AY1 T N ER0 +KREITZ K R IY1 T S +KREITZBERG K R AY1 T S B ER0 G +KREITZER K R AY1 T Z ER0 +KREJCI K R EH1 JH S IY0 +KRELL K R EH1 L +KREMER K R IY1 M ER0 +KREMERS K R IY1 M ER0 Z +KREMLIN K R EH1 M L AH0 N +KREMLIN(1) K R EH1 M L IH0 N +KREMLIN'S K R EH1 M L IH0 N Z +KREMLINOLOGIST K R EH2 M L IH0 N AA1 L AH0 JH IH0 S T +KREMLINOLOGISTS K R EH2 M L IH0 N AA1 L AH0 JH IH0 S T S +KREMPA K R EH1 M P AH0 +KREMPASKY K R IH0 M P AA1 S K IY0 +KREMPLER K R EH1 M P L ER0 +KREMPLERS K R EH1 M P L ER0 Z +KREN K R EH1 N +KRENEK K R EH1 N IH0 K +KRENGEL K R EH1 NG G AH0 L +KRENIK K R EH1 N IH0 K +KRENKE K R EH1 NG K +KRENN K R EH1 N +KRENTZ K R EH1 N T S +KRENWINKLE K R EH1 N W IH2 NG K AH0 L +KRENWINKLE'S K R EH1 N W IH2 NG K AH0 L Z +KRENZ K R EH1 N Z +KRENZER K R EH1 N Z ER0 +KREPPS K R EH1 P S +KREPS K R EH1 P S +KRESA K R IY1 S ER0 +KRESGE K R EH1 S G IY0 +KRESLOVSKY K R EH0 S L AO1 V S K IY0 +KRESS K R EH1 S +KRESSE K R EH1 S +KRESSER K R EH1 S ER0 +KRESSIN K R EH1 S IH0 N +KRESSLER K R EH1 S L ER0 +KRETCHMAN K R EH1 CH M AH0 N +KRETCHMER K R EH1 CH M ER0 +KRETSCH K R EH1 CH +KRETSCHMAR K R EH1 CH M ER0 +KRETSCHMER K R EH1 CH M ER0 +KRETZ K R EH1 T S +KRETZER K R EH1 T Z ER0 +KRETZSCHMAR K R EH1 CH M ER0 +KREUGER K R OY1 G ER0 +KREUL K R UW1 L +KREUSER K R OY1 S ER0 +KREUTER K R OY1 T ER0 +KREUTZ K R UW1 T S +KREUZER K R UW1 Z ER0 +KREWSON K R UW1 S AH0 N +KREY K R EY1 +KRIBS K R IH1 B Z +KRICHBAUM K R IH1 K B AW0 M +KRICK K R IH1 K +KRIDER K R AY1 D ER0 +KRIDLER K R IH1 D L ER0 +KRIEBEL K R IY1 B AH0 L +KRIEG K R IY1 G +KRIEGEL K R IY1 G AH0 L +KRIEGER K R IY1 G ER0 +KRIEGER'S K R IY1 G ER0 Z +KRIENKE K R IY1 NG K +KRIER K R AY1 ER0 +KRIESE K R IY1 Z +KRIESEL K R IY1 S AH0 L +KRIETE K R IY1 T +KRIGBAUM K R IH1 G B AW2 M +KRIGER K R AY1 G ER0 +KRIGSTEN K R IH1 G S T IH0 N +KRIKALEV K R IH1 K AH0 L EH2 V +KRIKALEV'S K R IH1 K AH0 L EH2 V Z +KRIKORIAN K R IH0 K AO1 R IY0 AH0 N +KRILL K R IH1 L +KRIM K R IH1 M +KRIMINYOK K R IH0 M IH1 N Y AO0 K +KRIMMEL K R IH1 M AH0 L +KRINER K R AY1 N ER0 +KRING K R IH1 NG +KRINGEN K R IH1 NG AH0 N +KRINGLEY K R IH1 NG G L IY0 +KRINGS K R IH1 NG Z +KRINKE K R IH1 NG K +KRINSKY K R IH1 N S K IY0 +KRIS K R IH1 S +KRISCH K R IH1 SH +KRISCHER K R IH1 SH ER0 +KRISE K R AY1 Z +KRISHER K R IH1 SH ER0 +KRISHNA K R IH1 SH N AH0 +KRISHNA(1) K R IY1 SH N AH0 +KRISHNAN K R IH1 SH N AH0 N +KRISKO K R IH1 S K OW0 +KRISPIES K R IH1 S P IY0 Z +KRISS K R IH1 S +KRIST K R IH1 S T +KRISTA K R IH1 S T AH0 +KRISTALL K R IH1 S T AH0 L +KRISTALLNACHT K R IH1 S T AH0 L N AA2 K T +KRISTEN K R IH1 S T AH0 N +KRISTENSEN K R IH1 S T AH0 N S AH0 N +KRISTI K R IH1 S T IY0 +KRISTI'S K R IH1 S T IY0 Z +KRISTIANSEN K R IH1 S CH AH0 N S AH0 N +KRISTIE K R IH1 S T IY0 +KRISTIN K R IH1 S T IH0 N +KRISTINA K R IH0 S T IY1 N AH0 +KRISTINE K R IH0 S T IY1 N +KRISTOF K R IH1 S T AH0 F +KRISTOFF K R IH1 S T AO0 F +KRISTOFFE K R IH1 S T AO0 F +KRISTOFFERSON K R IH2 S T AO1 F ER0 S AH0 N +KRISTOL K R IH1 S T AH0 L +KRISTOL'S K R IH1 S T AH0 L Z +KRISTOPHER K R IH1 S T AH0 F ER0 +KRISTOPHER'S K R IH1 S T AH0 F ER0 Z +KRISTY K R IH1 S T IY0 +KRITZ K R IH1 T S +KRITZER K R IH1 T Z ER0 +KRIVANEK K R IH1 V AH0 N IH0 K +KRIZ K R IH1 Z +KRIZAN K R IH1 Z AH0 N +KRIZEK K R IH1 Z EH0 K +KROB K R AA1 B +KROBOTH K R AA1 B AH0 TH +KROC K R AA1 K +KROC'S K R AA1 K S +KROCK K R AA1 K +KROEBER K R OW1 B ER0 +KROEBER'S K R OW1 B ER0 Z +KROEGER K R OW1 G ER0 +KROEGER'S K R OW1 G ER0 Z +KROEGERS K R OW1 G ER0 Z +KROEKER K R OW1 K ER0 +KROENER K R OW1 N ER0 +KROENING K R AA1 AH0 N IH0 NG +KROENKE K R OW1 NG K +KROES K R OW1 Z +KROESE K R OW1 S +KROEZE K R OW1 Z +KROFT K R AA1 F T +KROG K R AA1 G +KROGER K R OW1 G ER0 +KROGER'S K R OW1 G ER0 Z +KROGH K R OW1 +KROGMAN K R AA1 G M AH0 N +KROGSTAD K R AA1 G S T AH0 D +KROH K R OW1 +KROHN K R OW1 N +KROK K R AA1 K +KROL K R AO1 L +KROLAK K R OW1 L AH0 K +KROLCZYK K R OW1 L CH IH0 K +KROLICK K R AA1 L IH0 K +KROLIKOWSKI K R AH0 L IH0 K AO1 F S K IY0 +KROLL K R AO1 L +KROM K R AA1 M +KROME K R OW1 M +KROMER K R OW1 M ER0 +KROMM K R AA1 M +KRON K R AA1 N +KRONA K R OW1 N AH0 +KRONBERG K R AA1 N B ER0 G +KRONE K R OW1 N AH0 +KRONEN K R OW1 N AH0 N +KRONENBERG K R AA1 N AH0 N B ER0 G +KRONENBERGER K R AA1 N AH0 N B ER0 G ER0 +KRONER K R OW1 N ER0 +KRONICK K R AA1 N IH0 K +KRONISH K R AA1 N IH0 SH +KRONK K R AA1 NG K +KRONOR K R OW1 N ER0 +KRONOS K R OW1 N OW0 S +KRONTZ K R AA1 N T S +KROON K R UW1 N +KROPF K R AA1 P F +KROPP K R AA1 P +KROSS K R AO1 S +KROSSEL K R AO1 S AH0 L +KROTKOV K R AO1 T K AO0 V +KROTZ K R AA1 T S +KROTZER K R OW1 T Z ER0 +KROUNER K R UW1 N ER0 +KROUPA K R UW1 P AH0 +KROUSE K R AW1 S +KROUT K R AW1 T +KROWE K R OW1 +KROWITZ K R AW1 IH0 T S +KROY K R OY1 +KRUCHTEN K R AH1 K T AH0 N +KRUCK K R AH1 K +KRUCKEBERG K R AH1 K B ER0 G +KRUCKENBERG K R AH1 K AH0 N B ER0 G +KRUCZEK K R AH1 CH EH0 K +KRUDMAN K R AH1 D M AH0 N +KRUDMAN'S K R AH1 D M AH0 N Z +KRUEGER K R UW1 G ER0 +KRUER K R UW1 ER0 +KRUG K R AH1 G +KRUGER K R UW1 G ER0 +KRUGERRAND K R UW0 G EH1 R AE0 N D +KRUGH K R AH1 +KRUGMAN K R AH1 G M AH0 N +KRUK K R AH1 K +KRUKOWSKI K R AH0 K AO1 F S K IY0 +KRUL K R AH1 L +KRULL K R AH1 L +KRULWICH K R AH1 L W IH0 CH +KRUM K R AH1 M +KRUMHOLZ K R AH1 M HH OW2 L Z +KRUMM K R AH1 M +KRUMME K R AH1 M +KRUMMEL K R AH1 M AH0 L +KRUMMEL'S K R AH1 M AH0 L Z +KRUMREY K R AH1 M R IY0 +KRUMWIEDE K R AH1 M W IY2 D +KRUPA K R UW1 P AH0 +KRUPICKA K R UW2 P IH1 K AH0 +KRUPINSKI K R AH0 P IH1 N S K IY0 +KRUPKA K R AH1 P K AH0 +KRUPMAN K R AH1 P M AH0 N +KRUPNICK K R AH1 P N IH0 K +KRUPP K R AH1 P +KRUPP'S K R AH1 P S +KRUPPA K R AH1 P AH0 +KRUPSKI K R AH1 P S K IY0 +KRUS K R AH1 S +KRUSCHEV K R UW1 S CH EH2 V +KRUSCHKE K R AH1 SH K +KRUSE K R UW1 Z +KRUSEMARK K R AH1 S IH0 M AA0 R K +KRUSINSKI K R AH0 S IH1 N S K IY0 +KRUSZEWSKI K R AH0 SH EH1 F S K IY0 +KRUSZKA K R AH1 SH K AH0 +KRUSZYNSKI K R AH0 SH IH1 N S K IY0 +KRUTICK K R UW1 T IH2 K +KRUTSINGER K R AH1 T S IH0 N JH ER0 +KRUTTSCHNITT K R AH1 CH N IH0 T +KRUTZ K R AH1 T S +KRUZEL K R UW1 Z AH0 L +KRYCH K R IH1 CH +KRYDER K R AY1 D ER0 +KRYGER K R AY1 G ER0 +KRYGIER K R AY1 G IY0 ER0 +KRYPTON K R IH1 P T AO0 N +KRYPTONIAN K R IH0 P T OW1 N IY2 AH0 N +KRYPTONITE K R IH1 P T OW0 N AY2 T +KRYPTOS K R IH1 P T OW0 S +KRYSIAK K R IH1 S IY0 AE0 K +KRYSTAL K R IH1 S T AH0 L +KRZEMINSKI K R IH0 M IH1 N S K IY0 +KRZYSZTOF K R IY1 S T AO0 F +KRZYSZTOF(1) K R IY1 SH T AO0 F +KRZYWICKI K R IH0 V IH1 T S K IY0 +KRZYZANOWSKI K R IH0 Z AH0 N AO1 F S K IY0 +KSIAZEK K S Y AA1 Z EH0 K +KU K UW1 +KUALA K W AA1 L AH0 +KUAN K W AA1 N +KUBA K Y UW1 B AH0 +KUBACKI K AH0 B AA1 T S K IY0 +KUBALA K AH0 B AA1 L AH0 +KUBALA(1) K UW0 B AA1 L AH0 +KUBAN K Y UW1 B AH0 N +KUBAS K UW1 B AH0 Z +KUBAT K UW1 B AH0 T +KUBE K Y UW1 B +KUBENA K AH0 B IY1 N AH0 +KUBERSKI K UW0 B ER1 S K IY0 +KUBES K UW1 B EH2 S +KUBIAK K UW1 B IY0 AE0 K +KUBIC K Y UW1 B IH0 K +KUBICA K Y UW1 B IH0 K AH0 +KUBICEK K AH1 B IH0 CH EH0 K +KUBICK K Y UW1 B IH0 K +KUBICKI K AH0 B IH1 T S K IY0 +KUBIK K Y UW1 B IH0 K +KUBIN K Y UW1 B IH0 N +KUBINSKI K AH0 B IH1 N S K IY0 +KUBIS K UW1 B IH0 S +KUBISIAK K AH0 B IH1 S IY0 AE0 K +KUBITZ K Y UW1 B IH0 T S +KUBLER K Y UW1 B AH0 L ER0 +KUBLER(1) K Y UW1 B L ER0 +KUBLY K AH1 B L IY0 +KUBO K Y UW1 B OW0 +KUBOTA K UW0 B OW1 T AH0 +KUBRICK K Y UW1 B R IH2 K +KUBRICK'S K Y UW1 B R IH2 K S +KUBY K Y UW1 B IY0 +KUC K AH1 K +KUCAN K Y UW1 K AH0 N +KUCERA K AH0 CH IH1 R AH0 +KUCEWICZ K Y UW1 S IH0 W IH0 T S +KUCH K AH1 CH +KUCHAR K AH1 K ER0 +KUCHARSKI K AH0 CH AA1 R S K IY0 +KUCHENBECKER K AH1 K IH0 N B EH0 K ER0 +KUCHER K AH1 K ER0 +KUCHERA K AH1 CH ER0 AH0 +KUCHERA(1) K UW2 CH EH1 R AH0 +KUCHINSKI K AH0 CH IH1 N S K IY0 +KUCHINSKY K AH0 CH IH1 N S K IY0 +KUCHLER K AH1 K AH0 L ER0 +KUCHLER(1) K AH1 K L ER0 +KUCHMA K UW1 CH M AH0 +KUCHMA'S K UW1 CH M AH0 Z +KUCHTA K AH1 CH T AH0 +KUCINSKI K AH0 CH IH1 N S K IY0 +KUCK K AH1 K +KUCZEK K AH1 CH EH0 K +KUCZYNSKI K AH0 CH IH1 N S K IY0 +KUDER K Y UW1 D ER0 +KUDLA K AH1 D L AH0 +KUDLOW K AH1 D L OW0 +KUDNER K AH1 D N ER0 +KUDOS K UW1 D OW0 S +KUDRNA K AH2 D ER1 N AH0 +KUDZU K AH1 D Z UW0 +KUEBLER K UH1 B AH0 L ER0 +KUEBLER(1) K UH1 B L ER0 +KUECHLER K UH1 K AH0 L ER0 +KUECHLER(1) K UH1 K L ER0 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EH1 L +L.'S EH1 L Z +L.S EH1 L Z +LA L AA1 +LAABS L AA1 B Z +LAACK L AA1 K +LAACO L AA1 K OW0 +LAAKE L AA1 K +LAAKSO L AA1 K S OW0 +LAAS L AA1 Z +LAATSCH L AA1 CH +LAB L AE1 B +LAB'S L AE1 B Z +LABA L AA1 B AH0 +LABADIE L AE1 B AH0 D IY0 +LABAN L EY1 B AH0 N +LABAND L AA0 B AE1 N D +LABANT L AH0 B AE1 N T +LABAR L AH0 B AA1 R +LABARBERA L AA0 B AA0 R B EH1 R AH0 +LABARGE L AE1 B AA0 R JH +LABARR L AH0 B AE1 R +LABARRE L AA0 B AA1 R EY0 +LABAT L AA1 B AA0 T +LABATE L AA1 B EY0 T +LABATON L AE1 B AH0 T AH0 N +LABATT L AH0 B AE1 T +LABATT'S L AH0 B AE1 T S +LABAUVE L AH0 B OW1 V +LABAY L AE1 B EY0 +LABBE L AE1 B +LABE L EY1 B +LABEAU L AH0 B OW1 +LABEL L EY1 B AH0 L +LABEL'S L EY1 B AH0 L Z +LABELED L EY1 B AH0 L D +LABELING L EY1 B AH0 L IH0 NG +LABELING(1) L EY1 B L IH0 NG +LABELL L AH0 B EH1 L +LABELLA L AH0 B EH1 L AH0 +LABELLE L AH0 B EH1 L +LABELLED L EY1 B AH0 L D +LABELS L EY1 B AH0 L Z +LABENSKI L AA0 B EH1 N S K IY0 +LABER L EY1 B ER0 +LABERGE L AA1 B ER0 G +LABIANCA L AA0 B IY0 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L AA0 B R AA1 N K IY0 +LABRECK L AE1 B R IH0 K +LABRECQUE L AH0 B R EH1 K +LABREE L AH0 B R IY1 +LABRIE L AE1 B ER0 IY0 +LABRIOCHE L AA2 B R IY0 OW1 SH +LABRIOLA L AA0 B R IY0 OW1 L AH0 +LABROSSE L AA0 B R OW1 S IY0 +LABS L AE1 B Z +LABS' L AE1 B Z +LABUDA L AH0 B Y UW1 D AH0 +LABUS L AE1 B IH0 S +LABYRINTH L AE1 B ER0 IH2 N TH +LABYRINTHINE L AE2 B ER0 IH1 N TH IY2 N +LAC L AE1 K +LAC'S L AE1 K S +LACAN L AA0 K AA1 N +LACANA L AA0 K AE1 N AH0 +LACASSE L AA0 K AA1 S IY0 +LACAVA L AA0 K AA1 V AH0 +LACAYO L AA0 K EY1 OW0 +LACAZE L AA0 K AA1 Z IY0 +LACCOLITHS L AE1 K AH0 L IH0 TH S +LACE L EY1 S +LACED L EY1 S T +LACEFIELD L EY1 S F IY2 L D +LACER L EY1 S ER0 +LACERATE L AE1 S ER0 EY2 T +LACERATION L AE2 S ER0 EY1 SH AH0 N +LACERATIONS L AE2 S ER0 EY1 SH AH0 N Z +LACERTE L AA0 CH EH1 R T IY0 +LACES L EY1 S AH0 Z +LACES(1) L EY1 S IH0 Z +LACEWELL L EY1 S W EH2 L +LACEY L EY1 S IY0 +LACH L AE1 CH +LACHANCE L AA1 CH AH0 N S +LACHAPELLE L AE1 SH AH0 P AH0 L +LACHARITE L AE1 CH ER0 AY2 T +LACHE L AE1 CH +LACHENBRUCH L AE1 K AH0 N B R UW2 K +LACHER L AE1 K ER0 +LACHICA L AE1 CH IH0 K AH0 +LACHLAN L AE1 K L AH0 N +LACHMAN L AE1 K M AH0 N +LACHMAR L AE1 K M AA0 R +LACHNEY L AE1 K N IY0 +LACHOWICZ L AA1 HH AH0 V IH0 CH +LACHRYMOSE L AE1 K R IY0 M OW2 Z +LACINA L AA0 CH IY1 N AH0 +LACIVITA L AA0 CH IY0 V IY1 T AH0 +LACK L AE1 K +LACKADAISICAL L AE2 K AH0 D EY1 Z IH0 K AH0 L +LACKAWANNA L AE2 K AH0 W AA1 N AH0 +LACKED L AE1 K T +LACKEY L AE1 K IY0 +LACKEYS L AE1 K IY0 Z +LACKIE L AE1 K IY0 +LACKING L AE1 K IH0 NG +LACKLUSTER L AE1 K L AH2 S T ER0 +LACKMAN L AE1 K M AH0 N +LACKNER L AE1 K N ER0 +LACKO L AE1 K OW0 +LACKOVIC L AE1 K AH0 V IH0 K +LACKS L AE1 K S +LACKSADAISCIOUS L AE2 K S AH0 D EY1 S IY0 AH0 S +LACLAIR L AE1 K L ER0 +LACLEDE L AA0 K L IY1 D +LACOCK L AE1 K AH0 K +LACOMB L AE1 K AH0 M +LACOMBE L AA0 K OW1 M B IY0 +LACONIC L AA0 K AA1 N IH0 K +LACONTE L AA0 K OW1 N T IY0 +LACORTE L AA0 K AO1 R T IY0 +LACOSS L AH0 K AA1 S +LACOSSE L AA0 K OW1 S IY0 +LACOSTE L AA0 K AO1 S T +LACOUNT L AH0 K UW1 N T +LACOUR L AH0 K UH1 R +LACOURSE L AH0 K UH1 R S +LACOURSIERE L AE1 K UH0 R S IY0 EH0 R +LACOUTURE L AE1 K UW0 CH ER0 +LACOVARA L AA0 K OW0 V AA1 R AH0 +LACQUER L AE1 K ER0 +LACQUERED L AE1 K ER0 D +LACROIX L AH0 K R OY1 +LACROSS L AH0 K R AO1 S +LACROSSE L AH0 K R AO1 S +LACTASE L AE1 K T EY2 S +LACTATE L AE1 K T EY0 T +LACTATING L AE1 K T EY0 T IH0 NG +LACTATION L AE0 K T EY1 SH AH0 N +LACTEALS L AE1 K T IY2 L Z +LACTER L AE1 K T ER0 +LACTIC L AE1 K T IH0 K +LACTOBACILLUS L AE2 K T OW0 B AH0 S IH1 L AH0 S +LACTONE L AE1 K T OW0 N +LACTOSE L AE1 K T OW0 S +LACY L EY1 S IY0 +LAD L AE1 D +LADA L AA1 D AH0 +LADAKH L AA1 D AH0 K +LADAS L AA1 D AH0 Z +LADBROKE L AE1 D B R OW2 K +LADBROKE'S L AE1 D B R OW2 K S +LADD L AE1 D +LADD'S L AE1 D Z +LADDER L AE1 D ER0 +LADDERS L AE1 D ER0 Z +LADE L EY1 D +LADEHOFF L AE1 D AH0 HH AO0 F +LADEN L EY1 D AH0 N +LADENBURG L EY1 D AH0 N B ER0 G +LADER L EY1 D ER0 +LADEWIG L AE1 D UW0 IH0 G +LADIES L EY1 D IY0 Z +LADIES' L EY1 D IY2 Z +LADING L EY1 D IH0 NG +LADINO L AH0 D IY1 N OW0 +LADISH L AA0 D IH1 SH +LADLE L EY1 D AH0 L +LADLED L EY1 D AH0 L D +LADLES L EY1 D AH0 L Z +LADLEY L AE1 D L IY0 +LADLING L EY1 D L IH0 NG +LADNER L AE1 D N ER0 +LADNIER L AE1 D N IY0 ER0 +LADOUCEUR L AE1 D UW0 S ER0 +LADOW L AE1 D OW0 +LADS L AE1 D Z +LADSON L AE1 D S AH0 N +LADUCA L AA0 D UW1 K AH0 +LADUE L AA1 D W EH0 +LADUKE L AA0 D UW1 K EY0 +LADWIG L AE1 D W IH0 G +LADY L EY1 D IY0 +LADY'S L EY1 D IY0 Z +LADYBIRD L EY1 D IY0 B ER2 D +LADYBUG L EY1 D IY0 B AH2 G +LADYBUGS L EY1 D IY0 B AH2 G Z +LADYLIKE L EY1 D IY0 L AY2 K +LAENDERBANK L AE1 N D ER0 B AE2 NG K +LAEVO L EY1 V OW0 +LAFALCE L AA0 F AE1 L S IY0 +LAFALCE(1) L AH0 F AA1 L S +LAFARGE L AA0 F AA1 R JH +LAFATA L AA0 F AA1 T AH0 +LAFAUCI L AA0 F AO1 CH IY0 +LAFAVE L AH0 F EY1 V +LAFAVOR L AE1 F AH0 V ER0 +LAFAVRE L AH0 F EY1 V ER0 +LAFAYETTE L AA2 F IY0 EH1 T +LAFAYETTE(1) L AA2 F EY0 EH1 T +LAFER L EY1 F ER0 +LAFERRIERE L AE1 F EH0 R Y EH1 R +LAFEVER L AE1 F EH0 V ER0 +LAFEVERS L AE1 F EH0 V ER0 Z +LAFEYETTE L AA2 F IY0 EH1 T +LAFF L AE1 F +LAFFER L AE1 F ER0 +LAFFERTY L AE1 F ER0 T IY0 +LAFFEY L AE1 F IY0 +LAFFIN L AE1 F IH0 N +LAFFITTE L AA0 F IH1 T +LAFFOON L AA0 F UW1 N +LAFITE L AA0 F AY1 T +LAFITTE L AA0 F IH1 T +LAFLAM L AA0 F L AE1 M +LAFLAMME L AA2 F L AE1 M +LAFLECHE L AA0 F L EH1 SH +LAFLER L EY1 F AH0 L ER0 +LAFLER(1) L EY1 F L ER0 +LAFLEUR L AA0 F L ER1 +LAFLIN L AE1 F L IH0 N +LAFOE L AA0 F OW1 +LAFOLLETTE L AA2 F AH0 L EH1 T +LAFON L AE1 F AH0 N +LAFOND L AA0 F AO1 N D +LAFONT L AA0 F AO1 N T +LAFONTAINE L AA2 F AH0 N T EY1 N +LAFONTANT L AA0 F AA1 N T AH0 N T +LAFORCE L AA0 F AO1 R S +LAFOREST L AA0 F AO1 R AH0 S T +LAFORGE L AA0 F AO1 R G +LAFORTE L AA0 F AO1 R T +LAFORTUNE L AA2 F ER0 T UW1 N +LAFOSSE L AA0 F AA1 S +LAFOUNTAIN L AA2 F AA1 N T EY2 N +LAFOUNTAINE L AA2 F AA0 N T EY1 N +LAFOY L AA0 F OY1 +LAFRAMBOISE L AA2 F R AE2 M B W AA1 +LAFRANCE L AA0 F R AE1 N S +LAFRENIERE L AA1 F R IH0 N IY0 EH0 R +LAFRENZ L AE1 F R IH0 N S +LAFUENTE L AA0 F W EH1 N T EY0 +LAG L AE1 G +LAGACE L AA0 G AA1 CH IY0 +LAGAN L AE1 G AH0 N +LAGANA L AA0 G AE1 N AH0 +LAGARDE L AA0 G AA1 R D IY0 +LAGARDERE L AA0 G AA0 R D IH1 R +LAGASSE L AA0 G AA1 S IY0 +LAGATTUTA L AA0 G AA0 T UW1 T AH0 +LAGE L EY1 JH +LAGER L AA1 G ER0 +LAGERFELD L AA1 G ER0 F EH0 L D +LAGERFELD(1) L EY1 G ER0 F EH0 L D +LAGERGREN L EY1 G ER0 G R EH0 N +LAGERQUIST L EY1 G ER0 K W IH0 S T +LAGERSTROM L EY1 G ER0 S T R AH0 M +LAGESSE L AE1 G EH0 S +LAGGARD L AE1 G ER0 D +LAGGARDS L AE1 G ER0 D Z +LAGGED L AE1 G D +LAGGING L AE1 G IH0 NG +LAGLE L EY1 G AH0 L +LAGNADO L AA2 G N AA1 D OW0 +LAGNIAPPE L AE1 NG AA2 P +LAGO L AA1 G OW0 +LAGOMARSINO L AA0 G OW2 M AA0 R S IY1 N OW0 +LAGOON L AH0 G UW1 N +LAGOONS L AH0 G UW1 N Z +LAGOS L EY1 G AO0 S +LAGOW L AE1 G OW0 +LAGRANGE L AE1 G R EY2 N JH +LAGRECA L AA0 G R EH1 K AH0 +LAGROCERIA L AA0 G R OW2 S ER0 IY1 AH2 +LAGROCERIA(1) L AH0 G R OW2 S ER0 IY1 AH2 +LAGRONE L AA0 G R OW1 N IY0 +LAGROW L AE1 G R OW2 +LAGS L AE1 G Z +LAGUARDIA L AH0 G W AA1 R D IY0 AH0 +LAGUE L AA1 G +LAGUNA L AH0 G UW1 N AH0 +LAGUNAS L AH0 G UW1 N AH0 Z +LAHAIE L AE1 HH IY0 +LAHAIE(1) L AH0 HH AY1 +LAHAM L AE1 HH AH0 M +LAHAYE L AE1 HH EY0 +LAHEY L EY1 HH IY0 +LAHIFF L AE1 HH IH0 F +LAHM L AE1 M +LAHMAN L AA1 M AH0 N +LAHMANN L AA1 M AH0 N +LAHN L AE1 N +LAHOOD L AA1 HH UH0 D +LAHORE L AA0 HH AO1 R +LAHR L AA1 R +LAHTI L AA1 T IY0 +LAHUE L AE1 HH Y UW0 +LAI L AY1 +LAIB L EY1 B +LAIBLE L EY1 B AH0 L +LAIBOWITZ L EY1 B AH0 W IH0 T S +LAIBROOK L EY1 B R UH2 K +LAICHE L EY1 CH +LAID L EY1 D +LAIDIG L EY1 D IH0 G +LAIDLAW L EY1 D L AO2 +LAIDLAW'S L EY1 D L AO1 Z +LAIDLER L EY1 D L ER0 +LAIDLEY L EY1 D L IY0 +LAIL L EY1 L +LAIMBEER L EY2 M B IH1 R +LAIN L EY1 N +LAINE L EY1 N +LAING L AA1 IH0 NG +LAINHART L AY1 N HH AA0 R T +LAINO L EY1 N OW0 +LAIR L EH1 R +LAIRD L EH1 R D +LAIRMORE L EH1 R M AO0 R +LAIRSON L EH1 R S AH0 N +LAIS L EY1 Z +LAISSEZ L EH1 Z EY2 +LAISSEZ(1) L EY1 Z EY2 +LAIT L EY1 +LAITINEN L AY1 T IH0 N AH0 N +LAITY L EY1 AH0 T IY0 +LAJEUNE L AA0 JH AH1 N +LAJEUNESSE L AA0 JH AH1 N EH0 S +LAJOIE L AA1 JH W AA0 +LAJOUS L AH0 ZH UW1 S +LAK L AE1 K +LAKATOS L AE1 K AH0 T OW0 Z +LAKE L EY1 K +LAKE'S L EY1 K S +LAKEBERG L EY1 K B ER0 G +LAKEFIELD L EY1 K F IY2 L D +LAKEFRONT L EY1 K F R AH2 N T +LAKELAND L EY1 K L AH0 N D +LAKEMAN L EY1 K M AH0 N +LAKER L EY1 K ER0 +LAKERS L EY1 K ER0 Z +LAKES L EY1 K S +LAKES' L EY1 K S +LAKESHORE L EY1 K SH AO2 R +LAKESIDE L EY1 K S AY2 D +LAKEVIEW L EY1 K V Y UW2 +LAKEWOOD L EY1 K W UH2 D +LAKEY L EY1 K IY0 +LAKIN L AE1 K IH0 N +LAKINS L AE1 K IH0 N Z +LAKOTA L AA0 K OW1 T AH0 +LAKOTAS L AA0 K OW1 T AH0 Z +LAKOTAS' L AA0 K OW1 T AH0 Z +LAKSHAMANAN L AE0 K SH AH0 M AA1 N AH0 N +LAKSHAMANAN'S L AE0 K SH AH0 M AA1 N AH0 N Z +LAL L AE1 L +LALA L AA1 L AH0 +LALANDE L AA0 L AA1 N D IY0 +LALAS L AA1 L AH0 S +LALIBERTE L AA0 L IY0 B EH1 R T IY0 +LALIT L AH0 L IY1 T +LALITA L AH0 L IY1 T AH0 +LALITESH L AA1 L IH2 T EH2 SH +LALL L AO1 L +LALLA L AE1 L AH0 +LALLERA L AH0 L EH1 R AH0 +LALLEY L AE1 L IY0 +LALLI L AE1 L IY0 +LALLIE L AO1 L IY0 +LALLIER L AE1 L IY0 ER0 +LALLO L AE1 L OW0 +LALLY L AE1 L IY0 +LALONDE L AA0 L OW1 N D IY0 +LALONE L AA0 L OW1 N IY0 +LALOR L AE0 L AO1 R +LAM L AE1 M +LAMA L AA1 M AH0 +LAMA'S L AA1 M AH0 Z +LAMACCHIA L AA0 M AA1 K IY0 AH0 +LAMAGNA L AA0 M AA1 G N AA0 +LAMAGNA(1) L AA0 M AA1 N Y AA0 +LAMAIST L AA1 M AY0 IH0 S T +LAMAMRA L AA0 M AA1 M R AA0 +LAMAN L EY1 M AH0 N +LAMANNA L AE1 M IH0 N AH0 +LAMANTIA L AA0 M AA1 N SH AH0 +LAMAR L AA0 M AA1 R +LAMAR'S L AA0 M AA1 R Z +LAMARCA L AA0 M AA1 R K AH0 +LAMARCHE L AA0 M AA1 R K IY0 +LAMARR L AA0 M AA1 R +LAMARRE L AA0 M AA1 R +LAMARRE(1) L AA0 M AA1 R IY0 +LAMARTINA L AA0 M AA0 R T IY1 N AH0 +LAMAS L AA1 M AH0 Z +LAMASTER L AA1 M AE0 S T ER0 +LAMASTUS L AE1 M AH0 S T IH0 S +LAMATTINA L AA0 M AA0 T IY1 N AH0 +LAMAUR L AH0 M AO1 R +LAMAY L AE1 M EY0 +LAMB L AE1 M +LAMB'S L AE1 M Z +LAMBASTE L AE2 M B AE1 S T +LAMBASTE(1) L AE2 M B EY1 S T +LAMBASTED L AE2 M B AE1 S T IH0 D +LAMBASTED(1) L AE2 M B EY1 S T IH0 D +LAMBASTES L AE2 M B AE1 S T S +LAMBASTES(1) L AE2 M B EY1 S T S +LAMBASTES(2) L AE2 M B AE1 S +LAMBASTES(3) L AE2 M B EY1 S +LAMBASTING L AE0 M B EY1 S T IH0 NG +LAMBDA L AE1 M D AH0 +LAMBDIN L AE1 M D IH0 N +LAMBE L AE1 M +LAMBEAU L AE0 M B OW1 +LAMBERG L AE1 M B ER0 G +LAMBERSON L AE1 M B ER0 S AH0 N +LAMBERT L AE1 M B ER0 T +LAMBERT'S L AE1 M B ER0 T S +LAMBERTH L AE1 M B ER0 TH +LAMBERTI L AA0 M B EH1 R T IY0 +LAMBERTO L AA0 M B EH1 R T OW2 +LAMBERTON L AE1 M B ER0 T AH0 N +LAMBERTSON L AE1 M B ER0 T S AH0 N +LAMBERTY L AE1 M B ER0 T IY0 +LAMBETH L AE1 M B IH0 TH +LAMBIASE L AA0 M B IY0 AA1 S IY0 +LAMBIE L AE1 M B IY0 +LAMBING L AE1 M IH0 NG +LAMBORGHINI L AE2 M B ER0 G IY1 N IY0 +LAMBORGHINI'S L AE2 M B ER0 G IY1 N IY0 Z +LAMBORGHINIS L AE2 M B ER0 G IY1 N IY0 Z +LAMBORN L AH0 M B AO1 R N +LAMBOY L AE1 M B OY2 +LAMBREAU L AE0 M B R OW1 +LAMBRECHT L AE1 M B R IH0 K T +LAMBRIGHT L AE1 M B R AY2 T +LAMBRO L AE1 M B R OW0 +LAMBROS L AE1 M B R OW0 Z +LAMBS L AE1 M Z +LAMBS' L AE1 M Z +LAMBSDORFF L AE1 M Z D AO0 R F +LAMBSON L AE1 M S AH0 N +LAMBY L AE1 M B IY0 +LAME L EY1 M +LAMELLAR L AH0 M EH1 L ER0 +LAMELY L EY1 M L IY0 +LAMENDOLA L AA0 M EH0 N D OW1 L AH0 +LAMENT L AH0 M EH1 N T +LAMENTABLE L AH0 M EH1 N T AH0 B AH0 L +LAMENTED L AH0 M EH1 N T IH0 D +LAMENTING L AH0 M EH1 N T IH0 NG +LAMENTS L AH0 M EH1 N T S +LAMER L EY1 M ER0 +LAMERE L AA0 M EH1 R EY0 +LAMERS L EY1 M ER0 Z +LAMESA L AA0 M EY1 S AH0 +LAMETA L AH0 M EH1 T AH0 +LAMEY L EY1 M IY0 +LAMIA L EY1 M IY0 AH0 +LAMICA L AE1 M IH0 K AH0 +LAMIE L EY1 M IY0 +LAMINA L AE1 M AH0 N AH0 +LAMINACK L AE1 M IH0 N AH0 K +LAMINAR L AE1 M IH0 N ER0 +LAMINATE L AE1 M AH0 N AH0 T +LAMINATE(1) L AE1 M AH0 N EY2 T +LAMINATED L AE1 M AH0 N EY2 T AH0 D +LAMINATES L AE1 M AH0 N AH0 T S +LAMINATING L AE1 M AH0 N EY2 T IH0 NG +LAMINE L AH0 M IY1 N +LAMINE'S L AH0 M IY1 N Z +LAMINER L AE1 M AH0 N ER0 +LAMINNE L AH0 M IH1 N +LAMIRANDE L AA0 M IH0 R AA1 N D IY0 +LAMISON L AE1 M IH0 S AH0 N +LAMKE L AE1 M K IY0 +LAMKIN L AE1 M K IH0 N +LAMLE L AE1 M L IY0 +LAMM L AE1 M +LAMM'S L AE1 M Z +LAMME L AE1 M +LAMMERS L AE1 M ER0 Z +LAMMERT L AE1 M ER0 T +LAMMEY L AE1 M IY0 +LAMMI L AE1 M IY0 +LAMMON L AE1 M AH0 N +LAMMOND L AE1 M AH0 N D +LAMMONS L AE1 M AH0 N Z +LAMON L AA0 M AO1 N +LAMOND L AH0 M AA1 N D +LAMONICA L AA0 M OW0 N IY1 K AH0 +LAMONS L AA1 M OW0 N Z +LAMONT L AH0 M AA1 N T +LAMONTAGNE L AA2 M AA0 N T EY1 N +LAMONTE L AA0 M AA1 N T +LAMORA L AA0 M AO1 R AH0 +LAMORE L AA1 M AO0 R +LAMOREAUX L AE1 M ER0 OW0 +LAMOREUX L AE1 M ER0 OW0 +LAMORTE L AA0 M AO1 R T IY0 +LAMOS L AA1 M OW0 S +LAMOTHE L AA1 M AO0 DH +LAMOTT L AH0 M AA1 T +LAMOTTA L AA0 M OW1 T AH0 +LAMOTTE L AH0 M AO1 T +LAMOUNTAIN L AE1 M UW0 N T EY0 N +LAMOUREAUX L AA1 M UH0 R OW0 +LAMOUREUX L AA1 M UH0 R OW0 +LAMP L AE1 M P +LAMPE L AE1 M P +LAMPERT L AE1 M P ER2 T +LAMPF L AE1 M P F +LAMPHEAR L AE1 M HH ER0 +LAMPHERE L AE1 M F ER0 +LAMPHIER L AE1 M F IY0 ER0 +LAMPI L AE1 M P IY0 +LAMPING L AE1 M P IH0 NG +LAMPKIN L AE1 M P K IH0 N +LAMPKINS L AE1 M P K IH0 N Z +LAMPL L AE1 M P AH0 L +LAMPLEY L AE1 M P L IY0 +LAMPLIGHTER L AE1 M P L AY2 T ER0 +LAMPLIGHTER'S L AE1 M P L AY2 T ER0 Z +LAMPLIGHTERS L AE1 M P L AY2 T ER0 Z +LAMPMAN L AE1 M P M AH0 N +LAMPO L AE1 M P OW0 +LAMPOON L AE0 M P UW1 N +LAMPOON'S L AE0 M P UW1 N Z +LAMPOONED L AE0 M P UW1 N D +LAMPORT L AE1 M P AO2 R T +LAMPP L AE1 M P +LAMPPOST L AE1 M P P OW2 S T +LAMPPOST(1) L AE1 M P OW2 S T +LAMPPOSTS L AE1 M P P OW2 S T S +LAMPREY L AE1 M P R IY0 +LAMPREYS L AE1 M P R IY0 Z +LAMPRON L AE1 M P R AH0 N +LAMPROS L AE1 M P R OW0 Z +LAMPS L AE1 M P S +LAMPSON L AE1 M P S AH0 N +LAMPTON L AE1 M P T AH0 N +LAMSON L AE1 M S AH0 N +LAMSTON L AE1 M S T AH0 N +LAMY L EY1 M IY0 +LAN L AE1 N +LANA L AE1 N AH0 +LANAGAN L AE1 N AH0 G AE0 N +LANAHAN L AE1 N AH0 HH AE0 N +LANAI L AH0 N AY1 +LANAI_CITY L AH0 N AY1 S IH2 T IY0 +LANASA L AA0 N AA1 S AH0 +LANCASHIRE L AE1 NG K AH0 SH AY2 R +LANCASTER L AE1 N K AE2 S T ER0 +LANCASTER(1) L AE1 NG K 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G W IH1 S T IH0 K S +LINGUISTS L IH1 NG G W IH0 S T S +LINGUS L IH1 NG G AH0 S +LINH L IH1 N +LINHARDT L IH1 N HH AA2 R T +LINHARES L IH1 N HH ER0 Z +LINHART L IH1 N HH AA2 R T +LINI L IY1 N IY0 +LINING L AY1 N IH0 NG +LININGER L AY1 N IH0 NG ER0 +LININGS L AY1 N IH0 NG Z +LINK L IH1 NG K +LINK'S L IH1 NG K S +LINKAGE L IH1 NG K AH0 JH +LINKAGE(1) L IH1 NG K IH0 JH +LINKAGES L IH1 NG K IH0 JH IH0 Z +LINKE L IH1 NG K +LINKED L IH1 NG K T +LINKEDIN L IH1 NG K T IH2 N +LINKENHOKER L IH1 NG K IH0 N HH AH0 K ER0 +LINKER L IH1 NG K ER0 +LINKING L IH1 NG K IH0 NG +LINKLETTER L IH1 NG K L EH2 T ER0 +LINKOUS L IH1 NG K AH0 S +LINKS L IH1 NG K S +LINKUP L IH1 NG K AH2 P +LINKUPS L IH1 NG K AH2 P S +LINLEY L IH1 N L IY0 +LINN L IH1 N +LINNANE L IH1 N AH0 N +LINNAS L IH1 N AH0 S +LINNE L IH1 N +LINNEA L IH1 N IY0 AH0 +LINNEHAN L IH1 N IH0 HH AE0 N +LINNELL L IH1 N AH0 L +LINNEMAN L IH1 N M AH0 N +LINNEMANN L IH1 N M AH0 N +LINNET L IH1 N IH0 T +LINNEY L IH1 N IY0 +LINNIK L IH1 N IH0 K +LINO L IY1 N OW0 +LINOLEUM L AH0 N OW1 L IY0 AH0 M +LINOTYPE L IH1 N OW0 T AY2 P +LINOWES L IH1 N OW0 Z +LINQUIST L IH1 N K W IH0 S T +LINS L IH1 N Z +LINSAY L IH1 N S EY0 +LINSCOMB L IH1 N S K AH0 M +LINSCOTT L IH1 N S K AH0 T +LINSE L IH1 N S +LINSEED L IH1 N S IY2 D +LINSEY L IH1 N Z IY0 +LINSEY-WOOLSEY L IH1 N Z IY0 W UH1 L Z IY0 +LINSKEY L IH1 N S K IY0 +LINSKY L IH1 N S K IY0 +LINSLEY L IH1 N S L IY0 +LINSON L IH1 N S AH0 N +LINSTROM L IH1 N S T R AH0 M +LINT L IH1 N T +LINTAS L IH1 N T AH0 S +LINTEL L IH1 N T AH0 L +LINTERS L IH1 N T ER0 Z +LINTHICUM L IH1 N TH IH0 K AH0 M +LINTNER L IH1 N T N ER0 +LINTON L IH1 N T AH0 N +LINTZ L IH1 N T S +LINUS L AY1 N AH0 S +LINUX L IH1 N AH0 K S +LINVILLE L IY1 N V IH0 L +LINWICK L IH1 N W IH2 K +LINWOOD L IH1 N W UH2 D +LINZ L IH1 N Z +LINZER L IH1 N Z ER0 +LINZEY L IH1 N Z IY0 +LINZY L IH1 N Z IY0 +LIOMINE L IY1 AH0 M AY0 N +LION L AY1 AH0 N +LION'S L AY1 AH0 N Z +LIONBERGER L AY1 AH0 N B ER0 G ER0 +LIONEL L AY1 AH0 N AH0 L +LIONETTI L IY0 AH0 N EH1 T IY0 +LIONETTI(1) L AY0 AH0 N EH1 T IY0 +LIONHEART L AY1 AH0 N HH AA2 R T +LIONIZE L AY1 AH0 N AY2 Z +LIONIZED L AY1 AH0 N AY2 Z D +LIONS L AY1 AH0 N Z +LIONS' L AY1 AH0 N Z +LIOTIER L IY0 OW1 T IY0 EY2 +LIOTIER(1) L IY0 OW1 T IY0 ER0 +LIOTTA L IY0 OW1 T AH0 +LIOU L IY0 UW1 +LIP L IH1 P +LIPA L IY1 P AH0 +LIPARI L IY0 P AA1 R IY0 +LIPE L AY1 P +LIPFORD L IH1 P F ER0 D +LIPHAM L IH1 F AH0 M +LIPID L AY1 P AH0 D +LIPIDE L IH0 P IY1 D +LIPIDS L IH1 P IH0 D Z +LIPINSKI L IH0 P IH1 N S K IY0 +LIPKA L IH1 P K AH0 +LIPKE L IH1 P K +LIPKIN L IH1 P K IH0 N +LIPKIND L IH1 P K IH0 N D +LIPKIND(1) L IH1 P K AY0 N D +LIPMAN L IH1 P M AH0 N +LIPNICK L IH1 P N IH2 K +LIPOPROTEIN L IH2 P AH0 P R OW1 T IY0 N +LIPOPROTEINS L IH2 P OW0 P R OW1 T IY0 N Z +LIPOSOME L IH1 P AH0 S OW2 M +LIPOSOMES L IH1 P AH0 S OW2 M Z +LIPOSUCTION L IH1 P OW0 S AH2 K SH AH0 N +LIPOSUCTION(1) L AY1 P OW0 S AH2 K SH AH0 N +LIPOVSKY L IH0 P AA1 V S K IY0 +LIPP L IH1 P +LIPPA L IH1 P AH0 +LIPPARD L IH1 P ER0 D +LIPPE L IH1 P +LIPPED L IH1 P T +LIPPENS L IH1 P AH0 N Z +LIPPER L IH1 P ER0 +LIPPER'S L IH1 P ER0 Z +LIPPERT L IH1 P ER0 T +LIPPI L IH1 P IY0 +LIPPINCOTT L IH1 P IH0 N K AH0 T +LIPPITT L IH1 P IH0 T +LIPPMAN L IH1 P M AH0 N +LIPPMANN L IH1 P M AH0 N +LIPPO L IH1 P OW0 +LIPPOLD L IH1 P OW2 L D +LIPPS L IH1 P S +LIPPY L IH1 P IY0 +LIPS L IH1 P S +LIPS' L IH1 P S +LIPSCHITZ L IH1 P SH IH0 T S +LIPSCHULTZ L IH1 P SH AH0 L T S +LIPSCHUTZ L IH1 P SH AH0 T S +LIPSCOMB L IH1 P S K AH0 M +LIPSETT L IH1 P S IH0 T +LIPSEY L IH1 P S IY0 +LIPSHIE L IH1 P SH IY0 +LIPSHUTZ L IH1 P SH AH0 T S +LIPSIG L IH1 P S IH0 G +LIPSITZ L IH1 P S IH0 T S +LIPSKI L IH1 P S K IY2 +LIPSKY L IH1 P S K AY2 +LIPSON L IH1 P S AH0 N +LIPSTEIN L IH1 P S T IY2 N +LIPSTEIN(1) L IH1 P S T AY2 N +LIPSTICK L IH1 P S T IH2 K +LIPSTICKS L IH1 P S T IH2 K S +LIPTAK L IH1 P T AH0 K +LIPTON L IH1 P T AH0 N +LIPTON'S L IH1 P T AH0 N Z +LIPUMA L IY0 P UW1 M AH0 +LIQUEFACTION L IH2 K W AH0 F AE1 K SH AH0 N +LIQUEFIED L IH1 K W AH0 F AY2 D +LIQUEFY L IH1 K W AH0 F AY2 +LIQUEUR L IH0 K ER1 +LIQUEURS L IH0 K ER1 Z +LIQUID L IH1 K W AH0 D +LIQUID(1) L IH1 K W IH0 D +LIQUIDATE L IH1 K W IH0 D EY2 T +LIQUIDATED L IH1 K W IH0 D EY2 T IH0 D +LIQUIDATES L IH1 K W IH0 D EY2 T S +LIQUIDATING L IH1 K W IH0 D EY2 T IH0 NG +LIQUIDATION L IH2 K W IH0 D EY1 SH AH0 N +LIQUIDATIONS L IH2 K W IH0 D EY1 SH AH0 N Z +LIQUIDATOR L IH1 K W IH0 D EY2 T ER0 +LIQUIDATORS L IH1 K W IH0 D EY2 T ER0 Z +LIQUIDE L IH0 K W AY1 D +LIQUIDITIES L IH0 K W IH1 D AH0 T IY0 Z +LIQUIDITY L IH0 K W IH1 D AH0 T IY0 +LIQUIDITY(1) L IH0 K W IH1 D IH0 T IY0 +LIQUIDS L IH1 K W AH0 D Z +LIQUIDS(1) L IH1 K W IH0 D Z +LIQUN L IH0 K UW1 N +LIQUOR L IH1 K ER0 +LIQUORI L IY0 K AO1 R IY0 +LIQUORS L IH1 K ER0 Z +LIRA L IH1 R AH0 +LIRA'S L IH1 R AH0 Z +LIRE L IH1 R AH0 +LIRETTE L ER0 EH1 T +LIRO L IH1 R OW0 +LIROFF L IH1 R AO0 F +LIS L IH1 S +LISA L IY1 S AH0 +LISA'S L IY1 S AH0 Z +LISABET L IH1 S AH0 B EH0 T +LISABETH L IH1 S AH0 B EH0 TH +LISAK L IH1 S AH0 K +LISANTI L IH0 S AE1 N T IY0 +LISBETH L IH1 S B IH0 TH +LISBON L IH1 Z B AH0 N +LISBY L IH1 S B IY0 +LISCO L IH1 S K OW0 +LISCOM L IH1 S K AH0 M +LISE L AY1 Z +LISEC L IH1 Z AH0 K +LISENBEE L IH0 S EH1 N B IY0 +LISENBEE(1) L IH1 S AH0 N B IY0 +LISENBY L IH1 S IH0 N B IY0 +LISETTE L IH0 S EH1 T +LISH L IH1 SH +LISHMAN L IH1 SH M AH0 N +LISI L IY1 S IY0 +LISIECKI L IH0 S IY1 T S K IY0 +LISK L IH1 S K +LISKA L IH1 S K AH0 +LISKE L IH1 S K +LISKEY L IH1 S K IY0 +LISKO L IH1 S K OW0 +LISLE L AY1 AH0 L +LISMAN L IH1 Z M AH0 N +LISOWSKI L IH0 S AO1 F S K IY0 +LISP L IH1 S P +LISS L IH1 S +LISSA L IH1 S AH0 +LISSACK L IH1 S AH0 K +LISSIE L IH1 S IY0 +LISSNER L IH1 S N ER0 +LISSOUBA L IH0 S UW1 B AH0 +LISSY L IH1 S IY0 +LIST L IH1 S T +LIST'S L IH1 S T S +LISTED L IH1 S T AH0 D +LISTED(1) L IH1 S T IH0 D +LISTEN L IH1 S AH0 N +LISTENED L IH1 S AH0 N D +LISTENER L IH1 S AH0 N ER0 +LISTENER(1) L IH1 S N ER0 +LISTENERS L IH1 S AH0 N ER0 Z +LISTENERS(1) L IH1 S N ER0 Z +LISTENING L IH1 S AH0 N IH0 NG +LISTENING(1) L IH1 S N IH0 NG +LISTENS L IH1 S AH0 N Z +LISTER L IH1 S T ER0 +LISTERIA L IH0 S T IH1 R IY0 AH0 +LISTERINE L IH1 S T ER0 IY2 N +LISTERINES L IH1 S T ER0 IY2 N Z +LISTING L IH1 S T IH0 NG +LISTINGS L IH1 S T IH0 NG Z +LISTLESS L IH1 S T L AH0 S +LISTLESSLY L IH1 S T L AH0 S L IY0 +LISTON L IH1 S T AH0 N +LISTS L IH1 S T S +LISZEWSKI L IH0 SH EH1 F S K IY0 +LISZKA L IH1 SH K AH0 +LISZT L IH1 S T +LIT L IH1 T +LITA L IY1 T AH0 +LITAKER L IH1 T EY0 K ER0 +LITALIEN L IH1 T AH0 L IY0 N +LITAN L AY1 T AH0 N +LITANIES L IH1 T AH0 N IY0 Z +LITANY L IH1 T AH0 N IY0 +LITARO L IH0 T AA1 R OW0 +LITCHFIELD L IH1 CH F IY0 L D +LITCHFIELD'S L IH1 CH F IY0 L D Z +LITCHFORD L IH1 CH F ER0 D +LITCHFORD'S L IH1 CH F ER0 D Z +LITCO L IH1 T K OW2 +LITCO'S L IH1 T K OW2 Z +LITE L AY1 T +LITEM L AY1 T EH0 M +LITEM(1) L IY1 T EH0 M +LITER L IY1 T ER0 +LITERACY L IH1 T ER0 AH0 S IY0 +LITERAL L IH1 T ER0 AH0 L +LITERALLY L IH1 T ER0 AH0 L IY0 +LITERALLY(1) L IH1 T R AH0 L IY0 +LITERARY L IH1 T ER0 EH2 R IY0 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L IH0 V OW1 N Y AH0 +LIVOR L IH0 V AO1 R +LIVOTI L IY0 V OW1 T IY0 +LIVSEY L IH1 V Z IY0 +LIVVIE L IH1 V IY0 +LIZ L IH1 Z +LIZ'S L IH1 Z AH0 Z +LIZA L IY1 Z AH0 +LIZABETH L IH1 Z AH0 B EH0 TH +LIZAK L IH1 Z AH0 K +LIZARD L IH1 Z ER0 D +LIZARD'S L IH1 Z ER0 D Z +LIZARDS L IH1 Z ER0 D Z +LIZARRAGA L IY0 Z AA0 R AA1 G AH0 +LIZHI L IH1 Z IY0 +LIZOTTE L IH0 Z AO1 T +LIZZIE L IH1 Z IY0 +LIZZY L IH1 Z IY0 +LJUBLJANA L Y UW1 B L Y AA0 N AH0 +LJUBOMIR L Y UW1 B OW0 M IH2 R +LLAMA L AA1 M AH0 +LLAMAS L AA1 M AH0 Z +LLANA L AE1 N AH0 +LLANAS L AE1 N AH0 Z +LLANES L EY1 N Z +LLANO L AA1 N OW0 +LLANOS L AA1 N OW0 Z +LLANVIEW L AA2 N V Y UW1 +LLC EH2 L EH2 L S IY2 +LLERENA L EH0 R EY1 N AH0 +LLEWELLYN L UW2 EH1 L IH0 N +LLEWELYN L UW1 IH0 L IH0 N +LLORENS L AO0 R EH0 N Z +LLORENTE L AO0 R EH1 N T EY0 +LLOSA L OW1 S AH0 +LLOSA'S L OW1 S AH0 Z +LLOVIO L OW1 V IY0 OW0 +LLOYD L OY1 D +LLOYD'S L OY1 D Z +LLOYDS L OY1 D Z +LLOYDS' L OY1 D Z +LN L EY1 N +LO L OW1 +LO'S L OW1 Z +LOAD L OW1 D +LOADED L OW1 D 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N +MAGAN M EY1 G AH0 N +MAGANA M AA0 G AE1 N AH0 +MAGAR M AE1 G ER0 +MAGARIAN M AH0 G EH1 R IY0 AH0 N +MAGAW M AE1 G AO0 +MAGAZINE M AE1 G AH0 Z IY2 N +MAGAZINE'S M AE1 G AH0 Z IY2 N Z +MAGAZINER M AE2 G AH0 Z IY1 N ER0 +MAGAZINER'S M AE2 G AH0 Z IY1 N ER0 Z +MAGAZINES M AE1 G AH0 Z IY2 N Z +MAGAZINES' M AE1 G AH0 Z IY2 N Z +MAGBY M AE1 G B IY0 +MAGDA M AE1 G D AH0 +MAGDALA M AA0 G D AA1 L AH0 +MAGDALEN M AE1 G D AH0 L AH0 N +MAGDALENA M AE2 G D AH0 L IY1 N AH0 +MAGDALENE M AE1 G D AH0 L IY2 N +MAGDALENO M AA0 G D AA0 L EY1 N OW0 +MAGEE M AH0 G IY1 +MAGEL M AE1 G AH0 L +MAGELLAN M AH0 JH EH1 L AH0 N +MAGELLAN'S M AH0 JH EH1 L AH0 N Z +MAGELLANIC M AE2 JH AH0 L AE1 N IH0 K +MAGENTA M AH0 JH EH1 N T AH0 +MAGER M AE1 G ER0 +MAGER(1) M EY1 G ER0 +MAGERMAN M AE1 G ER0 M AH0 N +MAGERS M AE1 G ER0 Z +MAGES M EY1 JH IH0 Z +MAGGARD M AE1 G ER0 D +MAGGART M AE1 G ER0 T +MAGGI M AE1 JH IY2 +MAGGIE M AE1 G IY2 +MAGGIE'S M AE1 G IY2 Z +MAGGIO M AA1 JH IY2 OW0 +MAGGOT M AE1 G AH0 T +MAGGOTS M AE1 G AH0 T S +MAGGS M AE1 G Z +MAGI M EY1 JH AY0 +MAGIC M AE1 JH IH0 K +MAGIC'S M AE1 JH IH0 K S +MAGICAL M AE1 JH IH0 K AH0 L +MAGICALLY M AE1 JH IH0 K AH0 L IY0 +MAGICALLY(1) M AE1 JH IH0 K L IY0 +MAGICIAN M AH0 JH IH1 SH AH0 N +MAGICIANS M AH0 JH IH1 SH AH0 N Z +MAGID M AE1 JH IH0 D +MAGIE M EY1 JH IY0 +MAGIERA M AA0 JH IH1 R AH0 +MAGILL M AE1 JH AH0 L +MAGIN M AE1 JH IH0 N +MAGINN M AE1 JH IH0 N +MAGINNIS M AE1 JH IH0 N IH0 S +MAGINNIS(1) M AH0 G IH1 N IH0 S +MAGINOT M AE1 JH IH0 N AA0 +MAGINOT(1) M AE1 JH IH0 N AH0 T +MAGISTAD M AE1 JH IH0 S T AE2 D +MAGISTERIAL M AE2 JH IH0 S T IY1 R IY0 AH0 L +MAGISTRATE M AE1 JH AH0 S T R EY2 T +MAGISTRATE(1) M AE1 JH IH0 S T R EY2 T +MAGISTRATES M AE1 JH IH0 S T R EY2 T S +MAGISTRO M AA0 JH IY1 S T R OW0 +MAGLAJ M AA1 G L AY2 +MAGLAJ(1) M AE1 G L AY2 +MAGLAJ'S M AA1 G L AY2 Z +MAGLAJ'S(1) M AE1 G L AY2 Z +MAGLEV M AE1 G L EH2 V +MAGLEY M AE1 G L IY0 +MAGLI M AE1 G L IY0 +MAGLIANO M AA0 G L IY0 AA1 N OW0 +MAGLICA M AE1 G L IH0 K AH0 +MAGLIO M AE1 G L IY0 OW0 +MAGLIOCCO M AA0 G L IY0 OW1 K OW0 +MAGLIOLO M AE2 G L IY0 OW1 L OW0 +MAGLIONE M AA0 G L IY0 OW1 N IY0 +MAGLIS M AE1 G L IY0 Z +MAGMA M AE1 G M AH0 +MAGMA'S M AE1 G M AH0 Z +MAGNA M AE1 G N AH0 +MAGNA'S M AE1 G N AH0 Z +MAGNAN M AE1 G N AH0 N +MAGNANI M AA0 G N AA1 N IY0 +MAGNANIMOUS M AE0 G N AE1 N AH0 M AH0 S +MAGNANO M AA0 G N AA1 N OW0 +MAGNANT M AE1 G N AH0 N T +MAGNATE M AE1 G N AH0 T +MAGNATE(1) M AE1 G N EY2 T +MAGNATES M AE1 G N EY2 T S +MAGNAVOX M AE1 G N AH0 V AA0 K S +MAGNER M AE1 G N ER0 +MAGNESIA M AE0 G N IY1 ZH AH0 +MAGNESITE M AE1 G N AH0 S AY2 T +MAGNESIUM M AE0 G N IY1 Z IY0 AH0 M +MAGNESS M AH0 G N IY1 S +MAGNET M AE1 G N AH0 T +MAGNET'S M AE1 G N AH0 T S +MAGNETEK M AE1 G N EH0 T EH2 K +MAGNETI M AE0 G N EH1 T IY0 +MAGNETIC M AE0 G N EH1 T IH0 K +MAGNETICALLY M AE0 G N EH1 T IH0 K AH0 L IY0 +MAGNETICALLY(1) M AE0 G N EH1 T IH0 K L IY0 +MAGNETICS M AE0 G N EH1 T IH0 K S +MAGNETISM M AE1 G N AH0 T IH2 Z AH0 M +MAGNETITE M AE1 G N AH0 T AY2 T +MAGNETIZATION 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N AH0 S AH0 N +MAGNUSSEN M AE1 G N AH0 S AH0 N +MAGNUSSON M AE1 G N AH0 S AH0 N +MAGOON M AH0 G UW1 N +MAGOUIRK M AH0 G W ER1 K +MAGOWAN M AA0 G OW1 W AA0 N +MAGPIE M AE1 G P AY2 +MAGPIES M AE1 G P AY2 Z +MAGRANE M AE1 G R EY2 N +MAGRATH M AH0 G R AE1 TH +MAGRI M AE1 G R IY0 +MAGRINI M AA0 G R IY1 N IY0 +MAGRO M AE1 G R OW0 +MAGRUDER M AH0 G R UW1 D ER0 +MAGS M AE1 G Z +MAGTEN M AE1 G T EH1 N +MAGUIRE M AH0 G W AY1 R +MAGUS M EY1 G AH0 S +MAGWOOD M AE1 G W UH2 D +MAGYAR M AE1 G Y AA2 R +MAGYARS M AE1 G Y AA2 R Z +MAH M AA1 +MAHABHARATA M AA0 HH AA0 B ER0 AA1 T AH0 +MAHADY M AH0 HH AA1 D IY0 +MAHAFFEY M AH0 HH AE1 F IY0 +MAHAFFY M AE1 HH AH0 F IY0 +MAHAL M AH0 HH AA1 L +MAHALA M AE1 HH AH0 L AH0 +MAHALAH M AE1 HH AH0 L AH0 +MAHALIA M AH0 HH AE1 L IY0 AH0 +MAHAMUD M AH0 HH AA1 M UH2 D +MAHAN M EY1 AH0 N +MAHANEY M AH0 HH EY1 N IY0 +MAHANNAH M AH0 HH AE1 N AH0 +MAHANY M AE1 HH AH0 N IY0 +MAHAR M AE1 HH ER0 +MAHARAJA M AA2 HH ER0 AA1 ZH AH2 +MAHARAJA'S M AA0 HH ER0 AA1 ZH AH2 Z +MAHARAJAHS M AA0 HH ER0 AA1 JH AH0 Z +MAHARASHTRA M AA2 HH ER0 AA1 SH T R AH2 +MAHARIV M AA2 HH AA1 R IY0 V +MAHARIVE M AA2 HH AH0 R IY1 V +MAHATHIR M AE1 HH AH0 TH ER0 +MAHATHIR(1) M AH0 HH AE1 TH IH2 R +MAHATHIR(2) M AH0 HH AA1 TH IH2 R +MAHATMA M AH0 HH AA1 T M AH0 +MAHAVIRA M AA1 HH AA0 V IY2 R AA0 +MAHAYANA M AA2 HH AH0 Y AA1 N AH0 +MAHDI M AA1 D IY0 +MAHE M EY1 HH IY0 +MAHEN M EY1 HH EH2 N +MAHEN(1) M EY1 AH0 N +MAHER M AA1 R +MAHESH M AH0 HH EH1 SH +MAHEU M AE1 HH Y UW0 +MAHFOUZ M AA0 F UW1 Z +MAHFOUZ'S M AA0 F UW1 Z IH0 Z +MAHILA M AH0 HH IH1 L AH0 +MAHIN M AE1 HH IH0 N +MAHINDRA M AH0 HH IH1 N D R AH0 +MAHL M AA1 L +MAHLE M EY1 HH AH0 L +MAHLER M AA1 L ER0 +MAHLER'S M AA1 L ER0 Z +MAHLMAN M AA1 L M AH0 N +MAHLMANN M AA1 L M AH0 N +MAHLON M EY1 L AO2 N +MAHLSTEDT M AA1 L S T IH0 T +MAHLUM M AA1 L AH0 M +MAHMOOD M AE1 M UW0 D +MAHMOOD(1) M AA0 M UW1 D +MAHMOUD M AE1 M UW0 D +MAHMOUD(1) M AA0 M UW1 D +MAHMUD M AE1 M UW0 D +MAHMUD(1) M AA0 M UW1 D +MAHN M AE1 N +MAHNKE M AE1 NG K +MAHNKEN M AA1 NG K AH0 N +MAHOGANY M AH0 HH AA1 G AH0 N IY0 +MAHON M EY1 AH0 N +MAHONE M AE1 HH AH0 N +MAHONEY M AH0 HH OW1 N IY0 +MAHONY M AE1 HH AH0 N IY0 +MAHOOD M AA1 HH UH0 D +MAHOWALD M AE1 HH AW0 AO0 L D +MAHR M AA1 R +MAHRT M AA1 R T +MAHTAN M AA1 T AA2 N +MAHTAR M AA1 T ER0 +MAHURIN M AE1 HH Y ER0 IH0 N +MAHVI M AA1 V IY0 +MAHWAH M AA1 W AH0 +MAI M AY1 +MAIA M AY1 AH0 +MAID M EY1 D +MAID'S M EY1 D Z +MAIDA M EY1 D AH0 +MAIDAN M AY2 D AA1 N +MAIDEL M EY1 D AH0 L +MAIDEN M EY1 D AH0 N +MAIDENFORM M EY1 D AH0 N F AO2 R M +MAIDENS M EY1 D AH0 N Z +MAIDIE M EY1 D IY0 +MAIDS M EY1 D Z +MAIDS' M EY1 D Z +MAIELLO M AY2 EH1 L OW0 +MAIER M EY1 ER0 +MAIERS M EY1 ER0 Z +MAIETTA M AY0 EH1 T AH0 +MAIL M EY1 L +MAIL'S M EY1 L Z +MAILBAG M EY1 L B AE2 G +MAILBAGS M EY1 L B AE2 G Z +MAILBOX M EY1 L B AA2 K S +MAILBOXES M EY1 L B AA2 K S IH0 Z +MAILE M EY1 L +MAILED M EY1 L D +MAILER M EY1 L ER0 +MAILER'S M EY1 L ER0 Z +MAILERS M EY1 L ER0 Z +MAILEY M EY1 L IY0 +MAILGRAM M EY1 L G R AE2 M +MAILGRAMS M 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EY1 N S T R IY2 M +MAINSTREAMING M EY1 N S T R IY2 M IH0 NG +MAINSTREET M EY1 N S T R IY2 T +MAINTAIN M EY0 N T EY1 N +MAINTAINED M EY0 N T EY1 N D +MAINTAINING M EY0 N T EY1 N IH0 NG +MAINTAINS M EY0 N T EY1 N Z +MAINTENANCE M EY1 N T AH0 N AH0 N S +MAINTENANCE(1) M EY1 N T N AH0 N S +MAINVILLE M EY1 N V IH2 L +MAINWARING M EY1 N W EH2 R IH0 NG +MAINZ M EY1 N Z +MAIO M EY1 OW0 +MAIOLO M AY1 OW0 L OW0 +MAIONE M AY1 OW0 N IY0 +MAIORANA M AY0 AO0 R AE1 N AH0 +MAIORANO M AY1 AO0 R AA0 N OW0 +MAIORINO M AY0 AO0 R IY1 N OW0 +MAIR M EH1 R +MAIRE M EH1 R +MAIREAD M EY1 R EH0 +MAIRS M EH1 R Z +MAIS M EY1 S +MAISANO M AH0 S AA1 N OW0 +MAISCH M AY1 SH +MAISEL M AY1 S AH0 L +MAISH M AA1 IH0 SH +MAISIE M EY1 Z IY0 +MAISON M EY1 Z AH0 N +MAISONET M EH1 S AH0 N IH0 T +MAITI M EY1 T IY0 +MAITLAND M EY1 T L AH0 N D +MAITRE M EY1 T R AH0 +MAIZE M EY1 Z +MAIZE'S M EY1 Z AH0 Z +MAIZIERE M EY1 Z IH2 R +MAJ M AE1 JH +MAJCHER M AE1 JH K ER0 +MAJCHRZAK M AY1 R Z AH0 K +MAJER M EY1 JH ER0 +MAJERUS M AE1 JH ER0 IH0 S +MAJESKE M AY0 EH1 S K IY0 +MAJESKI M AY0 EH1 S K IY0 +MAJESTA M AA0 Y EY1 S T AH0 +MAJESTIC M AH0 JH EH1 S T IH0 K +MAJESTICALLY M AH0 JH EH1 S T IH0 K AH0 L IY0 +MAJESTICALLY(1) M AH0 JH EH1 S T IH0 K L IY0 +MAJESTY M AE1 JH AH0 S T IY0 +MAJESTY'S M AE1 JH AH0 S T IY0 Z +MAJETTE M AH0 ZH EH1 T +MAJEURE M AH0 JH UW1 R +MAJEWSKI M AY0 EH1 F S K IY0 +MAJID M AH0 JH IH1 D +MAJIK M AE1 JH IH0 K +MAJKA M AY1 K AH0 +MAJKOWSKI M AY0 K AO1 F S K IY0 +MAJNOON M AE2 JH N UW1 N +MAJOLICA M AH0 JH AO1 L AH0 K AH0 +MAJOR M EY1 JH ER0 +MAJOR'S M EY1 JH ER0 Z +MAJORCA M AY0 AO1 R K AH0 +MAJORDOMO M EY2 JH ER0 D OW1 M OW0 +MAJORED M EY1 JH ER0 D +MAJORING M EY1 JH ER0 IH0 NG +MAJORITARIAN M AE2 JH ER0 IH0 T EH1 R IY0 AH0 N +MAJORITIES M AH0 JH AO1 R IH0 T IY0 Z +MAJORITY M AH0 JH AO1 R AH0 T IY0 +MAJORITY'S M AH0 JH AO1 R AH0 T IY0 Z +MAJOROS M AA0 Y AO1 R OW0 Z +MAJORS M EY1 JH ER0 Z +MAJORS' M EY1 JH ER0 Z +MAJROOH M AE1 JH R UW0 +MAJURE M AA0 Y UH1 R EY0 +MAK M AE1 K +MAK-KWAN M AE1 K K W AA1 N +MAKAR M AE1 K ER0 +MAKARA M AA0 K AA1 R AH0 +MAKAREWICZ M AH0 K AA1 R IH0 V IH0 CH +MAKE M EY1 K +MAKE-DO M EY1 K D UW2 +MAKE-OVER M EY1 K OW2 V ER0 +MAKE-UP M EY1 K AH2 P +MAKEFIELD M EY1 K F IY0 L D +MAKEGOOD M EY1 K G UH2 D +MAKEGOODS M EY1 K G UH2 D Z +MAKELA M AE1 K IH0 L AH0 +MAKEOVER M AE1 K OW2 V ER0 +MAKEOVERS M AE1 K OW2 V ER0 Z +MAKEPEACE M AE1 K P IY0 S +MAKER M EY1 K ER0 +MAKER'S M EY1 K ER0 Z +MAKERS M EY1 K ER0 Z +MAKERS' M EY1 K ER0 Z +MAKES M EY1 K S +MAKESHIFT M EY1 K SH IH2 F T +MAKEUP M EY1 K AH2 P +MAKHOUL M AH0 K UW1 L +MAKI M AA1 K IY0 +MAKIN M AE1 K IH0 N +MAKIN' M EY1 K IH0 N +MAKINEN M AE1 K IH0 N AH0 N +MAKING M EY1 K IH0 NG +MAKINGS M EY1 K IH0 NG Z +MAKINSON M AE1 K IH0 N S AH0 N +MAKITA M AH0 K IY1 T AH0 +MAKO M AA1 K OW0 +MAKOS M EY1 K OW0 Z +MAKOTO M AH0 K OW1 T OW0 +MAKOWSKI M AH0 K AO1 F S K IY0 +MAKOWSKY M AH0 K AW1 S K IY0 +MAKRIS M AE1 K R IH0 S +MAKRO M AE1 K R OW0 +MAKSOUD M AE0 K S UW1 D +MAKSYMUK M AE1 K S IY0 M UH2 K +MAKTOUM M AE0 K T UW1 M +MAKTOUMS M AE0 K T UW1 M Z +MAKUCH M AE1 K AH0 K +MAL M AE1 L +MAL'S M AE1 L Z +MALA M AA1 L AH0 +MALABRE M AE1 L AH0 B R AH0 +MALACANANG M AH0 L AE1 K AH0 N AE0 NG +MALACCA M AH0 L AE1 K AH0 +MALACHOWSKI M AH0 L AH0 HH AO1 F S K IY0 +MALADICH M AE1 L AH0 D IH0 K +MALADICH(1) M AE1 L AH0 D IH0 CH +MALADIES M AE1 L AH0 D IY0 Z +MALADJUSTED M AE2 L AH0 JH AH1 S T IH0 D +MALADROIT M AE2 L AH0 D R OY1 T +MALADY M AE1 L AH0 D IY0 +MALAGA M AE1 L AH0 G AH0 +MALAGASY M AE2 L AH0 G AE1 S IY0 +MALAHIDE M AE2 L AH0 HH AY1 D +MALAISE M AE0 L EY1 Z +MALAK M AE1 L AH0 K +MALAMUD M AE1 L AH0 M AH0 D +MALAMUGI M AE1 L AH0 M Y UW2 JH IY0 +MALAMUTE M AE1 L AH0 M Y UW2 T +MALAN M EY1 L AH0 N +MALAND M AE1 L AH0 N D +MALANEY M AH0 L EY1 N IY0 +MALANGA M AA0 L AA1 NG G AH0 +MALANOWSKI M AH0 L AH0 N AO1 F S K IY0 +MALAPROP M AE1 L AH0 P R AA2 P +MALARA M AA0 L AA1 R AH0 +MALARIA M AH0 L EH1 R IY0 AH0 +MALARIAL M AH0 L EH1 R IY0 AH0 L +MALARKEY M AH0 L AA1 R K IY0 +MALARY M AE1 L AH0 R IY0 +MALASPINA M AA0 L AA0 S P IY1 N AH0 +MALATESTA M AA0 L AA0 T EH1 S T AH0 +MALATHION M AH0 L AE1 TH IY0 AO0 N +MALATHION(1) M AH0 L AE1 TH IY0 AH0 N +MALAVE M AA0 L AA1 V IY0 +MALAWI M AH0 L AA1 W IY0 +MALAWI'S M AH0 L AA1 W IY0 Z +MALAY M EY1 L EY0 +MALAYAN M AH0 L EY1 AH0 N +MALAYS M AH0 L EY1 Z +MALAYSIA M AH0 L EY1 ZH AH0 +MALAYSIA'S M AH0 L EY1 ZH AH0 Z +MALAYSIAN M AH0 L EY1 ZH AH0 N +MALAYSIANS M AH0 L EY1 ZH AH0 N Z +MALBON M AE1 L B AH0 N +MALBROUGH M AE1 L B R AW0 +MALBURG M AE1 L B ER0 G +MALCHOW M AA1 L HH AW0 +MALCOLM M AE1 L K AH0 M +MALCOLM'S M AE1 L K AH0 M Z +MALCOLMSON M AE1 L K AH0 M S AH0 N +MALCOM M AE1 L K AH0 M +MALCOMB M AE1 L K AH0 M +MALCOMSON M AE1 L K AH0 M S AH0 N +MALCONTENT M AE2 L K AH0 N T EH1 N T +MALCONTENTS M AE2 L K AH0 N T EH1 N T S +MALCZEWSKI M AH0 L CH EH1 F S K IY0 +MALDEN M AO1 L D AH0 N +MALDIVES M AO1 L D AY2 V Z +MALDONADO M AE0 L D AH0 N AA1 D OW0 +MALDUTIS M AA0 L D UW1 T IH0 S +MALE M EY1 L +MALE'S M EY1 L Z +MALEC M AA1 L IH0 K +MALECHA M AH0 L 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AH0 T M EY2 K ER0 +MARKETMAKERS M AA1 R K AH0 T M EY2 K ER0 Z +MARKETPLACE M AA1 R K AH0 T P L EY2 S +MARKETPLACE(1) M AA1 R K IH0 T P L EY2 S +MARKETPLACE'S M AA1 R K AH0 T P L EY2 S IH0 Z +MARKETPLACES M AA1 R K AH0 T P L EY2 S IH0 Z +MARKETS M AA1 R K AH0 T S +MARKETS(1) M AA1 R K IH0 T S +MARKETS' M AA1 R K IH0 T S +MARKETSCOPE M AA1 R K AH0 T S K OW2 P +MARKETWIDE M AA1 R K AH0 T W AY2 D +MARKEY M AA1 R K IY2 +MARKEY'S M AA1 R K IY2 Z +MARKGRAF M AA1 R K G R AH0 F +MARKHAM M AA1 R K AH0 M +MARKHAM'S M AA1 R K AH0 M Z +MARKIE M AA1 R K IY0 +MARKIEWICZ M AA1 R K AH0 V IH0 CH +MARKIN M AA1 R K IH0 N +MARKING M AA1 R K IH0 NG +MARKINGS M AA1 R K IH0 NG Z +MARKKA M AA1 R K AH0 +MARKKAA M AA0 R K AA1 +MARKKAS M AA1 R K AH0 S +MARKLAND M AA1 R K L AH0 N D +MARKLE M AA1 R K AH0 L +MARKLEY M AA1 R K L IY0 +MARKMAN M AA1 R K M AH0 N +MARKO M AA1 R K OW0 +MARKOFF M AA1 R K AO2 F +MARKOS M AA1 R K OW0 Z +MARKOV M AA1 R K OW0 V +MARKOVIAN M AA2 R K OW1 V IY2 AH0 N +MARKOVIC M AA1 R K AH0 V IH0 K +MARKOVICH M AA1 R K AH0 V IH0 CH +MARKOVITZ M AA1 R K AH0 V IH0 T S +MARKOW M AA1 R K OW0 +MARKOWICZ M AA1 R K AH0 V IH0 CH +MARKOWITZ M AA1 R K AH0 W IH0 T S +MARKOWSKI M ER0 K AO1 F S K IY0 +MARKS M AA1 R K S +MARKS'S M AA1 R K S IH0 Z +MARKSBERRY M AA1 R K S B EH2 R IY0 +MARKSMAN M AA1 R K S M AH0 N +MARKSMANSHIP M AA1 R K S M AH0 N SH IH0 P +MARKSMEN M AA1 R K S M EH0 N +MARKSON M AA1 R K S AH0 N +MARKUM M AA1 R K AH0 M +MARKUNAS M AA1 R K UW0 N AH0 Z +MARKUP M AA1 R K AH2 P +MARKUPS M AA1 R K AH2 P S +MARKUS M AA1 R K AH0 S +MARKUSON M AA1 R K AH0 S AH0 N +MARKWARDT M AA1 R K W AO0 R T +MARKWELL M AA1 R K W EH2 L +MARKWOOD M AA1 R K W UH2 D +MARKY M AA1 R K IY0 +MARLA M AA1 R L AH0 +MARLAND M AA1 R L AH0 N D +MARLAR M AA1 R L ER0 +MARLATT M AA1 R L AH0 T +MARLBORO M AA1 R L B ER0 OW0 +MARLBORO'S M AA1 R L B ER0 R OW0 Z +MARLBOROS M AA1 R L B ER0 R OW0 Z +MARLBOROUGH M AA1 R L B ER0 OW0 +MARLEEN M AA0 R L IY1 N +MARLEENE M AA0 R L IY1 N +MARLEN M AA1 R L AH0 N +MARLENA M AA0 R L EY1 N AH0 +MARLENE M AA1 R L IY2 N +MARLENS M AA1 R L AH0 N Z +MARLER M AA1 R L ER0 +MARLETT M AA1 R L IH0 T +MARLETTE M AA2 R L EH1 T +MARLEY M AA1 R L IY0 +MARLIAVE M AA2 R L IY0 EH1 V +MARLIN M AA1 R L AH0 N +MARLIN(1) M AA1 R L IH0 N +MARLING M AA1 R L IH0 NG +MARLINS M AA1 R L AH0 N Z +MARLINS' M AA1 R L AH0 N Z +MARLO M AA1 R L OW0 +MARLON M AA1 R L AH0 N +MARLOW M AA1 R L OW0 +MARLOWE M AA1 R L OW2 +MARLTON M AA1 R L T AH0 N +MARLYS M AA1 R L IY0 Z +MARMADUKE M AA1 R M AH0 D UW2 K +MARMADUKE'S M AA1 R M AH0 D UW2 K S +MARMALADE M AA1 R M AH0 L EY2 D +MARMALADES M AA1 R M AH0 L EY2 D Z +MARMARA M AA0 R M AA1 R AH0 +MARMER M AA1 R M ER0 +MARMION M AA1 R M IY0 AH0 N +MARMO M AA1 R M OW0 +MARMOLEJO M AA0 R M OW0 L EY1 Y OW0 +MARMON M AA1 R M AH0 N +MARMOR M AA1 R M ER0 +MARMOSET M AA1 R M AH0 Z EH2 T +MARNELL M AA1 R N AH0 L +MARNER M AA1 R N ER0 +MARNEY M AA1 R N IY0 +MARNIE M AA1 R N IY0 +MARO M AA1 R OW0 +MAROC M AA2 R AO1 K +MAROGEN M EH1 R OW0 G AH0 N +MAROHL M AE1 R OW0 L 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EH2 L OW0 +MARSHMALLOWS M AA1 R SH M EH2 L OW0 Z +MARSHMAN M AA1 R SH M AH0 N +MARSHY M AA1 R SH IY0 +MARSICANO M AA0 R S IY0 K AA1 N OW0 +MARSICO M AA0 R S IY1 K OW0 +MARSIGLIA M AA2 R S IH1 G L IY0 AH0 +MARSILI M AA0 R S IY1 L IY0 +MARSISA M AA0 R S IH1 S AH0 +MARSISA'S M AA0 R S IH1 S AH0 Z +MARSLAND M AA1 R S L AH0 N D +MARSO M AA1 R S OW0 +MARSOLEK M AA1 R S AH0 L EH0 K +MARSON M AA1 R S AH0 N +MARSTELLER M AA1 R Z T EH2 L ER0 +MARSTERS M AA1 R S T ER0 Z +MARSTON M AA1 R S T AH0 N +MARSUPIAL M AA0 R S UW1 P IY0 AH0 L +MARSUPIALS M AA0 R S UW1 P IY0 AH0 L S +MARSZALEK M ER0 SH AA1 L EH0 K +MART M AA1 R T +MART'S M AA1 R T S +MARTA M AA1 R T AH0 +MARTE M AA1 R T +MARTECH M AA1 R T EH2 K +MARTEK M AA1 R T EH2 K +MARTEL M AA1 R T EH2 L +MARTELL M AA1 R T EH2 L +MARTELLA M AA2 R T EH1 L AH0 +MARTELLE M AA0 R T EH1 L +MARTELLI M AA0 R T EH1 L IY0 +MARTELLINI M AA2 R T EH2 L IY1 N IY0 +MARTELLO M AA0 R T EH1 L OW0 +MARTEN M AA1 R T AH0 N +MARTENEY M AA1 R T IH0 N IY0 +MARTENS M AA1 R T 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IY1 N IY0 Z +MARTINKA M AA2 R T IH1 NG K AH0 +MARTINKO M AA2 R T IH1 NG K OW0 +MARTINO M AA0 R T IY1 N OW0 +MARTINOVICH M AA2 R T IH1 N AH0 V IH0 CH +MARTINS M AA1 R T IH0 N Z +MARTINS'S M AA1 R T IH0 N Z IH0 Z +MARTINSEN M AA0 R T IH1 N S AH0 N +MARTINSON M AA1 R T IH0 N S AH0 N +MARTINSVILLE M AA1 R T IH0 N Z V IH2 L +MARTINY M AA1 R T IH0 N IY0 +MARTION M AA1 R SH Y AH0 N +MARTIRE M AA0 R T IH1 R IY0 +MARTIROSOV M AA0 R T IH1 R AH0 S AA0 V +MARTIS M AA1 R T IH0 S +MARTITA M AA0 R T IY1 T AH0 +MARTOCCI M AA0 R T OW1 CH IY0 +MARTON M AA1 R T AH0 N +MARTONE M AA0 R T OW1 N IY0 +MARTORANA M AA0 R T AO0 R AE1 N AH0 +MARTORANO M AA0 R T AO0 R AA1 N OW0 +MARTORELLI M AA0 R T AO0 R EH1 L IY0 +MARTS M AA1 R T S +MARTUCCI M AA0 R T UW1 CH IY0 +MARTURANO M AA0 R T UH0 R AA1 N OW0 +MARTUS M AA1 R T AH0 S +MARTY M AA1 R T IY0 +MARTY'S M AA1 R T IY0 Z +MARTYN M AA1 R T IH0 N +MARTYR M AA1 R T ER0 +MARTYRDOM M AA1 R T ER0 D AH0 M +MARTYRE M AA0 R T AY1 R +MARTYRED M AA1 R T ER0 D +MARTYRS M AA1 R T ER0 Z +MARTZ M AA1 R T S +MARTZ'S M AA1 R T S IH0 Z +MARUBENI M AA2 R UW0 B IY1 N IY0 +MARUCA M ER0 UW1 K AH0 +MARUCCI M AA0 R UW1 CH IY0 +MARUI M ER0 UW1 IY0 +MARUKIN M ER0 UW1 K IH0 N +MARULANDA M AE2 R UW0 L AE1 N D AH0 +MARULLO M AA0 R UW1 L OW0 +MARUSKA M ER0 AH1 S K AH0 +MARUTI M ER0 UW1 T IY0 +MARUYAMA M AA2 R UW0 Y AA1 M AH0 +MARUYU M EH1 R UW0 Y UW0 +MARV M AA1 R V +MARVA M AA1 R V AH0 +MARVEL M AA1 R V AH0 L +MARVEL'S M AA1 R V AH0 L Z +MARVELA M AA0 R V EY1 L AH0 +MARVELED M AA1 R V EH0 L D +MARVELING M AA1 R V AH0 L IH0 NG +MARVELL M AA0 R V EH1 L +MARVELLA M AA2 R V EH1 L AH0 +MARVELLE M AA0 R V EH1 L +MARVELLED M AA0 R V EH1 L D +MARVELLOUS M AA1 R V AH0 L AH0 S +MARVELOUS M AA1 R V AH0 L AH0 S +MARVELOUSLY M AA1 R V AH0 L AH0 S L IY0 +MARVELS M AA1 R V AH0 L Z +MARVER M AA1 R V ER0 +MARVIN M AA1 R V IH0 N +MARVIN'S M AA1 R V IH0 N Z +MARWICK M AA1 R W IH2 K +MARWICK'S M AA1 R W IH2 K S +MARWIN M AA1 R W IH0 N +MARWOOD M AA1 R W UH2 D +MARX M AA1 R K S +MARXEN M AA1 R K S AH0 N +MARXISM M AA1 R K S IH0 Z AH0 M +MARXIST M AA1 R K S AH0 S T +MARXIST(1) M AA1 R K S IH0 S T +MARXISTS M AA1 R K S IH0 S T S +MARY M EH1 R IY0 +MARY'S M EH1 R IY0 Z +MARYA M AA1 R Y AH0 +MARYALICE M EH0 R IY0 AE1 L AH0 S +MARYANN M EH0 R IY0 AE1 N +MARYANNE M EH0 R IY0 AE1 N +MARYBETH M EH1 R IY0 B EH1 TH +MARYLAND M EH1 R AH0 L AH0 N D +MARYLAND'S M EH1 R AH0 L AH0 N D Z +MARYLEBONE M ER1 L AH0 B OW0 N +MARYLIN M AE1 R IH0 L IH0 N +MARYLOU M AE1 R IY0 L UW0 +MARYMOUNT M EH1 R IY0 M AW2 N T +MARYMOUNT'S M EH1 R IY0 M AW2 N T S +MARYRUTH M AE1 R IH0 R UW0 TH +MARYSE M AA0 R IY1 S +MARYSVILLE M EH1 R IY0 Z V IH2 L +MARYVILLE M EH1 R IY0 V IH2 L +MARZ M AA1 R Z +MARZAN M AA1 R Z AH0 N +MARZANO M AA0 R Z AA1 N OW2 +MARZEC M AA1 R Z IH0 K +MARZETTE M AA2 R Z EH1 T +MARZILLI M AA0 R Z IY1 L IY2 +MARZO M AA1 R Z OW2 +MARZOLF M AA1 R Z OW2 L F +MARZOTTO M AA2 R Z AA1 T OW2 +MARZULLO M AA0 R Z UW1 L OW2 +MAS M AA1 Z +MASA M AA1 S AA0 +MASAAKI M AA2 S AA0 AA1 K IY2 +MASAHIKO M AA2 S AA0 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M AE1 S +MASS.(1) M AE2 S AH0 CH UW1 S AH0 T S +MASSA M AE1 S AH0 +MASSACHUSETTS M AE2 S AH0 CH UW1 S AH0 T S +MASSACHUSETTS' M AE2 S AH0 CH UW1 S AH0 T S +MASSACHUSSETTS M AE2 S AH0 CH UW1 S AH0 T S +MASSACRE M AE1 S AH0 K ER0 +MASSACRED M AE1 S AH0 K ER0 D +MASSACRES M AE1 S IH0 K ER0 Z +MASSACRING M AE1 S AH0 K ER0 IH0 NG +MASSAD M AE1 S AH0 D +MASSAGE M AH0 S AA1 ZH +MASSAGED M AH0 S AA1 ZH D +MASSAGER M AH0 S AA1 ZH ER0 +MASSAGERS M AH0 S AA1 ZH ER0 Z +MASSAGES M AH0 S AA1 ZH IH0 Z +MASSAGING M AH0 S AA1 ZH IH0 NG +MASSAR M AE1 S ER0 +MASSARI M AA0 S AA1 R IY0 +MASSARO M AH0 S AA1 R OW0 +MASSAT M AH0 S AA1 T +MASSBAUCH M AE1 S B AA2 K +MASSE M AE1 S +MASSED M AE1 S T +MASSENBURG M AE1 S AH0 N B ER0 G +MASSENET M AE1 S AH0 N EH2 T +MASSENET'S M AE1 S AH0 N EH2 T S +MASSENGALE M AE1 S AH0 N G EY2 L +MASSENGILL M AE1 S AH0 N G IH2 L +MASSER M AE1 S ER0 +MASSERY M AE1 S ER0 IY0 +MASSES M AE1 S AH0 Z +MASSES(1) M AE1 S IH0 Z +MASSETT M AE1 S IH0 T +MASSEY M AE1 S IY0 +MASSI M AE1 S IY0 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W AA2 R +MEMOIRS M EH1 M W AA2 R Z +MEMOLI M EH0 M OW1 L IY0 +MEMORABILIA M EH2 M ER0 AH0 B IY1 L Y AH0 +MEMORABLE M EH1 M ER0 AH0 B AH0 L +MEMORABLY M EH1 M ER0 AH0 B L IY0 +MEMORANDA M EH2 M ER0 AE1 N D AH0 +MEMORANDUM M EH2 M ER0 AE1 N D AH0 M +MEMORANDUMS M EH2 M ER0 AE1 N D AH0 M Z +MEMOREX M EH1 M AO0 R EH2 K S +MEMORIAL M AH0 M AO1 R IY0 AH0 L +MEMORIALIZE M AH0 M AO1 R IY0 AH0 L AY2 Z +MEMORIALIZED M AH0 M AO1 R IY0 AH0 L AY2 Z D +MEMORIALS M AH0 M AO1 R IY0 AH0 L Z +MEMORIES M EH1 M ER0 IY0 Z +MEMORIES' M EH1 M ER0 IY2 Z +MEMORIZE M EH1 M ER0 AY2 Z +MEMORIZED M EH1 M ER0 AY2 Z D +MEMORIZES M EH1 M ER0 AY2 Z IH0 Z +MEMORIZING M EH1 M ER0 AY2 Z IH0 NG +MEMORY M EH1 M ER0 IY0 +MEMOS M EH1 M OW0 Z +MEMOTEC M EH1 M OW0 T EH2 K +MEMPHIS M EH1 M F AH0 S +MEMPHIS(1) M EH1 M F IH0 S +MEMPHIS(2) M EH1 M P F AH0 S +MEMPHIS(3) M EH1 M P F IH0 S +MEMTEC M EH1 M T EH2 K +MEMTEC'S M EH1 M T EH2 K S +MEN M EH1 N +MEN'S M EH1 N Z +MENA M IY1 N AH0 +MENACE M EH1 N AH0 S +MENACE(1) M EH1 N IH0 S 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T ER0 +MENTOR'S M EH1 N T AO2 R Z +MENTORED M EH1 N T ER0 D +MENTORING M EH1 N T ER0 IH0 NG +MENTORS M EH1 N T ER0 Z +MENTORS(1) M EH1 N T AO2 R Z +MENTZ M EH1 N T S +MENTZEL M EH1 N T Z AH0 L +MENTZER M EH1 N T Z ER0 +MENU M EH1 N Y UW0 +MENUDO M AH0 N Y UW1 D OW0 +MENUHIN M AH0 N UW1 HH IH0 N +MENUHIN(1) M IH0 N Y UW1 IH0 N +MENUS M EH1 N Y UW0 Z +MENZ M EH1 N Z +MENZE M EH1 N Z +MENZEL M EH1 N Z AH0 L +MENZER M EH1 N Z ER0 +MENZIE M EH1 N Z IY0 +MENZIES M EH1 N Z IY0 Z +MENZIONE M EH0 N Z IY0 OW1 N IY0 +MENZIONE(1) M EH0 N Z Y OW1 N IY0 +MEO M IY1 OW0 +MEOLA M IY0 AA1 L AH0 +MEOW M IY0 AW1 +MEQUON M EH1 K W AH0 N +MER M EH1 R +MER(1) M ER1 +MERABANK M EH1 R AH0 B AE2 NG K +MERANDA M ER0 AA1 N D AH0 +MERAZ M EH1 R AA0 Z +MERC M ER1 K +MERC(1) M AA1 R K +MERC'S M ER1 K S +MERC'S(1) M AA1 R K S +MERCADANTE M ER0 K AA0 D AA1 N T IY2 +MERCADO M ER0 K AA1 D OW0 +MERCANTIL M ER0 K AE1 N T IH0 L +MERCANTILE M ER1 K AH0 N T AY2 L +MERCANTILE'S M ER1 K AH0 N T IY2 L Z +MERCANTILISM M ER0 K AE1 N T AH0 L IH2 Z AH0 M +MERCANTILIST M ER0 K AE1 N T AH0 L IH0 S T +MERCATOR M ER0 K EY1 T ER0 +MERCE M ER1 S +MERCED M ER1 S T +MERCEDES M ER0 S EY1 D IY0 Z +MERCEDES'S M ER0 S EY1 D IY0 Z +MERCEDES'S(1) M ER0 S EY1 D IY0 Z IH0 Z +MERCEDESES M ER2 S EY1 D IY2 Z IH0 Z +MERCEDESES(1) M ER2 S EY1 D IY2 Z +MERCENARIES M ER1 S AH0 N EH2 R IY0 Z +MERCENARY M ER1 S AH0 N EH2 R IY0 +MERCER M ER1 S ER0 +MERCHANDISE M ER1 CH AH0 N D AY2 Z +MERCHANDISER M ER1 CH AH0 N D AY2 Z ER0 +MERCHANDISERS M ER1 CH AH0 N D AY2 Z ER0 Z +MERCHANDISING M ER1 CH AH0 N D AY2 Z IH0 NG +MERCHANT M ER1 CH AH0 N T +MERCHANT'S M ER1 CH AH0 N T S +MERCHANTMEN M ER1 CH AH0 N T M IH0 N +MERCHANTS M ER1 CH AH0 N T S +MERCHANTS' M ER1 CH AH0 N T S +MERCHANTSBANK M ER1 CH AH0 N T S B AE2 NG K +MERCI M ER0 S IY1 +MERCIER M ER1 S IY2 ER0 +MERCIES M ER1 S IY2 Z +MERCIFUL M ER1 S IH0 F AH0 L +MERCIFULLY M ER1 S IH0 F AH0 L IY2 +MERCILESS M ER1 S AH0 L AH0 S +MERCILESSLY M ER1 S AH0 L AH0 S L IY0 +MERCK M ER1 K +MERCK'S M ER1 K S +MERCLAND M ER1 K L AE0 N D +MERCOSUR M ER1 K OW2 S ER2 +MERCURE M ER0 K UH1 R +MERCURI M ER0 K UH1 R IY0 +MERCURIAL M ER0 K Y UH1 R IY0 AH0 L +MERCURIC M ER0 K Y UH1 R IH0 K +MERCURIO M ER0 K UH1 R IY0 OW2 +MERCURY M ER1 K Y ER0 IY0 +MERCURY'S M ER1 K Y ER0 IY0 Z +MERCY M ER1 S IY0 +MERDYCE M ER1 D AY0 S +MERE M IH1 R +MEREDITH M EH1 R IH0 D IH0 TH +MERELY M IH1 R L IY0 +MERENDA M EH0 R EY1 N D AA0 +MERENDINO M ER0 EH0 N D IY1 N OW2 +MERENGUE M ER0 EY1 NG +MEREST M EH1 R AH0 S T +MERETZ M EH1 R EH0 T S +MERFELD M ER1 F EH0 L D +MERGE M ER1 JH +MERGED M ER1 JH D +MERGEN M ER1 G AH0 N +MERGER M ER1 JH ER0 +MERGER'S M ER1 JH ER0 Z +MERGERS M ER1 JH ER0 Z +MERGES M ER1 JH IH0 Z +MERGING M ER1 JH IH0 NG +MERHIGE M ER0 HH IY1 JH +MERIAM M IH1 R IY0 IH0 M +MERICA M EH1 R IH0 K AH0 +MERICANTANTE M EH0 R IY2 K AH0 N T AA1 N T EY0 +MERICLE M EH1 R IH0 K AH0 L +MERICOPA M EH2 R AH0 K OW1 P AH0 +MERIDA M ER0 IY1 D AH0 +MERIDEN M EH1 R IH0 D AH0 N +MERIDETH M EH1 R IH0 D IH0 TH +MERIDIAN M ER0 IH1 D IY0 AH0 N +MERIDIAN'S M ER0 IH1 D IY0 AH0 N Z +MERIDIEN M ER0 IH1 D IY0 AH0 N +MERIDIONALE M ER0 IH2 D IY0 AH0 N AA1 L IY0 +MERIDITH M EH1 R IH0 D IH0 TH +MERIDOR M EH1 R IH0 D AO0 R +MERIEL M IH1 R IY0 L +MERIEUX M EH1 R IY0 UW2 +MERILLAT M EH1 R IH0 L AE0 T +MERINO M ER0 IY1 N OW0 +MERION M EH1 R IY0 AH0 N +MERIS M EH1 R AH0 S +MERISEL M EH1 R IH0 S EH2 L +MERIT M EH1 R AH0 T +MERITED M EH1 R IH0 T IH0 D +MERITHEW M ER0 IH1 TH Y UW0 +MERITING M EH1 R AH0 T IH0 NG +MERITLESS M EH1 R IH0 T L AH0 S +MERITOCRACY M EH0 R IH0 T AO1 K R AH0 S IY0 +MERITOR M EH1 R AH0 T ER0 +MERITOR(1) M EH1 R AH0 T AO2 R +MERITORIOUS M EH2 R AH0 T AO1 R IY0 AH0 S +MERITS M EH1 R AH0 T S +MERITS(1) M EH1 R IH0 T S +MERITT M EH1 R IH0 T +MERIWEATHER M EH1 R IH0 W EH2 DH ER0 +MERIWETHER M EH1 R IH0 W EH2 DH ER0 +MERK M ER1 K +MERKEL M ER1 K AH0 L +MERKER M ER1 K ER0 +MERKEY M ER1 K IY0 +MERKICH M ER1 K IH0 CH +MERKIN M ER1 K IH0 N +MERKLAN M ER1 K L AH0 N +MERKLE M ER1 K AH0 L +MERKLEY M ER1 K L IY0 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R AH0 L +MERYLL M EH1 R AH0 L +MERZ M ER1 Z +MESA M EY1 S AH0 +MESA'S M EY1 S AH0 Z +MESABA M EH0 S AA1 B AH0 +MESAROS M EY0 S AA1 R OW0 Z +MESBIC M EH1 S B IH0 K +MESBICS M EH1 S B IH0 K S +MESCALERO M EH2 S K AH0 L EH1 R OW0 +MESCALINE M EH1 S K AH0 L IY2 N +MESCH M EH1 SH +MESCHED M EH1 SH EH0 D +MESCHER M EH1 SH ER0 +MESCHKE M EH1 SH K +MESDAMES M EY0 D AE1 M Z +MESELSOHN M EH1 Z AH0 L S AH0 N +MESELSON M EH1 Z AH0 L S AH0 N +MESENBRINK M EH1 S IH0 N B R IH0 NG K +MESENCHYMAL M EH2 Z EH0 K AY1 M AH0 L +MESENCHYMAL(1) M EH2 Z EH1 N K AH0 M AH0 L +MESENTERIC M EH2 S AH0 N T EH1 R IH0 K +MESEROLE M EH0 S ER0 OW1 L IY0 +MESERVE M EH1 S ER0 V +MESERVEY M EH0 Z ER0 V EY1 +MESH M EH1 SH +MESHED M EH1 SH T +MESHELL M EH1 SH AH0 L +MESHES M EH1 SH IH0 Z +MESHING M EH1 SH IH0 NG +MESHULAM M EH1 SH UW0 L AE0 M +MESICK M EH1 S IH0 K +MESIROW M EH1 S IH0 R OW0 +MESKE M EH1 S K +MESKER M EH1 S K ER0 +MESKILL M EH1 S K IH0 L +MESKIMEN M EH1 S K IY0 M EH0 N +MESKO M EH1 S K OW0 +MESLER M EH1 S AH0 L ER0 +MESLER(1) M EH1 S L ER0 +MESMER M EH1 Z M ER0 +MESMERISM M EH1 S M ER0 IH2 Z AH0 M +MESMERIZE M EH1 Z M ER0 AY2 Z +MESMERIZED M EH1 Z M ER0 AY2 Z D +MESMERIZING M EH1 Z M ER0 AY2 Z IH0 NG +MESNER M EH1 S N ER0 +MESODERMAL M EH2 Z AH0 D ER1 M AH0 L +MESOLITHIC M EH2 Z AH0 L IH1 TH IH0 K +MESON M EY1 Z AA2 N +MESONS M IY1 Z AA2 N Z +MESOPOTAMIA M EH2 S AH0 P AH0 T EY1 M IY0 AH0 +MESOPOTAMIAN M EH2 S AH0 P AH0 T EY1 M IY0 AH0 N +MESOPOTAMIANS M EH2 S AH0 P AH0 T EY1 M IY0 AH0 N Z +MESOTHELIOMA M EH2 S AH0 TH IY2 L IY0 OW1 M AH0 +MESOTHORAX M EH2 Z AH0 TH AO1 R AE2 K S +MESOZOIC M EH2 S AH0 Z OW1 IH0 K +MESQUITE M EH1 S K IY2 T +MESS M EH1 S +MESSA M EH1 S AH0 +MESSAGE M EH1 S AH0 JH +MESSAGE(1) M EH1 S IH0 JH +MESSAGEPAD M EH1 S AH0 JH P AE2 D +MESSAGES M EH1 S AH0 JH AH0 Z +MESSAGES(1) M EH1 S IH0 JH IH0 Z +MESSAGING M EH1 S IH0 JH IH0 NG +MESSAMORE M EH0 S AA1 M AO0 R +MESSANA M EH0 S AE1 N AH0 +MESSED M EH1 S T +MESSEGHERO M EH2 S AH0 G EH1 R OW0 +MESSEL M EH1 S AH0 L +MESSENGER M EH1 S AH0 N JH ER0 +MESSENGER(1) M EH1 S IH0 N JH ER0 +MESSENGERS M EH1 S AH0 N JH ER0 Z +MESSER M EH1 S ER0 +MESSERLI M EH1 S ER0 L IY0 +MESSERLY M EH1 S ER0 L IY0 +MESSERSCHMIDT M EH1 S ER0 SH M IH2 T +MESSERSCHMITT M EH1 S ER0 SH M IH2 T +MESSERSMITH M EH1 S ER0 S M IH2 TH +MESSES M EH1 S IH0 Z +MESSIAEN M EH1 S IY0 EY2 N +MESSIAEN'S M EH1 S IY0 EY2 N Z +MESSIAH M AH0 S AY1 AH0 +MESSIAHS M AH0 S AY1 AH0 Z +MESSIANIC M EH2 S IY0 AE1 N IH0 K +MESSICK M EH1 S IH0 K +MESSIER M EH1 S IY0 ER0 +MESSIEURS M EY0 S Y ER1 Z +MESSIMER M EH1 S IH0 M ER0 +MESSINA M IH0 S IY1 N AH0 +MESSINEO M EH2 S IH1 N IY0 OW0 +MESSING M EH1 S IH0 NG +MESSINGER M EH1 S IH0 NG ER0 +MESSLER M EH1 S L ER0 +MESSMAN M EH1 S M AH0 N +MESSMER M EH1 S M ER0 +MESSMORE M EH1 S M AO0 R +MESSNER M EH1 S N ER0 +MESSRS M EH1 S ER0 Z +MESSRS. M EH1 S ER0 Z +MESSRS.(1) M IH0 S UW1 R Z +MESSY M EH1 S IY0 +MEST M EH1 S T +MESTA M EH1 S T AH0 +MESTAS M EH1 S T AH0 Z +MESTEK M EH1 S T EH2 K +MESTER M EH1 S T ER0 +MESTIZO M EH0 S T IY1 Z OW0 +MESTON M EH1 S T AH0 N +MESTRALLET M EH1 S T R AH0 L EH2 T +MESTRE M EH1 S T ER0 +MESTROVIC M EH1 S T R OW0 V IH0 K +MESZAROS M IH0 SH AA1 R OW0 Z +MET M EH1 T +MET'S M EH1 T S +META M IY1 T AH0 +METABOLIC M EH2 T AH0 B AA1 L IH0 K +METABOLISM M AH0 T AE1 B AH0 L IH2 Z AH0 M +METABOLISMS M AH0 T AE1 B AH0 L IH2 Z AH0 M Z +METABOLITE M AH0 T AE1 B AH0 L AY2 T +METABOLITES M AH0 T AE1 B AH0 L AY2 T S +METABOLIZE M AH0 T AE1 B AH0 L AY2 Z +METACARPAL M EH2 T AH0 K AA1 R P AH0 L +METACARPALS M EH2 T AH0 K AA1 R P AH0 L Z +METAGOGUE M EH1 T AH0 G AO2 G +METAGOGUED M EH1 T AH0 G AO2 G D +METAIRIE M AH0 T EH1 R IY0 +METAL M EH1 T AH0 L +METAL'S M EH1 T AH0 L Z +METALL M EH1 T AO1 L +METALLATZ M EH1 T AE1 L AH0 T S +METALLGESELLSCHAFT M EH2 T AH0 L G EH1 S AH0 L SH AE2 F T +METALLGESELLSCHAFT'S M EH2 T AH0 L G EH1 S AH0 L SH AE2 F T S +METALLIC M AH0 T AE1 L IH0 K +METALLIC'S M AH0 T AE1 L IH0 K S +METALLICA M AH0 T AE1 L IH0 K AH0 +METALLICA'S M AH0 T AE1 L IH0 K AH0 Z +METALLICS M AH0 T AE1 L IH0 K S +METALLO M EH0 T AA1 L OW0 +METALLURGICAL M EH2 T AH0 L ER1 JH IH0 K AH0 L +METALLURGY M EH1 T AH0 L ER0 JH IY0 +METALS M EH1 T AH0 L Z +METALS' M EH1 T AH0 L Z +METALWORK M EH1 T AH0 L W ER2 K +METALWORKER M EH1 T AH0 L W ER2 K ER0 +METALWORKERS M EH1 T AH0 L W ER2 K ER0 Z +METALWORKING M EH1 T AH0 L W ER2 K IH0 NG +METAMORPHASIS M EH2 T AH0 M AO1 R F AH0 S AH0 S +METAMORPHIC M EH2 T AH0 M AO1 R F IH0 K +METAMORPHOSE M EH2 T AH0 M AO1 R F OW0 Z +METAMORPHOSIS M EH2 T AH0 M AO1 R F AH0 S AH0 S +METAMUCIL M EH2 T AH0 M Y UW1 S AH0 L +METAMUCIL'S M EH2 T AH0 M Y UW1 S AH0 L Z +METAPHOR M EH1 T AH0 F AO0 R +METAPHORICAL M EH2 T AH0 F AO1 R IH0 K AH0 L +METAPHORICALLY M EH2 T AH0 F AO1 R IH0 K L IY0 +METAPHORS M EH1 T AH0 F AO0 R Z +METAPHYSICAL M EH2 T AH0 F IH1 Z IH0 K AH0 L +METAPHYSICS M EH2 T AH0 F IH1 Z IH0 K S +METASTASES M AH0 T AE1 S T EY2 S IY0 S +METASTASIS M AH0 T AE1 S T AH0 S IH0 S +METASTASIZE M AH0 T AE1 S T AH0 S AY2 Z +METASTASIZED M AH0 T AE1 S T AH0 S AY2 Z D +METASTATIC M EH2 T AH0 S T AE1 T IH0 K +METATHORAX M EH2 T AH0 TH AO1 R AE2 K S +METAVSKY M AH0 T AE1 V S K IY0 +METAXAS M AH0 T AE1 K S AH0 S +METCALF M EH1 T K AE2 F +METCALFE M EH1 T K AH0 L F +METCOM M EH1 T K AA0 M +METE M IY1 T +METE(1) M EH1 T AH0 +METED M IY1 T IH0 D +METEOR M IY1 T IY0 ER0 +METEORIC M IY2 T IY0 AO1 R IH0 K +METEORITE M IY1 T IY0 AO0 R AY2 T +METEOROLOGICAL M IY2 T IY0 AO2 R AH0 L AA1 JH IH0 K AH0 L +METEOROLOGIST M IY2 T IY0 ER0 AA1 L AH0 JH IH0 S T +METEOROLOGIST'S M IY2 T IY0 ER0 AA1 L AH0 JH IH0 S T S +METEOROLOGISTS M IY2 T IY0 ER0 AA1 L AH0 JH IH0 S T S +METEOROLOGY M IY2 T IY0 ER0 AA1 L AH0 JH IY0 +METEORS M IY1 T IY0 ER0 Z +METER M IY1 T ER0 +METERED M IY1 T ER0 D +METERING M IY1 T ER0 IH0 NG +METERS M IY1 T ER0 Z +METEX M EH1 T EH2 K S +METH M EH1 TH +METHADONE M EH1 TH AH0 D OW2 N +METHAMPHETAMINE M EH2 TH AE0 M F EH1 T AH0 M IY0 N +METHAMPHETAMINE(1) M EH2 TH AE0 M F EH1 T AH0 M AY0 N +METHANE M EH1 TH EY2 N +METHANEX M EH1 TH AH0 N EH2 K S +METHANOL M EH1 TH AH0 N AA2 L +METHAZINE M EH1 TH AH0 Z IY2 N +METHENEY M EH1 TH IH0 N IY0 +METHENY M EH1 TH IH0 N IY0 +METHNER M EH1 TH N ER0 +METHOD M EH1 TH AH0 D +METHODE M AH0 TH OW1 D +METHODICAL M AH0 TH AA1 D AH0 K AH0 L +METHODICAL(1) M AH0 TH AA1 D IH0 K AH0 L +METHODICALLY M AH0 TH AA1 D IH0 K AH0 L IY0 +METHODICALLY(1) M AH0 TH AA1 D IH0 K L IY0 +METHODISM M EH1 TH AH0 D IH2 Z AH0 M +METHODISMS M EH1 TH AH0 D IH2 Z AH0 M Z +METHODIST M EH1 TH AH0 D AH0 S T +METHODIST(1) M EH1 TH AH0 D IH0 S T +METHODOLOGICAL M EH2 TH AH0 D AH0 L AA1 JH IH0 K AH0 L +METHODOLOGIES M EH2 TH OW0 D AA1 L AH0 JH IY0 Z +METHODOLOGY M EH2 TH AH0 D AA1 L AH0 JH IY0 +METHODS M EH1 TH AH0 D Z +METHOT M EH1 TH AH0 T +METHOTREXATE M EH2 TH OW0 T R EH1 K S EY2 T +METHOUGHT M EH1 TH AO2 T +METHUSELAH M AH0 TH Y UW1 Z AH0 L AH0 +METHVIN M EH1 TH V IH0 N +METHYL M EH1 TH AH0 L +METHYLENE M EH1 TH IH0 L IY2 N +METICS M EH1 T IH0 K S +METICULOUS M AH0 T IH1 K Y AH0 L AH0 S +METICULOUSLY M AH0 T IH1 K Y AH0 L AH0 S L IY0 +METIER M EH1 T Y ER0 +METIS M EH1 T IH0 S +METIVIER M EH1 T IH0 V IY0 ER0 +METLAKATLA M EH0 T L AH0 K AE1 T L AH0 +METLIFE M EH1 T L AY2 F +METOLACHLOR M AH0 T OW1 L AH0 K L ER0 +METONOMY M AH0 T AO1 N AH0 M IY0 +METOYER M EH1 T OY0 ER0 +METPATH M EH1 T P AE2 TH +METRA M EH1 T R AH0 +METRAHEALTH M EH1 T R AH0 HH EH2 L TH +METRE M IY1 T ER0 +METRES M IY1 T ER0 Z +METRIC M EH1 T R IH0 K +METRICAL M EH1 T R IH0 K AH0 L +METRICALLY M EH1 T R IH0 K AH0 L IY0 +METRICK M EH1 T R IH0 K +METRICS M EH1 T R IH0 K S +METRO M EH1 T R OW2 +METRO'S M EH1 T R OW0 Z +METROBANC M EH1 T R OW0 B AE2 NG K +METROBANK M EH1 T R OW0 B AE2 NG K +METROCALL M EH1 T R OW2 K AO2 L +METROCOLOR M EH1 T R OW0 K AH1 L ER0 +METROCORP M EH1 T R OW0 K AO2 R P +METRODADE M EH2 T R OW0 D EY1 D +METRODOME M EH1 T R OW0 D OW2 M +METRODOME(1) M EH1 T R AH0 D OW2 M +METROMAIL M EH1 T R OW0 M EY2 L +METROMEDIA M EH2 T R OW0 M IY1 D IY0 AH0 +METROPLEX M EH1 T R OW0 P L EH2 K S +METROPLEXES M EH1 T R OW0 P L EH2 K S IH0 Z +METROPOL M EH1 T R AH0 P OW2 L +METROPOL'S M EH1 T R AH0 P OW2 L Z +METROPOLI M AH0 T R AA1 P AH0 L IY0 +METROPOLIS M AH0 T R AA1 P AH0 L AH0 S +METROPOLITAIN M EH2 T R AH0 P AO1 L AH0 T AH0 N +METROPOLITAN M EH2 T R AH0 P AA1 L AH0 T AH0 N +METROPOLITAN'S M EH2 T R AH0 P AA1 L AH0 T AH0 N Z +METROPOLITANS M EH2 T R AH0 P AA1 L AH0 T AH0 N Z +METROSEXUAL M EH2 T R AH0 S EH1 K SH UW2 AH0 L +METS M EH1 T S +METS' M EH1 T S +METSKER M EH1 T S K ER0 +METTE M EH1 T +METTER M EH1 T ER0 +METTERNICH M EH1 T ER0 N IH0 CH +METTLE M EH1 T AH0 L +METTLEN M EH1 T L AH0 N +METTLER M EH1 T L ER0 +METTS M EH1 T S +METTUR M EH1 T ER0 +METZ M EH1 T S +METZE M EH1 T Z +METZENBAUM M EH1 T S AH0 N B AW2 M +METZENBAUM'S M EH1 T S AH0 N B AW2 M Z +METZER M EH1 T S ER0 +METZGAR M EH1 T S G ER0 +METZGER M EH1 T S G ER0 +METZGER'S M EH1 T S G ER0 Z +METZINGER M EH1 T Z IH0 NG ER0 +METZKER M EH1 T S K ER0 +METZLER M EH1 T S L ER0 +METZNER M EH1 T S N ER0 +MEUNIER M OY1 N IY0 ER0 +MEURER M ER1 ER0 +MEUSE M Y UW1 Z +MEUSER M OY1 S ER0 +MEUTH M Y UW1 TH +MEVACOR M EH1 V AH0 K AO2 R +MEVARACH M EH0 V AA1 R AH0 CH +MEVARACH'S M EH0 V AA1 R AH0 CH AH0 Z +MEVARACHS M EH0 V AA1 R AH0 CH AH0 Z +MEW M Y UW1 +MEWAS M Y UW1 AH0 S +MEWAS(1) M IY1 W AH0 S +MEWBORN M Y UW1 B ER0 N +MEWES M Y UW1 Z +MEX M EH1 K S +MEXICALI M EH2 K S IH0 K AA1 L IY0 +MEXICAN M EH1 K S AH0 K AH0 N +MEXICANA M EH2 K S IH0 K AE1 N AH0 +MEXICANO M EH2 K S IH0 K AA1 N OW0 +MEXICANOS M EH2 K S IH0 K AA1 N OW0 Z +MEXICANS M EH1 K S IH0 K AH0 N Z +MEXICO M EH1 K S AH0 K OW2 +MEXICO'S M EH1 K S AH0 K OW2 Z +MEY M EY1 +MEYER M AY1 ER0 +MEYER'S M AY1 ER0 Z +MEYERBEER M AY1 ER0 B IH2 R +MEYERHOFF M AY1 ER0 HH AO0 F +MEYERING M EY1 ER0 IH0 NG +MEYERMAN M AY1 ER0 M AH0 N +MEYEROWITZ M AY1 ER0 AH0 W IH0 T S +MEYERS M AY1 ER0 Z +MEYERSON M AY1 ER0 S AH0 N +MEYN M EY1 N +MEYO M EY1 OW0 +MEYOHAS M EY0 OW1 HH AA0 S +MEZ M EH1 Z +MEZA M EH1 Z AH0 +MEZERA M EY0 Z EH1 R AH0 +MEZEY M EH1 Z IY0 +MEZGER M EH1 Z JH ER0 +MEZHDUMARODNOM M EH0 Z D UW2 M AH0 R AA1 D N AH0 M +MEZO M EH1 Z OW0 +MEZRO M EH1 Z R OW0 +MEZUZAH M AH0 Z UH1 Z AH0 +MEZVINSKY M EH2 Z V IH1 N S K IY0 +MEZVINSKY'S M EH2 Z V IH1 N S K IY0 Z +MEZZALUNA M EH2 Z AH0 L UW1 N AH0 +MEZZALUNA(1) M EH2 T S AH0 L UW1 N AH0 +MEZZANINE M EH1 Z AH0 N IY2 N +MEZZO M EH1 Z OW0 +MFUME M AH0 F UW1 M EY2 +MG EH2 M G IY1 +MGM EH2 M G IY2 EH1 M +MH EH1 M EY1 CH +MHM AH0 M HH AH0 M +MHOON M HH UW1 N +MI M IY1 +MI-VAMI M IY0 V AE1 M IY0 +MIA M IY1 AH0 +MIAMI M AY0 AE1 M IY0 +MIAMI'S M AY0 AE1 M IY0 Z +MIANO M IY0 AA1 N OW0 +MIARA M AY0 AA1 R AH0 +MIASMA M IY0 AE1 Z M AH0 +MIASMA(1) M AY0 AE1 Z M AH0 +MIATA M IY0 AA1 T AH0 +MIAZGA M IY0 AA1 Z G AH0 +MIB M IH1 B +MIC M IH1 K +MICA M AY1 K AH0 +MICAELA M IY0 K EY1 L AH0 +MICAH M AY1 K AH0 +MICALE M IY0 K AA1 L IY0 +MICALLEF M IH1 K AH0 L EH0 F +MICANOPY M IH0 K AE1 N AH0 P IY0 +MICATIN M AY1 K AH0 T IH0 N +MICCICHE M IY0 CH IY1 K IY0 +MICCIO M IY1 CH IY0 OW0 +MICCOSUKEE M IH2 K AH0 S UW2 K IY2 +MICE M AY1 S +MICEK M IH1 CH EH0 K +MICELI M IY0 CH EH1 L IY0 +MICH M IH1 CH +MICHAEL M AY1 K AH0 L +MICHAEL'S M AY1 K AH0 L Z +MICHAELA M AY0 K EH1 L AH0 +MICHAELINA M AY2 K AH0 L IY1 N AH0 +MICHAELINE M AY1 K AH0 L AY0 N +MICHAELINE(1) M AY1 K AH0 L IY0 N +MICHAELIS M AY2 K EH1 L IH0 S +MICHAELLA M AY2 K EH1 L AH0 +MICHAELS M AY1 K AH0 L Z +MICHAELSEN M AY1 K AH0 L S AH0 N +MICHAELSON M AY1 K AH0 L S AH0 N +MICHAL M IH1 CH AH0 L +MICHALAK M IH1 CH AH0 L AE0 K +MICHALEC M IH0 HH AA1 L IH0 K +MICHALEK M IH0 HH AA1 L EH0 K +MICHALIK M IH1 K AH0 L IH0 K +MICHALOWSKI M IH2 CH AH0 L AO1 F S K IY0 +MICHALS M IH1 CH AH0 L Z +MICHALSKI M IH2 CH AA1 L S K IY0 +MICHALSKY M IH2 CH AA1 L S K IY0 +MICHAUD M IH0 SH OW1 +MICHAUX M IH0 SH OW1 +MICHCON M IH1 SH K AA0 N +MICHCON'S M IH1 SH K AA0 N Z +MICHEAL M AY1 K AH0 L +MICHEAUX M IH0 SH 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AH0 T +MICROCLIMATES M AY1 K R OW0 K L AY2 M AH0 T S +MICROCODE M AY1 K R OW0 K OW2 D +MICROCODES M AY1 K R OW0 K OW2 D Z +MICROCOM M AY1 K R OW0 K AA2 M +MICROCOMPUTER M AY1 K R OW2 K AH0 M P Y UW1 T ER0 +MICROCOMPUTERS M AY1 K R OW2 K AH0 M P Y UW1 T ER0 Z +MICROCOSM M AY1 K R AH0 K AA2 Z AH0 M +MICROCREDIT M AY1 K R OW2 K R EH1 D IH0 T +MICRODYNE M AY1 K R OW0 D AY2 N +MICROECONOMIC M AY2 K R OW0 EH2 K AH0 N AA1 M IH0 K +MICROECONOMICS M AY2 K R OW0 EH2 K AH0 N AA1 M IH0 K S +MICROELECTRONIC M AY2 K R OW0 IH0 L EH0 K T R AA1 N IH0 K +MICROELECTRONICS M AY2 K R OW0 IH0 L EH0 K T R AA1 N IH0 K S +MICROELETTRONICA M AY2 K R OW0 IH0 L EH0 T R AA1 N IH0 K AH0 +MICROFICHE M AY1 K R OW0 F IY2 CH +MICROFILM M AY1 K R AH0 F IH2 L M +MICROFOSSIL M AY1 K R OW2 F AA1 S AH0 L +MICROFOSSILS M AY1 K R OW2 F AA1 S AH0 L Z +MICROGENESYS M AY2 K R OW0 JH EH1 N AH0 S IH0 S +MICROGRAFX M AY2 K R OW0 G R AE1 F EH0 K S +MICROGRAM M AY1 K R OW0 G R AE2 M +MICROGRAMS M AY1 K R OW0 G R AE2 M Z +MICROGRAPHIC M AY2 K R OW0 G R AE1 F IH0 K +MICROGRAPHICS M AY2 K R OW0 G R AE1 F IH0 K S +MICROLITER M AY1 K R OW0 L IY0 T ER0 +MICROLITERS M AY1 K R OW0 L IY0 T ER0 Z +MICROMANAGE M AY2 K R OW0 M AE1 N IH0 JH +MICROMANAGED M AY2 K R OW0 M AE1 N IH0 JH D +MICROMANAGEMENT M AY2 K R OW0 M AE1 N IH0 JH M AH0 N T +MICROMANAGES M AY2 K R OW0 M AE1 N IH0 JH AH0 Z +MICROMANAGING M AY2 K R OW0 M AE1 N IH0 JH IH0 NG +MICROMETER M AY0 K R AA1 M AH0 T ER0 +MICROMETERS M AY0 K R AA1 M AH0 T ER0 Z +MICRON M AY1 K R AA2 N +MICRON'S M AY1 K R AA2 N Z +MICRONESIA M AY2 K R OW0 N IY1 ZH AH0 +MICRONIC M AY2 K R AO1 N IH2 K +MICRONICS M AY2 K R AO1 N IH2 K S +MICRONS M AY1 K R AA2 N Z +MICROORGANISM M AY2 K R OW0 AO1 R G AH0 N IH2 Z AH0 M +MICROORGANISMS M AY2 K R OW0 AO1 R G AH0 N IH2 Z AH0 M Z +MICROPALEONTOLOGY M AY2 K R OW0 P EY2 L IY0 AH0 N T AA1 L AH0 JH IY0 +MICROPHONE M AY1 K R AH0 F OW2 N +MICROPHONES M AY1 K R OW0 F OW2 N Z +MICROPOLIS M AY2 K R AO1 P AH0 L IH0 S +MICROPRO M AY1 K R OW0 P R OW2 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ER0 Z +MILLIN M IH1 L AH0 N +MILLINER M IH1 L IH0 N ER0 +MILLING M IH1 L IH0 NG +MILLINGTON M IH1 L IH0 NG T AH0 N +MILLION M IH1 L Y AH0 N +MILLION-DOLLAR M IH1 L Y AH0 N D AO2 L ER0 +MILLIONAIRE M IH2 L Y AH0 N EH1 R +MILLIONAIRE'S M IH2 L Y AH0 N EH1 R Z +MILLIONAIRES M IH2 L Y AH0 N EH1 R Z +MILLIONS M IH1 L Y AH0 N Z +MILLIONTH M IH1 L Y AH0 N TH +MILLIONTHS M IH1 L Y AH0 N T TH S +MILLIPORE M IH1 L IH0 P AO2 R +MILLIRON M IH1 L ER0 AH0 N +MILLIRONS M IH1 L ER0 OW0 N Z +MILLIS M IH1 L IH0 S +MILLISECOND M IH1 L IH0 S EH2 K AH0 N D +MILLISECONDS M IH1 L IH0 S EH2 K AH0 N D Z +MILLISENT M IH1 L AH0 S AH0 N T +MILLMAN M IH1 L M AH0 N +MILLN M IH1 L N +MILLNER M IH1 L N ER0 +MILLON M IH1 L AH0 N +MILLOY M IH1 L OY0 +MILLS M IH1 L Z +MILLS' M IH1 L Z +MILLS'S M IH1 L Z IH0 Z +MILLSAP M IH1 L S AE2 P +MILLSAPS M IH1 L S AE2 P S +MILLSPAUGH M IH1 L S P AO0 +MILLSTEIN M IH1 L S T AY2 N +MILLSTEIN(1) M IH1 L S T IY2 N +MILLSTONE M IH1 L S T OW2 N +MILLWARD M IH1 L W ER0 D +MILLWOOD M IH1 L W UH2 D +MILLWORKER M IH1 L W AO0 R K ER0 +MILLWORKERS M IH1 L W AO0 R K ER0 Z +MILLWORKING M IH1 L W AO0 R K IH0 NG +MILLY M IH1 L IY0 +MILMAN M IH1 L M AH0 N +MILNE M IH1 L N +MILNER M IH1 L N ER0 +MILNES M IH1 L N Z +MILO M AY1 L OW0 +MILODIC M IH0 L OW1 D IH0 K +MILONAS M IY0 L OW1 N AA0 Z +MILONE M IH0 L OW1 N +MILOS M IY1 L OW0 Z +MILOSEVIC M IH0 L OW1 S AH0 V IH0 K +MILOSEVIC(1) M IH0 L OW1 S AH0 V IH0 CH +MILOSEVIC'S M IH0 L OW1 S AH0 V IH0 CH IH0 Z +MILOSEVICH M IH0 L AA1 S IH0 V IH0 CH +MILOSH M IH0 L AO1 SH +MILOT M IH1 L AH0 T +MILPITAS M IH0 L P IY1 T AH0 S +MILROY M IH1 L R OY2 +MILS M IH1 L Z +MILSAP M IH1 L S AE2 P +MILSON M IH1 L S AH0 N +MILSTEAD M IH1 L S T EH2 D +MILSTEIN M IH1 L S T AY2 N +MILSTEIN(1) M IH1 L S T IY2 N +MILT M IH1 L T +MILTENBERGER M IH1 L T AH0 N B ER0 G ER0 +MILTIE M IH1 T IY0 +MILTNER M IH1 L T N ER0 +MILTON M IH1 L T AH0 N +MILTONIC M IH0 L T AA1 N IH0 K +MILUM M IH1 L AH0 M +MILUNOVICH M IH0 L UW1 N AH0 V IH0 CH +MILWARD M IH1 L W ER0 D 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P R IY0 EY2 T +MISAPPROPRIATED M IH2 S AH0 P R OW1 P R IY0 EY2 T IH0 D +MISAPPROPRIATES M IH2 S AH0 P R OW1 P R IY0 EY2 T S +MISAPPROPRIATING M IH2 S AH0 P R OW1 P R IY0 EY2 T IH0 NG +MISAPPROPRIATION M IH2 S AH0 P R OW2 P R IY0 EY1 SH AH0 N +MISATER M IH0 S EY1 T ER0 +MISAWA M IH0 S AA1 W AH0 +MISBEGOTTEN M IH2 S B AH0 G AA1 T AH0 N +MISBEHAVE M IH2 S B AH0 HH EY1 V +MISBEHAVE(1) M IH2 S B IY0 HH EY1 V +MISBEHAVED M IH2 S B AH0 HH EY1 V D +MISBEHAVED(1) M IH2 S B IY0 HH EY1 V D +MISBEHAVES M IH2 S B AH0 HH EY1 V Z +MISBEHAVES(1) M IH2 S B IY0 HH EY1 V Z +MISBEHAVING M IH2 S B AH0 HH EY1 V IH0 NG +MISBEHAVING(1) M IH2 S B IY0 HH EY1 V IH0 NG +MISBEHAVIOR M IH2 S B AH0 HH EY1 V Y ER0 +MISBEHAVIOR(1) M IH2 S B IY0 HH EY1 V Y ER0 +MISBRENER M IH1 S B R EH2 N ER0 +MISCALCULATE M IH0 S K AE1 L K Y AH0 L EY2 T +MISCALCULATED M IH0 S K AE1 L K Y AH0 L EY2 T IH0 D +MISCALCULATES M IH0 S K AE1 L K Y AH0 L EY2 T S +MISCALCULATION M IH0 S K AE1 L K Y AH0 L EY1 SH AH0 N +MISCALCULATIONS M IH0 S K AE1 L K Y AH0 L EY1 SH AH0 N Z +MISCARRIAGE M IH0 S K EH1 R AH0 JH +MISCARRIAGES M IH0 S K EH1 R IH0 JH IH0 Z +MISCAST M IH0 S K AE1 S T +MISCAVIGE M IH0 S K AE1 V IH1 JH +MISCAYUNA M IH2 S K AY0 Y UW1 N AH0 +MISCAYUNA'S M IH2 S K AY0 Y UW1 N AH0 Z +MISCELLANEOUS M IH2 S AH0 L EY1 N IY0 AH0 S +MISCELLANY M IH1 S AH0 L EY2 N IY0 +MISCH M IH1 SH +MISCHA M IH1 SH AH0 +MISCHARACTERIZATION M IH0 S K AE2 R AH0 K T ER0 AH0 Z EY1 SH AH0 N +MISCHARACTERIZATIONS M IH0 S K AE2 R AH0 K T ER0 AH0 Z EY1 SH AH0 N Z +MISCHARACTERIZE M IH0 S K AE1 R AH0 K T ER0 AY2 Z +MISCHARACTERIZED M IH0 S K AE1 R AH0 K T ER0 AY2 Z D +MISCHARACTERIZES M IH0 S K AE1 R AH0 K T ER0 AY2 Z IH0 Z +MISCHARACTERIZING M IH0 S K AE1 R AH0 K T ER0 AY2 Z IH0 NG +MISCHARGE M IH0 S CH AA1 R JH +MISCHARGED M IH0 S CH AA1 R JH D +MISCHARGES M IH0 S CH AA1 R JH IH0 Z +MISCHARGING M IH0 S CH AA1 R JH IH0 NG +MISCHEL M IH1 SH AH0 L +MISCHER M IH1 SH ER0 +MISCHIEF M IH1 S CH AH0 F +MISCHIEVOUS M IH1 S CH AH0 V AH0 S +MISCHKE M IH1 SH K +MISCHLER M IH1 SH AH0 L ER0 +MISCHLER(1) M IH1 SH L ER0 +MISCIBILITY M IH2 S IH0 B IH1 L IH0 T IY0 +MISCIBLE M IH1 S AH0 B AH0 L +MISCIBLE(1) M IH1 S IH0 B AH0 L +MISCOMMUNICATE M IH0 S K AH0 M Y UW1 N AH0 K EY2 T +MISCOMMUNICATION M IH0 S K AH0 M Y UW2 N AH0 K EY1 SH AH0 N +MISCONCEIVE M IH0 S K AH0 N S IY1 V +MISCONCEIVED M IH0 S K AH0 N S IY1 V D +MISCONCEIVES M IH0 S K AH0 N S IY1 V Z +MISCONCEIVING M IH0 S K AH0 N S IY1 V IH0 NG +MISCONCEPTION M IH0 S K AH0 N S EH1 P SH AH0 N +MISCONCEPTIONS M IH0 S K AH0 N S EH1 P SH AH0 N Z +MISCONDUCT M IH0 S K AA1 N D AH0 K T +MISCONSTRUE M IH0 S K AH0 N S T R UW1 +MISCONSTRUED M IH2 S K AH0 N S T R UW1 D +MISCONSTRUES M IH0 S K AH0 N S T R UW1 Z +MISCONSTRUING M IH0 S K AH0 N S T R UW1 IH0 NG +MISCOUNT M IH1 S K AW1 N T +MISCREANT M IH1 S K R IY0 AH0 N T +MISCREANTS M IH1 S K R IY0 AH0 N T S +MISCREATION M IH0 S K R IY0 EY1 SH AH0 N +MISCREATIONS M IH2 S K R IY0 EY1 SH AH0 N Z +MISCUE M IH1 S K Y UW2 +MISCUES M IH1 S K Y UW2 Z +MISDEED M IH1 S D IY1 D +MISDEEDS M IH0 S D IY1 D Z +MISDEMEANOR M IH2 S D AH0 M IY1 N ER0 +MISDEMEANORS M IH2 S D AH0 M IY1 N ER0 Z +MISDIAGNOSE M IH0 S D AY2 IH0 G N OW1 Z +MISDIAGNOSED M IH0 S D AY2 IH0 G N OW1 Z D +MISDIAGNOSES M IH0 S D AY2 IH0 G N OW1 S IY0 Z +MISDIAGNOSES(1) M IH0 S D AY2 IH0 G N OW1 S AH0 Z +MISDIAGNOSIS M IH0 S D AY2 IH0 G N OW1 S AH0 S +MISDIRECT M IH0 S D IH0 R EH1 K T +MISDIRECTED M IH0 S D IH0 R EH1 K T IH0 D +MISEK M IH1 S EH0 K +MISENER M IH1 S IY0 N ER0 +MISENHEIMER M IH1 S IH0 N HH AY0 M ER0 +MISER M AY1 Z ER0 +MISERABLE M IH1 Z ER0 AH0 B AH0 L +MISERABLE(1) M IH1 Z R AH0 B AH0 L +MISERABLES M IH1 Z ER0 AH0 B AH0 L Z +MISERABLES(1) M IH1 Z R AH0 B AH0 L Z +MISERABLES(2) M IH2 Z ER0 AA1 B +MISERABLY M IH1 Z ER0 AH0 B L IY0 +MISERABLY(1) M IH1 Z R AH0 B L IY0 +MISERATION M IH0 Z ER0 EY1 SH AH0 N +MISERIES M IH1 Z ER0 IY0 Z +MISERLY M AY1 Z ER0 L IY0 +MISERS M AY1 Z ER0 Z +MISERY M IH1 Z ER0 IY0 +MISES M AY1 Z IH0 Z +MISFELDT M IH1 S F IH0 L T +MISFIRE M IH0 S F AY1 ER0 +MISFIT M IH1 S F IH2 T +MISFITS M IH1 S F IH2 T S +MISFORTUNE M IH0 S F AO1 R CH AH0 N +MISFORTUNES M IH0 S F AO1 R CH AH0 N Z +MISGIVE M IH0 S G IH1 V +MISGIVING M IH0 S G IH1 V IH0 NG +MISGIVINGS M IH0 S G IH1 V IH0 NG Z +MISGOVERNMENT M IH0 S G AH1 V ER0 N M AH0 N T +MISGUIDE M IH0 S G AY1 D +MISGUIDED M IH0 S G AY1 D IH0 D +MISGUIDES M IH0 S G AY1 D Z +MISH M IH1 SH +MISHA M IH1 SH AH0 +MISHANDLE M IH0 S HH AE1 N D AH0 L +MISHANDLED M IH0 S HH AE1 N D AH0 L D +MISHANDLES M IH0 S HH AE1 N D AH0 L Z +MISHANDLING M IH0 S HH AE1 N D L IH0 NG +MISHAP M IH1 S HH AE2 P +MISHAPS M IH1 S HH AE2 P S +MISHAWAKA M IH2 SH AH0 W AO1 K AH0 +MISHAWAUM M IH1 SH AH0 W AA2 M +MISHAWUM M IH1 SH AH0 W AH2 M +MISHEAR M IH0 S HH IY1 R +MISHEARD M IH2 S HH ER1 D +MISHKIN M IY1 SH K IY0 N +MISHLER M IH1 SH L ER0 +MISHMASH M IH1 SH M AE2 SH +MISHOE M IY1 SH UW0 +MISHRA M IH1 SH R AH0 +MISIAK M IH1 S IY0 AE0 K +MISIASZEK M IH0 S IY0 AA1 SH EH0 K +MISIDENTIFICATION M IH2 S AY0 D EH2 N T IH0 F IH0 K EY1 SH AH0 N +MISIDENTIFICATION(1) M IH2 S AY0 D EH2 N IH0 F IH0 K EY1 SH AH0 N +MISIDENTIFIED M IH0 S AY0 D EH1 N T IH0 F AY2 D +MISIDENTIFIED(1) M IH0 S AY0 D EH1 N IH0 F AY2 D +MISIDENTIFIES M IH0 S AY0 D EH1 N T IH0 F AY2 Z +MISIDENTIFIES(1) M IH0 S AY0 D EH1 N IH0 F AY2 Z +MISIDENTIFY M IH0 S AY0 D EH1 N T AH0 F AY2 +MISIDENTIFY(1) M IH0 S AY0 D EH1 N AH0 F AY2 +MISIDENTIFYING M IH0 S AY0 D EH1 N T AH0 F AY2 IH0 NG +MISIDENTIFYING(1) M IH0 S AY0 D EH1 N AH0 F AY2 IH0 NG +MISIEWICZ M IH1 S AH0 V IH0 CH +MISIMPRESSION M IH0 S IH0 M P R EH1 SH AH0 N +MISINFORM M IH0 S IH2 N F AO1 R M +MISINFORMATION M IH2 S IH0 N F ER0 M EY1 SH AH0 N +MISINFORMED M IH0 S IH0 N F AO1 R M D +MISINFORMING M IH0 S IH0 N F AO1 R M IH0 NG +MISINFORMS M IH0 S IH2 N F AO1 R M Z +MISINTERPRET M IH0 S IH0 N T ER1 P R AH0 T +MISINTERPRETATION M IH0 S IH0 N T ER2 P R AH0 T EY1 SH AH0 N +MISINTERPRETED M IH0 S IH0 N T ER1 P R AH0 T IH0 D +MISINTERPRETING M IH0 S IH0 N T ER1 P R AH0 T IH0 NG +MISINTERPRETS M IH0 S IH0 N T ER1 P R AH0 T S +MISJUDGE M IH0 S JH AH1 JH +MISJUDGED M IH0 S JH AH1 JH D +MISJUDGES M IH0 S JH AH1 JH IH0 Z +MISJUDGING M IH0 S JH AH1 JH IH0 NG +MISJUDGMENT M IH0 S JH AH1 JH M AH0 N T +MISJUDGMENTS M IH0 S JH AH1 JH M AH0 N T S +MISKA M IH1 S K AH0 +MISKE M IH1 S K +MISKELL M IH1 S K AH0 L +MISKITO M IH0 S K IY1 T OW0 +MISKITOS M IH0 S K IY1 T OW0 S +MISKO M IH1 S K OW0 +MISLABEL M IH0 S L EY1 B AH0 L +MISLABELED M IH0 S L EY1 B AH0 L D +MISLABELING M IH0 S L EY1 B AH0 L IH0 NG +MISLABELING(1) M IH0 S L EY1 B L IH0 NG +MISLABELS M IH0 S L EY1 B AH0 L Z +MISLAID M IH0 S L EY1 D +MISLEAD M IH0 S L IY1 D +MISLEADING M IH0 S L IY1 D IH0 NG +MISLEADINGLY M IH0 S L IY1 D IH0 NG L IY0 +MISLEADS M IH0 S L IY1 D Z +MISLED M IH0 S L EH1 D +MISMANAGE M IH0 S M AE1 N IH0 JH +MISMANAGED M IH0 S M AE1 N IH0 JH D +MISMANAGEMENT M IH0 S M AE1 N IH0 JH M AH0 N T +MISMANAGES M IH0 S M AE1 N IH0 JH AH0 Z +MISMANAGING M IH0 S M AE1 N IH0 JH IH0 NG +MISMATCH M IH0 S M AE1 CH +MISMATCH(1) M IH1 S M AE2 CH +MISMATCHED M IH0 S M AE1 CH T +MISMATCHES M IH0 S M AE1 CH IH0 Z +MISNER M IH1 Z N ER0 +MISNOMER M IH0 S N OW1 M ER0 +MISOGYNE M IH1 Z AH0 JH IH0 N +MISOGYNIST M IH1 Z AH0 JH IH0 N IH0 S T +MISOGYNISTS M IH1 Z AH0 JH IH0 N IH0 S T S +MISOGYNISTS(1) M IH1 Z AH0 JH IH0 N IH0 S +MISOGYNY M IH1 Z AH0 JH IH0 N IY0 +MISPERCEIVE M IH0 S P ER0 S IY1 V +MISPERCEIVED M IH0 S P ER0 S IY1 V D +MISPERCEIVES M IH0 S P ER0 S IY1 V Z +MISPERCEPTION M IH2 S P ER0 S EH1 P SH AH0 N +MISPERCEPTIONS M IH0 S P ER0 S EH1 P SH AH0 N Z +MISPLACE M IH0 S P L EY1 S +MISPLACED M IH0 S P L EY1 S T +MISPLACES M IH0 S P L EY1 S IH0 Z +MISPLACING M IH0 S P L EY1 S IH0 NG +MISPRICE M IH0 S P R AY1 S +MISPRICED M IH0 S P R AY1 S T +MISPRICES M IH0 S P R AY1 S IH0 Z +MISPRICING M IH0 S P R AY1 S IH0 NG +MISPRINT M IH1 S P R IH1 N T +MISPRINTED M IH1 S P R IH1 N T AH0 D +MISPRINTS M IH1 S P R IH1 N T S +MISPRISION M IH0 S P R IH1 ZH AH0 N +MISPRONOUNCE M IH0 S P R AH0 N AW1 N S +MISPRONOUNCED M IH0 S P R AH0 N AW1 N S T +MISPRONOUNCES M IH0 S P R AH0 N AW1 N S IH0 Z +MISPRONOUNCING M IH0 S P R AH0 N AW1 N S IH0 NG +MISQUOTE M IH0 S K W OW1 T +MISQUOTED M IH0 S K W OW1 T IH0 D +MISQUOTES M IH0 S K W OW1 T S +MISQUOTING M IH0 S K W OW1 T IH0 NG +MISREAD M IH0 S R IY1 D +MISREAD(1) M IH0 S R EH1 D +MISREADING M IH0 S R IY1 D IH0 NG +MISRECOGNITION M IH0 S R EH2 K AH0 G N IH1 SH AH0 N +MISRECOGNIZE M IH0 S R EH1 K AH0 G N AY2 Z +MISRECOGNIZED M IH0 S R EH1 K AH0 G N AY2 Z D +MISRECOGNIZES M IH0 S R EH1 K AH0 G N AY2 Z IH0 Z +MISRECOGNIZING M IH0 S R EH1 K AH0 G N AY2 Z IH0 NG +MISREMEMBER M IH0 S R IY0 M EH1 M B ER0 +MISREMEMBERED M IH0 S R IY0 M EH1 M B ER0 D +MISREPORT M IH0 S R IH0 P AO1 R T +MISREPORTED M IH0 S R IH0 P AO1 R T IH0 D +MISREPRESENT M IH0 S R EH2 P R AH0 Z EH1 N T +MISREPRESENTATION M IH0 S R EH2 P R IH0 Z EH0 N T EY1 SH AH0 N +MISREPRESENTATIONS M IH0 S R EH2 P R IH0 Z EH0 N T EY1 SH AH0 N Z +MISREPRESENTED M IH2 S R EH0 P R IH0 Z EH1 N T IH0 D +MISREPRESENTED(1) M IH2 S R EH0 P R IH0 Z EH1 N IH0 D +MISREPRESENTING M IH0 S R EH2 P R AH0 Z EH1 N T IH0 NG +MISREPRESENTING(1) M IH0 S R EH2 P R AH0 Z EH1 N IH0 NG +MISREPRESENTS M IH0 S R EH2 P R AH0 Z EH1 N T S +MISREPRESENTS(1) M IH0 S R EH2 P R AH0 Z EH1 N S +MISRULE M IH0 S R UW1 L +MISS M IH1 S +MISSAL M IH1 S AH0 L +MISSED M IH1 S T +MISSEL M IH1 S AH0 L +MISSES M IH1 S IH0 Z +MISSETT M IH1 S AH0 T +MISSEY M IH1 S IY0 +MISSHAPEN M IH0 S SH EY1 P AH0 N +MISSHAPEN(1) M IH0 S HH AE1 P AH0 N +MISSIE M IH1 S IY0 +MISSILDINE M IH0 S IY0 L D IY1 N IY0 +MISSILDINE(1) M IH0 S IH0 L D AY1 N +MISSILE M IH1 S AH0 L +MISSILE'S M IH1 S AH0 L Z +MISSILES M IH1 S AH0 L Z +MISSILES' M IH1 S AH0 L Z +MISSIMER M IH1 S IH0 M ER0 +MISSING M IH1 S IH0 NG +MISSION M IH1 SH AH0 N +MISSION'S M IH1 SH AH0 N Z +MISSIONARIES M IH1 SH AH0 N EH2 R IY0 Z +MISSIONARY M IH1 SH AH0 N EH2 R IY0 +MISSIONS M IH1 SH AH0 N Z +MISSIS M IH1 S IH0 Z +MISSISSAUGA M IH2 S IH0 S AO1 G AH0 +MISSISSIPPI M IH2 S IH0 S IH1 P IY0 +MISSISSIPPI'S M IH2 S IH0 S IH1 P IY0 Z +MISSISSIPPIAN M IH2 S IH0 S IH1 P IY0 AH0 N +MISSISSIPPIANS M IH2 S IH0 S IH1 P IY0 AH0 N Z +MISSISSIPPIS M IH2 S IH0 S IH1 P IY0 Z +MISSIVE M IH1 S IH0 V +MISSLER M IH1 S L ER0 +MISSOULA M IH0 Z UW1 L AH0 +MISSOURI M AH0 Z UH1 R IY0 +MISSOURI(1) M AH0 Z ER1 AH0 +MISSOURI'S M AH0 Z UH1 R IY0 Z +MISSOURI'S(1) M AH0 Z ER1 AH0 Z +MISSOURIAN M AH0 Z UH1 R IY0 AH0 N +MISSOURIANS M AH0 Z UH1 R IY0 AH0 N Z +MISSPEAK M IH0 S S P IY1 K +MISSPEAK(1) M IH0 S P IY1 K +MISSPELL M IH0 S S P EH1 L +MISSPELL(1) M IH0 S P EH1 L +MISSPELLED M IH0 S S P EH1 L D +MISSPELLED(1) M IH0 S P EH1 L D +MISSPELLING M IH0 S S P EH1 L IH0 NG +MISSPELLING(1) M IH0 S P EH1 L IH0 NG +MISSPELLS M IH0 S S P EH1 L Z +MISSPELLS(1) M IH0 S P EH1 L Z +MISSPEND M IH0 S S P EH1 N D +MISSPEND(1) M IH0 S P EH1 N D +MISSPENDING M IH0 S S P EH1 N D IH0 NG +MISSPENDING(1) M IH0 S P EH1 N D IH0 NG +MISSPENT M IH0 S S P EH1 N T +MISSPENT(1) M IH0 S P EH1 N T +MISSPOKE M IH0 S S P OW1 K +MISSPOKE(1) M IH0 S P OW1 K +MISSPOKEN M IH0 S S P OW1 K AH0 N +MISSPOKEN(1) M IH0 S P OW1 K AH0 N +MISSTATE M IH0 S S T EY1 T +MISSTATE(1) M IH0 S T EY1 T +MISSTATED M IH0 S S T EY1 T IH0 D +MISSTATED(1) M IH0 S T EY1 T IH0 D +MISSTATEMENT M IH0 S T EY1 T M AH0 N T +MISSTATEMENTS M IH0 S T EY1 T M AH0 N T S +MISSTATEMENTS(1) M IH0 S T EY1 T M AH0 N S +MISSTATES M IH0 S S T EY1 T S +MISSTATES(1) M IH0 S T EY1 T S +MISSTATING M IH0 S S T EY1 T IH0 NG +MISSTATING(1) M IH0 S T EY1 T IH0 NG +MISSTEP M IH0 S S T EH1 P +MISSTEP(1) M IH0 S T EH1 P +MISSTEPS M IH0 S S T EH1 P S +MISSTEPS(1) M IH0 S T EH1 P S +MISSUS M IH1 S IH0 Z +MISSY M IH1 S IY0 +MISSY'S M IH1 S IY0 Z +MIST M IH1 S T +MISTAKE M IH0 S T EY1 K +MISTAKEN M IH0 S T EY1 K AH0 N +MISTAKENLY M IH0 S T EY1 K AH0 N L IY0 +MISTAKES M IH0 S T EY1 K S +MISTAKING M IH0 S T EY1 K IH0 NG +MISTER M IH1 S T ER0 +MISTERO M IH0 S T EH1 R OW0 +MISTERS M IH1 S T ER0 Z +MISTIC M IH1 S T IH0 K +MISTLER M IH1 S T L ER0 +MISTLETOE M IH1 S AH0 L T OW2 +MISTOOK M IH0 S T UH1 K +MISTRAL M IH1 S T R AH0 L +MISTREAT M IH0 S T R IY1 T +MISTREATED M IH0 S T R IY1 T IH0 D +MISTREATING M IH0 S T R IY1 T IH0 NG +MISTREATMENT M IH0 S T R IY1 T M AH0 N T +MISTREATS M IH0 S T R IY1 T S +MISTRESS M IH1 S T R AH0 S +MISTRESSES M IH1 S T R AH0 S AH0 Z +MISTRESSES(1) M IH1 S T R AH0 S IH0 Z +MISTRETTA M IH0 S T R EH1 T AH0 +MISTRIAL M IH0 S T R AY1 AH0 L +MISTRIAL(1) M IH1 S T R AY2 AH0 L +MISTRIALS M IH0 S T R AY1 AH0 L Z +MISTRIALS(1) M IH1 S T R AY2 AH0 L Z +MISTRUST M IH0 S T R AH1 S T +MISTRUSTED M IH0 S T R AH1 S T IH0 D +MISTRUSTFUL M IH0 S T R AH1 S T F AH0 L +MISTRUSTFUL(1) M IH0 S T R AH1 S F AH0 L +MISTRUSTING M IH0 S T R AH1 S T IH0 NG +MISTRUSTS M IH0 S T R AH1 S T S +MISTRUSTS(1) M IH0 S T R AH1 S +MISTRY M IH1 S T R IY0 +MISTRY(1) M IH0 S T R AY1 +MISTS M IH1 S T S +MISTY M IH1 S T IY0 +MISUNDER M IH0 S AH1 N D ER0 +MISUNDERSTAND M IH2 S AH0 N D ER0 S T AE1 N D +MISUNDERSTANDING M IH2 S AH0 N D ER0 S T AE1 N D IH0 NG +MISUNDERSTANDINGS M IH2 S AH0 N D ER0 S T AE1 N D IH0 NG Z +MISUNDERSTANDS M IH2 S AH0 N D ER0 S T AE1 N D Z +MISUNDERSTOOD M IH2 S AH0 N D ER0 S T UH1 D +MISURACA M IH0 S UH0 R AA1 K AH0 +MISUSE M IH0 S Y UW1 Z +MISUSE(1) M IH0 S Y UW1 S +MISUSED M IH0 S Y UW1 Z D +MISUSES M IH0 S Y UW1 Z IH0 Z +MISUSES(1) M IH0 S Y UW1 S IH0 Z +MISUSING M IH0 S Y UW1 Z IH0 NG +MIT EH1 M AY1 T IY1 +MIT(1) M IH1 T +MITA M IY1 T AH0 +MITAMURA M IY2 T AH0 M UH1 R AH0 +MITCH M IH1 CH +MITCHAM M IH1 CH AH0 M +MITCHEL M IH1 CH AH0 L +MITCHELL M IH1 CH AH0 L +MITCHELL'S M IH1 CH AH0 L Z +MITCHELSON M IH1 CH AH0 L S AH0 N +MITCHELTREE M IH0 CH IH0 L T R IY1 +MITCHEM M IH1 CH IH0 M +MITCHEN M IH1 CH AH0 N +MITCHENER M IH1 CH IY0 N ER0 +MITCHNER M IH1 CH N ER0 +MITCHUM M IH1 CH AH0 M +MITE M AY1 T +MITEK M AY1 T EH2 K +MITEL M AY1 T EH2 L +MITER M AY1 T ER0 +MITERING M AY1 T ER0 IH0 NG +MITES M AY1 T S +MITHCELL M IH1 TH S AH0 L +MITHRIDATE M IH1 TH R IH0 D EY2 T +MITHRIDATES M IH1 TH R IH0 D EY2 T S +MITHUN M IH1 TH AH0 N +MITI M IH1 T IY2 +MITI(1) 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T EY2 T AH0 D +NECESSITATES N AH0 S EH1 S AH0 T EY2 T S +NECESSITATING N AH0 S EH1 S IH0 T EY2 T IH0 NG +NECESSITIES N AH0 S EH1 S IH0 T IY0 Z +NECESSITY N AH0 S EH1 S AH0 T IY0 +NECESSITY(1) N AH0 S EH1 S IH0 T IY0 +NECHAYEV N EH2 CH AY1 EH0 V +NECHYBA N EH2 CH IY1 B AH0 +NECK N EH1 K +NECKED N EH1 K T +NECKER N EH1 K ER0 +NECKLACE N EH1 K L AH0 S +NECKLACES N EH1 K L AH0 S IH0 Z +NECKLACING N EH1 K L AH0 S IH0 NG +NECKS N EH1 K S +NECKTIE N EH1 K T AY2 +NECKTIES N EH1 K T AY2 Z +NECKWEAR N EH1 K W EH2 R +NECMETTIN N EH2 JH M EH1 T IH0 N +NECO N IY1 K OW0 +NECO'S N IY1 K OW0 Z +NECROLOGIST N AH0 K R AO1 L AH0 JH IH0 S T +NECROLOGISTS N AH0 K R AO1 L AH0 JH IH0 S T S +NECROLOGISTS(1) N AH0 K R AO1 L AH0 JH IH0 S +NECROLOGY N AH0 K R AO1 L AH0 JH IY0 +NECROMANCER N EH1 K R AH0 M AE2 N S ER0 +NECROMANCY N EH1 K R AH0 M AE2 N S IY0 +NECROPOLIS N AH0 K R AA1 P AH0 L AH0 S +NECROSIS N AH0 K R OW1 S AH0 S +NECTAR N EH1 K T ER0 +NECULA N EH1 K Y UW0 L AH0 +NED N EH1 D +NED'S N EH1 D Z +NEDA N 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ER0 +NEEDLES N IY1 D AH0 L Z +NEEDLESS N IY1 D L AH0 S +NEEDLESSLY N IY1 D L AH0 S L IY0 +NEEDLEWORK N IY1 D AH0 L W ER2 K +NEEDLING N IY1 D L IH0 NG +NEEDN'T N IY1 D AH0 N T +NEEDS N IY1 D Z +NEEDY N IY1 D IY0 +NEEF N IY1 F +NEEL N IY1 L +NEELD N IY1 L D +NEELEY N IY1 L IY0 +NEELS N IY1 L Z +NEELY N IY1 L IY0 +NEEMAN N IY1 M AH0 N +NEENAN N IY1 N AH0 N +NEEPER N IY1 P ER0 +NEER N IH1 R +NEES N IY1 Z +NEESE N IY1 Z +NEESON N IY1 S AH0 N +NEET N IY1 T +NEFARIOUS N AH0 F EH1 R IY0 AH0 S +NEFF N EH1 F +NEFT N EH1 F T +NEFTEGORSK N EH1 F T IH0 G AO2 R S K +NEG N EH1 G +NEGARA N EH0 G AA1 R AH0 +NEGATE N IH0 G EY1 T +NEGATED N IY1 G EY0 T IH0 D +NEGATED(1) N IH0 G EY1 T AH0 D +NEGATES N IH0 G EY1 T S +NEGATING N IH0 G EY1 T IH0 NG +NEGATION N AH0 G EY1 SH AH0 N +NEGATIVE N EH1 G AH0 T IH0 V +NEGATIVELY N EH1 G AH0 T IH0 V L IY0 +NEGATIVES N EH1 G AH0 T IH0 V Z +NEGATIVISM N EH1 G AH0 T IH0 V IH2 Z AH0 M +NEGATIVITY N EH2 G AH0 T IH1 V AH0 T IY0 +NEGATRON N EH1 G AH0 T R AA0 N +NEGATRONS N EH1 G AH0 T R AA0 N Z +NEGENT N EH1 G AH0 N T +NEGENT(1) N EH1 JH AH0 N T +NEGEV N EH1 G EH2 V +NEGLECT N AH0 G L EH1 K T +NEGLECT(1) N IH0 G L EH1 K T +NEGLECTED N AH0 G L EH1 K T AH0 D +NEGLECTED(1) N IH0 G L EH1 K T IH0 D +NEGLECTFUL N IH0 G L EH1 K T F AH0 L +NEGLECTING N IH0 G L EH1 K T IH0 NG +NEGLECTS N IH0 G L EH1 K T S +NEGLEY N EH1 G L IY0 +NEGLIA N EH1 G L IY0 AH0 +NEGLIGENCE N EH1 G L AH0 JH AH0 N S +NEGLIGENCE(1) N EH1 G L IH0 JH AH0 N S +NEGLIGENT N EH1 G L AH0 JH AH0 N T +NEGLIGENT(1) N EH1 G L IH0 JH AH0 N T +NEGLIGENTLY N EH1 G L IH0 JH AH0 N T L IY0 +NEGLIGIBLE N EH1 G L AH0 JH AH0 B AH0 L +NEGLIGIBLE(1) N EH1 G L IH0 JH AH0 B AH0 L +NEGOTIABLE N AH0 G OW1 SH AH0 B AH0 L +NEGOTIATE N AH0 G OW1 SH IY0 EY2 T +NEGOTIATE(1) N IH0 G OW1 SH IY0 EY2 T +NEGOTIATED N AH0 G OW1 SH IY0 EY2 T AH0 D +NEGOTIATED(1) N IH0 G OW1 SH IY0 EY2 T IH0 D +NEGOTIATES N IH0 G OW1 SH IY0 EY2 T S +NEGOTIATING N IH0 G OW1 SH IY0 EY2 T IH0 NG +NEGOTIATION N IH0 G OW2 SH IY0 EY1 SH AH0 N +NEGOTIATIONS N AH0 G OW2 SH IY0 EY1 SH AH0 N Z +NEGOTIATIONS(1) N IH0 G OW2 SH IY0 EY1 SH AH0 N Z +NEGOTIATOR N AH0 G OW1 SH IY0 EY2 T ER0 +NEGOTIATOR(1) N IH0 G OW1 SH IY0 EY2 T ER0 +NEGOTIATOR'S N IH0 G OW1 SH IY0 EY2 T ER0 Z +NEGOTIATORS N IH0 G OW1 SH IY0 EY2 T ER0 Z +NEGOTIATORS' N AH0 G OW1 SH IY0 EY2 T ER0 Z +NEGRETE N EH1 G R IY2 T +NEGRI N EH1 G R IY0 +NEGRIN N EH1 G R IH0 N +NEGRO N IY1 G R OW0 +NEGROES N IY1 G R OW0 Z +NEGROID N IY1 G R OY0 D +NEGRON N EH1 G R AH0 N +NEGRONI N EH2 G R OW1 N IY0 +NEGROPALPUS N EH2 G R AH0 P AA1 L P AH0 S +NEGROS N IY1 G R OW0 Z +NEGS N EH1 G Z +NEGU N EH1 G UW0 +NEGUS N IY1 G AH0 S +NEHEMIAH N IY2 AH0 M AY1 AH0 +NEHER N EY1 ER0 +NEHLS N EH1 L Z +NEHRING N EH1 R IH0 NG +NEHRU N EY1 R UW2 +NEIBAUER N AY1 B AW0 ER0 +NEIBERG N AY1 B ER0 G +NEIBERT N IY1 B ER0 T +NEICE N IY1 S +NEIDER N IY1 D ER0 +NEIDHARDT N AY1 D HH AA0 R T +NEIDHART N AY1 D HH AA0 R T +NEIDIGH N IY1 D AY2 +NEIDL N IY1 D AH0 L +NEIDLINGER N AY1 D AH0 L IH0 NG ER0 +NEIDLINGER(1) N IY1 D L IH0 NG ER0 +NEIER N AY1 ER0 +NEIFERT N IY1 F ER0 T +NEIGER N AY1 G ER0 +NEIGH N EY1 +NEIGHBOR N EY1 B ER0 +NEIGHBOR'S N EY1 B ER0 Z +NEIGHBORHOOD N EY1 B ER0 HH UH2 D +NEIGHBORHOOD'S N EY1 B ER0 HH UH2 D Z +NEIGHBORHOODS N EY1 B ER0 HH UH2 D Z +NEIGHBORING N EY1 B ER0 IH0 NG +NEIGHBORLY N EY1 B ER0 L IY0 +NEIGHBORS N EY1 B ER0 Z +NEIGHBORS' N EY1 B ER0 Z +NEIGHBOUR N EY1 B ER0 +NEIGHBOUR'S N EY1 B ER0 Z +NEIGHBOURHOOD N EY1 B ER0 HH UH2 D +NEIGHBOURHOOD'S N EY1 B ER0 HH UH2 D Z +NEIGHBOURHOODS N EY1 B ER0 HH UH2 D Z +NEIGHBOURING N EY1 B ER0 IH0 NG +NEIGHBOURLY N EY1 B ER0 L IY0 +NEIGHBOURS N EY1 B ER0 Z +NEIGHBOURS' N EY1 B ER0 Z +NEIGHMOND N EY1 M AH0 N D +NEIGHMOND'S N EY1 M AH0 N D Z +NEIKIRK N IY1 K ER0 K +NEIL N IY1 L +NEIL'S N IY1 L Z +NEILAN N IY1 L AH0 N +NEILD N IY1 L D +NEILE N IY1 L +NEILL N IY1 L +NEILS N IY1 L Z +NEILSEN N AY1 L S AH0 N +NEILSON N IY1 L S AH0 N +NEIMAN N IY1 M AH0 N +NEIMEYER N AY1 M AY0 ER0 +NEIN N IY1 N +NEIRA N EH1 R AH0 +NEIS N IY1 Z +NEISEN N AY1 S AH0 N +NEISES N IY1 Z IH0 Z +NEISLER N AY1 S AH0 L ER0 +NEISLER(1) N AY1 S L ER0 +NEISS N IY1 S +NEISWENDER N AY1 S W EH0 N D ER0 +NEITHER N IY1 DH ER0 +NEITHER(1) N AY1 DH ER0 +NEITZ N IY1 T S +NEITZEL N AY1 T Z AH0 L +NEITZKE N AY1 T S K IY0 +NEJ N EY1 +NEJAMATIN N EH0 JH AH0 M AE1 T IH0 N +NEKIA N AH0 K IY1 AH0 +NEKOOSA N IH0 K UW1 S AH0 +NEKTON N EH1 K T AH0 N +NEL N EH1 L +NELA N EH1 L AH0 +NELDA N EH1 L D AH0 +NELIA N EH1 L IY0 AH0 +NELINA N EH0 L IY1 N AH0 +NELITA N EH0 L IY1 T AH0 +NELL N EH1 L +NELLA N EH1 L AH0 +NELLCOR N EH1 L K AO2 R +NELLE N EH1 L +NELLER N EH1 L ER0 +NELLES N EH1 L Z +NELLETTE N EH2 L EH1 T +NELLI N EH1 L IY0 +NELLIANA N EH2 L IY0 AE1 N AH0 +NELLIE N EH1 L IY0 +NELLIGAN N EH1 L IH0 G AH0 N +NELLIS N EH1 L IH0 S +NELLWYN N EH1 L W IH0 N +NELLY N EH1 L IY0 +NELMS N EH1 L M Z +NELOMS N EH1 L AH0 M Z +NELON N EH1 L AH0 N +NELS N EH1 L Z +NELSEN N EH1 L S AH0 N +NELSON N EH1 L S AH0 N +NELSON'S N EH1 L S AH0 N Z +NEMATODE N EH1 M AH0 T OW2 D +NEMATODES N EH1 M AH0 T OW2 D Z +NEMEAN N IY1 M IY0 AH0 N +NEMEC N EH1 M IH0 K +NEMECEK N EH1 M IH0 S IH0 K +NEMER N IY1 M ER0 +NEMEROFF N EH1 M ER0 AO0 F +NEMES N IY1 M Z +NEMESIS N EH1 M AH0 S IH0 S +NEMETH N EY1 M IH0 TH +NEMETZ N EH1 M IH0 T S +NEMIR N AH1 M ER0 +NEMITZ N EH1 M IH0 T S +NEMMERS N EH1 M ER0 Z +NEMO N EH1 M OW0 +NEMOS N IY1 M OW0 Z +NEMOURS N IH0 M AO1 R Z +NENDICK N EH1 N D IH0 K +NENE N IY1 N +NENET N EH1 N IH0 T +NENI N EH1 N IY0 +NENI'S N EH1 N IY0 S +NENNINGER N EH1 N IH0 NG ER0 +NEO N IY1 OW0 +NEOAX N IY2 OW0 AE1 K S +NEOCLASSIC N IY2 OW0 K L AE1 S IH0 K +NEOCLASSICAL N IY2 OW0 K L AE1 S IH0 K AH0 L +NEOCONSERVATIVE N IY2 OW0 K AH0 N S ER1 V AH0 T IH0 V +NEOCONSERVATIVES N IY2 OW0 K AH0 N S ER1 V AH0 T IH0 V Z +NEOLA N IY0 AA1 L AH0 +NEOLIBERAL N IY2 OW0 L IH1 B ER0 AH0 L +NEOLIBERALS N IY2 OW0 L IH1 B ER0 AH0 L Z +NEOLITH N IY1 OW0 L IH2 TH +NEOLITHIC N IY1 OW0 L IH2 TH IH0 K +NEOMA N EY0 OW1 M AH0 +NEON N IY1 AA0 N +NEONATAL N IY2 OW0 N EY1 T AH0 L +NEONAZI N IY2 OW0 N AA1 T S IY0 +NEONAZIS N IY2 OW0 N AA1 T S IY0 Z +NEONS N IY1 AA2 N Z +NEOPHYTE N IY1 AH0 F AY2 T +NEOPHYTES N IY1 AH0 F AY2 T S +NEOPLASM N IY1 AH0 P L AE2 Z AH0 M +NEOPLATONIC N IY2 OW0 P L AH0 T AA1 N IH0 K +NEOPLATONIST N IY2 OW0 P L EY1 T AH0 N AH0 S T +NEOPOLIS N IY0 AO1 P AH0 L IH0 S +NEOPOSITIVISM N IY0 OW0 P AO1 Z AH0 T AH0 V IH2 Z AH0 M +NEOPOSITIVIST N IY0 OW0 P AO1 Z AH0 T AH0 V IH2 S T +NEOPRENE N IY1 AH0 P R IY2 N +NEOPRENE(1) N IY1 OW0 P R IY2 N +NEOPROBE N IY1 OW0 P R OW2 B +NEORX N IY1 OW0 R EH2 K S +NEOTENIC N IY2 AH0 T IY1 N IH0 K +NEOTENY N IY0 AA1 T AH0 N IY0 +NEPA N IY1 P AH0 +NEPAL N AH0 P AO1 L +NEPALESE N EH2 P AH0 L IY1 Z +NEPALI N AH0 P AO1 L IY0 +NEPENTHE N EH2 P EH1 N TH IY0 +NEPHEW N EH1 F Y UW0 +NEPHEW'S N EH1 F Y UW0 Z +NEPHEWS N EH1 F Y UW0 Z +NEPHRIDIUM N AH0 F R IH1 D IY0 AH0 M +NEPHRITE N EH1 F R AY0 T +NEPHRON N EH1 F R AA0 N +NEPHROSIS N AH0 F R OW1 S AH0 S +NEPL N EH1 P AH0 L +NEPL(1) EH1 N IY1 P IY1 EH1 L +NEPONSET N AH0 P AA1 N S IH0 T +NEPOOL N AH0 P UW1 L +NEPOTISM N EH1 P AH0 T IH2 Z AH0 M +NEPTUNE N EH1 P T UW0 N +NEPTUNIUM N EH0 P T UW1 N IY0 AH0 M +NERCO N ER1 K OW0 +NERD N ER1 D +NERDS N ER1 D Z +NERDY N ER1 D IY0 +NERENBERG N IH1 R AH0 N B ER0 G +NERI N EH1 R IY0 +NERICE N EH1 R IH0 S +NERINE N EH1 R IY0 N +NERIO N EH1 R IY0 OW0 +NERITIC N ER0 IH1 T IH0 K +NERL N ER1 L +NERLICH N ER1 L IH0 K +NERNEY N ER1 N IY0 +NERO N IH1 R OW0 +NERO'S N IH1 R OW0 Z +NERONE N EH1 R AH0 N +NERREN N EH1 R AH0 N +NERUDA N AH0 R UW1 D AH0 +NERVANA N ER0 V AE1 N AH0 +NERVE N ER1 V +NERVE-RACKING N ER2 V R AE1 K IH0 NG +NERVES N ER1 V Z +NERVION N ER1 V IY0 AH0 N +NERVOSA N ER0 V OW1 S AH0 +NERVOUS N ER1 V AH0 S +NERVOUSLY N ER1 V AH0 S L IY0 +NERVOUSNESS N ER1 V AH0 S N AH0 S +NERVY N ER1 V IY0 +NES N EH1 S +NESBIT N EH1 S B IH0 T +NESBITT N EH1 Z B IH0 T +NESBY N EH1 S B IY0 +NESCI N EH1 S IY0 +NESHEIM N EH1 S HH AY2 M +NESI N EH1 S IY0 +NESLER N EH1 S AH0 L ER0 +NESLER(1) N EH1 S L ER0 +NESLER'S N EH1 S AH0 L ER0 Z +NESLER'S(1) N EH1 S L ER0 Z +NESMITH N EH1 Z M IH0 TH +NESS N EH1 S +NESSA N EH1 S AH0 +NESSEL N EH1 S AH0 L +NESSEN N IY1 S AH0 N +NESSER N EH1 S ER0 +NESSETH N EH1 S IH0 TH +NESSI N EH1 S IY0 +NESSIE N EH1 S IY0 +NESSLER N EH1 S L ER0 +NEST N EH1 S T +NEST-EGG N EH1 S T EY1 G +NESTA N EH1 S T AH0 +NESTE N EH1 S T +NESTEA N EH1 S T IY0 AH0 +NESTED N EH1 S T AH0 D +NESTED(1) N EH1 S T IH0 D +NESTER N EH1 S T ER0 +NESTERS N EH1 S T ER0 Z +NESTING N EH1 S T IH0 NG +NESTLE N EH1 S AH0 L +NESTLE(1) N EH1 S L IY1 +NESTLE'S N EH1 S AH0 L Z +NESTLE'S(1) N EH1 S L IY1 Z +NESTLED N EH1 S AH0 L D +NESTLER N EH1 S AH0 L ER0 +NESTLER(1) N EH1 S L ER0 +NESTLES N EH1 S AH0 L Z +NESTLING N EH1 S T L IH0 NG +NESTLING(1) N EH1 S L IH0 NG +NESTLINGS N EH1 S T L IH0 NG Z +NESTLINGS(1) N EH1 S L IH0 NG Z +NESTOR N EH1 S T ER0 +NESTORIAN N EH0 S T AO1 R IY0 AH0 N +NESTORIANISM N EH0 S T AO1 R IY0 AH0 N IH2 Z AH0 M +NESTS N EH1 S T S +NET N EH1 T +NETAN N EH1 T AH0 N +NETANYAHU N EH2 T AH0 N Y AA1 HH UW2 +NETANYAHU'S N EH2 T AH0 N Y AA1 HH UW2 Z +NETBACK N EH1 T B AE2 K +NETCOM N EH1 T K AA2 M +NETH N EH1 TH +NETHER N EH1 DH ER0 +NETHERCUTT N EH1 TH ER0 K AH0 T +NETHERLAND N EH1 DH ER0 L AH0 N D +NETHERLANDIC N EH1 DH ER0 L AE2 N D IH0 K +NETHERLANDS N EH1 DH ER0 L AH0 N D Z +NETHERLANDS' N EH1 TH ER0 L AE0 N D Z +NETHERS N EH1 DH ER0 Z +NETHERTON N EH1 DH ER0 T AH0 N +NETHERWORLD N EH1 DH ER0 W ER2 L D +NETHERY N EH1 DH ER0 IY0 +NETHUVA N EH2 TH UW1 V AH0 +NETHUVA'S N EH2 TH UW1 V AH0 Z +NETIQUETTE N EH1 T AH0 K AH2 T +NETLIKE N EH1 T L AY2 K +NETO N EH1 T OW0 +NETS N EH1 T S +NETSCAPE N EH1 T S K EY2 P +NETSCAPE'S N EH1 T S K EY2 P S +NETT N EH1 T +NETTA N EH1 T AH0 +NETTED N EH1 T IH0 D +NETTER N EH1 T ER0 +NETTERVILLE N EH1 T ER0 V IH0 L +NETTESHEIM N EH1 T IH0 S SH AY0 M +NETTIE N EH1 T IY0 +NETTING N EH1 T IH0 NG +NETTLE N EH1 T AH0 L +NETTLED N EH1 T AH0 L D +NETTLES N EH1 T AH0 L Z +NETTLESOME N EH1 T AH0 L S AH0 M +NETTLETON N EH1 T AH0 L T AH0 N +NETTLETON'S N EH1 T AH0 L T AH0 N Z +NETTO N EH1 T OW0 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+NIKKHAH N IH1 K HH AA0 +NIKKI N IH1 K IY0 +NIKKO N IY1 K OW0 +NIKKO'S N IY1 K OW0 Z +NIKO N IY1 K OW0 +NIKO'S N IY1 K OW0 Z +NIKOLA N IH0 K OW1 L AH0 +NIKOLAI N IH1 K OW0 L AY2 +NIKOLAIVICH N IH0 K OW0 L AY1 V IH0 CH +NIKOLAUS N IH1 K AH0 L AW0 Z +NIKOLIC N IH0 K AA1 L IH0 K +NIKOLICH N IH0 K AA1 L IH0 HH +NIKON N AY1 K AA2 N +NIKOU N IY1 K UW0 +NIKOVSKI N IH0 K AA1 F S K IY0 +NIL N IH1 L +NILA N IY1 L AH0 +NILAN N IY0 L AA1 N +NILAND N AY1 L AH0 N D +NILE N AY1 L +NILES N AY1 L Z +NILGES N IH1 L JH IH0 Z +NILL N IH1 L +NILLES N AY1 L Z +NILLY N IH1 L IY0 +NILS N IH1 L Z +NILSEN N IH1 L S AH0 N +NILSON N IH1 L S AH0 N +NILSSON N IH1 L S AH0 N +NIMBLE N IH1 M B AH0 L +NIMBLY N IH1 M B L IY0 +NIMBUS N IH1 M B AH0 S +NIMBY N IH1 M B IY0 +NIMITZ N IH1 M IH0 T S +NIMMER N IH1 M ER0 +NIMMO N IH1 M OW0 +NIMMONS N IH1 M AH0 N Z +NIMOY N IY1 M OY2 +NIMROD N IH1 M R AA0 D +NIMRODI N IH0 M R OW1 D IY0 +NIMS N IH1 M Z +NIMTZ N IH1 M T S +NINA N IY1 N AH0 +NINAD N AY1 N AH0 D +NINAGAWA N IY2 N AA0 G AA1 W AH0 +NINCOMPOOP N IH1 NG K AH0 M P UW2 P +NINCOMPOOPS N IH1 NG K AH0 M P UW2 P S +NINE N AY1 N +NINE'S N AY1 N Z +NINEFOLD N IH1 N F OW2 L D +NINER N AY1 N ER0 +NINERS N AY1 N ER0 Z +NINERS' N AY1 N ER0 Z +NINES N AY1 N Z +NINETEEN N AY1 N T IY1 N +NINETEENTH N AY1 N T IY1 N TH +NINETIES N AY1 N T IY0 Z +NINETIES' N AY1 N T IY0 Z +NINETIETH N AY1 N T IY0 IH0 TH +NINETTE N IH0 N EH1 T +NINETY N AY1 N T IY0 +NINETY'S N AY1 N T IY0 Z +NINEVEH N IH1 N AH0 V AH0 +NING N IH1 NG +NINJA N IH1 N JH AH0 +NINJAS N IH1 N JH AH0 Z +NINNEMAN N IH1 N M AH0 N +NINNY N IH1 N IY0 +NINO N IY1 N OW0 +NINO(1) N IY1 N Y OW0 +NINON N IH1 N AH0 N +NINOS N IY1 N OW0 Z +NINOS(1) N IY1 N Y OW0 Z +NINSU N IH1 N S UW0 +NINTENDO N IH0 N T EH1 N D OW0 +NINTENDO'S N IH0 N T EH1 N D OW0 Z +NINTH N AY1 N TH +NINTHS N AY1 N TH S +NIOBITE N AY1 OW0 B AY2 T +NIOBIUM N AY2 OW1 B IY0 AH0 M +NIP N IH1 P +NIPON N IH1 P AA2 N +NIPP N IH1 P +NIPPED N IH1 P T +NIPPER N IH1 P ER0 +NIPPERT N IH1 P ER0 T +NIPPING N IH1 P IH0 NG +NIPPLE N IH1 P AH0 L +NIPPLES N IH1 P AH0 L Z +NIPPON N IH2 P AA1 N +NIPPONDENSO N IH2 P AA2 N D EH1 N S OW0 +NIPPY N IH1 P IY0 +NIPS N IH1 P S +NIPSCO N IH1 P S K OW0 +NIQUETTE N IH0 K EH1 T +NIR N IH1 R +NIRENBERG N AY1 R AH0 N B ER0 G +NIRIKO N IH1 R IH0 K OW0 +NIRO N IH1 R OW0 +NIRVANA N IH0 R V AA1 N AH0 +NIRVANA(1) N ER0 V AA1 N AH0 +NIRVANA'S N IH0 R V AA1 N AH0 Z +NIRVANA'S(1) N ER0 V AA1 N AH0 Z +NIRVANAS N IH0 R V AA1 N AH0 Z +NIRVANAS(1) N ER0 V AA1 N AH0 Z +NISBET N IH1 Z B AH0 T +NISBETT N IH1 S B IH0 T +NISEI N IH0 S EY1 +NISHI N IY1 SH IY0 +NISHIDA N IY0 SH IY1 D AH0 +NISHIKAWA N IY0 SH IY0 K AA1 W AH0 +NISHIMO N IH0 SH IY1 M OW0 +NISHIMOTO N IY0 SH IY0 M OW1 T OW0 +NISHIMURA N IY0 SH IY0 M UH1 R AH0 +NISHIOKA N IY2 SH IY0 OW1 K AH0 +NISHIYAMA N IY0 SH IY0 Y AA1 M AH0 +NISHIZAWA N IY2 SH IH0 Z AA1 W AH0 +NISKANEN N IH1 S K AH0 N AH0 N +NISLEY N IH1 Z L IY0 +NISSA N IH1 S AH0 +NISSAN N IY1 S AA0 N +NISSAN'S N IY1 S AA0 N Z +NISSANS N IY1 S AA0 N Z +NISSEI N IH0 S 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R +NIZHNY N IH1 ZH N IY0 +NIZIOLEK N IH0 Z IY0 OW1 L EH0 K +NIZNIK N IH1 Z N IH0 K +NKOHSE EH0 NG K OW1 S IY0 +NMR EH2 N EH2 M AA1 R +NO N OW1 +NO'S N OW1 Z +NO-BRAINER N OW2 B R EY1 N ER0 +NO-GO N OW1 G OW2 +NO-GOOD N OW1 G UH2 D +NO-ONE N OW1 W AH0 N +NO-ONE'S N OW1 W AH0 N Z +NO-SHOW N OW1 SH OW2 +NOA N OW1 AH0 +NOAA N OW1 AH0 +NOAA(1) EH1 N OW1 EY1 EY1 +NOACK N OW1 K +NOAH N OW1 AH0 +NOAH'S N OW1 AH0 Z +NOAKES N OW1 K S +NOAM N OW1 M +NOAMI N OW1 M IY0 +NOBATOSHI N OW2 B AH0 T OW1 SH IY0 +NOBBE N AA1 B +NOBEC N OW0 B EH1 K +NOBEC'S N OW0 B EH1 K S +NOBEL N OW0 B EH1 L +NOBELIUM N OW0 B EH1 L IY0 AH0 M +NOBILE N AA1 B AH0 L +NOBILITY N OW0 B IH1 L AH0 T IY0 +NOBIS N OW1 B IH0 S +NOBLE N OW1 B AH0 L +NOBLE'S N OW1 B AH0 L Z +NOBLEMAN N OW1 B AH0 L M AH0 N +NOBLEMAN'S N OW1 B AH0 L M AH0 N Z +NOBLER N OW1 B L ER0 +NOBLES N OW1 B AH0 L Z +NOBLESSE N OW0 B L EH1 S +NOBLEST N OW1 B L IH0 S T +NOBLET N AA1 B L AH0 T +NOBLETT N AA1 B L IH0 T +NOBLEWOMAN N OW1 B AH0 L W UH2 M AH0 N +NOBLIN 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P IY1 EH1 M +P.S P IY1 Z +PA P AA1 +PAAP P AA1 P +PAAPE P AA1 P +PAAR P AA1 R +PAASCH P AA1 SH +PAAVOLA P AA2 V OW1 L AH0 +PABLO P AA1 B L OW0 +PABLUM P AE1 B L AH0 M +PABON P AA0 B AO1 N +PABST P AE1 B S T +PAC P AE1 K +PAC'S P AE1 K S +PACA P AA1 K AH0 +PACA(1) P AE1 K AH0 +PACCAR P AH0 K AA1 R +PACCIONE P AA0 K CH OW1 N IY0 +PACE P EY1 S +PACE'S P EY1 S IH0 Z +PACED P EY1 S T +PACELLA P AH0 S EH1 L AH0 +PACELLI P AH0 S EH1 L IY0 +PACEMAKER P EY1 S M EY2 K ER0 +PACEMAKERS P EY1 S M EY2 K ER0 Z +PACER P EY1 S ER0 +PACERS P EY1 S ER0 Z +PACES P EY1 S IH0 Z +PACESETTER P EY1 S EH2 T ER0 +PACEWAY P EY1 S W EY2 +PACEY P EY1 S IY0 +PACHECO P AH0 CH EH1 K OW0 +PACHINKO P AH0 CH IH1 NG K OW0 +PACHOLDER P AE1 CH AH0 L D ER0 +PACHOLSKI P AH0 HH OW1 L S K IY0 +PACHTER P AE1 K T ER0 +PACHYSANDRA P AE2 CH IH0 S AE1 N D R AH0 +PACI P AA1 CH IY0 +PACIFIC P AH0 S IH1 F IH0 K +PACIFIC'S P AH0 S IH1 F IH0 K S +PACIFICA P AH0 S IH1 F IH0 K AH0 +PACIFICARE P AH0 S IH1 F IH0 K EH2 R +PACIFICATION P AE2 S AH0 F AH0 K EY1 SH AH0 N +PACIFICO P AA0 CH IY0 F IY1 K OW0 +PACIFICORP P AH0 S IH1 F IH0 K AO0 R P +PACIFIED P AE1 S AH0 F AY2 D +PACIFIER P AE1 S AH0 F AY2 ER0 +PACIFIERS P AE1 S AH0 F AY2 ER0 Z +PACIFISM P AE1 S IH0 F IH2 Z AH0 M +PACIFIST P AE1 S IH0 F IH0 S T +PACIFISTS P AE1 S IH0 F IH0 S T S +PACIFY P AE1 S AH0 F AY2 +PACING P EY1 S IH0 NG +PACINI P AA0 CH IY1 N IY0 +PACINO P AH0 S IY1 N OW0 +PACK P AE1 K +PACKAGE P AE1 K AH0 JH +PACKAGE(1) P AE1 K IH0 JH +PACKAGE'S P AE1 K IH0 JH IH0 Z +PACKAGED P AE1 K IH0 JH D +PACKAGER P AE1 K IH0 JH ER0 +PACKAGERS P AE1 K IH0 JH ER0 Z +PACKAGES P AE1 K AH0 JH AH0 Z +PACKAGES(1) P AE1 K IH0 JH IH0 Z +PACKAGING P AE1 K IH0 JH IH0 NG +PACKARD P AE1 K ER0 D +PACKARD'S P AE1 K ER0 D Z +PACKED P AE1 K T +PACKER P AE1 K ER0 +PACKERS P AE1 K ER0 Z +PACKET P AE1 K AH0 T +PACKET(1) P AE1 K IH0 T +PACKETS P AE1 K IH0 T S +PACKETT P AE1 K IH0 T +PACKHAM P AE1 K HH AH0 M +PACKING P AE1 K IH0 NG +PACKINGHOUSE P AE1 K IH0 NG HH AW2 S +PACKMAN P AE1 K M AH0 N +PACKS P AE1 K S +PACKWOOD P AE1 K W UH2 D +PACKWOOD'S P AE1 K W UH2 D Z +PACMAN P AE1 K M AH0 N +PACO P EY1 K OW0 +PACS P AE1 K S +PACT P AE1 K T +PACT'S P AE1 K T S +PACTEL P AE1 K T EH2 L +PACTEL'S P AE1 K T EH2 L Z +PACTO P AE1 K T OW0 +PACTS P AE1 K T S +PACTS(1) P AE1 K S +PACYNA P AA1 K IY0 N AH0 +PACYNA(1) P AH0 S IY1 N AH0 +PACZKOWSKI P AH0 CH K AO1 F S K IY0 +PAD P AE1 D +PADAWAN P AA1 D AA2 W AH0 N +PADDACK P AE1 D AH0 K +PADDED P AE1 D IH0 D +PADDEN P AE1 D AH0 N +PADDIES P AE1 D IY0 Z +PADDING P AE1 D IH0 NG +PADDINGTON P AE1 D IH0 NG T AH0 N +PADDLE P AE1 D AH0 L +PADDLED P AE1 D AH0 L D +PADDLES P AE1 D AH0 L Z +PADDLING P AE1 D AH0 L IH0 NG +PADDLING(1) P AE1 D L IH0 NG +PADDOCK P AE1 D AH0 K +PADDY P AE1 D IY0 +PADDY'S P AE1 D IY0 Z +PADEN P EY1 D AH0 N +PADEREWSKI P AA2 D ER0 UW1 S K IY0 +PADFIELD P AE1 D F IY2 L D +PADGET P AE1 JH IH0 T +PADGETT P AE1 JH IH0 T +PADGITT P AE1 JH IH0 T +PADILLA P AH0 D IH1 L AH0 +PADLEY P AE1 D L IY0 +PADLOCK P AE1 D L AA2 K 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P AE1 L M AO0 R +PALMQUIST P AE1 L M K W IH0 S T +PALMS P AA1 M Z +PALMS(1) P AA1 L M Z +PALMSTIERNA P AO2 L M S T IY0 EH1 R N AH0 +PALO P AE1 L OW0 +PALO-ALTO P AE1 L OW0 AE1 L T OW0 +PALOMA P AA0 L OW1 M AH0 +PALOMAR P AE1 L AH0 M AA0 R +PALOMARES P AA0 L OW0 M AA1 R EH0 S +PALOMBA P AA0 L OW1 M B AH0 +PALOMBI P AH0 L AA1 M B IY0 +PALOMBO P AH0 L AA1 M B OW0 +PALOMETA P AA0 L OW0 M EH1 T AH0 +PALOMINO P AE2 L AH0 M IY1 N OW0 +PALOMITA P AA0 L OW0 M IY1 T AH0 +PALOMO P AA0 L OW1 M OW0 +PALONE P AH0 L OW1 N +PALONIUS P AH0 L OW1 N IY0 AH0 S +PALOS P AA1 L OW0 Z +PALPABLE P AE1 L P AH0 B AH0 L +PALPABLY P AE1 L P AH0 B L IY0 +PALPITATE P AE1 L P AH0 T EY0 T +PALPITATED P AE1 L P AH0 T EY0 T IH0 D +PALPITATES P AE1 L P AH0 T EY0 T S +PALPITATING P AE1 L P AH0 T EY0 T IH0 NG +PALPITATION P AE2 L P AH0 T EY1 SH AH0 N +PALPITATIONS P AE2 L P IH0 T EY1 SH AH0 N Z +PALS P AE1 L Z +PALSY P AO1 L Z IY0 +PALTON P AO1 L T AH0 N +PALTRY P AO1 L T R IY0 +PALTZ P AO1 L T S +PALUCH P AE1 L AH0 K 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AE0 N D AO1 R AH0 +PANDORA'S P AE0 N D AO1 R AH0 Z +PANDY P AE1 N D IY0 +PANDYA P AA1 N D Y AH0 +PANE P EY1 N +PANEBIANCO P AA0 N EH0 B IY0 AA1 N K OW0 +PANEK P AE1 N IH0 K +PANEL P AE1 N AH0 L +PANEL'S P AE1 N AH0 L Z +PANELED P AE1 N AH0 L D +PANELING P AE1 N AH0 L IH0 NG +PANELIST P AE1 N AH0 L AH0 S T +PANELISTS P AE1 N AH0 L IH0 S T S +PANELIZATION P AE1 N AH0 L AH0 Z EY1 SH AH0 N +PANELIZE P AE1 N AH0 L AY2 Z +PANELIZED P AE1 N AH0 L AY2 Z D +PANELLA P AH0 N EH1 L AH0 +PANELS P AE1 N AH0 L Z +PANELS' P AE1 N AH0 L Z +PANEM P EY1 N AH0 M +PANEPINTO P AA0 N EH0 P IY1 N T OW0 +PANES P EY1 N Z +PANETTA P AH0 N EH1 T AH0 +PANETTA'S P AH0 N EH1 T AH0 Z +PANFIDA P AE2 N F IY1 D AH0 +PANFIL P AE1 N F IH0 L +PANFILE P AE1 N F AY1 L +PANFUL P AE1 N F AH0 L +PANFULS P AE1 N F AH0 L Z +PANG P AE1 NG +PANGALLO P AA0 NG G AA1 L OW0 +PANGBORN P AE1 NG B AO2 R N +PANGBURN P AE1 NG B ER2 N +PANGELS P AE2 NG G EH1 L Z +PANGLE P AE1 NG G AH0 L +PANGLOSS P AE1 N G L AA2 S +PANGLOSS(1) P AE1 NG G L AA2 S +PANGS P AE1 NG Z +PANHANDLE P AE1 N HH AE2 N D AH0 L +PANHANDLE'S P AE1 N HH AE2 N D AH0 L Z +PANHANDLER P AE1 N HH AE2 N D L ER0 +PANHANDLERS P AE1 N HH AE2 N D L ER0 Z +PANHANDLING P AE1 N HH AE2 N D L IH0 NG +PANIAGUA P AA0 N IY0 AA1 G AH0 +PANIC P AE1 N IH0 K +PANIC'S P AE1 N IH0 K S +PANICCIA P AA0 N IY1 CH AH0 +PANICKED P AE1 N IH0 K T +PANICKING P AE1 N IH0 K IH0 NG +PANICKY P AE1 N IH0 K IY0 +PANICO P AA0 N IY1 K OW0 +PANICS P AE1 N IH0 K S +PANIK P AE1 N IH0 K +PANINI P AH0 N IY1 N IY2 +PANKAU P AE1 NG K AW0 +PANKEY P AE1 N K IY2 +PANKKI P AE1 NG K IY0 +PANKO P AE1 NG K OW0 +PANKONIN P AE1 NG K AH0 N IH0 N +PANKOW P AE1 NG K OW0 +PANKRATZ P AE1 NG K R AH0 T S +PANKY P AE1 NG K IY0 +PANMUNJOM P AE2 N M UW0 N JH AO1 M +PANMURE P AE1 N M UH2 R +PANNED P AE1 N D +PANNELL P AE1 N AH0 L +PANNIER P AE1 N IY0 ER0 +PANNILL P AE1 N IH0 L +PANNILL'S P AE1 N IH0 L Z +PANNING P AE1 N IH0 NG +PANNONE P AA0 N OW1 N IY0 +PANNU P AA1 N UW0 +PANNULLO P AA0 N UW1 L OW0 +PANNY P AE1 N IY0 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M AY2 M +PANTON P AE1 N T AH0 N +PANTRY P AE1 N T R IY0 +PANTS P AE1 N T S +PANTSUIT P AE1 N T S UW2 T +PANTSUITS P AE1 N T S UW2 T S +PANTUSO P AA0 N T UW1 S OW0 +PANTY P AE1 N T IY0 +PANTYHOSE P AE1 N T IY0 HH OW2 Z +PANZA P AE1 N Z AH0 +PANZARELLA P AA0 N Z AA0 R EH1 L AH0 +PANZER P AE1 N Z ER0 +PANZHIHUA P AE2 N Z IH0 HH Y UW1 AH0 +PANZICA P AE1 N Z IH0 K AH0 +PAO P AW1 +PAO'S P AW1 Z +PAOLELLA P AA0 OW0 L EH1 L AH0 +PAOLETTI P AA0 OW0 L EH1 T IY0 +PAOLI P EY2 OW1 L IY0 +PAOLI(1) P AW1 L IY0 +PAOLILLO P AA0 OW0 L IH1 L OW0 +PAOLINI P AA0 OW0 L IY1 N IY0 +PAOLINO P AA0 OW0 L IY1 N OW0 +PAOLO P AW1 L OW0 +PAOLUCCI P AA0 OW0 L UW1 CH IY0 +PAONE P EY1 OW2 N +PAONESSA P AA0 OW0 N EH1 S AH0 +PAP P AE1 P +PAPA P AA1 P AH2 +PAPA'S P AA1 P AA2 Z +PAPACY P EY1 P AH0 S IY0 +PAPADAKIS P AA0 P AA0 D AA1 K IH0 S +PAPADOPOULOS P AA2 P AH0 D AA1 P AH0 L AH0 S +PAPAGEORGE P AA2 P AH0 JH AO1 R JH +PAPAGO P AA1 P AH0 G OW2 +PAPAL P EY1 P AH0 L +PAPALE P AA0 P AA1 L IY0 +PAPALEO P AA0 P EY0 L IY1 AH0 +PAPALIA P AA0 P AA1 L IY0 AH0 +PAPANDREA P AA0 P AA1 N D R IY0 AH0 +PAPANDREOU P AH0 P AE1 N D R IY0 UW2 +PAPANIA P AA0 P AA1 N IY0 AH0 +PAPARAZZI P AA2 P AA0 R AO1 Z IY2 +PAPARAZZI'S P AA2 P AA0 R AO1 Z IY2 Z +PAPARAZZIS P AA2 P AA0 R AO1 Z IY2 Z +PAPARELLA P AA0 P AA0 R EH1 L AH0 +PAPAS P AA1 P AH0 Z +PAPAS(1) P AA1 P AA2 Z +PAPAW P AO1 P AO0 +PAPAY P AE1 P EY0 +PAPAYA P AH0 P AY1 AH0 +PAPAYAS P AH0 P AY1 AH0 Z +PAPAZIAN P AH0 P EY1 Z IY0 AH0 N +PAPE P EY1 P +PAPENFUSS P AE1 P AH0 N F AH2 S +PAPER P EY1 P ER0 +PAPER'S P EY1 P ER0 Z +PAPERAZZI P AE1 P AH0 R AA2 T S IY2 +PAPERBACK P EY1 P ER0 B AE2 K +PAPERBACKS P EY1 P ER0 B AE2 K S +PAPERBOARD P EY1 P ER0 B AO2 R D +PAPERBOY P EY1 P ER0 B OY2 +PAPERBOY'S P EY1 P ER0 B OY2 Z +PAPERBOYS P EY1 P ER0 B OY2 Z +PAPERED P EY1 P ER0 D +PAPERING P EY1 P ER0 IH0 NG +PAPERLESS P EY1 P ER0 L AH0 S +PAPERMAKING P AE1 P ER0 M EY2 K IH0 NG +PAPERMATE P EY1 P ER0 M EY2 T +PAPERNICK P EY1 P ER0 N IH2 K +PAPERS P EY1 P ER0 Z +PAPERS' P EY1 P ER0 Z 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AE2 F +PARAGRAPH(1) P EH1 R AH0 G R AE2 F +PARAGRAPHS P AE1 R AH0 G R AE2 F S +PARAGRAPHS(1) P EH1 R AH0 G R AE2 F S +PARAGUAY P EH1 R AH0 G W EY2 +PARAGUAYAN P EH2 R AH0 G W AY1 AH0 N +PARAKEET P EH1 R AH0 K IY2 T +PARAKEETS P EH1 R AH0 K IY2 T S +PARALEGAL P EH2 R AH0 L IY1 G AH0 L +PARALEGALS P EH2 R AH0 L IY1 G AH0 L Z +PARALLAX P EH1 R AH0 L AE2 K S +PARALLEL P EH1 R AH0 L EH2 L +PARALLELED P EH1 R AH0 L EH2 L D +PARALLELING P EH1 R AH0 L EH2 L IH0 NG +PARALLELISM P EH1 R AH0 L EH2 L IH2 Z AH0 M +PARALLELS P EH1 R AH0 L EH2 L Z +PARALYMPIC P EH2 R AH0 L IH1 M P IH0 K +PARALYSIS P ER0 AE1 L AH0 S AH0 S +PARALYSIS(1) P ER0 AE1 L IH0 S IH0 S +PARALYTIC P EH2 R AH0 L IH1 T IH0 K +PARALYZE P EH1 R AH0 L AY2 Z +PARALYZED P EH1 R AH0 L AY2 Z D +PARALYZES P EH1 R AH0 L AY2 Z IH0 Z +PARALYZING P EH1 R AH0 L AY2 Z IH0 NG +PARAMAGNETIC P AE2 R AH0 M AE2 G N EH1 T IH0 K +PARAMAX P EH1 R AH0 M AE0 K S +PARAMECIUM P EH2 R AH0 M IY1 S IY0 AH0 M +PARAMEDIC P EH2 R AH0 M EH1 D IH0 K +PARAMEDICS P EH2 R AH0 M EH1 D IH0 K S +PARAMETER P ER0 AE1 M AH0 T ER0 +PARAMETERS P ER0 AE1 M AH0 T ER0 Z +PARAMETRIC P EH2 R AH0 M EH1 T R IH0 K +PARAMILITARIES P EH2 R AH0 M IH1 L AH0 T EH2 R IY0 Z +PARAMILITARY P EH2 R AH0 M IH1 L AH0 T EH2 R IY0 +PARAMO P ER0 AE1 M OW0 +PARAMONOVA P EH2 R AH0 M AH0 N OW1 V AH0 +PARAMORE P EH1 AH0 M AO1 R +PARAMOUNT P EH1 R AH0 M AW2 N T +PARAMOUNT'S P EH1 R AH0 M AW2 N T S +PARAMUS P ER0 AE1 M AH0 S +PARANA P ER0 AA1 N AH0 +PARANOIA P EH2 R AH0 N OY1 AH0 +PARANOIAC P EH2 R AH0 N OY1 AE2 K +PARANOID P EH1 R AH0 N OY2 D +PARANORMAL P EH0 R AH0 N AO1 R M AH0 L +PARAPET P EH1 R AH0 P EH2 T +PARAPHERNALIA P EH2 R AH0 F AH0 N EY1 L Y AH0 +PARAPHRASE P EH1 R AH0 F R EY2 Z +PARAPHRASING P EH1 R AH0 F R EY2 Z IH0 NG +PARAPLEGIA P EH2 R AH0 P L IY1 JH IY0 AH0 +PARAPLEGIC P EH2 R AH0 P L EH1 G IH0 K +PARAPLEGIC(1) P EH2 R AH0 P L IY1 JH IH0 K +PARASITE P EH1 R AH0 S AY2 T +PARASITES P EH1 R AH0 S AY2 T S +PARASITIC P EH2 R AH0 S IH1 T IH0 K +PARASYMPATHETIC P EH2 R AH0 S IH2 M P AH0 TH EH1 T IH0 K +PARATORE P ER0 AH0 T AO1 R IY0 +PARATROOP P EH1 R AH0 T R UW2 P +PARATROOPER P EH1 R AH0 T R UW2 P ER0 +PARATROOPERS P EH1 R AH0 T R UW2 P ER0 Z +PARATROOPS P EH1 R AH0 T R UW2 P S +PARAZOA P EH2 R AH0 Z OW1 AH0 +PARBOIL P AA1 R B OY2 L +PARBOILING P AA1 R B OY2 L IH0 NG +PARC P AA1 R K +PARCEL P AA1 R S AH0 L +PARCELED P AA1 R S AH0 L D +PARCELING P AA1 R S AH0 L IH0 NG +PARCELING(1) P AA1 R S L IH0 NG +PARCELL P AA0 R S EY1 L +PARCELLS P AA1 R S AH0 L Z +PARCELS P AA1 R S AH0 L Z +PARCH P AA1 R CH +PARCHED P AA1 R CH T +PARCHER P AA1 R CH ER0 +PARCHMAN P AA1 R K M AH0 N +PARCHMENT P AA1 R CH M AH0 N T +PARCHMENTLIKE P AA1 R CH M AH0 N T L AY2 K +PARCPLACE P AA1 R K P L EY2 S +PARDE P AA1 R D +PARDEE P AA1 R D IY0 +PARDEN P AA1 R D AH0 N +PARDI P AA1 R D IY0 +PARDINI P AA0 R D IY1 N IY0 +PARDO P AA1 R D OW0 +PARDOE P AA1 R D OW2 +PARDON P AA1 R D AH0 N +PARDONED P AA1 R D AH0 N D +PARDONING P AA1 R D AH0 N IH0 NG +PARDONS P AA1 R D AH0 N Z +PARDUE P AA1 R D UW2 +PARDUS P AA1 R D AH0 S +PARDY P AA1 R D IY0 +PARE P EH1 R +PARED P EH1 R D +PAREDES P AA0 R EY1 D EH0 S +PAREDEZ P AA0 R EY1 D EH0 Z +PAREDIS P EH1 R AH0 D IH2 S +PAREDO P AH0 R EY1 D OW0 +PAREKH P AA1 R IH0 K +PARELLA P AA0 R EH1 L AH0 +PARENT P EH1 R AH0 N T +PARENT'S P EH1 R AH0 N T S +PARENTAGE P EH1 R AH0 N T AH0 JH +PARENTAL P ER0 EH1 N T AH0 L +PARENTE P AA0 R EH1 N T IY0 +PARENTEAU P AA0 R EH1 N T OW0 +PARENTHESES P ER0 EH1 N TH AH0 S IY2 Z +PARENTHESIS P ER0 EH1 N TH AH0 S IH0 S +PARENTHETICAL P ER0 EH0 N TH EH1 T IH0 K AH0 L +PARENTHETICALLY P ER0 EH0 N TH EH1 T IH0 K AH0 L IY0 +PARENTHETICALLY(1) P ER0 EH0 N TH EH1 T IH0 K L IY0 +PARENTHOOD P EH1 R AH0 N T HH UH2 D +PARENTI P AA0 R EH1 N T IY0 +PARENTING P EH1 R AH0 N T IH0 NG +PARENTS P EH1 R AH0 N T S +PARENTS' P EH1 R AH0 N T S +PARES P EH1 R Z +PARETI P EH2 R EH1 T IY0 +PARETO P AA2 R EH1 T OW0 +PARETTI P EH2 R EH1 T IY0 +PARFAIT P AA2 R F EY1 +PARFAITS P AA2 R F EY1 Z +PARFITT P AA1 R F IH0 T +PARFUMS P ER0 F Y UW1 M Z +PARFUMS(1) P AA0 R F Y UW1 M Z +PARGA P AA1 R G AH0 +PARGESA P AA0 R JH EH1 S AH0 +PARHAM P AA1 R HH AH0 M +PARIAGUA P AA0 R IY0 AA1 G W AH0 +PARIAH P ER0 AY1 AH0 +PARIAHS P ER0 AY1 AH0 Z +PARIBAS P EH0 R IY1 B AH0 S +PARIBAS'S P EH0 R IY1 B AH0 S IH0 Z +PARIETAL P ER0 AY1 AH0 T AH0 L +PARIKH P AE1 R IH0 K +PARILLO P AA0 R IH1 L OW0 +PARIMUTUEL P EH2 R IH0 M Y UW1 CH UW0 AH0 L +PARING P EH1 R IH0 NG +PARIS P EH1 R IH0 S +PARIS(1) P AE1 R IH0 S +PARIS' P EH1 R IH0 S +PARIS'(1) P AE1 R IH0 S +PARIS'S P EH1 R IH0 S IH0 Z +PARISE P AA1 R AY0 Z +PARISEAU P AE1 R IH0 S OW0 +PARISH P AE1 R IH0 SH +PARISH(1) P EH1 R IH0 SH +PARISHES P AE1 R IH0 SH IH0 Z +PARISHES(1) P EH1 R IH0 SH IH0 Z +PARISHIONER P ER0 IH1 SH AH0 N ER0 +PARISHIONERS P ER0 IH1 SH AH0 N ER0 Z +PARISI P AA0 R IY1 S IY0 +PARISIAN P ER0 IH1 ZH AH0 N +PARISIANS P ER0 IH1 S IY0 AH0 N Z +PARISIENNE P ER0 IH1 S IY0 EH2 N +PARITIES P EH1 R AH0 T IY0 Z +PARITY P EH1 R AH0 T IY0 +PARIZEAU P EH1 R IH0 Z OW2 +PARIZEK P ER0 IH1 Z EH0 K +PARIZO P AA0 R IY1 Z OW0 +PARK P AA1 R K +PARK'S P AA1 R K S +PARKA P AA1 R K AH0 +PARKAS P AA1 R K AH0 Z +PARKE P AA1 R K +PARKED P AA1 R K T +PARKER P AA1 R K ER0 +PARKER'S P AA1 R K ER0 Z +PARKERS P AA1 R K ER0 Z +PARKERSBURG P AA1 R K ER0 Z B ER0 G +PARKERSON P AA1 R K ER0 S AH0 N +PARKES P AA1 R K S +PARKEY P AA1 R K IY2 +PARKFIELD P AA1 R K F IY0 L D +PARKHILL P AA1 R K HH IH2 L +PARKHURST P AA1 R K HH ER0 S T +PARKIN P AA1 R K IH0 N +PARKING P AA1 R K IH0 NG +PARKINS P AA1 R K IH0 N Z +PARKINSON P AA1 R K IH0 N S AH0 N +PARKINSON'S P AA1 R K IH0 N S AH0 N Z +PARKINSONISM P AA1 R K IH0 N S AH0 N IH2 Z IH0 M +PARKISON P AA1 R K IH0 S AH0 N +PARKLAND P AA1 R K L AE2 N D +PARKMAN P AA1 R K M AH0 N +PARKS P AA1 R K S +PARKS' P AA1 R K S +PARKSIDE P AA1 R K S AY2 D +PARKWAY P AA1 R K W EY2 +PARLANCE P AA1 R L AH0 N S +PARLATO P AA0 R L AA1 T OW0 +PARLAY P AA1 R L EY0 +PARLAYED P AA1 R L EY2 D +PARLAYING P AA1 R L EY0 IH0 NG +PARLAYS P AA1 R L EY0 Z +PARLEE P AA1 R L IY2 +PARLER P AA1 R L ER0 +PARLETT P AA1 R L IH0 T +PARLETTE P AA2 R L EH1 T +PARLEY P AA1 R L IY0 +PARLIAMENT P AA1 R L AH0 M EH0 N T +PARLIAMENT'S P AA1 R L AH0 M EH0 N T S +PARLIAMENTARIAN P AA2 R L AH0 M EH0 N T EH1 R IY0 AH0 N +PARLIAMENTARIANISM P AA2 R L AH0 M EH0 N T EH1 R IY0 AH0 N IH2 Z AH0 M +PARLIAMENTARIANS P AA2 R L AH0 M EH0 N T EH1 R IY0 AH0 N Z +PARLIAMENTARY P AA2 R L AH0 M EH1 N T ER0 IY0 +PARLIAMENTS P AA1 R L AH0 M EH2 N T S +PARLIER P AA1 R L IY0 ER0 +PARLIN P AA1 R L IH0 N +PARLODEL P AA1 R L OW2 D EH2 L +PARLOR P AA1 R L ER0 +PARLORS P AA1 R L ER0 Z +PARLOUR P AA1 R L ER0 +PARLOW P AA1 R L OW2 +PARMA P AA1 R M AH0 +PARMALAT P AA1 R M AH0 L AE2 T +PARMAN P AA1 R M AH0 N +PARMAR P AA1 R M AA2 R +PARMELE P AA0 R M EH1 L IY0 +PARMELEE P AA1 R M IH0 L IY0 +PARMENTER P AA1 R M AH0 N T ER0 +PARMENTIER P AA1 R M AH0 N T IY0 ER0 +PARMER P AA1 R M ER0 +PARMESAN P AA1 R M AH0 Z AA2 N +PARMETER P AA1 R M IH0 T ER0 +PARMLEY P AA1 R M L IY0 +PARNASSUS P AA2 R N AE1 S AH0 S +PARNELL P AA1 R N AH0 L +PARNELLA P AA0 R N EH1 L AH0 +PARNES P AA1 R N Z +PARNESS P AA1 R N AH0 S +PARO P AA1 R OW0 +PAROCHIAL P ER0 OW1 K IY0 AH0 L +PAROCHIALISM P ER0 OW1 K IY0 AH0 L IH2 Z AH0 M +PARODI P AA0 R OW1 D IY0 +PARODIED P EH1 R AH0 D IY0 D +PARODIES P EH1 R AH0 D IY0 Z +PARODIST P AE1 R AH0 D IH0 S T +PARODY P EH1 R AH0 D IY0 +PAROLE P ER0 OW1 L +PAROLED P ER0 OW1 L D +PAROLEE P ER0 OW2 L IY1 +PAROLEES P ER0 OW2 L IY1 Z +PAROLES P ER0 OW1 L Z +PAROLING P ER0 OW1 L IH0 NG +PARPART P AA1 R P AA2 R T +PARQUET P AA0 R K EY1 +PARR P AA1 R +PARRA P AA1 R AH0 +PARRACK P AE1 R AH0 K +PARRAMORE P AA0 R AA1 M AO0 R +PARRAS P EH1 R AH0 Z +PARRELLA P AA0 R EH1 L AH0 +PARRENT P AA1 R AH0 N T +PARRETT P AE1 R IH0 T +PARRETTI P ER0 EH1 T IY0 +PARRETTI'S P ER0 EH1 T IY0 S +PARRIED P EH1 R IY0 D +PARRILL P AE1 R AH0 L +PARRILLA P AA2 R IH1 L AH0 +PARRILLO P AA2 R IH1 L OW0 +PARRINELLO P AA0 R IY0 N EH1 L OW0 +PARRINO P AA2 R IY1 N OW0 +PARRIOTT P AE1 R IY0 AH0 T +PARRIS P EH1 R IH0 S +PARRISH P EH1 R IH0 SH +PARRISHES P EH1 R IH0 SH IH0 Z +PARROT P EH1 R AH0 T +PARROTS P EH1 R AH0 T S +PARROTT P EH1 R AH0 T +PARROTTA P AA0 R OW1 T AH0 +PARROW P AE1 R OW0 +PARRY P EH1 R IY0 +PARS P AA1 R Z +PARSE P AA1 R S +PARSEC P AA1 R S EH2 K +PARSED P AA1 R S T +PARSEFAL P AA1 R S IH0 F AH0 L +PARSELL P AA1 R S AH0 L +PARSER P AA1 R S ER0 +PARSERS P AA1 R S ER0 Z +PARSHALL P AA1 R SH AH0 L +PARSHLEY P AA1 R SH L IY0 +PARSI P AA1 R S IY0 +PARSIFAL P AA1 R S IH0 F AH0 L +PARSIFAL(1) P AA1 R Z AH0 F AA2 L +PARSIMONIOUS P AA2 R S AH0 M OW1 N IY0 AH0 S +PARSIMONY P AA1 R S AH0 M OW2 N IY0 +PARSING P AA1 R S IH0 NG +PARSIPPANY P AA0 R S IH1 P AH0 N IY0 +PARSKY P AA1 R S K IY0 +PARSLEY P AA1 R S L IY0 +PARSLOW P AA1 R S L OW2 +PARSON P AA1 R S AH0 N +PARSONAGE P AA1 R S AH0 N IH0 JH +PARSONAGES P AA1 R S AH0 N IH0 JH AH0 Z +PARSONS P AA1 R S AH0 N Z +PARSOW P AA1 R S OW0 +PART P AA1 R T +PART'S P AA1 R T S +PART-TIME P AA1 R T T AY1 M +PARTAIN P AA0 R T EY1 N +PARTAKE P AA0 R T EY1 K +PARTCH P AA1 R CH +PARTE P AA1 R T +PARTE(1) P AA1 R T EY0 +PARTECIPAZIONI P AA2 R T EH2 S IH0 P AE2 Z IY0 OW1 N IY0 +PARTED P AA1 R T IH0 D +PARTEE P AA1 R T IY1 +PARTEN P AA1 R T AH0 N +PARTENOPE P AA1 R T AH0 N OW2 P +PARTHENIA P AA0 R TH EH1 N IY0 AH0 +PARTHENOGENETIC P AA2 R TH AH0 N OW0 JH AH0 N EH1 T IH0 K +PARTHENON P AA1 R TH AH0 N AA2 N +PARTHIAN P AA1 R TH IY0 AH0 N +PARTI P AA1 R T IY0 +PARTIAL P AA1 R SH AH0 L +PARTIALITY P AA2 R SH IY0 AE1 L AH0 T IY0 +PARTIALLY P AA1 R SH AH0 L IY0 +PARTIALLY(1) P AA1 R SH L IY0 +PARTICIPANT P AA0 R T IH1 S AH0 P AH0 N T +PARTICIPANTS P AA0 R T IH1 S AH0 P AH0 N T S +PARTICIPANTS' P AA0 R T IH1 S AH0 P AH0 N T S +PARTICIPATE P AA0 R T IH1 S AH0 P EY2 T +PARTICIPATED P AA0 R T IH1 S AH0 P EY2 T IH0 D +PARTICIPATES P AA0 R T IH1 S AH0 P EY2 T S +PARTICIPATING P AA0 R T IH1 S AH0 P EY2 T IH0 NG +PARTICIPATION P AA0 R T IH2 S AH0 P EY1 SH AH0 N +PARTICIPATIONS P AA0 R T IH2 S AH0 P EY1 SH AH0 N Z +PARTICIPATIVE P AA2 R T IH1 S AH0 P AH0 T IH0 V +PARTICIPATORY P AA2 R T IH1 S AH0 P AH0 T AO2 R IY0 +PARTICIPLE P AA1 R T IH0 S IH2 P AH0 L +PARTICIPLES P AA1 R T IH0 S IH2 P AH0 L Z +PARTICLE P AA1 R T AH0 K AH0 L +PARTICLE(1) P AA1 R T IH0 K AH0 L +PARTICLES P AA1 R T AH0 K AH0 L Z +PARTICLES(1) P AA1 R T IH0 K AH0 L Z +PARTICULAR P ER0 T IH1 K Y AH0 L ER0 +PARTICULAR(1) P AA2 T IH1 K Y AH0 L ER0 +PARTICULARITY P ER0 T IH2 K Y AH0 L AE1 R AH0 T IY0 +PARTICULARLY P AA2 R T IH1 K Y AH0 L ER0 L IY0 +PARTICULARLY(1) P ER0 T IH1 K Y AH0 L ER0 L IY0 +PARTICULARS P ER0 T IH1 K Y AH0 L ER0 Z +PARTICULATE P ER0 T IH1 K Y AH0 L AH0 T +PARTICULATES P AA2 R T IH1 K Y AH0 L AH0 T S +PARTIDA P AA0 R T IY1 D AH0 +PARTIDO P AA0 R T IY1 D OW0 +PARTIED P AA1 R T IY0 D +PARTIES P AA1 R T IY0 Z +PARTIES' P AA1 R T IY0 Z +PARTIES'(1) P AA1 R T IY2 Z +PARTIN P AA1 R T IH0 N +PARTING P AA1 R T IH0 NG +PARTINGTON P AA1 R T IH0 NG T AH0 N +PARTISAN P AA1 R T AH0 Z AH0 N +PARTISANED P AA1 R T AH0 Z AH0 N D +PARTISANS P AA1 R T AH0 Z AH0 N Z +PARTISANSHIP P AA1 R T AH0 Z AH0 N SH IH2 P +PARTITION P AA0 R T IH1 SH AH0 N +PARTITIONED P AA0 R T IH1 SH AH0 N D +PARTITIONING P AA0 R T IH1 SH AH0 N IH0 NG +PARTITIONS P AA0 R T IH1 SH AH0 N Z +PARTLOW P AA1 R T L OW2 +PARTLY P AA1 R T L IY0 +PARTNER P AA1 R T N ER0 +PARTNER'S P AA1 R T N ER0 Z +PARTNERING P AA1 R T N ER0 IH0 NG +PARTNERS P AA1 R T N ER0 Z +PARTNERS' P AA1 R T N ER0 Z +PARTNERSHIP P AA1 R T N ER0 SH IH2 P +PARTNERSHIP'S P AA1 R T N ER0 SH IH2 P S +PARTNERSHIPS P AA1 R T N ER0 SH IH2 P S +PARTNERSHIPS' P AA1 R T N ER0 SH IH0 P S +PARTNEY P AA1 R T N IY0 +PARTON P AA1 R T AH0 N +PARTRIDGE P AA1 R T R AH0 JH +PARTRIDGE(1) P AA1 R T R IH0 JH +PARTRIDGES P AA1 R T R IH0 JH IH0 Z +PARTS P AA1 R T S +PARTS' P AA1 R T S +PARTTIME P AA1 R T T AY2 M +PARTUM P AA1 R T AH0 M +PARTY P AA1 R T IY0 +PARTY'S P AA1 R T IY0 Z +PARTYING P AA1 R T IY0 IH0 NG +PARTYKA P ER0 T IH1 K AH0 +PARVIN P AA1 R V IH0 N +PARY P AA1 R IY0 +PARZIALE P AA2 R Z IY0 AA1 L IY0 +PARZYCH P AA1 R Z IH0 HH +PAS P AA1 Z +PAS-DE-DEUX P AA1 D AH0 D UW1 +PASADENA P AE2 S AH0 D IY1 N ER0 +PASCAGOULA P AE2 S K AH0 G UW1 L AH0 +PASCAL P AE0 S K AE1 L +PASCALE P AE0 S K AE1 L +PASCARELLA P AA0 S K AA0 R EH1 L AH0 +PASCARELLI P AA0 S K AA0 R EH1 L IY0 +PASCH P AE1 S K +PASCHAL P AE1 SH AH0 L +PASCHALL P AE1 SH AH0 L +PASCHEN P AE1 SH AH0 N +PASCHKE P AE1 SH K +PASCO P AA1 S K OW0 +PASCOE P AE1 S K OW0 +PASCUA P AA0 S K UW1 AH0 +PASCUAL P AE1 S K UW0 AH0 L +PASCUCCI P AA0 S K UW1 CH IY0 +PASCUTTO P AH0 S K Y UW1 T OW0 +PASCUZZI P AA0 S K UW1 T S IY0 +PASEK P AA1 S EH0 K +PASEO P AA0 S EY1 OW2 +PASH P AE1 SH +PASHA P AH0 SH AA1 +PASHA(1) P AA1 SH AH0 +PASHLEY P AE1 SH L IY0 +PASILLAS P AA0 S IH1 L AH0 Z +PASING P EY1 S IH0 NG +PASION P AA0 ZH IY1 N +PASK P AE1 S K +PASKE P EY1 S K +PASKEY P AE1 S K IY0 +PASKO P AA1 S K OW0 +PASLAY P AE1 S L EY0 +PASLEY P AE1 S L IY0 +PASMAN P AE1 S M AH0 N +PASO P AE1 S OW0 +PASO'S P AE1 S OW0 Z +PASOK P AA1 Z AA0 K +PASOK(1) P AE1 S AO0 K +PASQUA P AA1 S K W AH0 +PASQUALE P AA0 S K W AA1 L EY0 +PASQUARELLA P AA0 S K W AA0 R EH1 L AH0 +PASQUARELLI P AA0 S K W AA0 R EH1 L IY0 +PASQUARELLO P AA0 S K W AA0 R EH1 L OW0 +PASQUARIELLO P AA0 S K W AA0 R IY0 EH1 L OW0 +PASQUE P AE1 S K +PASQUINELLI P AA0 S K W IY0 N EH1 L IY0 +PASQUINI P AA0 S K W IY1 N IY0 +PASS P AE1 S +PASSABLE P AE1 S AH0 B AH0 L +PASSABLY P AE1 S AH0 B L IY0 +PASSAFIUME P AA0 S AA0 F IY1 UW0 M +PASSAGE P AE1 S AH0 JH +PASSAGE(1) P AE1 S IH0 JH +PASSAGES P AE1 S AH0 JH AH0 Z +PASSAGES(1) P AE1 S IH0 JH IH0 Z +PASSAGEWAY P AE1 S AH0 JH W EY2 +PASSAGEWAY(1) P AE1 S IH0 JH W EY2 +PASSAIC P AH0 S EY1 IH0 K +PASSALACQUA P AE2 S AH0 L AE1 K W AH0 +PASSANISI P AA0 S AA0 N IY1 S IY0 +PASSANTE P AA0 S AA1 N T IY0 +PASSANTINO P AA0 S AA0 N T IY1 N OW0 +PASSARELLA P AA0 S AA0 R EH1 L AH0 +PASSARELLI P AA0 S AA0 R EH1 L IY0 +PASSARETTI P AA0 S AA0 R EH1 T IY0 +PASSARO P AA0 S AA1 R OW0 +PASSAT P AE1 S AE0 T +PASSBOOK P AE1 S B UH2 K +PASSBOOKS P AE1 S B UH2 K S +PASSE P AE2 S EY1 +PASSED P AE1 S T +PASSEL P AE1 S IH0 L +PASSENGER P AE1 S AH0 N JH ER0 +PASSENGER'S P AE1 S AH0 N JH ER0 Z +PASSENGERS P AE1 S AH0 N JH ER0 Z +PASSENGERS' P AE1 S AH0 N JH ER0 Z +PASSER P AE1 S ER0 +PASSERBY P AE1 S ER0 B IY0 +PASSERO P AA0 S EH1 R OW0 +PASSERS P AE1 S ER0 Z +PASSERS-BY P AE1 S ER0 Z B AY2 +PASSERSBY P AE1 S ER0 Z B IY0 +PASSES P AE1 S AH0 Z +PASSES(1) P AE1 S IH0 Z +PASSEY P AE1 S IY0 +PASSIM P AE0 S IY1 M +PASSING P AE1 S IH0 NG +PASSINO P AA0 S IY1 N OW0 +PASSION P AE1 SH AH0 N +PASSIONATE P AE1 SH AH0 N AH0 T +PASSIONATELY P AE1 SH AH0 N AH0 T L IY0 +PASSIONS P AE1 SH AH0 N Z +PASSIVE P AE1 S IH0 V +PASSIVELY P AE1 S IH0 V L IY0 +PASSIVITY P AH0 S IH1 V IH0 T IY0 +PASSMAN P AE1 S M AH0 N +PASSMORE P AA1 S M AO0 R +PASSON P AE1 S AH0 N +PASSOVER P AE1 S OW2 V ER0 +PASSOW P AE1 S OW0 +PASSPORT P AE1 S P AO2 R T +PASSPORTS P AE1 S P AO2 R T S +PASSWORD P AE1 S W ER2 D +PASSWORDS P AE1 S W ER2 D Z +PAST P AE1 S T +PASTA P AA1 S T AH0 +PASTAS P AA1 S T AH0 Z +PASTE P EY1 S T +PASTED P EY1 S T IH0 D +PASTEL P AE0 S T EH1 L +PASTELS P AE0 S T EH1 L Z +PASTER P AE1 S T ER0 +PASTERNACK P AE1 S T ER0 N AE0 K +PASTERNAK P AE1 S T ER0 N AE0 K +PASTERNAK'S P AE1 S T ER0 N AE0 K S +PASTES P EY1 S T S +PASTEUR P AH0 S T UW1 R +PASTEURIZATION P AE2 S CH ER0 AH0 Z EY1 SH AH0 N +PASTEURIZE P AE1 S CH ER0 AY2 Z +PASTEURIZED P AE1 S CH ER0 AY2 Z D +PASTEURIZES P AE1 S CH ER0 AY2 Z IH0 Z +PASTEURIZING P AE1 S CH ER0 AY2 Z IH0 NG +PASTICHE P AE2 S T IY1 SH +PASTICHES P AE2 S T IY1 SH AH0 Z +PASTIME P AE1 S T AY2 M +PASTIMES P AE1 S T AY2 M Z +PASTING P EY1 S T IH0 NG +PASTOR P AE1 S T ER0 +PASTOR'S P AE1 S T ER0 Z +PASTORA P AE0 S T AO1 R AH0 +PASTORAL P AE1 S T ER0 AH0 L +PASTORALISM P AE1 S T ER0 AH0 L IH2 Z AH0 M +PASTORALIZE P AE1 T ER0 AH0 L AY2 Z +PASTORE P AE1 S T AO2 R +PASTORINO P AA0 S T AO0 R IY1 N OW0 +PASTORIUS P AE1 S T AO0 R IY0 IH0 S +PASTORS P AE1 S T ER0 Z +PASTRAMI P AH0 S T R AA1 M IY0 +PASTRANA P AA0 S T R AE1 N AH0 +PASTRIES P EY1 S T R IY0 Z +PASTRY P EY1 S T R IY0 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NG +PATENTLY P AE1 T AH0 N T L IY0 +PATENTS P AE1 T AH0 N T S +PATER P EY1 T ER0 +PATERA P AA0 T EH1 R AH0 +PATERNAL P AH0 T ER1 N AH0 L +PATERNALISM P AH0 T ER1 N AH0 L IH2 Z AH0 M +PATERNALISTIC P AH0 T ER2 N AH0 L IH1 S T IH0 K +PATERNITY P AH0 T ER1 N IH0 T IY0 +PATERNO P AA0 T EH1 R N OW0 +PATERNOSTRO P AA0 T ER0 N OW1 S T R OW0 +PATERSON P AE1 T ER0 S AH0 N +PATES P EY1 T S +PATESE P AH0 T IY1 S IY0 +PATESE(1) P AH0 T IY1 S +PATEY P EY1 T IY0 +PATH P AE1 TH +PATHAK P AH0 TH AA1 K +PATHAK(1) P AH0 T AA1 K +PATHAN P AE1 TH AH0 N +PATHANS P AE1 TH AH0 N Z +PATHE P AE1 TH +PATHET-LAO P AE1 TH AH0 T L AW1 +PATHETIC P AH0 TH EH1 T IH0 K +PATHETICALLY P AH0 TH EH1 T IH0 K AH0 L IY0 +PATHETICALLY(1) P AH0 TH EH1 T IH0 K L IY0 +PATHFINDER P AE1 TH F AY2 N D ER0 +PATHMARK P AE1 TH M AA2 R K +PATHMARK'S P AE1 TH M AA2 R K S +PATHOGEN P AE1 TH AH0 JH AH0 N +PATHOGENESIS P AE2 TH AH0 JH EH1 N AH0 S IH0 S +PATHOGENIC P AE2 TH AH0 JH EH1 N IH0 K +PATHOGENS P AE1 TH AH0 JH AH0 N Z +PATHOLOGIC P AE2 TH AH0 L AA1 JH IH0 K +PATHOLOGICAL P AE2 TH AH0 L AA1 JH IH0 K AH0 L +PATHOLOGICALLY P AE2 TH AH0 L AA1 JH IH0 K L IY0 +PATHOLOGIES P AH0 TH AA1 L AH0 JH IY0 Z +PATHOLOGIST P AH0 TH AA1 L AH0 JH AH0 S T +PATHOLOGISTS P AH0 TH AA1 L AH0 JH AH0 S T S +PATHOLOGY P AH0 TH AA1 L AH0 JH IY0 +PATHOS P EY1 TH AA0 S +PATHS P AE1 DH Z +PATHS(1) P AE1 TH S +PATHWAY P AE1 TH W EY2 +PATHWAYS P AE1 TH W EY2 Z +PATIENCE P EY1 SH AH0 N S +PATIENT P EY1 SH AH0 N T +PATIENT'S P EY1 SH AH0 N T S +PATIENTLY P EY1 SH AH0 N T L IY0 +PATIENTS P EY1 SH AH0 N T S +PATIENTS(1) P EY1 SH AH0 N Z +PATIENTS' P EY1 SH AH0 N T S +PATILLO P AH0 T IH1 L OW0 +PATIN P AE1 T IH0 N +PATINA P AH0 T IY1 N AH0 +PATINKIN P AH0 T IH1 NG K IH0 N +PATINO P AA0 T IY1 N OW0 +PATIO P AE1 T IY0 OW2 +PATIOS P AE1 T IY0 OW2 Z +PATLAN P AE1 T L AH0 N +PATLEX P AE1 T L EH0 K S +PATLEX'S P AE1 T L EH0 K S IH0 Z +PATMAN P AE1 T M AH0 N +PATMORE P AE1 T M AO0 R +PATNAUDE P AA0 T N AO1 D IY0 +PATNODE P AE1 T N OW2 D +PATOIS P AE2 T W AA1 +PATON P AE1 T AH0 N +PATONS P AE1 T AH0 N Z +PATRIARCA P AA0 T R IY0 AA1 R K AH0 +PATRIARCH P EY1 T R IY0 AA2 R K +PATRIARCH'S P EY1 T R IY0 AA2 R K S +PATRIARCHAL P EY2 T R IY0 AA1 R K AH0 L +PATRIARCHATE P EY1 T R IY0 AA2 R K AH0 T +PATRIARCHS P EY1 T R IY0 AA2 R K S +PATRIARCHY P EY1 T R IY0 AA2 R K IY0 +PATRICE P AH0 T R IY1 S +PATRICELLI P AA0 T R IY0 CH EH1 L IY0 +PATRICIA P AH0 T R IH1 SH AH0 +PATRICIAN P AH0 T R IH1 SH AH0 N +PATRICIANS P AH0 T R IH1 SH AH0 N Z +PATRICIO P AH0 T R IH1 S IY0 OW0 +PATRICK P AE1 T R IH0 K +PATRICK'S P AE1 T R IH0 K S +PATRICKS P AE1 T R IH0 K S +PATRICOF P AE1 T R IH0 K AO2 F +PATRIDGE P AE1 T R IH2 JH +PATRIE P AE1 T ER0 IY0 +PATRILINEAL P AE2 T R IH0 L IH1 N IY0 AH0 L +PATRIMONIAL P AE1 T R AH0 M OW2 N Y AH0 L +PATRIMONIAL(1) P AE1 T R AH0 M OW2 N IY0 AH0 L +PATRIMONY P AE1 T R AH0 M OW2 N IY0 +PATRIOT P EY1 T R IY0 AH0 T +PATRIOT'S P EY1 T R IY0 AH0 T S +PATRIOTIC P EY2 T R IY0 AA1 T IH0 K +PATRIOTISM P EY1 T R IY0 AH0 T IH2 Z AH0 M 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P ER0 M IH2 N T +PEPPERONI P EH2 P ER0 OW1 N IY0 +PEPPERS P EH1 P ER0 Z +PEPPI P EH1 P IY0 +PEPPIN P EH1 P IH0 N +PEPPLE P EH1 P AH0 L +PEPPLER P EH1 P L ER0 +PEPPY P EH1 P IY0 +PEPSI P EH1 P S IY0 +PEPSI'S P EH1 P S IY0 Z +PEPSICO P EH1 P S IH0 K OW0 +PEPSICO'S P EH1 P S IH0 K OW0 Z +PEPTIC P EH1 P T IH0 K +PEPTIDE P EH1 P T AY2 D +PEPTIDES P EH1 P T AY2 D Z +PEQUENO P EY0 K W EY1 N OW0 +PEQUIGNOT P IH0 K W IH1 G N AH0 T +PER P ER1 +PER-SE P ER2 S EY1 +PERA P ER1 AH0 +PERAGINE P ER0 AA0 JH IY1 N IY0 +PERAINO P ER0 AA0 IY1 N OW0 +PERALA P ER0 AA1 L AH0 +PERALES P ER0 AA1 L EH0 S +PERALEZ P ER0 AA1 L EH0 Z +PERALTA P ER0 AA1 L T AH0 +PERAS P EH1 R AH0 S +PERATIS P ER0 AA1 T IH0 S +PERATIS(1) P ER0 AE1 T IH0 S +PERATIS' P ER0 AA1 T IH0 S +PERATIS'(1) P ER0 AE1 T IH0 S +PERAZA P ER0 AA1 Z AH0 +PERAZZO P ER0 AA1 Z OW0 +PERC P ER1 K +PERCE P ER1 S +PERCEIVE P ER0 S IY1 V +PERCEIVED P ER0 S IY1 V D +PERCEIVES P ER0 S IY1 V Z +PERCEIVING P ER0 S IY1 V IH0 NG +PERCELL P ER0 S EH1 L +PERCENT P 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L EY2 T IH0 NG +PERCOLATOR P ER1 K AH0 L EY2 T ER0 +PERCOLATORS P ER1 K AH0 L EY2 T ER0 Z +PERCS P ER1 K S +PERCUSSION P ER0 K AH1 SH AH0 N +PERCUSSIONIST P ER0 K AH1 SH AH0 N IH0 S T +PERCUSSIVE P ER0 K AH1 S AH0 V +PERCUTANEOUS P ER0 K Y UW0 T EY1 N IY0 AH0 S +PERCY P ER1 S IY0 +PERCY'S P ER1 S IY0 Z +PERDEW P ER1 D UW0 +PERDITA P ER0 D IY1 T AH0 +PERDOMO P ER0 D OW1 M OW0 +PERDUE P ER0 D UW1 +PERE P ER1 +PEREA P ER0 IY1 AH0 +PEREDA P ER0 EY1 D AH0 +PEREGOY P ER1 IH0 G OY0 +PEREGRINE P EH1 R AH0 G R IY2 N +PEREGRINES P EH1 R AH0 G R IY2 N Z +PEREIRA P ER0 EH1 R AH0 +PERELLA P ER0 EH1 L AH0 +PERELMAN P EH1 R AH0 L M AH0 N +PERELMAN'S P EH1 R AH0 L M AH0 N Z +PEREMPTORY P ER0 EH1 M P T ER0 IY0 +PERENNIAL P ER0 EH1 N IY0 AH0 L +PERENNIALLY P ER0 EH1 N IY0 AH0 L IY0 +PERENNIALS P ER0 EH1 N IY0 AH0 L Z +PERERA P ER0 EH1 R AH0 +PERES P EH1 R EH0 Z +PERES' P EH1 R EH0 Z +PERES'S P EH1 R EH0 Z IH0 Z +PERESTROIKA P EH2 R AH0 S T R OY1 K AH0 +PERETTI P ER0 EH1 T IY0 +PERETZ P ER1 IH0 T S 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+PERFORMATIVE P ER0 F AO1 R M AH0 T IH0 V +PERFORMATIVES P ER0 F AO1 R M AH0 T IH0 V Z +PERFORMED P ER0 F AO1 R M D +PERFORMER P ER0 F AO1 R M ER0 +PERFORMERS P ER0 F AO1 R M ER0 Z +PERFORMERS' P ER0 F AO1 R M ER0 Z +PERFORMING P ER0 F AO1 R M IH0 NG +PERFORMS P ER0 F AO1 R M Z +PERFUME P ER0 F Y UW1 M +PERFUMED P ER0 F Y UW1 M D +PERFUMES P ER0 F Y UW1 M Z +PERFUMING P ER0 F Y UW1 M IH0 NG +PERFUNCTORY P ER0 F AH1 NG K T ER0 IY0 +PERFUSION P ER0 F Y UW1 Z AH0 N +PERGAMON P ER1 G AH0 M AH0 N +PERGANDE P ER1 G IH0 N D +PERGOLA P ER1 G AH0 L AH0 +PERGOLA(1) P ER0 G OW1 L AH0 +PERGOLAS P ER2 G OW1 L AH0 Z +PERHAM P ER1 HH AH0 M +PERHAPS P ER0 HH AE1 P S +PERIA P EH1 R IY0 AH0 +PERIA'S P EH1 R IY0 AH0 Z +PERICH P ER1 IH0 K +PERIDOT P EH1 R IH0 D AO0 T +PERIDOT(1) P EH1 R IH0 D OW0 +PERIGNON P ER0 IH1 N Y AA0 N +PERIGNON(1) P EH2 R IH0 G N AA1 N +PERIGO P ER0 IY1 G OW0 +PERIL P EH1 R AH0 L +PERILLO P ER0 IH1 L OW0 +PERILOUS P EH1 R AH0 L AH0 S +PERILOUSLY P EH1 R AH0 L AH0 S L IY0 +PERILS P EH1 R AH0 L Z +PERIMAN P ER1 IY0 M AH0 N +PERIMETER P ER0 IH1 M AH0 T ER0 +PERIMETERS P ER0 IH1 M AH0 T ER0 Z +PERIN P ER1 IH0 N +PERINE P ER0 IY1 N IY0 +PERINEURAL P ER2 IY1 N UH2 R AH0 L +PERINI P ER0 IY1 N IY0 +PERINO P ER0 IY1 N OW0 +PERIOD P IH1 R IY0 AH0 D +PERIOD'S P IH1 R IY0 AH0 D Z +PERIODIC P IH2 R IY0 AA1 D IH0 K +PERIODICAL P IH2 R IY0 AA1 D IH0 K AH0 L +PERIODICALLY P IY2 R IY0 AA1 D IH0 K AH0 L IY0 +PERIODICALLY(1) P IY2 R IY0 AA1 D IH0 K L IY0 +PERIODICALS P IH2 R IY0 AA1 D IH0 K AH0 L Z +PERIODONTAL P EH2 R IY0 AH0 D AA1 N T AH0 L +PERIODONTAL(1) P EH2 R IY0 AH0 D AA1 N AH0 L +PERIODS P IH1 R IY0 AH0 D Z +PERIPATETIC P EH2 R AH0 P AH0 T EH1 T IH0 K +PERIPHERAL P ER0 IH1 F ER0 AH0 L +PERIPHERAL(1) P ER0 IH1 F R AH0 L +PERIPHERALLY P ER0 IH1 F ER0 AH0 L IY0 +PERIPHERALLY(1) P ER0 IH1 F R AH0 L IY0 +PERIPHERALS P ER0 IH1 F ER0 AH0 L Z +PERIPHERALS(1) P ER0 IH1 F R AH0 L Z +PERIPHERY P ER0 IH1 F ER0 IY0 +PERISCOPE P EH1 R AH0 S K OW2 P +PERISCOPES P EH1 R AH0 S K OW2 P S 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N D IH1 K Y AH0 L ER0 +PERPETRATE P ER1 P AH0 T R EY2 T +PERPETRATED P ER1 P AH0 T R EY2 T IH0 D +PERPETRATES P ER1 P AH0 T R EY2 T S +PERPETRATING P ER1 P AH0 T R EY2 T IH0 NG +PERPETRATOR P ER1 P AH0 T R EY2 T ER0 +PERPETRATOR'S P ER1 P AH0 T R EY2 T ER0 Z +PERPETRATORS P ER1 P AH0 T R EY2 T ER0 Z +PERPETUA P ER0 P EH1 CH UW0 AH0 +PERPETUAL P ER0 P EH1 CH UW0 AH0 L +PERPETUALLY P ER0 P EH1 CH UW0 AH0 L IY0 +PERPETUALS P ER0 P EH1 CH UW0 AH0 L Z +PERPETUATE P ER0 P EH1 CH AH0 W EY2 T +PERPETUATED P ER0 P EH1 CH AH0 W EY2 T IH0 D +PERPETUATES P ER0 P EH1 CH AH0 W EY2 T S +PERPETUATING P ER0 P EH1 CH AH0 W EY2 T IH0 NG +PERPETUATION P ER0 P EH2 CH AH0 W EY1 SH AH0 N +PERPETUITY P ER2 P IH0 T Y UW1 IH0 T IY0 +PERPICH P ER1 P IH0 K +PERPLEX P ER0 P L EH1 K S +PERPLEXED P ER0 P L EH1 K S T +PERPLEXES P ER0 P L EH1 K S IH0 Z +PERPLEXING P ER0 P L EH1 K S IH0 NG +PERPLEXITY P ER0 P L EH1 K S AH0 T IY0 +PERQUISITE P ER1 K W AH0 Z IH0 T +PERQUISITES P ER1 K W AH0 Z IH0 T S +PERQUISITES(1) P ER1 K W IH0 Z IH0 T S +PERRA P ER1 R AH0 +PERRAS P ER1 R AH0 Z +PERRAULT P EH1 R AO0 L T +PERRAULT(1) P ER0 AO1 L T +PERREAULT P ER0 R OW1 +PERREIRA P ER0 R EH1 R AH0 +PERRELL P ER0 R EY1 L +PERRELLA P ER0 R EH1 L AH0 +PERRELLI P ER0 R EH1 L IY0 +PERREN P ER1 R AH0 N +PERRET P ER1 R IH0 T +PERRETT P ER1 R IH0 T +PERRETTA P ER0 R EH1 T AH0 +PERRETTI P ER0 R EH1 T IY0 +PERRI P ER1 R IY0 +PERRICONE P ER0 R IY0 K OW1 N IY0 +PERRIELLO P ER0 R IY0 EH1 L OW0 +PERRIER P EH1 R IY0 ER0 +PERRIER(1) P EH2 R IY0 EY1 +PERRIGO P ER0 R IY1 G OW0 +PERRIN P EH1 R IH0 N +PERRINE P ER0 R IY1 N IY0 +PERRINO P ER0 R IY1 N OW0 +PERRINS P EH1 R IH0 N Z +PERRITT P ER1 R IH0 T +PERRO P ER1 R OW0 +PERRODIN P ER1 R AH0 D IH0 N +PERRON P EH1 R AH0 N +PERRONE P ER0 R OW1 N IY0 +PERROT P ER1 R AH0 T +PERROTT P ER0 R AA1 T +PERROTTA P ER0 R OW1 T AH0 +PERROTTI P ER0 R OW1 T IY0 +PERROTTO P ER0 R OW1 T OW0 +PERROW P ER1 R OW0 +PERRY P EH1 R IY0 +PERRY'S P EH1 R IY0 Z +PERRYMAN P ER1 R IY0 M AH0 N +PERRYN P ER1 R IH0 N 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S AA1 N IH0 K S +PERSONIFICATION P ER0 S AA2 N AH0 F AH0 K EY1 SH AH0 N +PERSONIFIED P ER0 S AA1 N AH0 F AY2 D +PERSONIFIES P ER0 S AA1 N AH0 F AY2 Z +PERSONIFY P ER0 S AA1 N AH0 F AY2 +PERSONIFYING P ER0 S AA1 N AH0 F AY2 IH0 NG +PERSONNEL P ER2 S AH0 N EH1 L +PERSONS P ER1 S AH0 N Z +PERSPECTIVE P ER0 S P EH1 K T IH0 V +PERSPECTIVES P ER0 S P EH1 K T IH0 V Z +PERSPICACIOUS P ER0 S P AH0 K EY1 SH AH0 S +PERSPIRATION P ER2 S P ER0 EY1 SH AH0 N +PERSPIRE P ER0 S P AY1 R +PERSPIRING P ER0 S P AY1 R IH0 NG +PERSSON P ER1 S AH0 N +PERSUADABLE P ER0 S W EY1 D AH0 B AH0 L +PERSUADE P ER0 S W EY1 D +PERSUADED P ER0 S W EY1 D IH0 D +PERSUADES P ER0 S W EY1 D Z +PERSUADING P ER0 S W EY1 D IH0 NG +PERSUASION P ER0 S W EY1 ZH AH0 N +PERSUASIONS P ER0 S W EY1 ZH AH0 N Z +PERSUASIVE P ER0 S W EY1 S IH0 V +PERSUASIVELY P ER0 S W EY1 S IH0 V L IY0 +PERSUASIVENESS P ER0 S W EY1 S IH0 V N AH0 S +PERSYN P ER1 S IH0 N +PERT P ER1 T +PERTAIN P ER0 T EY1 N +PERTAINED P ER0 T EY1 N D +PERTAINING P ER0 T EY1 N IH0 NG +PERTAINS P ER0 T EY1 N Z +PERTAMINA P ER0 T AH0 M IY1 N AH0 +PERTH P ER1 TH +PERTINENT P ER1 T IH0 N IH0 N T +PERTINENTLY P ER1 T IH0 N IH0 N T L IY0 +PERTSCHUK P ER1 CH AH0 K +PERTUIT P ER1 T IH0 T +PERTUIT(1) P ER1 T UW0 AH0 T +PERTURB P ER0 T ER1 B +PERTURBATION P ER2 T ER0 B EY1 SH AH0 N +PERTURBATIONS P ER2 T ER0 B EY1 SH AH0 N Z +PERTURBED P ER0 T ER1 B D +PERTURBING P ER0 T ER1 B IH0 NG +PERTURBS P ER0 T ER1 B Z +PERTUSSIS P ER0 T AH1 S IH0 S +PERU P ER0 UW1 +PERU'S P ER0 UW1 Z +PERUGIA P ER0 UW1 G IY0 AH0 +PERUGINA P EH2 R UW0 JH IY1 N AH0 +PERUGINI P ER0 UW0 JH IY1 N IY0 +PERULAC P EH1 R UW0 L AE0 K +PERUSAL P ER0 UW1 Z AH0 L +PERUSE P ER0 UW1 Z +PERUSED P ER0 UW1 Z D +PERUSES P ER0 UW1 Z IH0 Z +PERUSING P ER0 UW1 Z IH0 NG +PERUSSE P ER0 UW1 S IY0 +PERUVIAN P ER0 UW1 V IY0 AH0 N +PERUVIANS P ER0 UW1 V IY0 AH0 N Z +PERUZZI P ER0 UW1 T S IY0 +PERVADE P ER0 V EY1 D +PERVADED P ER0 V EY1 D IH0 D +PERVADES P ER0 V EY1 D Z +PERVADING P ER0 V EY1 D IH0 NG +PERVASIVE P ER0 V EY1 S IH0 V +PERVASIVENESS P ER0 V EY1 S IH0 V N IH0 S +PERVERSE P ER0 V ER1 S +PERVERSELY P ER0 V ER1 S L IY0 +PERVERSION P ER0 V ER1 ZH AH0 N +PERVERSITY P ER0 V ER1 S AH0 T IY0 +PERVERT P ER1 V ER0 T +PERVERT(1) P ER0 V ER1 T +PERVERTED P ER0 V ER1 T IH0 D +PERVERTING P ER0 V ER1 T IH0 NG +PERVERTS P ER1 V ER0 T S +PERVERTS(1) P ER0 V ER1 T S +PERVOMAISKAYA P ER0 V OW0 M EY0 S K AY1 AH0 +PERZ P ER1 Z +PERZIGIAN P ER0 Z IH1 G IY0 AH0 N +PESATORI P EH2 S AH0 T AO1 R IY0 +PESAVENTO P EH2 S AH0 V EH1 N T OW0 +PESCATORE P EH0 S K AA0 T AO1 R IY0 +PESCE P EH1 S +PESCH P EH1 SH +PESCHEL P EH1 SH AH0 L +PESCHKE P EH1 SH K +PESCI P EH1 S K IY0 +PESEK P EH1 S EH0 K +PESETA P AH0 S EY1 T AH0 +PESETAS P AH0 S EY1 T AH0 Z +PESH P EH1 SH +PESHAWAR P EH1 SH AH0 W AO0 R +PESHEK P EH1 SH EH0 K +PESINA P EH0 S IY1 N AH0 +PESKIN P EH1 S K IH0 N +PESKY P EH1 S K IY0 +PESNELL P IH0 S N EH1 L +PESO P EY1 S OW0 +PESO'S P EY1 S OW0 Z +PESOLA P EH0 S OW1 L AH0 +PESOS P EY1 S OW0 Z +PESSIMISM P EH1 S AH0 M 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S K AH0 +PETRUZZELLI P EH0 T R UW0 T S EH1 L IY0 +PETRUZZI P EH0 T R UW1 T S IY0 +PETRY P EH1 T R IY0 +PETS P EH1 T S +PETSCH P EH1 CH +PETSCHE P EH1 CH +PETSMART P EH1 T S M AA2 R T +PETSTUFF P EH1 T S T AH2 F +PETT P EH1 T +PETTA P EH1 T AA0 +PETTAWAY P EH1 T AH0 W EY2 +PETTED P EH1 T IH0 D +PETTEE P EH1 T IY1 +PETTENGILL P EH1 T IH0 NG G AH0 L +PETTER P EH1 T ER0 +PETTERSEN P EH1 T ER0 S AH0 N +PETTERSON P EH1 T ER0 S AH0 N +PETTERSSON P IY1 T ER0 S AH0 N +PETTERSSON(1) P EH1 T ER0 S AH0 N +PETTET P EH1 T IH0 T +PETTEWAY P EH1 T W EY0 +PETTEY P EH1 T IY0 +PETTEYS P EH1 T IY0 Z +PETTI P EH1 T IY0 +PETTICOAT P EH1 T IY0 K OW2 T +PETTICOATS P EH1 T IY0 K OW2 T S +PETTIE P EH1 T IY0 +PETTIES P EH1 T IY0 Z +PETTIGREW P EH1 T IH0 G R UW2 +PETTIJOHN P EH1 T IH0 JH AA0 N +PETTINATO P EH0 T IY0 N AA1 T OW0 +PETTINE P EH0 T IY1 N IY0 +PETTINESS P EH1 T IY0 N EH2 S +PETTING P EH1 T IH0 NG +PETTINGER P EH1 T IH0 NG ER0 +PETTINGILL P IH0 T IH1 NG G AH0 L +PETTIS P EH1 T IH2 S +PETTIT P EH1 T IH2 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AA1 S T +PFUND F AH1 N D +PFUNDSTEIN F AH1 N D S T IY2 N +PFUNDSTEIN(1) F AH1 N D S T AY2 N +PGM P IY1 JH IY1 EH1 M +PH P IY1 EY1 CH +PH.D. P IY1 EY2 CH D IY1 +PHAGAN F EY1 G AH0 N +PHAGE F EY1 JH +PHAGOCYTE F AE1 G AH0 S AY2 T +PHAGOCYTES F AE1 G AH0 S AY2 T S +PHAIR F EH1 R +PHALANGE F AH0 L AE1 N JH +PHALANGE(1) F AH0 L EY1 N JH +PHALANGES F AH0 L AE1 N JH IY0 Z +PHALANGES(1) F AH0 L EY1 N JH IH0 Z +PHALANX F EY1 L AE0 NG K S +PHALEN F AE1 L AH0 N +PHALLIC F AE1 L IH0 K +PHAM F AE1 M +PHAN F AE1 N +PHANEUF F AE1 N UW0 F +PHANTASM F AE2 N T AE1 Z AH0 M +PHANTASMAGORIA F AE0 N T AE2 Z M AH0 G AO1 R IY0 AH0 +PHANTOM F AE1 N T AH0 M +PHANTOM(1) F AE1 N AH0 M +PHANTOMS F AE1 N T AH0 M Z +PHANTOMS(1) F AE1 N AH0 M Z +PHAR F AA1 R +PHARAOH F EH1 R OW0 +PHARAOH(1) F EY1 R OW0 +PHARAOHS F EH1 R OW0 Z +PHARAOHS(1) F EY1 R OW0 Z +PHARAON F EH1 R OW0 N +PHARAONIC F EH2 R AH0 AA1 N IH0 K +PHARES F EH1 R Z +PHARIS F AE1 R AH0 S +PHARISAISM F AA1 R IH0 S EY2 IH2 Z AH0 M +PHARISEE F AA1 R IH0 S IY2 +PHARISEES F AA1 R IH0 S IY2 Z +PHARISS F ER0 IH1 S +PHARMA F AA1 R M AH0 +PHARMACEUTICAL F AA2 R M AH0 S UW1 T IH0 K AH0 L 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K +PHILBROOK F IH1 L B R UH2 K +PHILBY F IH1 L B IY0 +PHILEAS F AH0 L EY1 AH0 S +PHILEMON F AH0 L EY1 M AH0 N +PHILENE F IH0 L IY1 N +PHILEO F IH1 L IY0 OW0 +PHILHARMONIA F IH2 L HH AA0 R M OW1 N IY0 AH0 +PHILHARMONIC F IH2 L HH AA2 R M AA1 N IH0 K +PHILHARMONIC'S F IH2 L HH AA0 R M AA1 N IH0 K S +PHILHOWER F IH1 L AW0 ER0 +PHILIBERT F IH1 L IH0 B ER0 T +PHILIBOSIAN F IH2 L IH0 B OW1 Z IY0 AH0 N +PHILIDA F AH0 L IY1 D AH0 +PHILINA F AH0 L IY1 N AH0 +PHILIP F IH1 L AH0 P +PHILIP(1) F IH1 L IH0 P +PHILIP'S F IH1 L AH0 P S +PHILIP'S(1) F IH1 L IH0 P S +PHILIPP F IH1 L IH0 P +PHILIPPA F IH0 L IH1 P AH0 +PHILIPPE F IH0 L IY1 P EY0 +PHILIPPI F IH0 L IH1 P IY0 +PHILIPPIC F IH0 L IH1 P IH0 K +PHILIPPINE F IH1 L AH0 P IY2 N +PHILIPPINES F IH1 L AH0 P IY2 N Z +PHILIPPINES' F IH1 L AH0 P IY2 N Z +PHILIPPINO F IH2 L AH0 P IY1 N OW0 +PHILIPPOUSSIS F IH2 L AH0 P UW1 S AH0 S +PHILIPPS F IH1 L IH0 P S +PHILIPS F IH1 L AH0 P S +PHILIPS(1) F IH1 L IH0 P S +PHILIPS' F IH1 L IH0 P S +PHILIPS'S F IH1 L IH0 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+PINQUATER P IH1 N K W AA2 T ER0 +PINS P IH1 N Z +PINSHAN P IH1 N SH AH0 N +PINSKER P IH1 N S K ER0 +PINSKY P IH1 N S K IY0 +PINSON P IH1 N S AH0 N +PINSONEAULT P IH1 N S AH0 N AO2 L T +PINSONEAULT(1) P IH2 N S AH0 N OW1 +PINSTRIPE P IH1 N S T R AY2 P +PINSTRIPED P IH1 N S T R AY2 P T +PINSTRIPES P IH1 N S T R AY2 P S +PINT P AY1 N T +PINT-SIZE P AY1 N T S AY1 Z +PINT-SIZED P AY1 N T S AY1 Z D +PINTA P IH1 N T AH0 +PINTAR P IY0 N T AA1 R +PINTER P AY1 N T ER0 +PINTO P IH1 N T OW2 +PINTS P AY1 N T S +PINY P AY1 N IY0 +PINYAN P IH1 N Y AH0 N +PINZON P IH2 N Z AO1 N +PIO P AY1 OW0 +PION P AY1 AA2 N +PIONEER P AY2 AH0 N IH1 R +PIONEER'S P AY2 AH0 N IH1 R Z +PIONEERED P AY2 AH0 N IH1 R D +PIONEERING P AY2 AH0 N IH1 R IH0 NG +PIONEERS P AY2 AH0 N IH1 R Z +PIONTEK P IY0 OW1 N T EH0 K +PIONTKOWSKI P IY0 OW0 N T K AO1 F S K IY0 +PIORKOWSKI P IY0 AO0 R K AO1 F S K IY0 +PIOTROWSKI P IY0 OW0 T R AO1 F S K IY0 +PIOTTER P IY0 AA1 T ER0 +PIOUS P AY1 AH0 S +PIOUSLY P AY1 AH0 S L IY0 +PIP P IH1 P +PIPE P AY1 P +PIPED P AY1 P T +PIPEFISH P AY1 P F IH2 SH +PIPEFISHES P AY1 P F IH2 SH IH0 Z +PIPELINE P AY1 P L AY2 N +PIPELINE'S P AY1 P L AY2 N Z +PIPELINES P AY1 P L AY2 N Z +PIPELINES' P AY1 P L AY2 N Z +PIPER P AY1 P ER0 +PIPERS P AY1 P ER0 Z +PIPES P AY1 P S +PIPETEC P AY1 P T EH2 K +PIPETTE P AY2 P EH1 T +PIPETTER P AY2 P EH1 T ER0 +PIPETTERS P AY2 P EH1 T ER0 Z +PIPETTES P AY2 P EH1 T S +PIPHER P IH1 F ER0 +PIPING P AY1 P IH0 NG +PIPITONE P IH1 P IH0 T OW2 N +PIPKIN P IH1 P K IH0 N +PIPKINS P IH1 P K IH0 N Z +PIPP P IH1 P +PIPPEN P IH1 P AH0 N +PIPPEN'S P IH1 P AH0 N Z +PIPPENGER P IH1 P IH0 N JH ER0 +PIPPERT P IH1 P ER0 T +PIPPIN P IH1 P IH0 N +PIPPINS P IH1 P IH0 N Z +PIPS P IH1 P S +PIQUANT P IY1 K AH0 N T +PIQUE P IY1 K +PIQUED P IY1 K T +PIQUETTE P IH0 K EH1 T +PIRACY P AY1 R AH0 S IY0 +PIRAEUS P AH0 R EY1 AH0 S +PIRAINO P IH0 R EY1 N OW0 +PIRANDELLO P IH2 R AH0 N D EH1 L OW0 +PIRANHA P IH0 R AE1 N HH AH0 +PIRATE P AY1 R AH0 T +PIRATE'S P AY1 R AH0 T S +PIRATED P AY1 R AH0 T IH0 D +PIRATES P AY1 R AH0 T S +PIRATING P AY1 R AH0 T IH0 NG +PIRELLI P IH0 R EH1 L IY0 +PIRELLI'S P IH0 R EH1 L IY0 Z +PIRES P AY1 R Z +PIRESTANI P IH2 R EH0 S T AA1 N IY0 +PIRIE P IH1 R IY0 +PIRKEY P ER1 K IY0 +PIRKL P ER1 K AH0 L +PIRKLE P ER1 K AH0 L +PIRKO P ER1 K OW0 +PIRO P IH1 R OW0 +PIROG P ER0 AA1 G +PIRONE P IH0 R OW1 N +PIROUETTE P IH2 R UW0 EH1 +PIROUETTES P IH2 R UW0 EH1 T S +PIROZZI P IH0 R AA1 Z IY0 +PIRRELLO P IH0 R EH1 L OW0 +PIRRO P IH1 R OW0 +PIRRONE P IH0 R OW1 N IY0 +PIRTLE P ER1 T AH0 L +PISA P IY1 S AH0 +PISANI P IY0 S AA1 N IY0 +PISANO P IY0 S AA1 N OW0 +PISAREK P IH1 S ER0 EH0 K +PISARSKI P IH0 S AA1 R S K IY0 +PISCA P IH1 S K AH0 +PISCATAWAY P IH0 S K AE1 T AH0 W EY2 +PISCES P AY1 S IY0 Z +PISCHEL P IH1 SH AH0 L +PISCHKE P IH1 SH K +PISCIOTTA P IY0 S CH OW1 T AH0 +PISCITELLI P IY0 S CH IY0 T EH1 L IY0 +PISCITELLO P IH2 S IH0 T EH1 L OW0 +PISCOPO P IY0 S K OW1 P OW0 +PISELLO P IH0 S EH1 L OW0 +PISONI P IH0 S OW1 N IY0 +PISS P IH1 S +PISS-POOR P IH1 S P UW2 R 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AH0 +PLEX P L EH1 K S +PLEXIGLAS P L EH1 K S IH0 G L AE2 S +PLEXIGLAS(1) P L EH1 K S IY0 G L AE2 S +PLEXIGLASS P L EH1 K S IH0 G L AE2 S +PLEXIGLASS(1) P L EH1 K S IY0 G L AE2 S +PLEXUS P L EH1 K S AH0 S +PLIABLE P L AY1 AH0 B AH0 L +PLIANT P L AY1 AH0 N T +PLICHTA P L IH1 CH T AH0 +PLIED P L AY1 D +PLIER P L AY1 ER0 +PLIERS P L AY1 ER0 Z +PLIES P L AY1 Z +PLIGHT P L AY1 T +PLILER P L AY1 L ER0 +PLIMPTON P L IH1 M P T AH0 N +PLINIUS P L IH1 N IY0 AH0 S +PLINK P L IH1 NG K +PLINKING P L IH1 NG K IH0 NG +PLINTH P L IH1 N TH +PLINY P L IH1 N IY0 +PLIOCENE P L AY1 AH0 S IY2 N +PLISETSKAYA P L IH2 S AH0 T S K AY1 AH0 +PLISKA P L IH1 S K AH0 +PLITT P L IH1 T +PLOCAR P L OW1 K AA0 R +PLOCEK P L OW1 CH EH2 K +PLOCH P L AA1 K +PLOCHER P L AA1 K ER0 +PLOCK P L AA1 K +PLOD P L AA1 D +PLODDED P L AA1 D IH0 D +PLODDING P L AA1 D IH0 NG +PLOEGER P L OW1 G ER0 +PLOETZ P L OW1 T S +PLOG P L AA1 G +PLOHN P L OW1 N +PLONKA P L OW1 NG K AH0 +PLONSKI P L AA1 N S K IY0 +PLOOF P L UW1 F +PLOP P L AA1 P 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AH0 S IY0 HH OW2 L D ER0 Z +POLICYMAKER P AA1 L AH0 S IY0 M EY2 K ER0 +POLICYMAKERS P AA1 L AH0 S IY0 M EY2 K ER0 Z +POLICYMAKING P AA1 L AH0 S IY0 M EY2 K IH0 NG +POLIDORI P OW0 L IY0 D AO1 R IY0 +POLIDORO P OW0 L IY0 D AO1 R OW0 +POLIFRONI P AA0 L AH0 F R OW1 N IY0 +POLIMENI P OW0 L IY0 M EH1 N IY0 +POLIN P OW1 L IH0 N +POLING P OW1 L IH0 NG +POLINO P OW0 L IY1 N OW0 +POLINSKI P AH0 L IH1 N S K IY0 +POLINSKY P AH0 L IH1 N S K IY0 +POLIO P OW1 L IY0 OW2 +POLIQUIN P OW0 L IY0 K W IY1 N +POLIS P OW1 L AH0 S +POLIS(1) P OW1 L AY0 Z +POLISARIO P OW2 L IH0 S EH1 R IY0 OW0 +POLISH P AA1 L IH0 SH +POLISH(1) P OW1 L IH0 SH +POLISHED P AA1 L IH0 SH T +POLISHING P AA1 L IH0 SH IH0 NG +POLITANO P OW0 L IY0 T AA1 N OW0 +POLITBURO P AA1 L AH0 T B Y UH2 R OW0 +POLITBURO'S P AA1 L AH0 T B Y UH2 R OW0 Z +POLITE P AH0 L AY1 T +POLITELY P AH0 L AY1 T L IY0 +POLITENESS P AH0 L AY1 T N AH0 S +POLITES P AH0 L AY1 T S +POLITI P OW0 L IY1 T IY0 +POLITIC P AA1 L AH0 T IH2 K +POLITICAL P AH0 L IH1 T AH0 K AH0 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AH0 S K R IH1 P SH AH0 N Z +PRESEASON P R IY2 S IY1 Z AH0 N +PRESENCE P R EH1 Z AH0 N S +PRESENCES P R EH1 Z AH0 N S IH0 Z +PRESENT P R EH1 Z AH0 N T +PRESENT(1) P R IY0 Z EH1 N T +PRESENT(2) P ER0 Z EH1 N T +PRESENTABLE P R AH0 Z EH1 N T AH0 B AH0 L +PRESENTATION P R EH2 Z AH0 N T EY1 SH AH0 N +PRESENTATIONS P R EH2 Z AH0 N T EY1 SH AH0 N Z +PRESENTED P R IY0 Z EH1 N T IH0 D +PRESENTER P R EH1 Z AH0 N T ER0 +PRESENTER(1) P R IY0 Z EH1 N T ER0 +PRESENTERS P R EH1 Z AH0 N T ER0 Z +PRESENTERS(1) P R IY0 Z EH1 N T ER0 Z +PRESENTING P R IH0 Z EH1 N T IH0 NG +PRESENTING(1) P R IY0 Z EH1 N T IH0 NG +PRESENTLY P R EH1 Z AH0 N T L IY0 +PRESENTMENT P R IY0 Z EH1 N T M AH0 N T +PRESENTS P R EH1 Z AH0 N T S +PRESENTS(1) P R IY0 Z EH1 N T S +PRESERVATION P R EH2 Z ER0 V EY1 SH AH0 N +PRESERVATIONIST P R EH2 Z ER0 V EY1 SH AH0 N IH0 S T +PRESERVATIONISTS P R EH2 Z ER0 V EY1 SH AH0 N IH0 S T S +PRESERVATIVE P R IY0 Z ER1 V AH0 T IH0 V +PRESERVATIVES P R AH0 Z ER1 V AH0 T IH0 V Z +PRESERVE P R AH0 Z 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OW2 T AH0 Z OW1 AH0 +PROTOZOAN P R OW2 T AH0 Z OW1 AH0 N +PROTOZOANS P R OW2 T AH0 Z OW1 AH0 N Z +PROTRACT P R OW0 T R AE1 K T +PROTRACT(1) P R OW1 T R AE0 K T +PROTRACTED P R OW0 T R AE1 K T IH0 D +PROTROPIN P R AA1 T R AH0 P IH0 N +PROTROPIN(1) P R OW0 T R OW1 P IH0 N +PROTRUDE P R OW0 T R UW1 D +PROTRUDING P R OW0 T R UW1 D IH0 NG +PROTUBERANCE P R OW0 T UW1 B ER0 AH0 N S +PROTUBERANCE(1) P R AH0 T UW1 B ER0 AH0 N S +PROTUBERANCES P R OW0 T UW1 B ER0 AH0 N S AH0 Z +PROTUBERANCES(1) P R AH0 T UW1 B ER0 AH0 N S AH0 Z +PROTZ P R AA1 T S +PROTZMAN P R AA1 T S M AH0 N +PROUD P R AW1 D +PROUDER P R AW1 D ER0 +PROUDEST P R AW1 D AH0 S T +PROUDFIT P R AW1 D F IH2 T +PROUDFOOT P R AW1 D F UH2 T +PROUDFOOT'S P R AW1 D F UH2 T S +PROUDLY P R AW1 D L IY0 +PROUGH P R AW1 +PROULX P R AW1 L K S +PROUSE P R AW1 S +PROUST P R AW1 S T +PROUST(1) P R UW1 S T +PROUT P R AW1 T +PROUTY P R AW1 T IY0 +PROVABLE P R UW1 V AH0 B AH0 L +PROVANCE P R OW1 V AH0 N S +PROVANT P R OW1 V AH0 N T +PROVE P R UW1 V 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IH1 K +QUICKEL K W IH1 K AH0 L +QUICKEN K W IH1 K AH0 N +QUICKENED K W IH1 K AH0 N D +QUICKENING K W IH1 K AH0 N IH0 NG +QUICKENS K W IH1 K AH0 N Z +QUICKER K W IH1 K ER0 +QUICKEST K W IH1 K IH0 S T +QUICKIE K W IH1 K IY0 +QUICKLY K W IH1 K L IY0 +QUICKNESS K W IH1 K N AH0 S +QUICKSAND K W IH1 K S AE2 N D +QUICKSANDS K W IH1 K S AE2 N D Z +QUICKSILVER K W IH1 K S IH1 L V ER0 +QUICKTIME K W IH1 K T AY2 M +QUID K W IH1 D +QUIESCENT K W AY0 EH1 S AH0 N T +QUIET K W AY1 AH0 T +QUIETED K W AY1 AH0 T IH0 D +QUIETER K W AY1 AH0 T ER0 +QUIETEST K W AY1 AH0 T AH0 S T +QUIETING K W AY1 AH0 T IH0 NG +QUIETIST K W AY1 AH0 T AH0 S T +QUIETLY K W AY1 AH0 T L IY0 +QUIETNESS K W AY1 AH0 T N AH0 S +QUIETS K W AY1 AH0 T S +QUIETT K W IY1 T +QUIEVONI K W IH0 V AO1 N IY0 +QUIGG K W IH1 G +QUIGGLE K W IH1 G AH0 L +QUIGLEY K W IH1 G L IY0 +QUIJADA K W IY0 Y AA1 D AH0 +QUIJANO K W IY0 Y AA1 N OW0 +QUIK K W IH1 K +QUIKSILVER K W IH1 K S IH1 L V ER0 +QUILALI K W IH0 L AA1 L IY0 +QUILES K W IY1 L EH0 S +QUILICI 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AA1 R +R.'S AA1 R Z +R.S AA1 R Z +RA R AA1 +RAAB R AA1 B +RAAB'S R AA1 B Z +RAABE R AA1 B +RAAD R AA1 D +RAAP R AA1 P +RAASCH R AA1 SH +RAATZ R AA1 T S +RAB R AE1 B +RABAGO R AA0 B AA1 G OW0 +RABALAIS R AE1 B AH0 L EY2 +RABB R AE1 B +RABBANI R AH0 B AE1 N IY0 +RABBANI(1) R AH0 B AA1 N IY0 +RABBI R AE1 B AY2 +RABBINIC R AH0 B IH1 N IH0 K +RABBINICAL R AH0 B IH1 N IH0 K AH0 L +RABBIS R AE1 B AY2 Z +RABBIT R AE1 B AH0 T +RABBIT(1) R AE1 B IH0 T +RABBITEARS R AE1 B IH0 T IY1 R Z +RABBITLIKE R AE1 B AH0 T L AY2 K +RABBITS R AE1 B AH0 T S +RABBITT R AE1 B IH0 T +RABBLE R AE1 B AH0 L +RABE R EY1 B +RABEL R AE1 B AH0 L +RABEN R AE1 B AH0 N +RABENOLD R AE1 B IH0 N OW2 L D +RABER R EY1 B ER0 +RABES R EY1 B IY0 Z +RABEY R EY1 B IY0 +RABI R AA1 B IY0 +RABID R AE1 B IH0 D +RABID(1) R EY1 B IH0 D +RABIDEAU R AE1 B IH0 D OW2 +RABIES R EY1 B IY0 Z +RABIN R AA2 B IY1 N +RABIN'S R AA2 B IY1 N Z +RABINE R AH0 B IY1 N +RABINER R AH0 B IY1 N ER0 +RABINOVICH R AH0 B IH1 N AH0 V IH0 CH +RABINOVITZ R AH0 B 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+RAFFISH R AE1 F IH0 SH +RAFFLE R AE1 F AH0 L +RAFFLES R AE1 F AH0 L Z +RAFFO R AE1 F OW0 +RAFI R AE1 F IY0 +RAFI(1) R AA1 F IY0 +RAFIK R AE1 F IH0 K +RAFSANJANI R AE2 F S AH0 N JH AA1 N IY0 +RAFT R AE1 F T +RAFTED R AE1 F T IH0 D +RAFTER R AE1 F T ER0 +RAFTERS R AE1 F T ER0 Z +RAFTERY R AE1 F T ER0 IY0 +RAFTING R AE1 F T IH0 NG +RAFTS R AE1 F T S +RAFUSE R AA0 F UW1 S IY0 +RAG R AE1 G +RAGAIN R AE1 G AH0 N +RAGAN R EY1 G AH0 N +RAGAS R AA1 G AH0 Z +RAGAVAN R AA1 G AH0 V AA2 N +RAGAVAN'S R AA1 G AH0 V AA2 N Z +RAGE R EY1 JH +RAGED R EY1 JH D +RAGEL R EY1 G AH0 L +RAGEN R AE1 G AH0 N +RAGER R EY1 G ER0 +RAGES R EY1 JH IH0 Z +RAGGED R AE1 G AH0 D +RAGGEDY R AE1 G AH0 D IY0 +RAGGIO R AA1 JH IY0 OW0 +RAGHIDA R AH0 G IY1 D AH0 +RAGIN R AE1 JH IH0 N +RAGING R EY1 JH IH0 NG +RAGLAND R AE1 G L AH0 N D +RAGLE R EY1 G AH0 L +RAGLIN R AE1 G L IH0 N +RAGMEN R AE1 G M AH0 N +RAGO R AA1 G OW0 +RAGON R AA0 G AO1 N +RAGONA R AA0 G OW1 N AH0 +RAGONE R AA0 G OW1 N IY0 +RAGONESE R AA0 G OW0 N EY1 Z IY0 +RAGS R AE1 G Z +RAGSDALE R AE1 G Z D EY2 L +RAGTAG R AE1 G T AE2 G +RAGTIME R AE1 G T AY2 M +RAGTOP R AE1 G T AO0 P +RAGU R AE0 G UW1 +RAGUCCI R AA0 G UW1 CH IY0 +RAGUE R EY1 G +RAGUE(1) R AE1 G +RAGUNATHAN R AA0 G UW1 N AH0 TH AA0 N +RAGUSA R AA0 G UW1 S AH0 +RAGWEED R AE1 G W IY2 D +RAH R AA1 +RAHAL R AH0 HH AA1 L +RAHE R EY1 HH IY0 +RAHEEM R AH0 HH IY1 M +RAHILL R AA1 HH IH0 L +RAHILLY R AE1 HH AH0 L IY0 +RAHIM R AH0 HH IY1 M +RAHL R AA1 L +RAHM R AE1 M +RAHM(1) R AA1 M +RAHMAN R AA1 M AH0 N +RAHMAN'S R AA1 M AH0 N Z +RAHMING R AA1 M IH0 NG +RAHN R AE1 N +RAHRIG R AE1 R IH0 G +RAHUL R AH0 HH UW1 L +RAHWAY R AA1 W EY2 +RAI R AA1 IY0 +RAIA R AA1 Y AH0 +RAIBLE R EY1 B AH0 L +RAICHE R EY1 CH +RAID R EY1 D +RAIDED R EY1 D IH0 D +RAIDER R EY1 D ER0 +RAIDER'S R EY1 D ER0 Z +RAIDERS R EY1 D ER0 Z +RAIDERS' R EY1 D ER0 Z +RAIDING R EY1 D IH0 NG +RAIDS R EY1 D Z +RAIFF R EY1 F +RAIFORD R EY1 F ER0 D +RAIKES R EY1 K S +RAIKO R EY1 K OW0 +RAIL R EY1 L +RAIL'S R EY1 L Z +RAILBIKE R EY1 L B AY2 K +RAILBIKER R EY1 L B AY0 K ER0 +RAILBIKERS R EY1 L B IH0 K ER0 Z +RAILCAR R EY1 L K AA2 R +RAILCARS R EY1 L K AA2 R Z +RAILE R EY1 L +RAILED R EY1 L D +RAILEY R EY1 L IY0 +RAILING R EY1 L IH0 NG +RAILINGS R EY1 L IH0 NG Z +RAILROAD R EY1 L R OW2 D +RAILROAD'S R EY1 L R OW2 D Z +RAILROADED R EY1 L R OW2 D IH0 D +RAILROADING R EY1 L R OW2 D IH0 NG +RAILROADS R EY1 L R OW2 D Z +RAILROADS' R EY1 L R OW2 D Z +RAILS R EY1 L Z +RAILSBACK R EY1 L Z B AE2 K +RAILTEX R EY1 L T EH2 K S +RAILWAY R EY1 L W EY2 +RAILWAY'S R EY1 L W EY2 Z +RAILWAYS R EY1 L W EY2 Z +RAIMER R EY1 M ER0 +RAIMO R EY1 M OW0 +RAIMOND R EY1 M AH0 N D +RAIMONDI R AH0 M OW1 N D IY0 +RAIMONDO R EY2 M AA1 N D OW0 +RAIN R EY1 N +RAINA R EY1 N AH0 +RAINBOLT R EY1 N B OW2 L T +RAINBOW R EY1 N B OW2 +RAINBOWS R EY1 N B OW2 Z +RAINCOAT R EY1 N K OW2 T +RAINCOAT'S R EY1 N K OW2 T S +RAINCOATS R EY1 N K OW2 T S +RAINDANCER R EY1 N D AE2 N S ER0 +RAINDROP R EY1 N D R AA2 P +RAINDROPS R EY1 N D R AA2 P S +RAINE R EY1 N +RAINED R EY1 N D +RAINER R EY1 N ER0 +RAINERI R AH0 N EH1 R IY0 +RAINES R EY1 N Z +RAINEY R EY1 N IY0 +RAINFALL R EY1 N F AO2 L +RAINFALLS R EY1 N F AO2 L Z +RAINFORD R AY1 N F ER0 D +RAINFOREST R AY1 N F AO2 R AH0 S T +RAINFORESTS R AY1 N F AO2 R AH0 S T S +RAINGER R AA1 IH0 NG ER0 +RAINIE R EY1 N IY0 +RAINIER R EY0 N IH1 R +RAINIEST R EY1 N IY0 AH0 S T +RAINING R EY1 N IH0 NG +RAINLEY R EY1 N L IY0 +RAINLEY'S R EY1 N L IY0 Z +RAINMAKER R EY1 N M EY2 K ER0 +RAINMAN R EY1 N M AH0 N +RAINONE R EY1 N OW2 N +RAINS R EY1 N Z +RAINSTORM R EY1 N S T AO2 R M +RAINSTORMS R EY1 N S T AO2 R M Z +RAINVILLE R EY1 N V IH2 L +RAINWATER R EY1 N W AO2 T ER0 +RAINY R EY1 N IY0 +RAIS R EY1 S +RAISA R EY1 S AH0 +RAISA(1) R AA2 IY1 S AH0 +RAISANEN R AY1 S AH0 N AH0 N +RAISBECK R EY1 Z B EH2 K +RAISCH R AY1 SH +RAISE R EY1 Z +RAISED R EY1 Z D +RAISER R EY1 Z ER0 +RAISERS R EY1 Z ER0 Z +RAISES R EY1 Z AH0 Z +RAISES(1) R EY1 Z IH0 Z +RAISIN R EY1 Z IH0 N +RAISING R EY1 Z IH0 NG +RAISINS R EY1 Z AH0 N Z +RAISINS(1) R EY1 Z IH0 N Z +RAISLER R EY1 Z L ER0 +RAISON R EY1 S AA0 N +RAISOR R EY1 Z ER0 +RAISSA R EY1 S AH0 +RAIT R EY1 T +RAITH R EY1 TH +RAITHEL R EY1 TH AH0 L +RAITT R EY1 T +RAJ R AA1 ZH +RAJ(1) R AA1 JH +RAJALA R AA0 Y AA1 L AH0 +RAJALA(1) R AA0 JH AA1 L AH0 +RAJARATNAM R AA0 JH ER0 AA1 T N AA0 M +RAJEWSKI R AY0 EH1 F S K IY0 +RAJIV R AA0 JH IY1 V +RAJIV(1) R AA0 ZH IY1 V +RAJKO R AA1 ZH K OW0 +RAJKUMAR R AA1 ZH K UW0 M AA1 R +RAJNEESH R AA0 JH N IY1 SH +RAJU R AA1 Y UW0 +RAK R AE1 K +RAKE R EY1 K +RAKED R EY1 K T +RAKER R EY1 K ER0 +RAKERS R EY1 K ER0 Z +RAKES R EY1 K S +RAKESTRAW R EY1 K S T R AO2 +RAKICH R AE1 K IH0 CH +RAKING R EY1 K IH0 NG +RAKISH R EY1 K IH0 SH +RAKIYA R AH0 K IY1 AH0 +RAKOCY R AH0 K OW1 CH IY0 +RAKOCZY R AH0 K OW1 CH IY0 +RAKOFF R AE1 K AO2 F +RAKOLTA R AH0 K AA1 L T AH0 +RAKOVICA R AH0 K OW1 V IH0 K AH0 +RAKOW R AE1 K AW0 +RAKOWSKI R AH0 K AW1 S K IY0 +RALEIGH R AO1 L IY0 +RALEIGH'S R AO1 L IY0 Z +RALES R EY1 L Z +RALES' R EY1 L Z +RALES'S R EY1 L Z IH0 Z +RALESES R AH0 L IY1 S IH0 Z +RALEY R AE1 L IY0 +RALF R AA1 L F +RALL R AO1 L +RALLIED R AE1 L IY0 D +RALLIES R AE1 L IY0 Z +RALLIS R AE1 L IH0 S +RALLO R AE1 L OW0 +RALLS R AO1 L Z +RALLY R AE1 L IY0 +RALLY'S R AE1 L IY0 Z +RALLYING R AE1 L IY0 IH0 NG +RALPH R AE1 L F +RALPH'S R AE1 L F S +RALPHS R AE1 L F S +RALSTON R AO1 L S T AH0 N +RALSTON'S R AA1 L S T AH0 N Z +RAM R AE1 M +RAMA R AA1 M AH0 +RAMADA R AH0 M AA1 D AH0 +RAMADA'S R AH0 M AA1 D AH0 Z +RAMADAN R AE1 M AH0 D AH0 N +RAMADAN(1) R AA1 M AH0 D AA2 N +RAMAGE R AE1 M IH0 JH +RAMAKER R AA1 M EY0 K ER0 +RAMALA R AH0 M AA1 L AH0 +RAMALLAH R AH0 M AE1 L AH0 +RAMALLAH(1) R AH0 M AA1 L AH0 +RAMAN R EY1 M AH0 N +RAMAN(1) R AA1 M AH0 N +RAMAPHOSA R AE2 M AH0 F OW1 S AH0 +RAMASWAMI R AA2 M AH0 S W AA1 M IY0 +RAMAT R AE1 M AE0 T +RAMAT(1) R AA1 M AH0 T +RAMBEAU R AH0 M B OW1 +RAMBEAU(1) R AE1 M B OW2 +RAMBERG R AE1 M B ER0 G +RAMBERT R AE1 M B ER0 T +RAMBIN R AE1 M B IH0 N +RAMBLE R AE1 M B AH0 L +RAMBLED R AE1 M B AH0 L D +RAMBLER R AE1 M B L ER0 +RAMBLERS R AE1 M B L ER0 Z +RAMBLING R AE1 M B L IH0 NG +RAMBLING(1) R AE1 M B AH0 L IH0 NG +RAMBO R AE1 M B OW0 +RAMBOW R AE1 M B OW0 +RAMBUNCTIOUS R AE0 M B AH1 NG K SH AH0 S +RAMEL R AE1 M AH0 L +RAMELLA R AH0 M EH1 L AH0 +RAMER R EY1 M ER0 +RAMERIZ R AA0 M EH1 R IY0 Z +RAMESES R AE1 M AH0 S IY2 Z +RAMESH R AA1 M EH2 SH +RAMESSES R AE1 M AH0 S IH0 Z +RAMESSES(1) R AE1 M S IY2 Z +RAMEY R AE1 M IY0 +RAMI R AA1 M IY0 +RAMIFICATION R AE2 M AH0 F AH0 K EY1 SH AH0 N +RAMIFICATIONS R AE2 M AH0 F AH0 K EY1 SH AH0 N Z +RAMIFY R AE1 M AH0 F AY2 +RAMIRES R AA0 M IH1 R EH0 S +RAMIREZ R AH0 M IH1 R EH0 Z +RAMIRO R AH0 M IH1 R OW0 +RAMLAWI R AE2 M L AW1 IY0 +RAMLER R AE1 M L ER0 +RAMLOW R AE1 M L OW2 +RAMM R AE1 M +RAMMED R AE1 M D +RAMMEL R AE1 M AH0 L +RAMMER R AE1 M ER0 +RAMMING R AE1 M IH0 NG +RAMO R EY1 M OW0 +RAMON R AH0 M OW1 N +RAMONA R AH0 M OW1 N AH0 +RAMONDA R AH0 M AA1 N D AH0 +RAMONE R AH0 M OW1 N +RAMOS R AA1 M OW0 S +RAMOS(1) R EY1 M OW0 S +RAMP R AE1 M P +RAMPAGE R AE1 M P EY2 JH +RAMPAGED R AE0 M P EY1 JH D +RAMPAGED(1) R AE1 M P EY2 JH D +RAMPAGER R AE1 M P EY2 JH ER0 +RAMPAGES R AE1 M P EY2 JH IH0 Z +RAMPAGING R AE1 M P EY2 JH IH0 NG +RAMPAGING(1) R AE1 M P AH0 JH IH0 NG +RAMPANT R AE1 M P AH0 N T +RAMPART R AE1 M P AA2 R T +RAMPARTS R AE1 M P AA2 R T S +RAMPELL R AE0 M P EH1 L +RAMPEY R AE1 M P IY0 +RAMPING R AE1 M P IH0 NG +RAMPLEY R AE1 M P L IY0 +RAMPS R AE1 M P S +RAMPY R AE1 M P IY0 +RAMQVIST R AE1 M K V IH2 S T +RAMQVIST(1) R AE1 M K W IH2 S T +RAMROD R AE1 M R AA2 D +RAMS R AE1 M Z +RAMSAY R AE1 M Z IY0 +RAMSAY(1) R AE1 M S EY2 +RAMSBURG R AE1 M S B ER0 G +RAMSDELL R AE1 M S D AH0 L +RAMSDEN R AE1 M S D AH0 N +RAMSER R AE1 M Z ER0 +RAMSES R AE1 M S IY2 Z +RAMSEUR R AH0 M S ER1 +RAMSEY R AE1 M Z IY0 +RAMSEY'S R AE1 M Z IY0 Z +RAMSEYER R AE1 M Z IY0 ER0 +RAMSEYS R AE1 M Z IY0 Z +RAMSEYS(1) R AE1 M S IY0 Z +RAMSHACKLE R AE1 M SH AE2 K AH0 L +RAMSTAD R AE1 M S T AH0 D +RAMSTEIN R AE1 M S T AY2 N +RAMSTEIN(1) R AE1 M S T IY2 N +RAMTANE R AE1 M T EY0 N +RAMTEK R AE1 M T EH2 K +RAMTHA R AE1 M TH AH0 +RAMTHUN R AE1 M TH AH0 N +RAMU R AA2 M UW1 +RAMUNE R AE1 M Y UW2 N +RAMUS R EY1 M AH0 S +RAMZI R AE1 M Z IY0 +RAN R AE1 N +RANA R AE1 N AH0 +RANALLI R AH0 N AE1 L IY0 +RANALLO R AH0 N AE1 L OW0 +RANCE R AE1 N S +RANCE'S R AE1 N S IH0 Z +RANCH R AE1 N CH +RANCH'S R AE1 N CH IH0 Z +RANCHER R AE1 N CH ER0 +RANCHERA R AA0 N CH EH1 R AH0 +RANCHERO R AA0 N CH EH1 R OW0 +RANCHERO(1) R AE0 N CH EH1 R OW0 +RANCHERS R AE1 N CH ER0 Z +RANCHES R AE1 N CH AH0 Z +RANCHING R AE1 N CH IH0 NG +RANCHLAND R AE1 N CH L AH0 N D +RANCHO R AE1 N CH OW0 +RANCID R AE1 N S IH0 D +RANCIDITY R AE0 N S IH1 D IH0 T IY0 +RANCK R AE1 NG K +RANCO R AE1 NG K OW0 +RANCOR R AE1 NG K ER0 +RANCOROUS R AE1 NG K ER0 AH0 S +RANCOROUSNESS R AE1 NG K ER0 AH0 S N IH0 S +RANCOURT R AH0 N K AO1 R T +RAND R AE1 N D +RAND'S R AE1 N D Z +RANDA R AA1 N D AH0 +RANDA'S R AA1 N D AH0 Z +RANDAL R AE1 N D AH0 L +RANDALL R AE1 N D AH0 L +RANDAZZO R AA0 N D AA1 Z OW0 +RANDEL R AE1 N D AH0 L +RANDELL R AE1 N D EH1 L +RANDER R AE1 N D ER0 +RANDI R AE1 N D IY0 +RANDLE R AE1 N D AH0 L +RANDLEMAN R AE1 N D AH0 L M AH0 N +RANDLES R AE1 N D AH0 L Z +RANDLETT R AE1 N D L IH0 T +RANDO R AA1 N D OW0 +RANDOL R AE1 N D AH0 L +RANDOLF R AE1 N D OW2 L F +RANDOLPH R AE1 N D AA0 L F +RANDOM R AE1 N D AH0 M +RANDOMIZE R AE1 N D AH0 M AY2 Z +RANDOMIZED R AE1 N D AH0 M AY2 Z D +RANDOMLY R AE1 N D AH0 M L IY0 +RANDOMNESS R AE1 N D AH0 M N AH0 S +RANDS R AE1 N D Z +RANDY R AE1 N D IY0 +RANDY'S R AE1 N D IY0 Z +RANEE R AE1 N IY1 +RANERI R AA0 N EH1 R IY0 +RANES R EY1 N Z +RANEY R EY1 N IY0 +RANFT R AE1 N F T +RANG R AE1 NG +RANGE R EY1 N JH +RANGED R EY1 N JH D +RANGEL R AE1 N JH EH1 L +RANGER R EY1 N JH ER0 +RANGER'S R EY1 N JH ER0 Z +RANGERS R EY1 N JH ER0 Z +RANGERS' R EY1 N JH ER0 Z +RANGES R EY1 N JH AH0 Z +RANGES(1) R EY1 N JH IH0 Z +RANGING R EY1 N JH IH0 NG +RANGOON R AE0 NG G UW1 N +RANGOON'S R AE0 NG G UW1 N Z +RANGY R EY1 N JH IY0 +RANH R AE1 N +RANI R AA1 N IY0 +RANIA R AA1 N IY0 AH0 +RANIERI R AE2 N IY0 EH1 R IY0 +RANIERI(1) R AH0 N IY0 EH1 R IY0 +RANK R AE1 NG K +RANKE R AE1 NG K +RANKED R AE1 NG K T +RANKER R AE1 NG K ER0 +RANKERS R AE1 NG K ER0 Z +RANKIN R AE1 NG K IH0 N +RANKINE R AE1 NG K AY2 N +RANKING R AE1 NG K IH0 NG +RANKINGS R AE1 NG K IH0 NG Z +RANKINS R AE1 NG K IH0 N Z +RANKLE R AE1 NG K AH0 L +RANKLED R AE1 NG K AH0 L D +RANKLES R AE1 NG K AH0 L Z +RANKLING R AE1 NG K L IH0 NG +RANKS R AE1 NG K S +RANLEY R AE1 N L IY0 +RANN R AE1 N +RANNEY R AE1 N IY0 +RANNOW R AE1 N OW0 +RANS R AE1 N Z +RANSACK R AE1 N S AE2 K +RANSACKED R AE1 N S AE2 K T +RANSACKING R AE1 N S AE2 K IH0 NG +RANSALL R AE1 N S AA0 L +RANSBOTTOM R AE1 N S B AA2 T AH0 M +RANSBURG R AE1 N Z B ER0 G +RANSBURG'S R AE1 N Z B ER0 G Z +RANSDELL R AE1 N Z D EH1 L +RANSFORD R AE1 N S F ER0 D +RANSIER R AE1 N S IY0 ER0 +RANSLEY R AE1 N S L IY0 +RANSOM R AE1 N S AH0 M +RANSOM'S R AE1 N S AH0 M Z +RANSOME R AE1 N S AH0 M +RANSOMS R AE1 N S AH0 M Z +RANSON R AE1 N S AH0 N +RANSONE R AE1 N S AH0 N +RANT R AE1 N T +RANTA R AE1 N T AH0 +RANTALA R AA0 N T AA1 L AH0 +RANTED R AE1 N T IH0 D +RANTING R AE1 N T IH0 NG +RANTOUL R AE2 N T UW1 L +RANTZ R AE1 N T S +RANUM R AE1 N AH0 M +RANZ R AE1 N Z +RAO R AW1 +RAO'S R AW1 Z +RAOUL R AA0 UW1 L +RAOUX R AE0 UW1 +RAP R AE1 P +RAPACIOUS R AH0 P AE1 SH IH0 S +RAPACIOUS(1) R AH0 P EY1 SH IH0 S +RAPACZ R AA1 P AH0 CH +RAPANELLI R AE2 P AH0 N EH1 L IY0 +RAPAPORT R AE1 P AH0 P AO2 R T +RAPE R EY1 P +RAPED R EY1 P T +RAPER R EY1 P ER0 +RAPERS R EY1 P ER0 Z +RAPES R EY1 P S +RAPESEED R EY1 P S IY2 D +RAPHAEL R AA2 F AY0 EH1 L +RAPHAEL(1) R AA2 F Y EH1 L +RAPHAEL(2) R EY1 F IY0 AH0 L +RAPHAELA R AE1 F AY0 EH1 L AH0 +RAPHAELITE R AE0 F Y EH1 L AY0 T +RAPHALIAN R AH0 F EY1 L IY0 AH0 N +RAPHEL R AE1 F AH0 L +RAPID R AE1 P IH0 D +RAPIDITY R AH0 P IH1 D AH0 T IY0 +RAPIDLY R AE1 P AH0 D L IY0 +RAPIDS R AE1 P IH0 D Z +RAPIER R EY1 P IY0 ER0 +RAPING R EY1 P IH0 NG +RAPIST R EY1 P IH0 S T +RAPIST'S R EY1 P IH0 S T S +RAPISTS R EY1 P IH0 S T S +RAPKIN R AE1 P K IH0 N +RAPLEY R AE1 P L IY0 +RAPOCA R AH0 P OW1 K ER0 +RAPOPORT R AH0 P AA1 P AO0 R T +RAPOPORT(1) R AE1 P AH0 P AO0 R T +RAPOSA R AA0 P OW1 S AH0 +RAPOSO R AA0 P OW1 S OW0 +RAPOZA R AA0 P OW1 Z AH0 +RAPOZO R AA0 P OW1 Z OW0 +RAPP R AE1 P +RAPPA R AE1 P AH0 +RAPPAHANNOCK R AE2 P AH0 HH AE1 N AH0 K +RAPPAPORT R AE1 P AH0 P AO0 R T +RAPPE R AE1 P +RAPPED R AE1 P T +RAPPELLING R AH0 P EH1 L IH0 NG +RAPPER R AE1 P ER0 +RAPPERS R AE1 P ER0 Z +RAPPING R AE1 P IH0 NG +RAPPOLD R AE1 P OW2 L D +RAPPOPORT R AE1 P AH0 P AO0 R T +RAPPORT R AE0 P AO1 R +RAPPROCHEMENT R AE2 P R OW2 SH M AA1 N +RAPS R AE1 P S +RAPSON R AE1 P S AH0 N +RAPT R AE1 P T +RAPTIS R AH0 P T IY1 S +RAPTLY R AE1 P T L IY0 +RAPTOPOULOS R AE0 P T AA1 P OW0 L AH0 S +RAPTOR R AE1 P T ER0 +RAPTORIAL R AE2 P T AO1 R IY0 AH0 L +RAPTORS R AE1 P T ER0 Z +RAPTURE R AE1 P CH ER0 +RAPTUROUS R AE1 P CH ER0 AH0 S +RAPUANO R AA0 P UW0 AA1 N OW0 +RAPUNZEL R AA2 P UH1 Z AH0 L +RAQUEL R AH0 K EH1 L +RARA R AA1 R AH0 +RARDON R AA1 R D AH0 N +RARE R EH1 R +RAREFIED R EH1 R AH0 F AY0 D +RAREFY R EH1 R AH0 F AY0 +RARELY R EH1 R L IY0 +RARENESS R EH1 R N IH0 S +RARER R EH1 R ER0 +RAREST R EH1 R AH0 S T +RARICK R AE1 R IH0 K +RARITAN R EH1 R IH0 T AH0 N +RARITIES R EH1 R IH0 T IY0 Z +RARITY R EH1 R AH0 T IY0 +RARITY(1) R EH1 R IH0 T IY0 +RAS R AE1 S +RASBURY R AE1 S B EH0 R IY0 +RASCAL R AE1 S K AH0 L +RASCALS R AE1 S K AH0 L Z +RASCH R AE1 SH +RASCHE R AE1 SH +RASCHKE R AE1 SH K +RASCO R AA1 S K OW0 +RASCOE R AE1 S K OW0 +RASCON R AE1 S K AH0 N +RASE R EY1 Z +RASER R EY1 Z ER0 +RASEY R AE1 S IY0 +RASH R AE1 SH +RASHAD R AH0 SH AA1 D +RASHEED R AH0 SH IY1 D +RASHES R AE1 SH IH0 Z +RASHID R AH0 SH IY1 D +RASHID(1) R AA0 SH IY1 D +RASIA R AA1 S IY0 AH0 +RASK R AE1 S K +RASKA R AA1 S K AH0 +RASKE R EY1 S K +RASKIN R AE1 S K IH0 N +RASKYN R AE1 S K IH0 N +RASMIN R AE1 S M AH0 N +RASMIN(1) R AE1 Z M IH0 N +RASMUS R AE1 Z M IH0 S +RASMUSON R AE1 Z M AH0 S AH0 N +RASMUSSEN R AE1 S M AH0 S AH0 N +RASMUSSON R AE1 Z M AH0 S AH0 N +RASNAKE R AE1 S N AH0 K +RASNER R AE1 S N ER0 +RASNICK R AE1 S N IH0 K +RASO R AA1 S OW0 +RASOR R EY1 Z ER0 +RASORITE R AE1 S ER0 AY2 T +RASP R AE1 S P +RASPBERRIES R AE1 Z B EH2 R IY0 Z +RASPBERRY R AE1 Z B EH2 R IY0 +RASPED R AE1 S P T +RASPS R AE1 S P S +RASPUTIN R AH0 S P Y UW1 T IH0 N +RASPUTIN'S R AE0 S P Y UW1 T AH0 N Z +RASPY R AE1 S P IY0 +RAST R AE1 S T +RASTER R AE1 S T ER0 +RASTEROP R AE1 S T ER0 AA2 P +RASTEROPS R AE1 S T ER0 AA2 P S +RASTETTER R EY1 S T IH0 T ER0 +RASTUS R AE1 S T AH0 S +RAT R AE1 T +RAT'S R AE1 T S +RAT-A-TAT R AE1 T AH0 T AE1 T +RATA R AE1 T AH0 +RATAJCZAK R AE1 T AH0 CH EH0 K +RATATISEMENT R AE1 T AH0 T AY2 Z M AH0 N T +RATATISEMENTS R AE1 T AH0 T AY2 Z M AH0 N T S +RATATOUILLE R AE2 T AH0 T UW1 Y +RATAY R AE1 T EY0 +RATCHET R AE1 CH AH0 T +RATCHET(1) R AE0 T CH AH0 T +RATCHETED R AE1 CH AH0 T IH0 D +RATCHETING R AE1 CH AH0 T IH0 NG +RATCHFORD R AE1 CH F ER0 D +RATCLIFF R AE1 T K L IH0 F +RATCLIFFE R AE1 T K L IH0 F +RATE R EY1 T +RATE'S R EY1 T S 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AO2 L Z +RECALLS(1) R IH0 K AO1 L Z +RECANT R IY0 K AE1 N T +RECANTATION R EH2 K AH0 N T EY1 SH AH0 N +RECANTATION(1) R IY0 K AE0 N T EY1 SH AH0 N +RECANTED R IY0 K AE1 N T IH0 D +RECANTING R AH0 K AE1 N T IH0 NG +RECAP R IY1 K AE2 P +RECAP(1) R IH0 K AE1 P +RECAPITALIZATION R IY2 K AE2 P IH0 T AH0 L IH0 Z EY1 SH AH0 N +RECAPITALIZATIONS R IY0 K AE2 P AH0 T AH0 L AH0 Z EY1 SH AH0 N Z +RECAPITALIZE R IY2 K AE1 P IH0 T AH0 L AY2 Z +RECAPITALIZED R IY2 K AE1 P IH0 T AH0 L AY2 Z D +RECAPITALIZING R IY2 K AE1 P IH0 T AH0 L AY2 Z IH0 NG +RECAPITULATE R IY2 K AH0 P IH1 CH AH0 L EY2 T +RECAPITULATES R IY2 K AH0 P IH1 CH AH0 L EY2 T S +RECAPPED R IY0 K AE1 P T +RECAPPING R IY0 K AE1 P IH0 NG +RECAPS R IY1 K AE2 P S +RECAPTURE R IY0 K AE1 P CH ER0 +RECAPTURED R IY0 K AE1 P CH ER0 D +RECAPTURING R IY0 K AE1 P CH ER0 IH0 NG +RECAREY R IY0 K EH1 R IY0 +RECAST R IY0 K AE1 S T +RECASTING R IY0 K AE1 S T IH0 NG +RECCHIA R EH1 K IY0 AH0 +RECEDE R IH0 S IY1 D +RECEDED R IH0 S IY1 D IH0 D +RECEDED(1) R IY0 S IY1 D IH0 D +RECEDES R IY0 S IY1 D Z +RECEDING R IH0 S IY1 D IH0 NG +RECEDING(1) R IY0 S IY1 D IH0 NG +RECEIPT R IH0 S IY1 T +RECEIPT(1) R IY0 S IY1 T +RECEIPTS R IH0 S IY1 T S +RECEIPTS(1) R IY0 S IY1 T S +RECEIVABLE R IH0 S IY1 V AH0 B AH0 L +RECEIVABLES R IH0 S IY1 V AH0 B AH0 L Z +RECEIVE R AH0 S IY1 V +RECEIVE(1) R IH0 S IY1 V +RECEIVE(2) R IY0 S IY1 V +RECEIVED R AH0 S IY1 V D +RECEIVED(1) R IH0 S IY1 V D +RECEIVED(2) R IY0 S IY1 V D +RECEIVER R AH0 S IY1 V ER0 +RECEIVER(1) R IH0 S IY1 V ER0 +RECEIVER(2) R IY0 S IY1 V ER0 +RECEIVERS R AH0 S IY1 V ER0 Z +RECEIVERS(1) R IH0 S IY1 V ER0 Z +RECEIVERS(2) R IY0 S IY1 V ER0 Z +RECEIVERSHIP R IH0 S IY1 V ER0 SH IH2 P +RECEIVERSHIP(1) R IY0 S IY1 V ER0 SH IH2 P +RECEIVERSHIPS R IH0 S IY1 V ER0 SH IH2 P S +RECEIVES R AH0 S IY1 V Z +RECEIVES(1) R IH0 S IY1 V Z +RECEIVES(2) R IY0 S IY1 V Z +RECEIVING R AH0 S IY1 V IH0 NG +RECEIVING(1) R IH0 S IY1 V IH0 NG +RECEIVING(2) R IY0 S IY1 V IH0 NG +RECENT R IY1 S AH0 N T +RECENTLY R IY1 S AH0 N T L IY0 +RECENTLY(1) R IY1 S AH0 N L IY0 +RECEPTACLE R AH0 S EH1 P T AH0 K AH0 L +RECEPTACLES R IH0 S EH1 P T IH0 K AH0 L Z +RECEPTECH R IY1 S EH2 P T EH1 K +RECEPTION R IH0 S EH1 P SH AH0 N +RECEPTION(1) R IY0 S EH1 P SH AH0 N +RECEPTIONIST R IH0 S EH1 P SH AH0 N IH0 S T +RECEPTIONIST(1) R IY0 S EH1 P SH AH0 N IH0 S T +RECEPTIONISTS R IH0 S EH1 P SH AH0 N IH0 S T S +RECEPTIONISTS(1) R IY0 S EH1 P SH AH0 N IH0 S T S +RECEPTIONISTS(2) R IH0 S EH1 P SH AH0 N IH0 S +RECEPTIONISTS(3) R IY0 S EH1 P SH AH0 N IH0 S +RECEPTIONS R IH0 S EH1 P SH AH0 N Z +RECEPTIVE R IH0 S EH1 P T IH0 V +RECEPTIVE(1) R IY0 S EH1 P T IH0 V +RECEPTIVITY R IY1 S EH2 P T IH1 V IH0 T IY0 +RECEPTOR R IY0 S EH1 P T ER0 +RECEPTORS R AH0 S EH1 P T ER0 Z +RECERTIFICATION R IY2 S ER0 T AH0 F AH0 K EY1 SH AH0 N +RECERTIFIED R IY0 S ER1 T IH0 F AY0 D +RECERTIFY R IY0 S ER1 T AH0 F AY0 +RECERTIFYING R IY0 S ER1 T AH0 F AY0 IH0 NG +RECESS R IH0 S EH1 S +RECESS(1) R IY1 S EH0 S +RECESSED R IH0 S EH1 S T +RECESSED(1) R IY1 S EH1 S T +RECESSES R IY1 S EH0 S AH0 Z +RECESSING R IY2 S EH1 S IH0 NG +RECESSION R IH0 S EH1 SH AH0 N +RECESSION(1) R IY2 S EH1 SH AH0 N +RECESSION'S R IY2 S EH1 SH AH0 N Z +RECESSIONARY R IY0 S EH1 SH AH0 N EH2 R IY0 +RECESSIONS R IH0 S EH1 SH AH0 N Z +RECESSIVE R AH0 S EH1 S IH0 V +RECH R EH1 K +RECHARGE R IY0 CH AA1 R JH +RECHARGEABLE R IY0 CH AA1 R JH AH0 B AH0 L +RECHARGED R IY0 CH AA1 R JH D +RECHARGING R IY0 CH AA1 R JH IH0 NG +RECHECK R IY1 CH EH1 K +RECHECKED R IY0 CH EH1 K T +RECHRISTEN R IY1 K R IH1 S AH0 N +RECHRISTENED R IY1 K R IH1 S AH0 N D +RECHT R EH1 K T +RECIDIVISM R AH0 S IH1 D IH0 V IH2 Z AH0 M +RECIDIVIST R AH0 S IH1 D IH0 V IH2 S T +RECIDIVISTS R AH0 S IH1 D IH0 V IH2 S T S +RECINE R EH0 CH IY1 N IY0 +RECIO R EH1 CH IY0 OW0 +RECIPE R EH1 S AH0 P IY0 +RECIPE'S R EH1 S AH0 P IY0 Z +RECIPES R EH1 S AH0 P IY0 Z +RECIPIENT R AH0 S IH1 P IY0 AH0 N T +RECIPIENT(1) R IH0 S IH1 P IY0 AH0 N T +RECIPIENT'S R IH0 S IH1 P IY0 AH0 N T S +RECIPIENTS R IH0 S IH1 P IY0 AH0 N T S +RECIPIENTS' R IH0 S IH1 P IY0 AH0 N T S +RECIPROCAL R IH0 S IH1 P R AH0 K AH0 L +RECIPROCANT R IY0 S IH1 P R AH0 K AH0 N T +RECIPROCANTS R IY0 S IH1 P R AH0 K AH0 N T S +RECIPROCATE R IH0 S IH1 P R AH0 K EY2 T +RECIPROCATED R IH0 S IH1 P R AH0 K EY2 T IH0 D +RECIPROCATES R IH0 S IH1 P R AH0 K EY2 T S +RECIPROCATING R IH0 S IH1 P R AH0 K EY2 T IH0 NG +RECIPROCITY R EH2 S IH0 P R AA1 S IH0 T IY0 +RECISION R IH0 S IH1 ZH AH0 N +RECISIONS R IH0 S IH1 ZH AH0 N Z +RECISSION R AH0 S IH1 SH AH0 N +RECITAL R AH0 S AY1 T AH0 L +RECITALS R IH0 S AY1 T AH0 L Z +RECITATION R EH2 S AH0 T EY1 SH AH0 N +RECITATIONS R EH2 S IH0 T EY1 SH AH0 N Z +RECITATIVES R EH2 S AH0 T AH0 T IY1 V Z +RECITE R AH0 S AY1 T +RECITED R AH0 S AY1 T IH0 D +RECITES R IY0 S AY1 T S +RECITING R IY0 S AY1 T IH0 NG +RECK R EH1 K +RECKARD R EH1 K ER0 D +RECKER R EH1 K ER0 +RECKITT R EH1 K IH0 T +RECKLESS R EH1 K L AH0 S +RECKLESSLY R EH1 K L AH0 S L IY0 +RECKLESSNESS R EH1 K L AH0 S N AH0 S +RECKNER R EH1 K N ER0 +RECKON R EH1 K AH0 N +RECKONED R EH1 K AH0 N D +RECKONING R EH1 K AH0 N IH0 NG +RECKONING(1) R EH1 K N IH0 NG +RECKONS R EH1 K AH0 N Z +RECKTENWALD R IH2 K T EH1 N W AH0 L D +RECLAIM R IY0 K L EY1 M +RECLAIMED R IY0 K L EY1 M D +RECLAIMER R IY0 K L EY1 M ER0 +RECLAIMER'S R IY0 K L EY1 M ER0 Z +RECLAIMING R IY0 K L EY1 M IH0 NG +RECLAMATION R EH2 K L AH0 M EY1 SH AH0 N +RECLASSIFICATION R IY0 K L AE2 S AH0 F AH0 K EY1 SH AH0 N +RECLASSIFIED R IY0 K L AE1 S AH0 F AY2 D +RECLASSIFY R IY0 K L AE1 S IH0 F AY2 +RECLASSIFYING R IY0 K L AE1 S IH0 F AY2 IH0 NG +RECLINE R IH0 K L AY1 N +RECLINED R IH0 K L AY1 N D +RECLINER R IH0 K L AY1 N ER0 +RECLINES R IH0 K L AY1 N Z +RECLINING R IH0 K L AY1 N IH0 NG +RECLINING(1) R IY0 K L AY1 N IH0 NG +RECLUSE R IH0 K L UW1 S +RECLUSIVE R IH0 K L UW1 S IH0 V +RECLUSIVE(1) R IY0 K L UW1 S IH0 V +RECO R EH1 K OW0 +RECOGNISE R EH1 K AH0 G N AY2 Z +RECOGNISED R EH1 K AH0 G N AY2 Z D +RECOGNISES R EH1 K AH0 G N AY2 Z IH0 Z +RECOGNISING R EH1 K AH0 G N AY2 Z IH0 NG +RECOGNITION R EH2 K AH0 G N IH1 SH AH0 N +RECOGNITION(1) R EH2 K IH0 G N IH1 SH AH0 N +RECOGNITION'S R EH2 K IH0 G N IH1 SH AH0 N Z +RECOGNIZABLE R EH2 K AH0 G N AY1 Z AH0 B AH0 L +RECOGNIZABLY R EH1 K AH0 G N AY2 Z AH0 B L IY0 +RECOGNIZANCE R IH0 K AA1 N AH0 Z AH0 N S +RECOGNIZE R EH1 K AH0 G N AY2 Z +RECOGNIZED R EH1 K AH0 G N AY2 Z D +RECOGNIZES R EH1 K AH0 G N AY2 Z IH0 Z +RECOGNIZING R EH1 K AH0 G N AY2 Z IH0 NG +RECOIL R IY0 K OY1 L +RECOILED R IY0 K OY1 L D +RECOILS R IY0 K OY1 L Z +RECOLLECT R EH2 K AH0 L EH1 K T +RECOLLECT(1) R IY2 K AH0 L EH1 K T +RECOLLECTED R EH2 K AH0 L EH1 K T IH0 D +RECOLLECTED(1) R IY2 K AH0 L EH1 K T IH0 D +RECOLLECTING R EH2 K AH0 L EH1 K T IH0 NG +RECOLLECTING(1) R IY2 K AH0 L EH1 K T IH0 NG +RECOLLECTION R EH2 K AH0 L EH1 K SH AH0 N +RECOLLECTIONS R EH2 K AH0 L EH1 K SH AH0 N Z +RECOLLECTS R EH2 K AH0 L EH1 K T S +RECOLLECTS(1) R IY2 K AH0 L EH1 K T S +RECOMBINANT R IY0 K AA1 M B IH0 N AH0 N T +RECOMBINATION R IY0 K AA2 M B IH0 N EY1 SH AH0 N 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IH0 NG +RECONFIGURATION R IY0 K AH0 N F IH2 G Y ER0 EY1 SH AH0 N +RECONFIGURE R IY2 K AH0 N F IH1 G Y ER0 +RECONFIGURED R IY2 K AH0 N F IH1 G Y ER0 D +RECONFIRM R IY2 K AH0 N F ER1 M +RECONFIRMATION R IY2 K AA2 N F ER0 M EY1 SH AH0 N +RECONFIRMED R IY2 K AH0 N F ER1 M D +RECONNAISSANCE R IY0 K AA1 N AH0 S AH0 N S +RECONNECT R IY0 K AH0 N EH1 K T +RECONNECTED R IY0 K AH0 N EH1 K T IH0 D +RECONNECTING R IY0 K AH0 N EH1 K T IH0 NG +RECONNECTS R IY0 K AH0 N EH1 K T S +RECONNOITER R IY2 K AH0 N OY1 T ER0 +RECONNOITRE R IY2 K AH0 N OY1 T ER0 +RECONQUER R IY0 K AO1 NG K ER0 +RECONQUERED R IY0 K AO1 NG K ER0 D +RECONSIDER R IY2 K AH0 N S IH1 D ER0 +RECONSIDERATION R IY0 K AH0 N S IH2 D ER0 EY1 SH AH0 N +RECONSIDERED R IY2 K AH0 N S IH1 D ER0 D +RECONSIDERING R IY2 K AH0 N S IH1 D ER0 IH0 NG +RECONSTITUTE R IY0 K AA1 N S T AH0 T UW2 T +RECONSTITUTED R IY0 K AA1 N S T AH0 T UW2 T IH0 D +RECONSTITUTING R IY0 K AA1 N S T IH0 T UW2 T IH0 NG +RECONSTRUCT R IY2 K AH0 N S T R AH1 K T +RECONSTRUCTED R IY2 K AH0 N S T R AH1 K T IH0 D +RECONSTRUCTING R IY2 K AH0 N S T R AH1 K T IH0 NG +RECONSTRUCTION R IY2 K AH0 N S T R AH1 K SH AH0 N +RECONSTRUCTIONS R IY2 K AH0 N S T R AH1 K SH AH0 N Z +RECONSTRUCTIVE R IY2 K AH0 N S T R AH1 K T IH0 V +RECONVENE R IY0 K AH0 N V IY1 N +RECONVENED R IY0 K AH0 N V IY1 N D +RECONVENES R IY0 K AH0 N V IY1 N Z +RECORD R AH0 K AO1 R D +RECORD(1) R EH1 K ER0 D +RECORD(2) R IH0 K AO1 R D +RECORD'S R EH1 K ER0 D Z +RECORDABLE R IH0 K AO1 R D AH0 B AH0 L +RECORDED R IH0 K AO1 R D IH0 D +RECORDER R IH0 K AO1 R D ER0 +RECORDER(1) R IY0 K AO1 R D ER0 +RECORDERS R IH0 K AO1 R D ER0 Z +RECORDERS(1) R IY0 K AO1 R D ER0 Z +RECORDING R AH0 K AO1 R D IH0 NG +RECORDING(1) R IH0 K AO1 R D IH0 NG +RECORDINGS R IH0 K AO1 R D IH0 NG Z +RECORDKEEPING R EH1 K ER0 D K IY2 P IH0 NG +RECORDS R AH0 K AO1 R D Z +RECORDS(1) R EH1 K ER0 D Z +RECORDS(2) R IH0 K AO1 R D Z +RECORDS' R EH1 K ER0 D Z +RECORE R EH0 K AO1 R IY0 +RECOTON R IH0 K AO1 T IH0 N +RECOUNT R IH0 K AW1 N T 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IY0 D UW1 IH0 NG +REDOLENT R EH1 D AH0 L AH0 N T +REDONDO R IH0 D AA1 N D OW0 +REDONE R IY0 D AH1 N +REDOUBLE R IY0 D AH1 B AH0 L +REDOUBLED R IY0 D AH1 B AH0 L D +REDOUBLING R IY0 D AH1 B AH0 L IH0 NG +REDOUBLING(1) R IY0 D AH1 B L IH0 NG +REDOUBT R IY0 D AW1 T +REDOUBTABLE R AH0 D AW1 T AH0 B AH0 L +REDOUND R IH0 D AW1 N D +REDPATH R EH1 D P AE2 TH +REDPOLL R EH1 D P OW2 L +REDPOLLS R EH1 D P OW2 L Z +REDRAFT R IY0 D R AE1 F T +REDRAFTED R IY0 D R AE1 F T IH0 D +REDRAW R IY0 D R AO1 +REDRAWING R IY0 D R AO1 IH0 NG +REDRAWN R IY0 D R AO1 N +REDRESS R IY0 D R EH1 S +REDRESS(1) R IY1 D R EH0 S +REDRESSING R IY0 D R EH1 S IH0 NG +REDS R EH1 D Z +REDS' R EH1 D Z +REDSHAW R EH1 D SH AO2 +REDSKIN R EH1 D S K IH2 N +REDSKINS R EH1 D S K IH2 N Z +REDSKINS' R EH1 D S K IH2 N Z +REDSTONE R EH1 D S T OW2 N +REDSTONE'S R EH1 D S T OW2 N Z +REDUCE R IH0 D UW1 S +REDUCED R IH0 D UW1 S T +REDUCES R IH0 D UW1 S IH0 Z +REDUCES(1) R IY0 D UW1 S IH0 Z +REDUCIBLE R IH0 D UW1 S AH0 B AH0 L +REDUCING R IH0 D UW1 S IH0 NG +REDUCTION R IH0 D AH1 K SH AH0 N +REDUCTIONS R IH0 D AH1 K SH AH0 N Z +REDUNDANCIES R IH0 D AH1 N D AH0 N S IY0 Z +REDUNDANCY R IH0 D AH1 N D AH0 N S IY0 +REDUNDANT R IH0 D AH1 N D AH0 N T +REDUS R IY1 D AH0 S +REDUX R IY1 D AH2 K S +REDWALD R EH1 D W AH0 L D +REDWINE R EH1 D W AY2 N +REDWOOD R EH1 D W UH2 D +REDWOODS R EH1 D W UH2 D Z +REE R IY1 +REEB R IY1 B +REEB'S R IY1 B Z +REEBOK R IY1 B AA0 K +REEBOK'S R IY1 B AA0 K S +REEBOKS R IY1 B AA0 K S +REEBS R IY1 B Z +REEBS' R IY1 B Z +REECE R IY1 S +REECHE R IY1 CH +REECK R IY1 K +REED R IY1 D +REED'S R IY1 D Z +REEDER R IY1 D ER0 +REEDERS R IY1 D ER0 Z +REEDS R IY1 D Z +REEDUCATE R IY1 EH2 JH AH0 K EY2 T +REEDUCATION R IY1 EH2 JH AH0 K EY2 SH AH0 N +REEDY R IY1 D IY0 +REEF R IY1 F +REEFER R IY1 F ER0 +REEFERS R IY1 F ER0 Z +REEFS R IY1 F S +REEG R IY1 G +REEH R IY1 +REEK R IY1 K +REEKING R IY1 K IH0 NG +REEKS R IY1 K S +REEL R IY1 L +REELECT R IY0 IH0 L EH1 K T +REELECTED R IY0 IH0 L EH1 K T IH0 D +REELECTING R IY0 IH0 L EH1 K T IH0 NG +REELECTION R IY0 IH0 L EH1 K SH AH0 N +REELED R IY1 L D +REELING R IY1 L IH0 NG +REELS R IY1 L Z +REEMERGE R IY0 IH0 M ER1 JH +REEMERGED R IY0 IH0 M ER1 JH D +REEMERGENCE R IY0 IH0 M ER1 JH AH0 N S +REEMPHASIZE R IY0 EH1 M F AH0 S AY2 Z +REEMPLOYMENT R IY0 IH0 M P L OY1 M AH0 N T +REEN R IY1 N +REENACT R IY0 IH0 N AE1 K T +REENACTED R IY0 IH0 N AE1 K T IH0 D +REENACTMENT R IY0 IH0 N AE1 K T M AH0 N T +REENACTMENTS R IY0 IH0 N AE1 K T M AH0 N T S +REENACTS R IY0 IH0 N AE1 K T S +REENGINEER R IY0 EH2 N JH AH0 N IH1 R +REENGINEERING R IY0 EH2 N JH AH0 N IH1 R IH0 NG +REENTER R IY0 IH1 N T ER0 +REENTERED R IY0 IH1 N T ER0 D +REENTERING R IY0 IH1 N T ER0 IH0 NG +REENTRY R IY0 IH1 N T R IY0 +REENTS R IY1 N T S +REEP R IY1 P +REES R IY1 Z +REESE R IY1 S +REESE'S R IY1 S IH0 Z +REESER R IY1 S ER0 +REESJONES R IY2 S JH OW1 N Z +REESJONES' R IY2 S JH OW1 N Z +REESJONES'(1) R IY2 S JH OW1 N Z AH0 Z +REESMAN R IY1 S M AH0 N +REESOR R IY1 S ER0 +REESTABLISH R IY0 IH0 S T AE1 B L IH0 SH +REESTABLISHED R IY2 IH0 S T AE1 B L IH0 SH T +REESTABLISHING R IY0 IH0 S T AE1 B L IH0 SH IH0 NG +REETZ R IY1 T S +REEVALUATE R IY2 IH0 V AE1 L UW0 EY2 T +REEVALUATED R IY0 IH0 V AE1 L Y UW0 EY2 T IH0 D +REEVALUATING R IY0 IH0 V AE1 L Y UW0 EY2 T IH0 NG +REEVALUATION R IY0 IH0 V AE2 L Y UW0 EY1 SH AH0 N +REEVE R IY1 V +REEVER R IY1 V ER0 +REEVES R IY1 V Z +REEVES' R IY1 V Z +REEVES'S R IY1 V Z IH0 Z +REEXAMINATION R IY0 IH0 G Z AE2 M AH0 N EY1 SH AH0 N +REEXAMINE R IY0 EH0 G Z AE1 M AH0 N +REEXAMINED R IY0 IH0 G Z AE1 M AH0 N D +REEXAMINING R IY0 IH0 G Z AE1 M AH0 N IH0 NG +REEXPORT R IY0 EH1 K S P AO2 R T +REEXPORTS R IY0 EH1 K S P AO2 R T S +REF R EH1 F +REFAAT R AH0 F AA1 T +REFAH R AH0 F AA1 +REFCO R EH1 F K OW0 +REFCORP R EH1 F K AO0 R P +REFENES R EH1 F IH0 N EH2 S +REFENES(1) R IH0 F IY1 N Z +REFER R AH0 F ER1 +REFER(1) R IH0 F ER1 +REFEREE R EH2 F ER0 IY1 +REFEREE'S R EH2 F ER0 IY1 Z +REFEREES R EH2 F ER0 IY1 Z +REFERENCE R EH1 F ER0 AH0 N S +REFERENCE(1) R EH1 F R AH0 N S +REFERENCED R EH1 F ER0 AH0 N S T +REFERENCED(1) R EH1 F R AH0 N S T +REFERENCES R EH1 F ER0 AH0 N S IH0 Z +REFERENCES(1) R EH1 F R AH0 N S IH0 Z +REFERENCING R EH1 F ER0 AH0 N S IH0 NG +REFERENCING(1) R EH1 F R AH0 N S IH0 NG +REFERENDA R EH2 F ER0 EH1 N D AH0 +REFERENDUM R EH2 F ER0 EH1 N D AH0 M +REFERENDUMS R EH2 F ER0 EH1 N D AH0 M Z +REFERING R IH0 F ER1 IH0 NG +REFERRAL R IH0 F ER1 AH0 L +REFERRALS R IH0 F ER1 AH0 L Z +REFERRED R AH0 F ER1 D +REFERRED(1) R IH0 F ER1 D +REFERRING R IH0 F ER1 IH0 NG +REFERS R AH0 F ER1 Z +REFERS(1) R IH0 F ER1 Z +REFF R EH1 F +REFFETT R EH1 F IH0 T +REFFITT R EH1 F IH0 T +REFFNER R EH1 F N ER0 +REFILE R IY0 F AY1 L +REFILED R IY0 F AY1 L D +REFILL R IY1 F IH0 L +REFILL(1) R IY0 F IH1 L +REFILLED R IY0 F IH1 L D +REFILLS R IY0 F IH1 L Z +REFILLS(1) R IY1 F IH0 L Z +REFINANCE R IY2 F AH0 N AE1 N S +REFINANCE(1) R IY1 F AY1 N AE2 N S +REFINANCED R IY2 F AH0 N AE1 N S T +REFINANCED(1) R IY1 F AY1 N AE2 N S T +REFINANCES R IY2 F AH0 N AE1 N S IH0 Z +REFINANCES(1) R IY1 F AY1 N AE2 N S IH0 Z +REFINANCING R IY2 F AH0 N AE1 N S IH0 NG +REFINANCING(1) R IY1 F AY1 N AE2 N S IH0 NG +REFINANCINGS R IY2 F AH0 N AE1 N S IH0 NG Z +REFINANCINGS(1) R IY1 F AY1 N AE2 N S IH0 NG Z +REFINE R AH0 F AY1 N +REFINE(1) R IH0 F AY1 N +REFINED R AH0 F AY1 N D +REFINED(1) R IH0 F AY1 N D +REFINEMENT R AH0 F AY1 N M AH0 N T +REFINEMENTS R IH0 F AY1 N M AH0 N T S +REFINER R IH0 F AY1 N ER0 +REFINER'S R IH0 F AY1 N ER0 Z +REFINERIES R IH0 F AY1 N ER0 IY0 Z +REFINERS R IH0 F AY1 N ER0 Z +REFINERS' R IH0 F AY1 N ER0 Z +REFINERY R IH0 F AY1 N ER0 IY0 +REFINERY'S R IH0 F AY1 N ER0 IY0 Z +REFINES R IH0 F AY1 N Z +REFINING R AH0 F AY1 N IH0 NG +REFINING(1) R IH0 F AY1 N IH0 NG +REFINISH R IY0 F IH1 N IH0 SH +REFINISHED R IY0 F IH1 N IH0 SH T +REFINISHING R IY0 F IH1 N IH0 SH IH0 NG +REFIT R IY0 F IH1 T +REFITTED R IY0 F IH1 T IH0 D +REFITTING R IY0 F IH1 T IH0 NG +REFLAG R IY0 F L AE1 G +REFLAGGED R IY0 F L AE1 G D +REFLAGGING R IY0 F L AE1 G IH0 NG +REFLATE R IY0 F L EY1 T +REFLATION R IY0 F L EY1 SH AH0 N +REFLECT R AH0 F L EH1 K T +REFLECT(1) R IH0 F L EH1 K T +REFLECTED R IH0 F L EH1 K T IH0 D +REFLECTING R AH0 F L EH1 K T IH0 NG +REFLECTING(1) R IH0 F L EH1 K T IH0 NG +REFLECTION R AH0 F L EH1 K SH AH0 N +REFLECTION(1) R IH0 F L EH1 K SH AH0 N +REFLECTIONS R IH0 F L EH1 K SH AH0 N Z +REFLECTIVE R IH0 F L EH1 K T IH0 V +REFLECTONE R IY0 F L EH1 K T OW2 N +REFLECTONE'S R IY0 F L EH1 K T OW2 N Z +REFLECTOR R IH0 F L EH1 K T ER0 +REFLECTORS R IH0 F L EH1 K T ER0 Z +REFLECTS R IH0 F L EH1 K T S +REFLECTS(1) R IH0 F L EH1 K S +REFLEX R IY1 F L EH0 K S +REFLEXES R IY1 F L EH0 K S AH0 Z +REFLEXIVE R AH0 F L EH1 K S IH0 V +REFLEXIVELY R IY0 F L EH1 K S IH0 V L IY0 +REFLEXIVITY R IY2 F L EH2 K S IH1 V IH0 T IY0 +REFLUX R IY1 F L AH2 K S +REFOCUS R IY0 F OW1 K AH0 S +REFOCUSED R IY0 F OW1 K AH0 S T +REFOCUSES R IY0 F OW1 K AH0 S IH0 Z +REFOCUSING R IY0 F OW1 K AH0 S IH0 NG +REFOREST R IY0 F AO1 R AH0 S T +REFORESTATION R IY2 F AO0 R AH0 S T EY1 SH AH0 N +REFORM R AH0 F AO1 R M +REFORM(1) R IH0 F AO1 R M +REFORMA R IH0 F AO1 R M AH0 +REFORMATION R EH2 F ER0 M EY1 SH AH0 N +REFORMATORIES R IH0 F AO1 R M AH0 T AO2 R IY0 Z +REFORMATORY R IH0 F AO1 R M AH0 T AO2 R IY0 +REFORMED R IH0 F AO1 R M D +REFORMER R IH0 F AO1 R M ER0 +REFORMERS R IH0 F AO1 R M ER0 Z +REFORMERS' R IH0 F AO1 R M ER0 Z +REFORMING R IH0 F AO1 R M IH0 NG +REFORMIST R IH0 F AO1 R M IH0 S T +REFORMISTS R IH0 F AO1 R M IH0 S T S +REFORMS R AH0 F AO1 R M Z +REFORMS(1) R IH0 F AO1 R M Z +REFORMULATE R IY0 F AO1 R M Y AH0 L EY2 T +REFORMULATED R IY0 F AO1 R M Y AH0 L EY2 T IH0 D +REFRACTIVE R AH0 F R AE1 K T IH0 V +REFRACTOR R AH0 F R AE1 K T ER0 +REFRACTORIES R IH0 F R AE1 K T ER0 IY0 Z +REFRACTORS R AH0 F R AE1 K T ER0 Z +REFRACTORY R AH0 F R AE1 K T ER0 IY0 +REFRAIN R IH0 F R EY1 N +REFRAINED R IH0 F R EY1 N D +REFRAINING R IH0 F R EY1 N IH0 NG +REFRAINS R IH0 F R EY1 N Z +REFRESH R IH0 F R EH1 SH +REFRESHED R IY0 F R EH1 SH T +REFRESHER R IH0 F R EH1 SH ER0 +REFRESHES R IH0 F R EH1 SH IH0 Z +REFRESHING R IH0 F R EH1 SH IH0 NG +REFRESHINGLY R IY0 F R EH1 SH IH0 NG L IY0 +REFRESHMENT R AH0 F R EH1 SH M AH0 N T +REFRESHMENTS R AH0 F R EH1 SH M AH0 N T S +REFRIGERANT R IH0 F R IH1 JH ER0 AH0 N T +REFRIGERANTS R IH0 F R IH1 JH ER0 AH0 N T S +REFRIGERATE R IH0 F R IH1 JH ER0 EY2 T +REFRIGERATED R IH0 F R IH1 JH ER0 EY2 T IH0 D +REFRIGERATION R IH0 F R IH2 JH ER0 EY1 SH AH0 N +REFRIGERATOR R AH0 F R IH1 JH ER0 EY2 T ER0 +REFRIGERATOR(1) R IH0 F R IH1 JH ER0 EY2 T ER0 +REFRIGERATORS R IH0 F R IH1 JH ER0 EY2 T ER0 Z +REFSNES R EH1 F S N IY0 Z +REFUEL R IY0 F Y UW1 AH0 L +REFUELED R IY0 F Y UW1 AH0 L D +REFUELING R IY0 F Y UW1 AH0 L IH0 NG +REFUELING(1) R IY0 F Y UW1 L IH0 NG +REFUGE R EH1 F Y UW0 JH +REFUGE'S R EH1 F Y UW0 JH IH0 Z +REFUGEE R EH1 F Y UW0 JH IY0 +REFUGEES R EH1 F Y UW2 JH IY0 Z +REFUGEES' R EH1 F Y UW2 JH IY0 Z +REFUGES R EH0 F Y UW1 JH IH0 Z +REFUGIO R AH0 F Y UW1 JH IY0 OW0 +REFUND R IH0 F AH1 N D +REFUND(1) R IY1 F AH2 N D +REFUNDABLE R IH0 F AH1 N D AH0 B AH0 L +REFUNDED R IH0 F AH1 N D IH0 D +REFUNDING R IH0 F AH1 N D IH0 NG +REFUNDINGS R IY1 F AH2 N D IH0 NG Z +REFUNDS R IH0 F AH1 N D Z +REFUNDS(1) R IY1 F AH2 N D Z +REFURBISH R IY0 F ER1 B IH0 SH +REFURBISHED R IY0 F ER1 B IH0 SH T +REFURBISHING R IY0 F ER1 B IH0 SH IH0 NG +REFURBISHMENT R IY0 F ER1 B IH0 SH M AH0 N T +REFUSAL R AH0 F Y UW1 Z AH0 L +REFUSAL(1) R IH0 F Y UW1 Z AH0 L +REFUSALS R IH0 F Y UW1 Z AH0 L Z +REFUSE R AH0 F Y UW1 Z +REFUSE(1) R EH1 F Y UW2 Z +REFUSE(2) R IH0 F Y UW1 Z +REFUSED R AH0 F Y UW1 Z D +REFUSED(1) R IH0 F Y UW1 Z D +REFUSENIK R IH0 F Y UW1 Z N IH0 K +REFUSENIKS R IH0 F Y UW1 Z N IH0 K S +REFUSES R AH0 F Y UW1 Z AH0 Z +REFUSES(1) R IH0 F Y UW1 Z IH0 Z +REFUSING R AH0 F Y UW1 Z IH0 NG +REFUSING(1) R IH0 F Y UW1 Z IH0 NG +REFUTATION R EH2 F Y UW0 T EY1 SH AH0 N +REFUTE R IH0 F Y UW1 T +REFUTED R IH0 F Y UW1 T IH0 D +REFUTES R IH0 F Y UW1 T S +REFUTING R IH0 F Y UW1 T IH0 NG +REG R EH1 G +REGA R IY1 G AH0 +REGAIN R IH0 G EY1 N +REGAINED R IY0 G EY1 N D +REGAINING R IH0 G EY1 N IH0 NG +REGAINS R IY0 G EY1 N Z +REGAL R IY1 G AH0 L +REGALADO R EY0 G AA0 L AA1 D OW0 +REGALE R IH0 G EY1 L +REGALED R IH0 G EY1 L D +REGALES R IH0 G EY1 L Z +REGALIA R IH0 G EY1 L Y AH0 +REGALING R IH0 G EY1 L IH0 NG +REGALLY R IY1 G AH0 L IY0 +REGAN R IY1 G AH0 N +REGAN'S R IY1 G AH0 N Z +REGARD R AH0 G AA1 R D +REGARD(1) R IH0 G AA1 R D +REGARDED R IH0 G AA1 R D IH0 D +REGARDING R AH0 G AA1 R D IH0 NG +REGARDING(1) R IH0 G AA1 R D IH0 NG +REGARDLESS R AH0 G AA1 R D L AH0 S +REGARDS R IH0 G AA1 R D Z +REGAS R IY1 G AH0 Z +REGATTA R IH0 G AA1 T AH0 +REGATTAS R AH0 G AA1 T AH0 Z +REGEHR R EH1 G IH0 R +REGEL R EH1 G AH0 L +REGEN R EH1 G AH0 N +REGENCY R IY1 JH AH0 N S IY0 +REGENCY'S R IY1 JH AH0 N S IY0 Z +REGENERATE R IY0 JH EH1 N ER0 EY2 T +REGENERATED R IY0 JH EH1 N ER0 EY2 T IH0 D +REGENERATING R IY0 JH EH1 N ER0 EY2 T IH0 NG +REGENERATION R IY0 JH EH1 N ER0 EY1 SH AH0 N +REGENERON R IY0 JH EH1 N ER0 AO2 N +REGENSBURG R IY1 G AH0 N Z B ER0 G +REGENSTEINER R EH1 G AH0 N S T AY2 N ER0 +REGENT R IY1 JH AH0 N T +REGENTS R IY1 JH AH0 N T S +REGER R IY1 G ER0 +REGESTER R EH1 JH IH0 S T ER0 +REGGAE R EH1 G EY2 +REGGAETON R EH2 G EY0 T OW1 N +REGGIE R EH1 JH IY0 +REGGIO R EH1 JH IY0 OW0 +REGGY R EH1 G IY0 +REGIE R EH1 G IY0 +REGIER R IY1 G IY0 ER0 +REGIME R AH0 ZH IY1 M +REGIME(1) R EY0 ZH IY1 M +REGIME'S R EY0 ZH IY1 M Z +REGIMEN R EH1 JH AH0 M AH0 N +REGIMENS R EH1 JH AH0 M AH0 N Z +REGIMENT R EH1 JH AH0 M AH0 N T +REGIMENTAL R EH2 JH AH0 M EH1 N T AH0 L +REGIMENTATION R EH2 JH AH0 M EH0 N T EY1 SH AH0 N +REGIMENTED R EH1 JH AH0 M EH2 N T IH0 D +REGIMENTS R EH1 JH AH0 M AH0 N T S +REGIMES R AH0 ZH IY1 M Z +REGIMES(1) R EY0 ZH IY1 M Z +REGINA R IH0 JH IY1 N AH0 +REGINALD R EH1 JH AH0 N AH0 L D +REGINALD'S R EH1 JH AH0 N AH0 L D Z +REGION R IY1 JH AH0 N +REGION'S R IY1 JH AH0 N Z +REGIONAL R IY1 JH AH0 N AH0 L +REGIONALIZE R IY1 JH AH0 N AH0 L AY2 Z +REGIONALIZED R IY1 JH AH0 N AH0 L AY2 Z D +REGIONALLY R IY1 JH AH0 N AH0 L IY0 +REGIONALS R IY1 JH AH0 N AH0 L Z +REGIONS R IY1 JH AH0 N Z +REGIS R IY1 JH IH0 S +REGISTER R EH1 JH IH0 S T ER0 +REGISTER'S R EH1 JH IH0 S T ER0 Z +REGISTERED R EH1 JH IH0 S T ER0 D +REGISTERING R EH1 JH IH0 S T ER0 IH0 NG +REGISTERING(1) R EH1 JH IH0 S T R IH0 NG +REGISTERS R EH1 JH AH0 S T ER0 Z +REGISTERS(1) R EH1 JH IH0 S T ER0 Z +REGISTRANT R EH1 JH AH0 S T R AH0 N T +REGISTRANTS R EH1 JH AH0 S T R AH0 N T S +REGISTRAR R EH1 JH IH0 S T R AA2 R +REGISTRARS R EH1 JH IH0 S T R AA2 R Z +REGISTRATION R EH2 JH IH0 S T R EY1 SH AH0 N +REGISTRATIONS R EH2 JH IH0 S T R EY1 SH AH0 N Z +REGISTRIES R EH1 JH IH0 S T R IY0 Z +REGISTRY R EH1 JH IH0 S T R IY0 +REGNER R EH1 G N ER0 +REGNERY R EH1 G N ER0 IY0 +REGNIER R EH1 G N IY0 ER0 +REGO R EH1 G OW0 +REGRESS R IY1 G R EH0 S +REGRESS(1) R IH0 G R EH1 S +REGRESSION R AH0 G R EH1 SH AH0 N +REGRESSIONS R AH0 G R EH1 SH AH0 N Z +REGRESSIVE R AH0 G R EH1 S IH0 V +REGRET R AH0 G R EH1 T +REGRET(1) R IH0 G R EH1 T +REGRETFUL R IH0 G R EH1 T F AH0 L +REGRETFULLY R IH0 G R EH1 T F AH0 L IY0 +REGRETS R IH0 G R EH1 T S +REGRETTABLE R IH0 G R EH1 T AH0 B AH0 L +REGRETTABLY R IH0 G R EH1 T AH0 B L IY0 +REGRETTED R IH0 G R EH1 T IH0 D +REGRETTING R IH0 G R EH1 T IH0 NG +REGROUP R IY0 G R UW1 P +REGROUPED R IY0 G R UW1 P T +REGROUPING R IY0 G R UW1 P IH0 NG +REGS R EH1 G Z +REGULA R EH0 G UW1 L AH0 +REGULAR R EH1 G Y AH0 L ER0 +REGULAR(1) R EY1 G Y AH0 L ER0 +REGULARITY R EH2 G Y AH0 L EH1 R AH0 T IY0 +REGULARLY R EH1 G Y AH0 L ER0 L IY0 +REGULARS R EH1 G Y AH0 L ER0 Z +REGULATE R EH1 G Y AH0 L EY2 T +REGULATED R EH1 G Y AH0 L EY2 T IH0 D +REGULATES R EH1 G Y AH0 L EY2 T S +REGULATING R EH1 G Y AH0 L EY2 T IH0 NG +REGULATINGLY R EH1 G Y AH0 L EY2 T IH0 NG L IY0 +REGULATION R EH2 G Y AH0 L EY1 SH AH0 N +REGULATIONS R EH2 G Y AH0 L EY1 SH AH0 N Z +REGULATIVE R EH1 G Y AH0 L EY2 T IH0 V +REGULATOR R EH1 G Y AH0 L EY2 T ER0 +REGULATOR'S R EH1 G Y AH0 L EY2 T ER0 Z +REGULATORS R EH1 G Y AH0 L EY2 T ER0 Z +REGULATORS' R EH1 G Y AH0 L EY2 T ER0 Z +REGULATORY R EH1 G Y AH0 L AH0 T AO2 R IY0 +REGURGITATE R IH2 G ER1 JH AH0 T EY2 T +REGWAN R EH1 G W AA0 N +REH R EH1 +REHA R IY1 HH AH0 +REHAB R IY0 HH AE0 B +REHABILITATE R IY2 HH AH0 B IH1 L AH0 T EY2 T +REHABILITATE(1) R IY2 AH0 B IH1 L AH0 T EY2 T +REHABILITATED R IY2 HH AH0 B IH1 L AH0 T EY2 T IH0 D +REHABILITATED(1) R IY2 AH0 B IH1 L AH0 T EY2 T IH0 D +REHABILITATING R IY2 HH AH0 B IH1 L AH0 T EY2 T IH0 NG +REHABILITATING(1) R IY2 AH0 B IH1 L AH0 T EY2 T IH0 NG +REHABILITATION R IY2 HH AH0 B IH2 L AH0 T EY1 SH AH0 N +REHABILITATION(1) R IY2 AH0 B IH2 L AH0 T EY1 SH AH0 N +REHABILITATIONS R IY2 HH AH0 B IH2 L AH0 T EY1 SH AH0 N Z +REHABILITATIONS(1) R IY2 AH0 B IH2 L AH0 T EY1 SH AH0 N Z +REHABILITATIVE R IY2 HH AH0 B IH1 L AH0 T EY2 T IH0 V +REHABILITATIVE(1) R IY2 AH0 B IH1 L AH0 T EY2 T IH0 V +REHABILITATOR R IY2 HH AH0 B IH1 L AH0 T EY0 T ER0 +REHABILITATORS R IY2 HH AH0 B IH1 L AH0 T EY0 T ER0 Z +REHABILITY R IY2 HH AH0 B IH1 L AH0 T IY0 +REHABILITY(1) R IY2 AH0 B IH1 L AH0 T IY0 +REHAK R EH1 HH AH0 K +REHASH R IY0 HH AE1 SH +REHASHING R IY0 HH AE1 SH IH0 NG +REHBEIN R EH1 B AY0 N +REHBEIN(1) R EH1 B IY0 N +REHBERG R EH1 B ER0 G +REHBERGER R EH1 B ER0 G ER0 +REHDER R EH1 D ER0 +REHEAR R IY0 HH IY1 R +REHEARING R IY0 HH IY1 R IH0 NG +REHEARINGS R IY0 HH IY1 R IH0 NG Z +REHEARSAL R IH0 HH ER1 S AH0 L +REHEARSAL(1) R IY0 HH ER1 S AH0 L +REHEARSALS R IH0 HH ER1 S AH0 L Z +REHEARSE R IY0 HH ER1 S +REHEARSED R IY0 HH ER1 S T +REHEARSES R IY0 HH ER1 S IH0 Z +REHEARSING R IH0 HH ER1 S IH0 NG +REHER R EH1 R +REHFELD R EH1 F EH2 L D +REHFELDT R EH1 F EH2 L T +REHG R EH1 JH +REHIRE R IY0 HH AY1 R +REHIRED R IY0 HH AY1 ER0 D +REHIRING R IY0 HH AY1 R IH0 NG +REHKOPF R EH1 K AO0 P F +REHKOPF(1) R EH1 K AO0 F +REHLING R EH1 L IH0 NG +REHM R EH1 M +REHMAN R EH1 M AH0 N +REHMANN R EH1 M AH0 N +REHMER R EH1 M ER0 +REHN R EH1 N +REHNQUIST R EH1 N K W IH2 S T +REHOR R EH1 HH ER0 +REHRIG R EH1 R IH0 G +REHYDRATE R IY0 HH AY1 D R EY0 T +REHYDRATION R IY2 HH AY0 D R EY1 SH AH0 N +REIBEL R AY1 B AH0 L +REIBER R AY1 B ER0 +REICH R AY1 K +REICH'S R AY1 K S +REICHARD R AY1 K ER0 D +REICHARDT R AY1 K AA0 R T +REICHART R IY1 IH0 K HH AA0 R T +REICHE R AY1 K +REICHEL R AY1 K AH0 L +REICHELDERFER R AY1 K IH0 L D ER0 F ER0 +REICHELT R AY1 K IH0 L T +REICHENBACH R AY1 K AH0 N B AA2 K +REICHENBERG R AY1 K AH0 N B ER0 G +REICHENBERGER R AY1 K AH0 N B ER0 G ER0 +REICHER R AY1 K ER0 +REICHERT R AY1 K ER0 T +REICHHOLD R AY1 K HH OW2 L D +REICHHOLD(1) R AY1 K OW2 L D +REICHHOLD'S R AY1 K HH OW2 L D Z +REICHHOLD'S(1) R AY1 K OW2 L D Z +REICHL R AY1 K AH0 L +REICHLE R AY1 K AH0 L +REICHLER R AY1 K L ER0 +REICHLEY R AY1 K L IY0 +REICHLIN R AY1 K L IH0 N +REICHLING R AY1 K AH0 L IH0 NG +REICHLING(1) R AY1 K L IH0 NG +REICHMAN R AY1 K M AH0 N +REICHMANN R AY1 K M AH0 N +REICHMANNS R AY1 K M AH0 N Z +REICHMUTH R AY1 K M UW2 TH +REICHOW R AY1 K OW0 +REICHSTUHL R AY1 K S T UW0 L +REICHWEIN R AY1 K W AY2 N +REICK R IY1 K +REICKS R AY1 K S +REID R IY1 D +REID'S R 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IH0 N UW1 D +RENEWED(1) R IY0 N UW1 D +RENEWING R IH0 N UW1 IH0 NG +RENEWS R IH0 N UW1 Z +RENFRED R EH1 N F ER0 D +RENFREW R EH1 N F R UW0 +RENFRO R EH1 N F R OW0 +RENFROE R EH1 N F R OW0 +RENFROW R EH1 N F R AW0 +RENGEL R EH1 NG G AH0 L +RENGO R EH1 NG G OW0 +RENGO'S R EH1 NG G OW0 Z +RENICK R EH1 N IH0 K +RENIER R IY1 N IY0 ER0 +RENIN R IY1 N AH0 N +RENISON R EH1 N IH0 S AH0 N +RENITA R EH0 N IY1 T AH0 +RENK R EH1 NG K +RENKEN R EH1 NG K AH0 N +RENKO R EH1 NG K OW0 +RENMINBI R EH0 N M IH1 N B IY0 +RENN R EH1 N +RENNA R EH1 N AH0 +RENNARD R IH0 N AA1 R D +RENNE R EH1 N +RENNELS R EH1 N AH0 L Z +RENNER R EH1 N ER0 +RENNERT R EH1 N ER0 T +RENNET R EH1 N AH0 T +RENNICK R EH1 N IH0 K +RENNIE R EH1 N IY0 +RENNINGER R EH1 N IH0 NG ER0 +RENNO R EH1 N OW0 +RENNY R EH1 N IY0 +RENO R IY1 N OW0 +RENO'S R IY1 N OW0 Z +RENOIR R EH0 N W AA1 R +RENOIRS R EH0 N W AA1 R Z +RENOMINATE R IY0 N AO1 M IH0 N EY2 T +RENOMINATED R IY0 N AA1 M AH0 N EY2 T IH0 D +RENOMINATION R IY1 N AA2 M AH0 N EY1 SH AH0 N 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R G AH0 N IH0 Z EY1 SH AH0 N Z +REORGANIZE R IY0 AO1 R G AH0 N AY2 Z +REORGANIZED R IY0 AO1 R G AH0 N AY2 Z D +REORGANIZES R IY0 AO1 R G AH0 N AY2 Z IH0 Z +REORGANIZING R IY0 AO1 R G AH0 N AY2 Z IH0 NG +REORIENT R IY0 AO1 R IY0 EH0 N T +REORIENTATE R IY0 AO1 R IY0 EH0 N T EY0 T +REP R EH1 P +REP(1) R EH0 P R IY0 Z EH1 T AH0 T IH0 V +REP'S R EH1 P S +REP. R EH0 P R IY0 Z EH1 T AH0 T IH0 V +REPACK R IY0 P AE1 K +REPACKAGE R IY2 P AE1 K IH0 JH +REPACKAGED R IY1 P AE0 K IH0 JH D +REPACKAGES R IY2 P AE1 K IH0 JH IH0 Z +REPACKAGING R IY1 P AE0 K IH0 JH IH0 NG +REPACKED R IY0 P AE1 K T +REPAID R IY0 P EY1 D +REPAINT R IY0 P EY1 N T +REPAINTED R IY0 P EY1 N T IH0 D +REPAINTING R IY0 P EY1 N T IH0 NG +REPAIR R IH0 P EH1 R +REPAIRABLE R IH0 P EH1 R AH0 B AH0 L +REPAIRED R IH0 P EH1 R D +REPAIRED(1) R IY0 P EH1 R D +REPAIRING R IH0 P EH1 R IH0 NG +REPAIRING(1) R IY0 P EH1 R IH0 NG +REPAIRMAN R IH0 P EH1 R M AE2 N +REPAIRMAN(1) R IY0 P EH1 R M AE2 N +REPAIRMEN R IH0 P EH1 R M EH2 N +REPAIRS R IH0 P EH1 R Z +REPAIRS(1) R IY0 P EH1 R Z +REPAP R IY1 P AE0 P +REPARATION R EH2 P ER0 EY1 SH AH0 N +REPARATIONS R EH2 P ER0 EY1 SH AH0 N Z +REPARTEE R EH2 P ER0 T IY1 +REPASKY R IH0 P AA1 S K IY0 +REPASS R IY0 P AE1 S +REPATRIATE R IY0 P EY1 T R IY0 EY2 T +REPATRIATED R IY0 P EY1 T R IY0 EY2 T IH0 D +REPATRIATING R IY0 P EY1 T R IY0 EY2 T IH0 NG +REPATRIATION R IY0 P EY2 T R IY0 EY1 SH AH0 N +REPAY R IY0 P EY1 +REPAYABLE R IY0 P EY1 AH0 B AH0 L +REPAYING R IY0 P EY1 IH0 NG +REPAYMENT R IY0 P EY1 M AH0 N T +REPAYMENTS R IY0 P EY1 M AH0 N T S +REPAYS R IY2 P EY1 Z +REPEAL R IH0 P IY1 L +REPEAL(1) R IY0 P IY1 L +REPEALED R IH0 P IY1 L D +REPEALED(1) R IY0 P IY1 L D +REPEALING R IY0 P IY1 L IH0 NG +REPEALS R IY0 P IY1 L Z +REPEAT R IH0 P IY1 T +REPEAT(1) R IY0 P IY1 T +REPEATABLE R IH0 P IY1 T AH0 B AH0 L +REPEATED R IH0 P IY1 T IH0 D +REPEATED(1) R IY0 P IY1 T IH0 D +REPEATEDLY R IH0 P IY1 T IH0 D L IY0 +REPEATER R IH0 P IY1 T ER0 +REPEATERS R IH0 P IY1 T ER0 Z +REPEATING R IH0 P IY1 T IH0 NG +REPEATING(1) R IY0 P IY1 T IH0 NG +REPEATS R IH0 P IY1 T S +REPEATS(1) R IY0 P IY1 T S +REPEL R IH0 P EH1 L +REPELLED R AH0 P EH1 L D +REPELLED(1) R IH0 P EH1 L D +REPELLENT R IH0 P EH1 L AH0 N T +REPELLENTS R IH0 P EH1 L AH0 N T S +REPELLING R AH0 P EH1 L IH0 NG +REPELS R IH0 P EH1 L Z +REPENT R IH0 P EH1 N T +REPENTANCE R IH0 P EH1 N T AH0 N S +REPENTANT R IH0 P EH1 N T AH0 N T +REPENTED R IH0 P EH1 N T IH0 D +REPENTING R IH0 P EH1 N T IH0 NG +REPENTS R IH0 P EH1 N T S +REPERCUSSION R IY2 P ER0 K AH1 SH AH0 N +REPERCUSSION(1) R IY2 P R AH0 K AH1 SH AH0 N +REPERCUSSIONS R IY2 P ER0 K AH1 SH AH0 N Z +REPERCUSSIONS(1) R IY2 P R AH0 K AH1 SH AH0 N Z +REPERFUSION R EH2 P ER0 F Y UW1 ZH AH0 N +REPERTOIRE R EH1 P ER0 T W AA2 R +REPERTORY R EH1 P ER0 T AO2 R IY0 +REPETITION R EH2 P AH0 T IH1 SH AH0 N +REPETITIONS R EH2 P AH0 T IH1 SH AH0 N Z +REPETITIOUS R EH2 P AH0 T IH1 SH AH0 S +REPETITIVE R IH0 P EH1 T IH0 T IH0 V +REPETTI R EH0 P EH1 T IY0 +REPETTO R EH0 P EH1 T OW0 +REPH R EH1 F +REPHRASE R IY0 F R EY1 Z +REPINSKI R IH0 P IH1 N S K IY0 +REPKA R EH1 P K AH0 +REPKO R EH1 P K OW0 +REPLACE R IY2 P L EY1 S +REPLACE(1) ER0 P L EY1 S +REPLACEABLE R IY2 P L EY1 S AH0 B AH0 L +REPLACED R IY2 P L EY1 S T +REPLACEMENT R IH0 P L EY1 S M AH0 N T +REPLACEMENTS R IY0 P L EY1 S M AH0 N T S +REPLACES R IH0 P L EY1 S IH0 Z +REPLACING R IH0 P L EY1 S IH0 NG +REPLANT R IY0 P L AE1 N T +REPLANTED R IY0 P L AE1 N T IH0 D +REPLANTED(1) R IY0 P L AE1 N IH0 D +REPLANTING R IY0 P L AE1 N T IH0 NG +REPLAY R IY0 P L EY1 +REPLAYED R IY0 P L EY1 D +REPLAYING R IY0 P L EY1 IH0 NG +REPLAYS R IY0 P L EY1 Z +REPLENISH R IY0 P L EH1 N IH0 SH +REPLENISHED R IY0 P L EH1 N IH0 SH T +REPLENISHING R IY0 P L EH1 N IH0 SH IH0 NG +REPLENISHMENT R IH0 P L EH1 N IH0 SH M AH0 N T +REPLETE R IY0 P L IY1 T +REPLICA R EH1 P L IH0 K AH0 +REPLICAS R EH1 P L IH0 K AH0 Z +REPLICASE R EH1 P L IH0 K EY2 Z +REPLICATE R EH1 P L IH0 K EY2 T +REPLICATED R EH1 P L IH0 K EY2 T IH0 D +REPLICATES R EH1 P L IH0 K EY2 T S +REPLICATING R EH1 P L IH0 K EY2 T IH0 NG +REPLICATION R EH2 P L IH0 K EY1 SH AH0 N +REPLICATOR R EH1 P L IH0 K EY2 T ER0 +REPLICATORS R EH1 P L IH0 K EY2 T ER0 S +REPLIED R IH0 P L AY1 D +REPLIED(1) R IY0 P L AY1 D +REPLIES R IH0 P L AY1 Z +REPLIES(1) R IY0 P L AY1 Z +REPLIGEN R IH2 P L AY1 JH IH0 N +REPLIGEN'S R IH2 P L AY1 JH IH0 N Z +REPLOGLE R EH1 P L OW0 G AH0 L +REPLY R IH0 P L AY1 +REPLY(1) R IY0 P L AY1 +REPLYING R IH0 P L AY1 IH0 NG +REPLYING(1) R IY0 P L AY1 IH0 NG +REPO R IY1 P OW0 +REPONSE R IH0 P AA1 N S +REPORT R IY0 P AO1 R T +REPORT(1) R IH0 P AO1 R T +REPORT'S R IY0 P AO1 R T S +REPORT'S(1) R IH0 P AO1 R T S +REPORTABLE R IH0 P AO1 R T AH0 B AH0 L +REPORTAGE R IH0 P AO1 R T IH0 JH +REPORTED R IY2 P AO1 R T IH0 D +REPORTED(1) R IH0 P AO1 R T IH0 D +REPORTEDLY R IH0 P AO1 R T IH0 D L IY0 +REPORTEDLY(1) R IY0 P AO1 R T IH0 D L IY0 +REPORTER R IH0 P AO1 R T ER0 +REPORTER'S R IH0 P AO1 R T ER0 Z +REPORTERS R IH0 P AO1 R T ER0 Z +REPORTERS' R IH0 P AO1 R T ER0 Z +REPORTING R IY0 P AO1 R T IH0 NG +REPORTING(1) R IH0 P AO1 R T IH0 NG +REPORTORIAL R EH2 P ER0 T AO1 R IY0 AH0 L +REPORTS R IH0 P AO1 R T S +REPORTS(1) R IY0 P AO1 R T S +REPORTS' R IH0 P AO1 R T S +REPORTS'(1) R IY0 P AO1 R T S +REPOS R IY1 P OW2 Z +REPOSA R EH0 P OW1 S AH0 +REPOSE R IY0 P OW1 Z +REPOSITION R IY2 P AH0 Z IH1 SH AH0 N +REPOSITIONED R IY2 P AH0 Z IH1 SH AH0 N D +REPOSITIONING R IY2 P AH0 Z IH1 SH AH0 N IH0 NG +REPOSITORIES R IY0 P AA1 Z AH0 T AO2 R IY0 Z +REPOSITORY R IY0 P AA1 Z AH0 T AO2 R IY0 +REPOSSESS R IY2 P AH0 Z EH1 S +REPOSSESSED R IY2 P AH0 Z EH1 S T +REPOSSESSION R IY2 P AH0 Z EH1 SH AH0 N +REPOSSESSIONS R IY2 P AH0 Z EH1 SH AH0 N Z +REPP R EH1 P +REPPERT R EH1 P ER0 T +REPPOND R EH1 P AH0 N D +REPPUCCI R EH0 P UW1 CH IY0 +REPR R EH1 P ER0 +REPREHENSIBLE R EH2 P R IH0 HH EH1 N S AH0 B AH0 L +REPRESENT R EH2 P R AH0 Z EH1 N T +REPRESENT(1) R EH2 P R IH0 Z EH1 N T +REPRESENTATION R EH2 P R AH0 Z EH0 N T EY1 SH AH0 N +REPRESENTATIONAL R EH2 P R AH0 Z AH0 N T EY1 SH AH0 N AH0 L +REPRESENTATIONS R EH2 P R AH0 Z AH0 N T EY1 SH AH0 N Z +REPRESENTATIVE R EH2 P R AH0 Z EH1 N T AH0 T IH0 V +REPRESENTATIVE(1) R EH2 P R IH0 Z EH1 N T AH0 T IH0 V +REPRESENTATIVE(2) R EH2 P R AH0 Z EH1 N AH0 T IH0 V +REPRESENTATIVE(3) R EH2 P R IH0 Z EH1 N AH0 T IH0 V +REPRESENTATIVE'S R EH2 P R IH0 Z EH1 N T AH0 T IH0 V Z +REPRESENTATIVE'S(1) R EH2 P R IH0 Z EH1 N AH0 T IH0 V Z +REPRESENTATIVES R EH2 P R AH0 Z EH1 N T AH0 T IH0 V Z +REPRESENTATIVES(1) R EH2 P R IH0 Z EH1 N T AH0 T IH0 V Z +REPRESENTATIVES(2) R EH2 P R AH0 Z EH1 N AH0 T IH0 V Z +REPRESENTATIVES(3) R EH2 P R IH0 Z EH1 N AH0 T IH0 V Z +REPRESENTATIVES' R EH2 P R AH0 S EH1 N T AH0 T IH0 V Z +REPRESENTATIVES'(1) R EH2 P R AH0 S EH1 N AH0 T IH0 V Z +REPRESENTED R EH2 P R IH0 Z EH1 N T IH0 D +REPRESENTING R EH2 P R IH0 Z EH1 N T IH0 NG +REPRESENTS R EH2 P R IH0 Z EH1 N T S +REPRESS R IY0 P R EH1 S +REPRESSED R IY0 P R EH1 S T +REPRESSING R IY0 P R EH1 S IH0 NG +REPRESSION R IY0 P R EH1 SH AH0 N +REPRESSIONS R IY0 P R EH1 SH AH0 N Z +REPRESSIVE R IY0 P R EH1 S IH0 V +REPRICE R IY0 P R AY1 S +REPRICED R IY0 P R AY1 S T +REPRICING R IY0 P R AY1 S IH0 NG +REPRIEVE R IY0 P R IY1 V +REPRIMAND R EH1 P R AH0 M AE2 N D +REPRIMANDED R EH1 P R AH0 M AE2 N D IH0 D +REPRIMANDS R EH1 P R AH0 M AE2 N D Z +REPRINT R IY0 P R IH1 N T +REPRINTED R IY0 P R IH1 N T IH0 D +REPRINTING R IY0 P R IH1 N T IH0 NG +REPRINTS R IY0 P R IH1 N T S +REPRISAL R IY0 P R AY1 Z AH0 L +REPRISALS R IH0 P R AY1 Z AH0 L Z +REPRISALS(1) R IY0 P R AY1 Z AH0 L Z +REPRISE R IH0 P R AY1 Z +REPRISE(1) R IH0 P R IY1 Z +REPROACH R IY0 P R OW1 CH +REPROBATE R EH1 P R AO0 B EY0 T +REPROCESS R IY0 P R AO1 S EH0 S +REPROCESSED R IY0 P R AO1 S EH0 S T +REPROCESSING R IY0 P R AO1 S EH0 S IH0 NG +REPRODUCE R IY2 P R AH0 D UW1 S +REPRODUCED R IY2 P R AH0 D UW1 S T +REPRODUCES R IY2 P R AH0 D UW1 S IH0 Z +REPRODUCING R IY2 P R AH0 D UW1 S IH0 NG +REPRODUCTION R IY2 P R AH0 D AH1 K SH AH0 N +REPRODUCTIONS R IY2 P R AH0 D AH1 K SH AH0 N Z +REPRODUCTIVE R IY2 P R AH0 D AH1 K T IH0 V +REPROGENETICS R IY1 P R AO2 JH AH0 N EH2 T IH0 K S +REPROGRAM R IY0 P R OW1 G R AE2 M +REPROGRAMMED R IY0 P R OW1 G R AE2 M D +REPROGRAMMING R IY0 P R OW1 G R AE2 M IH0 NG +REPROGRAMS R IY0 P R OW1 G R AE2 M Z +REPROGRAPH R EH1 P R OW0 G R AE2 F +REPROGRAPHIC R EH2 P R OW0 G R AE1 F IH0 K +REPROGRAPHICS R EH2 P R OW0 G R AE1 F IH0 K S +REPS R EH1 P S +REPSHER R EH1 P SH ER0 +REPSOL R EH1 P S AA0 L +REPTILE R EH1 P T AY0 L +REPTILES R EH1 P T AY0 L Z +REPTILIAN R EH0 P T IH1 L Y AH0 N +REPTILIANS R EH0 P T IH1 L Y AH0 N Z +REPUBLIC R IY0 P AH1 B L AH0 K +REPUBLIC(1) R IY0 P AH1 B L IH0 K +REPUBLIC'S R IY0 P AH1 B L IH0 K S +REPUBLICA R IH0 P AH1 B L IH0 K AH0 +REPUBLICAN R IH0 P AH1 B L IH0 K AH0 N +REPUBLICAN(1) R IY0 P AH1 B L AH0 K AH0 N +REPUBLICAN(2) R IY0 P AH1 B L IH0 K AH0 N +REPUBLICAN'S R IY0 P AH1 B L IH0 K AH0 N Z +REPUBLICANISM R IH0 P AH1 B L IH0 K AH0 N IH2 Z AH0 M +REPUBLICANS R IH0 P AH1 B L IH0 K AH0 N Z +REPUBLICANS(1) R IY0 P AH1 B L AH0 K AH0 N Z +REPUBLICANS(2) R IY0 P AH1 B L IH0 K AH0 N Z +REPUBLICANS' R IH0 P AH1 B L IH0 K AH0 N Z +REPUBLICANS'(1) R IY0 P AH1 B L IH0 K AH0 N Z +REPUBLICBANK R IY0 P AH1 B L IH0 K B AE2 NG K +REPUBLICBANK'S R IY0 P AH1 B L IH0 K B AE2 NG K S +REPUBLICS R IY0 P AH1 B L IH0 K S +REPUBLIKA R IH0 P AH1 B L IH0 K AH0 +REPUDIATE R IY0 P Y UW1 D IY0 EY2 T +REPUDIATED R IY0 P Y UW1 D IY0 EY2 T IH0 D +REPUDIATES R IY0 P Y UW1 D IY0 EY2 T S +REPUDIATING R IY0 P Y UW1 D IY0 EY2 T IH0 NG +REPUDIATION R IH0 P Y UW2 D IY0 EY1 SH AH0 N +REPUGNANT R IH0 P AH1 G N AH0 N T +REPUGNANT(1) R IY0 P AH1 G N AH0 N T +REPULSE R IY0 P AH1 L S +REPULSED R IY0 P AH1 L S T +REPULSING R IY0 P AH1 L S IH0 NG +REPULSIVE R IY0 P AH1 L S IH0 V +REPURCHASE R IY0 P ER1 CH AH0 S +REPURCHASED R IY0 P ER1 CH AH0 S T +REPURCHASES R IY0 P ER1 CH AH0 S IH0 Z +REPURCHASING R IY0 P ER1 CH AH0 S IH0 NG +REPUTABLE R EH1 P Y AH0 T AH0 B AH0 L +REPUTATION R EH2 P Y AH0 T EY1 SH AH0 N +REPUTATIONS R EH2 P Y AH0 T EY1 SH AH0 N Z +REPUTE R IY0 P Y UW1 T +REPUTED R IH0 P Y UW1 T IH0 D +REPUTED(1) R IY0 P Y UW1 T IH0 D +REPUTEDLY R IH0 P Y UW1 T IH0 D L IY0 +REQUA R EY1 K W AH0 +REQUALIFY R IY2 K W AA1 L AH0 F AY2 +REQUEST R IH0 K W EH1 S T +REQUEST(1) R IY0 K W EH1 S T +REQUESTED R IH0 K W EH1 S T IH0 D +REQUESTED(1) R IY0 K W EH1 S T IH0 D +REQUESTER R IH0 K W EH1 S T ER0 +REQUESTING R IH0 K W EH1 S T IH0 NG +REQUESTING(1) R IY0 K W EH1 S T IH0 NG +REQUESTS R IH0 K W EH1 S T S +REQUESTS(1) R IY0 K W EH1 S T S +REQUIEM R EH1 K W IY0 AH0 M +REQUIRE R IY2 K W AY1 ER0 +REQUIRE(1) R IY0 K W AY1 R +REQUIRE(2) R IH0 K W AY1 ER0 +REQUIRED R IY0 K W AY1 ER0 D +REQUIRED(1) R IY0 K W AY1 R D +REQUIREMENT R IH0 K W AY1 R M AH0 N T +REQUIREMENTS R IH0 K W AY1 R M AH0 N T S +REQUIRES R IY0 K W AY1 ER0 Z +REQUIRES(1) R IY0 K W AY1 R Z +REQUIRING R IY0 K W AY1 ER0 IH0 NG +REQUIRING(1) R IY0 K W AY1 R IH0 NG +REQUISITE R EH1 K W AH0 Z AH0 T +REQUISITES R EH1 K W AH0 Z AH0 T S +REQUISITION R EH2 K W AH0 Z IH1 SH AH0 N +REQUISITIONED R EH2 K W AH0 Z IH1 SH AH0 N D +REREAD R IY1 R IY1 D +REREADING R IY1 R IY1 D IH0 NG +REREGULATE R IY0 R EH1 G Y AH0 L EY2 T +REREGULATION R IY0 R EH0 G Y AH0 L EY1 SH AH0 N +REROUTE R IY0 R UW1 T +REROUTE(1) R IY0 R AW1 T +REROUTED R IY0 R UW1 T IH0 D +REROUTED(1) R IY0 R AW1 T IH0 D +REROUTING R IY0 R UW1 T IH0 NG +REROUTING(1) R IY0 R AW1 T IH0 NG +RERUN R IY1 R AH1 N +RERUNNING R IY1 R AH1 N IH0 NG +RERUNS R IY1 R AH1 N Z +RES R EY1 Z +RESALE R IY1 S EY2 L +RESALES R IY1 S EY2 L Z +RESCH R EH1 SH +RESCHEDULE R IY0 S K EH1 JH UW0 L +RESCHEDULED R IY0 S K EH1 JH UW0 L D +RESCHEDULING R IY0 S K EH1 JH UW0 L IH0 NG +RESCHEDULINGS R IY0 SH K EH1 JH UW0 L IH0 NG Z +RESCHKE R EH1 SH K +RESCIGNO R EH0 S CH IY1 G N OW0 +RESCIND R IH0 S IH1 N D +RESCIND(1) R IY0 S IH1 N D +RESCINDED R IH0 S IH1 N D IH0 D +RESCINDED(1) R IY0 S IH1 N D IH0 D +RESCINDING R IH0 S IH1 N D IH0 NG +RESCINDS R IH0 S IH1 N D Z +RESCINDS(1) R IY0 S IH1 N D Z +RESCISSION R IH0 S IH1 ZH AH0 N +RESCISSIONS R IH0 S IH1 ZH AH0 N Z +RESCUE R EH1 S K Y UW0 +RESCUED R EH1 S K Y UW0 D +RESCUER R EH1 S K Y UW2 ER0 +RESCUERS R EH1 S K Y UW2 ER0 Z +RESCUES R EH1 S K Y UW2 Z +RESCUING R EH1 S K Y UW0 IH0 NG +RESDEL R EH1 Z D EH2 L +RESEACHERS R IY0 S ER1 CH ER0 Z +RESEAL R IY0 S IY1 L +RESEALABLE R IY0 S IY1 L AH0 B AH0 L +RESEALED R IY0 S IY1 L D +RESEALS R IY0 S IY1 L Z +RESEARCH R IY0 S ER1 CH +RESEARCH(1) R IY1 S ER0 CH +RESEARCH'S R IY0 S ER1 CH IH0 Z +RESEARCHED R IY0 S ER1 CH T +RESEARCHER R IY1 S ER0 CH ER0 +RESEARCHERS R IY1 S ER0 CH ER0 Z +RESEARCHERS' R IY1 S ER0 CH ER0 Z +RESEARCHES R IY0 S ER1 CH IH0 Z +RESEARCHING R IY0 S ER1 CH IH0 NG +RESECTION R IY2 S EH1 K SH AH0 N +RESEDA R EH0 S EY1 D AH0 +RESEED R IY0 S IY1 D +RESELL R IY0 S EH1 L +RESELLER R IY0 S EH1 L ER0 +RESELLERS R IY0 S EH1 L ER0 Z +RESELLING R IY0 S EH1 L IH0 NG +RESELLS R IY0 S EH1 L Z +RESEMBLANCE R IH0 Z EH1 M B L AH0 N S +RESEMBLANCE(1) R IY0 Z EH1 M B L AH0 N S +RESEMBLANCES R IY0 Z EH1 M B L AH0 N S AH0 Z +RESEMBLE R IH0 Z EH1 M B AH0 L +RESEMBLE(1) R IY0 Z EH1 M B AH0 L +RESEMBLED R IH0 Z EH1 M B AH0 L D +RESEMBLED(1) R IY0 Z EH1 M B AH0 L D +RESEMBLES R IH0 Z EH1 M B AH0 L Z +RESEMBLES(1) R IY0 Z EH1 M B AH0 L Z +RESEMBLING R IH0 Z EH1 M B AH0 L IH0 NG +RESEMBLING(1) R IY0 Z EH1 M B AH0 L IH0 NG +RESEMBLING(2) R IY0 Z EH1 M B L IH0 NG +RESENDE R IH0 S EH1 N D EY0 +RESENDES R EH1 S IH0 N D Z +RESENDEZ R EY0 S EY1 N D EH0 Z +RESENDIZ R IH0 S EH1 N D IH0 Z +RESENT R IH0 Z EH1 N T +RESENT(1) R IY0 Z EH1 N T +RESENTED R IH0 Z EH1 N T IH0 D +RESENTED(1) R IY0 Z EH1 N T IH0 D +RESENTFUL R IH0 Z EH1 N T F AH0 L +RESENTING R IH0 Z EH1 N T IH0 NG +RESENTING(1) R IY0 Z EH1 N T IH0 NG +RESENTING(2) R IH0 Z EH1 N IH0 NG +RESENTING(3) R IY0 Z EH1 N IH0 NG +RESENTMENT R IH0 Z EH1 N T M AH0 N T +RESENTMENT(1) R IH0 Z EH1 N M AH0 N T +RESENTMENTS R IH0 Z EH1 N T M AH0 N T S +RESENTMENTS(1) R IH0 Z EH1 N M AH0 N T S +RESENTS R IH0 Z EH1 N T S +RESER R IY1 Z ER0 +RESERVATION R EH2 Z ER0 V EY1 SH AH0 N +RESERVATIONIST R EH2 Z ER0 V EY1 SH AH0 N IH0 S T +RESERVATIONISTS R EH2 Z ER0 V EY1 SH AH0 N IH0 S T S +RESERVATIONS R EH2 Z ER0 V EY1 SH AH0 N Z +RESERVE R IH0 Z ER1 V +RESERVE(1) R IY0 Z ER1 V +RESERVE'S R IH0 Z ER1 V Z +RESERVE'S(1) R IY0 Z ER1 V Z +RESERVED R IH0 Z ER1 V D +RESERVED(1) R IY0 Z ER1 V D +RESERVEESE R EH2 Z ER0 V IY1 S +RESERVES R IH0 Z ER1 V Z +RESERVES(1) R IY0 Z ER1 V Z +RESERVING R IH0 Z ER1 V IH0 NG +RESERVING(1) R IY0 Z ER1 V IH0 NG +RESERVIST R IH0 Z ER1 V IH0 S T +RESERVISTS R IH0 Z ER1 V IH0 S T S +RESERVOIR R EH1 Z AH0 V W AA2 R +RESERVOIR(1) R EH1 Z ER0 V W AA2 R +RESERVOIRS R EH1 Z ER0 V W AA2 R Z +RESET R IY0 S EH1 T +RESET(1) R IY1 S EH0 T +RESETAR R EH1 S IH0 T ER0 +RESETING R IY0 S EH1 T IH0 NG +RESETING(1) R IY1 S EH0 T IH0 NG +RESETS R IY0 S EH1 T S +RESETS(1) R IY1 S EH0 T S +RESETTABLE R IY0 S EH1 T AH0 B AH0 L +RESETTLE R IY0 S EH1 T AH0 L +RESETTLED R IY0 S EH1 T AH0 L D +RESETTLEMENT R IY0 S EH1 T AH0 L M AH0 N T +RESH R EH1 SH +RESHAPE R IY0 SH EY1 P +RESHAPED R IY0 SH EY1 P T +RESHAPING R IY0 SH EY1 P IH0 NG +RESHOT R IY0 SH AO1 T +RESHUFFLE R IY0 SH AH1 F AH0 L +RESHUFFLED R IY0 SH AH1 F AH0 L D +RESHUFFLING R IY0 SH AH1 F AH0 L IH0 NG +RESHUFFLING(1) R IY0 SH AH1 F L IH0 NG +RESIDE R IH0 Z AY1 D +RESIDE(1) R IY0 Z AY1 D +RESIDED R IH0 Z AY1 D IH0 D +RESIDENCE R EH1 Z IH0 D AH0 N S +RESIDENCES R EH1 Z IH0 D AH0 N S IH0 Z +RESIDENCIES R EH1 Z IH0 D EH2 N S IY0 Z +RESIDENCY R EH1 Z IH0 D AH0 N S IY0 +RESIDENT R EH1 Z IH0 D AH0 N T +RESIDENT'S R EH1 Z IH0 D AH0 N T S +RESIDENTIAL R EH2 Z IH0 D EH1 N SH AH0 L +RESIDENTS R EH1 Z IH0 D AH0 N T S +RESIDENTS' R EH1 Z IH0 D AH0 N T S +RESIDES R IH0 Z AY1 D Z +RESIDES(1) R IY0 Z AY1 D Z +RESIDING R IH0 Z AY1 D IH0 NG +RESIDING(1) R IY0 Z AY1 D IH0 NG +RESIDUAL R IH0 Z IH1 JH UW0 AH0 L +RESIDUALS R IH0 Z IH1 JH UW0 AH0 L Z +RESIDUE R EH1 Z AH0 D UW2 +RESIDUES R EH1 Z AH0 D UW2 Z +RESIGN R IH0 Z AY1 N +RESIGN(1) R IY0 Z AY1 N +RESIGN(2) R IY0 S AY1 N +RESIGNATION R EH2 Z AH0 G N EY1 SH AH0 N +RESIGNATION(1) R EH2 Z IH0 G N EY1 SH AH0 N +RESIGNATIONS R EH2 Z IH0 G N EY1 SH AH0 N Z +RESIGNED R IH0 Z AY1 N D +RESIGNED(1) R IY0 Z AY1 N D +RESIGNED(2) R IY0 S AY1 N D +RESIGNEE R EH2 Z IH0 G N IY1 +RESIGNEES R EH2 Z IH0 G N IY1 Z +RESIGNING R IH0 Z AY1 N IH0 NG +RESIGNING(1) R IY0 Z AY1 N IH0 NG +RESIGNING(2) R IY0 S AY1 N IH0 NG +RESIGNS R IH0 Z AY1 N Z +RESIGNS(1) R IY0 Z AY1 N Z +RESIGNS(2) R IY0 S AY1 N Z +RESILIENCE R IH0 Z IH1 L IY0 AH0 N S +RESILIENCE(1) R IH0 Z IH1 L Y AH0 N S +RESILIENCY R IH0 Z IH1 L Y AH0 N S IY0 +RESILIENT R IH0 Z IH1 L Y AH0 N T +RESIN R EH1 Z AH0 N +RESIN(1) R EH1 Z IH0 N +RESINS R EH1 Z AH0 N Z +RESINS(1) R EH1 Z IH0 N Z +RESIST R IH0 Z IH1 S T +RESIST(1) R IY0 Z IH1 S T +RESISTANCE R IH0 Z IH1 S T AH0 N S +RESISTANCE(1) R IY0 Z IH1 S T AH0 N S +RESISTANT R IH0 Z IH1 S T AH0 N T +RESISTANT(1) R IY0 Z IH1 S T AH0 N T +RESISTED R IH0 Z IH1 S T IH0 D +RESISTED(1) R IY0 Z IH1 S T IH0 D +RESISTENCE R IH0 Z IH1 S T AH0 N S +RESISTING R IH0 Z IH1 S T IH0 NG +RESISTING(1) R IY0 Z IH1 S T IH0 NG +RESISTIVENESS R IH2 Z IH1 S T IH2 V N AH0 S +RESISTOR R IH0 Z IH1 S T ER0 +RESISTORS R IH0 Z IH1 S T ER0 Z +RESISTS R IH0 Z IH1 S T S +RESISTS(1) R IY0 Z IH1 S T S +RESISTS(2) R IH0 Z IH1 S +RESISTS(3) R IY0 Z IH1 S +RESKE R EH1 S K +RESLER R EH1 Z L ER0 +RESNAIS R EH0 S N EY1 +RESNER R EH1 S N ER0 +RESNICK R EH1 Z N IH0 K +RESNICK'S R EH1 Z N IH0 K S +RESNIK R EH1 S N IH0 K +RESO R IH1 Z OW0 +RESO(1) R IY1 Z OW0 +RESO(2) R IH1 S OW0 +RESO(3) R IY1 S OW0 +RESO'S R IY1 S OW0 Z +RESO'S(1) R IY1 Z OW0 Z +RESO'S(2) R IH1 S OW0 Z +RESO'S(3) R IH1 Z OW0 Z +RESOLD R IY0 S OW1 L D +RESOLUTE R EH1 Z AH0 L UW2 T +RESOLUTELY R EH1 S AH0 L UW2 T L IY0 +RESOLUTELY(1) R EH1 Z AH0 L UW2 T L IY0 +RESOLUTION R EH2 Z AH0 L UW1 SH AH0 N +RESOLUTION'S R EH2 Z AH0 L UW1 SH AH0 N Z +RESOLUTIONS R EH2 Z AH0 L UW1 SH AH0 N Z +RESOLVE R IY0 Z AA1 L V +RESOLVED R IY0 Z AA1 L V D +RESOLVES R IY0 Z AA1 L V Z +RESOLVING R IY0 Z AA1 L V IH0 NG +RESONANCE R EH1 Z AH0 N AH0 N S +RESONANT R EH1 Z AH0 N AH0 N T +RESONATE R EH1 Z AH0 N EY2 T +RESONATED R EH1 Z AH0 N EY2 T IH0 D +RESONATES R EH1 Z AH0 N EY2 T S +RESONATING R EH1 Z AH0 N EY2 T IH0 NG +RESORT R IH0 Z AO1 R T +RESORT(1) R IY0 Z AO1 R T +RESORT(2) R IY0 S AO1 R T +RESORT'S R IH0 Z AO1 R T S +RESORTED R IH0 Z AO1 R T IH0 D +RESORTED(1) R IY0 Z AO1 R T IH0 D +RESORTED(2) R IY0 S AO1 R T IH0 D +RESORTING R IH0 Z AO1 R T IH0 NG +RESORTING(1) R IY0 Z AO1 R T IH0 NG +RESORTING(2) R IY0 S AO1 R T IH0 NG +RESORTS R IH0 Z AO1 R T S +RESORTS(1) R IY0 Z AO1 R T S +RESORTS(2) R IY0 S AO1 R T S +RESORTS' R IH0 Z AO1 R T S +RESOUND R IY2 S AW1 N D +RESOUND(1) R IY2 Z AW1 N D +RESOUNDING R IY0 S AW1 N D IH0 NG +RESOUNDINGLY R IH0 Z AW1 N D IH0 NG L IY0 +RESOURCE R IY1 S AO0 R S +RESOURCEFUL R IY0 S AO1 R S F AH0 L +RESOURCEFULNESS R IY0 S AO1 R S F AH0 L N AH0 S +RESOURCES R IY1 S AO0 R S IH0 Z +RESOURCES' R IY1 S AO0 R S IH0 Z +RESPEAK R IY2 S P IY1 K +RESPECT R IH0 S P EH1 K T +RESPECT(1) R IY0 S P EH1 K T +RESPECTABILITY R IY0 S P EH2 K T AH0 B IH1 L IH0 T IY0 +RESPECTABLE R IH0 S P EH1 K T AH0 B AH0 L +RESPECTABLE(1) R IY0 S P EH1 K T AH0 B AH0 L +RESPECTABLY R IY0 S P EH1 K T AH0 B L IY0 +RESPECTED R IH0 S P EH1 K T IH0 D +RESPECTED(1) R IY0 S P EH1 K T IH0 D +RESPECTFUL R IH0 S P EH1 K T F AH0 L +RESPECTFULLY R IH0 S P EH1 K T F AH0 L IY0 +RESPECTING R IY0 S P EH1 K T IH0 NG +RESPECTIVE R IH0 S P EH1 K T IH0 V +RESPECTIVE(1) R IY0 S P EH1 K T IH0 V +RESPECTIVELY R IH0 S P EH1 K T IH0 V L IY0 +RESPECTS R IH0 S P EH1 K T S +RESPECTS(1) R IY0 S P EH1 K T S +RESPECTS(2) R AH0 S P EH1 K S +RESPECTS(3) R IY0 S P EH1 K S +RESPESS R EY1 S P IH0 S +RESPIRATION R EH2 S P ER0 EY1 SH AH0 N +RESPIRATOR R EH1 S P ER0 EY2 T ER0 +RESPIRATORS R EH1 S P ER0 EY2 T ER0 Z +RESPIRATORY R EH1 S P ER0 AH0 T AO2 R IY0 +RESPIRONIC R EH2 S P ER0 AA1 N IH0 K +RESPIRONICS R EH2 S ER0 AA1 N IH0 K S +RESPITE R EH1 S P IH0 T +RESPLENDENT R IY0 S P L EH1 N D AH0 N T +RESPOND R IH0 S P AA1 N D +RESPOND(1) R IY0 S P AA1 N D +RESPONDED R IH0 S P AA1 N D IH0 D +RESPONDED(1) R IY0 S P AA1 N D AH0 D +RESPONDED(2) R IY0 S P AA1 N D IH0 D +RESPONDENT R IH0 S P AA1 N D AH0 N T +RESPONDENTS R IH0 S P AA1 N D AH0 N T S +RESPONDENTS' R IH0 S P AA1 N D AH0 N T S +RESPONDER R IH0 S P AA1 N D ER0 +RESPONDERS R IH0 S P AA1 N D ER0 Z +RESPONDING R IH0 S P AA1 N D IH0 NG +RESPONDING(1) R IY0 S P AA1 N D IH0 NG +RESPONDS R IH0 S P AA1 N D Z +RESPONDS(1) R IY0 S P AA1 N D Z +RESPONSE R IH0 S P AA1 N S +RESPONSE(1) R IY0 S P AA1 N S +RESPONSES R IH0 S P AA1 N S IH0 Z +RESPONSES(1) R IY0 S P AA1 N S AH0 Z +RESPONSES(2) R IY0 S P AA1 N S IH0 Z +RESPONSIBILITIES R IY0 S P AA2 N S AH0 B IH1 L AH0 T IY0 Z +RESPONSIBILITY R IY0 S P AA2 N S AH0 B IH1 L AH0 T IY0 +RESPONSIBLE R IY0 S P AA1 N S AH0 B AH0 L +RESPONSIBLY R IH0 S P AA1 N S AH0 B L IY0 +RESPONSIVE R IH0 S P AA1 N S IH0 V +RESPONSIVENESS R IH0 S P AA1 N S IH0 V N AH0 S +RESPRESS R EH1 S P R IH0 S +RESS R EH1 S +RESSA R EH1 S AH0 +RESSA'S R EH1 S AH0 Z +RESSEGUIE R EH1 S IH0 G W IY0 +RESSEL R EH1 S AH0 L +RESSLER R EH1 S L ER0 +REST R EH1 S T +RESTAGE R IY0 S T EY1 JH +RESTAGED R IY0 S T EY1 JH D +RESTAINO R EH0 S T AA0 IY1 N OW0 +RESTART R IY0 S T AA1 R T +RESTARTED R IY0 S T AA1 R T IH0 D +RESTARTING R IY0 S T AA1 R T IH0 NG +RESTATE R IY0 S T EY1 T +RESTATED R IY0 S T EY1 T IH0 D +RESTATEMENT R IY0 S T EY1 T M AH0 N T +RESTATEMENTS R IY0 S T EY1 T M AH0 N T S +RESTATES R IY0 S T EY1 T S +RESTATING R IY0 S T EY1 T IH0 NG +RESTAURANT R EH1 S T ER0 AA2 N T +RESTAURANT(1) R EH1 S T R AA2 N T +RESTAURANT'S R EH1 S T ER0 AA2 N T S +RESTAURANT'S(1) R EH1 S T R AA2 N T S +RESTAURANTEUR R EH0 S T R AA0 N T ER1 +RESTAURANTEURS R EH0 S T R AA0 N T ER1 Z +RESTAURANTS R EH1 S T ER0 AA2 N T S +RESTAURANTS(1) R EH1 S T R AA2 N T S +RESTAURANTS' R EH1 S T ER0 AA2 N T S +RESTAURANTS'(1) R EH1 S T R AA2 N T S +RESTAURATEUR R EH2 S T ER0 AH0 T ER1 +RESTAURATEUR(1) R EH2 S T R AH0 T ER1 +RESTAURATEURS R EH2 S T ER0 AH0 T ER1 Z +RESTAURATEURS(1) R EH2 S T R AH0 T ER1 Z +RESTED R EH1 S T AH0 D +RESTED(1) R EH1 S T IH0 D +RESTER R EH1 S T ER0 +RESTFUL R EH1 S T F AH0 L +RESTING R EH1 S T IH0 NG +RESTITUTE R EH1 S T IH0 T UW2 T +RESTITUTION R EH2 S T IH0 T UW1 SH AH0 N +RESTIVE R EH1 S T IH0 V +RESTIVENESS R EH1 S T IH0 V N AH0 S +RESTIVO R EH0 S T IY1 V OW0 +RESTLESS R EH1 S T L AH0 S +RESTLESSLY R EH1 S T L AH0 S L IY0 +RESTLESSNESS R EH1 S T L AH0 S N AH0 S +RESTO R EH1 S T OW0 +RESTOCK R IY0 S T AA1 K +RESTOCKED R IY0 S T AA1 K T +RESTOCKING R IY0 S T AA1 K IH0 NG +RESTON R EH1 S T AH0 N +RESTORATION R EH2 S T ER0 EY1 SH AH0 N +RESTORATIONS R EH2 S T ER0 EY1 SH AH0 N Z +RESTORATIVE R AH0 S T AO1 R AH0 T IH0 V +RESTORE R IH0 S T AO1 R +RESTORED R IH0 S T AO1 R D +RESTORER R IH0 S T AO1 R ER0 +RESTORES R IH0 S T AO1 R Z +RESTORING R IH0 S T AO1 R IH0 NG +RESTRAIN R IY0 S T R EY1 N +RESTRAINED R IY0 S T R EY1 N D +RESTRAINING R IY0 S T R EY1 N IH0 NG +RESTRAINS R IY0 S T R EY1 N Z +RESTRAINT R IH0 S T R EY1 N T +RESTRAINT(1) R IY0 S T R EY1 N T +RESTRAINTS R IH0 S T R EY1 N T S +RESTRAINTS(1) R IY0 S T R EY1 N T S +RESTREPO R EH0 S T R EH1 P OW0 +RESTRICT R IY0 S T R IH1 K T +RESTRICTED R IY0 S T R IH1 K T AH0 D +RESTRICTED(1) R IY0 S T R IH1 K T IH0 D +RESTRICTING R IY0 S T R IH1 K T IH0 NG +RESTRICTION R IY0 S T R IH1 K SH AH0 N +RESTRICTIONS R IY0 S T R IH1 K SH AH0 N Z +RESTRICTIVE R IY0 S T R IH1 K T IH0 V +RESTRICTIVENESS R AH0 S T R IH1 K T IH0 V N AH0 S +RESTRICTS R IY0 S T R IH1 K T S +RESTROOM R EH1 S T R UW2 M +RESTROOMS R EH1 S T R UW2 M Z +RESTRUCTURE R IY0 S T R AH1 K CH ER0 +RESTRUCTURED R IY0 S T R AH1 K CH ER0 D +RESTRUCTURES R IY0 S T R AH1 K CH ER0 Z +RESTRUCTURING R IY0 S T R AH1 K CH ER0 IH0 NG +RESTRUCTURINGS R IY0 S T R AH1 K CH ER0 IH0 NG Z +RESTS R EH1 S T S +RESTYLE R IY0 S T AY1 L +RESTYLED R IY0 S T AY1 L D +RESUBMIT R IY2 S AH0 B M IH1 T +RESUBMITTED R IY2 S AH0 B M IH1 T IH0 D +RESUBMITTING R IY2 S AH0 B M IH1 T IH0 NG +RESULT R IH0 Z AH1 L T +RESULT(1) R IY0 Z AH1 L T +RESULTANT R IY0 Z AH1 L T AH0 N T +RESULTED R IH0 Z AH1 L T IH0 D +RESULTED(1) R IY0 Z AH1 L T AH0 D +RESULTED(2) R IY0 Z AH1 L T IH0 D +RESULTING R IH0 Z AH1 L T IH0 NG +RESULTING(1) R IY0 Z AH1 L T IH0 NG +RESULTS R IH0 Z AH1 L T S +RESULTS(1) R IY0 Z AH1 L T S +RESUME R IH0 Z UW1 M +RESUME(1) R IY0 Z UW1 M +RESUME(2) R EH1 Z AH0 M EY2 +RESUMED R IH0 Z UW1 M D +RESUMED(1) R IY0 Z UW1 M D +RESUMES R IH0 Z UW1 M Z +RESUMES(1) R IY0 Z UW1 M Z +RESUMES(2) R EH1 Z AH0 M EY2 Z +RESUMING R IH0 Z UW1 M IH0 NG +RESUMING(1) R IY0 Z UW1 M IH0 NG +RESUMPTION R IH0 Z AH1 M P SH AH0 N +RESUMPTION(1) R IY0 Z AH1 M P SH AH0 N +RESUMPTION(2) R IH0 Z AH1 M SH AH0 N +RESUMPTION(3) R IY0 Z AH1 M SH AH0 N +RESUPPLY R IY0 S AH0 P L AY1 +RESURFACE R IY0 S ER1 F AH0 S +RESURFACED R IY0 S ER1 F AH0 S T +RESURFACING R IY0 S ER1 F AH0 S IH0 NG +RESURGENCE R IY0 S ER1 JH AH0 N S +RESURGENCY R IH0 S ER1 JH AH0 N S IY0 +RESURGENCY(1) R IY0 S ER1 JH AH0 N S IY0 +RESURGENT R IH0 S ER1 JH AH0 N T +RESURGENT(1) R IY0 S ER1 JH AH0 N T +RESURGING R IY0 S ER1 JH IH0 NG +RESURRECT R EH2 Z ER0 EH1 K T +RESURRECTED R EH2 Z ER0 EH1 K T IH0 D +RESURRECTING R EH2 Z ER0 EH1 K T IH0 NG +RESURRECTION R EH2 Z ER0 EH1 K SH AH0 N +RESUSCITATE R IH0 S AH1 S IH0 T EY2 T +RESUSCITATE(1) R IY0 S AH1 S IH0 T EY2 T +RESUSCITATED R IH0 S AH1 S IH0 T EY2 T IH0 D +RESUSCITATING R IH0 S AH1 S IH0 T EY2 T IH0 NG +RESUSCITATION R IH0 S AH2 S IH0 T EY1 SH AH0 N +RESVERATROL R EH0 S V ER1 AH0 T R AO0 L +RET R EH1 T +RETA R EH1 T AH0 +RETABLOS R IY0 T AE1 B L OW0 S +RETAIL R IY1 T EY2 L +RETAILED R IY1 T EY2 L D +RETAILER R IY1 T EY2 L ER0 +RETAILER'S R IY1 T EY2 L ER0 Z +RETAILERS R IY1 T EY2 L ER0 Z +RETAILERS' R IY1 T EY2 L ER0 Z +RETAILING R IY1 T EY2 L IH0 NG +RETAILING'S R IY1 T EY2 L IH0 NG Z +RETAILS R IY1 T EY2 L Z +RETAIN R IH0 T EY1 N +RETAIN(1) R IY0 T EY1 N +RETAINED R IH0 T EY1 N D +RETAINED(1) R IY0 T EY1 N D +RETAINER R IH0 T EY1 N ER0 +RETAINER(1) R IY0 T EY1 N ER0 +RETAINERS R IH0 T EY1 N ER0 Z +RETAINING R IH0 T EY1 N IH0 NG +RETAINING(1) R IY0 T EY1 N IH0 NG +RETAINS R IH0 T EY1 N Z +RETAINS(1) R IY0 T EY1 N Z +RETAKE R IY1 T EY1 K +RETAKE(1) R IY0 T EY1 K +RETAKEN R IY0 T EY1 K AH0 N +RETAKING R IY0 T EY1 K IH0 NG +RETALIATE R IH0 T AE1 L IY0 EY2 T +RETALIATE(1) R IY0 T AE1 L IY0 EY2 T +RETALIATED R IH0 T AE1 L IY0 EY2 T IH0 D +RETALIATED(1) R IY0 T AE1 L IY0 EY2 T IH0 D +RETALIATING R IH0 T AE1 L IY0 EY2 T IH0 NG +RETALIATION R IY0 T AE2 L IY0 EY1 SH AH0 N +RETALIATORY R IY0 T AE1 L Y AH0 T AO2 R IY0 +RETANA R EH0 T AE1 N AH0 +RETARD R IH0 T AA1 R D +RETARD(1) R IY0 T AA1 R D +RETARDANT R IY0 T AA1 R D AH0 N T +RETARDATION R IY0 T AA0 R D EY1 SH AH0 N +RETARDED R IH0 T AA1 R D IH0 D +RETARDED(1) R IY0 T AA1 R D AH0 D +RETARDED(2) R IY0 T AA1 R D IH0 D +RETARDING R IH0 T AA1 R D IH0 NG +RETARDING(1) R IY0 T AA1 R D IH0 NG +RETARDS R IH0 T AA1 R D Z +RETARDS(1) R IY0 T AA1 R D Z +RETELL R IY0 T EH1 L +RETELLING R IY0 T EH1 L IH0 NG +RETEMEYER R EH1 T AH0 M AY2 R +RETENTION R IY0 T EH1 N SH AH0 N +RETEST R IY1 T EH1 S T +RETESTED R IY0 T EH1 S T IH0 D +RETESTING R IY0 T EH1 S T IH0 NG +RETESTS R IY1 T EH1 S T S +RETHERFORD R IH0 TH ER1 F ER0 D +RETHINK R IY0 TH IH1 NG K +RETHINKING R IY0 TH IH1 NG K IH0 NG +RETHOUGHT R IY0 TH AO1 T +RETI R EH1 T IY0 +RETICENCE R EH1 T IH0 S AH0 N S +RETICENT R EH1 T IH0 S AH0 N T +RETIN R EH1 T IH0 N +RETINA R EH1 T AH0 N AH0 +RETINAL R EH1 T AH0 N AH0 L +RETINOBLASTOMA R EH2 T IH0 N OW2 B L AE2 S T OW1 M AH0 +RETINOID R EH1 T IH0 N OY0 D +RETINOIDS R EH1 T IH0 N OY0 D Z +RETINOL R EH1 T IH0 N AO2 L +RETINUE R EH1 T AH0 N UW2 +RETINYL R EH1 T IH0 N AH0 L +RETIRE R IH0 T AY1 R +RETIRE(1) R IY0 T AY1 R +RETIRE(2) R IY2 T AY1 ER0 +RETIRED R IH0 T AY1 R D +RETIRED(1) R IY0 T AY1 ER0 D +RETIRED(2) R IY0 T AY1 R D +RETIREE R IY0 T AY1 R IY1 +RETIREE'S R IH0 T AY2 R IY1 Z +RETIREES R IY0 T AY1 R IY1 Z +RETIREES' R IH0 T AY2 R IY1 Z +RETIREMENT R IY0 T AY1 ER0 M AH0 N T +RETIREMENT(1) R IH0 T AY1 ER0 M AH0 N T +RETIREMENT'S R IH0 T AY1 R M AH0 N T S +RETIREMENT'S(1) R IY0 T AY1 R M AH0 N T S +RETIREMENTS R IH0 T AY1 R M AH0 N T S +RETIREMENTS(1) R IY0 T AY1 R M AH0 N T S +RETIRES R IH0 T AY1 R Z +RETIRES(1) R IY0 T AY1 ER0 Z +RETIRES(2) R IY0 T AY1 R Z +RETIRING R IH0 T AY1 R IH0 NG +RETIRING(1) R IY0 T AY1 ER0 IH0 NG +RETIRING(2) R IY0 T AY1 R IH0 NG +RETLIN R EH1 T L IH0 N +RETO R IY1 T UW1 +RETOOK R IY0 T UH1 K +RETOOL R IY0 T UW1 L +RETOOLED R IY0 T UW1 L D +RETOOLING R IY0 T UW1 L IH0 NG +RETORT R IY1 T AO2 R T +RETORTED R IY0 T AO1 R T IH0 D +RETORTS R IH0 T AO1 R T S +RETORTS(1) R IY0 T AO1 R T S +RETOUCHING R IY0 T AH1 CH IH0 NG +RETRACE R IY0 T R EY1 S +RETRACED R IY0 T R EY1 S T +RETRACEMENT R IY0 T R EY1 S M AH0 N T +RETRACING R IY0 T R EY1 S IH0 NG +RETRACT R IY0 T R AE1 K T +RETRACTABLE R IY0 T R AE1 K T AH0 B AH0 L +RETRACTED R IY0 T R AE1 K T AH0 D +RETRACTING R IY0 T R AE1 K T IH0 NG +RETRACTION R IY0 T R AE1 K SH AH0 N +RETRACTS R IY0 T R AE1 K T S +RETRAIN R IY0 T R EY1 N +RETRAINED R IY0 T R EY1 N D +RETRAINING R IY0 T R EY1 N IH0 NG +RETRANSMISSION R IY2 T R AE0 N Z M IH1 SH AH0 N +RETREAD R IY0 T R EH1 D +RETREADING R IY0 T R EH1 D IH0 NG +RETREADS R IY0 T R EH1 D Z +RETREAT R IY0 T R IY1 T +RETREATED R IY0 T R IY1 T AH0 D +RETREATED(1) R IY0 T R IY1 T IH0 D +RETREATING R IY0 T R IY1 T IH0 NG +RETREATS R IY0 T R IY1 T S +RETRENCH R IY0 T R EH1 N CH +RETRENCHED R IY0 T R EH1 N CH T +RETRENCHING R IY0 T R EH1 N CH IH0 NG +RETRENCHMENT R IY0 T R EH1 N CH M AH0 N T +RETRENCHMENTS R IY0 T R EH1 N CH M AH0 N T S +RETRIAL R IY0 T R AY1 AH0 L +RETRIBUTION R EH2 T R AH0 B Y UW1 SH AH0 N +RETRIED R IY0 T R AY1 D +RETRIEVAL R IH0 T R IY1 V AH0 L +RETRIEVAL(1) R IY0 T R IY1 V AH0 L +RETRIEVE R IH0 T R IY1 V +RETRIEVE(1) R IY0 T R IY1 V +RETRIEVED R IY0 T R IY1 V D +RETRIEVER R IY0 T R IY1 V ER0 +RETRIEVERS R IY0 T R IY1 V ER0 Z +RETRIEVES R IH0 T R IY1 V Z +RETRIEVES(1) R IY0 T R IY1 V Z +RETRIEVING R IY0 T R IY1 V IH0 NG +RETRO R EH1 T R OW0 +RETROACTIVE R EH2 T R OW0 AE1 K T IH0 V +RETROACTIVELY R EH2 T R OW0 AE1 K T IH0 V L IY0 +RETROACTIVITY R EH2 T R OW0 AE0 K T IH1 V IH0 T IY0 +RETROCESSION R EH2 T R OW0 S EH1 SH AH0 N +RETROCESSIONARIES R EH2 T R OW0 S EH1 SH AH0 N EH0 R IY0 Z +RETROCESSIONARY R EH2 T R OW0 S EH1 SH AH0 N EH0 R IY0 +RETROFIT R EH1 T R OW0 F IH2 T +RETROFITS R EH1 T R OW0 F IH2 T S +RETROFITTED R EH1 T R OW2 F IH2 T IH0 D +RETROFITTER R EH1 T R OW2 F IH2 T ER0 +RETROFITTING R EH1 T R OW0 F IH2 T IH0 NG +RETROGRADE R EH1 T R AH0 G R EY2 D +RETROSPECT R EH1 T R AH0 S P EH2 K T +RETROSPECTIVE R EH2 T R AH0 S P EH1 K T IH0 V +RETROSPECTIVELY R EH2 T R OW0 S P EH1 K T IH0 V L IY0 +RETROVIR R EH1 T R OW0 V IH2 R +RETROVIRUS R EH2 T R OW0 V AY1 R AH0 S +RETROVIRUSES R EH2 T R OW0 V AY1 R AH0 S IH0 Z +RETRY R IY0 T R AY1 +RETRYING R IY0 T R AY1 IH0 NG +RETTBERG R EH1 T B ER0 G +RETTER R EH1 T ER0 +RETTEW R EH1 CH UW0 +RETTIG R EH1 T IH0 G +RETTINGER R EH1 T IH0 N JH ER0 +RETTINGER(1) R EH1 T IH0 NG ER0 +RETTKE R EH1 T K IY0 +RETTON R EH1 T AH0 N +RETURN R IH0 T ER1 N +RETURN(1) R IY0 T ER1 N +RETURNABLE R IY0 T ER1 N AH0 B AH0 L +RETURNED R IH0 T ER1 N D +RETURNED(1) R IY0 T ER1 N D +RETURNEE R IH0 T ER0 N IY1 +RETURNEES R IH0 T ER0 N IY1 Z +RETURNING R IH0 T ER1 N IH0 NG +RETURNING(1) R IY0 T ER1 N IH0 NG +RETURNS R IH0 T ER1 N Z +RETURNS(1) R IY0 T ER1 N Z +RETURNS' R AH0 T ER1 N Z +RETURNS'(1) R IY0 T ER1 N Z +RETZ R EH1 T S +RETZER R EH1 T Z ER0 +RETZLAFF R EH1 T Z L AH0 F +RETZLOFF R EH1 T Z L AO0 F +REUBEN R UW1 B AH0 N +REUBER R OY1 B ER0 +REUL R UW1 L +REULAND R OY1 L AH0 N D +REULE R UW1 L +REUM R IY1 AH0 M +REUNIFICATION R IY0 UW2 N AH0 F AH0 K EY1 SH AH0 N +REUNIFIED R IY0 UW1 N AH0 F AY2 D +REUNIFY R IY0 UW1 N AH0 F AY2 +REUNION R IY0 UW1 N Y AH0 N +REUNIONS R IY0 UW1 N Y AH0 N Z +REUNITE R IY2 UW0 N AY1 T +REUNITED R IY2 UW0 N AY1 T IH0 D +REUNITES R IY2 UW0 N AY1 T S +REUNITING R IY2 UW0 N AY1 T IH0 NG +REUSABLE R IY0 UW1 Z AH0 B AH0 L +REUSCH R OY1 SH +REUSE R IY0 Y UW1 S +REUSE(1) R IY0 Y UW1 Z +REUSED R IY0 UW1 Z D +REUSING R IY0 Y UW1 Z IH0 NG +REUSS R UW1 S +REUSSER R OY1 S ER0 +REUST R UW1 S T +REUTER R OY1 T ER0 +REUTER'S R OY1 T ER0 Z +REUTERS R OY1 T ER0 Z +REUTERS' R OY1 T ER0 Z +REUTERS'S R OY1 T ER0 Z IH0 Z +REUTERS'S(1) R OY1 T ER0 Z +REUTGERS R OY1 T G ER0 Z +REUTHER R OY1 DH ER0 +REUTTER R OY1 T ER0 +REUTZEL R OY1 T Z AH0 L +REV R EH1 V +REVA R EY1 V AH0 +REVAK R EH1 V AH0 K +REVALUATION R IY0 V AE1 L Y UW0 EY1 SH AH0 N +REVALUATIONS R IY0 IH0 V AE2 L Y UW0 EY1 SH AH0 N Z +REVALUE R IY0 V AE1 L Y UW2 +REVALUED R IY0 V AE1 L Y UW0 D +REVALUING R IY0 V AE1 L Y UW0 IH0 NG +REVAMP R IY0 V AE1 M P +REVAMPED R IY0 V AE1 M P T +REVAMPING R IY0 V AE1 M P IH0 NG +REVAMPS R IY0 V AE1 M P S +REVARD R IH0 V AA1 R D +REVCO R EH1 V K OW0 +REVCO'S R EH1 V K OW0 Z +REVEAL R IH0 V IY1 L +REVEAL(1) R IY0 V IY1 L +REVEALED R IH0 V IY1 L D +REVEALED(1) R IY0 V IY1 L D +REVEALING R IH0 V IY1 L IH0 NG +REVEALING(1) R IY0 V IY1 L IH0 NG +REVEALS R IH0 V IY1 L Z +REVEALS(1) R IY0 V IY1 L Z +REVEILLE R EH1 V AH0 L IY2 +REVEL R EH1 V AH0 L +REVELATION R EH2 V AH0 L EY1 SH AH0 N +REVELATIONS R EH2 V AH0 L EY1 SH AH0 N Z +REVELATORY R IH0 V EH1 L AH0 T AO2 R IY0 +REVELED R EH1 V AH0 L D +REVELER R EH1 V AH0 L ER0 +REVELERS R EH1 V AH0 L ER0 Z +REVELES R EY0 V EY1 L EH0 S +REVELING R EH1 V AH0 L IH0 NG +REVELL R EY0 V EY1 L +REVELLE R IH0 V EH1 L +REVELLER R EH1 V AH0 L ER0 +REVELLERS R EH1 V AH0 L ER0 Z +REVELLO R EH0 V EH1 L OW0 +REVELRY R EH1 V AH0 L R IY0 +REVELS R EH1 V AH0 L Z +REVENGE R IY0 V EH1 N JH +REVENUE R EH1 V AH0 N UW2 +REVENUE(1) R EH1 V AH0 N Y UW2 +REVENUER R EH1 V AH0 N UW2 ER0 +REVENUER(1) R EH1 V AH0 N Y UW2 ER0 +REVENUERS R EH1 V AH0 N UW2 ER0 Z +REVENUERS(1) R EH1 V AH0 N Y UW2 ER0 Z +REVENUES R EH1 V AH0 N UW2 Z +REVENUES(1) R EH1 V AH0 N Y UW2 Z +REVERB R IY0 V ER1 B +REVERBED R IY0 V ER1 B D +REVERBERATE R IH0 V ER1 B ER0 AH0 T +REVERBERATE(1) R IH0 V ER1 B ER0 EY0 T +REVERBERATED R IH0 V ER1 B ER0 EY2 T IH0 D +REVERBERATED(1) R IY0 V ER1 B ER0 EY2 T AH0 D +REVERBERATED(2) R IY0 V ER1 B ER0 EY2 T IH0 D +REVERBERATES R IH0 V ER1 B ER0 EY2 T S +REVERBERATING R IH0 V ER1 B ER0 EY2 T IH0 NG +REVERBERATING(1) R IY0 V ER1 B ER0 EY2 T IH0 NG +REVERBERATION R IY0 V ER2 B ER0 EY1 SH AH0 N +REVERBERATIONS R IH0 V ER2 B ER0 EY1 SH AH0 N Z +REVERCOMB R EH1 V ER0 K AH0 M +REVERE R IH0 V IH1 R +REVERED R IH0 V IH1 R D +REVERENCE R EH1 V ER0 AH0 N S +REVEREND R EH1 V ER0 AH0 N D +REVEREND(1) R EH1 V R AH0 N D +REVERENT R EH1 V ER0 AH0 N T +REVERENTIAL R EH2 V ER0 EH1 N SH AH0 L +REVERENTLY R EH1 V ER0 AH0 N T L IY0 +REVERES R IH0 V IH1 R Z +REVERIE R EH1 V ER0 IY0 +REVERIES R EH1 V ER0 IY0 Z +REVERING R IH0 V IH1 R IH0 NG +REVERON R EH1 V ER0 AA2 N +REVERON'S R EH1 V ER0 AA2 N Z +REVERSAL R IH0 V ER1 S AH0 L +REVERSAL(1) R IY0 V ER1 S AH0 L +REVERSALS R IH0 V ER1 S AH0 L Z +REVERSALS(1) R IY0 V ER1 S AH0 L Z +REVERSE R IH0 V ER1 S +REVERSE(1) R IY0 V ER1 S +REVERSED R IH0 V ER1 S T +REVERSED(1) R IY0 V ER1 S T +REVERSER R IH0 V ER1 S ER0 +REVERSERS R IH0 V ER1 S ER0 Z +REVERSES R IH0 V ER1 S IH0 Z +REVERSES(1) R IY0 V ER1 S AH0 Z +REVERSES(2) R IY0 V ER1 S IH0 Z +REVERSIBLE R IH0 V ER1 S AH0 B AH0 L +REVERSIBLE(1) R IY0 V ER1 S AH0 B AH0 L +REVERSING R IH0 V ER1 S IH0 NG +REVERSING(1) R IY0 V ER1 S IH0 NG +REVERSION R IH0 V ER1 ZH AH0 N +REVERT R IH0 V ER1 T +REVERT(1) R IY0 V ER1 T +REVERTED R IH0 V ER1 T IH0 D +REVERTED(1) R IY0 V ER1 T IH0 D +REVERTING R IH0 V ER1 T IH0 NG +REVERTS R IH0 V ER1 T S +REVES R IY1 V Z +REVETTE R IH0 V EH1 T +REVIER R IY1 V IY0 ER0 +REVIEW R IY2 V Y UW1 +REVIEW'S R IY0 V Y UW1 Z +REVIEWED R IY0 V Y UW1 D +REVIEWER R IY0 V Y UW1 ER0 +REVIEWER'S R IY0 V Y UW1 ER0 Z +REVIEWERS R IY0 V Y UW1 ER0 Z +REVIEWING R IY0 V Y UW1 IH0 NG +REVIEWS R IY0 V Y UW1 Z +REVIEWS(1) R AH0 V Y UW1 Z +REVIGLIO R AH0 V IH1 G L IY0 OW0 +REVILE R IY0 V AY1 L +REVILED R IY0 V AY1 L D +REVILLA R EH0 V IH1 L AH0 +REVILLE R EH1 V IH2 L +REVIS R EH1 V IH0 S +REVISE R IH0 V AY1 Z +REVISE(1) R IY0 V AY1 Z +REVISED R IH0 V AY1 Z D +REVISED(1) R IY0 V AY1 Z D +REVISES R IH0 V AY1 Z IH0 Z +REVISES(1) R IY0 V AY1 Z IH0 Z +REVISING R IH0 V AY1 Z IH0 NG +REVISING(1) R IY0 V AY1 Z IH0 NG +REVISION R IY0 V IH1 ZH AH0 N +REVISIONISM R IY0 V IH1 ZH AH0 N IH2 Z AH0 M +REVISIONIST R IY0 V IH1 ZH AH0 N IH0 S T +REVISIONISTS R IY0 V IH1 ZH AH0 N IH0 S T S +REVISIONS R IY0 V IH1 ZH AH0 N Z +REVISIT R IY0 V IH1 Z IH0 T +REVISITED R IY0 V IH1 Z AH0 T IH0 D +REVISITING R IY0 V IH1 Z IH0 T IH0 NG +REVISITS R IY0 V IH1 Z IH0 T S +REVITALIZATION R IY2 V AY2 T AH0 L AH0 Z EY1 SH AH0 N +REVITALIZE R IY0 V AY1 T AH0 L AY2 Z +REVITALIZED R IY0 V AY1 T AH0 L AY2 Z D +REVITALIZING R IY0 V AY1 T AH0 L AY2 Z IH0 NG +REVIVAL R IH0 V AY1 V AH0 L +REVIVAL(1) R IY0 V AY1 V AH0 L +REVIVALIST R IY0 V AY1 V AH0 L IH0 S T +REVIVALS R IY0 V AY1 V AH0 L Z +REVIVE R IH0 V AY1 V +REVIVE(1) R IY0 V AY1 V +REVIVED R IH0 V AY1 V D +REVIVED(1) R IY0 V AY1 V D +REVIVES R IY0 V AY1 V Z +REVIVING R IH0 V AY1 V IH0 NG +REVIVING(1) R IY0 V AY1 V IH0 NG +REVLON R EH1 V L AA0 N +REVLON'S R EH1 V L AA0 N Z +REVOCABLE R EH1 V AH0 K AH0 B AH0 L +REVOCATION R EH2 V AH0 K EY1 SH AH0 N +REVOCATIONS R EH2 V AH0 K EY1 SH AH0 N Z +REVOIR R IH0 V W AA1 R +REVOKE R IH0 V OW1 K +REVOKE(1) R IY0 V OW1 K +REVOKED R IH0 V OW1 K T +REVOKED(1) R IY0 V OW1 K T +REVOKING R IH0 V OW1 K IH0 NG +REVOKING(1) R IY0 V OW1 K IH0 NG +REVOLT R IH0 V OW1 L T +REVOLT(1) R IY0 V OW1 L T +REVOLTED R IH0 V OW1 L T IH0 D +REVOLTED(1) R IY0 V OW1 L T AH0 D +REVOLTED(2) R IY0 V OW1 L T IH0 D +REVOLTING R IY0 V OW1 L T IH0 NG +REVOLTS R IY0 V OW1 L T S +REVOLUCION R EH2 V OW0 L UW2 S IY0 OW1 N +REVOLUCIONARIO R EH2 V OW0 L UW2 S IY0 AH0 N EH1 R IY0 OW0 +REVOLUTION R EH2 V AH0 L UW1 SH AH0 N +REVOLUTION'S R EH2 V AH0 L UW1 SH AH0 N Z +REVOLUTIONARIES R EH2 V AH0 L UW1 SH AH0 N EH2 R IY0 Z +REVOLUTIONARY R EH2 V AH0 L UW1 SH AH0 N EH2 R IY0 +REVOLUTIONIST R EH2 V AH0 L UW1 SH AH0 N IH0 S T +REVOLUTIONISTS R EH2 V AH0 L UW1 SH AH0 N IH0 S T S +REVOLUTIONIZE R EH2 V AH0 L UW1 SH AH0 N AY2 Z +REVOLUTIONIZED R EH2 V AH0 L UW1 SH AH0 N AY2 Z D +REVOLUTIONIZING R EH2 V AH0 L UW1 SH AH0 N AY2 Z IH0 NG +REVOLUTIONS R EH2 V AH0 L UW1 SH AH0 N Z +REVOLVE R IY0 V AA1 L V +REVOLVED R IY0 V AA1 L V D +REVOLVER R IH0 V AA1 L V ER0 +REVOLVERS R IH0 V AA1 L V ER0 Z +REVOLVES R IY0 V AA1 L V Z +REVOLVING R IY0 V AA1 L V IH0 NG +REVORD R IH0 V AO1 R D +REVS R EH1 V Z +REVSON R EH1 V S AH0 N +REVUE R IH0 V Y UW1 +REVUELTA R AH0 V W EH1 L T AH0 +REVUES R IH0 V Y UW1 Z +REVULSION R IH0 V AH1 L SH AH0 N +REVULSION(1) R IY0 V AH1 L SH AH0 N +REVVED R EH1 V D +REVVING R EH1 V IH0 NG +REVZIN R EH1 V Z IH0 N +REW R UW1 +REWARD R IH0 W AO1 R D +REWARD(1) R IY0 W AO1 R D +REWARDED R IH0 W AO1 R D IH0 D +REWARDED(1) R IY0 W AO1 R D AH0 D +REWARDED(2) R IY0 W AO1 R D IH0 D +REWARDING R IH0 W AO1 R D IH0 NG +REWARDING(1) R IY0 W AO1 R D IH0 NG +REWARDS R IH0 W AO1 R D Z +REWARDS(1) R IY0 W AO1 R D Z +REWATCHING R IY0 W AA1 CH IH0 NG +REWERTS R UW1 ER0 T S +REWEY R UW1 IY0 +REWIND R IY1 W AY0 N D +REWIRE R IY0 W AY1 ER0 +REWIRED R IY0 W AY1 ER0 D +REWIRING R IY0 W AY1 ER0 IH0 NG +REWIS R UW1 IH0 S +REWORD R IY0 W ER1 D +REWORK R IY0 W ER1 K +REWORKED R IY0 W ER1 K T +REWORKING R IY0 W ER1 K IH0 NG +REWRITE R IY0 R AY1 T +REWRITE(1) R IY1 R AY2 T +REWRITES R IY0 R AY1 T S +REWRITING R IY0 R AY1 T IH0 NG +REWRITTEN R IY0 R IH1 T AH0 N +REWROTE R IY0 R OW1 T +REX R EH1 K S +REXALL R EH1 K S AO2 L +REXANA R IH0 G Z AE1 N AH0 +REXENE R EH1 K S IY0 N +REXFORD R EH1 K S F ER0 D +REXHAM R EH1 K S AH0 M +REXNORD R EH1 K S N AO0 R D +REXON R EH1 K S AH0 N +REXROAD R EH1 K S R OW2 D +REXROAT R EH1 K S R OW0 T +REXRODE R EH1 K S R OW0 D +REXRODT R EH1 K S R OW0 D +REXROTH R EH1 K S R AA0 TH +REY R EY1 +REYBURN R EY1 B ER0 N +REYCRAFT R EY1 K R AE2 F T +REYER R EY1 ER0 +REYES R EY1 IH0 S +REYKJAVIK R EH1 K Y AH0 V IH0 K +REYKJAVIK(1) R EY1 K AH0 V IH0 K +REYMAN R EY1 M AH0 N +REYNA R EY1 N AH0 +REYNAGA R IY0 N AA1 G AH0 +REYNALDO R EY2 N AA1 L D OW0 +REYNARD R EY1 N ER0 D +REYNAUD R EY1 N AO0 D +REYNOLD R EH1 N AH0 L D +REYNOLDS R EH1 N AH0 L D Z +REYNOLDS' R EH1 N AH0 L D Z +REYNOLDS'S R EH1 N AH0 L D Z IH0 Z +REYNOLDSON R EY1 N OW0 L D S AH0 N +REYNOSA R IY0 N OW1 S AH0 +REYNOSO R IY0 N OW1 S OW0 +REZA R EH1 Z AH0 +REZABEK R IH0 Z AA1 B EH0 K +REZAC R EH1 Z AH0 K +REZEK R EH1 Z EH0 K +REZENDES R EY0 Z EY1 N D EH0 S +REZNICEK R EH1 Z N IH0 CH EH2 K +REZNICK R EH1 Z N IH0 K +REZNIK R EH1 Z N IH0 K +REZONING R IY0 Z OW1 N IH0 NG +RHA R AA1 +RHAME R EY1 M +RHAMES R EY1 M Z +RHAPSODIC R AE0 P S AA1 D IH0 K +RHAPSODIZE R AE1 P S AH0 D AY2 Z +RHAPSODIZES R AE1 P S AH0 D AY2 Z IH0 Z +RHAPSODY R AE1 P S AH0 D IY0 +RHEA R IY1 AH0 +RHEAULT R OW1 +RHEAUME R UW1 M +RHEE R IY1 +RHEEM R IY1 M +RHEIN R AY1 N +RHEINBERGER R AY1 N B ER2 G ER0 +RHEINGOLD R AY1 N G OW2 L D +RHEINISCH R AY1 N IH0 SH +RHEINSTEIN R AY1 N S T AY2 N +RHEM R EH1 M +RHEOLOGY R IY0 AO1 L AH0 JH IY0 +RHESUS R IY1 S AH0 S +RHETA R IY1 T AH0 +RHETORIC R EH1 T ER0 IH0 K +RHETORICAL R IH0 T AO1 R IH0 K AH0 L +RHETORICALLY R AH0 T AO1 R IH0 K L IY0 +RHETORICIAN R EH2 T ER0 IH1 SH AH0 N +RHETORICIANS R EH2 T ER0 IH1 SH AH0 N Z +RHETT R EH1 T +RHEUMATIC R UW0 M AE1 T IH0 K +RHEUMATISM R UW1 M AH0 T IH2 Z AH0 M +RHEUMATOID R UW1 M AH0 T OY2 D +RHEUMATOLOGIST R UW2 M AH0 T AA1 L AH0 JH AH0 S T +RHEUMATOLOGY R UW2 M AH0 T AA1 L AH0 JH IY0 +RHEW R UW1 +RHIN R IH1 N +RHINE R AY1 N +RHINEHARDT R AY1 N HH AA2 R T +RHINEHART R AY1 N HH AA2 R T +RHINELAND R AY1 N L AE2 N D +RHINEMAN R AY1 N M AH0 N +RHINEMAN'S R AY1 N M AH0 N Z +RHINES R AY1 N Z +RHINESMITH R AY1 N S M IH2 TH +RHINESTONE R AY1 N S T OW2 N +RHINESTONES R AY1 N S T OW2 N Z +RHINO R AY1 N OW2 +RHINOCEROS R AY0 N AA1 S ER0 AH0 S +RHINOPLASTIES R AY2 N OW0 P L AE1 S T IY2 Z +RHINOPLASTY R AY2 N OW0 P L AE1 S T IY2 +RHINOPLASTY(1) R IH2 N OW0 P L AE1 S T IY2 +RHINOS R AY1 N OW2 Z +RHIZOID R AY1 Z OY2 D +RHIZOIDAL R AY2 Z OY1 D AH0 L +RHIZOME R AY1 Z OW2 M +RHIZOMES R AY1 Z OW2 M Z +RHO R OW1 +RHOAD R OW1 D +RHOADES R OW1 D Z +RHOADS R OW1 D Z +RHODA R OW1 D AH0 +RHODANTHE R OW2 D AE1 N TH +RHODE R OW1 D +RHODE-ISLAND R OW1 D AY1 L AH0 N D +RHODE-ISLAND'S R OW1 D AY1 L AH0 N D Z +RHODE-ISLANDER R OW1 D AY1 L AH0 N D ER0 +RHODE-ISLANDERS R OW1 D AY1 L AH0 N D ER0 Z +RHODEN R OW1 D AH0 N +RHODES R OW1 D Z +RHODESIA R OW0 D IY1 ZH AH0 +RHODESIAN R OW0 D IY1 ZH AH0 N 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B AO1 D OW0 +RIBAVIRIN R IH0 B AE1 V IH0 R IH0 N +RIBBED R IH1 B D +RIBBING R IH1 B IH0 NG +RIBBIT R IH1 B IH0 T +RIBBLE R IH1 B AH0 L +RIBBON R IH1 B AH0 N +RIBBONS R IH1 B AH0 N Z +RIBEIRO R IY0 B EH1 R OW0 +RIBERA R IY0 B EH1 R AH0 +RIBI R IY1 B IY0 +RIBICOFF R IH1 B IH0 K AO2 F +RIBKA R IH1 B K AH0 +RIBONUCLEIC R AY2 B OW0 N UW0 K L EY1 IH0 K +RIBS R IH1 B Z +RIC R IH1 K +RICA R IY1 K AH0 +RICA'S R IY1 K AH0 Z +RICADONNA R IY0 K AA0 D OW1 N AH0 +RICAN R IY1 K AH0 N +RICANS R IH1 K AH0 N Z +RICARD R IH0 K AA1 R D +RICARDO R IH0 K AA1 R D OW0 +RICAURTE R AH0 K AA1 R T EY2 +RICCA R IY1 K AH0 +RICCARDI R IY0 K AA1 R D IY0 +RICCARDO R IH0 K AA1 R D OW0 +RICCI R IY1 CH IY0 +RICCIARDELLI R IY0 CH ER0 D EH1 L IY0 +RICCIARDI R IY0 CH AA1 R D IY0 +RICCIO R IY1 CH IY0 OW0 +RICCITELLI R IY0 CH IY0 T EH1 L IY0 +RICCIUTI R IY0 K CH UW1 T IY0 +RICCO R IH1 K OW0 +RICCOBONO R IY0 K OW0 B OW1 N OW0 +RICE R AY1 S +RICE'S R AY1 S IH0 Z +RICEVILLE R AY1 S V IH0 L +RICH R IH1 CH +RICH'S R IH1 CH IH0 Z +RICHA R IH1 CH AH0 +RICHARD R IH1 CH ER0 D +RICHARD'S R IH1 CH ER0 D Z +RICHARDS R IH1 CH ER0 D Z +RICHARDS' R IH1 CH ER0 D Z +RICHARDS'S R IH1 CH ER0 D Z IH0 Z +RICHARDSON R IH1 CH ER0 D S AH0 N +RICHARDSON'S R IH1 CH ER0 D S AH0 N Z +RICHARDSONSMITH R IH1 CH ER0 D S AH0 N S M IH1 TH +RICHARDT R IH1 K AA0 R T +RICHARSON R IH1 CH AA2 R S AH0 N +RICHART R IH1 K HH AA2 R T +RICHAUD R IY2 SH OW1 D +RICHBOURG R IH1 CH B AO2 R G +RICHBURG R IH1 CH B ER0 G +RICHCO R IH1 K OW0 +RICHCREEK R IH1 CH K R IY2 K +RICHE R IH1 CH +RICHELIEU R IH1 SH AH0 L UW2 +RICHELSON R IH1 CH AH0 L S AH0 N +RICHEMONT R IH1 CH AH0 M AA2 N T +RICHENTHAL R IH1 K AH0 N TH AO2 L +RICHER R IH1 CH ER0 +RICHERD R IH1 CH ER0 D +RICHERSON R IH1 CH ER0 S AH0 N +RICHERT R IH1 K ER0 T +RICHES R IH1 CH AH0 Z +RICHES(1) R IH1 CH IH0 Z +RICHESIN R IH1 K IH0 S IH0 N +RICHESON R IH1 K IH0 S AH0 N +RICHEST R IH1 CH AH0 S T +RICHEY R IH1 CH IY0 +RICHFIELD R IH1 CH F IY2 L D +RICHFIELD'S R IH1 CH F IY2 L D Z +RICHFORD R IH1 CH F ER0 D +RICHIE R IH1 CH IY0 +RICHINS R IH1 K IH0 N Z +RICHISON R IH1 CH IH0 S AH0 N +RICHLAND R IH1 CH L AH0 N D +RICHLAND(1) R IH1 CH L AE0 N +RICHLY R IH1 CH L IY0 +RICHMAN R IH1 CH M AE2 N +RICHMOND R IH1 CH M AH0 N D +RICHMOND'S R IH1 CH M AH0 N D Z +RICHNER R IH1 K N ER0 +RICHNESS R IH1 CH N AH0 S +RICHOUX R IH0 SH UW1 +RICHSTONE R IH1 CH S T OW2 N +RICHTER R IH1 K T ER0 +RICHTON R IH1 CH T AH0 N +RICHTS R IH1 K T S +RICHWHITE R IH1 CH W AY2 T +RICHWINE R IH1 CH W AY2 N +RICIGLIANO R IH0 S IH2 G L IY0 AA1 N OW0 +RICK R IH1 K +RICK'S R IH1 K S +RICKABAUGH R IH1 K AH0 B AO2 +RICKARD R IH1 K ER0 D +RICKARDS R IH1 K ER0 D Z +RICKE R IH1 K +RICKEL R IH1 K AH0 L +RICKELS R IH1 K AH0 L Z +RICKEN R IH1 K AH0 N +RICKENBACH R IH1 K IH0 N B AA0 K +RICKENBAKER R IH1 K IH0 N B AH0 K ER0 +RICKER R IH1 K ER0 +RICKERS R IH1 K ER0 Z +RICKERSON R IH1 K ER0 S AH0 N +RICKERT R IH1 K ER0 T +RICKETS R IH1 K IH0 T S +RICKETSON R IH1 K IH0 T S AH0 N +RICKETT R IH1 K IH0 T +RICKETTS R IH1 K IH0 T S +RICKETY R IH1 K AH0 T IY0 +RICKEY R IH1 K IY0 +RICKI R IH1 K IY0 +RICKIE R IH1 K IY0 +RICKLEFS R IH1 K L IH0 F S +RICKLES R IH1 K AH0 L Z +RICKLES' R IH1 K AH0 L Z +RICKLES'(1) R IH1 K AH0 L Z IH0 Z +RICKMAN R IH1 K M AH0 N +RICKNER R IH1 K N ER0 +RICKS R IH1 K S +RICKSON R IH1 K S AH0 N +RICKWARD R IH1 K W ER0 D +RICKWOOD R IH1 K W UH2 D +RICKY R IH1 K IY2 +RICKY'S R IH1 K IY2 Z +RICO R IY1 K OW0 +RICO'S R IY1 K OW0 Z +RICOCHET R IH1 K AH0 SH EY2 +RICOCHETED R IH1 K AH0 SH EY2 D +RICOCHETING R IH1 K AH0 SH EY2 IH0 NG +RICOH R IY1 K OW0 +RICOH'S R IY1 K OW0 Z +RICOSTRUZIONE R IY0 K OW2 S T R UW0 Z IY0 OW1 N EY2 +RID R IH1 D +RIDABLE R AY1 D AH0 B AH0 L +RIDDANCE R IH1 D AH0 N S +RIDDELL R IH1 D AH0 L +RIDDEN R IH1 D AH0 N +RIDDER R IH1 D ER0 +RIDDER'S R IH1 D ER0 Z +RIDDICK R IH1 D IH0 K +RIDDING R IH1 D IH0 NG +RIDDLE R IH1 D AH0 L +RIDDLED R IH1 D AH0 L D +RIDDLER R IH1 D L ER0 +RIDDLES R IH1 D AH0 L Z +RIDDOCK R IH1 D AH0 K +RIDE R AY1 D +RIDEAU R IH0 D OW1 +RIDEAUX R IH0 D OW1 +RIDELL R IH0 D EH1 L +RIDEN R AY1 D AH0 N +RIDENER R IH1 D IY0 N ER0 +RIDENHOUR R IH1 D IH0 N AW0 R +RIDENOUR R IH1 D IH0 N UH0 R +RIDEOUT R AY1 D AW2 T +RIDER R AY1 D ER0 +RIDER'S R AY1 D ER0 Z +RIDERS R AY1 D ER0 Z +RIDERSHIP R AY1 D ER0 SH IH2 P +RIDES R AY1 D Z +RIDGE R IH1 JH +RIDGE'S R IH1 JH IH0 S +RIDGECREST R IH1 JH K R EH2 S T +RIDGED R IH1 JH D +RIDGEFIELD R IH1 JH F IY2 L D +RIDGELL R IH1 JH AH0 L +RIDGELY R IH1 JH L IY0 +RIDGES R IH1 JH AH0 Z +RIDGES(1) R IH1 JH IH0 Z +RIDGEWAY R IH1 JH W EY2 +RIDGEWOOD R IH1 JH W UH2 D +RIDGLEY R IH1 JH L IY0 +RIDGWAY R IH1 JH W EY2 +RIDICULE R IH1 D AH0 K Y UW2 L +RIDICULED R IH1 D AH0 K Y UW2 L D +RIDICULES R IH1 D AH0 K Y UW2 L Z +RIDICULING R IH1 D AH0 K Y UW2 L IH0 NG +RIDICULOUS R IH0 D IH1 K Y AH0 L AH0 S +RIDICULOUSLY R AH0 D IH1 K Y AH0 L AH0 S L IY0 +RIDING R AY1 D IH0 NG +RIDINGER R AY1 D IH0 NG ER0 +RIDINGS R AY1 D IH0 NG Z +RIDLEY R IH1 D L IY0 +RIDLING R IH1 D L IH0 NG +RIDLON R IH1 D L AH0 N +RIDNER R IH1 D N ER0 +RIDOLFI R IY0 D OW1 L F IY0 +RIDOUT R IH1 D AW2 T +RIDPATH R IH1 D P AE2 TH +RIDS R IH1 D Z +RIEBE R IY1 B +RIEBEL R IY1 B AH0 L +RIEBEN R IY1 B AH0 N +RIEBER R IY1 B ER0 +RIEBMAN R IY1 B M AH0 N +RIECHERS R IY1 K ER0 Z +RIECK R IY1 K +RIECKE R IY1 K +RIED R IY1 D +RIEDE R IY1 D +RIEDEL R IY1 D AH0 L +RIEDER R IY1 D ER0 +RIEDERER R IY1 D ER0 ER0 +RIEDERS R IY1 D ER0 Z +RIEDERS' R IY1 D ER0 Z +RIEDESEL R IY1 D IH0 S AH0 L +RIEDL R IY1 D AH0 L +RIEDLINGER R IY1 D AH0 L IH0 NG ER0 +RIEDLINGER(1) R IY1 D L IH0 NG ER0 +RIEDY R IY1 D IY0 +RIEF R IY1 F +RIEG R IY1 G +RIEGE R IY1 JH +RIEGEL R IY1 G AH0 L +RIEGER R IY1 G ER0 +RIEGERT R IY1 G ER0 T +RIEGLE R IY1 G AH0 L +RIEGLER R IY1 G L ER0 +RIEHL R IY1 L +RIEHLE R IY1 HH AH0 L +RIEHM R IY1 M +RIEK R IY1 K +RIEKE R IY1 K +RIEKEN R IY1 K AH0 N +RIEKER R IY1 K ER0 +RIEL R IY1 L +RIELLY R IY1 L IY0 +RIELY R IY1 L IY0 +RIEMAN R IY1 M AH0 N +RIEMANN R IY1 M AH0 N +RIEMENSCHNEIDER R IY1 M IH0 N SH N AY0 D ER0 +RIEMER R IY1 M ER0 +RIEMERSMA R IY0 M EH1 R S M AH0 +RIENDEAU R AH0 N D OW1 +RIENSTRA R IY1 N S T R AH0 +RIEPE R IY1 P +RIERA R IY1 R AH0 +RIERSON R IY1 R S AH0 N +RIES R AY1 Z +RIESBERG R IY1 S B ER0 G +RIESE R IY1 Z +RIESEN R IY1 S AH0 N +RIESENBERG R IY1 S AH0 N B ER0 G +RIESER R IY1 S ER0 +RIESH R AY1 SH +RIESH(1) R IY1 SH +RIESLING R IY1 Z L IH0 NG +RIESS R IY1 S +RIESTER R AY1 IH0 S T ER0 +RIESTERER R IY1 S T ER0 ER0 +RIETH R AY1 IH0 TH +RIETMAN R AY1 T M AH0 N +RIETVELD R IY1 T V IH0 L D +RIETZ R IY1 T S +RIEVES R IY1 V Z +RIFE R AY1 F +RIFENBURGH R IH1 F AH0 N B ER0 G +RIFF R IH1 F +RIFFE R IH1 F +RIFFED R IH1 F T +RIFFEL R IH1 F AH0 L +RIFFEY R IH1 F IY0 +RIFFING R IH1 F IH0 NG +RIFFLE R IH1 F AH0 L +RIFFRAFF R IH1 F R AE2 F +RIFFS R IH1 F S +RIFKIN R IH1 F K IH0 N +RIFKIN'S R IH1 F K IH0 N Z +RIFKIND R IH1 F K IH0 N D +RIFLE R AY1 F AH0 L +RIFLE-SHOT R AY1 F AH0 L SH AA2 T +RIFLED R AY1 F AH0 L D +RIFLEMAN R AY1 F AH0 L M AH0 N +RIFLERY R AY1 F AH0 L R IY0 +RIFLES R AY1 F AH0 L Z +RIFLING R AY1 F L IH0 NG +RIFT R IH1 F T +RIFTS R IH1 F T S +RIG R IH1 G +RIGA R IY1 G AH0 +RIGAS R AY1 G AH0 Z +RIGATONI R IH0 G AH0 T OW1 N IY0 +RIGBY R IH1 G B IY0 +RIGDON R IH1 G D AH0 N +RIGEL R AY1 JH AH0 L +RIGG R IH1 G +RIGGAN R IH1 G AH0 N +RIGGED R IH1 G D +RIGGEN R IH1 G AH0 N +RIGGENBACH R IH1 G IH0 N B AA0 K +RIGGI R IH1 JH IY0 +RIGGIN R IH1 G IH0 N +RIGGING R IH1 G IH0 NG +RIGGINGS R IH1 G IH0 NG Z +RIGGINS R IH1 G IH0 N Z +RIGGIO R IY1 JH IY0 OW0 +RIGGLE R IH1 G AH0 L +RIGGLEMAN R IH1 G AH0 L M AH0 N +RIGGS R IH1 G Z +RIGGSBEE R IH1 G Z B IY0 +RIGHETTI R IY0 G EH1 T IY0 +RIGHI R IY1 G IY0 +RIGHT R AY1 T +RIGHT'S R AY1 T S +RIGHT-BRACE R AY1 T B R EY1 S +RIGHT-HAND R AY0 T HH AE1 N D +RIGHT-HANDED R AY0 T HH AE1 N D IH0 D +RIGHT-WINGER R AY2 T W IH1 NG ER0 +RIGHT-WINGERS R AY2 T W IH1 NG ER0 Z +RIGHTED R AY1 T IH0 D +RIGHTEOUS R AY1 CH AH0 S +RIGHTEOUSLY R AY1 CH AH0 S L IY0 +RIGHTEOUSNESS R AY1 CH AH0 S N AH0 S +RIGHTER R AY1 T ER0 +RIGHTFUL R AY1 T F AH0 L +RIGHTFULLY R AY1 T F AH0 L IY0 +RIGHTHAND R AY0 T HH AE1 N D +RIGHTHANDED R AY0 T HH AE1 N D IH0 D +RIGHTISH R AY1 T IH0 SH +RIGHTIST R AY1 T IH0 S T +RIGHTISTS R AY1 T IH0 S T S +RIGHTLY R AY1 T L IY0 +RIGHTMIRE R AY1 T M AY2 R +RIGHTMYER R AY1 T M IY0 ER0 +RIGHTNESS R AY1 T N AH0 S +RIGHTO R AY1 T OW0 +RIGHTS R AY1 T S +RIGHTS' R AY1 T S +RIGHTWARD R AY1 T W ER0 D +RIGHTWING R AY1 T W IH2 NG +RIGHTY R AY1 T IY0 +RIGID R IH1 JH AH0 D +RIGID(1) R IH1 JH IH0 D +RIGIDITIES R IH0 JH IH1 D IH0 T IY0 Z +RIGIDITY R IH0 JH IH1 D AH0 T IY0 +RIGIDLY R IH1 JH IH0 D L IY0 +RIGLER R AY1 G AH0 L ER0 +RIGLER(1) R IH1 G L ER0 +RIGNEY R IH1 G N IY0 +RIGO R IY1 G OW0 +RIGOLETTO R IH2 G AH0 L EH1 T OW0 +RIGONI R IY0 G OW1 N IY0 +RIGOR R IH1 G ER0 +RIGOROUS R IH1 G ER0 AH0 S +RIGOROUSLY R IH1 G ER0 AH0 S L IY0 +RIGORS R IH1 G ER0 Z +RIGS R IH1 G Z +RIGSBEE R IH1 G Z B IY2 +RIGSBY R IH1 G Z B IY0 +RIGUEUR R IH0 G Y UW1 R +RIGUEUR(1) R IH1 G ER0 +RIHA R AY1 HH AH0 +RIHANNA R IY2 HH AA1 N AH0 +RIHN R IH1 N +RIJN R IY1 AH0 N +RIKARD R IH1 K ER0 D +RIKE R AY1 K +RIKELD R AY1 K EH0 L D +RIKELD(1) R IH1 K EH0 L D +RIKER R AY1 K ER0 +RIKER'S R AY1 K ER0 Z +RIKERS R AY1 K ER0 Z +RIKKI R IH1 K IY0 +RIKLIS R IH1 K L IH0 S +RIKSBANK R IH1 K S B AE2 NG K +RIKSDAG R IH1 K S D AE0 G +RILE R AY1 L +RILED R AY1 L D +RILES R AY1 L Z +RILEY R AY1 L IY0 +RILEY'S R AY1 L IY0 Z +RILL R IH1 L +RILL'S R IH1 L Z +RILLA R IH1 L AH0 +RILLETTE R IH0 L EH1 T +RILLING R IH1 L IH0 NG +RILWANU R IH0 L W AA1 N UW0 +RIM R IH1 M +RIMA R IY1 M AH0 +RIMBEY R IH1 M B IY0 +RIME R AY1 M +RIMEL R IH1 M AH0 L +RIMER R AY1 M ER0 +RIMES R AY1 M Z +RIMKUS R IH1 M K AH0 S +RIMMED R IH1 M D +RIMMER R IH1 M ER0 +RIMPOCHET R IH0 P OW1 CH IH0 T +RIMPOCHET(1) R IH2 M P OW1 CH AH0 T +RIMPOCHETS R IH2 P OW1 CH IH0 T S +RIMPOCHETS(1) R IH2 M P OW1 CH IH0 T S +RIMS R IH1 M Z +RIMSON R IH1 M S AH0 N +RINA R IY1 N AH0 +RINALDI R IY0 N AA1 L D IY0 +RINALDO R IH0 N AA1 L D OW0 +RINARD R IH1 N ER0 D +RINAS R AY1 N AH0 Z +RINAUDO R IY0 N AO1 D OW0 +RINCK R IH1 NG K +RINCON R IH1 NG K AH0 N +RIND R AY1 N D +RINDAHL R IH1 N D AA2 L +RINDERER R IH1 N D ER0 ER0 +RINDERKNECHT R IH1 N D ER0 K N IH0 K T +RINDFLEISCH R IH1 N D F L AY2 SH +RINDS R AY1 N D Z +RINDT R IH1 N T +RINE R AY1 N +RINEER R IH1 N IH0 R +RINEHARDT R AY1 N HH AA2 R T +RINEHART R AY1 N HH AA2 R T +RINEHIMER R AY1 N HH AY2 M ER0 +RINELLA R IH0 N EH1 L AH0 +RINER R AY1 N ER0 +RINES R AY1 N Z +RINEY R AY1 N IY0 +RING R IH1 NG +RING'S R IH1 NG Z +RING-AROUND-THE-ROSY R IH1 NG ER0 AW1 N DH ER0 OW1 Z IY0 +RINGBERG R IH1 NG B ER0 G +RINGDAHL R IH1 NG D AA0 L +RINGE R IH1 NG +RINGED R IH1 NG D +RINGEISEN R IH1 NG G AY0 S AH0 N +RINGEL R IH1 NG G AH0 L +RINGEN R IH1 NG AH0 N +RINGENBERG R IH1 NG AH0 N B ER0 G +RINGER R IH1 NG ER0 +RINGERS R IH1 NG ER0 Z +RINGGENBERG R IH1 NG G AH0 N B ER0 G +RINGGIT R IH1 NG IH0 T +RINGGOLD R IH1 NG G OW2 L D +RINGING R IH1 NG IH0 NG +RINGLAND R IH1 NG G L AH0 N D +RINGLE R IH1 NG G AH0 L +RINGLEADER R IH1 NG L IY2 D ER0 +RINGLEADERS R IH1 NG L IY2 D ER0 Z +RINGLER R IH1 NG G AH0 L ER0 +RINGLER(1) R IH1 NG G L ER0 +RINGLEY R IH1 NG G L IY0 +RINGLING R IH1 NG L IH0 NG +RINGMASTER R IH1 NG M AE2 S T ER0 +RINGNECK R IH1 NG N EH2 K +RINGO R IY1 NG G OW0 +RINGOLD R IH1 NG G OW0 L D +RINGQUIST R IH1 NG K W IH0 S T +RINGS R IH1 NG Z +RINGSIDE R IH1 NG S AY2 D +RINGSTAD R IH1 NG S T AH0 D +RINGUETTE R IH0 NG EH1 T +RINGWALD R IH1 NG W AO0 L D +RINGWOOD R IH1 NG W UH2 D +RINI R IY1 N IY0 +RININGER R IH1 N IH0 NG ER0 +RINK R IH1 NG K +RINKE R IH1 NG K +RINKENBERGER R IH1 NG K AH0 N B ER0 G ER0 +RINKER R IH1 NG K ER0 +RINKO R IH1 NG K OW0 +RINKS R IH1 NG K S +RINN R IH1 N +RINNE R IH1 N +RINSE R IH1 N S +RINSING R IH1 N S IH0 NG +RINTALA R IY0 N T AA1 L AH0 +RINTEL R IH0 N T EH1 L +RINTEL'S R IH0 N T EH1 L Z +RINTELS R IH0 N T EH1 L Z +RINTELS' R IH0 N T EH1 L Z +RIO R IY1 OW0 +RIO'S R IY1 OW0 Z +RIO-DE-JANEIRO R IY1 OW0 D IY1 JH AH0 N EH1 R OW2 +RIOJAS R IY0 OW1 Y AA0 Z +RIOLO R IY0 OW1 L OW0 +RION R AY1 AH0 N +RIOPEL R IY0 AH0 P EH1 L +RIOPELLE R IY0 AH0 P EH1 L IY0 +RIORDAN R IH1 R D AH0 N +RIORDAN'S R IH1 R D AH0 N Z +RIOS R IY1 OW0 S +RIOT R AY1 AH0 T +RIOTED R AY1 AH0 T IH0 D +RIOTER R AY1 AH0 T ER0 +RIOTERS R AY1 AH0 T ER0 Z +RIOTING R AY1 AH0 T IH0 NG +RIOTOUS R AY1 AH0 T AH0 S +RIOTS R AY1 AH0 T S +RIOTS' R AY1 AH0 T S +RIOUX R UW1 +RIP R IH1 P +RIPA R IY1 P AH0 +RIPE R AY1 P +RIPEN R AY1 P AH0 N +RIPENED R AY1 P AH0 N D +RIPENING R AY1 P AH0 N IH0 NG +RIPENING(1) R AY1 P N IH0 NG +RIPHAGEN R IH1 P AA2 G AH0 N +RIPKA R IY1 P K AH0 +RIPKE R IH1 P K +RIPKEN R IH1 P K AH0 N +RIPKEN'S R IH1 P K AH0 N Z +RIPKIN R IH1 P K IH0 N +RIPLEY R IH1 P L IY0 +RIPOFF R IH1 P AO2 F +RIPOFFS R IH1 P AO2 F S +RIPOSTE R IH0 P OW1 S T +RIPOSTES R IH0 P AO1 S T S +RIPP R IH1 P +RIPPE R IH1 P +RIPPED R IH1 P T +RIPPEE R IH1 P IY1 +RIPPEL R IH1 P AH0 L +RIPPEON R IH1 P IY0 AH0 N +RIPPER R IH1 P ER0 +RIPPERGER R IH1 P ER0 G ER0 +RIPPETOE R IH1 P IH0 T OW0 +RIPPEY R IH1 P IY0 +RIPPING R IH1 P IH0 NG +RIPPLE R IH1 P AH0 L +RIPPLED R IH1 P AH0 L D +RIPPLES R IH1 P AH0 L Z +RIPPLING R IH1 P AH0 L IH0 NG +RIPPLING(1) R IH1 P L IH0 NG +RIPPLINGER R IH1 P AH0 L IH0 NG ER0 +RIPPLINGER(1) R IH1 P L IH0 NG ER0 +RIPPON R IH1 P AH0 N +RIPPY R IH1 P IY0 +RIPS R IH1 P S +RISA R IY1 S AH0 +RISBERG R IH1 S B ER0 G +RISC R IH1 S K +RISCH R IH1 SH +RISDEN R IH1 S D AH0 N +RISDON R IH1 S D AH0 N +RISE R AY1 Z +RISEN R IH1 Z AH0 N +RISENHOOVER R IH1 S IH0 N HH UW0 V ER0 +RISENHOOVER(1) R AY1 Z IH0 N HH UW0 V ER0 +RISER R AY1 Z ER0 +RISES R AY1 Z AH0 Z +RISES(1) R AY1 Z IH0 Z +RISH R IH1 SH +RISHEL R IH1 SH AH0 L +RISHELL R IH1 SH AH0 L +RISHER R IH1 SH ER0 +RISI R IY1 S IY0 +RISIN R AY1 Z IH0 N +RISING R AY1 Z IH0 NG +RISINGER R AY1 Z IH0 NG ER0 +RISK R IH1 S K +RISKE R IH1 S K +RISKE'S R IH1 S K S +RISKED R IH1 S K T +RISKIER R IH1 S K IY0 ER0 +RISKIEST R IH1 S K IY0 AH0 S T +RISKIN R IH1 S K IH0 N +RISKINESS R IH1 S K IY0 N AH0 S +RISKING R IH1 S K IH0 NG +RISKLESS R IH1 S K L AH0 S +RISKO R IH1 S K OW0 +RISKS R IH1 S K S +RISKY R IH1 S K IY0 +RISLEY R IH1 Z L IY0 +RISNER R IH1 S N ER0 +RISO R IY1 S OW0 +RISON R IH1 S AH0 N +RISOTTO R IY2 S AO1 T OW2 +RISPOLI R IY0 S P OW1 L IY0 +RISQUE R IH2 S K EY1 +RISS R IH1 S +RISSE R IH1 S +RISSER R IH1 S ER0 +RISSLER R IH1 S L ER0 +RISSMAN R IH1 S M AH0 N +RISSMILLER R IH1 S M IH0 L ER0 +RISSMILLER'S R IH1 S M IH0 L ER0 Z +RISSO R IH1 S OW0 +RISSO'S R IH1 S OW0 Z +RISSOLI R IH0 S OW1 L IY0 +RISSOLI'S R IH0 S OW1 L IY0 Z +RIST R IH1 S T +RISTAU R IH1 S T AW0 +RISTER R IH1 S T ER0 +RISTON R IH1 S T AH0 N +RISTORANTE R IH0 S T ER0 AA1 N T EY0 +RISTORANTES R IH0 S T ER0 AA1 N T EY0 Z +RISTOW R IH1 S T OW0 +RITA R IY1 T AH0 +RITA'S R IY1 T AH0 Z +RITACCO R IY0 T AA1 K OW0 +RITALIN R IH1 T AH0 L IH0 N +RITCEY R IH1 T S IY0 +RITCEY'S R IH1 T S IY0 Z +RITCH R IH1 CH +RITCHEY R IH1 CH IY0 +RITCHEY'S R IH1 CH IY0 Z +RITCHIE R IH1 CH IY0 +RITCHIE'S R IH1 CH IY0 Z +RITE R AY1 T +RITE'S R AY1 T S +RITENOUR R IH1 T AH0 N AW0 R +RITENOUR(1) R AY1 T AH0 N AW0 R +RITENOUR'S R IH1 T AH0 N AW0 R Z +RITENOUR'S(1) R AY1 T AH0 N AW0 R Z +RITER R AY1 T ER0 +RITES R AY1 T S +RITESH R IH2 T EH1 SH +RITGER R IH1 T G ER0 +RITNER R IH1 T N ER0 +RITSEMA R IH0 T S IY1 M AH0 +RITSON R IH1 T S AH0 N +RITT R IH1 T +RITT'S R IH1 T S +RITTENBERG R IH1 T AH0 N B ER0 G +RITTENBERG'S R IH1 T AH0 N B ER0 G Z +RITTENBERRY R IH1 T AH0 N B EH0 R IY0 +RITTENBERRY'S R IH1 T AH0 N B EH0 R IY0 Z +RITTENHOUSE R IH1 T AH0 N HH AW2 S +RITTENHOUSE'S R IH1 T AH0 N HH AW2 S IH0 Z +RITTENOUR R IH1 T AH0 N AW0 R +RITTENOUR'S R IH1 T AH0 N AW0 R Z +RITTER R IH1 T ER0 +RITTER'S R IH1 T ER0 Z +RITTERBUSCH R IH1 T ER0 B UH2 SH +RITTEREISER R IH1 T ER0 AY2 Z ER0 +RITTEREISER'S R IH1 T ER0 AY2 Z ER0 Z +RITTGERS R IH1 T G ER0 Z +RITTHALER R IH1 TH AH0 L ER0 +RITTLE R IH1 T AH0 L +RITTMAN R IH1 T M AH0 N +RITTNER R IH1 T N ER0 +RITTS R IH1 T S +RITUAL R IH1 CH UW0 AH0 L +RITUALISTIC R IH2 CH UW0 AH0 L IH1 S T IH0 K +RITUALISTICALLY R IH2 CH UW0 AH0 L IH1 S T IH0 K AH0 L IY0 +RITUALISTICALLY(1) R IH2 CH UW0 AH0 L IH1 S T IH0 K L IY0 +RITUALS R IH1 CH UW0 AH0 L Z +RITZ R IH1 T S +RITZEL R IH1 T Z AH0 L +RITZENTHALER R IH1 T Z IH0 N TH AH0 L ER0 +RITZENTHALER(1) R IH1 T S IH0 N TH AA2 L ER0 +RITZER R IH1 T Z ER0 +RITZERT R IH1 T Z ER0 T +RITZIEST R IH1 T S IY0 AH0 S T +RITZMAN R IH1 T S M AH0 N +RITZY R IH1 T S IY0 +RIUNITE R IY0 UW0 N AY1 T +RIUNITE(1) R IY0 UW0 N AY1 T IY0 +RIVA R IY1 V AH0 +RIVAL R AY1 V AH0 L +RIVAL'S R AY1 V AH0 L Z +RIVALED R AY1 V AH0 L D +RIVALING R AY1 V AH0 L IH0 NG +RIVALING(1) R AY1 V L IH0 NG +RIVALRIES R AY1 V AH0 L R IY0 Z +RIVALRY R AY1 V AH0 L R IY0 +RIVALS R AY1 V AH0 L Z +RIVALS' R AY1 V AH0 L Z +RIVARD R IH1 V ER0 D +RIVAS R IY1 V AA0 Z +RIVEN R IH1 V AH0 N +RIVENBARK R IH1 V IH0 N B AA0 R K +RIVENBURG R IH1 V AH0 N B ER0 G +RIVENBURGH R IH1 V IH0 N B ER0 G +RIVER R IH1 V ER0 +RIVER'S R IH1 V ER0 Z +RIVERA R IH0 V EH1 R AH0 +RIVERBANK R IH1 V ER0 B AE2 NG K +RIVERBED R IH1 V ER0 B EH2 D +RIVERBEND R IH1 V ER0 B EH2 N D +RIVERBOAT R IH1 V ER0 B OW2 T +RIVERBOAT'S R IH1 V ER0 B OW2 T S +RIVERBOATS R IH1 V ER0 B OW2 T S +RIVERDALE R IH1 V ER0 D EY2 L +RIVERFRONT R IH1 V ER0 F R AH2 N T +RIVERHEAD R IH1 V ER0 HH EH2 D +RIVERO R IY0 V EH1 R OW0 +RIVERS R IH1 V ER0 Z +RIVERSIDE R IH1 V ER0 S AY2 D +RIVERSO R IH1 V ER0 S OW0 +RIVERWAY R IH1 V ER0 W EY2 +RIVERWOOD R IH1 V ER0 W UH2 D +RIVES R AY1 V Z +RIVEST R IH1 V IH0 S T +RIVET R IH1 V AH0 T +RIVETED R IH1 V AH0 T IH0 D +RIVETING R IH1 V AH0 T IH0 NG +RIVETS R IH1 V AH0 T S +RIVETT R IH1 V IH0 T +RIVETTE R IH0 V EH1 T +RIVIELLO R IY2 V IY0 EH1 L OW0 +RIVIERA R IH2 V IY0 EH1 R AH0 +RIVIERE R IH1 V IY0 EH0 R +RIVIERES R IH0 V Y IH1 R EH0 Z +RIVKIN R IH1 V K IH0 N +RIVKIND R IH1 V K IH0 N D +RIVLIN R IH1 V L IH0 N +RIX R IH1 K S +RIYAD R IY0 AA1 D +RIYAD(1) R IY0 AE1 D +RIYADH R IY0 AE1 D +RIYADH(1) R IY0 AA1 D +RIYALS R IY0 Y AA1 L Z +RIZ R IH1 Z +RIZER R AY1 Z ER0 +RIZK R IH1 Z K +RIZO R IY1 Z OW0 +RIZOR R AY1 Z ER0 +RIZZA R IH1 Z AH0 +RIZZI R IH1 Z IY0 +RIZZO R IH1 Z OW0 +RIZZOLI R IH0 Z OW1 L IY0 +RIZZOLO R IY0 T S OW1 L OW0 +RIZZUTI R IY0 T S UW1 T IY0 +RIZZUTO R IY0 T S UW1 T OW0 +RNA AA2 R EH2 N EY1 +RO R OW1 +ROA R OW1 AH0 +ROACH R OW1 CH +ROACHE R OW1 CH +ROACHES R OW1 CH IH0 Z +ROAD R OW1 D +ROAD'S R OW1 D Z +ROADBLOCK R OW1 D B L AA2 K +ROADBLOCKS R OW1 D B L AA2 K S +ROADCAP R OW1 D K AE2 P +ROADES R OW1 D Z +ROADHOUSE R OW1 D HH AW2 S +ROADIE R OW1 D IY0 +ROADMASTER R OW1 D M AE2 S T ER0 +ROADRAILER R OW1 D R EY2 L ER0 +ROADRUNNER R OW1 D R AH2 N ER0 +ROADS R OW1 D Z +ROADSHOW R OW1 D SH OW2 +ROADSIDE R OW1 D S AY2 D +ROADSIDES R OW1 D S AY2 D Z +ROADSTER R OW1 D S T ER0 +ROADWAY R OW1 D W EY2 +ROADWAYS R OW1 D W EY2 Z +ROADWORK R OW1 D W ER2 K +ROADY R OW1 D IY0 +ROALD R OW1 L D +ROAM R OW1 M +ROAMED R OW1 M D +ROAMING R OW1 M IH0 NG +ROAMS R OW1 M Z +ROAN R OW1 N +ROANE R OW1 N +ROANNA R OW1 N AH0 +ROANOKE R OW1 AH0 N OW2 K +ROAR R AO1 R +ROARED R AO1 R D +ROARING R AO1 R IH0 NG +ROARK R AO1 R K +ROARKE R AO1 R K +ROARS R AO1 R Z +ROARTY R AO1 R T IY0 +ROAST R OW1 S T +ROASTED R OW1 S T AH0 D +ROASTED(1) R OW1 S T IH0 D +ROASTER R OW1 S T ER0 +ROASTERS R OW1 S T ER0 Z +ROASTING R OW1 S T IH0 NG +ROASTS R OW1 S T S +ROAT R OW1 T +ROATH R OW1 TH +ROB R AA1 B +ROB'S R AA1 B Z +ROBACK R OW1 B AE2 K +ROBAINA R OW0 B EY1 N AH0 +ROBAK R OW1 B AH0 K +ROBAR R AH0 B AA1 R +ROBARDS R AA1 B ER0 D Z +ROBARE R OW0 B AA1 R EY0 +ROBARGE R AA1 B AA0 R G +ROBART R AA1 B AA2 R T +ROBARTS R AA1 B AA2 R T S +ROBB R AA1 B +ROBB'S R AA1 B Z +ROBBE R AA1 B +ROBBED R AA1 B D +ROBBEN R AA1 B AH0 N +ROBBER R AA1 B ER0 +ROBBERIES R AA1 B ER0 IY0 Z +ROBBERS R AA1 B ER0 Z +ROBBERSON R AA1 B ER0 S AH0 N +ROBBERY R AA1 B ER0 IY0 +ROBBIE R AA1 B IY0 +ROBBIE'S R AA1 B IY0 Z +ROBBIN R AA1 B IH0 N +ROBBING R AA1 B IH0 NG +ROBBINS R AA1 B IH0 N Z +ROBBS R AA1 B Z +ROBBY R AA1 B IY0 +ROBBY'S R AA1 B IY0 Z +ROBE R OW1 B +ROBECK R OW1 B EH2 K +ROBED R OW1 B D +ROBEL R OW1 B AH0 L +ROBELLO R OW0 B EH1 L OW0 +ROBELO R AA2 B EH1 L OW0 +ROBER R OW1 B ER0 +ROBERDS R AA1 B ER0 D Z +ROBERG R OW1 B ER0 G +ROBERGE R AA1 B ER0 JH +ROBERS R OW1 B ER0 Z +ROBERSON R AA1 B ER0 S AH0 N +ROBERT R AA1 B ER0 T +ROBERT'S R AA1 B ER0 T S +ROBERTA R AH0 B ER1 T AH0 +ROBERTI R AH0 B ER1 T IY0 +ROBERTO R AH0 B EH1 R T OW0 +ROBERTO(1) R OW0 B EH1 R T OW0 +ROBERTS R AA1 B ER0 T S +ROBERTS' R AA1 B ER0 T S +ROBERTS'S R AA1 B ER0 T S IH0 Z +ROBERTSHAW R AA1 B ER1 T SH AO1 +ROBERTSON R AA1 B ER0 T S AH0 N +ROBERTSON'S R AA1 B ER0 T S AH0 N Z +ROBES R OW1 B Z +ROBESON R OW1 B IH0 S AH0 N +ROBEY R OW1 B IY0 +ROBIA R OW1 B IY0 AH0 +ROBICHAUD R AA1 B IH0 SH OW2 +ROBICHAUX R AA1 B IH0 SH OW2 +ROBICHEAUX R AA1 B IH0 SH OW2 +ROBIDEAU R AA1 B IH0 D OW2 +ROBIDOUX R AA1 B IH0 D UW0 +ROBIE R OW1 B IY0 +ROBILLARD R AA1 B IH0 L ER0 D +ROBIN R AA1 B AH0 N +ROBIN(1) R AA1 B IH0 N +ROBIN'S R AA1 B AH0 N Z +ROBIN'S(1) R AA1 B IH0 N Z +ROBINA R AH0 B IY1 N AH0 +ROBINETT R AA1 B IH0 N EH0 T +ROBINETTE R AA1 B IH0 N EH2 T +ROBINHOOD R AA1 B IH0 N HH UH2 D +ROBINIA R OW0 B IY1 N IY0 AH0 +ROBINS R AA1 B AH0 N Z +ROBINS' R AA1 B AH0 N Z +ROBINS'S R AA1 B AH0 N Z IH0 Z +ROBINSON R AA1 B AH0 N S AH0 N +ROBINSON'S R AA1 B AH0 N S AH0 N Z +ROBINSONS R AA1 B AH0 N S AH0 N Z +ROBINSONS' R AA1 B AH0 N S AH0 N Z +ROBISHAW R AA1 B IH0 SH AO2 +ROBISON R AA1 B IH0 S AH0 N +ROBITAILLE R AA1 B IH0 T EY2 L +ROBITUSSIN R AA2 B IH0 T AH1 S IH0 N +ROBITUSSIN(1) R OW2 B AH0 T AH1 S IH0 N +ROBL R AA1 B AH0 L +ROBLE R OW1 B AH0 L +ROBLEDO R OW0 B L EY1 D OW0 +ROBLEE R AA1 B L IY2 +ROBLES R OW1 B AH0 L Z +ROBLEY R AA1 B L IY0 +ROBLIN R AA1 B L IH0 N +ROBLING R OW1 B AH0 L IH0 NG +ROBLING(1) R OW1 B L IH0 NG +ROBNETT R AA1 B N IH0 T +ROBO R OW1 B OW0 +ROBOCOP R OW1 B OW0 K AA2 P +ROBOT R OW1 B AA2 T +ROBOT(1) R OW1 B AH2 T +ROBOT'S R OW1 B AA2 T S +ROBOT'S(1) R OW1 B AH2 T S +ROBOTIC R OW2 B AA1 T IH0 K +ROBOTICS R OW2 B AA1 T IH0 K S +ROBOTS R OW1 B AA2 T S +ROBOTS(1) R OW1 B AH2 T S +ROBS R AA1 B Z +ROBSON R AA1 B S AH0 N +ROBUCK R OW1 B AH0 K +ROBUST R OW0 B AH1 S T +ROBUSTA R AO2 B UH1 S T AH0 +ROBUSTAS R AO2 B UH1 S T AH0 S +ROBUSTELLI R OW2 B AH0 S T EH1 L IY0 +ROBUSTELLI'S R OW2 B AH0 S T EH1 L IY0 Z +ROBUSTLY R OW2 B AH1 S T L IY0 +ROBUSTNESS R OW0 B AH1 S T N AH0 S +ROBY R OW1 B IY0 +ROBYN R AA1 B IH0 N +ROC R AA1 K +ROCA R OW1 K AH0 +ROCAP R OW1 K AE2 P +ROCARD R OW1 K ER0 D +ROCARD(1) R OW1 K AA2 R D +ROCARD(2) R OW2 SH AA1 R D +ROCARD(3) R AH0 K AA1 R D +ROCCA R AA1 K AH0 +ROCCAFORTE R OW0 K AH0 F AO1 R T IY0 +ROCCAS R AA1 K AH0 S +ROCCHI R OW1 K IY0 +ROCCHIO R OW1 K IY0 OW0 +ROCCO R AA1 K OW0 +ROCCO'S R AA1 K OW0 Z +ROCH R AA1 K +ROCHA R OW1 K AH0 +ROCHAT R AA1 CH AH0 T +ROCHBERG R OW1 CH B ER0 G +ROCHE R OW1 CH +ROCHE(1) R OW1 SH +ROCHE'S R OW1 SH IH0 Z +ROCHEFORT R AA1 K IH0 F ER0 T +ROCHEFORT(1) R AA1 SH F ER0 T +ROCHEFORT(2) R AA1 K F ER0 T +ROCHELEAU R AA1 SH IH0 L OW0 +ROCHELLA R AH0 CH EH1 L AH0 +ROCHELLE R OW0 SH EH1 L +ROCHELLE(1) R AH2 SH EH1 L +ROCHELLE'S R OW0 SH EH1 L Z +ROCHELLE'S(1) R AH2 SH EH1 L Z +ROCHER R OW1 CH ER0 +ROCHER(1) R OW1 SH ER0 +ROCHESTER R AA1 CH EH2 S T ER0 +ROCHESTER'S R AA1 CH EH2 S T ER0 Z +ROCHETTE R AH0 SH EH1 T +ROCHFORD R AA1 CH F ER0 D +ROCHLIN R AA1 K L IH0 N +ROCHON R AA1 CH AH0 N +ROCK R AA1 K +ROCK'N'ROLL R AA1 K AH0 N R OW1 L +ROCK'S R AA1 K S +ROCK-AND-ROLL R AA1 K AE1 N D R OW1 L +ROCKABILLY R AA1 K AH0 B IH2 L IY0 +ROCKAFELLOW R AA1 K AH0 F EH2 L OW0 +ROCKAWAY R AA1 K AH0 W EY2 +ROCKE R AA1 K +ROCKED R AA1 K T +ROCKEFELLER R AA1 K AH0 F EH2 L ER0 +ROCKEFELLER'S R AA1 K AH0 F EH2 L ER0 Z +ROCKEFELLERS R AA1 K AH0 F EH2 L ER0 Z +ROCKEL R AA1 K AH0 L +ROCKENBACH R AA1 K IH0 N B AA0 K +ROCKER R AA1 K ER0 +ROCKERS R AA1 K ER0 Z +ROCKET R AA1 K AH0 T +ROCKET'S R AA1 K AH0 T S +ROCKETDYNE R AA1 K IH0 T D AY2 N +ROCKETED R AA1 K AH0 T IH0 D +ROCKETING R AA1 K AH0 T IH0 NG +ROCKETRY R AA1 K AH0 T R IY0 +ROCKETS R AA1 K AH0 T S +ROCKETT R AA1 K IH0 T +ROCKETTE R AA0 K EH1 T +ROCKETTES R AA0 K EH1 T S +ROCKEY R AA1 K IY0 +ROCKFORD R AA1 K F ER0 D +ROCKHILL R AA1 K HH IH2 L +ROCKHOLD R AA1 K HH OW2 L D +ROCKHOLT R AA1 K HH OW2 L T +ROCKIES R AA1 K IY0 Z +ROCKIN' R AA1 K IH0 N +ROCKING R AA1 K IH0 NG +ROCKINGHAM R AA1 K IH0 NG HH AE2 M +ROCKLAND R AA1 K L AH0 N D +ROCKLEY R AA1 K L IY0 +ROCKLIN R AA1 K L IH0 N +ROCKMAN R AA1 K M AH0 N +ROCKMORE R AA1 K M AO0 R +ROCKNE R AA1 K N IY0 +ROCKOFF R AA1 K AO2 F +ROCKOW R AA1 S K OW0 +ROCKPORT R AA1 K P AO2 R T +ROCKRESORT R AA1 K R IH0 Z AO2 R T +ROCKRESORTS R AA1 K R IH0 Z AO2 R T S +ROCKROSE R AA1 K R OW2 Z +ROCKS R AA1 K S +ROCKVILLE R AA1 K V IH2 L +ROCKWELL R AA1 K W EH2 L +ROCKWELL'S R AA1 K W EH2 L Z +ROCKWOOD R AA1 K W UH2 D +ROCKY R AA1 K IY0 +ROCOCO R AH0 K OW1 K OW2 +ROCQUE R AA1 K +ROD R AA1 D +RODA R OW1 D AH0 +RODABAUGH R AA1 D AH0 B AO0 +RODAK R OW1 D AH0 K +RODALE R OW1 D EY2 L +RODARTE R AA1 D AA0 R T +RODAS R OW1 D AH0 Z +RODD R AA1 D +RODDEN R AA1 D AH0 N +RODDENBERRY R AA1 D AH0 N B EH0 R IY0 +RODDEY R AA1 D IY0 +RODDICK R AA1 D IH2 K +RODDIE R AA1 D IY0 +RODDING R AA1 D IH0 NG +RODDY R AA1 D IY0 +RODE R OW1 D +RODEBAUGH R AA1 D IH0 B AO0 +RODEFER R AA1 D IH0 F ER0 +RODEFFER R AA1 D IH0 F ER0 +RODEHEAVER R AA1 D IH0 HH IY0 V ER0 +RODELA R OW0 D EH1 L AH0 +RODELL R AA1 D AH0 L +RODEN R OW1 D AH0 N +RODENBAUGH R AA1 D IH0 N B AW0 +RODENBECK R OW1 D AH0 N B EH0 K +RODENBERG R OW1 D AH0 N B ER0 G +RODENBERGER R OW1 D AH0 N B ER0 G ER0 +RODENBURG R OW1 D AH0 N B ER0 G +RODENT R OW1 D AH0 N T +RODENTICIDE R OW0 D EH1 N T IH0 S AY0 D +RODENTS R OW1 D AH0 N T S +RODEO R OW1 D IY0 OW2 +RODEOS R OW1 D IY0 OW2 Z +RODER R OW1 D ER0 +RODERICA R OW0 D ER0 IY1 K AH0 +RODERICK R AA1 D R IH0 K +RODERICK'S R AA1 D R IH0 K S +RODES R OW1 D Z +RODEWALD R AA1 D UW0 AO0 L D +RODEWAY R OW1 D W EY2 +RODGE R AA1 JH +RODGER R AA1 JH ER0 +RODGERS R AA1 JH ER0 Z +RODGIN R AA1 JH IH0 N +RODHAM R AO1 D AH0 M +RODI R OW1 D IY0 +RODICK R AA1 D IH0 K +RODIER R OW1 D IY0 ER0 +RODIME R OW0 D IY1 M +RODIN R OW1 D IH0 N +RODIN(1) R OW2 D AE1 N +RODINE R OW0 D IY1 N IY0 +RODINO R OW0 D IY1 N OW0 +RODKEY R AA1 D K IY2 +RODMAN R AA1 D M AH0 N +RODMAN'S R AA1 D M AH0 N Z +RODMOND R AA1 D M AH0 N D +RODMUND R AA1 D M AH0 N D +RODNEY R AA1 D N IY0 +RODOCKER R AA1 D AH0 K ER0 +RODOLF R AA1 D OW0 L F +RODOLFO R OW0 D AA1 L F OW0 +RODOLPH R OW1 D AA2 L F +RODRICK R AA1 D R IH0 K +RODRIGEUZ R OW0 D R IY1 JH UW0 Z +RODRIGO R AH0 D R IY1 G OW0 +RODRIGUE R OW1 D R IY0 G +RODRIGUES R AA0 D R IY1 G IH0 S +RODRIGUEZ R AA0 D R IY1 G EH0 Z +RODRIGUEZ'S R AA0 D R IY1 G EH0 Z IH0 Z +RODRIQUES R AA0 D R IY1 G EH0 S +RODRIQUEZ R AA0 D R IY1 K EH0 Z +RODS R AA1 D Z +RODWELL R AA1 D W EH2 L +RODY R OW1 D IY0 +ROE R OW1 +ROEBER R OW1 B ER0 +ROEBKE R OW1 B K +ROEBLING R OW1 B L IH0 NG +ROEBUCK R OW1 B AH2 K +ROEBUCK'S R OW1 B AH2 K S +ROECKER R OW1 K ER0 +ROED R OW1 D +ROEDEL R OW1 D AH0 L +ROEDER R OW1 D ER0 +ROEDERER R OW1 D ER0 ER0 +ROEDIGER R OW1 D IH0 G ER0 +ROEDL R OW1 D AH0 L +ROEGNER R OW1 G N ER0 +ROEHI R OW1 IY0 +ROEHL R OW1 L +ROEHLING R OW1 L IH0 NG +ROEHM R OW1 M +ROEHR R AO1 R +ROEHRICH R AO1 R IH0 K +ROEHRIG R AO1 R IH0 G +ROEHRS R AO1 R Z +ROELAND R OW1 L AH0 N D +ROELKE R OW1 L K +ROELL R OW1 L +ROELLE R OW1 L +ROELLER R OW1 L ER0 +ROELOFS R OW1 L AH0 F S +ROEMER R OW1 M ER0 +ROEMMICH R OW1 M IH0 K +ROEN R OW1 N +ROEPER R OW1 P ER0 +ROEPKE R OW1 P K +ROES R OW1 Z +ROESCH R OW1 SH +ROESE R OW1 S +ROESEL R OW1 S AH0 L +ROESER R OW1 Z ER0 +ROESKE R OW1 S K +ROESLER R OW1 S AH0 L ER0 +ROESLER(1) R OW1 S L ER0 +ROESNER R OW1 S N ER0 +ROESSLER R OW1 S AH0 L ER0 +ROESSLER(1) R OW1 S L ER0 +ROESSNER R OW1 S N ER0 +ROETHER R OW1 DH ER0 +ROETHLER R OW1 TH AH0 L ER0 +ROETHLER(1) R OW1 TH L ER0 +ROETTGER R OW1 T G ER0 +ROEVER R AA1 EH0 V ER0 +ROFF R AO1 F +ROFFE R AA1 F +ROFFMAN R AO1 F M AH0 N +ROFIN R OW1 F IH0 N +ROG R AA1 G +ROGACHEV R OW1 G AH0 CH AH0 V +ROGACKI R AH0 G AA1 T S K IY0 +ROGAINE R OW0 G EY1 N +ROGAL R OW1 G AH0 L +ROGALA R OW0 G AA1 L AH0 +ROGALLA R OW0 G AA1 L AH0 +ROGALSKI R AH0 G AA1 L S K IY0 +ROGAN R OW1 G AH0 N +ROGEL R OW1 G AH0 L +ROGELIO R OW0 G IY1 L IY0 OW0 +ROGER R AA1 JH ER0 +ROGER'S R AA1 JH ER0 Z +ROGERNOMICS R OW2 G ER0 N AA1 M IH0 K S +ROGERS R AA1 JH ER0 Z +ROGERS' R AA1 JH ER0 Z +ROGERS'S R AA1 JH ER0 Z IH0 Z +ROGERSON R AA1 G ER0 S AH0 N +ROGET R OW0 ZH EY1 +ROGET'S R OW0 ZH EY1 Z +ROGGE R AA1 G +ROGGENBUCK R AA1 G IH0 N B AH0 K +ROGGENKAMP R AA1 G IH0 N K AE0 M P +ROGGIO R AA1 JH IY0 OW2 +ROGGOW R AA1 G OW0 +ROGIER R OW1 ZH Y ER0 +ROGIN R OW1 G IH0 N +ROGINSKI R AH0 G IH1 N S K IY0 +ROGNESS R AA1 G N IH0 S +ROGOFF R AA1 G AO0 F +ROGOWSKI R AH0 G AO1 F S K IY0 +ROGOZINSKI R AH0 G AH0 Z IH1 N S K IY0 +ROGSTAD R AA1 G S T AH0 D +ROGUE R OW1 G +ROGUES R OW1 G Z +ROGUS R OW1 G AH0 S +ROH R OW1 +ROH'S R OW1 Z +ROHAN R OW1 AH0 N +ROHANA R AH0 HH AE1 N AH0 +ROHATYN R AA1 HH AH0 T IH0 N +ROHATYN(1) R OW0 HH AE1 T AH0 N +ROHATYN'S R AA1 HH AH0 T IH0 N Z +ROHATYN'S(1) R OW0 HH AE1 T AH0 N Z +ROHDE R OW1 D +ROHDE(1) R OW1 D AH0 +ROHE R OW1 +ROHER R OW1 ER0 +ROHL R OW1 L +ROHLAND R OW1 L AH0 N D +ROHLEDER R OW1 L IH0 D ER0 +ROHLF R OW1 L F +ROHLFING R OW1 L F IH0 NG +ROHLFS R OW1 L F S +ROHLICEK R AA1 L AH0 CH EH0 K +ROHLING R OW1 L IH0 NG +ROHLMAN R OW1 L M AH0 N +ROHLOFF R OW1 L AO0 F +ROHM R OW1 M +ROHMAN R OW1 M AH0 N +ROHMER R OW1 M ER0 +ROHN R AA1 N +ROHNER R OW1 N ER0 +ROHR R AO1 R +ROHRBACH R AO1 R B AA0 K +ROHRBACHER R AO1 R B AA0 K ER0 +ROHRBACK R AO1 R B AE0 K +ROHRBAUGH R AO1 R B AW0 +ROHRBOUGH R AO1 R B AW0 +ROHRER R AO1 R ER0 +ROHRICH R AO1 R IH0 K +ROHRIG R AO1 R IH0 G +ROHRMAN R AO1 R M AH0 N +ROHRS R AO1 R Z +ROHS R OW1 Z +ROHSTOFF R OW1 S T AO0 F +ROHWEDDER R OW1 W IH0 D ER0 +ROHWEDER R OW1 W IH0 D ER0 +ROHWER R OW1 W ER0 +ROHYPNOL R OW2 HH AY1 P N AO2 L +ROI R OY1 +ROIG R OY1 G +ROIL R OY1 L +ROILED R OY1 L D +ROILING R OY1 L IH0 NG +ROISTER R OY1 S T ER0 +ROISTER'S R OY1 S T ER0 Z +ROJAS R OW1 HH AA0 S +ROJEK R OW1 Y EH0 K +ROJO R OW1 JH OW0 +ROKA R OW1 K AH0 +ROKAHR R OW1 K AA2 R +ROKAR R OW1 K AA2 R +ROKICKI R AH0 K IH1 K IY0 +ROKOS R OW1 K OW0 Z +ROKOSZ R AA1 K AH0 SH +ROL R OW1 L +ROLAN R OW1 L AH0 N +ROLAND R OW1 L AH0 N D +ROLANDA R OW0 L AA1 N D AH0 +ROLANDO R OW0 L AA1 N D OW0 +ROLDAN R OW1 L D AH0 N +ROLE R OW1 L +ROLEMODEL R OW1 L M AA2 D AH0 L +ROLEMODELS R OW1 L M AA2 D AH0 L Z +ROLEN R OW1 L AH0 N +ROLEPLAYING R OW1 L P L EY2 IH0 NG +ROLES R OW1 L Z +ROLETTE R OW0 L EH1 T +ROLEX R OW1 L EH0 K S +ROLEY R OW1 L IY0 +ROLF R OW1 L F +ROLFE R OW1 L F +ROLFES R OW1 L F S +ROLFS R OW1 L F S +ROLFSON R OW1 L F S AH0 N +ROLIN R OW1 L IH0 N +ROLING R OW1 L IH0 NG +ROLISON R AA1 L IH0 S AH0 N +ROLL R OW1 L +ROLL'S R OW1 L Z +ROLLA R AA1 L AH0 +ROLLAND R AA1 L AH0 N D +ROLLAND'S R OW1 L AH0 N D Z +ROLLBACK R OW1 L B AE2 K +ROLLBACKS R OW1 L B AE2 K S +ROLLE R OW1 L +ROLLED R OW1 L D +ROLLEI R OW1 L EY0 +ROLLEN R AO1 L AH0 N +ROLLER R OW1 L ER0 +ROLLERBLADE R OW1 L ER0 B L EY2 D +ROLLERBLADES R OW1 L ER0 B L EY2 D Z +ROLLERBLADING R OW1 L ER0 B L EY2 D IH0 NG +ROLLERCOASTER R OW1 L ER0 K OW2 S T ER0 +ROLLERS R OW1 L ER0 Z +ROLLET R OW0 L EH1 T +ROLLEY R AA1 L IY0 +ROLLI R AA1 L IY0 +ROLLICKING R AA1 L IH0 K IH0 NG +ROLLIE R OW1 L IY0 +ROLLIE(1) R AO1 L IY0 +ROLLIN R OW1 L IH0 N 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P N OW0 +RUPOSI R UW0 P OW1 S IY0 +RUPP R AH1 P +RUPPE R AH1 P +RUPPEL R AH1 P AH0 L +RUPPENTHAL R AH1 P IH0 N TH AH0 L +RUPPERT R AH1 P ER0 T +RUPPRECHT R UW1 P R EH2 K T +RUPRECHT R AH1 P R IH0 K T +RUPTURE R AH1 P CH ER0 +RUPTURED R AH1 P CH ER0 D +RUPTURES R AH1 P CH ER0 Z +RUPTURING R AH1 P CH ER0 IH0 NG +RURAL R UH1 R AH0 L +RURIK R UH1 R IH0 K +RURITANIA R UH2 R AH0 T EY1 N IY0 AH0 +RUS R AH1 S +RUSALKA R UW2 S AE1 L K AH0 +RUSCH R AH1 SH +RUSCHE R AH1 SH +RUSCITTI R UW0 S CH IY1 T IY0 +RUSCONI R UW0 S K OW1 N IY0 +RUSE R UW1 Z +RUSED R UW1 Z D +RUSELER R UW1 S IH0 L ER0 +RUSES R UW1 Z IH0 Z +RUSH R AH1 SH +RUSH'S R AH1 SH IH0 Z +RUSHDIE R AH1 SH D IY0 +RUSHDIE'S R AH1 SH D IY0 Z +RUSHED R AH1 SH T +RUSHER R AH1 SH ER0 +RUSHES R AH1 SH AH0 Z +RUSHES(1) R AH1 SH IH0 Z +RUSHFORD R AH1 SH F ER0 D +RUSHIN R AH1 SH IH0 N +RUSHING R AH1 SH IH0 NG +RUSHLOW R AH1 SH L OW2 +RUSHMORE R AH1 SH M AO0 R +RUSHTON R AH1 SH T AH0 N +RUSIN R UW1 S IH0 N +RUSINKO R UW2 S IH1 NG K OW0 +RUSK R AH1 S K +RUSK'S R AH1 S K S +RUSKIN R AH1 S K IH0 N +RUSLAN R AH1 S L AH0 N +RUSNAK R AH1 S N AH0 K +RUSNOCK R AH1 S N AH0 K +RUSS R AH1 S +RUSSA R UW1 S AH0 +RUSSAK R AH1 S AH0 K +RUSSE R AH1 S +RUSSEL R AH1 S AH0 L +RUSSEL'S R AH1 S AH0 L Z +RUSSELL R AH1 S AH0 L +RUSSELL'S R AH1 S AH0 L Z +RUSSELLVILLE R AH1 S AH0 L V IH2 L +RUSSERT R AH1 S ER0 T +RUSSET R AH1 S IH0 T +RUSSETS R AH1 S IH0 T S +RUSSETT R AH1 S IH0 T +RUSSEY R AH1 S IY0 +RUSSI R UW1 S IY0 +RUSSIA R AH1 SH AH0 +RUSSIA'S R AH1 SH AH0 Z +RUSSIAN R AH1 SH AH0 N +RUSSIAN'S R AH1 SH AH0 N Z +RUSSIANS R AH1 SH AH0 N Z +RUSSIANS' R AH1 SH AH0 N Z +RUSSIFICATION R AH2 S AH0 F AH0 K EY1 SH AH0 N +RUSSIFICATION(1) R UW2 S AH0 F AH0 K EY1 SH AH0 N +RUSSIFIED R AH1 S AH0 F AY0 D +RUSSIN R AH1 S IH0 N +RUSSLER R AH1 S L ER0 +RUSSMAN R AH1 S M AH0 N +RUSSO R UW1 S OW0 +RUSSOLILLO R UW2 S OW0 L IH1 L OW0 +RUSSOLILLO(1) R UW2 S OW0 L IY1 OW0 +RUSSOM R AH1 S AH0 M +RUSSOMANNO R AH1 S AH0 M IH0 N OW0 +RUSSOW R AH1 S OW0 +RUSSUM R AH1 S AH0 M +RUST R AH1 S T +RUST'S R AH1 S T S +RUSTAD R AH1 S T AA0 D +RUSTED R AH1 S T IH0 D +RUSTIC R AH1 S T IH0 K +RUSTIER R AH1 S T IY0 ER0 +RUSTIEST R AH1 S T IY0 AH0 S T +RUSTIGAN R AH1 S T IH0 G AH0 N +RUSTIN R AH1 S T IH0 N +RUSTING R AH1 S T IH0 NG +RUSTLE R AH1 S AH0 L +RUSTLER R AH1 S L ER0 +RUSTLERS R AH1 S AH0 L ER0 Z +RUSTLERS(1) R AH1 S L ER0 Z +RUSTLING R AH1 S L IH0 NG +RUSTON R AH1 S T AH0 N +RUSTPROOF R AH1 S T P R UW1 F +RUSTPROOFING R AH1 S T P R UW1 F IH0 NG +RUSTS R AH1 S T S +RUSTY R AH1 S T IY0 +RUSTY'S R AH1 S T IY0 Z +RUSTYS R AH1 S T IY0 Z +RUSZKOWSKI R AH0 SH K AO1 F S K IY0 +RUT R AH1 T +RUTA R UW1 T AH0 +RUTABAGA R UW1 T AH0 B EY0 G AH0 +RUTABAGAS R UW1 T AH0 B EY0 G AH0 Z +RUTAN R UW1 T AH0 N +RUTAN'S R UW1 T AH0 N Z +RUTER R UW1 T ER0 +RUTGARD R AH1 T G AA2 R D +RUTGER R AH1 T G ER0 +RUTGER'S R AH1 T G ER0 Z +RUTGERS R AH1 T G ER0 Z +RUTGERS' R AH1 T G ER0 Z +RUTH R UW1 TH +RUTH'S R UW1 TH S +RUTH-ANN R UW2 TH AE1 N +RUTH-ANNE R UW2 TH AE1 N +RUTHANN R UW2 TH AE1 N +RUTHENBERG R AH1 TH AH0 N B ER0 G +RUTHER R UW1 TH ER0 +RUTHERFORD R AH1 TH ER0 F ER0 D +RUTHIE R UW1 TH IY0 +RUTHLESS R UW1 TH L AH0 S +RUTHLESSLY R UW1 TH L AH0 S L IY0 +RUTHLESSNESS R UW1 TH L AH0 S N AH0 S +RUTHVEN R AH1 TH V AH0 N +RUTIGLIANO R UW0 T IY0 G L IY0 AA1 N OW0 +RUTILE R UW1 T IY0 L +RUTKOSKI R AH0 T K AW1 S K IY0 +RUTKOWSKI R AH0 T K AO1 F S K IY0 +RUTLAND R AH1 T L AH0 N D +RUTLEDGE R AH1 T L IH0 JH +RUTLEY R AH1 T L IY0 +RUTMAN R AH1 T M AH0 N +RUTS R AH1 T S +RUTSKOI R UW1 T S K OY0 +RUTSKOI'S R UW1 T S K OY0 Z +RUTSTEIN R AH1 T S T AY2 N +RUTSTEIN(1) R AH1 T S T IY2 N +RUTT R AH1 T +RUTTAN R AH1 T AH0 N +RUTTED R AH1 T IH0 D +RUTTEN R AH1 T AH0 N +RUTTENBERG R AH1 T AH0 N B ER0 G +RUTTER R AH1 T ER0 +RUTTLE R AH1 T AH0 L +RUTTLES R AH1 T AH0 L Z +RUTTS R AH1 T S +RUTZ R AH1 T S +RUTZEN R AH1 T Z AH0 N +RUUD R UW1 D +RUVALCABA R UW0 V AA0 L K AA1 B AH0 +RUVOLO R UW0 V OW1 L OW0 +RUWE R UW1 W +RUX R AH1 K S +RUXPIN R AH1 K S P IH0 N +RUXPIN'S R AH1 K S P IH0 N Z +RUYBAL R AY1 B AH0 L +RUYLE R AY1 L +RUZEK R UW1 Z EH0 K +RUZICH R AH1 Z IH0 HH +RUZICKA R UW2 Z IH1 K AH0 +RUZZO R UW1 Z OW0 +RWANDA R AH0 W AA1 N D AH0 +RWANDA(1) R UW2 AA1 N D AH0 +RWANDA'S R AH0 W AA1 N D AH0 Z +RWANDA'S(1) R UW2 AA1 N D AH0 Z +RWANDAN R AH0 W AA1 N D AH0 N +RWANDAN(1) R UW2 AA1 N D AH0 N +RWANDAN'S R AH0 W AA1 N D AH0 N Z +RWANDAN'S(1) R UW2 AA1 N D AH0 N Z +RWANDANS R AH0 W AA1 N D AH0 N Z +RWANDANS(1) R UW2 AA1 N D AH0 N Z +RWANDESE R AH0 W AA2 D IY1 Z +RWANDESE(1) R UW0 AA2 D IY1 Z +RYAL R IY0 AA1 L +RYALL R IY0 AA1 L +RYALS R IY0 AA1 L Z +RYAN R AY1 AH0 N +RYAN'S R AY1 AH0 N Z +RYANAIR R AY1 AH0 N EH2 R +RYANODINE R AY0 AE1 N AH0 D IY0 N +RYANS R AY1 AH0 N Z +RYAVA R AY0 AA1 V AH0 +RYAVE R AY1 AH0 V +RYBA R IH1 B AH0 +RYBACK R AY1 B AE2 K +RYBACKI R IH0 B AA1 T S K IY0 +RYBACKI(1) R IH2 B AA1 K IY0 +RYBAK R IH1 B AH0 K +RYBAKOV R AY1 B AH0 K AA2 V +RYBAKOV'S R AY1 B AH0 K AA2 V Z +RYBARCZYK R IH1 B ER0 CH IH0 K +RYBERG R AY1 B ER0 G +RYBICKI R IH0 B IH1 T S K IY0 +RYBINSKI R IH0 B IH1 N S K IY0 +RYBKA R IH1 B K AH0 +RYBOLT R IH1 B OW0 L T +RYBURN R IH1 B ER0 N +RYCHLIK R IH1 CH L IH0 K +RYCHLIK(1) R IH1 K L IH0 K +RYCKMAN R IH1 K M AH0 N +RYCROFT R IH1 K R AH0 F T +RYCZEK R IH1 CH EH0 K +RYDBERG R IH1 D B ER0 G +RYDELL R IH1 D AH0 L +RYDEN R AY1 D AH0 N +RYDER R AY1 D ER0 +RYDER'S R AY1 D ER0 Z +RYDMAN R IH1 D M AH0 N +RYDZEWSKI R IH0 JH EH1 F S K IY0 +RYE R AY1 +RYEN R AY1 AH0 N +RYER R AY1 ER0 +RYERSON R AY1 R S AH0 N +RYGEL R IH1 G EH0 L +RYGIEL R IH1 G IY2 AH0 L +RYKA R AY1 K AH0 +RYKER R AY1 K ER0 +RYKIEL R IY1 K Y EH0 L +RYKIEL(1) R IH1 K Y EH0 L +RYKOFF R AY1 K AO2 F +RYKOWSKI R IH0 K AO1 F S K IY0 +RYLAN R AY1 L AH0 N +RYLAND R IH1 L AH0 N D +RYLANDER R IH1 L AH0 N D ER0 +RYLE R AY1 L +RYLEE R IH1 L IY0 +RYLES R AY1 L Z +RYLEY R AY1 L IY0 +RYMAN R AY1 M AH0 N +RYMER R AY1 M ER0 +RYNDERS R IH1 N D ER0 Z +RYNEARSON R IH1 N ER0 S AH0 N +RYNER R AY1 N ER0 +RYNES R AY1 N Z +RYNO R IH1 N OW0 +RYOBI R AY2 OW1 B IY0 +RYOHEI R AY1 OW0 HH EY2 +RYON R AY1 AH0 N +RYRIE R AY1 R IY0 +RYS R IH1 S +RYSAVY R IH0 S AA1 V IY0 +RYSER R AY1 S ER0 +RYSKAMP R AY1 S K AE2 M P +RYTHER R IH1 DH ER0 +RYTON R IH1 T AH0 N +RYUTARO R Y UW0 T AA1 R OW0 +RYUZO R AY2 UW1 Z OW0 +RYZHKOV R AY1 Z K AA0 V +RZASA ER0 Z AA1 S AH0 +RZEPKA ER0 Z EH1 P K AH0 +S EH1 S +S'S EH1 S IH0 Z +S. EH1 S +S.'S EH1 S IH0 Z +SA S AA1 +SAAB S AA1 B +SAAB'S S AA1 B Z +SAAD S AA1 D +SAAL S AA1 L +SAAM S AA1 M +SAAMSTAAN S AA1 M S T AA2 N +SAAR S AA1 R +SAARI S AA1 R IY0 +SAARINEN S AA1 R IH0 N AH0 N +SAARINEN(1) S AH0 R IY1 N AH0 N +SAATCHI S AA1 CH IY0 +SAATCHI'S S AA1 CH IY0 Z +SAATHOFF S AA1 T HH AO2 F +SAAVEDRA S AA0 V EY1 D R AH0 +SAB'S S AE1 B Z +SABA S AA1 B AH0 +SABAH S AA1 B AH0 +SABALA S AA0 B AA1 L AH0 +SABALAN S AE1 B AH0 L AH0 N +SABAN S EY1 B AH0 N +SABAS S AA1 B AH0 Z +SABAT S AA1 B AA0 T +SABATINE S AA0 B AA0 T IY1 N IY0 +SABATINI S AE2 B AH0 T IY1 N IY0 +SABATINO S AA0 B AA0 T IY1 N OW0 +SABATISTA S AA2 B AH0 T IY1 S T AH0 +SABATISTA'S S AA2 B AH0 T IY1 S T AH0 Z +SABATISTAS S AA2 B AH0 T IY1 S T AH0 Z +SABATISTAS' S AA2 B AH0 T IY1 S T AH0 Z +SABATKA S AA0 B AA1 T K AH0 +SABATO S AA0 B AA1 T OW0 +SABAUDIA S AH0 B AO1 D IY0 AH0 +SABB S AE1 B +SABBAGH S AE1 B AH0 G +SABBATH S AE1 B AH0 TH +SABBATHS S AE1 B AH0 TH S +SABBATICAL S AH0 B AE1 T IH0 K AH0 L +SABBATICALS S AH0 B AE1 T IH0 K AH0 L Z +SABEDRA S AH0 B EH1 D R AH0 +SABEL S AA0 B EH1 L +SABELLA S AH0 B EH1 L AH0 +SABENA S AH0 B IY1 N AH0 +SABER S EY1 B ER0 +SABERBEIN S EY1 B ER0 B AY2 N +SABERBEIN'S S EY1 B ER0 B AY2 N Z +SABERS S EY1 B ER0 Z +SABERTECH S EY1 B ER0 T EH2 K +SABEY S EY1 B IY0 +SABIA S AA1 B IY0 AH0 +SABIN S EY1 B IH0 N +SABINA S AH0 B IY1 N AH0 +SABINE S AH0 B IY1 N +SABINE'S S AH0 B IY1 N Z +SABINO S AA0 B IY1 N OW0 +SABINS S EY1 B IH0 N Z +SABIR S EY1 B ER0 +SABIR(1) S AH0 B IH1 R +SABLAN S AE1 B L AH0 N +SABLE S EY1 B AH0 L +SABLES S EY1 B AH0 L Z +SABO S AA1 B OW0 +SABOL S AA0 B AO1 L +SABOL'S S AA0 B AO1 L Z +SABORTECH S EY1 B ER0 T EH2 K +SABOTAGE S AE1 B AH0 T AA2 ZH +SABOTAGED S AE1 B AH0 T AA2 ZH D +SABOTAGING S AE1 B AH0 T AA2 ZH IH0 NG +SABOTEUR S AE2 B AH0 T ER1 +SABOTEURS S AE2 B AH0 T ER1 Z +SABOTEURS(1) S AE2 B IH0 T AO1 R Z +SABOURIN S AE1 B UH0 R AE0 N +SABRA S AA1 B R AH0 +SABRE S EY1 B ER0 +SABRES S EY1 B ER0 Z +SABRETECH S EY1 B ER0 T EH2 K +SABRINA S AH0 B R IY1 N AH0 +SABRY S AA1 B R IY0 +SABTA S AE1 B T AH0 +SABUNUMA S AE0 B UW1 N AH0 M AH0 +SAC S AE1 K +SACCA S AE1 K AH0 +SACCHARIN S AE1 K ER0 AH0 N +SACCHARINE S AE1 K ER0 AY2 N +SACCO S AE1 K OW0 +SACCO'S S AE1 K OW0 Z +SACCOCCIO S AA0 K OW1 CH IY0 OW0 +SACCOMANNO S AE1 K AH0 M AE2 N OW0 +SACCONE S AA0 K OW1 N IY0 +SACCULE S AE1 K Y UW2 L +SACHA S AE1 CH AH0 +SACHDEV S AE1 CH D EH2 V +SACHER S AE1 K ER0 +SACHER(1) S AA1 SH ER0 +SACHET S AE0 SH EY1 +SACHI S AE1 CH IY0 +SACHIN S AE1 CH AH0 N +SACHS S AE1 K S +SACHS(1) S AA1 K S +SACHS' S AE1 K S +SACHS'S S AE1 K S IH0 Z +SACHSE S AE1 CH S +SACILOR S AE1 S AH0 L ER0 +SACIRBEY S AA1 K ER0 B IY0 +SACIRBEY'S S AA1 K ER0 B IY0 Z +SACK S AE1 K +SACKED S AE1 K T +SACKETT S AE1 K IH0 T +SACKING S AE1 K IH0 NG +SACKLER S AE1 K L ER0 +SACKMAN S AE1 K M AH0 N +SACKMANN S AE1 K M AH0 N +SACKRIDER S AE1 K R AY2 D ER0 +SACKS S AE1 K S +SACKSTEDER S AE1 K S T EH2 D ER0 +SACKVILLE S AE1 K V IH2 L +SACO S EY1 K OW0 +SACRA S AE1 K R AH0 +SACRAMENT S AE1 K R AH0 M AH0 N T +SACRAMENTAL S AE1 K R AH0 M AH0 N T AH0 L +SACRAMENTO S AE2 K R AH0 M EH1 N T OW0 +SACRAMENTO'S S AE2 K R AH0 M EH1 N T OW0 Z +SACRAMENTS S AE1 K R AH0 M AH0 N T S +SACRED S EY1 K R IH0 D +SACREDNESS S EY1 K R IH0 D N IH0 S +SACRIFICE S AE1 K R AH0 F AY2 S +SACRIFICED S AE1 K R AH0 F AY2 S T +SACRIFICES S AE1 K R AH0 F AY2 S IH0 Z +SACRIFICIAL S AE2 K R AH0 F IH1 SH AH0 L +SACRIFICING S AE1 K R AH0 F AY2 S IH0 NG +SACRILEGE S AE1 K R AH0 L AH0 JH +SACRILEGIOUS S AE2 K R AH0 L EH1 JH IH0 S +SACROSANCT S AE1 K R OW0 S AE0 NG K T +SACS S AE1 K S +SAD S AE1 D +SADA S AA1 D AH0 +SADAKA S AH0 D AA1 K AH0 +SADAKO S AA0 D AA1 K OW0 +SADAO S AH0 D AW1 +SADAT S AA0 D AA1 T +SADAT(1) S AH0 D AE1 T +SADAT'S S AA0 D AA1 T S +SADAT'S(1) S AH0 D AE1 T S +SADDAM S AA1 D AH0 M +SADDAM(1) S AH0 D AA1 M +SADDAM'S S AA1 D AH0 M Z +SADDAM'S(1) S AH0 D AA1 M Z +SADDEN S AE1 D AH0 N +SADDENED S AE1 D AH0 N D +SADDENING S AE1 D AH0 N IH0 NG +SADDENING(1) S AE1 D N IH0 NG +SADDENS S AE1 D AH0 N Z +SADDER S AE1 D ER0 +SADDEST S AE1 D AH0 S T +SADDLE S AE1 D AH0 L +SADDLEBAG S AE1 D AH0 L B AE2 G +SADDLEBAGS S AE1 D AH0 L B AE2 G Z +SADDLED S AE1 D AH0 L D +SADDLER S AE1 D AH0 L ER0 +SADDLER(1) S AE1 D L ER0 +SADDLES S AE1 D AH0 L Z +SADDLING S AE1 D AH0 L IH0 NG +SADDLING(1) S AE1 D L IH0 NG +SADDORIS S AE1 D ER0 IH0 S +SADEGHI S AA0 D EH1 G IY0 +SADEH S AA1 D EH2 +SADEH-KONIECPOL S AA1 D EH2 K OW2 N IY0 EH1 K P AO2 L +SADEK S AE1 D IH0 K +SADELLA S AH0 D EH1 L AH0 +SADER S EY1 D ER0 +SADIE S AE1 D IY0 +SADIE'S S EY1 D IY0 Z +SADIRA S AA0 D IH1 R AH0 +SADISM S EY1 D IH0 Z AH0 M +SADIST S EY1 D AH0 S T +SADISTIC S AH0 D IH1 S T IH0 K +SADLER S AE1 D L ER0 +SADLIER S AE1 D L IY0 ER0 +SADLON S AE1 D L AH0 N +SADLOWSKI S AE0 D L AW1 S K IY0 +SADLY S AE1 D L IY0 +SADNESS S AE1 D N AH0 S +SADO S EY1 D OW0 +SADOFF S AE1 D AO2 F +SADOWSKI S AH0 D AO1 F S K IY0 +SADOWSKY S AH0 D AW1 S K IY0 +SADYE S AE1 D AY0 +SAECHAO S IY1 CH AW0 +SAEED S AA0 IY1 D +SAEGER S EH1 G ER0 +SAEHAN S EY1 AH0 N +SAELENS S EH1 L AH0 N Z +SAEMAUL S EY1 M AO0 L +SAENGER S EH1 N JH ER0 +SAENS'S S EY1 N Z IH0 Z +SAENZ S IY1 N Z +SAEZ S IY1 Z +SAFARI S AH0 F AA1 R IY0 +SAFARIK S AE1 F ER0 IH0 K +SAFARIS S AH0 F AA1 R IY0 Z +SAFDIE S AE1 F D IY0 +SAFE S EY1 F +SAFECARD S EY1 F K AA2 R D +SAFECARD'S S EY1 F K AA2 R D Z +SAFECO S EY1 F K OW0 +SAFEGUARD S EY1 F G AA2 R D +SAFEGUARDED S EY1 F G AA2 R D IH0 D +SAFEGUARDING S EY1 F G AA2 R D IH0 NG +SAFEGUARDS S EY1 F G AA2 R D Z +SAFEHOUSE S EY1 F HH AW2 S +SAFEKEEPING S EY1 F K IY1 P IH0 NG +SAFELY S EY1 F L IY0 +SAFER S EY1 F ER0 +SAFES S EY1 F S +SAFEST S EY1 F AH0 S T +SAFETIES S EY1 F T IY0 Z +SAFETY S EY1 F T IY0 +SAFETY'S S EY1 F T IY0 Z +SAFEWAY S EY1 F W EY2 +SAFEWAY'S S EY1 F W EY2 Z +SAFFELL S AE1 F AH0 L +SAFFER S AE1 F ER0 +SAFFERSTEIN S AE1 F ER0 S T IY2 N +SAFFERSTEIN(1) S AE1 F ER0 S T AY2 N +SAFFIR S AH0 F IY1 R +SAFFLE S AE1 F AH0 L +SAFFLOWER S AE1 F L AW2 ER0 +SAFFOLD S AE1 F OW2 L D +SAFFORD S AE1 F ER0 D +SAFFRAN S AE1 F R AH0 N +SAFFRON S AE1 F R AH0 N +SAFIAN S EY1 F IY0 AH0 N +SAFIER S AH0 F IH1 R +SAFING S EY1 F IH0 NG +SAFIR S AE1 F ER0 +SAFIRE S AH0 F AY1 R +SAFIRE'S S AH0 F AY1 R Z +SAFKO S AA1 F K OW0 +SAFLEY S AE1 F L IY0 +SAFRA S AE1 F R AH0 +SAFRA'S S AE1 F R AH0 Z +SAFRAN S AE1 F R AH0 N +SAFRANEK S AE1 F R AH0 N IH0 K +SAFRIT S AE1 F R IH0 T +SAG S AE1 G +SAGA S AA1 G AH0 +SAGAN S EY1 G AH0 N +SAGANSKY S AH0 G AE1 N S K IY0 +SAGAR S AA0 G AA1 R +SAGAS S AA1 G AH0 Z +SAGE S EY1 JH +SAGE'S S EY1 JH AH0 Z +SAGEBRUSH S EY1 JH B R AH2 SH +SAGEN S AE1 G AH0 N +SAGER S EY1 G ER0 +SAGERS S EY1 G ER0 Z +SAGES S EY1 JH IH0 Z +SAGGED S AE1 G D +SAGGESE S AE1 G IY0 Z +SAGGING S AE1 G IH0 NG +SAGINAW S AE1 G IH0 N AO2 +SAGITTAL S AE1 JH AH0 T AH0 L +SAGO S EY1 G OW0 +SAGONA S AA0 G OW1 N AH0 +SAGRAVES S AA0 G R AA1 V EH0 S +SAGS S AE1 G Z +SAGUARO S AH0 G W AO1 R OW0 +SAGUENAY S AE1 G AH0 N EY0 +SAHA S AA1 HH AH0 +SAHAGIAN S AH0 HH IY1 JH IY0 AH0 N +SAHAGUN S AE1 HH AH0 G AH0 N +SAHARA S AH0 HH EH1 R AH0 +SAHARAN S AE1 HH ER0 AH0 N +SAHGAL S AA1 G AH0 L +SAHL S AA1 L +SAHLEN S AA1 L AH0 N +SAHLI S AA1 L IY0 +SAHLIN S AA1 L IH0 N +SAHLMAN S AA1 L M AH0 N +SAHM S AE1 M +SAHR S AE1 R +SAI S AY1 +SAI(1) EH1 S EY1 AY1 +SAIA S AA1 Y AH0 +SAID S EH1 D +SAIDAN S EY1 D AH0 N +SAIDINER S EY1 D IH0 N ER0 +SAIF S AA2 IY1 F +SAIF(1) S AY1 F +SAIGON S AY2 G AA1 N +SAIKI S EY1 K IY0 +SAIL S EY1 L +SAILBOAT S EY1 L B OW2 T +SAILBOATS S EY1 L B OW2 T S +SAILED S EY1 L D +SAILER S EY1 L ER0 +SAILFISH S EY1 L F IH2 SH +SAILING S EY1 L IH0 NG +SAILOR S EY1 L ER0 +SAILOR'S S EY1 L ER0 Z +SAILORS S EY1 L ER0 Z +SAILORS' S EY1 L ER0 Z +SAILS S EY1 L Z +SAIN S EY1 N +SAINATO S AH0 N AA1 T OW0 +SAINDON S EY1 N D AH0 N +SAINE S EY1 N +SAINSBURY S EY1 N S B EH0 R IY0 +SAINT S EY1 N T +SAINT'S S EY1 N T S +SAINT-SAENS S EY1 N T S AA1 N Z +SAINTED S EY1 N T IH0 D +SAINTHOOD S EY1 N T HH UH2 D +SAINTLY S EY1 N T L IY0 +SAINTS S EY1 N T S +SAINTS' S EY1 N T S +SAINZ S EY1 N Z +SAIPAN S EY1 P AH0 N +SAIPAN'S S EY1 P AH0 N Z +SAIS S EY1 Z +SAISON S EY1 S AA0 N +SAITAMA S AA2 IH0 T AA1 M AH0 +SAITO S EY1 T OW2 +SAITTA S EY1 T AH0 +SAIZ S EY1 Z +SAJAK S AE1 JH AE0 K +SAJDAK S AY1 D AH0 K +SAK S AE1 K +SAKAGUCHI S AA0 K AA0 G UW1 CH IY0 +SAKAI S AA0 K AA1 IY0 +SAKAL S EY1 K AH0 L +SAKAMOTO S AA0 K AA0 M OW1 T OW0 +SAKAROV S AA0 K AA1 R AO2 V +SAKATA S AA0 K AA1 T AH0 +SAKAU S AA0 K AA1 UW0 +SAKE S EY1 K +SAKE'S S EY1 K S +SAKER S EY1 K ER0 +SAKES S EY1 K S +SAKHALIN S AE1 K AH0 L IH0 N +SAKHALINSK S AE2 K AH0 L IH1 N S K +SAKHAROV S AA0 K AA1 R AO2 V +SAKI S AA1 K IY0 +SAKIGAKE S AA2 K IY0 G AA1 K EH2 +SAKINA S AH0 K IY1 N AH0 +SAKO S AA1 K OW0 +SAKOWITZ S AE1 K AH0 W IH0 T S +SAKOWSKI S AH0 K AO1 F S K IY2 +SAKS S AE1 K S +SAKS'S S AE1 K S IH0 Z +SAKSA S AE1 K S AH0 +SAKSIDA S AA2 K S IY1 D AA2 +SAKUMA S AA2 K UW1 M AA2 +SAKURA S AA2 K UW1 R AA2 +SAKURAI S AA2 K UW1 R AY2 +SAL S AE1 L +SAL'S S AE1 L Z +SALA S AA1 L AH0 +SALAAM S AH0 L AA1 M +SALABLE S EY1 L AH0 B AH0 L +SALABLES S EY1 L AH0 B AH0 L Z +SALACIOUS S AH0 L EY1 SH AH0 S +SALAD S AE1 L AH0 D +SALADA S AH0 L AA1 D AH0 +SALADIN S AE1 L AH0 D IH0 N +SALADINO S AA0 L AA0 D IY1 N OW0 +SALADS S AE1 L AH0 D Z +SALAFIA S AH0 L EY1 F IY0 AH0 +SALAH S AE1 L AH0 +SALAK S AE1 L AH0 K +SALAM S AA0 L AA1 M +SALAMA S AA0 L AA1 M AH0 +SALAMANCA S AE2 L AH0 M AE1 NG K AH0 +SALAMANDER S AE2 L AH0 M AE1 N D ER0 +SALAMANDERS S AE2 L AH0 M AE1 N D ER0 Z +SALAMEH S AA1 L AA0 M EH0 +SALAMEH'S S AA1 L AA0 M EH0 Z +SALAMI S AH0 L AA1 M IY0 +SALAMIS S AH0 L AA1 M IY0 Z +SALAMON S AE1 L AH0 M AH0 N +SALAMONE S AE1 L AH0 M OW2 N +SALANT S AE1 L AH0 N T +SALARIED S AE1 L ER0 IY0 D +SALARIES S AE1 L ER0 IY0 Z +SALARY S AE1 L ER0 IY0 +SALARYMEN S AE1 L ER0 IY0 M AH0 N +SALAS S AA1 L AA0 Z +SALATA S AA0 L AA1 T AH0 +SALATINO S AA0 L AA0 T IY1 N OW0 +SALAWAH S AE1 L AH0 W AA0 +SALAY S AE1 L EY0 +SALAZ S AA1 L AA0 Z +SALAZAR S AE1 L AH0 Z AA0 R +SALBERG S AE1 L B ER0 G +SALCE S EY1 L S +SALCEDO S AA0 L CH EY1 D OW0 +SALCIDO S AA0 L CH IY1 D OW0 +SALDANA S AA0 L D AE1 N AH0 +SALDIVAR S AA0 L D IY0 V AA1 R +SALDOVAR S AA0 L D AH0 V AA1 R +SALE S EY1 L +SALE'S S EY1 L Z +SALEABLE S EY1 L AH0 B AH0 L +SALEEBY S AE1 L IY0 B IY0 +SALEEM S AE1 L IY0 M +SALEH S AA1 L EH0 HH +SALEK S AA1 L EH0 K +SALEM S EY1 L AH0 M +SALEM'S S EY1 L AH0 M Z +SALEMA S AH0 L IY1 M AH0 +SALEMI S AA0 L EH1 M IY0 +SALEMME S AE1 L IH0 M +SALERNO S AH0 L EH1 R N OW0 +SALES S EY1 L Z +SALES' S EY1 L Z +SALESMAN S EY1 L Z M AH0 N +SALESMAN'S S EY1 L Z M AH0 N Z +SALESMANSHIP S EY1 L Z M AH0 N SH IH2 P +SALESMEN S EY1 L Z M IH0 N +SALESMEN'S S EY1 L Z M IH0 N Z +SALESPEOPLE S EY1 L Z P IY2 P AH0 L +SALESPERSON S EY1 L Z P ER2 S AH0 N +SALESWOMAN S EY1 L Z W UH2 M AH0 N +SALESWOMEN S EY1 L Z W IH2 M AH0 N +SALGADO S AA0 L G AA1 D OW0 +SALGUERO S AA0 L G EH1 R OW0 +SALHANY S AE2 L HH EY1 N IY0 +SALIBA S AA0 L IY1 B AH0 +SALICK S AE1 L IH0 K +SALIENT S EY1 L IY0 AH0 N T +SALIENT(1) S EY1 L Y AH0 N T +SALIF S AH0 L IY1 F +SALIGMAN S AE1 L IH0 G M AH0 N +SALIM S AE1 L IH0 M 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R IY0 +SALSER S AE1 L S ER0 +SALSGIVER S AE1 L S G IH0 V ER0 +SALSMAN S AO1 L S M AH0 N +SALT S AO1 L T +SALTARELLI S AO0 L T AA0 R EH1 L IY0 +SALTBOX S AO1 L T B AA2 K S +SALTED S AO1 L T IH0 D +SALTER S AO1 L T ER0 +SALTER'S S AO1 L T ER0 Z +SALTERS S AO1 L T ER0 Z +SALTIER S AO1 L T IY0 ER0 +SALTING S AO1 L T IH0 NG +SALTLIKE S AO1 L T L AY2 K +SALTMARSH S AO1 L T M AA2 R SH +SALTON S AO1 L T AH0 N +SALTS S AO1 L T S +SALTSMAN S AO1 L T S M AH0 N +SALTWATER S AO2 L T W AA1 T ER0 +SALTY S AO1 L T IY0 +SALTZ S AE1 L T S +SALTZBURG S AO1 L T S B ER0 G +SALTZMAN S AO1 L T S M AH0 N +SALUS S AE1 L IH0 S +SALUTARY S AE1 L Y AH0 T EH2 R IY0 +SALUTATORIAN S AH0 L UW2 T AH0 T AO1 R IY0 AH0 N +SALUTE S AH0 L UW1 T +SALUTED S AH0 L UW1 T IH0 D +SALUTES S AH0 L UW1 T S +SALUTING S AH0 L UW1 T IH0 NG +SALVA S AA1 L V AH0 +SALVADOR S AE1 L V AH0 D AO2 R +SALVADOR'S S AE1 L V AH0 D AO2 R Z +SALVADORAN S AE1 L V AH0 D AO2 R AH0 N +SALVADORANS S AE0 L V AH0 D AO1 R AH0 N Z +SALVADORE S AA0 L V AA0 D AO1 R EY0 +SALVAGE S AE1 L V AH0 JH +SALVAGE(1) S AE1 L V IH0 JH +SALVAGEABLE S AE1 L V IH0 JH AH0 B AH0 L +SALVAGED S AE1 L V IH0 JH D +SALVAGER S AE1 L V IH0 JH ER0 +SALVAGERS S AE1 L V IH0 JH ER0 Z +SALVAGGIO S AA0 L V AA1 JH IY0 OW0 +SALVAGING S AE1 L V IH0 JH IH0 NG +SALVAS S AA1 L V AA0 Z +SALVATI S AA0 L V AA1 T IY0 +SALVATIERRA S AA0 L V AA0 T IH1 R AH0 +SALVATION S AE0 L V EY1 SH AH0 N +SALVATO S AA0 L V AA1 T OW0 +SALVATORE S AE0 L V AH0 T AO1 R IY0 +SALVATORE(1) S AE1 L V AH0 D AO2 R +SALVATORI S AA0 L V AA0 T AO1 R IY0 +SALVE S AA1 V +SALVES S AA1 V Z +SALVESEN S AA0 L V IY1 Z AH0 N +SALVESON S AA0 L V EY1 S AH0 N +SALVETTI S AA0 L V EH1 T IY0 +SALVI S AA1 L V IY0 +SALVI'S S AA1 L V IY0 Z +SALVIA S AE1 L V IY0 AH0 +SALVIGSEN S AE1 L V IH0 G S AH0 N +SALVIGSTEN S AE1 L V IH0 G S T AH0 N +SALVINA S AA0 L V IY1 N AH0 +SALVINO S AE0 L V IY1 N OW0 +SALVO S AE1 L V OW0 +SALVOS S AE1 L V OW0 Z +SALVUCCI S AA0 L V UW1 CH IY0 +SALWAY S AE1 L W EY0 +SALWEN S AE1 L W AH0 N +SALYARD S AO1 L Y ER0 D +SALYARDS S AE1 L Y AA0 R D Z +SALYER S AA1 L IY0 ER0 +SALYERS S AA1 L IY0 ER0 Z +SALZ S AO1 L Z +SALZANO S AA0 L Z AA1 N OW0 +SALZBERG S AO1 L Z B ER0 G +SALZBERG(1) S AO1 L T S B ER0 G +SALZBURG S AO1 L Z B ER0 G +SALZBURG(1) S AO1 L T S B ER0 G +SALZER S EY1 L Z ER0 +SALZGITTER S AO1 L T S G IH2 T ER0 +SALZHAUER S AO1 L T S HH AW2 R +SALZHAUER(1) S AO1 L T S AW2 R +SALZMAN S AO1 L Z M AH0 N +SALZMANN S AO1 L Z M AH0 N +SALZWEDEL S AE1 L Z W IH0 D AH0 L +SAM S AE1 M +SAM'S S AE1 M Z +SAM-JOO S AA1 M JH UW2 +SAMA S AA1 M AH0 +SAMAHA S AE1 M AH0 HH AH0 +SAMANIEGO S AA0 M AA0 N IY1 G OW0 +SAMANO S AA0 M AA1 N OW0 +SAMANTHA S AH0 M AE1 N TH AH0 +SAMAR S AE1 M AA0 R +SAMARA S AE1 M ER0 AH0 +SAMARANCH S AE1 M ER0 AE0 N CH +SAMARAS S AE1 M ER0 AH0 Z +SAMARIA S EY2 M ER0 IY1 AH0 +SAMARIN S AA0 M AA1 R IY0 N +SAMARITAN S AH0 M EH1 R IH0 T AH0 N +SAMARITANS S AH0 M EH1 R IH0 T AH0 N Z +SAMARKAND S AE1 M AA0 R K AE2 N D +SAMATAR S AE1 M AH0 T AA2 R +SAMBA S AA1 M B AH0 +SAMBERG S AE1 M B ER0 G +SAMBO S AE1 M B OW0 +SAMBORSKI S AH0 M B AO1 R S K IY0 +SAMBRANO S AA0 M B R AA1 N OW0 +SAMBRE S AE1 M B R AH0 +SAMBUCA S AE2 M B Y UW1 K AH0 +SAMCOR S AE1 M K AO2 R +SAME S EY1 M +SAME'S S EY1 M Z +SAME-SEX S EY2 M S EH1 K S +SAMEDAN S AE1 M AH0 D AH0 N +SAMEER S AA2 M IH1 R +SAMEK S AE1 M IH0 K +SAMELLA S AH0 M EH1 L AH0 +SAMELLE S AH0 M EH1 L +SAMELSON S AE1 M IH0 L S AH0 N +SAMENESS S EY1 M N AH0 S +SAMEROL S AE1 M ER0 AO2 L +SAMES S EY1 M Z +SAMET S AE1 M IH0 T +SAMFORD S AE1 M F ER0 D +SAMI S AE1 M IY0 +SAMI'S S AE1 M IY0 Z +SAMINA S AH0 M IH1 N AH0 +SAMIR S AH0 M IH1 R +SAMIR(1) S AA0 M IH1 R +SAMMARCO S AA0 M AA1 R K OW0 +SAMMARTINO S AA0 M AA0 R T IY1 N OW0 +SAMMET S AE1 M IH0 T +SAMMIE S AE1 M IY0 +SAMMIS S AE1 M IH0 S +SAMMON S AE1 M AH0 N +SAMMONS S AE1 M AH0 N Z +SAMMS S AE1 M Z +SAMMUT S AE1 M AH0 T +SAMMY S AE1 M IY0 +SAMOA S AH0 M OW1 AH0 +SAMOAN S AH0 M OW1 AH0 N +SAMOJLIK S AH0 M OY1 L IH0 K +SAMONS S AA1 M OW0 N Z +SAMORA S AA0 M AO1 R AH0 +SAMOS S EY1 M AA0 S +SAMOTH S AE1 M AH0 TH +SAMP S AE1 M P +SAMPAN S AE1 M P AE0 N +SAMPANS S AE1 M P AE0 N Z +SAMPER S AE1 M P ER0 +SAMPER'S S AE1 M P ER0 Z +SAMPERE S AE0 M P IY1 R +SAMPEY S AE1 M P IY0 +SAMPLE S AE1 M P AH0 L +SAMPLE'S S AE1 M P AH0 L Z +SAMPLED S AE1 M P AH0 L D +SAMPLER S AE1 M P L ER0 +SAMPLERS S AE1 M P L ER0 Z +SAMPLES S AE1 M P AH0 L Z +SAMPLEY S AE1 M P L IY0 +SAMPLING S AE1 M P L IH0 NG +SAMPLINGS S AE1 M P L IH0 NG Z +SAMPRAS S AE1 M P R AH0 S +SAMPRAS' S AE1 M P R AH0 S +SAMPRAS'S S AE1 M P R AH0 S IH0 Z +SAMPRE S AE1 M P R IY0 +SAMPRE(1) S AE1 M P ER0 +SAMPSEL S AE1 M P S AH0 L +SAMPSELL S AE1 M P S AH0 L +SAMPSON S AE1 M P S AH0 N +SAMRA S AE1 M R AH0 +SAMS S AE1 M Z +SAMSARA S AH0 M S AA1 R AH0 +SAMSEL S AE1 M S AH0 L +SAMSOM S AE1 M S AH0 M +SAMSON S AE1 M S AH0 N +SAMSONITE S AE1 M S AH0 N AY2 T +SAMSUNG S AE1 M S AH2 NG +SAMSUNG'S S AE1 M S AH2 NG Z +SAMUDIO S AA0 M UW1 D IY0 OW0 +SAMUEL S AE1 M Y UW0 L +SAMUEL'S S AE1 M Y UW0 L Z +SAMUELA S AE2 M Y UW0 EH1 L AH0 +SAMUELLE S AE1 M Y UW0 EH2 L +SAMUELS S AE1 M Y UW0 AH0 L Z +SAMUELSEN S AE1 M UH0 L S AH0 N +SAMUELSON S AE1 M Y UW0 AH0 L S AH0 N +SAMURAI S AE1 M UH0 R AY2 +SAMURAI(1) S AE1 M ER0 AY2 +SAMURAI'S S AE1 M ER0 AY2 Z +SAMURAIS S AE1 M ER0 AY2 Z +SAMURAIS(1) S AE1 M ER0 IH0 Z +SAN S AE1 N +SAN-ANDREAS S AE2 N AA0 N D R EY1 AH0 S +SAN-DIEGO S AE1 N D IY0 EY1 G OW0 +SAN-FRAN S AE1 N F R AE1 N +SAN-FRANCISCO S AE1 N F R AE0 N S IH1 S K OW0 +SAN-JOSE S AE2 N HH OW0 Z EY1 +SAN-JUAN S AE1 N W AA1 N +SAN-SALVADOR S AE1 N S AE1 L V AH0 D AO2 R +SANA S AA1 N AH0 +SANAA S AH0 N AA1 +SANABRIA S AH0 N AE1 B R IY0 AH0 +SANADA S AA0 N AA1 D AH0 +SANBORN S AE1 N B AO2 R N +SANCHES S AA1 N CH EH0 S +SANCHEZ S AE1 N CH EH0 Z +SANCHEZ'S S AE1 N CH EH0 Z IH0 Z +SANCHO S AA1 N K OW0 +SANCIA S AA1 N CH AH0 +SANCTIFICATION S AE2 NG K T AH0 F AH0 K EY1 SH AH0 N +SANCTIFY S AE1 NG K T AH0 F AY0 +SANCTIMONIOUS S AE2 NG K T AH0 M OW1 N IY0 AH0 S +SANCTIMONY S AE1 NG K T IH0 M OW2 N IY0 +SANCTION S AE1 NG K SH AH0 N +SANCTION'S S AE1 NG K SH AH0 N Z +SANCTIONED S AE1 NG K SH AH0 N D +SANCTIONING S AE1 NG K SH AH0 N IH0 NG +SANCTIONS S AE1 NG K SH AH0 N Z +SANCTIONS' S AE1 NG K SH AH0 N Z +SANCTITY S AE1 NG K T IH0 T IY0 +SANCTUARIES S AE1 NG K CH UW0 EH2 R IY0 Z +SANCTUARY S AE1 NG K CH UW0 EH2 R IY0 +SANCTUM S AE1 NG K T AH0 M +SAND S AE1 N D +SAND'S S AE1 N D Z +SANDA S AE1 N D AH0 +SANDAGE S AE1 N D IH0 JH +SANDAHL S AE1 N D AA2 L +SANDAL S AE1 N D AH0 L +SANDALL S AE1 N D AA0 L +SANDALO S AE2 N D AE1 L OW0 +SANDALS S AE1 N D AH0 L Z +SANDAU S AE1 N D AW0 +SANDBAG S AE1 N D B AE2 G +SANDBAGGED S AE1 N D B AE2 G D +SANDBAGGER S AE1 N D B AE2 G ER0 +SANDBAGGERS S AE1 N D B AE2 G ER0 Z +SANDBAGGING S AE1 N D B AE2 G IH0 NG +SANDBAGS S AE1 N D B AE2 G Z +SANDBAR S AE1 N D B AA2 R +SANDBERG S AE1 N D B ER0 G +SANDBLAST S AE1 N D B L AE2 S T +SANDBLASTED S AE1 N D B L AE2 S T IH0 D +SANDBOX S AE1 N D B AA2 K S +SANDBURG S AE1 N D B ER0 G +SANDE S AE1 N D +SANDED S AE1 N D IH0 D +SANDEEN S AE1 N D IY0 N +SANDEFER S AE1 N D IY0 F ER0 +SANDEFUR S AE1 N D EH0 F ER0 +SANDEL S AE1 N D EH0 L +SANDELL S AE1 N D EH0 L +SANDEN S AE1 N D AH0 N +SANDER S AE1 N D ER0 +SANDERFER S AE1 N D ER0 F ER0 +SANDERFORD S AE1 N D ER0 F AO0 R D +SANDERLIN S AE1 N D ER0 L IH0 N +SANDERS S AE1 N D ER0 Z +SANDERS'S S AE1 N D ER0 Z IH0 Z +SANDERSON S AE1 N D ER0 S AH0 N +SANDFORD S AE1 N D F ER0 D +SANDGREN S AE1 N D G R EH0 N +SANDHILL S AE1 N D HH IH2 L +SANDHOG S AE1 N D HH AO2 G +SANDHOGS S AE1 N D HH AO2 G Z +SANDHU S AE1 N D HH UW0 +SANDI S AE1 N D IY0 +SANDIA S AE1 N D IY0 AH0 +SANDIDGE S AE1 N D IH0 JH +SANDIE S AE1 N D IY0 +SANDIFER S AE1 N D AY0 F ER0 +SANDIFORD S AE1 N D IH0 F ER0 D +SANDIN S AE1 N D IH2 N +SANDING S AE1 N D IH0 NG +SANDINISTA S AE2 N D IH0 N IH1 S T AH0 +SANDINISTA(1) S AE2 N D IH0 N IY1 S T AH0 +SANDINISTAS S AE2 N D IH0 N IY1 S T AH0 Z +SANDINISTAS' S AE2 N D IH0 N IY1 S T AH0 Z +SANDINO S AE0 N D IY1 N OW0 +SANDINO'S S AE0 N D IY1 N OW0 Z +SANDLER S AE1 N D L ER0 +SANDLIN S AE1 N D L IH0 N +SANDLING S AE1 D L IH0 NG +SANDMAN S AE1 N D M AE2 N +SANDMANN S AE1 N D M AH0 N +SANDMEYER S AE1 N D M AY0 ER0 +SANDNER S AE1 N D N ER0 +SANDNESS S AE1 N D N AH0 S +SANDO S AE1 N D OW0 +SANDOM S AE1 N D AH0 M +SANDON S AE1 N D AO2 N +SANDOR S AE1 N D ER0 +SANDOS S AE1 N D OW0 Z +SANDOS(1) S AE1 N D OW0 S +SANDOSE S AE1 N D OW0 Z +SANDOVAL S AE1 N D OW2 V AH0 L +SANDOW S AE1 N D OW0 +SANDOZ S AE1 N D OW0 Z +SANDOZ'S S AE1 N D AH0 Z IH0 Z +SANDPAPER S AE1 N D P EY2 P ER0 +SANDPOINT S AE1 N D P OY2 N T +SANDQUIST S AE1 N D K W IH2 S T +SANDRA S AE1 N D R AH0 +SANDRIDGE S AE1 N D R IH2 JH +SANDRO S AE1 N D R OW0 +SANDROCK S AE1 N D R AA2 K +SANDS S AE1 N D Z +SANDSTONE S AE1 N D S T OW2 N +SANDSTONE(1) S AE1 N S T OW2 N +SANDSTORM S AE1 N D S T AO2 R M +SANDSTORMS S AE1 N D S T AO2 R M Z +SANDSTROM S AE1 N D S T R AH0 M +SANDT S AE1 N T +SANDTOWN S AE1 N D T AW2 N +SANDTOWN(1) S AE1 N T AW2 N +SANDUSKY S AE0 N D AH1 S K IY0 +SANDVIG S AE1 N D V IH2 G +SANDVIK S AE1 N D V IH0 K +SANDWICH S AE1 N D W IH0 CH +SANDWICH(1) S AE1 N W IH0 CH +SANDWICH(2) S AE1 M W IH0 CH +SANDWICHED S AE1 N D W IH2 CH T +SANDWICHED(1) S AE1 N W IH2 CH T +SANDWICHED(2) S AE1 M W IH2 CH T +SANDWICHES S AE1 N D W IH0 CH IH0 Z +SANDWICHES(1) S AE1 N W IH0 CH IH0 Z +SANDWICHES(2) S AE1 M W IH0 CH IH0 Z +SANDWICK S AE1 N D W IH2 K +SANDY S AE1 N D IY0 +SANDY'S S AE1 N D IY0 Z +SANE S EY1 N +SANER S EY1 N ER0 +SANFILIPPO S AE2 N F IH0 L IH1 P OW0 +SANFORD S AE1 N F ER0 D +SANFORD'S S AE1 N F ER0 D Z +SANG S AE1 NG +SANG-GON S AA1 NG G AO1 N +SANGER S AE1 NG ER0 +SANGFROID S AA2 N F R AW1 +SANGIOVESE S AE2 N JH IY1 OW0 V IY2 S +SANGSTER S AE1 NG S T ER0 +SANGUINE S AE1 NG G W IH0 N +SANGUINETTI S AA0 NG IY0 N EH1 T IY0 +SANGYO S AE1 N JH Y OW0 +SANHEDRIN S AE2 N HH IY1 D R IH0 N +SANI S AE1 N IY0 +SANI(1) S AE1 N IH0 +SANITARY S AE1 N IH0 T EH2 R IY0 +SANITATION S AE2 N AH0 T EY1 SH AH0 N +SANITATION(1) S AE2 N IH0 T EY1 SH AH0 N +SANITIZE S AE1 N IH0 T AY2 Z +SANITIZED S AE1 N IH0 T AY2 Z D +SANITIZING S AE1 N AH0 T AY2 Z IH0 NG +SANITY S AE1 N AH0 T IY0 +SANJAY S AE1 N JH EY0 +SANJIV S AA2 N JH IY1 V +SANJUAN S AA0 N Y UW0 AA1 N +SANK S AE1 NG K +SANKA S AE1 NG K AH0 +SANKARA S AA0 N K AA1 R AH0 +SANKARA'S S AA0 N K AA1 R AH0 Z +SANKEI S AE1 NG K IY0 +SANKER S AE1 NG K ER0 +SANKEY S AE1 NG K IY0 +SANKO S AE1 NG K OW0 +SANKS S AE1 NG K S +SANKYO S AE1 NG K Y OW0 +SANMARK S AE1 N M AA2 R K +SANMARTIN S AE1 N M AA0 R T IH0 N +SANMIGUEL S AA0 N M IY0 G EH1 L +SANNA S AE1 N AH0 +SANNER S AE1 N ER0 +SANNES S AE1 N Z +SANO S AA1 N OW0 +SANOFI S AH0 N OW1 F IY0 +SANRIO S AE1 N R IY0 OW0 +SANS S AE1 N Z +SANS-CULOTTES S AA1 N K UW0 L AO1 T +SANSBURY S AE1 N S B EH0 R IY0 +SANSEVERINO S AA0 N S EH0 V ER0 IY1 N OW0 +SANSING S AE1 N S IH0 NG +SANSKRIT S AE1 N S K R IH0 T +SANSO S AE1 N S OW0 +SANSOM S AE1 N S AH0 M +SANSON S AE1 N S AH0 N +SANSONE S AE1 N S AH0 N +SANSOUCIE S AE1 N S OW0 K IY0 +SANSUI S AE0 N S UW1 IY0 +SANSUI'S S AE0 N S UW1 IY0 Z +SANT S AE1 N T +SANTA S AE1 N T AH0 +SANTA(1) S AE1 N AH0 +SANTA'S S AE1 N T AH0 Z +SANTA-CROCE S AE1 N T AH0 K R OW1 CH IY0 +SANTA-CRUZ S AE1 N T AH0 K R UW1 Z +SANTA-FE S AE1 N T AH0 F EY1 +SANTA-FE'S S AE1 N T AH0 F EY1 Z +SANTA-MARIA S AE1 N T AH0 M ER0 IY1 AH0 +SANTAGATA S AA0 N T AA0 G AA1 T AH0 +SANTALA S AE0 N T AA1 L AH0 +SANTANA S AE0 N T AE1 N AH0 +SANTANDER S AE2 N T AE1 N D ER0 +SANTANGELO S AA0 N T AA0 NG G EH1 L OW0 +SANTANIELLO S AA0 N T AA0 N IY0 EH1 L OW0 +SANTARELLI S AA0 N T AA0 R EH1 L IY0 +SANTARSIERO S AA0 N T AA0 R S IH1 R OW0 +SANTAS S AE1 N T AH0 S +SANTAYANA S AE0 N T AY2 AA1 N AH0 +SANTE S AE1 N T AH0 +SANTELLA S AA0 N T EH1 L AH0 +SANTELLI S AA0 N T EH1 L IY0 +SANTER S AE1 N T ER0 +SANTERIA S AE2 N T EH1 R IY0 AH0 +SANTERRE S AE0 N T EH1 R +SANTI S AE1 N T IY0 +SANTIA S AA1 N T Y AH0 +SANTIAGO S AE2 N T IY0 AA1 G OW0 +SANTIDAD S AA1 N T IH0 D AE0 D +SANTIESTEBAN S AE1 N T IY0 S T IH0 B AH0 N +SANTILLAN S AE2 N T IH1 L AH0 N +SANTILLANES S AE1 N T IH0 L EY2 N Z +SANTILLI S AA0 N T IY1 L IY0 +SANTILLO S AE2 N T IH1 L OW0 +SANTIN S AE1 N T IH0 N +SANTINI S AE0 N T IY1 N IY0 +SANTINO S AA0 N T IY1 N OW0 +SANTISTEVAN S AA2 N T IY0 S T EY0 V AA1 N +SANTO S AE1 N T OW0 +SANTON S AE1 N T AH0 N +SANTONE S AA0 N T OW1 N IY0 +SANTONI S AA0 N T OW1 N IY0 +SANTOPIETRO S AA0 N T OW0 P IY1 T R OW0 +SANTOR S AE1 N T ER0 +SANTORA S AA0 N T AO1 R AH0 +SANTORE S AA0 N T AO1 R IY0 +SANTORELLI S AA0 N T AO0 R EH1 L IY0 +SANTORO S AE0 N T AO1 R OW0 +SANTORUM S AE0 N T AO1 R AH0 M +SANTORUM'S S AE0 N T AO1 R AH0 M Z +SANTOS S AE1 N T OW0 S +SANTOSH S AA1 N T AA2 SH +SANTOSUOSSO S AA0 N T OW0 S W OW1 S OW0 +SANTOW S AE1 N T OW0 +SANTOYO S AA0 N T OW1 Y OW0 +SANTRY S AE1 N T R IY0 +SANTUCCI S AA0 N T UW1 CH IY0 +SANTULLI S AA0 N T UW1 L IY0 +SANTY S AE1 N T IY0 +SANVILLE S AA1 N V IH0 L +SANWA S AE1 N W AH0 +SANWA'S S AE1 N W AH0 Z +SANYO S AA1 N Y OW0 +SANZ S AE1 N Z +SANZO S AE1 N Z OW0 +SANZONE S AA0 N Z OW1 N IY0 +SAO S AW1 +SAONE S EY1 OW2 N +SAOUMA S AW2 Y UW1 M AH0 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CH IY1 N OW0 +SARAFIAN S ER0 EY1 F IY0 AH0 N +SARAFIN S AE1 R AH0 F IH0 N +SARAFINA S AE2 R AH0 F IY1 N AH0 +SARAGE S AE1 R AH0 JH +SARAGE'S S AE1 R AH0 JH IH0 Z +SARAH S EH1 R AH0 +SARAH'S S EH1 R AH0 Z +SARAJEVAN S AA2 R AH0 Y EY1 V AH0 N +SARAJEVAN'S S AA2 R AH0 Y EY1 V AH0 N Z +SARAJEVANS S AA2 R AH0 Y EY1 V AH0 N Z +SARAJEVO S AA2 R AH0 Y EY1 V OW0 +SARAJEVO'S S AA2 R AH0 Y EY1 V OW0 Z +SARAN S ER0 AE1 N +SARANDON S EH1 R AH0 N D IH0 N +SARANDON(1) S EH2 R AE1 N D IH0 N +SARANT S AE1 R AH0 N T +SARASIN S EH1 R IH0 S IH0 N +SARASOTA S EH2 R AH0 S OW1 T AH0 +SARATOGA S EH2 R AH0 T OW1 G AH0 +SARATOV S EH1 R AH0 T AO2 V +SARATOV(1) S EH1 R AH0 T AO2 F +SARAVIA S ER0 EY1 V IY0 AH0 +SARAWAK S EH1 R AH0 W AA0 K +SARAZEN S EH1 R AH0 Z AH0 N +SARAZIN S AA0 R AA0 Z IY1 N +SARBANE S AA1 R B EY2 N +SARBANES S AA1 R B EY2 N Z +SARBER S AA1 R B ER0 +SARCASM S AA1 R K AE2 Z AH0 M +SARCASTIC S AA0 R K AE1 S T IH0 K +SARCASTICALLY S AA0 R K AE1 S T IH0 K L IY0 +SARCHET S AA0 R SH EH1 T +SARCOMA S AA0 R K OW1 M ER0 +SARCOPHAGUS S AA0 R K AA1 F AH0 G AH0 S +SARDAS S AA1 R D AH0 S +SARDELLA S AA2 R D EH1 L AH0 +SARDINA S AA0 R D IY1 N AH0 +SARDINAS S AA1 R D IH0 N AH0 Z +SARDINE S AA0 R D IY1 N +SARDINES S AA0 R D IY1 N Z +SARDINHA S AA2 R D IH1 N HH AH0 +SARDINIA S AA0 R D IY1 N IY0 AH0 +SARDO S AA1 R D OW0 +SARDONIC S AA0 R D AA1 N IH0 K +SARDONICALLY S AA0 R D AA1 N IH0 K AH0 L IY0 +SARDONICALLY(1) S AA0 R D AA1 N IH0 K L IY0 +SARDOODLEDOM S AA2 R D UW1 D AH0 L D AH0 M +SARE S EH1 R +SAREJEVO S AA2 R AH0 Y EY1 V OW0 +SAREJEVO'S S AA2 R AH0 Y EY1 V OW0 Z +SARENE S ER0 IY1 N +SARETTE S ER0 EH1 T +SARFF S AA1 R F +SARGASSO S AA0 R G AE1 S OW0 +SARGE S AA1 R JH +SARGEANT S AA1 R JH AH0 N T +SARGEN S AA1 R G AH0 N +SARGENT S AA1 R JH AH0 N T +SARGIS S AA1 R G IH0 S +SARI S AA1 R IY0 +SARI'S S AA1 R IY0 Z +SARICH S AE1 R IH0 K +SARIN S AA0 R IH0 N +SARINE S AA0 R IY1 N IY0 +SARIS S AA1 R IY0 Z +SARISI S AH0 R IY1 S IY0 +SARK S AA1 R K +SARKA S AA1 R K AH0 +SARKAR S AA1 R K AA2 R +SARKIS S AA1 R K IH0 S +SARKISIAN S AA0 R K IH1 ZH IH0 N +SARKISSIAN S AA0 R K IH1 S ZH IH0 N +SARLES S AA1 R L Z +SARLI S AA1 R L IY0 +SARLO S AA1 R L OW0 +SARLOS S AA1 R L OW0 S +SARMATIAN S AA0 R M EY1 SH AH0 N +SARMENTO S AA0 R M EH1 N T OW0 +SARMIENTO S AA0 R M IY1 N T OW0 +SARNA S AA1 R N AH0 +SARNEY S AA1 R N IY0 +SARNEY'S S AA1 R N IY0 Z +SARNI S AA1 R N IY0 +SARNO S AA1 R N OW0 +SARNOFF S AA1 R N AO0 F +SARNOWSKI S ER0 N AO1 F S K IY0 +SAROFIM S EH2 R AH0 F IY1 M +SAROKIN S EH1 R AH0 K IH0 N +SARONG S ER0 AO1 NG +SARONGS S ER0 AO1 NG Z +SAROS S AA1 R OW0 S +SAROWIWA S AE2 R OW0 W IY1 W AH0 +SARRA S AA1 R AA2 +SARRAJ S AA2 R AY1 +SARRATT S ER2 AE1 T +SARRAZIN S AA1 R AH0 Z IH2 N +SARRETT S AE1 R IH0 T +SARRIS S AE1 R IH0 S +SARRO S AA1 R OW0 +SARS S AA1 R Z +SARSFIELD S AA1 R S F IY0 L D +SARTAIN S AA0 R T EY1 N +SARTI S AA1 R T IY0 +SARTIN S AA1 R T IH0 N +SARTOR S AA1 R T ER0 +SARTORI S AA0 R T AO1 R IY0 +SARTORIAL S AA0 R T AO1 R IY0 AH0 L +SARTORIUS S AA0 R T AO1 R IY0 IH0 S +SARTRAIN S AA1 R T R EY2 N +SARTRE S AA1 R T R AH0 +SARTWELL S AA1 R T W EH2 L +SARUM S AE1 R AH0 M +SARVER S AA1 R V ER0 +SARVIS S AA1 R V IH0 S +SAS S AE1 S +SASAKI S AA0 S AA1 K IY0 +SASAYAMA S AE2 S AH0 Y AA1 M AH0 +SASEK S AE1 S IH0 K +SASH S AE1 SH +SASHA S AE1 SH AH0 +SASHES S AE1 SH IH0 Z +SASKATCHEWAN S AE0 S K AE1 CH AH0 W AO2 N +SASKATOON S AE1 S K AH0 T UW2 N +SASLOW S AE1 S L OW0 +SASNETT S AE1 S N IH0 T +SASS S AE1 S +SASSAFRAS S AE1 S AH0 F R AE2 S +SASSAFRAS'S S AE1 S AH0 F R AE2 S AH0 Z +SASSAFRAS'S(1) S AE1 S AH0 F R AE2 S IH0 Z +SASSAMAN S AE1 S AH0 M AH0 N +SASSANO S AA0 S AA1 N OW0 +SASSE S AE1 S +SASSEEN S AE1 S IY0 N +SASSER S AE1 S ER0 +SASSER'S S AE1 S ER0 Z +SASSI S AE1 S IY0 +SASSMAN S AE1 S M AH0 N +SASSNET S AE1 S N EH2 T +SASSNET'S S AE1 S N EH2 T S +SASSNETS S AE1 S N EH2 T S +SASSO S AE1 S OW0 +SASSON S AE1 S AH0 N +SASSONE S AA0 S OW1 N IY0 +SASSOON S AH0 S UW1 N +SASSOU S AE1 S UW0 +SASSOUNGUESSO S AE2 S UW0 NG G EH1 S OW0 +SASSULO S AH0 S UW1 L OW0 +SASSY S AE1 S IY0 +SASSY'S S AE1 S IY0 Z +SAT S AE1 T +SATAGAJ S AE1 T AH0 G AY2 +SATAN S EY1 T AH0 N +SATAN'S S EY1 T AH0 N Z +SATANIC S AH0 T AE1 N IH0 K +SATANISM S EY1 T AH0 N IH2 Z AH0 M +SATANIST S EY1 T AH0 N IH0 S T +SATANJEEV S AA2 T AA0 N JH IY1 V +SATANS S EY1 T AH0 N Z +SATCHELL S AE1 CH AH0 L +SATCHER S AE1 CH ER0 +SATE S EY1 T +SATED S EY1 T IH0 D +SATELLITE S AE1 T AH0 L AY2 T +SATELLITE'S S AE1 T AH0 L AY2 T S +SATELLITES S AE1 T AH0 L AY2 T S +SATER S AE1 T ER0 +SATES S EY1 T S +SATHER S AE1 DH ER0 +SATHRE S AE1 TH ER0 +SATHYAVAGISWARAN S AE0 TH Y AH0 V AA2 G IH0 S W AA2 R AH0 N +SATIATED S EY1 SH IY2 EY2 T IH0 D +SATIETY S AA0 T AY1 AH0 T IY2 +SATIN S AE1 T AH0 N +SATINS S AE1 T AH0 N Z +SATIRE S AE1 T AY2 ER0 +SATIRES S AE1 T AY2 ER0 Z +SATIRIC S AH0 T IH1 R IH0 K +SATIRICAL S AH0 T IH1 R AH0 K AH0 L +SATIRICAL(1) S AH0 T IH1 R IH0 K AH0 L +SATIRIST S AE1 T ER0 AH0 S T +SATIRISTS S AE1 T ER0 AH0 S T S +SATIRIZE S AE1 T ER0 AY2 Z +SATIRIZES S AE1 T ER0 AY2 Z IH0 Z +SATIRIZING S AE1 T ER0 AY2 Z IH0 NG +SATISFACTION S AE2 T AH0 S F AE1 K SH AH0 N +SATISFACTION(1) S AE2 T IH0 S F AE1 K SH AH0 N +SATISFACTIONS S AE2 T AH0 S F AE1 K SH AH0 N Z +SATISFACTORILY S AE2 T IH0 S F AE1 K T R AH0 L IY0 +SATISFACTORY S AE2 T AH0 S F AE1 K T R IY0 +SATISFACTORY(1) S AE2 T IH0 S F AE1 K T ER0 IY0 +SATISFIED S AE1 T AH0 S F AY2 D +SATISFIED(1) S AE1 T IH0 S F AY2 D +SATISFIES S AE1 T IH0 S F AY2 Z +SATISFY S AE1 T AH0 S F AY2 +SATISFY(1) S AE1 T IH0 S F AY2 +SATISFYING S AE1 T IH0 S F AY2 IH0 NG +SATLOFF S AE1 T L AO2 F +SATO S AA1 T OW0 +SATOH S AA1 T OW0 +SATOSHI S AA0 T OW1 SH IY0 +SATRE S EY1 T ER0 +SATRIANI S AE2 T R IY0 AA1 N IY0 +SATTER S AE1 T ER0 +SATTERFIELD S AE1 T ER0 F IY1 L D +SATTERLEE S AE1 T ER0 L IY1 +SATTERLY S AE1 T ER0 L IY0 +SATTERWHITE S AE1 T ER0 W AY1 T +SATTLER S AE1 T L ER0 +SATURATE S AE1 CH ER0 EY2 T +SATURATED S AE1 CH ER0 EY2 T IH0 D +SATURATING S AE1 CH ER0 EY2 T IH0 NG +SATURATION S AE2 CH ER0 EY1 SH AH0 N +SATURDAY S AE1 T ER0 D IY0 +SATURDAY(1) S AE1 T IH2 D EY2 +SATURDAY'S S AE1 T ER0 D IY0 Z +SATURDAY'S(1) S AE1 T ER0 D EY0 Z +SATURDAYS S AE1 T ER0 D IY0 Z +SATURDAYS(1) S AE1 T ER0 D EY0 Z +SATURN S AE1 T ER0 N +SATURN'S S AE1 T ER0 N Z +SATURNS S AE1 T ER0 N Z +SATYA S AA1 T Y AH0 +SATYANDRA S AA2 T Y AA1 N D R AH0 +SATZ S AE1 T S +SAUBER S AO1 B ER0 +SAUCE S AO1 S +SAUCEDA S AW0 S EY1 D AH0 +SAUCEDO S AW0 S EY1 D OW0 +SAUCEPAN S AO1 S P AE2 N +SAUCER S AO1 S ER0 +SAUCERS S AO1 S ER0 Z +SAUCES S AO1 S AH0 Z +SAUCES(1) S AO1 S IH0 Z +SAUCIER S AO1 S IY0 ER0 +SAUCONY S AO1 K AH0 N IY0 +SAUCY S AO1 S IY0 +SAUD S AO1 D +SAUDER S AO1 D ER0 +SAUDI S AO1 D IY0 +SAUDI(1) S AW1 D IY0 +SAUDIA S AO1 D IY0 AH0 +SAUDIA(1) S AW1 D IY0 AH0 +SAUDIIZATION S AW2 IY0 IH0 Z EY1 SH AH0 N +SAUDIS S AO1 D IY0 Z +SAUDIS(1) S AW1 D IY0 Z +SAUDIS' S AO1 D IY0 Z +SAUDIS'(1) S AW1 D IY0 Z +SAUER S AW1 ER0 +SAUERKRAUT S AW1 ER0 K R AW2 T +SAUERS S AW1 ER0 Z +SAUERTEIG S AW1 ER0 T EY2 G +SAUERWEIN S AW1 ER0 W AY0 N +SAUEY S AO1 IY0 +SAUGERTIES S AO1 G ER0 T IY0 Z +SAUK S AO1 K +SAUL S AO1 L +SAULNIER S AW1 L N IY0 ER0 +SAULS S AO1 L Z +SAULSBERRY S AO1 L S B EH2 R IY0 +SAULSBURY S AO1 L S B EH0 R IY0 +SAULT S AO1 L T +SAULTER S AO1 L T ER0 +SAULTERS S AW1 L T ER0 Z +SAUM S AO1 M +SAUNA S AO1 N AH0 +SAUNAS S AO1 N AH0 Z +SAUNDERS S AO1 N D ER0 Z +SAUNDERS' S AO1 N D ER0 Z +SAUNDERS'S S AO1 N D ER0 Z IH0 Z +SAUNDERSON S AO1 N D ER0 S AH0 N +SAUNDRA S AO1 N D R AH0 +SAUNDRA'S S AO1 N D R AH0 Z +SAUNIER S AO1 N IY0 ER0 +SAUNTER S AO1 N T ER0 +SAUR S AO1 R +SAURER S AW1 ER0 R +SAURO S AO1 R OW0 +SAUS S AO1 Z +SAUSAGE S AO1 S AH0 JH +SAUSAGE(1) S AO1 S IH0 JH +SAUSAGES S AO1 S IH0 JH IH0 Z +SAUSALITO S AO2 S AH0 L IY1 T OW0 +SAUSE S AO1 Z +SAUSEDA S AW0 S EY1 D AH0 +SAUSER S AW1 S ER0 +SAUSSER S AO1 S ER0 +SAUTE S AO0 T EY1 +SAUTEED S AO0 T EY1 D +SAUTER S AO0 T EY1 ER0 +SAUTERNE S OW0 T ER1 N +SAUTERNES S OW0 T ER1 N Z +SAUTTER S AO1 T ER0 +SAUVAGE S AO1 V IH0 JH +SAUVAGEAU S OW1 V AH0 ZH OW0 +SAUVE S AO1 V +SAUVIGNON S AO2 V IH1 N Y AA0 N +SAVA S AA1 V AH0 +SAVAGE S AE1 V AH0 JH +SAVAGE(1) S AE1 V IH0 JH +SAVAGED S AE1 V IH0 JH D +SAVAGELY S AE1 V IH0 JH L IY0 +SAVAGERY S AE1 V IH0 JH EH2 R IY0 +SAVAGES S AE1 V AH0 JH AH0 Z +SAVAGES(1) S AE1 V IH0 JH IH0 Z +SAVAGING S AE1 V IH0 JH IH0 NG +SAVAIKO S AH0 V EY1 K OW0 +SAVALA S AA0 V AA1 L AH0 +SAVALAS S AH0 V AA1 L AH0 S +SAVANNA S AH0 V AE1 N AH0 +SAVANNAH S AH0 V AE1 N AH0 +SAVANNAS S AH0 V AE1 N AH0 Z +SAVANT S AH0 V AA1 N T +SAVANTS S AE1 V AH0 N T S +SAVARD S AE1 V ER0 D +SAVARESE S AA0 V AA0 R EY1 Z IY0 +SAVARINO S AA0 V AA0 R IY1 N OW0 +SAVARY S AE1 V EH0 R IY0 +SAVAS S AA1 V AA0 Z +SAVASTA S AH0 V AE1 S T AH0 +SAVASTANO S AA0 V AA0 S T AA1 N OW0 +SAVE S EY1 V +SAVE'S S EY1 V Z +SAVED S EY1 V D +SAVEDRA S AH0 V EH1 D R AH0 +SAVEL S AA0 V EH1 L +SAVELL S AA0 V EY1 L +SAVELY S EY1 V L IY0 +SAVER S EY1 V ER0 +SAVERS S EY1 V ER0 Z +SAVERY S EY1 V ER0 IY0 +SAVES S EY1 V Z +SAVIANO S AA0 V IY0 AA1 N OW0 +SAVICH S AE1 V IH0 CH +SAVICKAS S AE1 V IH0 K AH0 Z +SAVIDGE S AE1 V IH0 JH +SAVIER S EY1 V Y ER0 +SAVIKAS S AH0 V IY1 K AH0 S +SAVILL S AA0 V IY1 L +SAVILLE S AA1 V IH0 L +SAVIMBI S AH0 V IH1 M B IY0 +SAVIN S AE1 V IH0 N +SAVIN'S S AE1 V IH0 N Z +SAVINA S AH0 V IY1 N AH0 +SAVING S EY1 V IH0 NG +SAVINGS S EY1 V IH0 NG Z +SAVINGS' S EY1 V IH0 NG Z +SAVINGS'S S EY1 V IH0 NG Z +SAVINGS'S(1) S EY1 V IH0 NG Z IH0 Z +SAVINI S AA0 V IY1 N IY0 +SAVINO S AA0 V IY1 N OW0 +SAVIO S AA1 V IY0 OW0 +SAVION S AE1 V IY0 AO0 N +SAVION(1) S AE1 V Y AO0 N +SAVIOR S EY1 V Y ER0 +SAVIOR'S S EY1 V Y ER0 Z +SAVIORS S EY1 V Y ER0 Z +SAVIR S EY1 V ER0 +SAVIR(1) S AH0 V IY1 R +SAVITCH S AE1 V IH0 CH +SAVITSKY S AH0 V IH1 T S K IY0 +SAVITT S AH0 V IH1 T +SAVITZ S AE1 V IH0 T S +SAVKO S AE1 V K OW0 +SAVO S AA1 V OW0 +SAVOCA S AA0 V OW1 K AH0 +SAVOIA S AA0 V OW1 Y AH0 +SAVOIE S AA1 V W AA0 +SAVON S EY1 V AO0 N +SAVONA S AA0 V OW1 N AH0 +SAVOR S EY1 V ER0 +SAVORED S EY1 V ER0 D +SAVORING S EY1 V ER0 IH0 NG +SAVORS S EY1 V ER0 Z +SAVORY S EY1 V ER0 IY0 +SAVOY S AH0 V OY1 +SAVR S EY1 V ER0 +SAVVIEST S AE1 V IY0 IH0 S T +SAVVY S AE1 V IY0 +SAW S AO1 +SAWA S AO1 W AH0 +SAWALL S AO1 W AO0 L +SAWASDEE S AH0 W AA1 Z D IY0 +SAWATZKY S AH0 W AA1 T S K IY0 +SAWAYA S AO0 W AA1 Y AH0 +SAWCHUK S AO1 CH AH0 K +SAWDEY S AO1 D IY0 +SAWDON S AO1 D AH0 N +SAWDUST S AO1 D AH2 S T +SAWDY S AO1 D IY0 +SAWED S AO1 D +SAWHILL S AO1 HH IH2 L +SAWICKI S AO0 IH1 T S K IY0 +SAWICZ S AW1 IH0 T S +SAWIN S AO1 IY0 N +SAWING S AO1 IH0 NG +SAWKA S AO1 K AH0 +SAWMILL S AO1 M IH2 L +SAWMILLS S AO1 M IH2 L Z +SAWS S AO1 Z +SAWSHANK S AO1 SH AE2 N K +SAWTELL S AO1 T EH2 L +SAWTELLE S AO2 T EH1 L +SAWYER S AO1 Y ER0 +SAWYER(1) S OY1 ER0 +SAWYER'S S AO1 Y ER0 Z +SAWYERS S AO1 Y ER0 Z +SAX S AE1 K S +SAXBY S AE1 K S B IY0 +SAXE S AE1 K S +SAXENA S AE1 K S IH0 N AH0 +SAXER S AE1 K S ER0 +SAXMAN S AE1 K S M AH0 N +SAXON S AE1 K S AH0 N +SAXON'S S AE1 K S AH0 N Z +SAXONA S AE1 K S AH0 N AH0 +SAXONS S AE1 K S AH0 N Z +SAXONY S AE1 K S AH0 N IY0 +SAXOPHONE S AE1 K S AH0 F OW2 N +SAXOPHONES S AE1 K S AH0 F OW2 N Z +SAXOPHONIST S AE1 K S AH0 F OW2 N IH0 S T +SAXTON S AE1 K S T AH0 N +SAY S EY1 +SAYAD S AY1 AE0 D +SAYAD'S S AY1 AE0 D Z +SAYBROOK S EY1 B R UH2 K +SAYE S EY1 +SAYED S AA2 Y EH1 D +SAYED(1) S EY2 Y IH1 D +SAYED(2) S EY1 D +SAYEGH S EY1 IH0 G +SAYER S EY1 ER0 +SAYERS S EY1 ER0 Z +SAYIID S AY1 IH0 D +SAYIID(1) S AY0 IY1 D +SAYIN' S EY1 IH0 N +SAYING S EY1 IH0 NG +SAYINGS S EY1 IH0 NG Z +SAYITO S AY0 IY1 T OW0 +SAYLE S EY1 L +SAYLER S EY1 L ER0 +SAYLES S EY1 L Z +SAYLOR S EY1 L ER0 +SAYLORS S EY1 L ER0 Z +SAYRE S EH1 R +SAYRES S EH1 R Z +SAYS S EH1 Z +SAYS(1) S IH1 Z +SAYYID S AY1 IH0 D +SAZAMA S AA0 Z AA1 M AH0 +SBA EH2 S B IY2 EY1 +SBARRO S B AA1 R OW0 +SBF EH2 S B IY2 EH1 F +SCAB S K AE1 B +SCABBARD S K AE1 B ER0 D +SCABS S K AE1 B Z +SCACCIA S K AA1 CH AH0 +SCAD S K AE1 D +SCADDEN S K AE1 D AH0 N +SCADS S K AE1 D Z +SCADUTO S K AA0 D UW1 T OW0 +SCAFF S K AE1 F +SCAFFIDI S K AA0 F IY1 D IY0 +SCAFFOLD S K AE1 F AH0 L D +SCAFFOLDING S K AE1 F AH0 L D IH0 NG +SCAFFOLDS S K AE1 F AH0 L D Z +SCAFIDI S K AA0 F IY1 D IY0 +SCAGGS S K AE1 G Z +SCAGLIONE S K AE2 G L IY0 OW1 N IY0 +SCAGS S K AE1 G Z +SCAHILL S K EY1 HH IH2 L +SCAIFE S K EY1 F +SCALA S K AA1 L AH0 +SCALABLE S K EY1 L AH0 B AH0 L +SCALAMANDRE S K AA1 L AH0 M AA2 N D ER0 +SCALAMANDRE(1) S K AE1 L AH0 M AE2 N D ER0 +SCALAR S K EY1 L ER0 +SCALD S K AO1 L D +SCALDED S K AO1 L D IH0 D +SCALDING S K AO1 L D IH0 NG +SCALDS S K AO1 L D Z +SCALE S K EY1 L +SCALEATRON S K EY1 L IY0 AH0 T R AO0 N +SCALED S K EY1 L D +SCALERA S K AA0 L EH1 R AH0 +SCALES S K EY1 L Z +SCALESE S K AA0 L EY1 Z IY0 +SCALF S K AE1 L F +SCALFARO S K AE2 L F AA1 R OW0 +SCALI S K AA1 L IY0 +SCALI(1) S K EY1 L IY0 +SCALIA S K AA1 L IY0 AH0 +SCALIA(1) S K AA1 L Y AH0 +SCALIA'S S K AA1 L IY0 AH0 Z +SCALIA'S(1) S K AA1 L Y AH0 Z +SCALING S K EY1 L IH0 NG +SCALISE S K AA1 L AY0 Z +SCALISI S K AA0 L IY1 S IY0 +SCALLAN S K AE1 L AH0 N +SCALLION S K AE1 L Y AH0 N +SCALLIONS S K AE1 L Y AH0 N Z +SCALLON S K AE1 L AH0 N +SCALLOP S K AE1 L AH0 P +SCALLOPED S K AA1 L AH0 P T +SCALLOPS S K AE1 L AH0 P S +SCALLY S K AE1 L IY0 +SCALP S K AE1 L P +SCALPED S K AE1 L P T +SCALPEL S K AE1 L P AH0 L +SCALPELS S K AE1 L P AH0 L Z +SCALPER S K AE1 L P ER0 +SCALPERS S K AE1 L P ER0 Z +SCALPING S K AE1 L P IH0 NG +SCALPS S K AE1 L P S +SCALZI S K AA1 L Z IY0 +SCALZITTI S K AA0 L Z IY1 T IY0 +SCALZO S K AA1 L Z OW0 +SCAM S K AE1 M +SCAMMED S K AE1 M D +SCAMMELL S K AE1 M AH0 L +SCAMMER S K AE1 M ER0 +SCAMMERS S K AE1 M ER0 Z +SCAMMON S K AE1 M AH0 N +SCAMPER S K AE1 M P ER0 +SCAMPERED S K AE1 M P ER0 D +SCAMPERING S K AE1 M P ER0 IH0 NG +SCAMS S K AE1 M Z +SCAN S K AE1 N +SCANDAL S K AE1 N D AH0 L +SCANDAL'S S K AE1 N D AH0 L Z +SCANDALIZE S K AE1 N D AH0 L AY2 Z +SCANDALIZED S K AE1 N D AH0 L AY2 Z D +SCANDALOUS S K AE1 N D AH0 L AH0 S +SCANDALS S K AE1 N D AH0 L Z +SCANDIA S K AE1 N D IY0 AH0 +SCANDINAVIA S K AE2 N D IH0 N EY1 V IY0 AH0 +SCANDINAVIA'S S K AE2 N D IH0 N EY1 V IY0 AH0 Z +SCANDINAVIAN S K AE2 N D IH0 N EY1 V IY0 AH0 N +SCANDINAVIANS S K AE2 N D IH0 N EY1 V IY0 AH0 N Z +SCANIA S K AA1 N IY0 AH0 +SCANLAN S K AE1 N L AH0 N +SCANLAND S K AE1 N L AH0 N D +SCANLIN S K AE1 N L IH0 N +SCANLON S K AE1 N L AH0 N +SCANLON'S S K AE1 N L AH0 N Z +SCANNED S K AE1 N D +SCANNELL S K AE1 N AH0 L +SCANNER S K AE1 N ER0 +SCANNERS S K AE1 N ER0 Z +SCANNING S K AE1 N IH0 NG +SCANS S K AE1 N Z +SCANT S K AE1 N T +SCANTILY S K AE1 N T AH0 L IY0 +SCANTINESS S K AE1 N T IY0 N AH0 S +SCANTLIN S K AE1 N T L IH0 N +SCANTY S K AE1 N T IY0 +SCAPA S K AA1 P AH0 +SCAPE S K EY1 P +SCAPEGOAT S K EY1 P G OW2 T +SCAPEGOATED S K EY1 P G OW2 T IH0 D +SCAPEGOATING S K EY1 P G OW2 T IH0 NG +SCAPEGOATS S K EY1 P G OW2 T S +SCAPULA S K AE1 P Y AH0 L AH0 +SCAR S K AA1 R +SCARAMOUCH S K AE1 R AH0 M AW2 CH +SCARANO S K AA0 R AA1 N OW0 +SCARBERRY S K AA1 R B EH2 R IY0 +SCARBOROUGH S K AA1 R B ER2 OW0 +SCARBRO S K AA1 R B R OW0 +SCARBROUGH S K AA1 R B R AW0 +SCARCE S K EH1 R S +SCARCELLA S K AA2 R S EH1 L AH0 +SCARCELY S K EH1 R S L IY0 +SCARCER S K EH1 R S ER0 +SCARCITY S K EH1 R S IH0 T IY0 +SCARDINA S K AA0 R D IY1 N AH0 +SCARDINO S K AA0 R D IY1 N OW0 +SCARE S K EH1 R +SCARECROW S K AE1 R K R OW2 +SCARECROW'S S K AE1 R K R OW2 Z +SCARECROWS S K AE1 R K R OW2 Z +SCARED S K EH1 R D +SCARES S K EH1 R Z +SCARF S K AA1 R F +SCARFACE S K AA1 R F EY2 S +SCARFF S K AA1 R F +SCARFO S K AA1 R F OW0 +SCARFS S K AA1 R F S +SCARGILL S K AA1 R G IH2 L +SCARIER S K EH1 R IY0 ER0 +SCARIEST S K EH1 R IY0 AH0 S T +SCARING S K EH1 R IH0 NG +SCARLATA S K AA0 R L AA1 T AH0 +SCARLET S K AA1 R L AH0 T +SCARLETT S K AA1 R L IH0 T +SCAROLA S K AA0 R OW1 L AH0 +SCARP S K AA1 R P +SCARPA S K AA1 R P AH0 +SCARPATI S K AA0 R P AA1 T IY0 +SCARPELLI S K AA0 R P EH1 L IY0 +SCARPELLO S K AA2 R P EH1 L OW0 +SCARPINATTO S K AA2 R P IH0 N AA1 T OW0 +SCARPINO S K AA0 R P IY1 N OW0 +SCARPONE S K AA0 R P OW1 N IY0 +SCARPULLA S K AA2 R P UH1 L AH0 +SCARRED S K AA1 R D +SCARRING S K AA1 R IH0 NG +SCARRY S K AE1 R IY0 +SCARS S K AA1 R Z +SCARSDALE S K AA1 R Z D EY2 L +SCARSELLA S K AA2 R S EH1 L AH0 +SCARVES S K AA1 R V Z +SCARY S K EH1 R IY0 +SCAT S K AE1 T +SCATENA S K AA0 T EH1 N AH0 +SCATES S K EY1 T S +SCATHING S K EY1 DH IH0 NG +SCATOLOGICAL S K AE0 T AH0 L AO1 JH AH0 K AH0 L +SCATOLOGY S K AE0 T AO1 L AH0 JH IY0 +SCATTER S K AE1 T ER0 +SCATTERED S K AE1 T ER0 D +SCATTERGOOD S K AE1 T ER0 G UH2 D +SCATTERGORIES S K AE1 T ER0 G AO2 R IY0 Z +SCATTERGORY S K AE1 T ER0 G AO2 R IY0 +SCATTERING S K AE1 T ER0 IH0 NG +SCATTERSHOT S K AE1 T ER0 SH AA2 T +SCATURRO S K AA0 T UH1 R OW0 +SCAVENGE S K AE1 V AH0 N JH +SCAVENGER S K AE1 V AH0 N JH ER0 +SCAVENGERS S K AE1 V AH0 N JH ER0 Z +SCAVENGING S K AE1 V AH0 N JH IH0 NG +SCAVO S K AA1 V OW0 +SCAVONE S K AH0 V OW1 N +SCAVUZZO S K AA0 V UW1 Z OW0 +SCEARCE S ER1 S +SCENARIO S IH0 N EH1 R IY0 OW0 +SCENARIOS S IH0 N EH1 R IY0 OW0 Z +SCENE S IY1 N +SCENERIES S IY1 N ER0 IY0 Z +SCENERY S IY1 N ER0 IY0 +SCENES S IY1 N Z +SCENIC S IY1 N IH0 K +SCENT S EH1 N T +SCENTED S EH1 N T IH0 D +SCENTS S EH1 N T S +SCEPTIC S K EH1 P T IH0 K +SCEPTICS S K EH1 P T IH0 K S +SCEPTRE S EH1 P T ER0 +SCEPTRE(1) S K EH1 P T ER0 +SCERBO S K EH1 R B OW0 +SCERZUSKY S ER0 Z UW1 S K IY0 +SCHAAB SH AA1 B +SCHAACK SH AA1 K +SCHAAD SH AA1 D +SCHAADT SH AA1 T +SCHAAF SH AA1 F +SCHAAFSMA SH AA1 F S M AH0 +SCHAAL SH AA1 L +SCHAAP SH AA1 P +SCHAAR SH AA1 R +SCHAB SH AE1 B +SCHABACKER SH AA1 B AE2 K ER0 +SCHABEL SH AE1 B AH0 L +SCHABEN SH AE1 B AH0 N +SCHABER SH EY1 B ER0 +SCHABERG SH AA1 B ER0 G +SCHABES SH EY1 B Z +SCHACHER SH AE1 K ER0 +SCHACHNER SH AE1 K N ER0 +SCHACHT SH AE1 K T +SCHACHTER SH AE1 K T ER0 +SCHACK SH AE1 K +SCHAD SH AE1 D +SCHADE SH EY1 D +SCHADEL SH AE1 D AH0 L +SCHADEN SH AE1 D AH0 N +SCHADENFREUDE SH AE1 D IH0 N F R OY2 D +SCHADER SH EY1 D ER0 +SCHADLER SH EY1 D AH0 L ER0 +SCHADLER(1) SH EY1 D L ER0 +SCHADT SH AE1 T +SCHAECHER SH EH1 K ER0 +SCHAEDEL SH EH1 D AH0 L +SCHAEDLER SH EH1 D AH0 L ER0 +SCHAEDLER(1) SH EH1 D L ER0 +SCHAEFER SH EY1 F ER0 +SCHAEFERS SH EY1 F ER0 Z +SCHAEFFER SH EH1 F ER0 +SCHAEFFLER SH AE1 F L ER0 +SCHAER SH AA1 ER0 +SCHAFER SH EY1 F ER0 +SCHAFF SH AE1 F +SCHAFFER SH EY1 F ER0 +SCHAFFERT SH AE1 F ER0 T +SCHAFFLER SH AE1 F L ER0 +SCHAFFNER SH AE1 F N ER0 +SCHAIBLE S K EY1 B AH0 L +SCHAIRER SH AY1 ER0 R +SCHAJA SH AA1 JH AH0 +SCHAKE SH EY1 K +SCHALK SH AO1 K +SCHALL SH AO1 L +SCHALLER SH AO1 L ER0 +SCHALLOCK SH AE1 L AH0 K +SCHALOW SH AE1 L OW0 +SCHAMA SH AA1 M AH0 +SCHAMBER SH AE1 M B ER0 +SCHAMBERGER SH AE1 M B ER0 G ER0 +SCHAMEL SH AE1 M AH0 L +SCHAMP SH AE1 M P +SCHANBACHER SH AE1 N B AA2 K ER0 +SCHANCK SH AE1 NG K +SCHANER SH EY1 N ER0 +SCHANK SH AE1 NG K +SCHANTZ SH AE1 N T S +SCHANZ SH AE1 N S +SCHAPER SH EY1 P ER0 +SCHAPIRO SH AE1 P AY0 R OW0 +SCHAPP SH AE1 P +SCHAPPELL SH AE1 P AH0 L +SCHAPPERT SH AE1 P ER0 T +SCHAR SH AA1 R +SCHARA S K AE1 R AH0 +SCHARDT SH AA1 R T +SCHARENBERG SH EH1 R AH0 N B ER0 G +SCHARER SH EH1 R ER0 +SCHARF SH AA1 R F +SCHARFE S K AA1 R F +SCHARFENBERG SH AA1 R F AH0 N B ER0 G +SCHARFF SH AA1 R F +SCHARFFENBERGER SH AA1 R F AH0 N B ER0 G ER0 +SCHARLAU SH AA1 R L AW0 +SCHARNHORST SH AA1 R N HH AO0 R S T +SCHARP SH AA1 R P +SCHARPF SH AA1 R P F +SCHARR SH AA1 R +SCHARRER SH AA1 R ER0 +SCHARTZ SH AA1 R T S +SCHATTNER SH AE1 T N ER0 +SCHATZ SH AE1 T S +SCHATZBERG SH AE1 T S B ER0 G +SCHATZEL SH AE1 T Z AH0 L +SCHATZMAN SH AE1 T Z M AH0 N +SCHAU SH OW1 +SCHAUB SH AO1 B +SCHAUBLE SH OW1 B AH0 L +SCHAUER SH AW1 ER0 +SCHAUF SH AW1 F +SCHAUFLER SH AW1 F AH0 L ER0 +SCHAUFLER(1) SH AW1 F L ER0 +SCHAUL SH OW1 L +SCHAUM SH OW1 M +SCHAUMBERG SH OW1 M B ER0 G +SCHAUMBURG SH AW1 M B ER0 G +SCHAUS S K AW1 S +SCHAUT SH OW1 T +SCHAVE SH EY1 V +SCHEAR SH IH1 R +SCHECHTER SH EH1 K T ER0 +SCHECHTMAN SH EH1 K T M AH0 N +SCHECK SH EH1 K +SCHECKEL SH EH1 K AH0 L +SCHECTER SH EH1 K T ER0 +SCHEDLER SH EH1 D AH0 L ER0 +SCHEDLER(1) SH EH1 D L ER0 +SCHEDULE S K EH1 JH UH0 L +SCHEDULE(1) S K EH1 JH UW0 L +SCHEDULED S K EH1 JH UH0 L D +SCHEDULED(1) S K EH1 JH UW0 L D +SCHEDULER S K EH1 JH UH0 L ER0 +SCHEDULER(1) S K EH1 JH UW0 L ER0 +SCHEDULERS S K EH1 JH UH0 L ER0 Z +SCHEDULERS(1) S K EH1 JH UW0 L ER0 Z +SCHEDULES S K EH1 JH UH0 L Z +SCHEDULES(1) S K EH1 JH UW0 L Z +SCHEDULING S K EH1 JH UH0 L IH0 NG +SCHEDULING(1) S K EH1 JH UW0 L IH0 NG +SCHEEL SH IY1 L +SCHEELE SH IY1 L +SCHEELER SH IY1 L ER0 +SCHEER SH IH1 R +SCHEERER SH IH1 R ER0 +SCHEETS SH IY1 T S +SCHEETZ SH IY1 T S +SCHEFF SH EH1 F +SCHEFFEL SH EH1 F AH0 L +SCHEFFER SH EH1 F ER0 +SCHEFFLER SH EH1 F AH0 L ER0 +SCHEFFLER(1) SH EH1 F L ER0 +SCHEHR SH EH1 R +SCHEIB SH AY1 B +SCHEIBE SH AY1 B +SCHEIBEL SH AY1 B AH0 L +SCHEIBER SH AY1 B ER0 +SCHEIBLE S K AY1 B AH0 L +SCHEIBNER SH AY1 B N ER0 +SCHEID SH AY1 D +SCHEIDECKER SH AY1 D IH0 K ER0 +SCHEIDEGGER SH AY1 D IH0 G ER0 +SCHEIDEL SH AY1 D AH0 L +SCHEIDER SH AY1 D ER0 +SCHEIDERER SH AY1 D ER0 ER0 +SCHEIDLER SH AY1 D AH0 L ER0 +SCHEIDLER(1) SH AY1 D L ER0 +SCHEIDT SH AY1 T +SCHEIER SH AY1 ER0 +SCHEIMAN SH AY1 M AH0 N +SCHEIN SH AY1 N +SCHEINBERG SH AY1 N B ER0 G +SCHEINER SH AY1 N ER0 +SCHEIRER SH AY1 ER0 R +SCHELER SH IY1 L ER0 +SCHELIN SH EH1 L IH0 N +SCHELL S K EH1 L +SCHELLENBERG SH EH1 L AH0 N B ER0 G +SCHELLENBERGER SH EH1 L AH0 N B ER0 G ER0 +SCHELLENGER SH EH1 L IH0 N JH ER0 +SCHELLER S K EH1 L ER0 +SCHELLHAMMER SH EH1 L HH AH0 M ER0 +SCHELLHASE SH EH1 L HH AH0 S +SCHELLHORN SH EH1 L HH ER0 N +SCHELLING S K EH1 L IH0 NG +SCHELLINGER SH EH1 L IH0 NG ER0 +SCHEMA S K IY1 M AH0 +SCHEMAS S K IY1 M AH0 Z +SCHEMATA S K IH0 M AE1 T AH0 +SCHEMATIC S K IH0 M AE1 T IH0 K +SCHEMATICS S K IH0 M AE1 T IH0 K S +SCHEMBRI SH EH1 M B R IY0 +SCHEME S K IY1 M +SCHEMED S K IY1 M D +SCHEMEL SH EH1 M AH0 L +SCHEMER S K IY1 M ER0 +SCHEMES S K IY1 M Z +SCHEMING S K IY1 M IH0 NG +SCHEMM SH EH1 M +SCHEMMEL SH EH1 M AH0 L +SCHEMPF SH EH1 M F +SCHEMPP SH EH1 M P +SCHENA SH IY1 N AH0 +SCHENCK SH EH1 NG K +SCHENDEL SH EH1 N D AH0 L +SCHENECTADY S K AH0 N EH1 K T AH0 D IY0 +SCHENECTADY'S S K AH0 N EH1 K T AH0 D IY0 Z +SCHENK SH EH1 NG K +SCHENKEL SH EH1 NG K AH0 L +SCHENKEN SH EH1 NG K AH0 N +SCHENKER SH EH1 NG K ER0 +SCHENLEY SH EH1 N L IY0 +SCHEPER SH IY1 P ER0 +SCHEPERS SH IY1 P ER0 Z +SCHEPIS SH EH1 P IH0 S +SCHEPP SH EH1 P +SCHER SH ER1 +SCHERB SH ER1 B +SCHERBARTH SH ER1 B AA0 R TH +SCHERER SH IH1 R ER0 +SCHERER'S SH EH1 R ER0 Z +SCHERF SH ER1 F +SCHERFF SH ER1 F +SCHERGER SH ER1 G ER0 +SCHERING SH ER1 IH0 NG +SCHERING(1) SH EH1 R IH0 NG +SCHERING'S SH EH1 R IH0 NG Z +SCHERLIS SH ER1 L IH0 S +SCHERMAN SH ER1 M AH0 N +SCHERMER SH ER1 M ER0 +SCHERMERHORN SH ER1 M ER0 HH ER0 N +SCHERR SH EH1 R +SCHERRER SH EH1 R ER0 +SCHERTZ SH ER1 T S +SCHERTZER SH ER1 T S ER0 +SCHERZ SH ER1 Z +SCHERZER SH ER1 Z ER0 +SCHERZINGER SH ER1 Z IH0 NG ER0 +SCHETTER SH EH1 T ER0 +SCHETTINO SH EH1 T IY0 N OW0 +SCHETTLER SH EH1 T AH0 L ER0 +SCHETTLER(1) SH EH1 T L ER0 +SCHEU SH OY1 +SCHEUER SH OY1 ER0 +SCHEUERMAN SH OY1 ER0 M AH0 N +SCHEUERMANN SH OY1 ER0 M AH0 N +SCHEUFLER SH OY1 F AH0 L ER0 +SCHEUFLER(1) SH OY1 F L ER0 +SCHEUNEMANN SH OY1 N M AH0 N +SCHEURER SH ER1 ER0 +SCHEURICH SH OY1 R IH0 K +SCHEURING SH ER1 IH0 NG +SCHEVE SH IY1 V +SCHEWE SH Y UW1 +SCHEXNAYDER SH EH1 K S N EY0 D ER0 +SCHEXNIDER SH EH1 K S N AY0 D ER0 +SCHEY SH EY1 +SCHIANO S K IY0 AA1 N OW0 +SCHIAPPA S K IY0 AA1 P AH0 +SCHIAVI S K IY0 AA1 V IY0 +SCHIAVO S K IY0 AA1 V OW0 +SCHIAVO'S S K IY0 AA1 V OW0 Z +SCHIAVONE S K IY0 AA0 V OW1 N IY0 +SCHIAVONI S K IY0 AA0 V OW1 N IY0 +SCHICK SH IH1 K +SCHICKER SH IH1 K ER0 +SCHICKLER SH IH1 K AH0 L ER0 +SCHICKLER(1) SH IH1 K L ER0 +SCHICKLING SH IH1 K AH0 L IH0 NG +SCHICKLING(1) SH IH1 K L IH0 NG +SCHIEBEL SH IY1 B AH0 L +SCHIEBER SH IY1 B ER0 +SCHIEFELBEIN SH IY1 F IH0 L B AY0 N +SCHIEFER SH IY1 F ER0 +SCHIEFFELIN SH IY1 F AH0 L IH0 N +SCHIEFFER SH IY1 F ER0 +SCHIEL SH IY1 L +SCHIELD SH IY1 L D +SCHIELE SH IY1 L +SCHIELKE SH IY1 L K +SCHIEMANN SH IY1 M AH0 N +SCHIER SH AY1 ER0 +SCHIEREN SH IH1 R AH0 N +SCHIERL SH IH1 R L +SCHIESS SH IY1 S +SCHIESSER SH IY1 S ER0 +SCHIEWE SH IY1 W IY0 +SCHIFANO S K IY0 F AA1 N OW0 +SCHIFERON SH IH1 F ER0 AO2 N +SCHIFERON(1) SH IH1 F R AO2 N +SCHIFERON'S SH IH1 F ER0 AO2 N Z +SCHIFERON'S(1) SH IH1 F R AO2 N Z +SCHIFF SH IH1 F +SCHIFFBAUER SH IH1 F B AW0 ER0 +SCHIFFER SH IH1 F ER0 +SCHIFFLER SH IH1 F AH0 L ER0 +SCHIFFLER(1) SH IH1 F L ER0 +SCHIFFMAN SH IH1 F M AH0 N +SCHIFFNER SH IH1 F N ER0 +SCHILD SH AY1 L D +SCHILDER SH AY1 L D ER0 +SCHILDKNECHT SH AY1 L D K AH0 N EH2 K T +SCHILDT SH IH1 L T +SCHILKE SH IH1 L K +SCHILL SH IH1 L +SCHILLACI S K IY0 L AA1 CH IY0 +SCHILLER SH IH1 L ER0 +SCHILLER'S SH IH1 L ER0 Z +SCHILLING SH IH1 L IH0 NG +SCHILLING'S SH IH1 L IH0 NG Z +SCHILLINGER SH IH1 L IH0 NG ER0 +SCHILLINGS SH IH1 L IH0 NG Z +SCHILLO S K IH1 L OW0 +SCHILT SH IH1 L T +SCHILTKNECHT SH IH1 L T N EH2 K T +SCHILTZ SH IH1 L T S +SCHILZ SH IH1 L Z +SCHIMBERNI SH IH0 M B ER1 N IY0 +SCHIMEK SH IH1 M IH0 K +SCHIMKE S K IH1 M K +SCHIMMEL SH IH1 M AH0 L +SCHIMMELBUSCH SH IH1 M AH0 L B UH2 SH +SCHIMMING SH IH1 M IH0 NG +SCHIMPF SH IH1 M P F +SCHINDEL SH IH1 N D AH0 L +SCHINDLER SH IH1 N D L ER0 +SCHINDLER'S SH IH1 N D L ER0 Z +SCHINKE S K IH1 NG K +SCHINKEL SH IH1 NG K AH0 L +SCHIPANI S K IY0 P AA1 N IY0 +SCHIPHOL S K IH1 P AH0 L +SCHIPKE SH IH1 P K IY0 +SCHIPPER SH IH1 P ER0 +SCHIPPERS SH IH1 P ER0 Z +SCHIRALDI S K IH0 R AA1 L D IY0 +SCHIRM SH ER1 M +SCHIRMER SH ER1 M ER0 +SCHIRO S K IH1 R OW0 +SCHIRTZINGER SH ER1 T Z IH0 NG ER0 +SCHISLER SH IH1 S AH0 L ER0 +SCHISLER(1) SH IH1 S L ER0 +SCHISM S K IH1 Z AH0 M +SCHISMS S K IH1 Z AH0 M Z +SCHISSEL SH IH1 S AH0 L +SCHISSLER SH IH1 S AH0 L ER0 +SCHISSLER(1) SH IH1 S L ER0 +SCHIST SH IH1 S T +SCHISTS SH IH1 S T S +SCHIZOPHRENIA S K IH2 T S AH0 F R IY1 N IY0 AH0 +SCHIZOPHRENIC SH IH2 Z AH0 F R EH1 N IH0 K +SCHLABACH SH L AE1 B AA0 K +SCHLACHTER SH L AE1 K T ER0 +SCHLACK SH L AE1 K +SCHLAFER SH L EY1 F ER0 +SCHLAFLY SH L AE1 F L IY0 +SCHLAG SH L AE1 G +SCHLAGEL SH L AE1 G AH0 L +SCHLAGER SH L EY1 G ER0 +SCHLAGETER SH L AE1 G IY0 T ER0 +SCHLAKE SH L EY1 K +SCHLANG SH L AE1 NG +SCHLANGEN SH L AE1 NG AH0 N +SCHLANGER SH L AE1 NG ER0 +SCHLARB SH L AA1 R B +SCHLATER SH L EY1 T ER0 +SCHLATTER SH L AE1 T ER0 +SCHLAUCH SH L AW1 K +SCHLECHT SH L EH1 K T +SCHLECHTER SH L EH1 K T ER0 +SCHLEE SH L IY1 +SCHLEETER SH L IY1 T ER0 +SCHLEGEL SH L EY1 G AH0 L +SCHLEGELMILCH SH L EH1 G IH0 L M IH0 L K +SCHLEICH SH L AY1 K +SCHLEICHER SH L AY1 K ER0 +SCHLEIF SH L AY1 F +SCHLEIFER SH L AY1 F ER0 +SCHLEIGER SH L AY1 G ER0 +SCHLEIMER SH L AY1 M ER0 +SCHLEIN SH L AY1 N +SCHLEIS SH L AY1 Z +SCHLEMMER SH L EH1 M ER0 +SCHLENDER SH L EH1 N D ER0 +SCHLENKER SH L EH1 NG K ER0 +SCHLEPP SH L EH1 P +SCHLERETH SH L EH1 R IH0 TH +SCHLESINGER SH L EH1 S IH0 N JH ER0 +SCHLESSER SH L EH1 S ER0 +SCHLESSINGER SH L EH1 S IH0 N JH ER0 +SCHLESWIG SH L EH1 S W IH0 G +SCHLEY SH L EY1 +SCHLEYER SH L EY1 ER0 +SCHLICHER SH L IH1 K ER0 +SCHLICHT SH L IH1 K T +SCHLICHTER SH L IH1 K T ER0 +SCHLICHTING SH L IH1 K T IH0 NG +SCHLICK SH L IH1 K +SCHLICKER SH L IH1 K ER0 +SCHLICT SH L IH1 K T +SCHLIE SH L IY1 +SCHLIEP SH L IY1 P +SCHLIEPER SH L IY1 P ER0 +SCHLINK SH L IH1 NG K +SCHLITT SH L IH1 T +SCHLITTER SH L IH1 T ER0 +SCHLITZ SH L IH1 T S +SCHLOBOHM SH L AA1 B OW0 M +SCHLOCK SH L AA1 K +SCHLOEMER SH L OW1 M ER0 +SCHLOESSER SH L AA1 IH0 S ER0 +SCHLOESSER(1) SH L AA1 S ER0 +SCHLOSBERG SH L AA1 S B ER0 G +SCHLOSS SH L AO1 S +SCHLOSSBERG SH L AO1 S B ER0 G +SCHLOSSER SH L AO1 S ER0 +SCHLOSSMAN SH L AO1 S M AH0 N +SCHLOTT SH L AA1 T +SCHLOTTER SH L AA1 T ER0 +SCHLOTTERBECK SH L AA1 T ER0 B EH0 K +SCHLOTTMAN SH L AA1 T M AH0 N +SCHLOTZHAUER SH L AA1 T S HH AW0 ER0 +SCHLOUGH SH L AW1 +SCHLUETER SH L UH1 T ER0 +SCHLUMBERGER SH L AH1 M B ER0 ZH EY2 +SCHLUMBERGER(1) SH L AH1 M B ER0 G ER0 +SCHLUND SH L AH1 N D +SCHLUP SH L AH1 P +SCHLUTER SH L UW1 T ER0 +SCHMADER SH M EY1 D ER0 +SCHMAHL SH M AA1 L +SCHMAL SH M AE1 L +SCHMALE SH M EY1 L +SCHMALL SH M AO1 L +SCHMALTZ SH M AA1 L T S +SCHMALZ SH M AO1 L Z +SCHMANCY SH M AE1 N S IY0 +SCHMAUS SH M AW1 Z +SCHMEAD SH M IY1 D +SCHMECHEL SH M EH1 K AH0 L +SCHMECK SH M EH1 K +SCHMEHL SH M EH1 L +SCHMEICHEL SH M AY1 K AH0 L +SCHMEISER SH M AY1 S ER0 +SCHMELING SH M EH1 L IH0 NG +SCHMELTER SH M EH1 L T ER0 +SCHMELTZ SH M EH1 L T S +SCHMELTZER SH M EH1 L T Z ER0 +SCHMELZ SH M EH1 L Z +SCHMELZER SH M EH1 L Z ER0 +SCHMELZLE SH M EH1 L Z AH0 L +SCHMERGEL SH M ER1 G AH0 L +SCHMERTZ SH M ER1 T S +SCHMETTERER SH M EH1 T ER0 ER0 +SCHMICK SH M IH1 K +SCHMID SH M IH1 D +SCHMIDDY SH M IH1 D IY0 +SCHMIDGALL SH M IH1 JH AH0 L +SCHMIDL SH M IH1 D AH0 L +SCHMIDLIN SH M IH1 D L IH0 N +SCHMIDT SH M IH1 T +SCHMIDT'S SH M IH1 T S +SCHMIDTKE SH M IH1 T K IY0 +SCHMIED SH M AY1 D +SCHMIEDER SH M AY1 D ER0 +SCHMIEG SH M IY1 G +SCHMIERER SH M AY1 ER0 ER0 +SCHMIESING SH M IY1 S IH0 NG +SCHMIT SH M IH1 T +SCHMITT SH M IH1 T +SCHMITTER SH M IH1 T ER0 +SCHMITTOU SH M IH1 CH UW0 +SCHMITZ SH M IH1 T S +SCHMITZER SH M IH1 T S ER0 +SCHMOKE SH M OW1 K +SCHMOKER SH M OW1 K ER0 +SCHMOLDT SH M OW1 L T +SCHMOLL SH M AA1 L +SCHMOOZE SH M UW1 Z +SCHMOOZING SH M UW1 Z IH0 NG +SCHMOTZER SH M OW1 T Z ER0 +SCHMOYER SH M OY1 ER0 +SCHMUCK SH M AH1 K +SCHMUCKER SH M AH1 K ER0 +SCHMUCKLER SH M AH1 K L ER0 +SCHMUHL SH M AH1 L +SCHMULTS SH M AH1 L T S +SCHMUNK SH M AH1 NG K +SCHMUTZ SH M AH1 T S +SCHMUTZLER SH M AH1 T Z AH0 L ER0 +SCHMUTZLER(1) SH M AH1 T Z L ER0 +SCHNABEL SH N AE1 B AH0 L +SCHNACK SH N AE1 K +SCHNACKENBERG SH N AE1 K AH0 N B ER0 G +SCHNAKE SH N EY1 K +SCHNAKENBERG SH N EY1 K AH0 N B ER0 G +SCHNALL SH N AO1 L +SCHNAPP SH N AE1 P +SCHNAPPS SH N AE1 P S +SCHNARR SH N AE1 R +SCHNAUZER SH N AW1 Z ER0 +SCHNEBERGER SH N IY1 B ER0 G ER0 +SCHNEBLY SH N EH1 B L IY0 +SCHNECK SH N EH1 K +SCHNECKLOTH SH N EH1 K L AH0 TH +SCHNEE SH N IY1 +SCHNEEBERGER SH N IY1 B ER0 G ER0 +SCHNEEMAN SH N IY1 M AH0 N +SCHNEERSON SH N IH1 R S AH0 N +SCHNEERSON'S SH N IH1 R S AH0 N Z +SCHNEID SH N AY1 D +SCHNEIDER SH N AY1 D ER0 +SCHNEIDER'S SH N AY1 D ER0 Z +SCHNEIDERMAN SH N AY1 D ER0 M AH0 N +SCHNEIDERMAN'S SH N AY1 D ER0 M AH0 N Z +SCHNEIDERS SH N AY1 D ER0 Z +SCHNEIDERS' SH N AY1 D ER0 Z +SCHNEIDEWIND SH N AY1 D AH0 W IH2 N D +SCHNEIDEWIND'S SH N AY1 D AH0 W IH2 N D Z +SCHNEIER SH N AY1 ER0 +SCHNEITER SH N AY1 T ER0 +SCHNELL SH N EH1 L +SCHNELLE SH N EH1 L +SCHNELLER SH N EH1 L ER0 +SCHNEPF SH N EH1 P F +SCHNEPP SH N EH1 P +SCHNETTLER SH N EH1 T AH0 L ER0 +SCHNETTLER(1) SH N EH1 T L ER0 +SCHNETZER SH N EH1 T Z ER0 +SCHNICK SH N IH1 K +SCHNIDER SH N AY1 D ER0 +SCHNIEDER SH N AY1 D ER0 +SCHNIEDERS SH N AY1 D ER0 Z +SCHNIER SH N AY1 ER0 +SCHNITKER SH N IH1 T K ER0 +SCHNITTKE SH N IH1 T K IY0 +SCHNITZ SH N IH1 T S +SCHNITZER SH N IH1 T Z ER0 +SCHNITZLER SH N IH1 T S L ER0 +SCHNOEBELEN SH N OW1 B AH0 L AH0 N +SCHNOOK SH N UH1 K +SCHNOOKS SH N UH1 K S +SCHNOOR SH N UH1 R +SCHNORR SH N AO1 R +SCHNUR SH N ER1 +SCHNURR SH N ER1 +SCHNYDER SH N AY1 D ER0 +SCHNYDER'S SH N AY1 D ER0 Z +SCHOBEL SH OW1 B AH0 L +SCHOBER SH OW1 B ER0 +SCHOBERT SH AA1 B ER0 T +SCHOCH SH AA1 K +SCHOCK SH AA1 K +SCHOECK SH OW1 K +SCHOEFFLER SH OW1 F AH0 L ER0 +SCHOEFFLER(1) SH OW1 F L ER0 +SCHOELLER SH OW1 L ER0 +SCHOELLHORN SH OW1 L HH AO2 R N +SCHOEMAKER SH OW1 M EY2 K ER0 +SCHOEN SH OW1 N +SCHOENBAUM SH OW1 N B AW2 M +SCHOENBECK SH OW1 N B EH2 K +SCHOENBERG SH OW1 N B ER0 G +SCHOENBERGER SH OW1 N B ER0 G ER0 +SCHOENBORN SH OW1 N B ER0 N +SCHOENDORF SH OW1 N D AO0 R F +SCHOENE SH AA1 IY0 N +SCHOENECK SH OW1 N EH0 K +SCHOENECKER SH OW1 N EH0 K ER0 +SCHOENEMAN SH AA1 IY0 N M AH0 N +SCHOENEMANN SH AA1 IY0 N M AH0 N +SCHOENER SH OW1 N ER0 +SCHOENFELD SH OW1 N F EH2 L D +SCHOENFELDER SH OW1 N F EH0 L D ER0 +SCHOENFELDT SH OW1 N F EH2 L T +SCHOENHALS SH OW1 N HH AH0 L Z +SCHOENHERR SH OW1 N HH ER0 +SCHOENHOF SH OW1 N HH AA2 F +SCHOENHOF'S SH OW1 N HH AA2 F S +SCHOENHOLTZ SH OW1 N HH OW2 L T S +SCHOENIG SH OW1 N IH0 G +SCHOENING SH AA1 AH0 N IH0 NG +SCHOENROCK SH OW1 N R AH0 K +SCHOENTHAL SH OW1 N TH AO2 L +SCHOENWALD SH OW1 N W AO2 L D +SCHOEPE SH OW1 P +SCHOEPF SH OW1 P +SCHOEPKE SH OW1 P K IY0 +SCHOEPP SH OW1 P +SCHOEPPNER SH OW1 P N ER0 +SCHOETTLE SH OW1 T AH0 L +SCHOFF SH AO1 F +SCHOFFSTALL SH AO1 F S T AH0 L +SCHOFIELD S K 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S EH1 L K ER0 K +SELKIRK'S S EH1 L K ER0 K S +SELL S EH1 L +SELL-OUT S EH1 L AW2 T +SELLA S EH1 L AH0 +SELLAND S EH1 L AH0 N D +SELLARDS S EH1 L ER0 D Z +SELLARS S EH1 L ER0 Z +SELLARS'S S EH1 L ER0 Z IH0 Z +SELLE S EH1 L +SELLECK S EH1 L IH0 K +SELLEN S EH1 L AH0 N +SELLER S EH1 L ER0 +SELLER'S S EH1 L ER0 Z +SELLERS S EH1 L ER0 Z +SELLERS' S EH1 L ER0 Z +SELLEY S EH1 L IY0 +SELLICK S EH1 L IH0 K +SELLIER S EH1 L Y ER0 +SELLIN S EH1 L IH0 N +SELLING S EH1 L IH0 NG +SELLINGER S EH1 L IH0 NG ER0 +SELLINGS S EH1 L IH0 NG Z +SELLMAN S EH1 L M AH0 N +SELLMEYER S EH1 L M AY0 ER0 +SELLNER S EH1 L N ER0 +SELLOFF S EH1 L AO2 F +SELLOFFS S EH1 L AO2 F S +SELLON S EH1 L AH0 N +SELLOUT S EH1 L AW2 T +SELLOUTS S EH1 L AW2 T S +SELLS S EH1 L Z +SELMA S EH1 L M AH0 +SELMAN S EH1 L M AH0 N +SELMER S EH1 L M ER0 +SELMON S EH1 L M AH0 N +SELNER S EH1 L N ER0 +SELOVER S EH1 L AH0 V ER0 +SELOWSKY S EH0 L AW1 S K IY0 +SELPH S EH1 L F +SELSOR S EH1 L S ER0 +SELTZ S EH1 L T S +SELTZER S EH1 L T S ER0 +SELVA S EY1 L V AH0 +SELVAGE S EH1 L V IH0 JH +SELVAGGIO S EH0 L V AA1 JH IY0 OW0 +SELVES S EH1 L V Z +SELVEY S EH1 L V IY0 +SELVIDGE S EH1 L V IH0 JH +SELVIG S EH1 L V IH0 G +SELWAY S EH1 L W EY2 +SELWIN S EH1 L W IH0 N +SELWITZ S EH1 L W IH0 T S +SELWYN S EH1 L W IH0 N +SELZ S EH1 L Z +SELZER S EH1 L Z ER0 +SELZER'S S EH1 L Z ER0 Z +SEMA S IY1 M AH0 +SEMAN S IY1 M AH0 N +SEMANS S IY1 M AH0 N Z +SEMANTIC S IH0 M AE1 N T IH0 K +SEMANTICS S IH0 M AE1 N T IH0 K S +SEMATECH S EH1 M AH0 T EH2 K +SEMBER S EH1 M B ER0 +SEMBLANCE S EH1 M B L AH0 N S +SEMEGRAN S EH1 M AH0 G R AH0 N +SEMEL S EH1 M AH0 L +SEMELE S EH1 M AH0 L IY2 +SEMEN S IY1 M AH0 N +SEMENZA S EH0 M EH1 N Z AH0 +SEMERAD S EH1 M ER0 AE0 D +SEMESTER S AH0 M EH1 S T ER0 +SEMESTERS S AH0 M EH1 S T ER0 Z +SEMI S EH1 M IY0 +SEMI(1) S EH1 M AY0 +SEMI-COLON S EH1 M IY0 K OW1 L AH0 N +SEMI-COLON(1) S EH1 M AH0 K OW1 L AH0 N +SEMI-HEIGHT S EH1 M IY0 HH AY1 T +SEMI-HEIGHT(1) S EH1 M IH0 HH AY1 T +SEMI-HEIGHT(2) S EH1 M AY0 HH AY1 T +SEMI-HEIGHTS S EH1 M IY0 HH AY1 T S +SEMI-HEIGHTS(1) S EH1 M AY0 HH AY1 T S +SEMI-HEIGHTS(2) S EH1 M IH0 HH AY1 T S +SEMI-HUMAN S EH2 M IY0 HH Y UW1 M AH0 N +SEMIANNUAL S EH2 M IY0 AE1 N Y AH0 W AH0 L +SEMIANNUAL(1) S EH2 M AY0 AE1 N Y AH0 W AH0 L +SEMIANNUAL(2) S EH2 M AH0 AE1 N Y AH0 W AH0 L +SEMIANNUALLY S EH2 M IY0 AE1 N UW0 AH0 L IY0 +SEMIANNUALLY(1) S EH2 M AY0 AE1 N UW0 AH0 L IY0 +SEMIANNUALLY(2) S EH2 M IY0 AE1 N UW0 L IY0 +SEMIANNUALLY(3) S EH2 M AY0 AE1 N UW0 L IY0 +SEMIAUTOMATIC S EH2 M IY0 AO2 T AH0 M AE1 T IH0 K +SEMIAUTOMATIC(1) S EH2 M AY0 AO2 T AH0 M AE1 T IH0 K +SEMIAUTOMATIC(2) S EH2 M IH0 AO2 T AH0 M AE1 T IH0 K +SEMICIRCULAR S EH2 M IY0 S ER1 K Y AH0 L ER0 +SEMICIRCULAR(1) S EH2 M AY0 S ER1 K Y AH0 L ER0 +SEMICIRCULAR(2) S EH2 M AH0 S ER1 K Y AH0 L ER0 +SEMICLAD S EH1 M IY0 K L AE2 D +SEMICLAD(1) S EH1 M AY0 K L AE2 D +SEMICLAD(2) S EH1 M AH0 K L AE2 D +SEMICLASSICAL S EH2 M IY0 K L AE1 S IH0 K AH0 L +SEMICLASSICAL(1) S EH2 M IH0 K L AE1 S IH0 K AH0 L 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IY0 F AY1 N AH0 L +SEMIFINAL(1) S EH2 M IH0 F AY1 N AH0 L +SEMIFINAL(2) S EH2 M AY0 F AY1 N AH0 L +SEMIFINALIST S EH2 M IY0 F AY1 N AH0 L IH0 S T +SEMIFINALIST(1) S EH2 M IH0 F AY1 N AH0 L IH0 S T +SEMIFINALIST(2) S EH2 M AY0 F AY1 N AH0 L IH0 S T +SEMIFINALISTS S EH2 M IY0 F AY1 N AH0 L IH0 S T S +SEMIFINALISTS(1) S EH2 M IY0 F AY1 N AH0 L IH0 S +SEMIFINALISTS(2) S EH2 M AY0 F AY1 N AH0 L IH0 S T S +SEMIFINALISTS(3) S EH2 M AY0 F AY1 N AH0 L IH0 S +SEMIFINALS S EH2 M IY0 F AY1 N AH0 L Z +SEMIFINALS(1) S EH2 M IH0 F AY1 N AH0 L Z +SEMIFINALS(2) S EH2 M AY0 F AY1 N AH0 L Z +SEMIFINISH S EH2 M IY0 F IH1 N IH0 SH +SEMIFINISH(1) S EH2 M AY0 F IH1 N IH0 SH +SEMIFINISH(2) S EH2 M IH0 F IH1 N IH0 SH +SEMIFINISHED S EH2 M IY0 F IH1 N IH0 SH T +SEMIFINISHED(1) S EH2 M AY0 F IH1 N IH0 SH T +SEMIFINISHED(2) S EH2 M IH0 F IH1 N IH0 SH T +SEMIGLOSS S EH2 M IY0 G L AA1 S +SEMIGLOSS(1) S EH2 M IH0 G L AA1 S +SEMILEGENDARY S EH2 M IY0 L EH1 JH AH0 N D EH2 R IY0 +SEMILEGENDARY(1) S EH2 M IH0 L EH1 JH AH0 N D EH2 R IY0 +SEMINAL S EH1 M AH0 N AH0 L +SEMINAR S EH1 M AH0 N AA2 R +SEMINARA S EH2 M IH0 N AA1 R AH0 +SEMINARIAN S EH2 M AH0 N EH1 R IY0 AH0 N +SEMINARIANS S EH2 M AH0 N EH1 R IY0 AH0 N Z +SEMINARIES S EH1 M AH0 N EH2 R IY0 Z +SEMINARIO S EH2 M IH0 N EH1 R IY0 OW0 +SEMINARS S EH1 M AH0 N AA2 R Z +SEMINARY S EH1 M AH0 N EH2 R IY0 +SEMINOLE S EH1 M IH0 N OW2 L +SEMINOLES S EH1 M IH0 N OW2 L Z +SEMIONENKOV S EH2 M IY0 OW0 N EH1 NG K AA0 V +SEMIOTIC S EH2 M IY0 AA1 T IH0 K +SEMIOTICS S EH2 M IY0 AA1 T IH0 K S +SEMIPERMANENT S EH2 M IY0 P ER1 M AH0 N AH0 N T +SEMIPERMANENT(1) S EH2 M IH0 P ER1 M AH0 N AH0 N T +SEMIPERMANENT(2) S EH2 M AY0 P ER1 M AH0 N AH0 N T +SEMIPRECIOUS S EH2 M IY0 P R EH1 SH AH0 S +SEMIPRECIOUS(1) S EH2 M IH0 P R EH1 SH AH0 S +SEMIPRECIOUS(2) S EH2 M AY0 P R EH1 SH AH0 S +SEMIRA S EH0 M IH1 R AH0 +SEMIRELIGIOUS S EH2 M IY0 R IH0 L IH1 JH AH0 S +SEMIRELIGIOUS(1) S EH2 M IH0 R IH0 L IH1 JH AH0 S +SEMIRELIGIOUS(2) S EH2 M AY0 R IH0 L IH1 JH AH0 S +SEMIS S EH1 M AY0 Z +SEMISECRECY S EH2 M IY0 S IY1 K R AH0 S IY0 +SEMISECRECY(1) S EH2 M IH0 S IY1 K R AH0 S IY0 +SEMITE S EH1 M AY0 T +SEMITIC S AH0 M IH1 T IH0 K +SEMITISM S EH1 M IH0 T IH2 Z AH0 M +SEMITRAILER S EH2 M IY0 T R EY1 L ER0 +SEMITRAILER(1) S EH2 M IH0 T R EY1 L ER0 +SEMITROPICAL S EH2 M IY0 T R AA1 P IH0 K AH0 L +SEMITROPICAL(1) S EH2 M IH0 T R AA1 P IH0 K AH0 L +SEMITROPICAL(2) S EH2 M AY0 T R AA1 P IH0 K AH0 L +SEMLER S EH1 M L ER0 +SEMMEL S EH1 M AH0 L +SEMMENS S EH1 M AH0 N Z +SEMMES S EH1 M Z +SEMMLER S EH1 M L ER0 +SEMOLINA S EH2 M AH0 L IY1 N AH0 +SEMON S EH1 M AH0 N +SEMONES S EY0 M OW1 N EH0 S +SEMPLE S EH1 M P AH0 L +SEMRAD S EH1 M R AA0 D +SEMRAU S EH1 M R AW0 +SEMROW S EH1 M R OW0 +SEMTEX S EH1 M T EH0 K S +SEN S EH1 N +SENA S EH1 N AH0 +SENATE S EH1 N AH0 T +SENATE(1) S EH1 N IH0 T +SENATE'S S EH1 N IH0 T S +SENATOR S EH1 N AH0 T ER0 +SENATOR'S S EH1 N AH0 T ER0 Z +SENATORE S EH0 N AA0 T AO1 R IY0 +SENATORIAL S EH2 N AH0 T AO1 R IY0 AH0 L +SENATORS S EH1 N AH0 T ER0 Z 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EH1 N S EY2 +SENSELESS S EH1 N S L AH0 S +SENSENBRENNER S EH1 N S AH0 N B R EH2 N ER0 +SENSENEY S EH1 N S IH0 N IY0 +SENSENIG S EH1 N S IH0 N IH0 G +SENSES S EH1 N S IH0 Z +SENSIBILITIES S EH2 N S IH0 B IH1 L IH0 T IY0 Z +SENSIBILITY S EH2 N S IH0 B IH1 L IH0 T IY0 +SENSIBLE S EH1 N S AH0 B AH0 L +SENSIBLY S EH1 N S AH0 B L IY0 +SENSING S EH1 N S IH0 NG +SENSITIVE S EH1 N S AH0 T IH0 V +SENSITIVE(1) S EH1 N S IH0 T IH0 V +SENSITIVELY S EH1 N S IH0 T IH0 V L IY0 +SENSITIVENESS S EH1 N S AH0 T IH0 V N AH0 S +SENSITIVITIES S EH2 N S IH0 T IH1 V IH0 T IY0 Z +SENSITIVITY S EH2 N S IH0 T IH1 V IH0 T IY0 +SENSITIZE S EH1 N S AH0 T AY2 Z +SENSITIZED S EH1 N S AH0 T AY2 Z D +SENSKE S EH1 N S K +SENSOR S EH1 N S ER0 +SENSOR'S S EH1 N S ER0 Z +SENSORMATIC S EH2 N S ER0 M AE1 T IH0 K +SENSORS S EH1 N S ER0 Z +SENSORY S EH1 N S ER0 IY0 +SENSUAL S EH1 N SH AH0 W AH0 L +SENSUALITY S EH2 N SH UW2 AE1 L AH0 T IY2 +SENSUOUS S EH1 N SH AH0 W AH0 S +SENT S EH1 N T +SENTELL S EH1 N T AH0 L +SENTELLE S EH0 N T EH1 L +SENTENCE S EH1 N T AH0 N S +SENTENCED S EH1 N T AH0 N S T +SENTENCES S EH1 N T AH0 N S AH0 Z +SENTENCES(1) S EH1 N T AH0 N S IH0 Z +SENTENCING S EH1 N T AH0 N S IH0 NG +SENTER S EH1 N T ER0 +SENTERS S EH1 N T ER0 Z +SENTIMENT S EH1 N T AH0 M AH0 N T +SENTIMENT(1) S EH1 N AH0 M AH0 N T +SENTIMENTAL S EH2 N T AH0 M EH1 N T AH0 L +SENTIMENTAL(1) S EH2 N AH0 M EH1 N T AH0 L +SENTIMENTAL(2) S EH2 N T AH0 M EH1 N AH0 L +SENTIMENTAL(3) S EH2 N AH0 M EH1 N AH0 L +SENTIMENTALITY S EH2 N T AH0 M EH0 N T AE1 L IH0 T IY0 +SENTIMENTALITY(1) S EH2 N AH0 M EH0 N T AE1 L IH0 T IY0 +SENTIMENTS S EH1 N T AH0 M AH0 N T S +SENTIMENTS(1) S EH1 N AH0 M AH0 N T S +SENTINEL S EH1 N T AH0 N AH0 L +SENTINELS S EH1 N T AH0 N AH0 L Z +SENTMAN S EH1 N T M AH0 N +SENTRA S EH1 N T R AH0 +SENTRAS S EH1 N T R AH0 S +SENTRIES S EH1 N T R IY0 Z +SENTRY S EH1 N T R IY0 +SENTY S EH1 N T IY0 +SENTZ S EH1 N T S +SENZAKI S EY0 N Z AA1 K IY0 +SEO S IY1 OW0 +SEO(1) S EY1 OW0 +SEOUL S OW1 L +SEOUL'S S OW1 L Z +SEOW S IY1 OW0 +SEOW(1) S IY1 AW0 +SEOW'S S IY1 OW2 Z +SEP S EH1 P +SEP(1) EH1 S IY1 P IY1 +SEPARATE S EH1 P ER0 EY2 T +SEPARATE(1) S EH1 P ER0 IH0 T +SEPARATE(2) S EH1 P R AH0 T +SEPARATED S EH1 P ER0 EY2 T IH0 D +SEPARATELY S EH1 P ER0 AH0 T L IY0 +SEPARATELY(1) S EH1 P R AH0 T L IY0 +SEPARATENESS S EH1 P ER0 AH0 T N AH0 S +SEPARATES S EH1 P ER0 EY2 T S +SEPARATES(1) S EH1 P ER0 IH0 T S +SEPARATING S EH1 P ER0 EY2 T IH0 NG +SEPARATION S EH2 P ER0 EY1 SH AH0 N +SEPARATIONS S EH2 P ER0 EY1 SH AH0 N Z +SEPARATISM S EH1 P ER0 AH0 T IH2 Z AH0 M +SEPARATIST S EH1 P ER0 AH0 T IH0 S T +SEPARATISTS S EH1 P ER0 AH0 T IH0 S T S +SEPARATISTS(1) S EH1 P R AH0 T IH0 S T S +SEPARATOR S EH1 P AH0 R EY2 T ER0 +SEPARATORS S EH1 P AH0 R EY2 T ER0 Z +SEPE S IY1 P +SEPEDA S EY0 P EY1 D AH0 +SEPHARDIC S AH0 F AA1 R D IH0 K +SEPHARDIM S IH0 F AA1 R D IH0 M +SEPHARDIM(1) S EH0 F AA2 R D IY1 M +SEPHLON S EH1 F L AO0 N +SEPHLON'S S EH1 F L AO0 N Z +SEPIA S IY1 P IY0 AH0 +SEPICH S EH1 P IH0 CH +SEPIK S EH1 P IH0 K 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IY0 AH0 +SERIAL S IH1 R IY2 AH0 L +SERIALIZE S IH1 R IY2 AH0 L AY2 Z +SERIALIZED S IH1 R IY2 AH0 L AY2 Z D +SERIALS S IH1 R IY0 AH0 L Z +SERIES S IH1 R IY0 Z +SERIES' S IH1 R IY0 Z +SERILDA S ER0 IY1 L D AH0 +SERINO S ER0 IY1 N OW0 +SERIO S IY1 R IY0 OW0 +SERIOUS S IH1 R IY0 AH0 S +SERIOUSLY S IH1 R IY0 AH0 S L IY0 +SERIOUSNESS S IH1 R IY0 AH0 S N AH0 S +SERLE S ER1 AH0 L +SERLIN S ER1 L IH0 N +SERLING S ER1 L IH0 NG +SERLO S EH1 R L OW0 +SERMERSHEIM S ER1 M ER0 S HH AY0 M +SERMON S ER1 M AH0 N +SERMONS S ER1 M AH0 N Z +SERNA S EH1 R N AH0 +SEROKA S EH0 R OW1 K AH0 +SEROLOGICAL S EH0 R AH0 L AO1 JH IH0 K AH0 L +SEROLOGIST S EH0 R AA1 L AH0 JH IH0 S T +SEROLOGY S EH0 R AA1 L AH0 JH IY0 +SERONO S EH2 R AA1 N OW0 +SEROTA S ER0 OW1 T AH0 +SEROTONIN S ER0 AH0 T OW1 N IH0 N +SEROWSKI S ER0 AW1 S K IY0 +SERPA S EH1 R P AH0 +SERPAS S ER1 P AH0 Z +SERPE S ER1 P +SERPENT S ER1 P AH0 N T +SERPENT'S S ER1 P AH0 N T S +SERPENTINE S ER1 P AH0 N T AY2 N +SERPENTS S ER1 P AH0 N T S +SERPICO S ER0 P IY1 K OW0 +SERR S EH1 R +SERRA S EH1 R AH0 +SERRA'S S EH1 R AH0 Z +SERRANO S ER0 AA1 N OW0 +SERRANO(1) S ER0 AE1 N OW0 +SERRANO'S S ER0 AA1 N OW0 Z +SERRANO'S(1) S ER0 AE1 N OW0 Z +SERRANTO S ER0 AA1 N T OW0 +SERRAO S EH1 R AW0 +SERRATE S EH1 R EY2 T +SERRATED S EH1 R EY2 T IH0 D +SERRATO S ER0 AA1 T OW0 +SERRATORE S ER0 AA0 T AO1 R IY0 +SERRES S EH1 R EH0 S +SERRITELLA S EH2 R IH0 T EH1 L AH0 +SERTICH S ER1 T IH0 K +SERUM S IH1 R AH0 M +SERV S ER1 V +SERVAAS S ER1 V AA0 S +SERVAIS S ER0 V EY1 +SERVAM S ER1 V AH0 M +SERVAN S ER1 V AH0 N +SERVANT S ER1 V AH0 N T +SERVANTS S ER1 V AH0 N T S +SERVANTS' S ER1 V AH0 N T S +SERVE S ER1 V +SERVED S ER1 V D +SERVELLO S ER0 V EH1 L OW0 +SERVER S ER1 V ER0 +SERVERS S ER1 V ER0 Z +SERVES S ER1 V Z +SERVICE S ER1 V AH0 S +SERVICE(1) S ER1 V IH0 S +SERVICE'S S ER1 V IH0 S IH0 Z +SERVICEABLE S ER1 V AH0 S AH0 B AH0 L +SERVICED S ER1 V IH0 S T +SERVICEMAN S ER1 V AH0 S M AE2 N +SERVICEMASTER S ER1 V IH0 S M AE2 S T ER0 +SERVICEMEN S ER1 V AH0 S M EH0 N +SERVICEMEN'S S ER1 V IH0 S M EH0 N Z +SERVICER S ER1 V IH0 S ER0 +SERVICES S ER1 V AH0 S AH0 Z +SERVICES(1) S ER1 V IH0 S IH0 Z +SERVICES' S ER1 V IH0 S IH0 Z +SERVICES'(1) S ER1 V AH0 S AH0 Z +SERVICING S ER1 V IH0 S IH0 NG +SERVICO S ER1 V IH0 K OW2 +SERVIDIO S ER0 V IY1 D IY0 OW0 +SERVILE S ER1 V IH0 L +SERVILITY S ER1 V IH0 L AH0 T IY2 +SERVIN S ER1 V IH0 N +SERVING S ER1 V IH0 NG +SERVINGS S ER1 V IH0 NG Z +SERVIOU S ER1 V IY0 UW0 +SERVIS S ER1 V IH0 S +SERVISS S ER1 V IH0 S +SERVITUDE S ER1 V AH0 T UW2 D +SERVO S ER1 V OW0 +SESAME S EH1 S AH0 M IY0 +SESDAQ S EH1 S D AE0 K +SESE S IY1 S IY0 +SESHADRI S EH0 SH AA1 D R IY0 +SESIT S EH1 Z IH0 T +SESKAR S EH1 S K AA2 R +SESKAR'S S EH1 S K AA2 R Z +SESLER S EH1 S AH0 L ER0 +SESLER(1) S EH1 S L ER0 +SESNO S EH1 S N OW2 +SESNO'S S EH1 S N OW2 Z +SESSA S EH1 S AH0 +SESSION S EH1 SH AH0 N +SESSION'S S EH1 SH AH0 N Z +SESSIONS S EH1 SH AH0 N Z +SESSIONS' S EH1 SH AH0 N Z +SESSLER S EH1 S L ER0 +SESSOMS S EH1 S AH0 M Z +SESSUMS S EH1 S AH0 M Z +SESTAK S EH1 S T AH0 K +SESTANOVICH S EH0 S T AE1 N AH0 V IH0 CH +SESTITO S EH0 S T IY1 T OW0 +SET S EH1 T +SET-UP S EH1 T AH2 P +SET-UPS S EH1 T AH2 P S +SETARO S EH0 T AA1 R OW0 +SETBACK S EH1 T B AE2 K +SETBACKS S EH1 T B AE2 K S +SETH S EH1 TH +SETH'S S EH1 TH S +SETHER S EH1 DH ER0 +SETHI S EH1 TH IY0 +SETHNESS S EH1 TH N AH0 S +SETHURAMAN S EH2 TH ER0 AA1 M AA0 N +SETI S EH1 T IY2 +SETLIFF S EH1 T L IH0 F +SETO S EH1 T OW0 +SETON S IY1 T AH0 N +SETS S EH1 T S +SETSER S EH1 T S ER0 +SETTANNI S EH0 T AA1 N IY0 +SETTE S EH1 T +SETTER S EH1 T ER0 +SETTERLUND S EH1 T ER0 L AH0 N D +SETTERS S EH1 T ER0 Z +SETTING S EH1 T IH0 NG +SETTINGS S EH1 T IH0 NG Z +SETTLE S EH1 T AH0 L +SETTLED S EH1 T AH0 L D +SETTLEMENT S EH1 T AH0 L M AH0 N T +SETTLEMENT'S S EH1 T AH0 L M AH0 N T S +SETTLEMENTS S EH1 T AH0 L M AH0 N T S +SETTLEMIRE S EH1 T AH0 L M AY2 R +SETTLEMYRE S EH1 T AH0 L M AY2 R +SETTLER S EH1 T AH0 L ER0 +SETTLER(1) S EH1 T L ER0 +SETTLERS S EH1 T L ER0 Z +SETTLERS(1) S EH1 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SH AE1 D B UH2 SH +SHADD SH AE1 D +SHADDEN SH AE1 D AH0 N +SHADDIX SH AE1 D IH0 K S +SHADDOCK SH AE1 D AH0 K +SHADDUCK SH AE1 D AH0 K +SHADE SH EY1 D +SHADED SH EY1 D IH0 D +SHADEGG SH AE1 D EH0 G +SHADEL SH AE1 D AH0 L +SHADER SH EY1 D ER0 +SHADES SH EY1 D Z +SHADID SH AE1 D IH0 D +SHADING SH EY1 D IH0 NG +SHADINGS SH EY1 D IH0 NG Z +SHADLE SH EY1 D AH0 L +SHADLEY SH AE1 D L IY0 +SHADOAN SH AE1 D OW0 N +SHADOW SH AE1 D OW2 +SHADOWED SH AE1 D OW0 D +SHADOWENS SH AE1 D OW0 AH0 N Z +SHADOWING SH AE1 D OW0 IH0 NG +SHADOWLAND SH AE1 D OW0 L AE2 N D +SHADOWLANDS SH AE1 D OW0 L AE2 N D Z +SHADOWS SH AE1 D OW2 Z +SHADOWY SH AE1 D OW0 IY0 +SHADRICK SH AE1 D R IH0 K +SHADUR SH AE1 D ER0 +SHADWELL SH AE1 D W EH0 L +SHADWICK SH AE1 D W IH0 K +SHADY SH EY1 D IY0 +SHAEFER SH EY1 F ER0 +SHAEFFER SH EH1 F ER0 +SHAER SH EY1 ER0 +SHAFER SH EY1 F ER0 +SHAFF SH AE1 F +SHAFFER SH EY1 F ER0 +SHAFFNER SH AE1 F N ER0 +SHAFRAN SH AE1 F R AH0 N +SHAFT SH AE1 F T +SHAFTED SH AE1 F T IH0 D +SHAFTING SH AE1 F T IH0 NG +SHAFTS SH AE1 F T S +SHAG SH AE1 G +SHAGGING SH AE1 G IH0 NG +SHAGGY SH AE1 G IY0 +SHAGS SH AE1 G Z +SHAH SH AA1 +SHAH'S SH AA1 Z +SHAHAN SH AE1 HH AH0 N +SHAHAR SH AH0 HH AA1 R +SHAHAR'S SH AH0 HH AA1 R Z +SHAHEED SH AH0 HH IY1 D +SHAHEEN SH AH0 HH IY1 N +SHAHIAN SH AH0 HH IY1 AH0 N +SHAHIDI SH AH0 HH IY1 D IY0 +SHAHIN SH AE1 HH IH0 N +SHAHINIAN SH AH0 HH IH1 N IY0 AH0 N +SHAHROKH SH AA1 R AA0 K +SHAHRZAD SH AA2 R Z AE1 D +SHAI SH AY1 +SHAIK SH EY1 K +SHAIKEN SH EY1 K AH0 N +SHAIKH SH EY1 K +SHAIN SH EY1 N +SHAINE SH EY1 N +SHAKA SH AA1 K AH0 +SHAKE SH EY1 K +SHAKEDOWN SH EY1 K D AW2 N +SHAKEDOWNS SH EY1 K D AW2 N Z +SHAKEN SH EY1 K AH0 N +SHAKEOUT SH EY1 K AW2 T +SHAKER SH EY1 K ER0 +SHAKERS SH EY1 K ER0 Z +SHAKES SH EY1 K S +SHAKESPEARE SH EY1 K S P IY2 R +SHAKESPEARE'S SH EY1 K S P IY2 R Z +SHAKESPEAREAN SH EY2 K S P IH1 R IY0 AH0 N +SHAKEUP SH EY1 K AH2 P +SHAKEUPS SH EY1 K AH2 P S +SHAKIER SH EY1 K IY0 ER0 +SHAKIEST SH EY1 K IY0 IH0 S T +SHAKINESS SH EY1 K IY0 N AH0 S +SHAKING SH EY1 K IH0 NG +SHAKIR SH AE1 K IH0 R +SHAKIRA SH AE2 K IY1 R AH0 +SHAKLEE SH AE1 K L IY0 +SHAKUNAGA SH AA2 K UW0 N AA1 G AH0 +SHAKUR SH AA1 K ER0 +SHAKY SH EY1 K IY0 +SHALALA SH AH0 L EY1 L AH0 +SHALALA'S SH AH0 L EY1 L AH0 Z +SHALE SH EY1 L +SHALER SH EY1 L ER0 +SHALES SH EY1 L Z +SHALEV SH AA1 L EH2 V +SHALI SH AE1 L IY0 +SHALIKASHVILI SH AE2 L IY0 K AA0 SH V IY1 L IY0 +SHALIKASHVILI'S SH AE2 L IY0 K AA0 SH V IY1 L IY0 Z +SHALL SH AE1 L +SHALL'S SH AE1 L Z +SHALLCROSS SH AE1 L K R AA2 S +SHALLENBERGER SH AO1 L AH0 N B ER0 G ER0 +SHALLOW SH AE1 L OW0 +SHALLOWER SH AE1 L OW0 ER0 +SHALLOWNESS SH AE1 L OW0 N AH0 S +SHALNEV SH AA1 L N EH0 V +SHALNEV(1) SH AA1 L N EH0 F +SHALOM SH AH0 L OW1 M +SHALT SH AE1 L T +SHAM SH AE1 M +SHAMALIA SH AH0 M AA1 L Y AH0 +SHAMALIA(1) SH AH0 M EY1 L Y AH0 +SHAMAN SH EY1 M AH0 N +SHAMANISM SH EY1 M AH0 N IH2 Z M +SHAMANISTS SH EY1 M AH0 N IH2 S T S +SHAMANS SH EY1 M AH0 N Z +SHAMAS SH AE1 M AH0 S +SHAMBAUGH SH AE1 M B AO2 +SHAMBERGER SH AE1 M B ER0 G ER0 +SHAMBLE SH AE1 M B AH0 L +SHAMBLES SH AE1 M B AH0 L Z +SHAMBLEY SH AE1 M B L IY0 +SHAMBLIN SH AE1 M B L IH0 N +SHAMBO SH AE1 M B OW0 +SHAMBURG SH AE1 M B ER0 G +SHAMBURGER SH AE1 M B ER0 G ER0 +SHAME SH EY1 M +SHAMED SH EY1 M D +SHAMEFUL SH EY1 M F AH0 L +SHAMEL SH AE1 M AH0 L +SHAMELESS SH EY1 M L AH0 S +SHAMELESSLY SH EY1 M L AH0 S L IY0 +SHAMELLE SH AH0 M EH1 L +SHAMES SH EY1 M Z +SHAMING SH EY1 M IH0 NG +SHAMIR SH AH0 M IH1 R +SHAMIR'S SH AH0 M IH1 R Z +SHAMMOND SH AE1 M AH0 N D +SHAMP SH AE1 M P +SHAMPINE SH AE1 M P AY2 N +SHAMPOO SH AE0 M P UW1 +SHAMPOOED SH AE0 M P UW1 D +SHAMPOOS SH AE0 M P UW1 Z +SHAMROCK SH AE1 M R AA2 K +SHAMROCK'S SH AE1 M R AA2 K S +SHAMU SH AA0 M UW1 +SHAMUS SH EY1 M AH0 S +SHAN SH AE1 N +SHANA SH AE1 N AH0 +SHANA(1) SH EY1 N AH0 +SHANAFELT SH AE1 N AH0 F EH2 L T +SHANAHAN SH AE1 N AH0 HH AE0 N +SHANANSKY SH AH0 N AE1 N S K IY0 +SHAND SH AE1 N D +SHANDLING SH AE1 N D L IH0 NG +SHANDONG SH AA2 N D OW1 NG +SHANDS SH AE1 N D Z +SHANDWICK SH AE1 N D W IH2 K +SHANDWICK'S SH AE1 N D W IH2 K S +SHANDY SH AE1 N D IY0 +SHANE SH EY1 N +SHANER SH EY1 N ER0 +SHANEYFELT SH AE1 N IY0 F EH0 L T +SHANGHAI SH AE1 NG HH AY1 +SHANGHAI'S SH AE1 NG HH AY1 Z +SHANGKUN SH AE1 NG K AH0 N +SHANGRI SH AE1 NG G R IY0 +SHANHOLTZ SH AE1 N HH OW2 L T S +SHANHOLTZER SH AE1 N HH OW0 L T Z ER0 +SHANK SH AE1 NG K +SHANKAR SH AE1 NG K AA0 R +SHANKEL SH AE1 NG K AH0 L +SHANKEN SH AE1 NG K AH0 N +SHANKER SH AE1 NG K ER0 +SHANKLAND SH AE1 NG K L AH0 N D +SHANKLE SH AE1 NG K AH0 L +SHANKLES SH AE1 NG K AH0 L Z +SHANKLIN SH AE1 NG K L IH0 N +SHANKMAN SH AE1 NG K M AH0 N +SHANKS SH AE1 NG K S +SHANLEY SH AE1 N L IY0 +SHANNA SH AE1 N AH0 +SHANNAHAN SH AE1 N AH0 HH AE0 N +SHANNON SH AE1 N AH0 N +SHANNON'S SH AE1 N AH0 N Z +SHANSEV SH AE1 N S EH0 V +SHANSEV(1) SH AE1 N S EH0 F +SHANT SH AA1 N T +SHANTI SH AE1 N T IY0 +SHANTIES SH AE1 N T IY0 Z +SHANTY SH AE1 N T IY0 +SHANTYTOWN SH AE1 N T IY0 T AW2 N +SHANTYTOWNS SH AE1 N T IY0 T AW2 N Z +SHANTZ SH AE1 N T S +SHAO SH AW1 +SHAOLIN SH AA1 OW0 L IH2 N +SHAP SH AE1 P +SHAPE SH EY1 P +SHAPED SH EY1 P T +SHAPELESS SH EY1 P L AH0 S +SHAPELY SH EY1 P L IY0 +SHAPERO SH AH0 P IH1 R OW0 +SHAPES SH EY1 P S +SHAPING SH EY1 P IH0 NG +SHAPIRA SH AH0 P IH1 R AH0 +SHAPIRO SH AH0 P IH1 R OW0 +SHAPIRO'S SH AH0 P IH1 R OW0 Z +SHAPIROS SH AH0 P IH1 R OW0 Z +SHAPLEY SH AE1 P L IY0 +SHAPP SH AE1 P +SHAPPELL SH AE1 P AH0 L +SHAQ SH AE1 K +SHAQUILLE SH AH0 K IY1 L +SHARA SH AA1 R AH0 +SHARAA SH AA1 R AH0 +SHARANSKY SH ER0 AE1 N S K IY0 +SHARAR SH ER0 AA1 R +SHARBER SH AA1 R B ER0 +SHARBONO SH AA0 R B OW1 N OW0 +SHARD SH AA1 R D +SHARDS SH AA1 R D Z +SHARE SH EH1 R +SHARE'S SH EH1 R Z +SHARECROP SH EH1 R K R AA2 P +SHARECROPPER SH EH1 R K R AA2 P ER0 +SHARECROPPERS SH EH1 R K R AA2 P ER0 Z +SHARED SH EH1 R D +SHAREHOLDER SH EH1 R HH OW2 L D ER0 +SHAREHOLDER'S SH EH1 R HH OW2 L D ER0 Z +SHAREHOLDERS SH EH1 R HH OW2 L D ER0 Z +SHAREHOLDERS' SH EH1 R HH OW2 L D ER0 Z +SHAREHOLDING SH EH1 R HH OW2 L D IH0 NG +SHAREHOLDINGS SH EH1 R HH OW2 L D IH0 NG Z +SHARELL SH AH0 R EH1 L +SHAREOWNER SH EH1 R OW2 N ER0 +SHAREOWNERS SH EH1 R OW2 N ER0 Z +SHARER SH EH1 R ER0 +SHARES SH EH1 R Z +SHARES' SH EH1 R Z +SHAREWARE SH EH1 R W EH2 R +SHARF SH AA1 R F +SHARFMAN SH AA1 R F M AH0 N +SHARI SH AA1 R IY0 +SHARIA SH AA1 R IY0 AH0 +SHARIF SH ER0 IY1 F +SHARING SH EH1 R IH0 NG +SHARK SH AA1 R K +SHARKEY SH AA1 R K IY0 +SHARKING SH AA1 R K IH0 NG +SHARKLIKE SH AA1 R K L AY2 K +SHARKS SH AA1 R K S +SHARLA SH AA1 R L AH0 +SHARLEEN SH AA0 R L IY1 N +SHARLENE SH AA1 R L IY2 N +SHARLINE SH AA1 R L AY2 N +SHARLOW SH AA1 R L OW0 +SHARM SH AA1 R M +SHARMA SH AA1 R M AH0 +SHARMA'S SH AA1 R M AH0 Z +SHARMAN SH AA1 R M AH0 N +SHARON SH AE1 R AH0 N +SHARON(1) SH EH1 R AH0 N +SHARON(2) SH AH0 R OW1 N +SHARON'S SH EH1 R AH0 N Z +SHARON'S(1) SH AE1 R AH0 N Z +SHARON'S(2) SH AH0 R OW1 N Z +SHARP SH AA1 R P +SHARP'S SH AA1 R P S +SHARP-SIGN SH AA1 R P S AY1 N +SHARPE SH AA1 R P +SHARPEN SH AA1 R P AH0 N +SHARPENED SH AA1 R P AH0 N D +SHARPENING SH AA1 R P AH0 N IH0 NG +SHARPENING(1) SH AA1 R P N IH0 NG +SHARPENS SH AA1 R P AH0 N Z +SHARPER SH AA1 R P ER0 +SHARPEST SH AA1 R P AH0 S T +SHARPEVILLE SH AA1 R P AH0 V IH2 L +SHARPIE SH AA1 R P IY0 +SHARPIES SH AA1 R P IY0 Z +SHARPLES SH AA1 R P AH0 L Z +SHARPLESS SH AA1 R P L AH0 S +SHARPLEY SH AA1 R P L IY0 +SHARPLY SH AA1 R P L IY0 +SHARPNACK SH AA1 R P N AH0 K +SHARPNESS SH AA1 R P N AH0 S +SHARPS SH AA1 R P S +SHARPSHOOTER SH AA1 R P SH UW0 T ER0 +SHARPSHOOTER(1) SH AA1 R P SH UW2 T ER0 +SHARPSHOOTERS SH AA1 R P SH UW0 T ER0 Z +SHARPTON SH AA1 R P T AH0 N +SHARPY SH AA1 R P IY0 +SHARPY'S SH AA1 R P IY0 Z +SHARRAR SH ER0 AA1 R +SHARRER SH AA1 R ER0 +SHARRETT SH AE1 R IH0 T +SHARROCK SH AE1 R AH0 K +SHARRON SH AE1 R AH0 N +SHARROW SH AE1 R OW0 +SHARRY SH AA1 R IY0 +SHARTZER SH AA1 R T Z ER0 +SHARUM SH AA2 R AH1 M +SHARYL SH AA1 R AH0 L +SHAS SH AA1 S +SHASHLIK SH AA1 SH L IH0 K +SHASHOUA SH AH0 SH UW1 AH0 +SHASTA SH AE1 S T AH0 +SHASTA'S SH AE1 S T AH0 Z +SHASTEEN SH AE0 S T IY1 N +SHATKIN SH AE1 T K IH0 N +SHATLEY SH AE1 T L IY0 +SHATMAN SH AE1 T M AH0 N +SHATNER SH AE1 T N ER0 +SHATROV SH AE1 T R AA0 V +SHATT SH AE1 T +SHATTER SH AE1 T ER0 +SHATTERED SH AE1 T ER0 D +SHATTERING SH AE1 T ER0 IH0 NG +SHATTERPROOF SH AE1 T ER0 P R UW2 F +SHATTERS SH AE1 T ER0 Z +SHATTUCK SH AE1 T AH0 K +SHATZ SH AE1 T S +SHATZ(1) SH AA1 T S +SHATZER SH EY1 T Z ER0 +SHAUB SH AO1 B +SHAUGER SH AW1 G ER0 +SHAUGHNESSY SH AO1 N IH0 S IY0 +SHAUL SH AO1 L +SHAULIS SH AW1 L IH0 S +SHAULL SH AO1 L +SHAUN SH AO1 N +SHAUNA SH AO1 N AH0 +SHAVE SH EY1 V +SHAVED SH EY1 V D +SHAVELSON SH EY1 V AH0 L S IH0 N +SHAVELSON(1) SH AE1 V AH0 L S IH0 N +SHAVEN SH EY1 V AH0 N +SHAVER SH EY1 V ER0 +SHAVERS SH EY1 V ER0 Z +SHAVES SH EY1 V Z +SHAVING SH EY1 V IH0 NG +SHAVINGS SH EY1 V IH0 NG Z +SHAVORD SH AH0 V AO1 R D +SHAW SH AO1 +SHAW'S SH AO1 Z +SHAWCROSS SH AO1 K R AO2 S +SHAWGO SH AO1 G OW2 +SHAWHAN SH AE1 W AH0 N +SHAWINIGAN SH AH0 W IH1 N IH0 G AH0 N +SHAWL SH AO1 L +SHAWLER SH AO1 L ER0 +SHAWLEY SH AO1 L IY0 +SHAWLS SH AO1 L Z +SHAWMUT SH AO1 M AH0 T +SHAWMUT'S SH AO1 M AH0 T S +SHAWN SH AO1 N +SHAWN'S SH AO1 N Z +SHAWNA SH AO1 N AH0 +SHAWNEE SH AO1 N IY0 +SHAWNUT SH AO1 N AH0 T +SHAWSHANK SH AO1 SH AE2 N K +SHAWVER SH AO1 V ER0 +SHAY SH EY1 +SHAYKIN SH EY1 K IH0 N +SHAYKIN'S SH EY1 K IH0 N Z +SHAYNE SH EY1 N +SHAYS SH EY1 Z +SHCHARANSKY SH ER0 AE1 N S K IY0 +SHCHEDRIN SH EH1 D R IH0 N +SHCHERBITSKY SH ER0 B IH1 T S K IY0 +SHE SH IY1 +SHE'D SH IY1 D +SHE'LL SH IY1 L +SHE'S SH IY1 Z +SHEA SH EY1 +SHEA'S SH EY1 Z +SHEAD S HH EH1 D +SHEAF SH IY1 F +SHEAFFER SH IY1 F ER0 +SHEAHAN SH IY1 AH0 N +SHEALEY SH IY1 L IY0 +SHEALY SH IY1 L IY0 +SHEAN SH IY1 N +SHEAR SH IH1 R +SHEAR'S SH IY1 R Z +SHEARD SH IH1 R D +SHEARED SH IH1 R D +SHEARER SH IH1 R ER0 +SHEARIN SH IH1 R IH0 N +SHEARING SH IH1 R IH0 NG +SHEARMAN SH IY1 R M AH0 N +SHEARN SH IH1 R N +SHEARON SH IH1 R AH0 N +SHEAROUSE SH IH1 R AW0 S +SHEARS SH IY1 R Z +SHEARSON SH IH1 R S AH0 N +SHEARSON'S SH IH1 R S AH0 N Z +SHEATH SH IY1 TH +SHEATH-KNIFE SH IY1 TH N AY2 F +SHEATHBILL SH IY1 TH B IH0 L +SHEATHBILLS SH IY1 TH B IH0 L Z +SHEATHE SH IY1 DH +SHEATHED SH IY1 DH D +SHEATHING SH IY1 DH IH0 NG +SHEATS SH IY1 T S +SHEAVES SH IY1 V Z +SHEBA SH IY1 B AH0 +SHEBEK SH EH1 B AH0 K +SHEBOYGAN SH AH0 B OY1 G AH0 N +SHECK SH EH1 K +SHECK'S SH EH1 K S +SHECKLER SH EH1 K L ER0 +SHED SH EH1 D +SHEDD SH EH1 D +SHEDDEN SH EH1 D AH0 N +SHEDDING SH EH1 D IH0 NG +SHEDLOCK SH EH1 D L AA2 K +SHEDRICK SH EH1 D R IH0 K +SHEDS SH EH1 D Z +SHEEDER SH IY1 D ER0 +SHEEDY SH IY1 D IY0 +SHEEHAN SH IY1 AH0 N +SHEEHAN(1) SH IY1 HH AH0 N +SHEEHAN'S SH IY1 AH0 N Z +SHEEHAN'S(1) SH IY1 HH AH0 N Z +SHEEHY SH IY1 HH IY0 +SHEEHY(1) SH IY1 IY0 +SHEEK SH IY1 K +SHEEKS SH IY1 K S +SHEELA SH IY1 L AH0 +SHEELAH SH IY1 L AH0 +SHEELEN SH IY1 L AH0 N +SHEELER SH IY1 L ER0 +SHEELEY SH IY1 L IY0 +SHEELY SH IY1 L IY0 +SHEEN SH IY1 N +SHEEN'S SH IY1 N Z +SHEENA SH IY1 N AH0 +SHEENS SH IY1 N Z +SHEEP SH IY1 P +SHEEP'S SH IY1 P S +SHEEPISH SH IY1 P IH0 SH +SHEEPISHLY SH IY1 P IH0 SH L IY0 +SHEEPS SH IY1 P S +SHEEPSKIN SH IY1 P S K IH2 N +SHEER SH IH1 R +SHEERAN SH IH1 R AH0 N +SHEERER SH IY1 R ER0 +SHEERIN SH IH1 R IH0 N +SHEESH SH IY1 SH +SHEESLEY SH IY1 Z L IY0 +SHEET SH IY1 T +SHEETING SH IY1 T IH0 NG +SHEETS SH IY1 T S +SHEETZ SH IY1 T S +SHEFF SH EH1 F +SHEFFER SH EH1 F ER0 +SHEFFEY SH EH1 F IY0 +SHEFFIELD SH EH1 F IY0 L D +SHEFFLER SH EH1 F L ER0 +SHEFTEL SH EH2 F T EH1 L +SHEFTEL'S SH EH2 F T EH1 L Z +SHEGOG SH EH1 G AA0 G +SHEHAN SH EH1 HH AH0 N +SHEHANE SH EH1 HH AH0 N +SHEHORN SH EH1 HH ER0 N +SHEIK SH IY1 K +SHEIK'S SH IY1 K S +SHEIKDOM SH IY1 K D AH0 M +SHEIKDOMS SH IY1 K D AH0 M Z +SHEIKH SH IY1 K +SHEIKS SH IY1 K S +SHEIL SH AY1 L +SHEILA SH IY1 L AH0 +SHEILA'S SH IY1 L AH0 Z +SHEILAH SH IY1 L AH0 +SHEILDS SH AY1 L D Z +SHEILS SH AY1 L Z +SHEIN SH AY1 N +SHEINBERG SH AY1 N B ER0 G +SHEK SH EH1 K +SHEK'S SH EH1 K S +SHEKEL SH EH1 K AH0 L +SHEKELS SH EH1 K AH0 L Z +SHELBURNE SH EH1 L B ER0 N +SHELBY SH EH1 L B IY0 +SHELBY'S SH EH1 L B IY0 Z +SHELBYVILLE SH EH1 L B IY0 V IH2 L +SHELDAHL SH EH1 L D AA2 L +SHELDEN SH EH1 L D AH0 N +SHELDON SH EH1 L D AH0 N +SHELEV SH EH1 L IH0 V +SHELEY SH IY1 L IY0 +SHELF SH EH1 L F +SHELHAH SH EH1 L HH AH0 +SHELHAMER SH EH1 L HH AH0 M ER0 +SHELIA SH IH1 L Y AH0 +SHELINE SH EH1 L AY0 N +SHELL SH EH1 L +SHELL'S SH EH1 L Z +SHELLABARGER SH EH1 L AH0 B AA2 R G ER0 +SHELLAC SH EH1 L AE2 K +SHELLACK SH EH2 L AE1 K +SHELLACKED SH EH2 L AE1 K D +SHELLACKING SH EH2 L AE1 K IH0 NG +SHELLED SH EH1 L D +SHELLENBARGER SH EH1 L IH0 N B AA0 R G ER0 +SHELLENBERGER SH EH1 L AH0 N B ER0 G ER0 +SHELLER SH EH1 L ER0 +SHELLEY SH EH1 L IY0 +SHELLEY'S SH EH1 L IY0 Z +SHELLFISH SH EH1 L F IH2 SH +SHELLHAMMER SH EH1 L HH AE2 M ER0 +SHELLHORN SH EH1 L HH ER0 N +SHELLING SH EH1 L IH0 NG +SHELLINGS SH EH1 L IH0 NG Z +SHELLITO SH EY0 L IY1 T OW0 +SHELLMAN SH EH1 L M AH0 N +SHELLS SH EH1 L Z +SHELLSHOCK SH EH1 L SH AA2 K +SHELLSHOCKED SH EH1 L SH AA2 K T +SHELLY SH EH1 L IY0 +SHELMAN SH EH1 L M AH0 N +SHELNUTT SH EH1 L N AH0 T +SHELOR SH EH1 L ER0 +SHELP SH EH1 L P +SHELSTAD SH EH1 L S T AH0 D +SHELTER SH EH1 L T ER0 +SHELTERED SH EH1 L T ER0 D +SHELTERING SH EH1 L T ER0 IH0 NG +SHELTERS SH EH1 L T ER0 Z +SHELTON SH EH1 L T AH0 N +SHELTON'S SH EH1 L T AH0 N Z +SHELVE SH EH1 L V +SHELVED SH EH1 L V D +SHELVES SH EH1 L V Z +SHELVING SH EH1 L V IH0 NG +SHEMA SH IH0 M AH1 +SHEMANSKI SH IH0 M AE1 N S K IY0 +SHEMONA SH IH0 M OW1 N AH0 +SHEMWELL SH EH1 M W EH2 L +SHEN SH EH1 N +SHENA SH IY1 N AH0 +SHENANDOAH SH EH2 N AH0 N D OW1 AH0 +SHENANIGAN SH AH0 N AE1 N IH0 G AH0 N +SHENANIGANS SH AH0 N AE1 N IH0 G AH0 N Z +SHENBERGER SH EH1 N B ER0 G ER0 +SHENEFIELD SH EH1 N IH0 F IY2 L D +SHENEMAN SH IY1 N M AH0 N +SHENG SH EH1 NG +SHENG-FEN SH EH1 NG F EH1 N +SHENICE SH AH0 N IY1 S +SHENK SH EH1 NG K +SHENKER SH EH1 NG K ER0 +SHENKMAN SH EH1 NG K M AH0 N +SHENTON SH EH1 N T AH0 N +SHENYANG SH EH0 N Y AE1 NG +SHENZHEN SH EH1 N ZH EH2 N +SHEP SH EH1 P +SHEPARD SH EH1 P ER0 D +SHEPARD'S SH EH1 P ER0 D Z +SHEPARDSON SH EH1 P ER0 D S AH0 N +SHEPERD SH EH1 P ER0 D +SHEPHARD SH EH1 P ER0 D +SHEPHEARD SH EH1 P ER0 D +SHEPHERD SH EH1 P ER0 D +SHEPHERD'S SH EH1 P ER0 D Z +SHEPHERDED SH EH1 P ER0 D IH0 D +SHEPHERDING SH EH1 P ER0 D IH0 NG +SHEPHERDS SH EH1 P ER0 D Z +SHEPLER SH EH1 P L ER0 +SHEPLEY SH EH1 P L IY0 +SHEPP SH EH1 P +SHEPPARD SH EH1 P ER0 D +SHEPPARD'S SH EH1 P ER0 D Z +SHEPPARDS SH EH1 P ER0 D Z +SHEPPER SH EH1 P ER0 +SHEPPERD SH EH1 P ER0 D +SHEPPERSON SH EH1 P ER0 S AH0 N +SHEPPY SH EH1 P IY0 +SHER SH ER1 +SHERAK SH EH1 R AE0 K +SHERARD SH EH1 R ER0 D +SHERATON SH EH1 R AH0 T AH0 N +SHERATON'S SH EH1 R AH0 T AH0 N Z +SHERBERT SH ER1 B ER0 T +SHERBET SH ER1 B AH0 T +SHERBONDY SH ER0 B AA1 N D IY0 +SHERBORNE SH ER1 B ER0 N +SHERBOURN SH ER0 B UH1 R N +SHERBOURNE SH ER0 B UH1 R N +SHERBURN SH ER1 B ER0 N +SHERBURNE SH ER1 B ER0 N +SHERE SH IH1 R +SHEREE SH ER0 IY1 +SHERER SH IH1 R ER0 +SHERFEY SH ER1 F IY0 +SHERFIELD SH ER1 F IY0 L D +SHERI SH EH1 R IY0 +SHERICK SH EH1 R IH0 K +SHERIDAN SH EH1 R IH0 D AH0 N +SHERIFF SH EH1 R AH0 F +SHERIFF(1) SH EH1 R IH0 F +SHERIFF'S SH EH1 R AH0 F S +SHERIFF'S(1) SH EH1 R IH0 F S +SHERIFFS SH EH1 R AH0 F S +SHERIN SH EH1 R IH0 N +SHERK SH ER1 K +SHERLEY SH ER1 L IY0 +SHERLIN SH ER1 L IH0 N +SHERLOCK SH ER1 L AA2 K +SHERLOCK'S SH ER1 L AA2 K S +SHERLUND SH ER1 L AH0 N D +SHERMAN SH ER1 M AH0 N +SHERMAN'S SH ER1 M AH0 N Z +SHERMER SH ER1 M ER0 +SHERNOFF SH ER1 N AO2 F +SHEROD SH EH1 R AH0 D +SHERR SH EH1 R +SHERR'S SH EH1 R Z +SHERRARD SH EH1 R ER0 D +SHERRELL SH EH1 R AH0 L +SHERRER SH EH1 R ER0 +SHERRGOLD SH EH1 R G OW2 L D +SHERRI SH EH1 R IY0 +SHERRI'S SH EH1 R IY0 Z +SHERRICK SH EH1 R IH0 K +SHERRIE SH EH1 R IY0 +SHERRIFF SH EH1 R IH0 F +SHERRILL SH EH1 R IH0 L +SHERRIN SH EH1 R IH0 N +SHERRIT SH EH1 R IH0 T +SHERRITT SH EH1 R IH0 T +SHERROD SH EH1 R AH0 D +SHERRON SH EH1 R AH0 N +SHERROW SH EH1 R OW0 +SHERRY SH EH1 R IY0 +SHERRY'S SH EH1 R IY0 Z +SHERTZER SH ER1 T Z ER0 +SHERVA SH ER1 V AH0 +SHERWIN SH ER1 W IH0 N +SHERWOOD SH ER1 W UH2 D +SHERWOOD'S SH ER1 W UH2 D Z +SHERYL SH EH1 R AH0 L +SHESHUNOFF SH EH1 SH UW0 N AO0 F +SHETH SH EH1 TH +SHETLAND SH EH1 T L AH0 N D +SHETLER SH EH1 T L ER0 +SHETLEY SH EH1 T L IY0 +SHETTER SH EH1 T ER0 +SHETTERLY SH EH1 T ER0 L IY0 +SHEVARDNADZE SH EH2 V ER0 D N AA1 D Z IY0 +SHEVARDNADZE'S SH EH2 V ER0 D N AA1 D Z IY0 Z +SHEVLIN SH EH1 V L IH0 N +SHEVTL SH EH1 V T IH0 L +SHEW SH UW1 +SHEWARD SH UW1 ER0 D +SHEWCHUK SH EH1 CH AH0 K +SHEWELL SH EH1 W EH0 L +SHEWMAKE SH UW1 M EY2 K +SHEWMAKER SH UW1 M EY0 K ER0 +SHI SH IY1 +SHIA SH IY1 AH0 +SHIAH SH IY1 AH0 +SHIAS SH IY1 AH0 Z +SHIBANNA SH IH0 B AE1 N AH0 +SHIBATA SH IY0 B AA1 T AH0 +SHIBBOLETH SH IH1 B AH0 L EH2 TH +SHIBLEY SH IH1 B L IY0 +SHICK SH IH1 K +SHICOFF SH IH1 K AO2 F +SHIDELER SH IH1 D AH0 L ER0 +SHIDLER SH AY1 D AH0 L ER0 +SHIDLER(1) SH AY1 D L ER0 +SHIED SH AY1 D +SHIEH SH IY1 +SHIEL SH IY1 L +SHIELA SH AY1 L AH0 +SHIELD SH IY1 L D +SHIELD'S SH IY1 L D Z +SHIELDED SH IY1 L D IH0 D +SHIELDING SH IY1 L D IH0 NG +SHIELDS SH IY1 L D Z +SHIELS SH IY1 L Z +SHIER SH AY1 ER0 +SHIES SH AY1 Z +SHIFF SH IH1 F +SHIFFER SH IH1 F ER0 +SHIFFLER SH IH1 F L ER0 +SHIFFLET SH IH1 F L IH0 T +SHIFFLETT SH IH1 F L IH0 T +SHIFFMAN SH IH1 F M AH0 N +SHIFLET SH IH1 F L IH0 T +SHIFLETT SH IH1 F L IH0 T +SHIFRIN SH IH1 F R IH0 N +SHIFT SH IH1 F T +SHIFTED SH IH1 F T IH0 D +SHIFTER SH IH1 F T ER0 +SHIFTING SH IH1 F T IH0 NG +SHIFTLESS SH IH1 F T L IH0 S +SHIFTS SH IH1 F T S +SHIFTY SH IH1 F T IY0 +SHIGEKI SH IH0 G EY1 K IY2 +SHIGEKUNI SH IY2 G IH0 K UW1 N IY2 +SHIGEO SH IH0 G EY1 OW2 +SHIGERU SH IH0 G EY1 R UW2 +SHIGLEY SH IH1 G L IY0 +SHIH SH IY1 +SHIHAN SH IY1 HH AA2 N +SHIINA SH IY1 N AH0 +SHIITE SH IY1 AY2 T +SHIITES SH IY1 AY2 T S +SHILEY SH IH1 L IY0 +SHILL SH IH1 L +SHILLER SH IH1 L ER0 +SHILLING SH IH1 L IH0 NG +SHILLINGBURG SH IH1 L IH0 NG B ER0 G +SHILLINGER SH IH1 L IH0 N JH ER0 +SHILLINGLAW SH IH1 L IH0 NG L AO2 +SHILLINGS SH IH1 L IH0 NG Z +SHILLINGTON SH IH1 L IH0 NG T AH0 N +SHILOH SH AY1 L OW0 +SHILTS SH IH1 L T S +SHIM SH IH1 M +SHIMA SH IY1 M AH0 +SHIMABUKURO SH IY0 M AA0 B UW0 K UH1 R OW0 +SHIMADA SH IY0 M AA1 D AH0 +SHIMBUN SH IH1 M B AH2 N +SHIMBUN(1) SH IH1 M B UW2 N +SHIMEK SH IH1 M IH0 K +SHIMEL SH IH1 M AH0 L +SHIMER SH AY1 M ER0 +SHIMIZU SH IH0 M IY1 Z UW0 +SHIMKO SH IH1 M K OW0 +SHIMKUS SH IH1 M K AH0 S +SHIMMEL SH IH1 M AH0 L +SHIMMER SH IH1 M ER0 +SHIMMERED SH IH1 M ER0 D +SHIMMERING SH IH1 M ER0 IH0 NG +SHIMMERLIK SH IH1 M ER0 L IH0 K +SHIMMERS SH IH1 M ER0 Z +SHIMMIN SH IH1 M IH0 N +SHIMMY SH IH1 M IY0 +SHIMODA SH IH0 M OW1 D AH0 +SHIMOGA SH IH0 M OW1 G AH0 +SHIMOKAWA SH IH2 M OW0 K AA1 W AH0 +SHIMON SH IY1 M OW0 N +SHIMON(1) SH IY1 M AH0 N +SHIMONE SH IY1 M OW0 N +SHIMP SH IH1 M P +SHIN SH IH1 N +SHINALL SH IH1 N AH0 L +SHINAULT SH IH1 N AW0 L T +SHINBEIN SH IH1 N B AY2 N +SHINBONE SH IH1 N B OW2 N +SHINDIG SH IH1 N D IH0 G +SHINDLE SH IH1 N D AH0 L +SHINDLEDECKER SH IH1 N D AH0 L D IH0 K ER0 +SHINDLER SH IH1 N D L ER0 +SHINDLER'S SH IH1 N D L ER0 Z +SHINDOU SH IH1 N D OW2 +SHINE SH AY1 N +SHINED SH AY1 N D +SHINER SH AY1 N ER0 +SHINES SH AY1 N Z +SHING SH IH1 NG +SHINGLE SH IH1 NG G AH0 L +SHINGLEDECKER SH IH1 NG G AH0 L D IH0 K ER0 +SHINGLER SH IH1 NG L ER0 +SHINGLES SH IH1 NG G AH0 L Z +SHINGLETON SH IH1 NG G AH0 L T AH0 N +SHINICHI SH IH0 N IY1 CH IY0 +SHINING SH AY1 N IH0 NG +SHINKLE SH IH1 NG K AH0 L +SHINKO SH IH1 NG K OW0 +SHINN SH IH1 N +SHINNERS SH IH1 N ER0 Z +SHINNICK SH IH1 N IH0 K +SHINRI SH IH1 N R IY0 +SHINRIKYO SH IH0 N R IY1 K Y OW0 +SHINSEI SH IH0 N S EY1 +SHINSKY SH IH1 N S K IY0 +SHINTARO SH IH0 N T AA1 R OW0 +SHINTO SH IH1 N T OW2 +SHINWA SH IH1 N W AH0 +SHINXIAKU SH IH2 N CH Y AA1 K UW0 +SHINY SH AY1 N IY0 +SHINYUKA SH IH2 N Y UW1 K AH0 +SHIONG SH IY1 AO0 NG +SHIONOGI SH IY2 AH0 N OW1 G IY0 +SHIP SH IH1 P +SHIP'S SH IH1 P S +SHIPBOARD SH IH1 P B AO2 R D +SHIPBUILDER SH IH1 P B IH2 L D ER0 +SHIPBUILDERS SH IH1 P B IH2 L D ER0 Z +SHIPBUILDING SH IH1 P B IH2 L D IH0 NG +SHIPBUILDINGS SH IH1 P B IH2 L D IH0 NG Z +SHIPE SH AY1 P +SHIPES SH AY1 P S +SHIPHOLDING SH IH1 P HH OW2 L D IH0 NG +SHIPLETT SH IH1 P L IH0 T +SHIPLEY SH IH1 P L IY0 +SHIPLOAD SH IH1 P L OW2 D +SHIPLOADS SH IH1 P L OW2 D Z +SHIPMAN SH IH1 P M AH0 N +SHIPMATE SH IH1 P M EY2 T +SHIPMATES SH IH1 P M EY2 T S +SHIPMENT SH IH1 P M AH0 N T +SHIPMENTS SH IH1 P M AH0 N T S +SHIPOWNER SH IH1 P OW2 N ER0 +SHIPOWNERS SH IH1 P OW2 N ER0 Z +SHIPP SH IH1 P +SHIPP'S SH IH1 P S +SHIPPED SH IH1 P T +SHIPPEE SH IH1 P IY1 +SHIPPER SH IH1 P ER0 +SHIPPER'S SH IH1 P ER0 Z +SHIPPERS SH IH1 P ER0 Z +SHIPPEY SH IH1 P IY0 +SHIPPING SH IH1 P IH0 NG +SHIPPINGPORT SH IH1 P IH0 NG P AO2 R T +SHIPPS SH IH1 P S +SHIPPY SH IH1 P IY0 +SHIPS SH IH1 P S +SHIPS' SH IH1 P S +SHIPSHAPE SH IH1 P SH EY2 P +SHIPTON SH IH1 P T AH0 N +SHIPWASH SH IH1 P W AA2 SH +SHIPWRECK SH IH1 P R EH0 K +SHIPWRIGHT SH IH1 P R AY2 T +SHIPWRIGHTS SH IH1 P R AY2 T S +SHIPYARD SH IH1 P Y AA2 R D +SHIPYARD'S SH IH1 P Y AA2 R D Z +SHIPYARDS SH IH1 P Y AA2 R D Z +SHIR SH ER1 +SHIRA SH IH1 R AH0 +SHIRAH SH IH1 R AH0 +SHIRAISHI SH IH0 R AA0 IY1 SH IY0 +SHIRAZI SH IH0 R AA1 Z IY0 +SHIRE SH AY1 R +SHIRELL SH IH0 R EH1 L +SHIRELLE SH IH0 R EH1 L +SHIREMAN SH IH0 R EY1 M AH0 N +SHIREMANSTOWN SH AY1 R M AH0 N Z T AW2 N +SHIRER SH AY1 ER0 R +SHIRES SH AY1 R Z +SHIREY SH AY1 R IY0 +SHIRIN SH IH1 R AH0 N +SHIRK SH ER1 K +SHIRKED SH ER1 K T +SHIRKEY SH ER1 K IY0 +SHIRKING SH ER1 K IH0 NG +SHIRL SH ER1 L +SHIRLEE SH ER1 L IY0 +SHIRLEEN SH ER0 L IY1 N +SHIRLENE SH ER1 L IY0 N +SHIRLEY SH ER1 L IY0 +SHIRLEY'S SH ER1 L IY0 Z +SHIRLIE SH ER1 L IY0 +SHIROMA SH IH0 R OW1 M AH0 +SHIRONE SH IH0 R OW1 N +SHIRR SH ER1 +SHIRRELL SH ER2 EH1 L +SHIRT SH ER1 T +SHIRTED SH ER1 T IH0 D +SHIRTING SH ER1 T IH0 NG +SHIRTS SH ER1 T S +SHIRTSLEEVE SH ER1 T S L IY2 V +SHISEIDO SH IH0 S EY1 D OW0 +SHISHIDO SH IY0 SH IY1 D OW0 +SHISLER SH IH1 S AH0 L ER0 +SHISLER(1) SH IH1 S L ER0 +SHISSLER SH IH1 S L ER0 +SHIT SH IH1 T +SHIT'S SH IH1 T S +SHITHEAD SH IH1 T HH EH2 D +SHITHOLE SH IH1 T HH OW2 L +SHITILA SH AH0 T IH1 L AH0 +SHITLOAD SH IH1 T L OW2 D +SHITS SH IH1 T S +SHITSTORM SH IH1 T S T AO2 R M +SHITTING SH IH1 T IH0 NG +SHITTY SH IH1 T IY2 +SHIU SH UW1 +SHIVA SH IY1 V AH0 +SHIVE SH AY1 V +SHIVELEY SH IH1 V IH0 L IY0 +SHIVELEY(1) SH IH1 V L IY0 +SHIVELY SH AY1 V L IY0 +SHIVER SH IH1 V ER0 +SHIVERDECKER SH IH1 V ER0 D IH0 K ER0 +SHIVERED SH IH1 V ER0 D +SHIVERING SH IH1 V ER0 IH0 NG +SHIVERS SH IH1 V ER0 Z +SHIVES SH AY1 V Z +SHIVLEY SH IH1 V L IY0 +SHIYUAN SH IY1 UW0 AA0 N +SHIZUKA SH IH0 Z UW1 K AH0 +SHIZUOKA SH IY0 Z W OW1 K AH0 +SHLAES SH L EY1 Z +SHLENKER SH L EH1 NG K ER0 +SHLOBIDAN SH L OW0 B IH1 D AH0 N +SHMOOZE SH M UW1 Z +SHMOOZER SH M UW1 Z ER0 +SHMOOZING SH M UW1 Z IH0 NG +SHMYREV SH M IY1 R EH2 V +SHOAF SH OW1 F +SHOAFF SH OW1 F +SHOALS SH OW1 L Z +SHOBANA SH OW2 B AA1 N AH0 +SHOBANA'S SH OW2 B AA1 N AH0 Z +SHOBANNA SH OW2 B AA1 N AH0 +SHOBANNA'S SH OW2 B AA1 N AH0 Z +SHOBE SH OW1 B +SHOBER SH OW1 B ER0 +SHOBERG SH OW1 B ER0 G +SHOBERT SH AA1 B ER0 T +SHOCK SH AA1 K +SHOCKED SH AA1 K T +SHOCKER SH AA1 K ER0 +SHOCKEY SH AA1 K IY0 +SHOCKING SH AA1 K IH0 NG +SHOCKINGLY SH AA1 K IH0 NG L IY0 +SHOCKLEY SH AA1 K L IY0 +SHOCKS SH AA1 K S +SHOCKWAVE SH AA1 K W EY2 V +SHOCKWAVES SH AA1 K W EY2 V Z +SHOD SH AA1 D +SHODDY SH AA1 D IY0 +SHOE SH UW1 +SHOE'S SH UW1 Z +SHOEBOX SH UW1 B AA0 K S +SHOEHORN SH UW1 HH AO2 R N +SHOEHORNED SH UW1 HH AO0 R N D +SHOELACE SH UW1 L EY2 S +SHOELACES SH UW1 L EY2 S IH0 Z +SHOEMAKE SH UW1 M EY2 K +SHOEMAKER SH UW1 M EY2 K ER0 +SHOEMAKERS SH UW1 M EY2 K ER0 Z +SHOEMATE SH UW1 M EY2 T +SHOEN SH UW1 N +SHOEPRINT SH UW1 P R IH2 N T +SHOEPRINTS SH UW1 P R IH2 N T S +SHOES SH UW1 Z +SHOESHINE SH UW1 SH AY2 N +SHOESTRING SH UW1 S T R IH2 NG +SHOFF SH AO1 F +SHOFFNER SH AO1 F N ER0 +SHOFNER SH AA1 F N ER0 +SHOGREN SH AA1 G R EH0 N +SHOGUN SH OW1 G AH0 N +SHOHAT SH OW1 HH AE0 T +SHOICHI SH OW0 IY1 CH IY0 +SHOICHIRO SH OW2 IH0 CH IH1 R OW0 +SHOJI SH OW1 JH IY0 +SHOKHIN SH OW1 K IH2 N +SHOKO SH OW1 K OW0 +SHOLAR SH OW1 L ER0 +SHOLEM SH OW1 L AH0 M +SHOLES SH OW1 L Z +SHOLL SH AA1 L +SHOLLENBERGER SH AA1 L AH0 N B ER0 G ER0 +SHOLLY SH AA1 L IY0 +SHOLTIS SH OW1 L T IH0 S +SHOLTO SH OW1 L T OW0 +SHOMAKER SH OW1 M EY2 K ER0 +SHOMO SH OW1 M OW0 +SHON SH AA1 N +SHONA SH OW1 N AH0 +SHONE SH OW1 N +SHONEY SH OW1 N IY0 +SHONEY'S SH OW1 N IY0 Z +SHONK SH AA1 NG K +SHONKA SH AA1 NG K AH0 +SHONKWILER SH AA1 NG K W AY2 L ER0 +SHONTZ SH AA1 N T S +SHOO SH UW1 +SHOOB SH UW1 B +SHOOED SH UW1 D +SHOOFLY SH UW1 F L AY2 +SHOOK SH UH1 K +SHOOP SH UW1 P +SHOOPMAN SH UW1 P M AH0 N +SHOOSHAN SH UW1 SH AH0 N +SHOOT SH UW1 T +SHOOTDOWN SH UW1 T D AW2 N +SHOOTER SH UW1 T ER0 +SHOOTER'S SH UW1 T ER0 Z +SHOOTERS SH UW1 T ER0 Z +SHOOTIN' SH UW1 T IH0 N +SHOOTING SH UW1 T IH0 NG +SHOOTINGS SH UW1 T IH0 NG Z +SHOOTOUT SH UW1 T AW0 T +SHOOTOUTS SH UW1 T AW0 T S +SHOOTS SH UW1 T S +SHOP SH AA1 P +SHOP'S SH AA1 P S +SHOPE SH OW1 P +SHOPKEEPER SH AA1 P K IY2 P ER0 +SHOPKEEPER'S SH AA1 P K IY2 P ER0 Z +SHOPKEEPERS SH AA1 P K IY2 P ER0 Z +SHOPKO SH AA1 P K OW0 +SHOPKORN SH AA1 P K AO2 R N +SHOPLIFT SH AA1 P L IH2 F T +SHOPLIFTER SH AA1 P L IH2 F T ER0 +SHOPLIFTERS SH AA1 P L IH2 F T ER0 Z +SHOPLIFTING SH AA1 P L IH2 F T IH0 NG +SHOPLIFTS SH AA1 P L IH2 F T S +SHOPPE SH AA1 P +SHOPPED SH AA1 P T +SHOPPER SH AA1 P ER0 +SHOPPER'S SH AA1 P ER0 Z +SHOPPERS SH AA1 P ER0 Z +SHOPPERS' SH AA1 P ER0 Z +SHOPPES SH AA1 P S +SHOPPING SH AA1 P IH0 NG +SHOPPING'S SH AA1 P IH0 NG Z +SHOPS SH AA1 P S +SHOPTAW SH AA1 P T AO0 +SHOPWELL SH AA1 P W EH2 L +SHOPWORN SH AA1 P W AO2 R N +SHOR SH AO1 R +SHORB SH AO1 R B +SHORE SH AO1 R +SHORE'S SH AO1 R Z +SHOREBIRD SH AO1 R B ER2 D +SHORED SH AO1 R D +SHOREHAM SH AO1 R AH0 M +SHOREHAM(1) SH AO1 R HH AE2 M +SHORELINE SH AO1 R L AY2 N +SHORENSTEIN SH AO1 R AH0 N S T IY0 N +SHORENSTEIN(1) SH AO1 R AH0 N S T AY0 N +SHORES SH AO1 R Z +SHOREWARD SH AO1 R W ER0 D +SHOREY SH AO1 R IY0 +SHORIN SH AO1 R IH0 N +SHORING SH AO1 R IH0 NG +SHORKEY SH AO1 R K IY0 +SHORN SH AO1 R N +SHORR SH AO1 R +SHORT SH AO1 R T 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R T HH EH2 R +SHORTHAIRED SH AO1 R T HH EH2 R D +SHORTHAND SH AO1 R T HH AE2 N D +SHORTING SH AO1 R T IH0 NG +SHORTLIVED SH AO1 R T L IH1 V D +SHORTLIVED(1) SH AO1 R T L AY1 V D +SHORTLY SH AO1 R T L IY0 +SHORTNESS SH AO1 R T N AH0 S +SHORTRIDGE SH AO1 R T R IH0 JH +SHORTS SH AO1 R T S +SHORTS' SH AO1 R T S +SHORTSIGHTED SH AO1 R T S AY1 T IH0 D +SHORTSIGHTEDNESS SH AO1 R T S AY1 T IH0 D N IH0 S +SHORTSTOP SH AO1 R T S T AA2 P +SHORTT SH AO1 R T +SHORTTERM SH AO1 R T T ER2 M +SHORTWAVE SH AO1 R T W EY1 V +SHORTY SH AO1 R T IY0 +SHORTZ SH AO1 R T S +SHORTZ' SH AO1 R T S +SHORTZ'S SH AO1 R T S IH0 Z +SHOSH SH OW1 SH +SHOSHONE SH OW0 SH OW1 N IY0 +SHOSTAK SH AA1 S T AH0 K +SHOSTAKOVICH SH AO2 S T AH0 K OW1 V IH0 CH +SHOT SH AA1 T +SHOTGUN SH AA1 T G AH2 N +SHOTGUNS SH AA1 T G AH2 N Z +SHOTS SH AA1 T S +SHOTT SH AA1 T +SHOTTS SH AA1 T S +SHOTWELL SH AA1 T W EH2 L +SHOUGANG SH AW1 G AA1 NG +SHOUGH SH AW1 +SHOULD SH UH1 D +SHOULD'VE SH UH1 D AH0 V +SHOULDER SH OW1 L D ER0 +SHOULDERED SH OW1 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IY0 +SIRAGUSA S IH0 R AA0 G UW1 S AH0 +SIRAVO S IH0 R AA1 V OW0 +SIRCY S ER1 K IY0 +SIRE S AY1 ER0 +SIREK S AY1 R IH0 K +SIREN S AY1 R AH0 N +SIRENA S IH0 R EH1 N AH0 +SIRENS S AY1 R AH0 N Z +SIRES S AY1 R Z +SIRHAN S IH1 R HH AA2 N +SIRHAN(1) S IH1 R HH AE2 N +SIRI S IH1 R IY0 +SIRIANNI S IH0 R IY0 AA1 N IY0 +SIRIGNANO S IH2 R IY0 N Y AA1 N OW0 +SIRIS S AY1 R IH0 S +SIRIS(1) S IH1 R IH0 S +SIRIUS S IH1 R IH2 AH0 S +SIRK S ER1 K +SIRKIN S ER1 K IH0 N +SIRKO S ER1 K OW0 +SIRLES S ER1 L Z +SIRMAN S ER1 M AH0 N +SIRMANS S ER1 M AH0 N Z +SIRMON S ER1 M AH0 N +SIRMONS S ER1 M AH0 N Z +SIRNA S ER1 N AH0 +SIROHI S ER0 OW1 HH IY0 +SIROIS S AY0 R W AA1 +SIROKY S IH1 R AH0 K IY0 +SIRON S IH1 R AH0 N +SIROTA S IH0 R OW1 T AH0 +SIROWITZ S IH1 R AH0 W IH0 T S +SIRRI S IH1 R IY0 +SIRRINE S IH0 R IY1 N IY0 +SIRS S ER1 R Z +SIS S IH1 S +SISCO S IY1 S K OW0 +SISCOE S IH1 S K OW0 +SISEMORE S AY1 Z M AO0 R +SISK S IH1 S K +SISKA S IY1 S K AH0 +SISKEL S IH1 S K AH0 L +SISKEL'S S IH1 S K AH0 L Z +SISKIN S IH1 S K IH0 N +SISKIND S IH1 S K IH0 N D +SISKO S IH1 S K OW0 +SISLER S IH1 S AH0 L ER0 +SISLER(1) S IH1 S L ER0 +SISLEY S IH1 Z L IY0 +SISNEROS S IH1 S N ER0 OW0 Z +SISNEY S IH1 Z N IY0 +SISON S IH1 S AH0 N +SISSEL S IH1 S AH0 L +SISSIE S IH1 S IY0 +SISSOM S IH1 S AH0 M +SISSON S IH1 S AH0 N +SISSY S IH1 S IY0 +SISTARE S IY0 S T AA1 R IY0 +SISTEK S IH1 S T IH0 K +SISTER S IH1 S T ER0 +SISTER'S S IH1 S T ER0 Z +SISTER-IN-LAW S IH1 S T ER0 IH0 N L AO2 +SISTERHOOD S IH1 S T ER0 HH UH0 D +SISTERS S IH1 S T ER0 Z +SISTERS-IN-LAW S IH1 S T ER0 Z IH0 N L AO2 +SISTI S IH1 S T IY0 +SISTINE S IH0 S T IY1 N +SISTINE(1) S IH1 S T IY0 N +SISTO S IH1 S T OW0 +SISTRUNK S IH1 S T R AH0 NG K +SISULU S IH0 S UW1 L UW0 +SIT S IH1 T +SITAR S IH0 T AA1 R +SITARS S IH0 T AA1 R Z +SITCOM S IH1 T K AA2 M +SITCOMS S IH1 T K AA0 M Z +SITE S AY1 T +SITE'S S AY1 T S +SITED S AY1 T IH0 D +SITEK S IH1 T EH0 K +SITENSKI S IH0 T EH1 N S K IY0 +SITENSKI'S S IH0 T EH1 N S K IY0 Z +SITENSKIS S IH0 T EH1 N S K IY0 Z +SITES S AY1 T S +SITHE S AY1 DH +SITING S AY1 T IH0 NG +SITIVENI S IY2 T IH0 V IY1 N IY0 +SITKA S IH1 T K AH0 +SITKO S IH1 T K OW0 +SITLER S AY1 T AH0 L ER0 +SITLER(1) S AY1 T L ER0 +SITLER(2) S IH1 T L ER0 +SITMAR S IH1 T M AA2 R +SITO S IY1 T OW0 +SITO'S S IY1 T OW0 Z +SITRICK S IH1 T R IH0 K +SITS S IH1 T S +SITTER S IH1 T ER0 +SITTERLY S IH1 T ER0 L IY0 +SITTERS S IH1 T ER0 Z +SITTIG S IH1 T IH0 G +SITTIN' S IH1 T AH0 N +SITTING S IH1 T IH0 NG +SITTLER S IH1 T L ER0 +SITTNER S IH1 T N ER0 +SITTON S IH1 T AH0 N +SITTS S IH1 T S +SITUATE S IH1 CH UW0 EY2 T +SITUATED S IH1 CH UW0 EY2 T IH0 D +SITUATION S IH2 CH UW0 EY1 SH AH0 N +SITUATION'S S IH2 CH UW0 EY1 SH AH0 N Z +SITUATIONAL S IH2 CH UW0 EY1 SH AH0 N AH0 L +SITUATIONS S IH2 CH UW0 EY1 SH AH0 N Z +SITUS S AY1 T AH0 S +SITZ S IH1 T S +SITZE S IH1 T Z +SITZER S IH1 T Z ER0 +SITZES S IH1 T S IH0 Z +SITZMAN S IH1 T S M AH0 N +SITZMANN S IH1 T S M AH0 N +SIU S IY1 UW0 +SIUDA S IY0 UW1 D AH0 +SIVAK S IH1 V AH0 K +SIVER S AY1 V ER0 +SIVERLING S IH1 V ER0 L IH0 NG +SIVERSON S IH1 V ER0 S AH0 N +SIVERTSEN S IH1 V ER0 T S AH0 N +SIVERTSON S IH1 V ER0 T S AH0 N +SIVILS S IH1 V AH0 L Z +SIVLEY S IH1 V L IY0 +SIVY S IH1 V IY0 +SIWEK S IH1 W IH0 K +SIX S IH1 K S +SIX'S S IH1 K S IH0 Z +SIX-PACK S IH1 K S P AE2 K +SIXED S IH1 K S T +SIXER S IH1 K S ER0 +SIXERS S IH1 K S ER0 Z +SIXES S IH1 K S IH0 Z +SIXFOLD S IH1 K S F OW2 L D +SIXTEEN S IH0 K S T IY1 N +SIXTEEN(1) S IH1 K S T IY1 N +SIXTEEN'S S IH2 K S T IY1 N Z +SIXTEENS S IH1 K S T IY1 N Z +SIXTEENTH S IH0 K S T IY1 N TH +SIXTEENTH(1) S IH1 K S T IY1 N TH +SIXTEENTHS S IH1 K S T IY1 N TH S +SIXTH S IH1 K S TH +SIXTHS S IH1 K S TH S +SIXTIES S IH1 K S T IY0 Z +SIXTIETH S IH1 K S T IY0 IH0 TH +SIXTY S IH1 K S T IY0 +SIXTY'S S IH1 K S T IY0 Z +SIZABLE S AY1 Z AH0 B AH0 L +SIZE S AY1 Z +SIZEABLE S AY1 Z AH0 B AH0 L +SIZED S AY1 Z D +SIZELER S AY1 Z L ER0 +SIZELOVE S AY1 Z L AH2 V +SIZEMORE S AY1 Z M AO0 R +SIZER S AY1 Z ER0 +SIZES S AY1 Z AH0 Z +SIZES(1) S AY1 Z IH0 Z +SIZING S AY1 Z IH0 NG +SIZZLE S IH1 Z AH0 L +SIZZLED S IH1 Z AH0 L D +SIZZLER S IH1 Z L ER0 +SIZZLERS S IH1 Z L ER0 Z +SIZZLIN S IH1 Z L IH0 N +SIZZLING S IH1 Z AH0 L IH0 NG +SIZZLING(1) S IH1 Z L IH0 NG +SJOBERG SH OW1 B ER0 G +SJOBLOM SH OW1 B L AA0 M +SJODIN SH OW1 D IH0 N +SJOGREN SH OW1 G R AH0 N +SJOLANDER SH OW1 L AE2 N D ER0 +SJOQUIST SH OW1 K W IH0 S T +SJOSTROM SH OW1 S T R AH0 M +SKA S K AA1 +SKAAR S K AA1 R +SKADDEN S K AE1 D IH0 N +SKAFF S K AE1 F +SKAGGS S K AE1 G Z +SKAINS S K EY1 N Z +SKALA S K AA1 L AH0 +SKALICKY S K AH0 L IH1 K IY0 +SKALLA S K AE1 L AH0 +SKALSKI S K AA1 L S K IY0 +SKALSKY S K AA1 L S K IY0 +SKANDIA S K AE1 N D IY0 ER0 +SKANDIA(1) S K AE1 N D IY0 AH0 +SKANDIA(2) S K AE1 N D Y AH0 +SKANDINAVISKA S K AE2 N D IH0 N AH0 V IH1 S K AH0 +SKANSKA S K AE1 N S K AH0 +SKARDA S K AA1 R D AH0 +SKARE S K EH1 R +SKASE S K EY1 Z +SKATE S K EY1 T +SKATEBOARD S K EY1 T B AO2 R D +SKATEBOARDING S K EY1 T B AO2 R D IH0 NG +SKATED S K EY1 T IH0 D +SKATER S K EY1 T ER0 +SKATERS S K EY1 T ER0 Z +SKATES S K EY1 T S +SKATING S K EY1 T IH0 NG +SKEAT S K IY1 T +SKEEL S K IY1 L +SKEELS S K IY1 L Z +SKEEN S K IY1 N +SKEENS S K IY1 N Z +SKEES S K IY1 Z +SKEET S K IY1 T +SKEETE S K IY1 T +SKEETER S K IY1 T ER0 +SKEETERS S K IY1 T ER0 Z +SKEETS S K IY1 T S +SKEFFINGTON S K EH1 F IH0 NG T AH0 N +SKEHAN S K EY1 AH0 N +SKEIN S K EY1 N +SKEINS S K EY1 N Z +SKELETAL S K EH1 L AH0 T AH0 L +SKELETON S K EH1 L AH0 T AH0 N +SKELETONS S K EH1 L AH0 T AH0 N Z +SKELLENGER S K EH1 L IH0 N JH ER0 +SKELLEY S K EH1 L IY0 +SKELLY S K EH1 L IY0 +SKELTER S K EH1 L T ER0 +SKELTON S K EH1 L T AH0 N +SKENANDORE S K IH0 N AE1 N D ER0 +SKENDER S K EH1 N D ER0 +SKENDERIAN S K EH2 N D EH1 R IY0 AH0 N +SKENE S K IY1 N +SKEOCH S K IY1 AA0 CH +SKEPTIC S K EH1 P T IH0 K +SKEPTICAL S K EH1 P T AH0 K AH0 L +SKEPTICAL(1) S K EH1 P T IH0 K AH0 L +SKEPTICALLY S K EH1 P T IH0 K AH0 L IY0 +SKEPTICALLY(1) S K EH1 P T IH0 K L IY0 +SKEPTICISM S K EH1 P T IH0 S IH2 Z AH0 M +SKEPTICS S K EH1 P T IH0 K S +SKERDAL S K EH1 R D AA2 L +SKERRY S K EH1 R IY0 +SKETCH S K EH1 CH +SKETCHBOOK S K EH1 CH B UH2 K +SKETCHBOOKS S K EH1 CH B UH2 K S +SKETCHED S K EH1 CH T +SKETCHES S K EH1 CH AH0 Z +SKETCHES(1) S K EH1 CH IH0 Z +SKETCHING S K EH1 CH IH0 NG +SKETCHY S K EH1 CH IY0 +SKEW S K Y UW1 +SKEWED S K Y UW1 D +SKEWER S K Y UW1 ER0 +SKEWERED S K Y UW1 ER0 D +SKEWERS S K Y UW1 ER0 Z +SKEWES S K Y UW1 Z +SKEWING S K Y UW1 IH0 NG +SKEWS S K Y UW1 Z +SKI S K IY1 +SKIBA S K AY1 B AH0 +SKIBBE S K IH1 B +SKIBICKI S K IH0 B IH1 K IY0 +SKIBINSKI S K IH0 B IH1 N S K IY0 +SKIBO S K AY1 B OW0 +SKIBO(1) S K IY1 B OW0 +SKID S K IH1 D +SKIDDED S K IH1 D IH0 D +SKIDDING S K IH1 D IH0 NG +SKIDGEL S K IH1 JH AH0 L +SKIDMORE S K IH1 D M AO0 R +SKIDS S K IH1 D Z +SKIED S K IY1 D +SKIER S K AY1 R +SKIER(1) S K IY1 ER0 +SKIERS S K IY1 ER0 Z +SKIES S K AY1 Z +SKIFF S K IH1 F +SKIFFINGTON S K IH1 F IH0 NG T AH0 N +SKIFFS S K IH1 F S +SKIING S K IY1 IH0 NG +SKILES S K AY1 L Z +SKILL S K IH1 L +SKILLED S K IH1 L D +SKILLEN S K IH1 L AH0 N +SKILLERN S K IH1 L ER0 N +SKILLET S K IH1 L AH0 T +SKILLFUL S K IH1 L F AH0 L +SKILLFULLY S K IH1 L F AH0 L IY0 +SKILLIN S K IH1 L IH0 N +SKILLING S K IH1 L IH0 NG +SKILLINGS S K IH1 L IH0 NG Z +SKILLMAN S K IH1 L M AH0 N +SKILLS S K IH1 L Z +SKILTON S K IH1 L T AH0 N +SKIM S K IH1 M +SKIMMED S K IH1 M D +SKIMMER S K IH1 M ER0 +SKIMMERS S K IH1 M ER0 Z +SKIMMING S K IH1 M IH0 NG +SKIMP S K IH1 M P +SKIMPIER S K IH1 M P IY0 ER0 +SKIMPIEST S K IH1 M P IY0 AH0 S T +SKIMPING S K IH1 M P IH0 NG +SKIMPY S K IH1 M P IY0 +SKIN S K IH1 N +SKIN'S S K IH1 N Z +SKINFLINT S K IH1 N F L IH0 N T +SKINHEAD S K IH1 N HH EH2 D +SKINHEADS S K IH1 N HH EH2 D Z +SKINKS S K IH1 NG K S +SKINLESS S K IH1 N L AH0 S +SKINNED S K IH1 N D +SKINNER S K IH1 N ER0 +SKINNER'S S K IH1 N ER0 Z +SKINNIER S K IH1 N IY0 ER0 +SKINNIEST S K IH1 N IY0 AH0 S T +SKINNY S K IH1 N IY0 +SKINS S K IH1 N Z +SKINS' S K IH1 N Z +SKIP S K IH1 P +SKIPJACK S K IH1 P JH AE2 K +SKIPJACK'S S K IH1 P JH AE2 K S +SKIPJACKS S K IH1 P JH AE2 K S +SKIPP S K IH1 P +SKIPPA S K IH1 P AH0 +SKIPPA'S S K IH1 P AH0 Z +SKIPPED S K IH1 P T +SKIPPER S K IH1 P ER0 +SKIPPER'S S K IH1 P ER0 Z +SKIPPERS S K IH1 P ER0 Z +SKIPPING S K IH1 P IH0 NG +SKIPPY S K IH1 P IY0 +SKIPS S K IH1 P S +SKIPTON S K IH1 P T AH0 N +SKIPWITH S K IH1 P W IH2 TH +SKIPWORTH S K IH1 P W ER2 TH +SKIRDALL S K ER1 D AA2 L +SKIRMISH S K ER1 M IH0 SH +SKIRMISHES S K ER1 M IH0 SH IH0 Z +SKIRMISHING S K ER1 M IH0 SH IH0 NG +SKIRT S K ER1 T +SKIRTED S K ER1 T IH0 D +SKIRTING S K ER1 T IH0 NG +SKIRTS S K ER1 T S +SKIRVIN S K ER1 V IH0 N +SKIS S K IY1 Z +SKIT S K IH1 T +SKITS S K IH1 T S +SKITTISH S K IH1 T IH0 SH +SKITTISHNESS S K IH1 T IH0 SH N AH0 S +SKITTLE S K IH1 T AH0 L +SKITTLES S K IH1 T AH0 L Z +SKIVER S K AY1 V ER0 +SKLAR S K L AA1 R +SKLENAR S K L EH1 N ER0 +SKOAL S K OW1 L +SKOCZYLAS S K AH0 CH IH1 L AH0 Z +SKODA S K OW1 D AA2 +SKOFF S K AO1 F +SKOG S K AA1 G +SKOGEN S K AA1 G AH0 N +SKOGLUND S K AA1 G L AH0 N D +SKOK S K AA1 K +SKOKIE S K OW1 K IY0 +SKOLER S K OW1 L ER0 +SKOLNICK S K OW1 L N IH0 K +SKOLNIK S K OW1 L N IH0 K +SKOLNIKS S K OW1 L N IH0 K S +SKONIECZNY S K AH0 N IY1 CH N IY2 +SKOOG S K UW1 G +SKOP S K AA1 P +SKOPJE S K AO1 P Y EH2 +SKORA S K AO1 R AH0 +SKORUPA S K ER0 UW1 P AA2 +SKORUPSKI S K ER0 AH1 P S K IY2 +SKOUSEN S K UW1 S AH0 N +SKOV S K AA1 V +SKOW S K AW1 +SKOWHEGAN S K OW1 HH IY2 G AH0 N +SKOWRON S K AW1 R AH0 N +SKOWRONEK S K AW0 R OW1 N EH0 K +SKOWRONSKI S K AW0 R AA1 N S K IY2 +SKRAMSTAD S K R AE1 M S T AE0 D +SKREW-UP S K R UW1 AH2 P +SKREW-UPS S K R UW1 AH2 P S +SKROCH S K R AA1 K +SKROCKI S K R AA1 K IY0 +SKRZYPEK S K ER0 Z IH1 P EH0 K +SKUDRA S K UW1 D R AA0 +SKUFCA S K AH1 F K AA0 +SKULDUGGERY S K AH0 L D AH1 G ER0 IY2 +SKULK S K AH1 L K +SKULKING S K AH1 L K IH0 NG +SKULKS S K AH1 L K S +SKULL S K AH1 L +SKULLCAP S K AH1 L K AE2 P +SKULLCAPS S K AH1 L K AE2 P S +SKULLS S K AH1 L S +SKULLS(1) S K AH1 L Z +SKUNK S K AH1 NG K +SKUNKS S K AH1 NG K S +SKURA S K UH1 R AA0 +SKURDAL S K ER1 D AA0 L +SKURKA S K ER1 K AA0 +SKUTT S K AH1 T +SKY S K AY1 +SKY'S S K AY1 Z +SKYBOX S K AY1 B AA2 K S +SKYBOXES S K AY1 B AA2 K S IH0 Z +SKYCAP S K AY1 K AE2 P +SKYDIVE S K AY1 D AY0 V +SKYDIVING S K AY1 D AY0 V IH0 NG +SKYDOME S K AY1 D OW2 M +SKYE S K AY1 +SKYHAWK S K AY1 HH AO2 K +SKYHAWKS S K AY1 HH AO2 K S +SKYHIGH S K AY1 HH AY2 +SKYHOPPING S K AY1 HH AO0 P IH0 NG +SKYLARK S K AY1 L AA2 R K +SKYLARKS S K AY1 L AA2 R K S +SKYLAWN S K AY1 L AO2 N +SKYLES S K AY1 L Z +SKYLIGHT S K AY1 L AY2 T +SKYLIGHTS S K AY1 L AY2 T S +SKYLINE S K AY1 L AY2 N +SKYLINES S K AY1 L AY2 N Z +SKYLITE S K AY1 L AY2 T +SKYLITES S K AY1 L AY2 T S +SKYNET S K AY1 N EH2 T +SKYPE S K AY1 P +SKYROCKET S K AY1 R AA2 K AH0 T +SKYROCKETED S K AY1 R AA2 K AH0 T IH0 D +SKYROCKETING S K AY1 R AA2 K AH0 T IH0 NG +SKYROCKETS S K AY1 R AA2 K AH0 T S +SKYSCRAPER S K AY1 S K R EY2 P ER0 +SKYSCRAPERS S K AY1 S K R EY2 P ER0 Z +SKYTEL S K AY1 T EH2 L +SKYWALKER S K AY1 W AO2 K ER0 +SKYWARD S K AY1 W ER0 D +SKYWAVE S K AY1 W EY2 V +SKYWAY S K AY1 W EY2 +SKYWEST S K AY1 W EH2 S T +SKYWRITER S K AY1 R AY2 T ER0 +SKYWRITERS S K AY1 R AY2 T ER0 Z +SKYWRITING S K AY1 R AY2 T IH0 NG +SLAB S L AE1 B +SLABAUGH S L AE1 B AO0 +SLABS S L AE1 B Z +SLABY S L EY1 B IY0 +SLACK S L AE1 K +SLACKED S L AE1 K T +SLACKEN S L AE1 K AH0 N +SLACKENED S L AE1 K AH0 N D +SLACKENING S L AE1 K AH0 N IH0 NG +SLACKENS S L AE1 K AH0 N Z +SLACKER S L AE1 K ER0 +SLACKERS S L AE1 K ER0 Z +SLACKNESS S L AE1 K N AH0 S +SLACKS S L AE1 K S +SLADE S L EY1 D +SLADEK S L AE1 D IH0 K +SLADKY S L AE1 D K IY0 +SLAG S L AE1 G +SLAGEL S L AE1 G AH0 L +SLAGER S L EY1 G ER0 +SLAGGING S L AE1 G IH0 NG +SLAGHT S L AE1 T +SLAGLE S L EY1 G AH0 L +SLAGTER S L AE1 G T ER0 +SLAIN S L EY1 N +SLAINE S L EY1 N +SLALOM S L AA1 L AH0 M +SLAM S L AE1 M +SLAMA S L AA1 M AH0 +SLAMMED S L AE1 M D +SLAMMER S L AE1 M ER0 +SLAMMING S L AE1 M IH0 NG +SLAMS S L AE1 M Z +SLANDER S L AE1 N D ER0 +SLANDERED S L AE1 N D ER0 D +SLANDERER S L AE1 N D ER0 ER0 +SLANDERING S L AE1 N D ER0 IH0 NG +SLANDEROUS S L AE1 N D ER0 AH0 S +SLANDERS S L AE1 N D ER0 Z +SLANE S L EY1 N +SLANEY S L EY1 N IY0 +SLANG S L AE1 NG +SLANINA S L AA0 N IY1 N AH0 +SLANKARD S L AE1 NG K ER0 D +SLANT S L AE1 N T +SLANTED S L AE1 N T IH0 D +SLANTING S L AE1 N T IH0 NG +SLAP S L AE1 P +SLAPDASH S L AE1 P D AE2 SH +SLAPE S L EY1 P +SLAPHAPPY S L AE1 P HH AE2 P IY0 +SLAPPED S L AE1 P T +SLAPPEY S L AE1 P IY0 +SLAPPING S L AE1 P IH0 NG +SLAPS S L AE1 P S +SLAPSTICK S L AE1 P S T IH2 K +SLASH S L AE1 SH +SLASHED S L AE1 SH T +SLASHER S L AE1 SH ER0 +SLASHES S L AE1 SH IH0 Z +SLASHING S L AE1 SH IH0 NG +SLAT S L AE1 T +SLATE S L EY1 T +SLATED S L EY1 T IH0 D +SLATEN S L EY1 T AH0 N +SLATER S L EY1 T ER0 +SLATER'S S L EY1 T ER0 Z +SLATERS S L EY1 T ER0 Z +SLATES S L EY1 T S +SLATHER S L AE1 DH ER0 +SLATHERED S L AE1 DH ER0 D +SLATHERING S L AE1 DH ER0 IH0 NG +SLATHERS S L AE1 DH ER0 Z +SLATING S L EY1 T IH0 NG +SLATKIN S L AE1 T K IH0 N +SLATON S L AE1 T AH0 N +SLATS S L AE1 T S +SLATTEN S L AE1 T AH0 N +SLATTER S L AE1 T ER0 +SLATTERY S L AE1 T ER0 IY0 +SLATTON S L AE1 T AH0 N +SLAUGH S L AO1 +SLAUGHTER S L AO1 T ER0 +SLAUGHTERED S L AO1 T ER0 D +SLAUGHTERHOUSE S L AO1 T ER0 HH AW2 S +SLAUGHTERHOUSES S L AO1 T ER0 HH AW2 S IH0 Z +SLAUGHTERING S L AO1 T ER0 IH0 NG +SLAUGHTERINGS S L AO1 T ER0 IH0 NG Z +SLAUGHTERS S L AO1 T ER0 Z +SLAUSON S L AW1 Z AH0 N +SLAV S L AA1 V +SLAVA S L AA1 V AH0 +SLAVE S L EY1 V +SLAVEN S L EY1 V AH0 N +SLAVENS S L EY1 V AH0 N Z +SLAVERY S L EY1 V ER0 IY0 +SLAVES S L EY1 V Z +SLAVIC S L AA1 V IH0 K +SLAVICK S L AE1 V IH0 K +SLAVIK S L AA1 V IH0 K +SLAVIN S L AE1 V IH0 N +SLAVINSKI S L AH0 V IH1 N S K IY0 +SLAVISH S L EY1 V IH0 SH +SLAVISHLY S L AE1 V IH0 SH L IY0 +SLAVONIA S L AH0 V OW1 N IY0 AH0 +SLAVONIA(1) S L AH0 V OW1 N Y AH0 +SLAVS S L AA1 V Z +SLAW S L AO1 +SLAWINSKI S L AA0 V IH1 N S K IY0 +SLAWSON S L AO1 S AH0 N +SLAY S L EY1 +SLAYBACK S L EY1 B AE2 K +SLAYBAUGH S L EY1 B AO2 +SLAYDEN S L EY1 D AH0 N +SLAYDON S L EY1 D AH0 N +SLAYER S L EY1 ER0 +SLAYING S L EY1 IH0 NG +SLAYINGS S L EY1 IH0 NG Z +SLAYMAKER S L EY1 M EY2 K ER0 +SLAYTER S L EY1 T ER0 +SLAYTON S L EY1 T AH0 N +SLEASMAN S L IY1 Z M AH0 N +SLEATOR S L EY1 T ER0 +SLEAZE S L IY1 Z +SLEAZY S L IY1 Z IY0 +SLECHTA S L EH1 CH T AH0 +SLED S L EH1 D +SLEDD S L EH1 D +SLEDDING S L EH1 D IH0 NG +SLEDGE S L EH1 JH +SLEDGEHAMMER S L EH1 JH HH AE2 M ER0 +SLEDS S L EH1 D Z +SLEDZ S L EH1 D Z +SLEE S L IY1 +SLEEK S L IY1 K +SLEEKER S L IY1 K ER0 +SLEEKEST S L IY1 K AH0 S T +SLEEKLY S L IY1 K L IY0 +SLEEMAN S L IY1 M AH0 N +SLEEP S L IY1 P +SLEEPER S L IY1 P ER0 +SLEEPERS S L IY1 P ER0 Z +SLEEPILY S L IY1 P AH0 L IY0 +SLEEPINESS S L IY1 P IY0 N AH0 S +SLEEPING S L IY1 P IH0 NG +SLEEPLESS S L IY1 P L AH0 S +SLEEPOVER S L IY1 P OW2 V ER0 +SLEEPOVERS S L IY1 P OW2 V ER0 Z +SLEEPS S L IY1 P S +SLEEPWALK S L IY1 P W AO2 K +SLEEPWALKER S L IY1 P W AO2 K ER0 +SLEEPWALKERS S L IY1 P W AO2 K ER0 Z +SLEEPWALKING S L IY1 P W AO2 K IH0 NG +SLEEPWEAR S L IY1 P W EH2 R +SLEEPY S L IY1 P IY0 +SLEET S L IY1 T +SLEETER S L IY1 T ER0 +SLEETH S L IY1 TH +SLEEVE S L IY1 V +SLEEVED S L IY1 V D +SLEEVELESS S L IY1 V L IH0 S +SLEEVES S L IY1 V Z +SLEIGH S L EY1 +SLEIGHT S L AY1 T +SLEIPNER S L AY1 P N ER0 +SLEMMER S L EH1 M ER0 +SLEMP S L EH1 M P +SLENDER S L EH1 N D ER0 +SLENTZ S L EH1 N T S +SLEPIAN S L IY1 P IY0 AH0 N +SLEPIAN(1) S L IY1 P Y AH0 N +SLEPT S L EH1 P T +SLESSENGER S L EH1 S EH0 N G ER0 +SLETTEN S L EH1 T AH0 N +SLEUTH S L UW1 TH +SLEUTHING S L UW1 TH IH0 NG +SLEUTHS S L UW1 TH S +SLEVEN S L IY1 V AH0 N +SLEVIN S L EH1 V IH0 N +SLEW S L UW1 +SLEZAK S L EH1 Z AH0 K +SLICE S L AY1 S +SLICED S L AY1 S T +SLICER S L AY1 S ER0 +SLICES S L AY1 S AH0 Z +SLICES(1) S L AY1 S IH0 Z +SLICING S L AY1 S IH0 NG +SLICK S L IH1 K +SLICKED S L IH1 K T +SLICKER S L IH1 K ER0 +SLICKERS S L IH1 K ER0 Z +SLICKEST S L IH1 K AH0 S T +SLICKLY S L IH1 K L IY0 +SLICKS S L IH1 K S +SLID S L IH1 D +SLIDE S L AY1 D +SLIDER S L AY1 D ER0 +SLIDES S L AY1 D Z +SLIDING S L AY1 D IH0 NG +SLIFE S L AY1 F +SLIFER S L AY1 F ER0 +SLIFKA S L IH1 F K AH0 +SLIFKO S L IH1 F K OW0 +SLIGAR S L IH1 G ER0 +SLIGER S L AY1 G ER0 +SLIGH S L AY1 +SLIGHT S L AY1 T +SLIGHTED S L AY1 T IH0 D +SLIGHTEST S L AY1 T AH0 S T +SLIGHTING S L AY1 T IH0 NG +SLIGHTLY S L AY1 T L IY0 +SLIGHTS S L AY1 T S +SLIKER S L AY1 K ER0 +SLIM S L IH1 M +SLIMAK S L IH1 M AH0 K +SLIME S L AY1 M +SLIMMED S L IH1 M D +SLIMMER S L IH1 M ER0 +SLIMMEST S L IH1 M AH0 S T +SLIMMING S L IH1 M IH0 NG +SLIMP S L IH1 M P +SLIMS S L IH1 M Z +SLIMY S L AY1 M IY0 +SLINEY S L IH1 N IY0 +SLING S L IH1 NG +SLINGER S L IH1 NG ER0 +SLINGERLAND S L IH1 NG G ER0 L AH0 N D +SLINGING S L IH1 NG IH0 NG +SLINGS S L IH1 NG Z +SLINGSHOT S L IH1 NG SH AA2 T +SLINGSHOTS S L IH1 NG SH AA2 T S +SLINKARD S L IH1 NG K ER0 D +SLINKER S L IH1 NG K ER0 +SLINKY S L IH1 NG K IY0 +SLIP S L IH1 P +SLIP-ON S L IH1 P AA2 N +SLIP-ONS S L IH1 P AA2 N Z +SLIPPAGE S L IH1 P IH0 JH +SLIPPED S L IH1 P T +SLIPPER S L IH1 P ER0 +SLIPPERS S L IH1 P ER0 Z +SLIPPERY S L IH1 P ER0 IY0 +SLIPPERY(1) S L IH1 P R IY0 +SLIPPING S L IH1 P IH0 NG +SLIPS S L IH1 P S +SLIPSHOD S L IH1 P SH AA2 D +SLIT S L IH1 T +SLITER S L IY1 T ER0 +SLITHER S L IH1 DH ER0 +SLITHERING S L IH1 DH ER0 IH0 NG +SLITS S L IH1 T S +SLITTING S L IH1 T IH0 NG +SLIVA S L IY1 V AH0 +SLIVER S L IH1 V ER0 +SLIVERS S L IH1 V ER0 Z +SLIVINSKI S L IH0 V IH1 N S K IY0 +SLIVKA S L IH1 V K AH0 +SLIVOVITZ S L IH1 V AH0 V IH0 T S +SLIWA S L AY1 V AH0 +SLIWINSKI S L IH0 V IH1 N S K IY0 +SLOAN S L OW1 N +SLOAN'S S L OW1 N Z +SLOANE S L OW1 N +SLOAT S L OW1 T +SLOATE S L OW1 T +SLOB S L AA1 B +SLOBBER S L AA1 B ER0 +SLOBBERING S L AA1 B ER0 IH0 NG +SLOBODA S L AH0 B OW1 D AH0 +SLOBODAN S L OW1 B OW0 D AA2 N +SLOBOGIN S L AH0 B OW1 G AH0 N +SLOBOGIN'S S L AH0 B OW1 G AH0 N Z +SLOBS S L AA1 B Z +SLOCAN S L OW1 K AH0 N +SLOCAN'S S L OW1 K AH0 N Z +SLOCOMB S L OW1 K AH0 M +SLOCUM S L OW1 K AH0 M +SLOCUMB S L OW1 K AH0 M +SLOE S L OW1 +SLOG S L AA1 G +SLOGAN S L OW1 G AH0 N +SLOGANS S L OW1 G AH0 N Z +SLOGGED S L AA1 G D +SLOGGING S L AA1 G IH0 NG +SLOKUM S L OW1 K AH0 M +SLOMA S L OW1 M AH0 +SLOMAN S L OW1 M AH0 N +SLOMINSKI S L AH0 M IH1 N S K IY0 +SLOMSKI S L AA1 M S K IY0 +SLONAKER S L AA1 N AH0 K ER0 +SLONE S L OW1 N +SLONIKER S L AA1 N IH0 K ER0 +SLOOP S L UW1 P +SLOP S L AA1 P +SLOPE S L OW1 P +SLOPER S L OW1 P ER0 +SLOPES S L OW1 P S +SLOPING S L OW1 P IH0 NG +SLOPPIER S L AA1 P IY0 ER0 +SLOPPIEST S L AA1 P IY0 AH0 S T +SLOPPILY S L AA1 P AH0 L IY0 +SLOPPINESS S L AA1 P IY0 N AH0 S +SLOPPY S L AA1 P IY0 +SLORC S L AO1 R K +SLOSH S L AA1 SH +SLOSHING S L AA1 SH IH0 NG +SLOSS S L AO1 S +SLOT S L AA1 T +SLOTA S L OW1 T AH0 +SLOTH S L OW1 TH +SLOTHOWER S L AA1 TH OW0 ER0 +SLOTNICK S L AA1 T N IH0 K +SLOTS S L AA1 T S +SLOTT S L AA1 T +SLOTTED S L AA1 T IH0 D +SLOTTING S L AA1 T IH0 NG +SLOUCH S L AW1 CH +SLOUCHES S L AW1 CH IH0 Z +SLOUCHING S L AW1 CH IH0 NG +SLOUGH S L AH1 F +SLOUGHS S L AH1 F S +SLOVACEK S L AA1 V AA0 CH EH0 K +SLOVAK S L OW1 V AA0 K +SLOVAKIA S L OW2 V AA1 K IY2 AH0 +SLOVAKIA'S S L OW0 V AA1 K IY2 AH0 Z +SLOVAKIAN S L OW1 V AA0 K IY2 AH0 N +SLOVAKS S L OW1 V AA0 K S +SLOVENE S L OW2 V IY1 N +SLOVENES S L OW2 V IY1 N Z +SLOVENIA S L OW2 V IY1 N IY0 AH0 +SLOVENIAN S L OW2 V IY1 N IY0 AH0 N +SLOVENLINESS S L AH1 V AH0 N L IY0 N AH0 S +SLOVENLY S L AH1 V AH0 N L IY0 +SLOVER S L OW1 V ER0 +SLOVES S L OW1 V Z +SLOVO S L OW1 V OW0 +SLOVONIA S L AH0 V OW1 N IY0 AH0 +SLOVONIA(1) S L AH0 V OW1 N Y AH0 +SLOW S L OW1 +SLOWDOWN S L OW1 D AW2 N +SLOWDOWNS S L OW1 D AW2 N Z +SLOWED S L OW1 D +SLOWER S L OW1 ER0 +SLOWEST S L OW1 AH0 S T +SLOWEY S L OW1 IY0 +SLOWIK S L OW1 IH0 K +SLOWING S L OW1 IH0 NG +SLOWINSKI S L OW0 IH1 N S K IY0 +SLOWLY S L OW1 L IY0 +SLOWNESS S L OW1 N AH0 S +SLOWPOKE S L OW1 P OW2 K +SLOWS S L OW1 Z +SLUDER S L UW1 D ER0 +SLUDGE S L AH1 JH +SLUDGY S L AH1 JH IY0 +SLUG S L AH1 G +SLUGA S L UW1 G AH0 +SLUGFEST S L AH1 G F EH2 S T +SLUGGED S L AH1 G D +SLUGGER S L AH1 G ER0 +SLUGGERS S L AH1 G ER0 Z +SLUGGING S L AH1 G IH0 NG +SLUGGISH S L AH1 G IH0 SH +SLUGGISHLY S L AH1 G IH0 SH L IY0 +SLUGGISHNESS S L AH1 G IH0 SH N AH0 S +SLUGS S L AH1 G Z +SLUICE S L UW1 S +SLUICING S L UW1 S IH0 NG +SLUITER S L UW1 T ER0 +SLUKA S L UW1 K AH0 +SLUM S L AH1 M +SLUMBER S L AH1 M B ER0 +SLUMBERING S L AH1 M B ER0 IH0 NG +SLUMP S L AH1 M P +SLUMPED S L AH1 M P T +SLUMPING S L AH1 M P IH0 NG +SLUMPS S L AH1 M P S +SLUMS S L AH1 M Z +SLUNG S L AH1 NG +SLUPIC S L UW1 P IH0 K +SLUR S L ER1 +SLURP S L ER1 P +SLURRED S L ER1 D +SLURRING S L ER1 IH0 NG +SLURRY S L ER1 IY0 +SLURS S L ER1 Z +SLUSH S L AH1 SH +SLUSHAYETE S L UH0 SH EY0 EH1 T +SLUSHER S L AH1 SH ER0 +SLUSS S L AH1 S +SLUSSER S L AH1 S ER0 +SLUT S L AH1 T +SLUTS S L AH1 T S +SLUTSKY S L AH1 T S K IY0 +SLUTTY S L AH1 T IY2 +SLUTZ S L AH1 T S +SLUTZKY S L AH1 T S K IY0 +SLUYTER S L AY1 T ER0 +SLY S L AY1 +SLYE S L AY1 +SLYLY S L AY1 L IY0 +SLYNESS S L AY1 N AH0 S +SLYTER S L AY1 T ER0 +SMABY S M EY1 B IY0 +SMACK S M AE1 K +SMACKED S M AE1 K T +SMACKING S M AE1 K IH0 NG +SMACKS S M AE1 K S +SMAIL S M EY1 L +SMALDONE S M AE1 L D AH0 N +SMALE S M EY1 L +SMALL S M AO1 L +SMALLCAP S M AO1 L K AE2 P +SMALLEN S M AO1 L AH0 N +SMALLER S M AO1 L ER0 +SMALLEST S M AO1 L AH0 S T +SMALLEY S M AA1 L IY0 +SMALLING S M AO1 L IH0 NG +SMALLISH S M AO1 L IH0 SH +SMALLMAN S M AO1 L M AH0 N +SMALLNESS S M AO1 L N AH0 S +SMALLPOX S M AO1 L P AA2 K S +SMALLRIDGE S M AO1 L R IH2 JH +SMALLS S M AO1 L Z +SMALLTALK S M AO1 L T AO2 K +SMALLTOWN S M AO1 L T AW2 N +SMALLWOOD S M AO1 L W UH2 D +SMALTZ S M AE1 L T S +SMARMY S M AA1 R M IY0 +SMARR S M AE1 R +SMART S M AA1 R T +SMART-ASS S M AA1 R T AE2 S +SMARTALECK S M AA1 R T EH0 L AH0 K +SMARTASS S M AA1 R T AE1 S +SMARTCARD S M AA1 R T K AA2 R D +SMARTED S M AA1 R T IH0 D +SMARTEN S M AA1 R T AH0 N +SMARTENED S M AA1 R T AH0 N D +SMARTENING S M AA1 R T AH0 N IH0 NG +SMARTER S M AA1 R T ER0 +SMARTEST S M AA1 R T AH0 S T +SMARTIES S M AA1 R T IY0 Z +SMARTING S M AA1 R T IH0 NG +SMARTISH S M AA1 R T IH0 SH +SMARTLY S M AA1 R T L IY0 +SMARTMONEY S M AA1 R T M AH2 N IY0 +SMARTNESS S M AA1 R T N IH0 S +SMARTS S M AA1 R T S +SMARTT S M AA1 R T +SMARTY S M AA1 R T IY0 +SMASH S M AE1 SH +SMASHED S M AE1 SH T +SMASHER S M AE1 SH ER0 +SMASHES S M AE1 SH IH0 Z +SMASHING S M AE1 SH IH0 NG +SMATHER S M AE1 DH ER0 +SMATHERS S M AE1 DH ER0 Z +SMATTER S M AE1 T ER0 +SMATTERING S M AE1 T ER0 IH0 NG +SMAY S M EY1 +SMEAD S M IY1 D +SMEAL S M IY1 L +SMEAR S M IH1 R +SMEARED S M IH1 R D +SMEARING S M IH1 R IH0 NG +SMEARS S M IH1 R Z +SMEBY S M IY1 B IY0 +SMEDBERG S M EH1 D B ER0 G +SMEDLEY S M EH1 D L IY0 +SMEE S M IY1 +SMEETING S M IY1 T IH0 NG +SMEJKAL S M EH1 JH K AH0 L +SMELCER S M EH1 L S ER0 +SMELL S M EH1 L +SMELLED S M EH1 L D +SMELLEY S M EH1 L IY0 +SMELLING S M EH1 L IH0 NG +SMELLS S M EH1 L Z +SMELLY S M EH1 L IY0 +SMELSER S M EH1 L S ER0 +SMELT S M EH1 L T +SMELTER S M EH1 L T ER0 +SMELTER'S S M EH1 L T ER0 Z +SMELTERS S M EH1 L T ER0 Z +SMELTING S M EH1 L T IH0 NG +SMELTZ S M EH1 L T S +SMELTZER S M EH1 L T Z ER0 +SMESTAD S M EH1 S T AH0 D +SMET S M EH1 T +SMETANA S M EH1 T AH0 N AH0 +SMETHERS S M EH1 DH ER0 Z +SMETHURST S M EH1 TH ER0 S T +SMETZER S M EH1 T Z ER0 +SMICK S M IH1 K +SMID S M IH1 D +SMIDDY S M IH1 D IY0 +SMIDGEN S M IH1 JH AH0 N +SMIDT S M IH1 D T +SMIGEL S M IH1 JH AH0 L +SMIGELSKI S M IH0 G EH1 L S K IY0 +SMIGIEL S M IH1 JH IY0 L +SMIGIELSKI S M IH0 G IY1 L S K IY0 +SMILE S M AY1 L +SMILED S M AY1 L D +SMILES S M AY1 L Z +SMILEY S M AY1 L IY0 +SMILGIS S M IH1 L G IH0 Z +SMILGIS(1) S M IH1 L JH IH0 Z +SMILIE S M IH1 L IY0 +SMILING S M AY1 L IH0 NG +SMILINGLY S M AY1 L IH0 NG L IY0 +SMILLIE S M IH1 L IY0 +SMILOW S M IH1 L OW0 +SMINK S M IH1 NG K +SMIRK S M ER1 K +SMIRKING S M ER1 K IH0 NG +SMIRKS S M ER1 K S +SMIRNOFF S M ER1 N AO0 F +SMIRNOV S M ER1 N AA0 F +SMIRNOVA S M ER2 N OW1 V AH0 +SMISEK S M IH1 S EH0 K +SMIT S M IH1 T +SMITH S M IH1 TH +SMITH'S S M IH1 TH S +SMITHBURG S M IH1 TH B ER0 G +SMITHEE S M IH1 TH IY1 +SMITHER S M IH1 DH ER0 +SMITHEREEN S M IH2 DH ER0 IY1 N +SMITHEREENS S M IH2 DH ER0 IY1 N Z +SMITHERMAN S M IH1 DH ER0 M AH0 N +SMITHERS S M IH1 DH ER0 Z +SMITHEY S M IH1 TH IY0 +SMITHFIELD S M IH1 TH F IY0 L D +SMITHHART S M IH1 TH HH AA2 R T +SMITHKLINE S M IH1 TH K L AY2 N +SMITHKLINE'S S M IH1 TH K L AY2 N Z +SMITHS S M IH1 TH S +SMITHSON S M IH1 TH S AH0 N +SMITHSON'S S M IH1 TH S AH0 N Z +SMITHSONIAN S M IH0 TH S OW1 N IY0 AH0 N +SMITHSONIAN(1) S M IH0 S OW1 N IY0 AH0 N +SMITHSONIAN'S S M IH2 TH S OW1 N IY0 AH0 N Z +SMITHSONIAN'S(1) S M IH2 S OW1 N IY0 AH0 N Z +SMITHTOWN S M IH1 TH T AW2 N +SMITHWICK S M IH1 TH W IH2 K +SMITLEY S M IH1 T L IY0 +SMITS S M IH1 T S +SMITTEN S M IH1 T AH0 N +SMITTLE S M IH1 T AH0 L +SMITTY S M IH1 T IY0 +SMOAK S M OW1 K +SMOCK S M AA1 K +SMOG S M AA1 G +SMOGGIEST S M AA1 G IY0 AH0 S T +SMOGGY S M AO1 G IY0 +SMOKE S M OW1 K +SMOKED S M OW1 K T +SMOKEJUMPER S M OW1 K JH AH2 M P ER0 +SMOKEJUMPERS S M OW1 K JH AH2 M P ER0 Z +SMOKELESS S M OW1 K L AH0 S +SMOKER S M OW1 K ER0 +SMOKER'S S M OW1 K ER0 Z +SMOKERS S M OW1 K ER0 Z +SMOKERS' S M OW1 K ER0 Z +SMOKES S M OW1 K S +SMOKESCREEN S M OW1 K S K R IY2 N +SMOKESTACK S M OW1 K S T AE2 K +SMOKESTACKS S M OW1 K S T AE2 K S +SMOKEY S M OW1 K IY0 +SMOKING S M OW1 K IH0 NG +SMOKING'S S M OW1 K IH0 NG Z +SMOKY S M OW1 K IY0 +SMOLA S M OW1 L AA0 +SMOLAK S M OW1 L AA0 K +SMOLDER S M OW1 L D ER0 +SMOLDERING S M OW1 L D ER0 IH0 NG +SMOLEN S M AA1 L AH0 N +SMOLENSK S M OW0 L EH1 N S K +SMOLENSKI S M AH0 L EH1 N S K IY0 +SMOLEY S M OW1 L IY0 +SMOLIK S M OW1 L IH0 K +SMOLIN S M OW1 L IH0 N +SMOLINSKI S M AH0 L IH1 N S K IY0 +SMOLINSKY S M AH0 L IH1 N S K IY0 +SMOLKA S M OW1 L K AH0 +SMOOCH S M UW1 CH +SMOOCHES S M UW1 CH IH0 Z +SMOOT S M UW1 T +SMOOTH S M UW1 DH +SMOOTH-SHAVEN S M UW2 TH SH EY1 V AH0 N +SMOOTHED S M UW1 DH D +SMOOTHEN S M UW1 DH IH0 N +SMOOTHENS S M UW1 DH IH0 N Z +SMOOTHER S M UW1 DH ER0 +SMOOTHEST S M UW1 DH AH0 S T +SMOOTHING S M UW1 DH IH0 NG +SMOOTHLY S M UW1 DH L IY0 +SMOOTHNESS S M UW1 DH N AH0 S +SMOOTHS S M UW1 DH Z +SMOOTS S M UW1 T S +SMORGASBORD S M AO1 R G AH0 S B AO2 R D +SMOSH S M UH1 SH +SMOSHED S M UH1 SH T +SMOSHES S M UH1 SH AH0 Z +SMOSHING S M UH1 SH IH0 NG +SMOTHER S M AH1 DH ER0 +SMOTHERED S M AH1 DH ER0 D +SMOTHERING S M AH1 DH ER0 IH0 NG +SMOTHERMAN S M AH1 DH ER0 M AH0 N +SMOTHERMON S M AA1 TH ER0 M OW0 N +SMOTHERS S M AH1 DH ER0 Z +SMOTRICH S M AA1 T R IH0 K +SMOUSE S M AW1 S +SMOYER S M OY1 ER0 +SMREKAR S M R EH1 K ER0 +SMREKAR(1) S M ER1 IH0 K ER0 +SMS EH2 S EH2 M EH1 S +SMUCK S M AH1 K +SMUCKER S M AH1 K ER0 +SMUDGE S M AH1 JH +SMUDGED S M AH1 JH D +SMUG S M AH1 G +SMUGGLE S M AH1 G AH0 L +SMUGGLED S M AH1 G AH0 L D +SMUGGLER S M AH1 G L ER0 +SMUGGLER(1) S M AH1 G AH0 L ER0 +SMUGGLER'S S M AH1 G L ER0 Z +SMUGGLERS S M AH1 G L ER0 Z +SMUGGLERS(1) S M AH1 G AH0 L ER0 Z +SMUGGLERS' S M AH1 G L ER0 Z +SMUGGLERS'(1) S M AH1 G AH0 L ER0 Z +SMUGGLING S M AH1 G L IH0 NG +SMUGGLING(1) S M AH1 G AH0 L IH0 NG +SMUGLY S M AH1 G L IY0 +SMUGNESS S M AH1 G N AH0 S +SMULL S M AH1 L +SMULLEN S M AH1 L AH0 N +SMURF S M ER1 F +SMURFIT S M ER1 F IH0 T +SMURFS S M ER1 F S +SMUT S M AH1 T +SMUTTY S M AH1 T IY2 +SMYERS S M AY1 ER0 Z +SMYLIE S M IH1 L IY0 +SMYLY S M IH1 L IY0 +SMYRE S M AY1 R +SMYRNA S M ER1 N AH0 +SMYSER S M AY1 S ER0 +SMYTH S M AY1 TH +SMYTH(1) S M IH1 TH +SMYTHE S M AY1 DH +SNABEL S N AA1 B AH0 L +SNACK S N AE1 K +SNACKBAR S N AE1 K B AA0 R +SNACKED S N AE1 K T +SNACKING S N AE1 K IH0 NG +SNACKS S N AE1 K S +SNACKWELL S N AE1 K W EH2 L +SNACKWELL'S S N AE1 K W EH2 L Z +SNACKWELLS S N AE1 K W EH2 L Z +SNADER S N EY1 D ER0 +SNAFU S N AE1 F UW0 +SNAFUS S N AE1 F AH0 S +SNAG S N AE1 G +SNAGGED S N AE1 G D +SNAGGER S N AE1 G ER0 +SNAGGERS S N AE1 G ER0 Z +SNAGGING S N AE1 G IH0 NG +SNAGS S N AE1 G Z +SNAIL S N EY1 L +SNAIL'S S N EY1 L Z +SNAILS S N EY1 L Z +SNAKE S N EY1 K +SNAKE'S S N EY1 K S +SNAKEBITE S N EY1 K B AY2 T +SNAKEBITES S N EY1 K B AY2 T S +SNAKELIKE S N EY1 K L AY2 K +SNAKES S N EY1 K S +SNAKING S N EY1 K IH0 NG +SNAP S N AE1 P +SNAPCHAT S N AE1 P CH AE2 T +SNAPDRAGON S N AE1 P D R AE2 G AH0 N +SNAPDRAGONS S N AE1 P D R AE2 G AH0 N Z +SNAPE S N EY1 P +SNAPP S N AE1 P +SNAPPED S N AE1 P T +SNAPPER S N AE1 P ER0 +SNAPPIEST S N AE1 P IH0 EH2 S T +SNAPPING S N AE1 P IH0 NG +SNAPPLE S N AE1 P AH0 L +SNAPPLE'S S N AE1 P AH0 L Z +SNAPPLES S N AE1 P AH0 L Z +SNAPPY S N AE1 P IY0 +SNAPS S N AE1 P S +SNAPSHOT S N AE1 P SH AA2 T +SNAPSHOTS S N AE1 P SH AA2 T S +SNARE S N EH1 R +SNARED S N EH1 R D +SNARES S N EH1 R Z +SNARING S N EH1 R IH0 NG +SNARL S N AA1 R L +SNARLED S N AA1 R AH0 L D +SNARLING S N AA1 R L IH0 NG +SNARLS S N AA1 R L Z +SNARR S N AE1 R +SNARSKI S N AA1 R S K IY0 +SNATCH S N AE1 CH +SNATCHED S N AE1 CH T +SNATCHER S N AE1 CH ER0 +SNATCHERS S N AE1 CH ER0 Z +SNATCHES S N AE1 CH IH0 Z +SNATCHING S N AE1 CH IH0 NG +SNAVELY S N EY1 V L IY0 +SNAY S N EY1 +SNAZZIER S N AE1 Z IY0 ER0 +SNAZZY S N AE1 Z IY0 +SNEAD S N IY1 D +SNEAK S N IY1 K +SNEAKED S N IY1 K T +SNEAKER S N IY1 K ER0 +SNEAKERS S N IY1 K ER0 Z +SNEAKING S N IY1 K IH0 NG +SNEAKS S N IY1 K S +SNEAKY S N IY1 K IY0 +SNEARY S N IH1 R IY0 +SNEATH S N EH1 TH +SNECMA S N EH1 K M AA0 +SNEDAKER S N EH1 D AH0 K ER0 +SNEDDEN S N EH1 D AH0 N +SNEDDON S N EH1 D AH0 N +SNEDEGAR S N EH1 D IH0 G ER0 +SNEDEKER S N EH1 D IH0 K ER0 +SNEE S N IY1 +SNEED S N IY1 D +SNEER S N IH1 R +SNEERED S N IH1 R D +SNEERING S N IH1 R IH0 NG +SNEERINGER S N IH1 R IH0 N JH ER0 +SNEERS S N IH1 R Z +SNEEZE S N IY1 Z +SNEEZED S N IY1 Z D +SNEEZES S N IY1 Z IH0 Z +SNEEZING S N IY1 Z IH0 NG +SNEH S N EH1 +SNEIDER S N AY1 D ER0 +SNELGROVE S N EH1 L G R OW2 V +SNELL S N EH1 L +SNELLEN S N EH1 L AH0 N +SNELLENBERGER S N EH1 L AH0 N B ER0 G ER0 +SNELLER S N EH1 L ER0 +SNELLGROVE S N EH1 L G R OW2 V +SNELLING S N EH1 L IH0 NG +SNELLINGS S N EH1 L IH0 NG Z +SNELSON S N EH1 L S AH0 N +SNETHEN S N EH1 TH AH0 N +SNIA S N IY1 AH0 +SNICKER S N IH1 K ER0 +SNICKERED S N IH1 K ER0 D +SNICKERING S N IH1 K ER0 IH0 NG +SNICKERS S N IH1 K ER0 Z +SNIDE S N AY1 D +SNIDER S N AY1 D ER0 +SNIDOW S N IH1 D OW0 +SNIEGOWSKI S N IY0 G AO1 F S K IY0 +SNIFF S N IH1 F +SNIFFED S N IH1 F T +SNIFFEN S N IH1 F AH0 N +SNIFFER S N IH1 F ER0 +SNIFFIER S N IH1 F IY0 ER0 +SNIFFIEST S N IH1 F IY0 AH0 S T +SNIFFILY S N IH1 F AH0 L IY0 +SNIFFING S N IH1 F IH0 NG +SNIFFLE S N IH1 F AH0 L +SNIFFLER S N IH1 F L ER0 +SNIFFLES S N IH1 F AH0 L Z +SNIFFLING S N IH1 F L IH0 NG +SNIFFS S N IH1 F S +SNIFFY S N IH1 F IY0 +SNIFTER S N IH1 F T ER0 +SNIFTERS S N IH1 F T ER0 Z +SNIP S N IH1 P +SNIPE S N AY1 P +SNIPED S N AY1 P T +SNIPER S N AY1 P ER0 +SNIPER'S S N AY1 P ER0 Z +SNIPERS S N AY1 P ER0 Z +SNIPERS' S N AY1 P ER0 Z +SNIPES S N AY1 P S +SNIPING S N AY1 P IH0 NG +SNIPPET S N IH1 P AH0 T +SNIPPETS S N IH1 P AH0 T S +SNIPS S N IH1 P S +SNITCH S N IH1 CH +SNITCHING S N IH1 CH IH0 NG +SNITKER S N IH1 T K ER0 +SNITZER S N IH1 T Z ER0 +SNIVELY S N AY1 V L IY0 +SNOB S N AA1 B +SNOBBERY S N AA1 B ER0 IY0 +SNOBBISH S N AA1 B IH0 SH +SNOBBY S N AA1 B IY0 +SNOBS S N AA1 B Z +SNODDERLY S N AA1 D ER0 L IY0 +SNODDY S N AA1 D IY0 +SNODGRASS S N AA1 D G R AE2 S +SNOG S N AO1 G +SNOHOMISH S N AA1 HH AH0 M IH0 SH +SNOKE S N OW1 K +SNOOK S N UH1 K +SNOOKER S N UH1 K ER0 +SNOOKERED S N UH1 K ER0 D +SNOOKS S N UH1 K S +SNOOP S N UW1 P +SNOOPING S N UW1 P IH0 NG +SNOOPS S N UW1 P S +SNOOPY S N UW1 P IY0 +SNOOTY S N UW1 T IY0 +SNOOZE S N UW1 Z +SNOOZING S N UW1 Z IH0 NG +SNORE S N AO1 R +SNORER S N AO1 R ER0 +SNORERS S N AO1 R ER0 Z +SNORES S N AO1 R Z +SNORING S N AO1 R IH0 NG +SNORKEL S N AO1 R K AH0 L +SNORKELING S N AO1 R K AH0 L IH2 NG +SNORT S N AO1 R T +SNORTED S N AO1 R T IH0 D +SNORTER S N AO1 R T ER0 +SNORTERS S N AO1 R T ER0 Z +SNORTING S N AO1 R T IH0 NG +SNORTS S N AO1 R T S +SNOT S N AO1 T +SNOT-FACE S N AO1 T F EY2 S +SNOT-FACED S N AO1 T F EY2 S T +SNOTTY S N AO1 T IY2 +SNOUFFER S N OW1 F ER0 +SNOUT S N AW1 T +SNOUT'S S N AW1 T S +SNOUTS S N AW1 T S +SNOVER S N OW1 V ER0 +SNOW S N OW1 +SNOW'S S N OW1 Z +SNOWBALL S N OW1 B AO2 L +SNOWBALL'S S N OW1 B AO2 L Z +SNOWBALLED S N OW1 B AO2 L D +SNOWBALLING S N OW1 B AO2 L IH0 NG +SNOWBALLS S N OW1 B AO2 L Z +SNOWBERGER S N OW1 B ER0 G ER0 +SNOWBIRD S N OW1 B ER2 D +SNOWBIRDS S N OW1 B ER2 D Z +SNOWBOARD S N OW1 B AO2 R D +SNOWBOARDER S N OW1 B AO2 R D ER0 +SNOWBOARDERS S N OW1 B AO2 R D ER0 Z +SNOWBOARDS S N OW1 B AO2 R D Z +SNOWBOUND S N OW1 B AW2 N D +SNOWDEN S N OW1 D AH0 N +SNOWDON S N OW1 D AH0 N +SNOWE S N OW1 +SNOWED S N OW1 D +SNOWFALL S N OW1 F AA0 L +SNOWFALLS S N OW1 F AA0 L Z +SNOWFLAKE S N OW1 F L EY2 K +SNOWFLAKES S N OW1 F L EY2 K S +SNOWING S N OW1 IH0 NG +SNOWMAN S N OW1 M AE2 N +SNOWMOBILE S N OW1 M OW0 B IY2 L +SNOWMOBILES S N OW1 M OW0 B IY2 L Z +SNOWPLOW S N OW1 P L AW2 +SNOWPLOWS S N OW1 P L AW2 Z +SNOWS S N OW1 Z +SNOWSHOE S N OW1 SH UW2 +SNOWSHOES S N OW1 SH UW2 Z +SNOWSTORM S N OW1 S T AO2 R M +SNOWSTORMS S N OW1 S T AO2 R M Z +SNOWY S N OW1 IY0 +SNUB S N AH1 B +SNUBBED S N AH1 B D +SNUBBING S N AH1 B IH0 NG +SNUBS S N AH1 B Z +SNUCK S N AH1 K +SNUFF S N AH1 F +SNUFFED S N AH1 F T +SNUFFER S N AH1 F ER0 +SNUFFING S N AH1 F IH0 NG +SNUFFS S N AH1 F S +SNUG S N AH1 G +SNUGGING S N AH1 G IH0 NG +SNUGGLE S N AH1 G AH0 L +SNUGGLED S N AH1 G AH0 L D +SNUGGS S N AH1 G Z +SNUGLY S N AH1 G L IY0 +SNYDER S N AY1 D ER0 +SNYDER'S S N AY1 D ER0 Z +SNYDERGENERAL S N AY2 D ER0 JH EH1 N ER0 AH0 L +SO S OW1 +SO'S S OW1 Z +SO-CALLED S OW1 K AO1 L D +SO-SO S OW1 S OW1 +SOADY S OW1 D IY0 +SOAK S OW1 K +SOAKED S OW1 K T +SOAKER S OW1 K ER0 +SOAKING S OW1 K IH0 NG +SOAKS S OW1 K S +SOAP S OW1 P +SOAPBOX S OW1 P B AA2 K S +SOAPS S OW1 P S +SOAPY S OW1 P IY0 +SOAR S AO1 R +SOARD S AO1 R D +SOARED S AO1 R D +SOARES S AO1 R EH0 S +SOARING S AO1 R IH0 NG +SOARS S AO1 R Z +SOAVE S OW1 V +SOB S AA1 B +SOBBED S AA1 B D +SOBBING S AA1 B IH0 NG +SOBBINGLY S AA1 B IH0 NG L IY0 +SOBCZAK S AA1 B CH AE0 K +SOBCZYK S AA1 B CH IH0 K +SOBECK S OW1 B EH2 K +SOBECKI S AH0 B EH1 T S K IY0 +SOBEK S OW1 B IH0 K +SOBEL S OW1 B AH0 L +SOBELMAN S OW1 B AH0 L M AH0 N +SOBER S OW1 B ER0 +SOBERED S OW1 B ER0 D +SOBERING S OW1 B ER0 IH0 NG +SOBERLY S OW1 B ER0 L IY0 +SOBERS S OW1 B ER0 Z +SOBEY S OW1 B IY0 +SOBIBOR S OW0 B IY1 B AO0 R +SOBIBOR(1) S OW0 B IH1 B AO0 R +SOBIECH S AA1 B IY0 HH +SOBIESKI S OW2 B IY0 EH1 S K IY0 +SOBIL S OW1 B AH0 L +SOBIL'S S OW1 B AH0 L Z +SOBILS S OW1 B AH0 L Z +SOBIN S OW1 B IH0 N +SOBKOWIAK S AH0 B K OW1 V IH0 AE2 K +SOBLE S OW1 B AH0 L +SOBOCINSKI S AO2 B AH0 CH IH1 N S K IY0 +SOBOL S OW1 B AH0 L +SOBOLESKI S AH0 B AH0 L EH1 S K IY0 +SOBOLEWSKI S AH0 B AH0 L EH1 F S K IY0 +SOBOLIK S AH0 B OW1 L IH0 K +SOBON S OW0 B AO1 N +SOBOTA S OW0 B OW1 T AH0 +SOBOTKA S OW0 B OW1 T K AH0 +SOBOTTA S OW0 B OW1 T AH0 +SOBRIETY S OW0 B R AY1 AH0 T IY0 +SOBRIQUET S OW1 B R AH0 K EY2 +SOBRIQUET(1) S OW2 B R AH0 K EH1 T +SOBS S AA1 B Z +SOCAL S OW1 K AH0 L +SOCALLED S OW1 K AA2 L D +SOCANAV S AA1 K AH0 N AA0 V +SOCARRAS S OW0 K AA1 R AA0 Z +SOCCER S AA1 K ER0 +SOCCER'S S AA1 K ER0 Z +SOCCI S OW1 CH IY0 +SOCHA S OW1 CH AH0 +SOCHACKI S AH0 CH AE1 K IY0 +SOCHET S OW0 SH EY1 +SOCHI S OW1 CH IY0 +SOCHOR S AA1 K ER0 +SOCIA S OW1 CH AH0 +SOCIABLE S OW1 SH AH0 B AH0 L +SOCIAL S OW1 SH AH0 L +SOCIALISM S OW1 SH AH0 L IH2 Z AH0 M +SOCIALIST S OW1 SH AH0 L IH0 S T +SOCIALISTIC S OW2 SH AH0 L IH1 S T IH0 K +SOCIALISTS S OW1 SH AH0 L IH0 S T S +SOCIALISTS' S OW1 SH AH0 L IH0 S T S +SOCIALITE S OW1 SH AH0 L AY2 T +SOCIALITES S OW1 SH AH0 L AY2 T S +SOCIALIZATION S OW2 SH AH0 L IH0 Z EY1 SH AH0 N +SOCIALIZE S OW1 SH AH0 L AY2 Z +SOCIALIZED S OW1 SH AH0 L AY2 Z D +SOCIALIZING S OW1 SH AH0 L AY2 Z IH0 NG +SOCIALLY S OW1 SH AH0 L IY0 +SOCIEDAD S OW2 S IY0 D AE1 D +SOCIETA S OW2 S IY0 EH1 T AH0 +SOCIETAL S AH0 S AY1 IH0 T AH0 L +SOCIETE S OW2 S IY0 EH0 T EY1 +SOCIETIES S AH0 S AY1 IH0 T IY0 Z +SOCIETY S OW0 S AY1 IH0 T IY0 +SOCIETY'S S OW0 S AY1 IH0 T IY0 Z +SOCIO S OW1 S IY0 OW0 +SOCIOECONOMIC S OW0 S IY2 OW2 EH2 K AH0 N AA1 M IH0 K +SOCIOLOGICAL S OW2 S IY0 AH0 L AA1 JH IH0 K AH0 L +SOCIOLOGIST S OW2 S IY0 AA1 L AH0 JH IH0 S T +SOCIOLOGISTS S OW2 S IY0 AA1 L AH0 JH IH0 S T S 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OW2 +SOTER S OW1 T ER0 +SOTHEBY S AA1 TH AH0 B IY2 +SOTHEBY'S S AA1 TH AH0 B IY0 Z +SOTO S OW1 T OW0 +SOTOLONGO S OW2 T OW0 L OW1 NG G OW2 +SOTOMAYOR S OW2 T OW0 M EY0 AO1 R +SOTTI S OW1 T IY2 +SOTTILE S OW1 T AH0 L +SOUCCAR S UW1 K AA2 R +SOUCEK S OW1 S IH0 K +SOUCIE S UW1 S IY2 +SOUCY S OW1 S IY0 +SOUDER S AW1 D ER0 +SOUDERS S AW1 D ER0 Z +SOUERS S AW1 ER0 Z +SOUFFLE S UW0 F L EY1 +SOUGH S AW1 F +SOUGH(1) S OW1 +SOUGHT S AO1 T +SOUK S UW1 K +SOUKUP S AW1 K AH0 P +SOUL S OW1 L +SOULE S AW1 L +SOULES S UW1 L Z +SOULFUL S OW1 L F AH0 L +SOULIER S UW1 L IY2 ER0 +SOULJAH S OW1 L Y AA2 +SOULLESS S OW1 L L AH0 S +SOULLIERE S UW1 L IY0 EH0 R +SOULS S OW1 L Z +SOUND S AW1 N D +SOUND'S S AW1 N D Z +SOUNDBITE S AW1 N D B AY2 T +SOUNDBITES S AW1 N D B AY2 T S +SOUNDED S AW1 N D IH0 D +SOUNDER S AW1 N D ER0 +SOUNDEST S AW1 N D IH0 S T +SOUNDING S AW1 N D IH0 NG +SOUNDINGS S AW1 N D IH0 NG Z +SOUNDLY S AW1 N D L IY0 +SOUNDNESS S AW1 N D N AH0 S +SOUNDS S AW1 N D Z +SOUNDS(1) S AW1 N Z +SOUNDSCAN S AW1 N D S K AE2 N +SOUNDTRACK S AW1 N D T R AE2 K +SOUNDTRACK(1) S AW1 N T R AE2 K +SOUNDTRACKS S AW1 N D T R AE2 K S +SOUNDTRACKS(1) S AW1 N T R AE2 K S +SOUNDVIEW S AW1 N D V Y UW2 +SOUP S UW1 P +SOUP'S S UW1 P S +SOUPED S UW1 P T +SOUPS S UW1 P S +SOUPY S UW1 P IY2 +SOUR S AW1 ER0 +SOUR(1) S AW1 R +SOURBY S AW1 R B IY0 +SOURCE S AO1 R S +SOURCE'S S AO1 R S IH0 Z +SOURCEBOOK S AO1 R S B UH2 K +SOURCES S AO1 R S AH0 Z +SOURCES' S AO1 R S AH0 Z +SOURCING S AO1 R S IH0 NG +SOURED S AW1 ER0 D +SOURING S AW1 ER0 IH0 NG +SOURIS S UW1 R IH0 S +SOURROUILLE S AO0 R UW1 IY0 +SOURS S AW1 ER0 Z +SOURS(1) S AW1 R Z +SOUS S UW1 Z +SOUSA S UW1 Z AH0 +SOUSA'S S UW1 Z AH0 Z +SOUSAPHONE S UW1 Z AH0 F OW2 N +SOUSLEY S AW1 S L IY0 +SOUTAR S UW0 T AA1 R +SOUTER S UW1 T ER0 +SOUTER(1) S AW1 T ER0 +SOUTH S AW1 TH +SOUTH'S S AW1 TH S +SOUTHALL S AW1 TH AH0 L +SOUTHAM S AW1 TH AH0 M +SOUTHAMPTON S AW2 TH HH AE1 M P T AH0 N +SOUTHARD S AW1 TH ER0 D +SOUTHBOUND S AW1 TH B AW2 N D +SOUTHDOWN S AW1 TH D AW2 N 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P EY1 S K R AE2 F T +SPACECRAFT'S S P EY1 S K R AE2 F T S +SPACED S P EY1 S T +SPACEHAB S P EY1 S HH AE2 B +SPACEK S P AA1 CH EH2 K +SPACEK(1) S P AA1 S EH2 K +SPACELINK S P EY1 S L IH2 NG K +SPACENET S P EY1 S N EH2 T +SPACEPORT S P EY1 S P AO2 R T +SPACEPORTS S P EY1 S P AO2 R T S +SPACER S P EY1 S ER0 +SPACERS S P EY1 S ER0 Z +SPACES S P EY1 S AH0 Z +SPACES(1) S P EY1 S IH0 Z +SPACESHIP S P EY1 S SH IH2 P +SPACESHIPS S P EY1 S SH IH2 P S +SPACESUIT S P EY1 S UW2 T +SPACESUITS S P EY1 S UW2 T S +SPACEWALK S P EY1 S W AA2 K +SPACEWALKING S P EY1 S W AA2 K IH0 NG +SPACEWALKS S P EY1 S W AA2 K S +SPACEY S P EY1 S IY0 +SPACIAL S P EY1 SH AH0 L +SPACING S P EY1 S IH0 NG +SPACIOUS S P EY1 SH AH0 S +SPACK S P AE1 K +SPACKLE S P AE1 K AH0 L +SPACKMAN S P AE1 K M AH0 N +SPADA S P AA1 D AH0 +SPADACCINI S P AA0 D AA0 CH IY1 N IY0 +SPADAFORA S P AA0 D AA0 F AO1 R AH0 +SPADAFORE S P AA0 D AO1 F AO0 R +SPADARO S P AA0 D AA1 R OW0 +SPADE S P EY1 D +SPADER S P EY1 D ER0 +SPADES S P EY1 D Z 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AH0 L D +SPARKLES S P AA1 R K AH0 L Z +SPARKLING S P AA1 R K L IH0 NG +SPARKLING(1) S P AA1 R K AH0 L IH0 NG +SPARKLY S P AA1 R K L IY0 +SPARKMAN S P AA1 R K M AH0 N +SPARKS S P AA1 R K S +SPARKY S P AA1 R K IY0 +SPARLIN S P AA1 R L IH0 N +SPARLING S P AA1 R L IH0 NG +SPARR S P AE1 R +SPARRED S P AA1 R D +SPARRING S P AA1 R IH0 NG +SPARROW S P EH1 R OW0 +SPARROWS S P EH1 R OW0 Z +SPARSE S P AA1 R S +SPARSELY S P AA1 R S L IY0 +SPARTA S P AA1 R T AA0 +SPARTACUS S P AA1 R T AA0 K AH0 S +SPARTAN S P AA1 R T AH0 N +SPARTANBURG S P AA1 R T AH0 N B ER2 G +SPARTANS S P AA1 R T AH0 N Z +SPARTECH S P AA1 R T EH2 K +SPARTZ S P AA1 R T S +SPAS S P AA1 Z +SPASM S P AE1 Z AH0 M +SPASMODIC S P AE0 Z M AO1 D IH0 K +SPASMODICALLY S P AE0 Z M AO1 D IH0 K L IY0 +SPASMS S P AE1 Z AH0 M Z +SPASSO S P AE1 S OW2 +SPASTIC S P AE1 S T IH0 K +SPAT S P AE1 T +SPATAFORA S P AA0 T AA0 F AO1 R AA2 +SPATAFORE S P AE1 T AH0 F AO2 R +SPATARO S P AA0 T AA1 R OW2 +SPATE S P EY1 T +SPATES S P EY1 T S +SPATH S P AE1 TH +SPATIAL S P EY1 SH AH0 L +SPATOLA S P AA0 T OW1 L AA0 +SPATS S P AE1 T S +SPATTER S P AE1 T ER0 +SPATTERED S P AE1 T ER0 D +SPATTERING S P AE1 T ER0 IH0 NG +SPATTERS S P AE1 T ER0 Z +SPATULA S P AE1 CH UH2 L AH0 +SPATULAS S P AE1 CH UH2 L AH0 Z +SPATZ S P AE1 T S +SPAUGH S P AO1 +SPAULDING S P AO1 L D IH0 NG +SPAUR S P AO1 R +SPAVO S P AA1 V OW2 +SPAW S P AO1 +SPAWN S P AA1 N +SPAWN(1) S P AO1 N +SPAWNED S P AO1 N D +SPAWNING S P AA1 N IH0 NG +SPAWNING(1) S P AO1 N IH0 NG +SPAWNS S P AA1 N Z +SPAWNS(1) S P AO1 N Z +SPAY S P EY1 +SPAYD S P EY1 D +SPAYDE S P EY1 D +SPAYED S P EY1 D +SPAZ S P AE1 Z +SPAZES S P AE1 Z EH0 Z +SPAZIANI S P AA0 Z IY0 AA1 N IY2 +SPEAGLE S P IY1 G AH0 L +SPEAK S P IY1 K +SPEAK-EASY S P IY1 K IY2 Z IY2 +SPEAKE S P IY1 K +SPEAKER S P IY1 K ER0 +SPEAKER'S S P IY1 K ER0 Z +SPEAKERS S P IY1 K ER0 Z +SPEAKERSHIP S P IY1 K ER0 SH IH2 P +SPEAKES S P IY1 K S +SPEAKES'S S P IY1 K S IH0 Z +SPEAKING S P IY1 K IH0 NG +SPEAKMAN S P IY1 K M AH0 N +SPEAKS S P IY1 K S +SPEAR S P IH1 R +SPEARE S P IY1 R +SPEARHEAD S P IH1 R HH EH2 D +SPEARHEADED S P IH1 R HH EH2 D IH0 D +SPEARHEADING S P IH1 R HH EH2 D IH0 NG +SPEARING S P IH1 R IH0 NG +SPEARMAN S P IH1 R M AH0 N +SPEARS S P IH1 R Z +SPEAS S P IY1 Z +SPEASE S P IY1 Z +SPEC S P EH1 K +SPECHT S P EH1 K T +SPECIAL S P EH1 SH AH0 L +SPECIAL'S S P EH1 SH AH0 L Z +SPECIALE S P EH1 CH AH0 L IY0 +SPECIALIST S P EH1 SH AH0 L IH0 S T +SPECIALISTS S P EH1 SH AH0 L IH0 S T S +SPECIALISTS' S P EH1 SH AH0 L IH0 S T S +SPECIALITIES S P EH1 SH AH0 L T IY0 Z +SPECIALITY S P EH2 SH IY0 AE1 L IH0 T IY0 +SPECIALIZATION S P EH2 SH AH0 L AH0 Z EY1 SH AH0 N +SPECIALIZE S P EH1 SH AH0 L AY2 Z +SPECIALIZED S P EH1 SH AH0 L AY2 Z D +SPECIALIZES S P EH1 SH AH0 L AY2 Z IH0 Z +SPECIALIZING S P EH1 SH AH0 L AY2 Z IH0 NG +SPECIALLY S P EH1 SH AH0 L IY0 +SPECIALLY(1) S P EH1 SH L IY0 +SPECIALS S P EH1 SH AH0 L Z +SPECIALTIES S P EH1 SH AH0 L T IY0 Z +SPECIALTY S P EH1 SH AH0 L T IY0 +SPECIALTY(1) S P EY1 SH AH0 L T IY0 +SPECIES S P IY1 SH IY0 Z +SPECIES' S P IY1 SH IY0 Z +SPECIFIC S P AH0 S IH1 F IH0 K +SPECIFIC(1) S P IH0 S IH1 F IH0 K +SPECIFICALLY S P AH0 S IH1 F IH0 K L IY0 +SPECIFICATION S P EH2 S IH0 F IH0 K EY1 SH AH0 N +SPECIFICATIONS S P EH2 S AH0 F AH0 K EY1 SH AH0 N Z +SPECIFICITY S P EH2 S AH0 F IH1 S AH0 T IY0 +SPECIFICS S P IH0 S IH1 F IH0 K S +SPECIFIED S P EH1 S AH0 F AY2 D +SPECIFIES S P EH1 S AH0 F AY2 Z +SPECIFY S P EH1 S AH0 F AY2 +SPECIFYING S P EH1 S AH0 F AY2 IH0 NG +SPECIMEN S P EH1 S AH0 M AH0 N +SPECIMENS S P EH1 S AH0 M AH0 N Z +SPECIOUS S P IY1 SH AH0 S +SPECK S P EH1 K +SPECKER S P EH1 K ER0 +SPECKLE S P EH1 K AH0 L +SPECKLED S P EH1 K AH0 L D +SPECKMAN S P EH1 K M AH0 N +SPECKS S P EH1 K S +SPECS S P EH1 K S +SPECTACLE S P EH1 K T AH0 K AH0 L +SPECTACLES S P EH1 K T AH0 K AH0 L Z +SPECTACULAR S P EH0 K T AE1 K Y AH0 L ER0 +SPECTACULARLY S P EH0 K T AE1 K Y AH0 L ER0 L IY0 +SPECTATOR S P EH1 K T EY0 T ER0 +SPECTATORS S P EH1 K T EY0 T ER0 Z +SPECTER S P EH1 K T ER0 +SPECTER'S S P EH1 K T ER0 Z +SPECTHRIE S P EH1 K TH R IY0 +SPECTOR S P EH1 K T ER0 +SPECTRA S P EH1 K T R AH0 +SPECTRA'S S P EH1 K T R AH0 Z +SPECTRADYNE S P EH1 K T R AH0 D AY2 N +SPECTRAL S P EH1 K T R AH0 L +SPECTRAMED S P EH1 K T R AH0 M D +SPECTRAMED(1) S P EH1 K T R AH0 M EH2 D +SPECTRAN S P EH1 K T R AE2 N +SPECTRAVISION S P EH1 K T R AH0 V IH2 ZH AH0 N +SPECTRE S P EH1 K T ER0 +SPECTROGRAPH S P EH1 K T R AH0 G R AE2 F +SPECTROMETER S P EH0 K T R AA1 M AH0 T ER0 +SPECTROMETRY S P EH0 K T R AA1 M AH0 T R IY0 +SPECTROSCOPY S P EH0 K T R AA1 S K AH0 P IY0 +SPECTRUM S P EH1 K T R AH0 M +SPECTRUM'S S P EH1 K T R AH0 M Z +SPECTRUMS S P EH1 K T R AH0 M Z +SPECULATE S P EH1 K Y AH0 L EY2 T +SPECULATED S P EH1 K Y AH0 L EY2 T IH0 D +SPECULATES S P EH1 K Y AH0 L EY2 T S +SPECULATING S P EH1 K Y AH0 L EY2 T IH0 NG +SPECULATION S P EH2 K Y AH0 L EY1 SH AH0 N +SPECULATIONS S P EH2 K Y AH0 L EY1 SH AH0 N Z +SPECULATIVE S P EH1 K Y AH0 L AH0 T IH0 V +SPECULATOR S P EH1 K Y AH0 L EY2 T ER0 +SPECULATORS S P EH1 K Y AH0 L EY2 T ER0 Z +SPECULATORS' S P EH1 K Y AH0 L ER0 T EY2 Z +SPED S P EH1 D +SPEECE S P IY1 S +SPEECH S P IY1 CH +SPEECHES S P IY1 CH AH0 Z +SPEECHES(1) S P IY1 CH IH0 Z +SPEECHIFY S P IY1 CH AH0 F AY2 +SPEECHIFYING S P IY1 CH AH0 F AY2 IH0 NG +SPEECHLESS S P IY1 CH L AH0 S +SPEECHWRITER S P IY1 CH R AY2 T ER0 +SPEECHWRITERS S P IY1 CH R AY2 T ER0 Z +SPEED S P IY1 D +SPEEDBOAT S P IY1 D B OW2 T +SPEEDBOATS S P IY1 D B OW2 T S +SPEEDED S P IY1 D IH0 D +SPEEDER S P IY1 D ER0 +SPEEDERS S P IY1 D ER0 Z +SPEEDIER S P IY1 D IY0 ER0 +SPEEDILY S P IY1 D AH0 L IY0 +SPEEDING S P IY1 D IH0 NG +SPEEDOMETER S P IY0 D AA1 M AH0 T ER0 +SPEEDRING S P IY1 D R IH2 NG +SPEEDS S P IY1 D Z +SPEEDSKATE S P IY1 D S K EY2 T +SPEEDSKATING S P IY1 D S K EY2 T IH0 NG +SPEEDUP S P IY1 D AH2 P +SPEEDWAY S P IY1 D W EY2 +SPEEDY S P IY1 D IY2 +SPEEGLE S P IY1 G AH0 L +SPEELMAN S P IY1 L M AH0 N +SPEER S P IH1 R +SPEES S P IY1 Z +SPEGAL S P IY1 G AH0 L +SPEHAR S P EH1 HH ER0 +SPEICH S P AY1 K +SPEICHER S P AY1 K ER0 +SPEIDEL S P AY1 D AH0 L +SPEIER S P AY1 ER0 +SPEIGHT S P EY1 T +SPEIGHTS S P EY1 T S +SPEIGNER S P AY1 G N ER0 +SPEIR S P IH1 R +SPEIRS S P IH1 R Z +SPEISER S P AY1 Z ER0 +SPEKTR S P EH1 K T ER0 +SPEKTR'S S P EH1 K T ER0 Z +SPELL S P EH1 L +SPELLACY S P EH1 L AH0 S IY0 +SPELLBINDING S P EH1 L B AY2 N D IH0 NG +SPELLBOUND S P EH1 L B AW2 N D +SPELLED S P EH1 L D +SPELLER S P EH1 L ER0 +SPELLERS S P EH1 L ER0 Z +SPELLING S P EH1 L IH0 NG +SPELLING'S S P EH1 L IH0 NG Z +SPELLINGS S P EH1 L IH0 NG Z +SPELLMAN S P EH1 L M AH0 N +SPELLMAN'S S P EH1 L M AH0 N Z +SPELLMEYER S P EH1 L M AY0 ER0 +SPELLMEYER'S S P EH1 L M AY0 ER0 Z +SPELLS S P EH1 L Z +SPELMAN S P EH1 L M AH0 N +SPELTZ S P EH1 L T S +SPELUNK S P AH0 L AH1 NG K +SPELUNKED S P AH0 L AH1 NG K T +SPELUNKER S P AH0 L AH1 NG K ER0 +SPELUNKERS S P AH0 L AH1 NG K ER0 Z +SPELUNKING S P AH0 L AH1 NG K IH0 NG +SPELUNKS S P AH0 L AH1 NG K S +SPENCE S P EH1 N S +SPENCER S P EH1 N S ER0 +SPENCER'S S P EH1 N S ER0 Z +SPENCERS S P EH1 N S ER0 Z +SPEND S P EH1 N D +SPENDABLE S P EH1 N D AH0 B AH0 L +SPENDER S P EH1 N D ER0 +SPENDERS S P EH1 N D ER0 Z +SPENDING S P EH1 N D IH0 NG +SPENDLEY S P EH1 N D L IY0 +SPENDLOVE S P EH1 N D L AH2 V +SPENDS S P EH1 N D Z +SPENDS(1) S P EH1 N Z +SPENDTHRIFT S P EH1 N D TH R IH2 F T +SPENGLER S P IH1 NG AH0 L ER0 +SPENGLER(1) S P IH1 NG L ER0 +SPENNER S P EH1 N ER0 +SPENO S P EH1 N OW0 +SPENS S P EH1 N S +SPENSER S P EH1 N S ER0 +SPENSER'S S P EH1 N S ER0 Z +SPENSERS S P EH1 N S ER0 Z +SPENT S P EH1 N T +SPERA S P EH1 R AH0 +SPERANZA S P ER0 AA1 N Z AH0 +SPERBECK S P ER1 B EH0 K +SPERBER S P ER1 B ER0 +SPERDUTO S P ER0 D UW1 T OW0 +SPERL S P ER1 L +SPERLE S P ER1 L +SPERLICH S P ER1 L IH0 K +SPERLING S P ER1 L IH0 NG +SPERM S P ER1 M +SPERMS S P ER1 M Z +SPERO S P EH1 R OW0 +SPEROS S P EH1 R OW0 Z +SPERRAZZA S P ER0 AA1 T S AH0 +SPERRFRIST S P EH1 R F R IH0 S T +SPERRY S P EH1 R IY0 +SPESSARD S P EH1 S ER0 D +SPETH S P EH1 TH +SPETHMANN S P EH1 TH M AH0 N +SPETSNAZ S P EH1 T S N AE0 Z +SPEVAK S P EH1 V AH0 K +SPEW S P Y UW1 +SPEWED S P Y UW1 D +SPEWING S P Y UW1 IH0 NG +SPEWS S P Y UW1 Z +SPEY S P EY1 +SPEYER S P EY1 ER0 +SPEZIALE S P EH0 Z IY0 AA1 L IY0 +SPEZZANO S P EH0 T S AA1 N OW0 +SPHAR S F AA1 R +SPHERE S F IH1 R +SPHERES S F IH1 R Z +SPHERICAL S F EH1 R IH0 K AH0 L +SPHEROID S F IH1 R OY2 D +SPHINCTER S F IH1 NG K T ER0 +SPHINCTERS S F IH1 NG K T ER0 Z +SPHINX S F IH1 NG K S +SPIC S P IH1 K +SPICE S P AY1 S +SPICED S P AY1 S T +SPICELAND S P AY1 S L AE2 N D +SPICER S P AY1 S ER0 +SPICES S P AY1 S AH0 Z +SPICES(1) S P AY1 S IH0 Z +SPICEY S P AY1 S IY0 +SPICHER S P IH1 CH ER0 +SPICING S P AY1 S IH0 NG +SPICKARD S P IH1 K ER0 D +SPICKLER S P IH1 K L ER0 +SPICUZZA S P IY0 K UW1 T S AH0 +SPICY S P AY1 S IY0 +SPIDEL S P IH1 D AH0 L +SPIDELL S P IH1 D AH0 L +SPIDER S P AY1 D ER0 +SPIDER-MAN S P AY1 D ER0 M AE0 N +SPIDERMAN S P AY1 D ER0 M AE0 N +SPIDERS S P AY1 D ER0 Z +SPIDLE S P AY1 D AH0 L +SPIE S P IY1 +SPIED S P AY1 D +SPIEGEL S P IY1 G AH0 L +SPIEGELBERG S P IY1 G AH0 L B ER0 G +SPIEGELMAN S P IY1 G AH0 L M AH0 N +SPIEGLER S P IY1 G L ER0 +SPIEKER S P IY1 K ER0 +SPIEL S P IY1 L +SPIELBERG S P IY1 L B ER0 G +SPIELBERG'S S P IY1 L B ER0 G Z +SPIELBERGER S P IY1 L B ER0 G ER0 +SPIELER S P IY1 L ER0 +SPIELMAN S P IY1 L M AH0 N +SPIELMANN S P IY1 L M AH0 N +SPIELVOGEL S P IY1 L V OW2 G AH0 L +SPIER S P AY1 ER0 +SPIERING S P AY1 ER0 IH0 NG +SPIERS S P AY1 ER0 Z +SPIES S P AY1 Z +SPIESS S P IY1 Z +SPIETH S P AY1 AH0 TH +SPIEWAK S P IY1 W AE2 K +SPIFFING S P IH1 F IH0 NG +SPIFFY S P IH1 F IY0 +SPIGHT S P AY1 T +SPIGNER S P AY1 G N ER0 +SPIGOT S P IH1 G AH0 T +SPIGOTS S P IH1 G AH0 T S +SPIKE S P AY1 K +SPIKED S P AY1 K T +SPIKER S P AY1 K ER0 +SPIKES S P AY1 K S +SPIKING S P AY1 K IH0 NG +SPIKY S P AY1 K IY0 +SPILDE S P IH1 L D +SPILKER S P IH1 L K ER0 +SPILL S P IH1 L +SPILL'S S P IH1 L Z +SPILLAGE S P IH1 L IH0 JH +SPILLANE S P IH1 L AH0 N +SPILLED S P IH1 L D +SPILLER S P IH1 L ER0 +SPILLERS S P IH1 L ER0 Z +SPILLING S P IH1 L IH0 NG +SPILLMAN S P IH1 L M AH0 N +SPILLOVER S P IH1 L OW2 V ER0 +SPILLS S P IH1 L Z +SPILLWAY S P IH1 L W EY2 +SPILMAN S P IH1 L M AH0 N +SPILOTRO S P IH0 L AA1 T R OW0 +SPILT S P IH1 L T +SPIN S P IH1 N +SPINA S P IY1 N AH0 +SPINACH S P IH1 N AH0 CH +SPINAL S P AY1 N AH0 L +SPINALE S P IY0 N AA1 L IY0 +SPINDEL S P IH1 N D AH0 L +SPINDLE S P IH1 N D AH0 L +SPINDLER S P IH1 N D AH0 L ER0 +SPINDLER(1) S P IH1 N D L ER0 +SPINE S P AY1 N +SPINELESS S P AY1 N L AH0 S +SPINELLA S P IH0 N EH1 L AH0 +SPINELLI S P IH0 N EH1 L IY0 +SPINELLO S P IH0 N EH1 L OW0 +SPINES S P AY1 N Z +SPINFIZZ S P IH1 N F IH0 Z +SPINIFEX S P IH1 N IH0 F EH0 K S +SPINK S P IH1 NG K +SPINKS S P IH1 NG K S +SPINKS'S S P IH1 NG K S IH0 Z +SPINNER S P IH1 N ER0 +SPINNER'S S P IH1 N ER0 Z +SPINNERS S P IH1 N ER0 Z +SPINNEY S P IH1 N IY0 +SPINNING S P IH1 N IH0 NG +SPINO S P IY1 N OW0 +SPINOFF S P IH1 N AO2 F +SPINOFFS S P IH1 N AO2 F S +SPINOLA S P IY0 N OW1 L AH0 +SPINOSA S P IY0 N OW1 S AH0 +SPINOZA S P IH0 N OW1 Z AH0 +SPINS S P IH1 N Z +SPINSTER S P IH1 N S T ER0 +SPINY S P AY1 N IY0 +SPIRA S P IH1 R AH0 +SPIRAL S P AY1 R AH0 L +SPIRALED S P AY1 R AH0 L D +SPIRALING S P AY1 R AH0 L IH0 NG +SPIRALLING S P AY1 R AH0 L IH0 NG +SPIRALS S P AY1 R AH0 L Z +SPIRE S P AY1 R +SPIRES S P AY1 R Z +SPIRIT S P IH1 R AH0 T +SPIRIT(1) S P IH1 R IH0 T +SPIRIT'S S P IH1 R IH0 T S +SPIRITED S P IH1 R IH0 T IH0 D +SPIRITEDNESS S P IH1 R IH0 T IH0 D N AH0 S +SPIRITO S P IH0 R IY1 T OW2 +SPIRITS S P IH1 R IH0 T S +SPIRITUAL S P IH1 R IH0 CH UW2 AH0 L +SPIRITUALISM S P IH1 R IH0 CH UW2 AH0 L IH2 Z M +SPIRITUALIST S P IH1 R IH0 CH UW2 AH0 L IH2 S T +SPIRITUALISTS S P IH1 R IH0 CH UW2 AH0 L IH2 S T S +SPIRITUALITY S P IH2 R IH0 CH UW2 AE1 L AH0 T IY2 +SPIRITUALLY S P IH1 R IH0 CH UW2 AH0 L IY2 +SPIRITUALS S P IH1 R IH0 CH UW2 AH0 L Z +SPIRO S P IH1 R OW2 +SPIRO'S S P IH1 R OW2 Z +SPIROS S P IH1 R OW2 Z +SPISAK S P IH1 S AH0 K +SPIT S P IH1 T +SPITALE S P IY0 T AA1 L IY0 +SPITBALL S P IH1 T B AO2 L +SPITBALL'S S P IH1 T B AO2 L Z +SPITE S P AY1 T +SPITEFUL S P AY1 T F AH0 L +SPITERI S P IY0 T EH1 R IY0 +SPITLER S P IH1 T L ER0 +SPITS S P IH1 T S +SPITTING S P IH1 T IH0 NG +SPITTLE S P IH1 T AH0 L +SPITTLER S P IH1 T L ER0 +SPITZ S P IH1 T S +SPITZER S P IH1 T Z ER0 +SPITZLEY S P IH1 T S L IY0 +SPITZNAGEL S P IH1 T S N EY2 G AH0 L +SPIVA S P IY1 V AH0 +SPIVACK S P IH1 V AH0 K +SPIVAK S P IH1 V AH0 K +SPIVEY S P IH1 V IY0 +SPIWAK S P IH1 V AH0 K +SPIZZIRRI S P IY0 T S IH1 R IY0 +SPLAIN S P L EY1 N +SPLAINE S P L EY1 N +SPLASH S P L AE1 SH +SPLASHED S P L AE1 SH T +SPLASHES S P L AE1 SH IH0 Z +SPLASHING S P L AE1 SH IH0 NG +SPLASHY S P L AE1 SH IY0 +SPLAT S P L AE1 T +SPLATTER S P L AE1 T ER0 +SPLATTERED S P L AE1 T ER0 D +SPLATTERING S P L AE1 T AH0 R IH2 NG +SPLATTERS S P L AE1 T ER0 Z +SPLAWN S P L AO1 N +SPLEEN S P L IY1 N +SPLEISSON S P EY1 S AH0 N +SPLENDID S P L EH1 N D IH0 D +SPLENDIDLY S P L EH1 N D AH0 D L IY0 +SPLENDOR S P L EH1 N D ER0 +SPLENIC S P L EH1 N IH0 K +SPLENIC(1) S P L IY1 N IH0 K +SPLICE S P L AY1 S +SPLICED S P L AY1 S T +SPLICES S P L AY1 S IH0 Z +SPLICHAL S P L IH1 CH AH0 L +SPLICING S P L AY1 S IH0 NG +SPLINT S P L IH1 N T +SPLINTER S P L IH1 N T ER0 +SPLINTERED S P L IH1 N T ER0 D +SPLINTERING S P L IH1 N T ER0 IH0 NG +SPLINTERS S P L IH1 N T ER0 Z +SPLINTERY S P L IH1 N T ER0 IY0 +SPLINTS S P L IH1 N T S +SPLIT S P L IH1 T +SPLITS S P L IH1 T S +SPLITT S P L IH1 T +SPLITTER S P L IH1 T ER0 +SPLITTING S P L IH1 T IH0 NG +SPLURGE S P L ER1 JH +SPLURGED S P L ER1 JH D +SPLURGES S P L ER1 JH IH0 S +SPLURGING S P L ER1 JH IH0 NG +SPOARER S P AO1 R ER0 +SPOCK S P AA1 K +SPODEN S P OW1 D AH0 N +SPOELSTRA S P OW1 L S T R AA0 +SPOERL S P AO1 R L +SPOFFORD S P AA1 F ER0 D +SPOGLI S P AA1 G L IY0 +SPOHN S P AA1 N +SPOHR S P AA1 R +SPOIL S P OY1 L +SPOILAGE S P OY1 L AH0 JH +SPOILAGE(1) S P OY1 L IH0 JH +SPOILED S P OY1 L D +SPOILER S P OY1 L ER0 +SPOILERS S P OY1 L ER0 Z +SPOILING S P OY1 L IH0 NG +SPOILS S P OY1 L Z +SPOKANE S P OW0 K AE1 N +SPOKANE(1) S P OW0 K EY1 N +SPOKE S P OW1 K +SPOKEN S P OW1 K AH0 N +SPOKENLY S P OW1 K AH0 N L IY0 +SPOKES S P OW1 K S +SPOKESMAN S P OW1 K S M AH0 N +SPOKESMEN S P OW1 K S M IH0 N +SPOKESPEOPLE S P OW1 K S P IY2 P AH0 L +SPOKESPERSON S P OW1 K S P ER0 S AH0 N +SPOKESPERSONS S P OW1 K S P ER0 S AH0 N Z +SPOKESWOMAN S P OW1 K S W UH2 M AH0 N +SPOKESWOMEN S P OW1 K S W IH2 M AH0 N +SPOLETO S P OW0 L EY1 T OW0 +SPOLETTO S P OW0 L EY1 T OW0 +SPOLETTO'S S P OW0 L EY1 T OW0 Z +SPOMER S P OW1 M ER0 +SPONAUGLE S P AA1 N AO0 G AH0 L +SPONG S P AO1 NG +SPONGE S P AH1 N JH +SPONGED S P AH1 N JH D +SPONGEFORM S P AH1 N JH IH0 F AO2 R M +SPONGES S P AH1 N JH IH0 Z +SPONGIFORM S P AH1 N JH IH0 F AO2 R M +SPONGY S P AH1 N JH IY0 +SPONSEL S P AA1 N S AH0 L +SPONSELLER S P AA1 N S AH0 L ER0 +SPONSLER S P AA1 N S AH0 L ER0 +SPONSLER(1) S P AA1 N S L ER0 +SPONSOR S P AA1 N S ER0 +SPONSOR'S S P AA1 N S ER0 Z +SPONSORED S P AA1 N S ER0 D +SPONSORING S P AA1 N S ER0 IH0 NG +SPONSORS S P AA1 N S ER0 Z +SPONSORSHIP S P AA1 N S ER0 SH IH2 P +SPONSORSHIPS S P AA1 N S ER0 SH IH2 P S +SPONTANEITY S P AA2 N T AH0 N IY1 AH0 T IY0 +SPONTANEOUS S P AA0 N T EY1 N IY0 AH0 S +SPONTANEOUSLY S P AA0 N T EY1 N IY0 AH0 S L IY0 +SPOOF S P UW1 F +SPOOFED S P UW1 F T +SPOOFING S P UW1 F IH0 NG +SPOOFS S P UW1 F S +SPOOK S P UW1 K +SPOOKED S P UW1 K T +SPOOKS S P UW1 K S +SPOOKY S P UW1 K IY0 +SPOOL S P UW1 L +SPOON S P UW1 N +SPOONEMORE S P UW1 N M AO0 R +SPOONER S P UW1 N ER0 +SPOONFUL S P UW1 N F UH2 L +SPOONFULS S P UW1 N F UH2 L Z +SPOONS S P UW1 N Z +SPOOR S P UH1 R +SPOOR'S S P UH1 R Z +SPORADIC S P ER0 AE1 D IH0 K +SPORADICALLY S P ER0 AE1 D IH0 K L IY0 +SPORCK S P AO1 R K +SPORE S P AO1 R +SPORER S P AO1 R ER0 +SPORES S P AO1 R Z +SPORKIN S P AO1 R K IH0 N +SPORKIN'S S P AO1 R K IH0 N Z +SPORLEDER S P AO1 R L IH0 D ER0 +SPORN S P AO1 R N +SPOROPHYTE S P AO1 R F AY2 T +SPOROPHYTES S P AO1 R F AY2 T S +SPORRER S P AO1 ER0 R +SPORT S P AO1 R T +SPORT'S S P AO1 R T S +SPORTED S P AO1 R T IH0 D +SPORTIER S P AO1 R T IY0 ER0 +SPORTING S P AO1 R T IH0 NG +SPORTINGLY S P AO1 R T IH0 NG L IY0 +SPORTS S P AO1 R T S +SPORTS' S P AO1 R T S +SPORTSBAR S P AO1 R T S B AA2 R +SPORTSCASTER S P AO1 R T S K AE2 S T ER0 +SPORTSCASTERS S P AO1 R T S K AE2 S T ER0 Z +SPORTSCHANNEL S P AO1 R T S CH AE1 N AH0 L +SPORTSCLUB S P AO1 R T S K L AH2 B +SPORTSMAN S P AO1 R T S M AH0 N +SPORTSMANSHIP S P AO1 R T S M AH0 N SH IH2 P +SPORTSMEN S P AO1 R T S M IH0 N +SPORTSTER S P AO1 R T S T ER0 +SPORTSWEAR S P AO1 R T S W EH2 R +SPORTSWRITER S P AO1 R T S R AY2 T ER0 +SPORTSWRITERS S P AO1 R T S R AY2 T ER0 Z +SPORTY S P AO1 R T IY0 +SPOSATO S P OW0 S AA1 T OW0 +SPOSITO S P OW0 S IY1 T OW0 +SPOT S P AA1 T +SPOTLESS S P AA1 T L AH0 S +SPOTLIGHT S P AA1 T L AY2 T +SPOTLIGHTED S P AA1 T L AY2 T IH0 D +SPOTLIGHTING S P AA1 T L AY2 T IH0 NG +SPOTLIGHTS S P AA1 T L AY2 T S +SPOTO S P OW1 T OW0 +SPOTS S P AA1 T S +SPOTTED S P AA1 T IH0 D +SPOTTER S P AA1 T ER0 +SPOTTERS S P AA1 T ER0 Z +SPOTTING S P AA1 T IH0 NG +SPOTTS S P AA1 T S +SPOTTY S P AA1 T IY0 +SPOUSAL S P AW1 Z AH0 L +SPOUSE S P AW1 S +SPOUSE'S S P AW1 S IH0 Z +SPOUSES S P AW1 S IH0 Z +SPOUT S P AW1 T +SPOUTED S P AW1 T IH0 D +SPOUTING S P AW1 T IH0 NG +SPOUTS S P AW1 T S +SPRACKLEN S P R AE1 K AH0 L AH0 N +SPRADLEY S P R AE1 D L IY0 +SPRADLIN S P R AE1 D L IH0 N +SPRADLING S P R AE1 D L IH0 NG +SPRAGG S P R AE1 G +SPRAGGINS S P R AE1 G IH0 N Z +SPRAGUE S P R EY1 G +SPRAGUE'S S P R EY1 G Z +SPRAIN S P R EY1 N +SPRAINED S P R EY1 N D +SPRAINING S P R EY1 N IH0 NG +SPRAINS S P R EY1 N Z +SPRAKER S P R EY1 K ER0 +SPRANG S P R AE1 NG +SPRANGER S P R AE1 NG ER0 +SPRANKLE S P R AE1 NG K AH0 L +SPRATLEY S P R AE1 T L IY0 +SPRATLIN S P R AE1 T L IH0 N +SPRATLING S P R AE1 T L IH0 NG +SPRATT S P R AE1 T +SPRAWL S P R AO1 L +SPRAWLED S P R AO1 L D +SPRAWLING S P R AO1 L IH0 NG +SPRAWLS S P R AO1 L Z +SPRAY S P R EY1 +SPRAYBERRY S P R EY1 B EH2 R IY0 +SPRAYED S P R EY1 D +SPRAYER S P R EY1 ER0 +SPRAYERS S P R EY1 ER0 Z +SPRAYING S P R EY1 IH0 NG +SPRAYS S P R EY1 Z +SPREAD S P R EH1 D +SPREADER S P R EH1 D ER0 +SPREADING S P R EH1 D IH0 NG +SPREADS S P R EH1 D Z +SPREADSHEET S P R EH1 D SH IY2 T +SPREADSHEETS S P R EH1 D SH IY2 T S +SPRECHER S P R EH1 K ER0 +SPRECKELS S P R EH1 K AH0 L Z +SPREE S P R IY1 +SPREEMAN S P R IY1 M AH0 N +SPREEN S P R IY1 N +SPREES S P R IY1 Z +SPREHE S P R IY1 HH +SPREITZER S P R AY1 T Z ER0 +SPRENG S P R EH1 NG +SPRENGER S P R EH1 N JH ER0 +SPRENKLE S P R EH1 NG K AH0 L +SPRICK S P R IH1 K +SPRIGG S P R IH1 G +SPRIGGED S P R IH1 G D +SPRIGGS S P R IH1 G Z +SPRIGHTLY S P R AY1 T L IY0 +SPRING S P R IH1 NG +SPRING(1) S P ER0 IH1 NG +SPRING'S S P R IH1 NG Z +SPRINGBOARD S P R IH1 NG B AO2 R D +SPRINGBORN S P R IH1 NG G B ER0 N +SPRINGDALE S P R IH1 NG D EY2 L +SPRINGER S P R IH1 NG ER0 +SPRINGERVILLE S P R IH1 NG ER0 V IH2 L +SPRINGFIELD S P R IH1 NG F IY2 L D +SPRINGFIELD'S S P R IH1 NG F IY2 L D Z +SPRINGING S P R IH1 NG IH0 NG +SPRINGMAN S P R IH1 NG M AH0 N +SPRINGS S P R IH1 NG Z +SPRINGS(1) S P ER0 IH1 NG Z +SPRINGSTEAD S P R IH1 NG S T EH2 D +SPRINGSTEEN S P R IH1 NG S T IY2 N +SPRINGSTEEN'S S P R IH1 NG S T IY2 N Z +SPRINGSTON S P R IH1 NG S T AH0 N +SPRINGTIME S P R IH1 NG T AY2 M +SPRINKEL S P R IH1 NG K AH0 L +SPRINKLE S P R IH1 NG K AH0 L +SPRINKLED S P R IH1 NG K AH0 L D +SPRINKLER S P R IH1 NG K L ER0 +SPRINKLER(1) S P R IH1 NG K AH0 L ER0 +SPRINKLERS S P R IH1 NG K L ER0 Z +SPRINKLERS(1) S P R IH1 NG K AH0 L ER0 Z +SPRINKLES S P R IH1 NG K AH0 L Z +SPRINKLING S P R IH1 NG K L IH0 NG +SPRINKLING(1) S P R IH1 NG K AH0 L IH0 NG +SPRINT S P R IH1 N T +SPRINT'S S P R IH1 N T S +SPRINTED S P R IH1 N T IH0 D +SPRINTER S P R IH1 N T ER0 +SPRINTERS S P R IH1 N T ER0 Z +SPRINTING S P R IH1 N T IH0 NG +SPRINTS S P R IH1 N T S +SPRITE S P R AY1 T +SPRIZZO S P R IH1 Z OW0 +SPROAT S P R OW1 T +SPROCK S P R AA1 K +SPROCKET S P R AA1 K AH0 T +SPROGUS S P R OW1 G AH0 S +SPROGUS'S S P R OW1 G AH0 S IH0 Z +SPROLES S P R OW1 L Z +SPRONG S P R AO1 NG +SPROTT S P R AA1 T +SPROUL S P R AW1 L +SPROULE S P R UW1 L +SPROULL S P R UW1 L +SPROULS S P R AW1 L Z +SPROUSE S P R AW1 S +SPROUT S P R AW1 T +SPROUTAPHILE S P R AW1 T AH0 F AY0 L +SPROUTAPHILES S P R AW1 T AH0 F AY0 L Z +SPROUTED S P R AW1 T IH0 D +SPROUTING S P R AW1 T IH0 NG +SPROUTS S P R AW1 T S +SPROW S P R AW1 +SPROWL S P R AW1 L +SPROWLE S P R AW1 AH0 L +SPROWLS S P R AW1 L Z +SPRUCE S P R UW1 S +SPRUCED S P R UW1 S T +SPRUCING S P R UW1 S IH0 NG +SPRUELL S P R UW1 L +SPRUIELL S P R UW1 L +SPRUILL S P R UW1 L +SPRUNG S P R AH1 NG +SPRUNGER S P R AH1 NG ER0 +SPRY S P R AY1 +SPUD S P AH1 D +SPUD'S S P AH1 D Z +SPUDS S P AH1 D Z +SPUHLER S P UW1 L ER0 +SPUN S P AH1 N +SPUNK S P AH1 NG K +SPUNKY S P AH1 NG K IY0 +SPUR S P ER1 +SPURDLE S P ER1 D AH0 L +SPURGE S P ER1 JH +SPURGEON S P ER1 JH IH0 N +SPURGIN S P ER1 JH IH0 N +SPURIOUS S P Y UH1 R IY0 AH0 S +SPURIOUS(1) S P ER1 IY0 AH0 S +SPURLIN S P ER1 L IH0 N +SPURLING S P ER1 L IH0 NG +SPURLOCK S P ER1 L AA2 K +SPURN S P ER1 N +SPURNED S P ER1 N D +SPURNING S P ER1 N IH0 NG +SPURNS S P ER1 N Z +SPURR S P ER1 +SPURRED S P ER1 D +SPURRIER S P ER1 IY0 ER0 +SPURRING S P ER1 IH0 NG +SPURS S P ER1 Z +SPURT S P ER1 T +SPURTED S P ER1 T IH0 D +SPURTING S P ER1 T IH0 NG +SPURTS S P ER1 T S +SPUTNIK S P AH1 T N IH0 K +SPUTNIKS S P AH1 T N IH0 K S +SPUTTER S P AH1 T ER0 +SPUTTERED S P AH1 T ER0 D +SPUTTERING S P AH1 T ER0 IH0 NG +SPUTTERS S P AH1 T ER0 Z +SPUTUM S P Y UW1 T AH0 M +SPY S P AY1 +SPY'S S P AY1 Z +SPYCATCHER S P AY1 K AE2 CH ER0 +SPYCHALSKI S P IH0 HH AA1 L S K IY0 +SPYGLASS S P AY1 G L AE2 S +SPYING S P AY1 IH0 NG +SPYKER S P AY1 K ER0 +SPYWARE S P AY1 W EH2 R +SQL EH2 S K Y UW2 EH1 L +SQL(1) S IY1 K W UH0 L +SQUABBLE S K W AA1 B AH0 L +SQUABBLED S K W AA1 B AH0 L D +SQUABBLES S K W AA1 B AH0 L Z +SQUABBLING S K W AA1 B AH0 L IH0 NG +SQUABBLING(1) S K W AA1 B L IH0 NG +SQUAD S K W AA1 D +SQUAD'S S K W AA1 D Z +SQUADRON S K W AA1 D R AH0 N +SQUADRONS S K W AA1 D R AH0 N Z +SQUADS S K W AA1 D Z +SQUALID S K W AA1 L IH0 D +SQUALL S K W AO1 L +SQUALLS S K W AO1 L Z +SQUALOR S K W AA1 L ER0 +SQUAMOUS S K W EY1 M AH0 S +SQUANDER S K W AA1 N D ER0 +SQUANDERED S K W AA1 N D ER0 D +SQUANDERING S K W AA1 N D ER0 IH0 NG +SQUANDERS S K W AA1 N D ER0 Z +SQUARE S K W EH1 R +SQUARED S K W EH1 R D +SQUARELY S K W EH1 R L IY0 +SQUARES S K W EH1 R Z +SQUARING S K W EH1 R IH0 NG +SQUASH S K W AA1 SH +SQUASHED S K W AA1 SH T +SQUASHING S K W AA1 SH IH0 NG +SQUASHY S K W AA1 SH IY0 +SQUAT S K W AA1 T +SQUATS S K W AA1 T S +SQUATTER S K W AA1 T ER0 +SQUATTERS S K W AA1 T ER0 Z +SQUATTING S K W AA1 T IH0 NG +SQUATTY S K W AA1 T IY0 +SQUAWK S K W AO1 K +SQUAWKING S K W AO1 K IH0 NG +SQUAWKS S K W AO1 K S +SQUEAK S K W IY1 K +SQUEAKED S K W IY1 K T +SQUEAKER S K W IY1 K ER0 +SQUEAKERS S K W IY1 K ER0 Z +SQUEAKING S K W IY1 K IH0 NG +SQUEAKS S K W IY1 K S +SQUEAKY S K W IY1 K IY0 +SQUEAL S K W IY1 L +SQUEALING S K W IY1 L IH0 NG +SQUEALS S K W IY1 L Z +SQUEAMISH S K W IY1 M IH0 SH +SQUEAMISHNESS S K W IY1 M IH0 SH N AH0 S +SQUEEGEE S K W IY1 JH IY0 +SQUEEZE S K W IY1 Z +SQUEEZED S K W IY1 Z D +SQUEEZES S K W IY1 Z IH0 Z +SQUEEZING S K W IY1 Z IH0 NG +SQUELCH S K W EH1 L CH +SQUELCHED S K W EH1 L CH T +SQUELCHING S K W EH1 L CH IH0 NG +SQUIBB S K W IH1 B +SQUIBB'S S K W IH1 B Z +SQUID S K W IH1 D +SQUIER S K W AY1 ER0 +SQUIERS S K W AY1 ER0 Z +SQUIGGLE S K W IH1 G AH0 L +SQUIGGLES S K W IH1 G AH0 L Z +SQUILLACE S K W IH1 L AH0 S +SQUILLACOTE S K W IH1 L AH0 K OW0 T +SQUILLACOTE'S S K W IH1 L AH0 K OW0 T S +SQUILLANTE S K W IY0 L AA1 N T EY0 +SQUINT S K W IH1 N T +SQUINTING S K W IH1 N T IH0 NG +SQUIRE S K W AY1 R +SQUIRES S K W AY1 ER0 Z +SQUIRM S K W ER1 M +SQUIRMING S K W ER1 M IH0 NG +SQUIRMS S K W ER1 M Z +SQUIRREL S K W ER1 AH0 L +SQUIRRELED S K W ER1 AH0 L D +SQUIRRELS S K W ER1 AH0 L Z +SQUIRT S K W ER1 T +SQUIRTED S K W ER1 T IH0 D +SQUIRTING S K W ER1 T IH0 NG +SQUIRTS S K W ER1 T S +SQUISHY S K W IH1 SH IY0 +SQUITIERI S K W IY0 T IH1 R IY0 +SQUYRES S K W AY1 R Z +SR S IY1 N Y ER0 +SR(1) S IH1 S T ER0 +SRADER SH R EY1 D ER0 +SRAM SH R AE1 M +SRAM(1) EH1 S R AE1 M +SRAMEK SH R AE1 M IH0 K +SRDAN S ER1 D AE2 N +SREBRENICA S R EY2 B R EH0 N IY1 T S AH0 +SREBRENICA(1) SH R EY2 B R AH0 N IY1 T S AH0 +SREBRENICA'S S R EY2 B R EH0 N IY1 T S AH0 Z +SREBRENICA'S(1) SH R EY2 B R AH0 N IY1 T S AH0 Z +SREMAC S R IY1 M AE2 K +SRI SH R IY1 +SRI(1) EH1 S AA1 R AY1 +SRI(2) S R IY1 +SRI-LANKA S R IY1 L AE1 NG K AH0 +SRI-LANKA(1) SH R IY1 L AE1 NG K AH0 +SRINAGAR S R IY1 N AH0 G AA2 R +SRINAGAR(1) SH R IY1 N AH0 G AA2 R +SRINAGARB S R IY1 N AH0 G AA2 R B +SRINAGARB(1) SH R IY1 N AH0 G AA2 R B +SRINIVAS S R IY1 N IH0 V AA2 S +SRINIVASAN S R IY0 N IY2 V AA0 S AA1 N +SRINIVASAN(1) SH R IY0 N IY2 V AA0 S AA1 N +SRIRAM S R IY1 R AA2 M +SRIRAM(1) SH R IY1 R AA2 M +SRIVASTAVA S R IY0 V AA0 S T AA1 V AH0 +SRIVASTAVA(1) SH R IY0 V AA0 S T AA1 V AH0 +SROCK SH R AA1 K +SROGE SH R OW1 G +SROKA SH R OW1 K AH0 +SROUFE SH R OW1 F +SRPSKA S R AH1 P S K AH0 +SSANGYONG S AE1 NG Y AO2 NG +ST-JAMES S EY1 N T JH EY1 M Z +ST-JOHNS S EY1 N T JH AA1 N Z +ST. S T R IY1 T +ST.(1) S EY1 N T +STA S T AH1 +STA(1) EH1 S T IY1 EY1 +STAAB S T AA1 B +STAACK S T AA1 K +STAAL S T AA1 L +STAAR S T AA1 R +STAAR'S S T AA1 R Z +STAAS S T AA1 Z +STAAT S T AA1 T +STAATS S T AA1 T S +STAB S T AE1 B +STABBED S T AE1 B D +STABBING S T AE1 B IH0 NG +STABBINGS S T AE1 B IH0 NG Z +STABENOW S T AE1 B IH0 N OW0 +STABILE S T EY1 B IH0 L +STABILITY S T AH0 B IH1 L IH0 T IY0 +STABILIZATION S T EY2 B AH0 L AH0 Z EY1 SH AH0 N +STABILIZE S T EY1 B AH0 L AY2 Z +STABILIZED S T EY1 B AH0 L AY2 Z D +STABILIZER S T EY1 B AH0 L AY2 Z ER0 +STABILIZERS S T EY1 B AH0 L AY2 Z ER0 Z +STABILIZES S T EY1 B AH0 L AY2 Z AH0 Z +STABILIZES(1) S T EY1 B AH0 L AY2 Z IH0 Z +STABILIZING S T EY1 B AH0 L AY2 Z IH0 NG +STABLE S T EY1 B AH0 L +STABLER S T EY1 B AH0 L ER0 +STABLER(1) S T EY1 B L ER0 +STABLES S T EY1 B AH0 L Z +STABLEST S T EY1 B AH0 L AH0 S T +STABLEY S T AE1 B L IY0 +STABS S T AE1 B Z +STAC S T AE1 K +STAC'S S T AE1 K S +STACCATO S T AH0 K AA1 T OW2 +STACEY S T EY1 S IY0 +STACH S T AE1 CH +STACHNIK S T AE1 K N IH0 K +STACHOWIAK S T AH0 CH AW1 IY0 AE0 K +STACHOWICZ S T AA1 CH AH0 V IH0 CH +STACHOWSKI S T AH0 CH AO1 F S K IY0 +STACHURA S T AA0 CH UH1 R AH0 +STACHURSKI S T AH0 CH ER1 S K IY0 +STACIA S T AA1 CH AH0 +STACIE S T EY1 S IY0 +STACK S T AE1 K +STACKED S T AE1 K T +STACKER S T AE1 K ER0 +STACKHOUSE S T AE1 K HH AW2 S +STACKING S T AE1 K IH0 NG +STACKPOLE S T AE1 K P OW2 L +STACKS S T AE1 K S +STACY S T EY1 S IY0 +STADE S T EY1 D +STADEL S T AE1 D AH0 L +STADELMAN S T AE1 D AH0 L M AH0 N +STADER S T EY1 D ER0 +STADIA S T AA1 D IY2 AA0 +STADIUM S T EY1 D IY0 AH0 M +STADIUM'S S T EY1 D IY0 AH0 M Z +STADIUMS S T EY1 D IY0 AH0 M Z +STADLER S T AE1 D L ER0 +STADNIK S T AE1 D N IH0 K +STADT S T AE1 D T +STADTLANDER SH T AE1 T L AE2 N D ER0 +STADTMILLER SH T AE1 T M IH1 L ER0 +STAEBELL S T EH1 B EH0 L +STAEBLER S T EY1 L ER0 +STAEHLE S T EY1 L +STAFF S T AE1 F +STAFF'S S T AE1 F S +STAFFA S T AA1 F AA2 +STAFFED S T AE1 F T +STAFFER S T AE1 F ER0 +STAFFERS S T AE1 F ER0 Z +STAFFIERI S T AA0 F IH1 R IY0 +STAFFING S T AE1 F IH0 NG +STAFFORD S T AE1 F ER0 D +STAFFORD'S S T AE1 F ER0 D Z +STAFFORDSHIRE S T AE1 F ER0 D SH ER0 +STAFFORDSHIRE(1) S T AE1 F ER0 D SH AY2 ER0 +STAFFORDSHIRE'S S T AE1 F ER0 D SH ER0 Z +STAFFORDSHIRE'S(1) S T AE1 F ER0 D SH AY2 ER0 Z +STAFFS S T AE1 F S +STAG S T AE1 G +STAG-PARTY S T AE1 G P AE2 R T IY0 +STAGE S T EY1 JH +STAGECOACH S T EY1 JH K OW2 CH +STAGECRAFT S T EY1 JH K R AE2 F T +STAGED S T EY1 JH D +STAGEHAND S T EY1 JH HH AE2 N D +STAGEHANDS S T EY1 JH HH AE2 N D Z +STAGER S T EY1 JH ER0 +STAGES S T EY1 JH IH0 Z +STAGFLATE S T AE2 G F L EY1 T +STAGFLATION S T AE0 G F L EY1 SH AH0 N +STAGG S T AE1 G +STAGGER S T AE1 G ER0 +STAGGERED S T AE1 G ER0 D +STAGGERING S T AE1 G ER0 IH2 NG +STAGGERINGLY S T AE1 G ER0 IH2 NG L IY2 +STAGGERS S T AE1 G ER0 Z +STAGGS S T AE1 G Z +STAGING S T EY1 JH IH0 NG +STAGLIANO S T AA0 G L IY0 AA1 N OW2 +STAGNANT S T AE1 G N AH0 N T +STAGNARO S T AA0 G N AA1 R OW2 +STAGNATE S T AE1 G N EY2 T +STAGNATED S T AE1 G N EY2 T IH0 D +STAGNATING S T AE1 G N EY2 T IH0 NG +STAGNATION S T AE0 G N EY1 SH AH0 N +STAGNER S T AE1 G N ER0 +STAHL S T AA1 L +STAHLBERG S T AA1 L B ER0 G +STAHLE S T EY1 HH AH0 L +STAHLECKER S T AA1 L IH0 K ER0 +STAHLER S T AA1 L ER0 +STAHLEY S T AE1 L IY0 +STAHLHUT S T AA1 L HH AH0 T +STAHLMAN S T AA1 L M AH0 N +STAHLY S T AE1 L IY0 +STAHMER S T AA1 M ER0 +STAHNKE S T AE1 NG K +STAHR S T AE1 R +STAI S T AA1 IY0 +STAIB S T EY1 B +STAID S T EY1 D +STAIGER S T AY1 G ER0 +STAILEY S T EY1 L IY0 +STAIN S T EY1 N +STAINBACK S T EY1 N B AE2 K +STAINBROOK S T EY1 N B R UH2 K +STAINED S T EY1 N D +STAINES S T EY1 N Z +STAINING S T EY1 N IH0 NG +STAINLESS S T EY1 N L AH0 S +STAINMASTER S T EY1 N M AE2 S T ER0 +STAINS S T EY1 N Z +STAIR S T EH1 R +STAIRCASE S T EH1 R K EY2 S +STAIRCASES S T EH1 R K EY2 S IH0 Z +STAIRS S T EH1 R Z +STAIRWAY S T EH1 R W EY2 +STAIRWAYS S T EH1 R W EY2 Z +STAIRWELL S T EH1 R W EH2 L +STAIRWELLS S T EH1 R W EH2 L Z +STAKE S T EY1 K +STAKE'S S T EY1 K S +STAKE-OUT S T EY1 K AW1 T +STAKED S T EY1 K T +STAKEHOLDER S T EY1 K HH OW2 L D ER0 +STAKEHOLDERS S T EY1 K HH OW2 L D ER0 Z +STAKEOUT S T EY1 K AW2 T +STAKEOUTS S T EY1 K AW2 T S +STAKER S T EY1 K ER0 +STAKES S T EY1 K S +STAKING S T EY1 K IH0 NG +STALAG S T AE1 L AE2 G +STALAGMITE S T AE1 L AH0 G M AY2 T +STALCUP S T AO1 L K AH2 P +STALDER S T AO1 L D ER0 +STALE S T EY1 L +STALEMATE S T EY1 L M EY2 T +STALEMATED S T EY1 L M EY2 T IH0 D +STALEY S T EY1 L IY0 +STALEY'S S T EY1 L IY0 Z +STALIN S T AA1 L AH0 N +STALIN'S S T AA1 L IH0 N Z +STALINGRAD S T AE1 L IH0 N G R AE2 D +STALINISM S T AE1 L IH0 N IH2 Z AH0 M +STALINIST S T AA1 L IH0 N IH0 S T +STALINISTIC S T AA2 L IH0 N IH1 S T IH0 K +STALINISTS S T AE1 L IH0 N IH0 S T S +STALINIZATION S T AE2 L IH0 N IH0 Z EY1 SH AH0 N +STALINIZE S T AE1 L IH0 N AY2 Z +STALK S T AO1 K +STALKED S T AO1 K T +STALKER S T AO1 K ER0 +STALKERS S T AO1 K ER0 Z +STALKING S T AO1 K IH0 NG +STALKS S T AO1 K S +STALKY S T AO1 K IY0 +STALL S T AO1 L +STALLARD S T AE1 L ER0 D +STALLCUP S T AO1 L K AH2 P +STALLED S T AO1 L D +STALLER S T AO1 L ER0 +STALLIBRASS S T AE1 L IH0 B R AE0 S +STALLING S T AO1 L IH0 NG +STALLINGS S T AO1 L IH0 NG Z +STALLION S T AE1 L Y AH0 N +STALLIONS S T AE1 L Y AH0 N Z +STALLKAMP S T AO1 L K AE2 M P +STALLMAN S T AO1 L M AH0 N +STALLONE S T AH0 L OW1 N +STALLONE'S S T AH0 L OW1 N Z +STALLS S T AO1 L Z +STALLSMITH S T AO1 L S M IH2 TH +STALLWORTH S T AO1 L W ER2 TH +STALNAKER S T AE1 L N AH0 K ER0 +STALOFF S T AE1 L AO0 F +STALON S T EY1 L AH0 N +STALOWA S T AH0 L OW1 AH0 +STALTER S T AO1 L T ER0 +STALVEY S T AE1 L V IY0 +STALWART S T AO1 L W ER0 T +STALWARTS S T AO1 L W ER0 T S +STALZER S T EY1 L Z ER0 +STAM S T AE1 M +STAMAND S T AE1 M AH0 N D +STAMANT S T AE1 M AH0 N T +STAMAS S T AA1 M AH0 Z +STAMATY S T AE1 M AH0 T IY0 +STAMBAUGH S T AE1 M B AO0 +STAMBERG S T AE1 M B ER0 G +STAMENSON S T EY1 M AH0 N S AH0 N +STAMER S T EY1 M ER0 +STAMEY S T EY1 M IY0 +STAMFORD S T AE1 M F ER0 D +STAMINA S T AE1 M AH0 N AH0 +STAMLER S T AE1 M L ER0 +STAMM S T AE1 M +STAMMEN S T AE1 M AH0 N +STAMMER S T AE1 M ER0 +STAMOS S T EY1 M OW0 Z +STAMOUR S T AH0 M UH1 R +STAMP S T AE1 M P +STAMPED S T AE1 M P T +STAMPEDE S T AE0 M P IY1 D +STAMPEDED S T AE0 M P IY1 D IH0 D +STAMPEDING S T AE0 M P IY1 D IH0 NG +STAMPER S T AE1 M P ER0 +STAMPFLI S T AE1 M P F L IY0 +STAMPING S T AE1 M P IH0 NG +STAMPINGS S T AE1 M P IH0 NG Z +STAMPLEY S T AE1 M P L IY0 +STAMPS S T AE1 M P S +STAN S T AE1 N +STAN'S S T AE1 N Z +STANADYNE S T AE1 N AH0 D AY2 N +STANALAND S T AE1 N AH0 L AH0 N D +STANARD S T AE1 N ER0 D +STANAWAY S T AE1 N AH0 W EY0 +STANBACK S T AE1 N B AE2 K +STANBERRY S T AE1 N B EH2 R IY0 +STANBERY S T AE1 N B ER0 IY0 +STANBIC S T AE1 N B IH0 K +STANBROUGH S T AE1 N B R AW0 +STANBURY S T AE1 N B EH2 R IY0 +STANCE S T AE1 N S +STANCES S T AE1 N S IH0 Z +STANCH S T AE1 N CH +STANCHED S T AE1 N CH T +STANCHFIELD S T AE1 N CH F IY0 L D +STANCHING S T AE1 N CH IH0 NG +STANCIK S T AE1 N S IH0 K +STANCIL S T AE1 N S IH0 L +STANCILL S T AE1 N S IH0 L +STANCLIFF S T AE1 N K L IH0 F +STANCO S T AE1 NG K OW0 +STANCZAK S T AE1 N CH AE0 K +STANCZYK S T AE1 N CH IH0 K +STAND S T AE1 N D +STAND-BY S T AE1 N D B AY2 +STAND-UP S T AE1 N D AH2 P +STANDA S T AE1 N D AH0 +STANDARD S T AE1 N D ER0 D +STANDARD'S S T AE1 N D ER0 D Z +STANDARD-BEARER S T AE1 N D ER0 D B EH1 R ER0 +STANDARD-BEARERS S T AE1 N D ER0 D B EH1 R ER0 Z +STANDARDIZATION S T AE0 N D ER0 D IH0 Z EY1 SH AH0 N +STANDARDIZE S T AE1 N D ER0 D AY2 Z +STANDARDIZED S T AE1 N D ER0 D AY2 Z D +STANDARDIZING S T AE1 N D ER0 D AY2 Z IH0 NG +STANDARDS S T AE1 N D ER0 D Z +STANDBY S T AE1 N D B AY1 +STANDBYS S T AE1 N D B AY2 Z +STANDEFER S T AE1 N D IH0 F ER0 +STANDEN S T AE1 N D AH0 N +STANDER S T AE1 N D ER0 +STANDERFER S T AE1 N D ER0 F ER0 +STANDERFORD S T AE1 N D ER0 F ER0 D +STANDEX S T AE1 N D AH0 K S +STANDFIELD S T AE1 N D F IY2 L D +STANDIFER S T AE1 N D IH0 F ER0 +STANDIFORD S T AE1 N D IH0 F ER0 D +STANDIN' S T AE1 N D IH0 N +STANDING S T AE1 N D IH0 NG +STANDINGS S T AE1 N D IH0 NG Z +STANDISH S T AE1 N D IH0 SH +STANDLEE S T AE1 N D L IY2 +STANDLEY S T AE1 N D L IY0 +STANDOFF S T AE1 N D AO2 F +STANDOFFS S T AE1 N D AO2 F S +STANDOUT S T AE1 N D AW2 T +STANDOUTS S T AE1 N D AW2 T S +STANDPOINT S T AE1 N D P OY2 N T +STANDPOINTS S T AE1 N D P OY2 N T S +STANDRE S T AE1 N D ER0 +STANDRIDGE S T AE1 N D R IH0 JH +STANDS S T AE1 N D Z +STANDSTILL S T AE1 N D S T IH2 L +STANDUP S T AE1 N D AH2 P +STANEK S T AE1 N IH0 K +STANFIELD S T AE1 N F IY2 L D +STANFILL S T AE1 N F AH0 L +STANFORD S T AE1 N F ER0 D +STANFORD'S S T AE1 N F ER0 D Z +STANFORTH S T AE1 N F ER0 TH +STANG S T AE1 NG +STANGA S T AA1 NG G AH0 +STANGE S T AE1 N JH +STANGEL S T EY1 NG G AH0 L +STANGELAND S T EY1 NG G IH0 L AH0 N D +STANGELAND(1) S T EY1 NG G L AH0 N D +STANGELO S T AA0 NG G EH1 L OW0 +STANGER S T AE1 NG ER0 +STANGL S T AE1 NG G AH0 L +STANGLAND S T AE1 NG G L AH0 N D +STANGLE S T AE1 NG G AH0 L +STANGLER S T AE1 NG G AH0 L ER0 +STANGLER(1) S T AE1 NG G L ER0 +STANGO S T AA1 NG G OW0 +STANHOPE S T AE1 N HH OW2 P +STANIAR S T EY1 N IY0 AA0 R +STANICH S T AE1 N IH0 CH +STANIFER S T AE1 N IH0 F ER0 +STANIS S T AE1 N IH0 S +STANISH S T AE1 N IH0 SH +STANISLAS S T AE1 N IH0 S L AA0 S +STANISLAV S T AE1 N IH0 S L AA0 V +STANISLAW S T AE1 N IH0 S L AO2 +STANISLAWSKI S T AE2 N IH0 S L AA1 F S K IY2 +STANISZEWSKI S T AE2 N IH0 SH EH1 F S K IY2 +STANK S T AE1 NG K +STANKE S T AE1 NG K +STANKEVICH S T AE1 NG K AH0 V IH2 CH +STANKEY S T AE1 NG K IY0 +STANKIEWICZ S T AE1 N K AH0 V IH0 CH +STANKO S T AE1 NG K OW0 +STANKOVICH S T AE1 NG K AH0 V IH0 CH +STANKOWSKI S T AH0 NG K AO1 F S K IY0 +STANKUS S T AE1 NG K AH0 S +STANLEIGH S T AE1 N L AH0 +STANLEY S T AE1 N L IY0 +STANLEY'S S T AE1 N L IY0 Z +STANLEYTOWN S T AE1 N L IY0 T AW2 N +STANLINE S T AE1 N L AY2 N +STANLY S T AE1 N L IY0 +STANMORE S T AE1 N M AO0 R +STANN S T AE1 N +STANNARD S T AE1 N ER0 D +STANNIE S T AE1 N IY0 +STANO S T AA1 N OW0 +STANPHILL S T AE1 N P HH IH2 L +STANSBERRY S T AE1 N S B EH2 R IY0 +STANSBURY S T AE1 N S B EH0 R IY0 +STANSEL S T AE1 N S AH0 L +STANSELL S T AE1 N S AH0 L +STANSFIELD S T AE1 N S F IY0 L D +STANSKY S T AE1 N S K IY0 +STANT S T AE1 N T +STANTON S T AE1 N T AH0 N +STANWAY S T AE1 N W EY2 +STANWICK S T AE1 N W IH0 K +STANWOOD S T AE1 N W UH2 D +STANZA S T AE1 N Z AH0 +STANZAS S T AE1 N Z AH0 Z +STANZIONE S T AA0 N Z IY0 OW1 N IY0 +STAPEL S T AE1 P AH0 L +STAPF S T AE1 P F +STAPH S T AE1 F +STAPHYLOCOCCUS S T AE2 F AH0 L AH0 K AO1 K AH0 S +STAPLE S T EY1 P AH0 L +STAPLED S T EY1 P AH0 L D +STAPLER S T EY1 P AH0 L ER0 +STAPLER(1) S T EY1 P L ER0 +STAPLERS S T EY1 P AH0 L ER0 Z +STAPLERS(1) S T EY1 P L ER0 Z +STAPLES S T EY1 P AH0 L Z +STAPLETON S T EY1 P AH0 L T AH0 N +STAPLEY S T AE1 P L IY0 +STAPLING S T EY1 P AH0 L IH0 NG +STAPLING(1) S T EY1 P L IH0 NG +STAPP S T AE1 P +STAR S T AA1 R +STAR'S S T AA1 R Z +STARACE S T AA0 R AA1 CH IY0 +STARBIRD S T AA1 R B ER2 D +STARBOARD S T AA1 R B ER0 D +STARBOARDS S T AA1 R B ER0 R D Z +STARBOARDS(1) S T AA1 R B AO2 R D Z +STARBUCK S T AA1 R B AH2 K +STARBUCK'S S T AA1 R B AH2 K S +STARBUCKS S T AA1 R B AH2 K S +STARCEVICH S T AA1 R S IH0 V IH0 CH +STARCH S T AA1 R CH +STARCHED S T AA1 R CH T +STARCHER S T AA1 R CH ER0 +STARCHES S T AA1 R CH IH0 Z +STARCHLIKE S T AA1 R CH L AY2 K +STARCHY S T AA1 R CH IY0 +STARCK S T AA1 R K +STARCKMANN S T AA1 R K M AH0 N +STARCRAFT S T AA1 R K R AE2 F T +STARCROSS S T AA1 R K R AO2 S +STARDEL S T AA1 R D EH2 L +STARDENT S T AA1 R D EH2 N T +STARDOM S T AA1 R D AH0 M +STARDUST S T AA1 R D AH2 S T +STARE S T EH1 R +STARED S T EH1 R D +STARER S T EH1 R ER0 +STARES S T EH1 R Z +STARFISH S T AA1 R F IH2 SH +STARFLEET S T AA1 R F IY2 T +STARFLEET'S S T AA1 R F IY2 T S +STARGATE S T AA1 R G EY2 T +STARGATES S T AA1 R G EY2 T S +STARGAZER S T AA1 R G EY2 Z ER0 +STARGAZERS S T AA1 R G EY2 Z ER0 Z +STARIN S T AE1 R IH0 N +STARIN' S T EH1 R IH0 N +STARING S T EH1 R IH0 NG +STARK S T AA1 R K +STARK'S S T AA1 R K S +STARKE S T AA1 R K +STARKEL S T AA1 R K AH0 L +STARKER S T AA1 R K ER0 +STARKERS S T AA1 R K ER0 Z +STARKES S T AA1 R K S +STARKEY S T AA1 R K IY2 +STARKIST S T AA1 R K IH0 S T +STARKLY S T AA1 R K L IY0 +STARKMAN S T AA1 R K M AH0 N +STARKNESS S T AA1 R K N IH0 S +STARKOVICH S T AA1 R K AH0 V IH0 CH +STARKS S T AA1 R K S +STARKWEATHER S T AA1 R K W EH2 DH ER0 +STARLET S T AA1 R L AH0 T +STARLETS S T AA1 R L AH0 T S +STARLIGHT S T AA1 R L AY2 T +STARLIKE S T AA1 R L AY2 K +STARLIN S T AA1 R L IH0 N +STARLING S T AA1 R L IH0 NG +STARLIPER S T AA1 R L IH0 P ER0 +STARLIT S T AA1 R L IH0 T +STARMAN S T AA1 R M AH0 N +STARMER S T AA1 R M ER0 +STARN S T AA1 R N +STARNER S T AA1 R N ER0 +STARNES S T AA1 R N Z +STARNS S T AA1 R N Z +STARODUBSTEV S T AA2 R OW0 D AH1 B S T EH2 V +STARON S T AE1 R AH0 N +STARPLEX S T AA1 R P L EH2 K S +STARPOINTE S T AA1 R P OY2 N T +STARR S T AA1 R +STARR'S S T AA1 R Z +STARRED S T AA1 R D +STARRETT S T AE1 R EH0 T +STARRING S T AA1 R IH0 NG +STARRS S T AA1 R Z +STARRY S T AA1 R IY2 +STARS S T AA1 R Z +STARS' S T AA1 R Z +STARSHIP S T AA1 R SH IH2 P +STARSIGHT S T AA1 R S AY2 T +STARSTREAM S T AA1 R S T R IY2 M +STARSTRUCK S T AA1 R S T R AH2 K +START S T AA1 R T +START-UP S T AA1 R T AH2 P +START-UPS S T AA1 R T AH1 P S +STARTED S T AA1 R T IH0 D +STARTER S T AA1 R T ER0 +STARTERS S T AA1 R T ER0 Z +STARTING S T AA1 R T IH0 NG +STARTLE S T AA1 R T AH0 L +STARTLED S T AA1 R T AH0 L D +STARTLES S T AA1 R T AH0 L Z +STARTLING S T AA1 R T L IH0 NG +STARTLINGLY S T AA1 R T L IH0 NG L IY2 +STARTS S T AA1 R T S +STARTUP S T AA1 R T AH2 P +STARTUPS S T AA1 R T AH2 P S +STARVATION S T AA0 R V EY1 SH AH0 N +STARVE S T AA1 R V +STARVED S T AA1 R V D +STARVES S T AA1 R V Z +STARVING S T AA1 R V IH0 NG +STARWALT S T AA1 R W AH0 L T +STARWAVE S T AA1 R W EY2 V +STARY S T EH1 R IY0 +STARZYK S T AA1 R Z IH0 K +STASH S T AE1 SH +STASHED S T AE1 SH T +STASHING S T AE1 SH IH0 NG +STASI S T AA1 S IY0 +STASIAK S T AA1 S IY0 AE0 K +STASIK S T AA1 S IH0 K +STASIO S T AA1 S IY0 OW0 +STASKO S T AA1 S K OW0 +STASNEY S T AE1 S N IY0 +STASNY S T AE1 S N IY0 +STASSEN S T AE1 S AH0 N +STASSI S T AE1 S IY0 +STASTNY S T AE1 S T N IY2 +STASZAK S T AA1 SH AH0 K +STASZEWSKI S T AH0 SH EH1 F S K IY2 +STAT S T AE1 T +STATE S T EY1 T +STATE'S S T EY1 T S +STATE-OF-THE-ART S T EY2 T AH0 V DH IH0 AA1 R T +STATECRAFT S T EY1 T K R AE2 F T +STATED S T EY1 T IH0 D +STATEHOOD S T EY1 T HH UH2 D +STATEHOUSE S T EY1 T HH AW2 S +STATEHOUSES S T EY1 T HH AW2 S IH0 Z +STATELESS S T EY1 T L IH0 S +STATELY S T EY1 T L IY0 +STATEMENT S T EY1 T M AH0 N T +STATEMENT'S S T EY1 T M AH0 N T S +STATEMENTS S T EY1 T M AH0 N T S +STATEN S T AE1 T AH0 N +STATER S T EY1 T ER0 +STATER'S S T EY1 T ER0 Z +STATERS S T EY1 T ER0 Z +STATES S T EY1 T S +STATES' S T EY1 T S +STATESBOROUGH S T EY1 T S B AH0 R OW0 +STATESIDE S T EY1 T S AY1 D +STATESMAN S T EY1 T S M AH0 N +STATESMAN'S S T EY1 T S M AH0 N Z +STATESMANLIKE S T AH0 T EH1 S M AH0 N L AY2 K +STATESMANSHIP S T EY1 T S M AH0 N SH IH2 P +STATESMEN S T EY1 T S M IH0 N +STATESWEST S T EY2 T S W EH1 S T +STATEWIDE S T EY1 T W AY2 D +STATHAM S T AE1 TH AH0 M +STATHIS S T AE1 TH IH0 S +STATHOPOULOS S T AH0 TH AA1 P AH0 L IH0 S +STATIC S T AE1 T IH0 K +STATICS S T AE1 T IH0 K S +STATIN S T EY1 T IH0 N +STATIN'S S T EY1 T IH0 N Z +STATING S T EY1 T IH0 NG +STATINS S T EY1 T IH0 N Z +STATION S T EY1 SH AH0 N +STATION'S S T EY1 SH AH0 N Z +STATIONARY S T EY1 SH AH0 N EH2 R IY0 +STATIONED S T EY1 SH AH0 N D +STATIONER S T EY1 SH AH0 N ER0 +STATIONERS S T EY1 SH AH0 N ER0 Z +STATIONERY S T EY1 SH AH0 N EH2 R IY0 +STATIONING S T EY1 SH AH0 N IH0 NG +STATIONS S T EY1 SH AH0 N Z +STATIONS' S T EY1 SH AH0 N Z +STATISM S T EY1 T IH2 Z AH0 M +STATIST S T EY1 T IH0 S T +STATISTIC S T AH0 T IH1 S T IH0 K +STATISTICAL S T AH0 T IH1 S T IH0 K AH0 L +STATISTICALLY S T AH0 T IH1 S T IH0 K AH0 L IY0 +STATISTICALLY(1) S T AH0 T IH1 S T IH0 K L IY0 +STATISTICIAN S T AE2 T AH0 S T IH1 SH AH0 N +STATISTICIANS S T AE2 T IH0 S T IH1 SH AH0 N Z +STATISTICS S T AH0 T IH1 S T IH0 K S +STATISTICS' S T AH0 T IH1 S T IH0 K S +STATISTS S T EY1 T IH0 S T S +STATLER S T AE1 T L ER0 +STATOIL S T AH0 T OY1 L +STATON S T AE1 T AH0 N +STATS S T AE1 T S +STATTIN S T AE1 T IH0 N +STATTON S T AE1 T AH0 N +STATUARY S T AE1 CH UW0 EH2 R IY0 +STATUE S T AE1 CH UW2 +STATUES S T AE1 CH UW2 Z +STATUESQUE S T AE2 CH UW0 EH1 S K +STATUETTE S T AE2 CH UW0 EH1 T +STATUETTES S T AE2 CH UW0 EH1 T S +STATUM S T AE1 T AH0 M +STATURE S T AE1 CH ER0 +STATUS S T AE1 T AH0 S +STATUS(1) S T EY1 T AH0 S +STATUTE S T AE1 CH UW0 T +STATUTE'S S T AE1 CH UW0 T S +STATUTES S T AE1 CH UW0 T S +STATUTORILY S T AE1 CH AH0 T AO2 R AH0 L IY0 +STATUTORILY(1) S T AE1 CH Y UW0 T AO2 R AH0 L IY0 +STATUTORY S T AE1 CH AH0 T AO2 R IY0 +STATZ S T AE1 T S +STATZER S T AE1 T Z ER0 +STATZER(1) S T EY1 T Z ER0 +STAUB S T AO1 B +STAUBER S T AW1 B ER0 +STAUBIN S T AW1 B IH0 N +STAUBS S T AO1 B Z +STAUCH S T AO1 CH +STAUDACHER S T AW1 D AH0 K ER0 +STAUDE S T AO1 D +STAUDER S T AW1 D ER0 +STAUDINGER S T AW1 D IH0 NG ER0 +STAUDT S T AO1 D T +STAUFF S T AO1 F +STAUFFACHER S T AW1 F AH0 K ER0 +STAUFFER S T AO1 F ER0 +STAUFFER'S S T AO1 F ER0 Z +STAUNCH S T AO1 N CH +STAUNCHEST S T AO1 N CH AH0 S T +STAUNCHLY S T AO1 N CH L IY0 +STAUNTON S T AO1 N T AH0 N +STAUP S T AO1 P +STAUSS S T AO1 S +STAUTER S T AW1 T ER0 +STAVE S T EY1 V +STAVED S T EY1 V D +STAVELY S T EY1 V L IY0 +STAVER S T EY1 V ER0 +STAVES S T EY1 V Z +STAVING S T EY1 V IH0 NG +STAVINOHA S T AE0 V IH0 N OW1 HH AH0 +STAVOLA S T AA0 V OW1 L AH0 +STAVROPOULOS S T AH0 V R AA1 P AH0 L IH0 S +STAVROS S T AH0 V R OW1 Z +STAWICKI S T AA0 V IH1 T S K IY0 +STAWSKI S T AA1 F S K IY0 +STAY S T EY1 +STAYED S T EY1 D +STAYER S T EY1 ER0 +STAYING S T EY1 IH0 NG +STAYNER S T EY1 N ER0 +STAYOVER S T EY1 OW2 V ER0 +STAYOVERS S T EY1 OW2 V ER0 Z +STAYS S T EY1 Z +STAYTON S T EY1 T AH0 N +STDS EH1 S T IY1 D IY1 Z +STDS(1) EH1 S T IY1 D IY1 EH1 S +STEAD S T EH1 D +STEADFAST S T EH1 D F AE2 S T +STEADFASTLY S T EH1 D F AE2 S T L IY0 +STEADFASTNESS S T EH1 D F AE2 S T N AH0 S +STEADHAM S T EH1 D HH AH0 M +STEADIED S T EH1 D IY0 D +STEADIER S T EH1 D IY0 ER0 +STEADILY S T EH1 D AH0 L IY0 +STEADINESS S T EH1 D IY0 N IH0 S +STEADMAN S T EH1 D M AH0 N +STEADY S T EH1 D IY0 +STEAGALL S T IY1 G AH0 L +STEAGLE S T IY1 G AH0 L +STEAK S T EY1 K +STEAKHOUSE S T EY1 K HH AW2 S +STEAKHOUSES S T EY1 K HH AW2 S IH0 Z +STEAKLEY S T IY1 K L IY0 +STEAKS S T EY1 K S +STEAL S T IY1 L +STEALER S T IY1 L ER0 +STEALEY S T IY1 L IY0 +STEALING S T IY1 L IH0 NG +STEALS S T IY1 L Z +STEALTH S T EH1 L TH +STEALTHIER S T EH1 L TH IY0 ER0 +STEALTHIES S T EH1 L TH IY0 Z +STEALTHIEST S T EH1 L TH IY0 AH0 S T +STEALTHY S T EH1 L TH IY0 +STEAM S T IY1 M +STEAMBOAT S T IY1 M B OW2 T +STEAMBOATS S T IY1 M B OW2 T S +STEAMED S T IY1 M D +STEAMER S T IY1 M ER0 +STEAMERS S T IY1 M ER0 Z +STEAMIER S T IY1 M IY0 ER0 +STEAMIEST S T IY1 M IY0 AH0 S T +STEAMILY S T IY1 M AH0 L IY0 +STEAMING S T IY1 M IH0 NG +STEAMROLLER S T IY1 M R OW2 L ER0 +STEAMROLLERED S T IY1 M R OW2 L ER0 D +STEAMS S T IY1 M Z +STEAMSHIP S T IY1 M SH IH2 P +STEAMY S T IY1 M IY0 +STEAR S T IH1 R +STEARIC S T IY1 R IH0 K +STEARMAN S T IH1 R M AH0 N +STEARN S T ER1 N +STEARNE S T ER1 N +STEARNS S T ER1 N Z +STEARNS'S S T ER1 N Z IH0 Z +STEARS S T IY1 R Z +STEBBINS S T EH1 B IH0 N Z +STEBER S T IY1 B ER0 +STEBNER S T EH1 B N ER0 +STEC S T EH1 K +STECH S T EH1 K +STECHER S T EH1 K ER0 +STECHLER S T EH1 K L ER0 +STECHSCHULTE S T EH1 K SH AH0 L T +STECK S T EH1 K +STECKEL S T EH1 K AH0 L +STECKELBERG S T EH1 K AH0 L B ER0 G +STECKER S T EH1 K ER0 +STECKLEIN S T EH1 K L AY2 N +STECKLER S T EH1 K L ER0 +STECKLEY S T EH1 K L IY0 +STECKMAN S T EH1 K M AH0 N +STEDMAN S T EH1 D M AH0 N +STEEB S T IY1 B +STEEBER S T IY1 B ER0 +STEED S T IY1 D +STEED'S S T IY1 D Z +STEEDLEY S T IY1 D L IY0 +STEEDMAN S T IY1 D M AH0 N +STEEDS S T IY1 D Z +STEEG S T IY1 G +STEEGE S T IY1 JH +STEEGO S T IY1 G OW0 +STEEL S T IY1 L +STEEL'S S T IY1 L Z +STEELCASE S T IY1 L K EY2 S +STEELE S T IY1 L +STEELED S T IY1 L D +STEELER S T IY1 L ER0 +STEELERS S T IY1 L ER0 Z +STEELEY S T IY1 L IY0 +STEELHEAD S T IY1 L HH EH2 D +STEELMAKER S T IY1 L M EY2 K ER0 +STEELMAKER'S S T IY1 L M EY2 K ER0 Z +STEELMAKERS S T IY1 L M EY2 K ER0 Z +STEELMAKERS' S T IY1 L M AH0 K ER0 Z +STEELMAKING S T IY1 L M EY2 K IH0 NG +STEELMAN S T IY1 L M AH0 N +STEELS S T IY1 L Z +STEELWORKER S T IY1 L W ER2 K ER0 +STEELWORKERS S T IY1 L W ER2 K ER0 Z +STEELWORKERS' S T IY1 L W ER0 K ER0 Z +STEELWORKS S T IY1 L W ER2 K S +STEELY S T IY1 L IY0 +STEEN S T IY1 N +STEENBERGEN S T IY1 N B ER0 G AH0 N +STEENBURGEN S T IY1 N B ER0 G AH0 N +STEENKAMP S T IY1 N K AE2 M P +STEENKISTE S T IY1 N K IH2 S T +STEENROD S T IY1 N R AH0 D +STEENSMA S T IY1 N Z M AH0 +STEENSON S T IY1 N S AH0 N +STEEP S T IY1 P +STEEPED S T IY1 P T +STEEPENED S T IY1 P AH0 N D +STEEPER S T IY1 P ER0 +STEEPEST S T IY1 P AH0 S T +STEEPLE S T IY1 P AH0 L +STEEPLECHASE S T IY1 P AH0 L CH EY2 S +STEEPLES S T IY1 P AH0 L Z +STEEPLY S T IY1 P L IY0 +STEEPNESS S T IY1 P N AH0 S +STEER S T IH1 R +STEERE S T IH1 R +STEERED S T IH1 R D +STEERING S T IH1 R IH0 NG +STEERS S T IH1 R Z +STEES S T IY1 Z +STEETON S T IY1 T AH0 N +STEEVER S T IY1 V ER0 +STEEVES S T IY1 V Z +STEFA S T EH1 F AH0 +STEFAN S T EH1 F AA0 N +STEFANELLI S T EH0 F AA0 N EH1 L IY0 +STEFANI S T EH1 F AH0 N IY0 +STEFANI'S S T EH1 F AH0 N IY0 Z +STEFANIAK S T IH0 F AE1 N IY0 AE0 K +STEFANIC S T IH0 F AE1 N IH0 K +STEFANICH S T EH1 F AH0 N IH0 CH +STEFANICK S T EH1 F AH0 N IH0 K +STEFANIE S T EH1 F AH0 N IY0 +STEFANIK S T IH0 F AE1 N IH0 K +STEFANKO S T IH0 F AE1 NG K OW0 +STEFANO S T EH1 F AH0 N OW0 +STEFANOPOLIS S T EH2 F AH0 N AO1 P AH0 L AH0 S +STEFANOWICZ S T IH0 F AE1 N AH0 V IH0 CH +STEFANSKI S T IH0 F AE1 N S K IY0 +STEFFAN S T EH1 F AH0 N +STEFFANCI S T EH2 F AA1 N S IY0 +STEFFE S T EH1 F +STEFFEK S T EH1 F IH0 K +STEFFEL S T EH1 F AH0 L +STEFFEN S T EH1 F AH0 N +STEFFENHAGEN S T EH1 F IH0 N HH AH0 G AH0 N +STEFFENS S T EH1 F AH0 N Z +STEFFENSEN S T EH1 F IH0 N S AH0 N +STEFFENSMEIER S T EH1 F IH0 N S M AY0 ER0 +STEFFENSON S T EH1 F IH0 N S AH0 N +STEFFES S T EH1 F S +STEFFEY S T EH1 F IY0 +STEFFI S T EH1 F IY0 +STEFFIE S T EH1 F IY0 +STEFFLER S T EH1 F L ER0 +STEFFY S T EH1 F IY0 +STEFKO S T EH1 F K OW0 +STEFL S T EH1 F AH0 L +STEGALL S T EH1 G AH0 L +STEGAR S T IY1 G ER0 +STEGAR'S S T IY1 G ER0 Z +STEGE S T IY1 JH +STEGEMAN S T IY1 G M AH0 N +STEGEMANN S T IY1 G M AH0 N +STEGEMEIER S T EH1 G M AY2 R +STEGENGA S T EH0 JH EH1 NG G AH0 +STEGER S T IY1 G ER0 +STEGMAIER S T EH1 G M AY0 ER0 +STEGMAN S T EH1 G M AH0 N +STEGMANN S T EH1 G M AH0 N +STEGNER S T EH1 G N ER0 +STEGOSAURUS S T EH2 G AH0 S AO1 R AH0 S +STEHLE S T EH1 HH AH0 L +STEHLIK S T EH1 L IH0 K +STEHLIN S T EH1 L IH0 N +STEHLING S T EH1 L IH0 NG +STEHMAN S T EH1 M AH0 N +STEHR S T EH1 R +STEIB S T IY1 B +STEICHEN S T AY1 K AH0 N +STEIDEL S T AY1 D AH0 L +STEIDINGER S T AY1 D IH0 NG ER0 +STEIDL S T IY1 D AH0 L +STEIDLE S T IY1 D AH0 L +STEIDTMANN S T AY1 T M AH0 N +STEIER S T AY1 ER0 +STEIG S T IY1 G +STEIGER S T AY1 G ER0 +STEIGERWALD S T AY1 G ER0 W AO2 L D +STEIGERWALT S T AY1 G ER0 W AH0 L T +STEIL S T IY1 L +STEIMAN S T AY1 M AH0 N +STEIMEL S T AY1 M AH0 L +STEIMER S T AY1 M ER0 +STEIMLE S T IY1 M AH0 L +STEIN S T AY1 N +STEIN'S S T AY1 N Z +STEINACKER S T AY1 N AE0 K ER0 +STEINBACH S T AY1 N B AA2 K +STEINBACHER S T AY1 N B AA2 K ER0 +STEINBACK S T AY1 N B AE2 K +STEINBAUER S T AY1 N B AW0 ER0 +STEINBAUGH S T AY1 N B AW0 +STEINBECK S T AY1 N B EH2 K +STEINBECK'S S T AY1 N B EH2 K S +STEINBERG S T AY1 N B ER0 G +STEINBERG'S S T AY1 N B ER0 G Z +STEINBERGEN S T AY1 N B AH0 R G AH0 N +STEINBERGER S T AY1 N B ER0 G ER0 +STEINBOCK S T AY1 N B AA2 K +STEINBORN S T AY1 N B AO1 R N +STEINBRECHER S T AY1 N B R EH2 K ER0 +STEINBRENNER S T AY1 N B R EH2 N ER0 +STEINBRINK S T AY1 N B R IH2 NG K +STEINEM S T AY1 N AH0 M +STEINER S T AY1 N ER0 +STEINER'S S T AY1 N ER0 Z +STEINERT S T AY1 N ER0 T +STEINES S T AY1 N Z +STEINFELD S T AY1 N F EH2 L D +STEINFELDT S T AY1 N F EH2 L T +STEINGUT S T AY1 N G AH2 T +STEINHAGEN S T AY1 N HH AE0 G AH0 N +STEINHARDT S T AY1 N HH AA2 R T +STEINHARDT'S S T AY1 N HH AA0 R T S +STEINHART S T AY1 N HH AA2 R T +STEINHAUER S T AY1 N HH AW0 ER0 +STEINHAUS S T AY1 N HH AW2 S +STEINHAUSER S T AY1 N HH AW2 Z ER0 +STEINHILBER S T AY1 N HH IH2 L B ER0 +STEINHOFF S T AY1 N HH AO2 F +STEINHORST S T AY1 N HH AO0 R S T +STEININGER S T AY1 N IH0 NG ER0 +STEINKAMP S T AY1 NG K AE0 M P +STEINKE S T AY1 NG K +STEINKRAUS S T AY1 NG K R AW0 Z +STEINKRAUSS S T AY1 N K R AW2 S +STEINKUEHLER S T AY1 N K Y UW2 L ER0 +STEINLE S T AY1 N AH0 L +STEINMAN S T AY1 N M AH0 N +STEINMANN S T AY1 N M AH0 N +STEINMETZ S T AY1 N M EH0 T S +STEINMEYER S T AY1 N M AY0 ER0 +STEINMILLER S T AY1 N M IH2 L ER0 +STEINROE S T AY1 N R OW2 +STEINWAY S T AY1 N W EY2 +STEINWAY'S S T AY1 N W EY2 Z +STEITZ S T IY1 T S +STEJSKAL S T EH1 JH S K AH0 L +STEKETEE S T EH1 K IH0 T IY0 +STEKLY S T EH1 K L IY0 +STELCO S T EH1 L K OW0 +STELIAN S T IY1 L IY0 AH0 N +STELL S T EH1 L +STELLA S T EH1 L AH0 +STELLA'S S T EH1 L AH0 Z +STELLAR S T EH1 L ER0 +STELLARTON S T EH1 L ER0 T AH0 N +STELLATO S T EH0 L AA1 T OW0 +STELLE S T EH1 L +STELLENBOSCH S T EH1 L AH0 N B AO2 SH +STELLER S T EH1 L ER0 +STELLHORN S T EH1 L HH ER0 N +STELLING S T EH1 L IH0 NG +STELLJES S T EY1 L Y EH0 S +STELLMACH S T EH1 L M AH0 K +STELLMACHER S T EH1 L M AH0 K ER0 +STELLMAN S T EH1 L M AH0 N +STELLO S T EH1 L OW0 +STELLY S T EH1 L IY0 +STELMACH S T EH1 L M AH0 K +STELMACK S T EH1 L M AH0 K +STELOFF S T EH1 L AO0 F +STELTER S T EH1 L T ER0 +STELTZ S T EH1 L T S +STELZER S T EH1 L Z ER0 +STELZNER S T EH1 L Z N ER0 +STEM S T EH1 M +STEMBERG S T EH1 M B ER0 G +STEMBRIDGE S T EH1 M B R IH2 JH +STEMEN S T EH1 M AH0 N +STEMLER S T EH1 M L ER0 +STEMLIKE S T EH1 M L AY2 K +STEMM S T EH1 M +STEMMED S T EH1 M D +STEMMER S T EH1 M ER0 +STEMMING S T EH1 M IH0 NG +STEMMLER S T EH1 M L ER0 +STEMPEL S T EH1 M P AH0 L +STEMPEL'S S T EH1 M P AH0 L Z +STEMPER S T EH1 M P ER0 +STEMPIEN S T EH1 M P IY0 N +STEMPLE S T EH1 M P AH0 L +STEMPLER S T EH1 M P L ER0 +STEMPLER'S S T EH1 M P L ER0 Z +STEMPOSTS S T EH1 M P OW2 S T S +STEMS S T EH1 M Z +STEN S T EH1 N +STENA S T IY1 N AH0 +STENA(1) S T EH1 N AH0 +STENA(2) S T EY1 N AH0 +STENBERG S T EH1 N B ER0 G +STENCEL S T EH1 N S AH0 L +STENCH S T EH1 N CH +STENCIL S T EH1 N S IH0 L +STENCILED S T EH1 N S IH0 L D +STENCILING S T EH1 N S IH0 L IH0 NG +STENCILING(1) S T EH1 N S L IH0 NG +STENDAL S T EH1 N D AH0 L +STENDER S T EH1 N D ER0 +STENDHAL S T EH1 N D AA0 L +STENDIG S T EH1 N D IH0 G +STENE S T IY1 N +STENERSON S T EH1 N ER0 S AH0 N +STENGEL S T EH1 NG G AH0 L +STENGER S T EH1 N JH ER0 +STENGLEIN S T IH1 NG L AY0 N +STENHOLM S T EH1 N HH OW2 L M +STENHOUSE S T EH1 N HH AW2 S +STENNER S T EH1 N ER0 +STENNETT S T EH1 N IH0 T +STENNIS S T EH1 N IH0 S +STENO S T EH1 N OW0 +STENOGRAPHER S T EH0 N AH1 G R AH0 F ER0 +STENOGRAPHIC S T EH2 N AH0 G R AE1 F IH0 K +STENOSIS S T EH2 N OW1 S IH0 S +STENQUIST S T EH1 N K W IH2 S T +STENSETH S T EH1 N S IH0 TH +STENSLAND S T EH1 N S L AH0 N D +STENSON S T EH1 N S AH0 N +STENSRUD S T EH1 N S R AH0 D +STENSTROM S T EH1 N S T R AH0 M +STENT S T EH1 N T +STENTOR S T EH1 N T ER0 +STENTORS S T EH1 N T ER0 Z +STENTZ S T EH1 N T S +STENY S T EH1 N IY0 +STENZ S T EH1 N Z +STENZEL S T EH1 N Z AH0 L +STEP S T EH1 P +STEPAN S T EH1 P AH0 N +STEPANAKERT S T AH0 P AE1 N AH0 K ER0 T +STEPANEK S T EH1 P AH0 N IH0 K +STEPANIAN S T IH0 P EY1 N IY0 AH0 N +STEPANIAN'S S T IH0 P EY1 N IY0 AH0 N Z +STEPANSKI S T IH0 P AE1 N S K IY0 +STEPCHILD S T EH1 P CH AY2 L D +STEPCHILDREN S T EH1 P CH IH1 L D R AH0 N +STEPDAUGHTER S T EH1 P D AO2 T ER0 +STEPDAUGHTERS S T EH1 P D AO2 T ER0 Z +STEPFATHER S T EH1 P F AA2 DH ER0 +STEPH S T EH1 F +STEPHA S T EH1 F AH0 +STEPHAN S T EH1 F AH0 N +STEPHANA S T EH0 F AA1 N AH0 +STEPHANE S T EH0 F AA1 N +STEPHANI S T EH1 F AH0 N IY0 +STEPHANIA S T IH0 F AE1 N IY0 AH0 +STEPHANIE S T EH1 F AH0 N IY0 +STEPHANOPOULOS S T EH2 F AH0 N AA1 P AH0 L AH0 S +STEPHANOPOULOS' S T EH2 F AH0 N AA1 P AH0 L AH0 S +STEPHANOPOULOS'S S T EH2 F AH0 N AA1 P AH0 L AH0 S IH0 S +STEPHANS S T EH1 F AH0 N Z +STEPHANY S T EH1 F AH0 N IY0 +STEPHEN S T IY1 V AH0 N +STEPHEN'S S T IY1 V AH0 N Z +STEPHENS S T IY1 V AH0 N Z +STEPHENS(1) S T EH1 F AH0 N Z +STEPHENS'S S T IY1 V IH0 N Z IH0 Z +STEPHENSON S T IY1 V AH0 N S AH0 N +STEPHENVILLE S T IY1 V IH0 N V IH2 L +STEPIEN S T EH1 P IY0 AH0 N +STEPKA S T EH1 P K AA2 +STEPLADDER S T EH1 P L AE2 D ER0 +STEPLADDERS S T EH1 P L AE2 D ER0 Z +STEPMOTHER S T EH1 P M AH2 DH ER0 +STEPNEY S T EH1 P N IY0 +STEPP S T EH1 P +STEPPE S T EH1 P +STEPPED S T EH1 P T +STEPPEL S T EH1 P AH0 L +STEPPENWOLF S T EH1 P AH0 N W UH2 L F +STEPPER S T EH1 P ER0 +STEPPERS S T EH1 P ER0 Z +STEPPES S T EH1 P S +STEPPIN' S T EH1 P IH0 N +STEPPING S T EH1 P IH0 NG +STEPPINGSTONE S T EH1 P IH0 NG S T OW2 N +STEPS S T EH1 P S +STEPSISTER S T EH1 P S IH2 S T ER0 +STEPSISTERS S T EH1 P S IH2 S T ER0 Z +STEPSON S T EH1 P S AH2 N +STEPTOE S T EH1 P T OW2 +STERBA S T EH1 R B AH0 +STERBENZ S T ER1 B IH0 N S +STERCHI S T EH1 R K IY0 +STEREO S T EH1 R IY0 OW2 +STEREOGRAPHIC S T EH2 R IY2 OW0 G R AE1 F IH0 K +STEREOLAB S T EH1 R IY2 OW0 L AE2 B +STEREOMICROSCOPE S T EH2 R IY2 OW0 M AY1 K R AH0 S K OW2 P +STEREOS S T EH1 R IY0 OW2 Z +STEREOTACTIC S T EH2 R IY0 OW2 T AE1 K T IH0 K +STEREOTYPE S T EH1 R IY0 OW0 T AY2 P +STEREOTYPED S T EH1 R IY0 OW0 T AY2 P T +STEREOTYPES S T EH1 R IY0 OW0 T AY2 P S +STEREOTYPICAL S T EH2 R IY0 OW0 T IH1 P IH0 K AH0 L +STEREOTYPICALLY S T EH2 R IY0 OW0 T IH1 P IH0 K AH0 L IY2 +STEREOTYPING S T EH1 R IY0 OW0 T AY2 P IH0 NG +STERETT S T EH1 R IH0 T +STERETT'S S T EH1 R AH0 T S +STERILE S T EH1 R AH0 L +STERILITY S T ER0 IH1 L IH0 T IY0 +STERILIZATION S T EH2 R AH0 L AH0 Z EY1 SH AH0 N +STERILIZATION(1) S T EH2 R AH0 L IH0 Z EY1 SH AH0 N +STERILIZATIONS S T EH2 R AH0 L AH0 Z EY1 SH AH0 N Z +STERILIZATIONS(1) S T EH2 R AH0 L IH0 Z EY1 SH AH0 N Z +STERILIZE S T EH1 R AH0 L AY2 Z +STERILIZED S T EH1 R AH0 L AY2 Z D +STERILIZER S T EH1 R AH0 L AY2 Z ER0 +STERILIZERS S T EH1 R AH0 L AY2 Z ER0 Z +STERILIZES S T EH1 R AH0 L AY2 Z IH0 Z +STERILIZING S T EH1 R AH0 L AY2 Z IH0 NG +STERK S T ER1 K +STERKEL S T ER1 K AH0 L +STERLE S T ER1 AH0 L +STERLING S T ER1 L IH0 NG +STERLING'S S T ER1 L IH0 NG Z +STERMAN S T ER1 M AH0 N +STERMER S T ER1 M ER0 +STERN S T ER1 N +STERN'S S T ER1 N Z +STERNBACH S T ER1 N B AA0 K +STERNBERG S T ER1 N B ER0 G +STERNBERGER S T ER1 N B ER0 G ER0 +STERNE S T ER1 N +STERNEM S T ER1 N EH0 M +STERNER S T ER1 N ER0 +STERNEST S T ER1 N AH0 S T +STERNFELD S T ER1 N F EH0 L D +STERNHAGEN S T ER1 N HH AH0 G AH0 N +STERNLY S T ER1 N L IY0 +STERNNESS S T ER1 N N AH0 S +STERNNESS(1) S T ER1 N AH0 S +STERNPOST S T ER1 N P OW2 S T +STERNPOSTS S T ER1 N P OW2 S T S +STERNS S T ER1 N Z +STEROID S T ER0 OY1 D +STEROIDS S T EH1 R OY0 D Z +STERR S T EH1 R +STERRETT S T EH1 R IH0 T +STERRY S T EH1 R IY0 +STET S T EH1 T +STETHEM S T EH1 TH AH0 M +STETHEM(1) S T EH1 T AH0 M +STETHOSCOPE S T EH1 TH AH0 S K OW2 P +STETHOSCOPES S T EH1 TH AH0 S K OW2 P S +STETLER S T EH1 T L ER0 +STETSON S T EH1 T S AH0 N +STETTER S T EH1 T ER0 +STETTLER S T EH1 T L ER0 +STETTNER S T EH1 T N ER0 +STETZ S T EH1 T S +STETZEL S T EH1 T Z AH0 L +STETZER S T EH1 T Z ER0 +STEUART S T OY1 AA0 R T +STEUBEN S T Y UW1 B IH0 N +STEUBEN(1) S T UW1 B IH0 N +STEUBENVILLE S T UW1 B AH0 N V IH2 L +STEUBER S T OY1 B ER0 +STEUCK S T UW1 K +STEUER S T OY1 ER0 +STEUERWALD S T OY1 ER0 W AO0 L D +STEURER S T ER1 ER0 +STEUVER S T UW1 V ER0 +STEVANA S T IH0 V AE1 N AH0 +STEVE S T IY1 V +STEVE'S S T IY1 V Z +STEVEDORE S T IY1 V AH0 D AO2 R +STEVEDORING S T IY1 V AH0 D AO2 R IH0 NG +STEVEN S T IY1 V AH0 N +STEVEN'S S T IY1 V AH0 N Z +STEVENA S T EH1 V IH0 N AH0 +STEVENS S T IY1 V AH0 N Z +STEVENS' S T IY1 V AH0 N Z +STEVENS'S S T IY1 V AH0 N Z AH0 Z +STEVENS'S(1) S T IY1 V AH0 N Z IH0 Z +STEVENSON S T IY1 V AH0 N S AH0 N +STEVER S T IY1 V ER0 +STEVERSON S T EH1 V ER0 S AH0 N +STEVES S T IY1 V Z +STEVESON S T EH1 V IH0 S AH0 N +STEVICK S T EH1 V IH0 K +STEVIE S T IY1 V IY0 +STEVISON S T EH1 V IH0 S AH0 N +STEW S T UW1 +STEW'S S T UW1 Z +STEWARD S T UW1 ER0 D +STEWARDESS S T UW1 ER0 D AH0 S +STEWARDESSES S T UW1 ER0 D AH0 S IH0 Z +STEWARDS S T UW1 ER0 D Z +STEWARDSHIP S T UW1 ER0 D SH IH2 P +STEWART S T UW1 ER0 T +STEWART'S S T UW1 ER0 T S +STEWED S T UW1 D +STEWING S T UW1 IH0 NG +STEWS S T UW1 Z +STEYER S T EY1 ER0 +STIBEL S T IH1 B AH0 L +STICE S T AY1 S +STICH S T IH1 CH +STICHA S T IH1 CH AH0 +STICHNOTH S T IH1 K N AA2 TH +STICHT S T IH1 K T +STICHTER S T IH1 K T ER0 +STICK S T IH1 K +STICKA S T IH1 K AH0 +STICKBALL S T IH1 K B AO2 L +STICKEL S T IH1 K AH0 L +STICKELS S T IH1 K AH0 L Z +STICKER S T IH1 K ER0 +STICKERS S T IH1 K ER0 Z +STICKIER S T IH1 K IY0 ER0 +STICKIEST S T IH1 K IY0 AH0 S T +STICKING S T IH1 K IH0 NG +STICKLAND S T IH1 K L AH0 N D +STICKLE S T IH1 K AH0 L +STICKLER S T IH1 K AH0 L ER0 +STICKLER(1) S T IH1 K L ER0 +STICKLES S T IH1 K AH0 L Z +STICKLEY S T IH1 K L IY0 +STICKNEY S T IH1 K N IY0 +STICKS S T IH1 K S +STICKTIGHT S T IH1 K T AY2 T +STICKTIGHTS S T IH1 K T AY2 T S +STICKY S T IH1 K IY0 +STIDD S T IH1 D +STIDHAM S T IH1 D HH AH0 M +STIEBEL S T IY1 B AH0 L +STIEBER S T IY1 B ER0 +STIEF S T IY1 F +STIEFEL S T IY1 F AH0 L +STIEFELHAGEN S T IY1 F AH0 L HH EY2 G AH0 N +STIEFELHAGEN(1) S T AY1 F AH0 L HH EY2 G AH0 N +STIEFVATER S T IY1 F V AH0 T ER0 +STIEG S T IY1 G +STIEGEMEIER S T IY1 JH AH0 M AY2 R +STIEGLER S T IY1 G L ER0 +STIEGLITZ S T IY1 G L IH0 T S +STIEHL S T IY1 L +STIENS S T IY1 N Z +STIER S T AY1 ER0 +STIERS S T AY1 ER0 Z +STIERWALT S T IH1 R W AH0 L T +STIEVE S T IY1 V +STIFEL S T IH1 F AH0 L +STIFF S T IH1 F +STIFFED S T IH1 F T +STIFFEL S T IH1 F AH0 L +STIFFEN S T IH1 F AH0 N +STIFFENED S T IH1 F AH0 N D +STIFFENER S T IH1 F AH0 N ER0 +STIFFENING S T IH1 F AH0 N IH0 NG +STIFFENING(1) S T IH1 F N IH0 NG +STIFFENS S T IH1 F AH0 N Z +STIFFER S T IH1 F ER0 +STIFFEST S T IH1 F AH0 S T +STIFFLER S T IH1 F L ER0 +STIFFLY S T IH1 F L IY0 +STIFFNESS S T IH1 F N AH0 S +STIFFS S T IH1 F S +STIFLE S T AY1 F AH0 L +STIFLED S T AY1 F AH0 L D +STIFLER S T AY1 F L ER0 +STIFLES S T AY1 F AH0 L Z +STIFLING S T AY1 F L IH0 NG +STIFLING(1) S T AY1 F AH0 L IH0 NG +STIFTER S T IH1 F T ER0 +STIG S T IH1 G +STIGALL S T IH1 G AH0 L +STIGER S T AY1 G ER0 +STIGERS S T AY1 G ER0 Z +STIGLER S T IH1 G L ER0 +STIGLITZ S T IH1 G L IH0 T S +STIGMA S T IH1 G M AH0 +STIGMATA S T IH0 G M AA1 T AH0 +STIGMATISM S T IH1 G M AH0 T IH2 Z AH0 M +STIGMATIZE S T IH1 G M AH0 T AY2 Z +STIGMATIZED S T IH1 G M AH0 T AY2 Z D +STIGMATIZING S T IH1 G M AH0 T AY2 Z IH0 NG +STIHL S T IH1 L +STIKA S T IH1 K AH0 +STIKELEATHER S T IH1 K IH0 L EH0 DH ER0 +STIKELEATHER(1) S T IH1 K L EH0 DH ER0 +STIKELEATHER(2) S T AY1 K L EH0 DH ER0 +STIL S T IH1 L +STILE S T AY1 L +STILES S T AY1 L Z +STILETTO S T AH0 L EH1 T OW0 +STILETTOS S T AH0 L EH1 T OW0 Z +STILL S T IH1 L +STILLBORN S T IH1 L B AO1 R N +STILLE S T IH1 L +STILLED S T IH1 L D +STILLER S T IH1 L ER0 +STILLER'S S T IH1 L ER0 Z +STILLEY S T IH1 L IY0 +STILLINGER S T IH1 L IH0 NG ER0 +STILLINGS S T IH1 L IH0 NG Z +STILLION S T IH1 L Y AH0 N +STILLMAN S T IH1 L M AH0 N +STILLNESS S T IH1 L N AH0 S +STILLS S T IH1 L Z +STILLSON S T IH1 L S AH0 N +STILLWAGON S T IH1 L W AE2 G AH0 N +STILLWATER S T IH1 L W AO2 T ER0 +STILLWELL S T IH1 L W EH2 L +STILLWELL'S S T IH1 L W EH2 L Z +STILS S T IH1 L Z +STILSON S T IH1 L S AH0 N +STILT S T IH1 L T +STILTED S T IH1 L T IH0 D +STILTNER S T IH1 L T N ER0 +STILTS S T IH1 L T S +STILWELL S T IH1 L W EH2 L +STIMAC S T IH1 M AH0 K +STIMMEL S T IH1 M AH0 L +STIMPERT S T IH1 M P ER0 T +STIMPSON S T IH1 M P S AH0 N +STIMPY S T IH1 M P IY0 +STIMSON S T IH1 M S AH0 N +STIMULANT S T IH1 M Y AH0 L AH0 N T +STIMULANTS S T IH1 M Y AH0 L AH0 N T S +STIMULATE S T IH1 M Y AH0 L EY2 T +STIMULATED S T IH1 M Y AH0 L EY2 T IH0 D +STIMULATES S T IH1 M Y AH0 L EY2 T S +STIMULATING S T IH1 M Y AH0 L EY2 T IH0 NG +STIMULATION S T IH2 M Y AH0 L EY1 SH AH0 N +STIMULATIVE S T IH1 M Y AH0 L EY2 T IH0 V +STIMULATOR S T IH1 M Y AH0 L EY2 T ER0 +STIMULATORS S T IH1 M Y AH0 L EY2 T ER0 Z +STIMULI S T IH1 M Y AH0 L AY2 +STIMULUS S T IH1 M Y AH0 L AH0 S +STINAR S T AY1 N AA0 R +STINCHCOMB S T IH1 N CH K AH0 M +STINCHFIELD S T IH1 N CH F IY0 L D +STINE S T AY1 N +STINEBAUGH S T IH1 N IH0 B AO0 +STINEL S T IH1 N AH0 L +STINEL(1) S T IH2 N EH1 L +STINEL'S S T IH1 N AH0 L Z +STINEL'S(1) S T IH2 N EH1 L Z +STINEMAN S T AY1 N M AH0 N +STINER S T AY1 N ER0 +STINES S T AY1 N Z +STING S T IH1 NG +STING'S S T IH1 NG Z +STINGER S T IH1 NG ER0 +STINGERS S T IH1 NG ER0 Z +STINGIER S T IH1 N JH IY0 ER0 +STINGINESS S T IH1 N JH IY0 N IH0 S +STINGING S T IH1 NG IH0 NG +STINGLEY S T IH1 NG G L IY0 +STINGS S T IH1 NG Z +STINGY S T IH1 N JH IY0 +STINK S T IH1 NG K +STINKBUG S T IH1 NG K B AH0 G +STINKBUGS S T IH1 NG K B AH0 G Z +STINKERS S T IH1 NG K ER0 Z +STINKING S T IH1 NG K IH0 NG +STINKS S T IH1 NG K S +STINKY S T IH1 NG K IY0 +STINNETT S T IH1 N IH0 T +STINNETTE S T IH0 N EH1 T +STINSON S T IH1 N S AH0 N +STINT S T IH1 N T +STINTS S T IH1 N T S +STIPANOVICH S T IH0 P AE1 N AH0 V IH0 CH +STIPE S T AY1 P +STIPEND S T AY1 P AH0 N D +STIPENDS S T AY1 P AH0 N D Z +STIPES S T AY1 P S +STIPP S T IH1 P +STIPULATE S T IH1 P Y AH0 L EY2 T +STIPULATED S T IH1 P Y AH0 L EY2 T IH0 D +STIPULATES S T IH1 P Y AH0 L EY2 T S +STIPULATING S T IH1 P Y AH0 L EY2 T IH0 NG +STIPULATION S T IH2 P Y AH0 L EY1 SH AH0 N +STIPULATIONS S T IH2 P Y AH0 L EY1 SH AH0 N Z +STIR S T ER1 +STIRES S T AY1 R Z +STIREWALT S T ER1 W AA2 L T +STIRLING S T ER1 L IH0 NG +STIRLING'S S T ER1 L IH0 NG Z +STIRN S T ER1 N +STIRRED S T ER1 D +STIRRING S T ER1 IH0 NG +STIRRINGS S T ER1 IH0 NG Z +STIRRUP S T ER1 AH0 P +STIRRUPS S T ER1 AH0 P S +STIRS S T ER1 Z +STITCH S T IH1 CH +STITCHED S T IH1 CH T +STITCHES S T IH1 CH IH0 Z +STITCHING S T IH1 CH IH0 NG +STITELER S T AY1 T L ER0 +STITELY S T AY1 T L IY0 +STITES S T AY1 T S +STITH S T IH1 TH +STITT S T IH1 T +STITZ S T IH1 T S +STITZEL S T IH1 T Z AH0 L +STITZER S T IH1 T Z ER0 +STIVER S T AY1 V ER0 +STIVERS S T AY1 V ER0 Z +STIVERSON S T IH1 V ER0 S AH0 N +STIVORIC S T IH0 V AO1 R IH0 K +STJOHN S EY1 N T JH AA1 N +STOBAUGH S T AA1 B AO0 +STOBBE S T AA1 B +STOBER S T OW1 B ER0 +STOBIE S T AA1 B IY0 +STOCHASTIC S T OW0 K AE1 S T IH0 K +STOCHASTICALLY S T OW0 K AE1 S T IH0 K AH0 L IY2 +STOCHASTICS S T OW0 K AE1 S T IH0 K S +STOCK S T AA1 K +STOCK'S S T AA1 K S +STOCKADE S T AA1 K EY2 D +STOCKADE'S S T AA1 K EY2 D Z +STOCKADES S T AA1 K EY2 D Z +STOCKARD S T AA1 K ER0 D +STOCKBRIDGE S T AA1 K B R IH0 JH +STOCKBROKER S T AA1 K B R OW2 K ER0 +STOCKBROKER'S S T AA1 K B R OW2 K ER0 Z +STOCKBROKERAGE S T AA1 K B R OW2 K ER0 IH0 JH +STOCKBROKERAGES S T AA1 K B R OW2 K ER0 IH0 JH IH0 Z +STOCKBROKERS S T AA1 K B R OW2 K ER0 Z +STOCKBROKERS' S T AA1 K B R OW2 K ER0 Z +STOCKBROKING S T AA1 K B R OW2 K IH0 NG +STOCKBURGER S T AA1 K B ER0 G ER0 +STOCKDALE S T AA1 K D EY2 L +STOCKDALE'S S T AA1 K D EY2 L Z +STOCKE S T AA1 K +STOCKED S T AA1 K T +STOCKEL S T AA1 K AH0 L +STOCKER S T AA1 K ER0 +STOCKERT S T AA1 K ER0 T +STOCKETT S T AA1 K IH0 T +STOCKFORD S T AA1 K F ER0 D +STOCKHAM S T AA1 K HH AH0 M +STOCKHAUSEN S T AA1 K HH AW2 Z AH0 N +STOCKHOLDER S T AA1 K HH OW2 L D ER0 +STOCKHOLDERS S T AA1 K HH OW2 L D ER0 Z +STOCKHOLDERS' S T AA1 K HH OW2 L D ER0 Z +STOCKHOLDING S T AA1 K HH OW2 L D IH0 NG +STOCKHOLDINGS S T AA1 K HH OW2 L D IH0 NG Z +STOCKHOLM S T AA1 K HH OW2 L M +STOCKHOLM'S S T AA1 K HH OW2 L M Z +STOCKING S T AA1 K IH0 NG +STOCKINGER S T AA1 K IH0 NG ER0 +STOCKINGS S T AA1 K IH0 NG Z +STOCKLEY S T AA1 K L IY0 +STOCKMAN S T AA1 K M AH0 N +STOCKMAN'S S T AA1 K M AE2 N Z +STOCKMARKET S T AA1 K M AA2 R K IH0 T +STOCKPILE S T AA1 K P AY2 L +STOCKPILED S T AA1 K P AY2 L D +STOCKPILES S T AA1 K P AY2 L Z +STOCKPILING S T AA1 K P AY2 L IH0 NG +STOCKROOM S T AA1 K R UW2 M +STOCKS S T AA1 K S +STOCKS' S T AA1 K S +STOCKSDALE S T AA1 K S D EY2 L +STOCKSLAGER S T AA1 K S L EY0 G ER0 +STOCKSTILL S T AA1 K S T IH2 L +STOCKTON S T AA1 K T AH0 N +STOCKWELL S T AA1 K W EH2 L +STOCKY S T AA1 K IY0 +STOCKYARD S T AA1 K Y AA2 R D +STOCKYARDS S T AA1 K Y AA2 R D Z +STOCUM S T OW1 K AH0 M +STODDARD S T AA1 D ER0 D +STODDARD'S S T AA1 D ER0 D Z +STODGHILL S T AA1 JH HH IH2 L +STODGY S T AA1 JH IY0 +STODOLA S T OW0 D OW1 L AA2 +STODOLSKY S T AH0 D AO1 L S K IY2 +STOEBER S T OW1 B ER0 +STOECKEL S T OW1 K AH0 L +STOECKER S T OW1 K ER0 +STOECKLE S T OW1 K AH0 L +STOECKLEIN S T OW1 K L AY2 N +STOEGER S T OW1 G ER0 +STOEHR S T AO1 R +STOELTING S T OW1 L T IH0 NG +STOELTZE S T OW1 L T S +STOERMER S T AO1 R M ER0 +STOESSEL S T OW1 S AH0 L +STOEVER S T AA1 EH0 V ER0 +STOFER S T OW1 F ER0 +STOFF S T AO1 F +STOFFEL S T AA1 F AH0 L +STOFFELS S T AA1 F AH0 L Z +STOFFER S T AO1 F ER0 +STOFFERS S T AO1 F ER0 Z +STOFFREGEN S T AA1 F R IH0 G AH0 N +STOFKO S T OW1 F K OW2 +STOGA S T OW1 G AH0 +STOGDILL S T AA1 G D IH0 L +STOGIE S T OW1 G IY2 +STOGIES S T OW1 G IY2 Z +STOGNER S T AA1 G N ER0 +STOGSDILL S T AA1 G Z D IH0 L +STOHL S T OW1 L +STOHLER S T OW1 L ER0 +STOHR S T AO1 R +STOIA S T OW1 Y AA2 +STOIBER S T OY1 B ER0 +STOIC S T OW1 IH0 K +STOICALLY S T OW1 IH0 K L IY0 +STOICISM S T OW1 AH0 S IH2 Z AH0 M +STOICS S T OW1 IH0 K S +STOKE S T OW1 K +STOKED S T OW1 K T +STOKELY S T OW1 K L IY0 +STOKER S T OW1 K ER0 +STOKERS S T OW1 K ER0 Z +STOKES S T OW1 K S +STOKING S T OW1 K IH0 NG +STOKKE S T AA1 K +STOKLEY S T AA1 K L IY0 +STOKLOSA S T AH0 K L OW1 S AA2 +STOL S T OW1 L +STOLAR S T OW1 L ER0 +STOLARSKI S T AH0 L AA1 R S K IY2 +STOLARZ S T OW1 L AA0 R Z +STOLBERG S T OW1 L B ER0 G +STOLDT S T OW1 L T +STOLE S T OW1 L +STOLEN S T OW1 L AH0 N +STOLER S T OW1 L ER0 +STOLFI S T OW1 L F IY0 +STOLICHNAYA S T OW2 L IH0 K N AY1 AH0 +STOLID S T AA1 L AH0 D +STOLL S T OW1 L +STOLLAR S T AA1 L ER0 +STOLLE S T AA1 L +STOLLEN S T AA1 L AH0 N +STOLLER S T OW1 L ER0 +STOLLEY S T AA1 L IY0 +STOLLINGS S T OW1 L IH0 NG Z +STOLP S T OW1 L P +STOLPE S T OW1 L P +STOLPER S T OW1 L P ER0 +STOLT S T OW1 L T +STOLTE S T OW1 L T +STOLTENBERG S T OW1 L T AH0 N B ER0 G +STOLTMAN S T OW1 L T M AH0 N +STOLTZ S T OW1 L T S +STOLTZFUS S T OW1 L T S F AH0 S +STOLTZMAN S T OW1 L T S M AH0 N +STOLZ S T OW1 L Z +STOLZE S T OW1 L Z +STOMA S T OW1 M AH0 +STOMACH S T AH1 M AH0 K +STOMACHS S T AH1 M AH0 K S +STOMATA S T OW1 M AH0 T AH0 +STOMBAUGH S T AA1 M B AO2 +STOMP S T AA1 M P +STOMPED S T AA1 M P T +STOMPING S T AA1 M P IH0 NG +STONE S T OW1 N +STONE'S S T OW1 N Z +STONEBACK S T OW1 N B AE2 K +STONEBERG S T OW1 N B ER0 G +STONEBERGER S T OW1 N B ER0 G ER0 +STONEBRAKER S T AA1 N IH0 B R AH0 K ER0 +STONEBRAKER(1) S T OW1 N B R EY0 K ER0 +STONEBURNER S T OW1 N B ER2 N ER0 +STONECIPHER S T OW1 N S AY2 F ER0 +STONECUTTER S T OW1 N K AH2 T ER0 +STONECUTTERS S T OW1 N K AH2 T ER0 Z +STONECYPHER S T AA1 N IH0 S IH0 F ER0 +STONECYPHER(1) S T OW1 N S AY0 F ER0 +STONED S T OW1 N D +STONEHAM S T OW1 N AH0 M +STONEHENGE S T OW1 N HH EH2 N JH +STONEHILL S T OW1 N HH IH2 L +STONEHOCKER S T OW1 N HH AA2 K ER0 +STONEHOUSE S T OW1 N HH AW2 S +STONEKING S T OW1 N K IH2 NG +STONEMAN S T OW1 N M AH0 N +STONER S T OW1 N ER0 +STONERIDGE S T OW1 N R IH2 JH +STONEROCK S T OW1 N R AA2 K +STONES S T OW1 N Z +STONES' S T OW1 N Z +STONESIFER S T OW1 N S AY2 F ER0 +STONESTREET S T OW1 N S T R IY2 T +STONEWALL S T OW1 N W AO2 L +STONEWALLED S T OW1 N W AO2 L D +STONEWALLING S T OW1 N W AO2 L IH0 NG +STONEWARE S T OW1 N W EH2 R +STONEY S T OW1 N IY0 +STONG S T AO1 NG +STONGE S T AA1 N JH +STONING S T OW1 N IH0 NG +STONY S T OW1 N IY0 +STONYFIELD S T OW1 N IY0 F IY2 L D +STOOD S T UH1 D +STOOGE S T UW1 JH +STOOGES S T UW1 JH IH0 Z +STOOKEY S T UW1 K IY0 +STOOKSBURY S T UW1 K S B EH0 R IY0 +STOOL S T UW1 L +STOOLS S T UW1 L Z +STOOP S T UW1 P +STOOPED S T UW1 P T +STOOPING S T UW1 P IH0 NG +STOOPS S T UW1 P S +STOOTS S T UW1 T S +STOP S T AA1 P +STOP-GAP S T AA1 P G AE2 P +STOPA S T OW1 P AH0 +STOPGAP S T AA1 P G AE2 P +STOPHER S T AA1 F ER0 +STOPKA S T OW1 P K AH0 +STOPLIGHT S T AA1 P L AY2 T +STOPLIGHTS S T AA1 P L AY2 T S +STOPOVER S T AA1 P OW2 V ER0 +STOPOVERS S T AA1 P OW2 V ER0 Z +STOPPAGE S T AA1 P IH0 JH +STOPPAGES S T AA1 P IH0 JH IH0 Z +STOPPED S T AA1 P T +STOPPEL S T AA1 P AH0 L +STOPPER S T AA1 P ER0 +STOPPERS S T AA1 P ER0 Z +STOPPING S T AA1 P IH0 NG +STOPS S T AA1 P S +STOPWATCH S T AA1 P W AA2 CH +STOPWATCHES S T AA1 P W AA2 CH IH0 Z +STORA S T AO1 R AH0 +STORA'S S T AO1 R AH0 Z +STORAGE S T AO1 R AH0 JH +STORAGE(1) S T AO1 R IH0 JH +STORAGETEK S T AO1 R AH0 JH T EH2 K +STORASKA S T AO2 R AE1 S AH0 +STORBECK S T AO1 R B EH0 K +STORCH S T AO1 R K +STORCK S T AO1 R K +STORDAHL S T AO1 R D AA0 L +STORE S T AO1 R +STORE'S S T AO1 R Z +STORED S T AO1 R D +STOREFRONT S T AO1 R F R AA2 N T +STOREFRONTS S T AO1 R F R AA2 N T S +STOREHOUSE S T AO1 R HH AW2 S +STOREHOUSE'S S T AO1 R HH AW2 S IH0 Z +STOREHOUSES S T AO1 R HH AW2 Z AH0 Z +STOREKEEPER S T AO1 R K IY2 P ER0 +STOREKEEPERS S T AO1 R K IY2 P ER0 Z +STORER S T AO1 R ER0 +STORER'S S T AO1 R ER0 Z +STOREROOM S T AO1 R R UW2 M +STORES S T AO1 R Z +STORES' S T AO1 R Z +STOREY S T AO1 R IY0 +STORFER S T AO1 R F ER0 +STORIE S T AO1 R IY0 +STORIED S T AO1 R IY0 D +STORIES S T AO1 R IY0 Z +STORING S T AO1 R IH0 NG +STORK S T AO1 R K +STORLIE S T AO1 R L IY0 +STORM S T AO1 R M +STORM'S S T AO1 R M Z +STORMED S T AO1 R M D +STORMENT S T AO1 R M AH0 N T +STORMER S T AO1 R M ER0 +STORMES S T AO1 R M Z +STORMIEST S T AO1 R M IY0 IH0 S T +STORMINESS S T AO1 R M IY0 N IH0 S +STORMING S T AO1 R M IH0 NG +STORMONT S T AO1 R M OW0 N T +STORMS S T AO1 R M Z +STORMY S T AO1 R M IY0 +STORR S T AO1 R +STORROW S T AA1 R OW0 +STORRS S T AO1 R Z +STORTI S T AO1 R T IY0 +STORTING S T AO1 R T IH0 NG +STORTS S T AO1 R T S +STORTZ S T AO1 R T S +STORY S T AO1 R IY0 +STORY'S S T AO1 R IY0 Z +STORYBOARD S T AO1 R IY0 B AO2 R D +STORYBOOK S T AO1 R IY0 B UH2 K +STORYBOOKS S T AO1 R IY0 B UH2 K S +STORYLINE S T AO1 R IY0 L AY2 N +STORYLINES S T AO1 R IY0 L AY2 N Z +STORYTELLER S T AO1 R IY0 T EH2 L ER0 +STORYTELLERS S T AO1 R IY0 T EH2 L ER0 Z +STORYTELLING S T AO1 R IY0 T EH2 L IH0 NG +STORZ S T AO1 R Z +STOSSEL S T AA1 S AH0 L +STOSSEL'S S T AA1 S AH0 L Z +STOTLER S T AA1 T L ER0 +STOTT S T AA1 T +STOTTLEMYER S T AA1 T AH0 L M AY0 ER0 +STOTTS S T AA1 T S +STOTZ S T AA1 T S +STOUDEMIRE S T UW1 D AH0 M AY2 R +STOUDENMIRE S T UW1 D AH0 N M AY2 R +STOUDER S T AH1 D ER0 +STOUDT S T AH1 D T +STOUFFER S T AH1 F ER0 +STOUFFER(1) S T OW1 F ER0 +STOUFFS S T AH1 F S +STOUFFS(1) S T OW1 F S +STOUGH S T AH1 F +STOUGHTON S T OW1 T AH0 N +STOUP S T UW1 P +STOUT S T AW1 T +STOUTE S T AW1 T +STOUTENBURG S T AW1 T AH0 N B ER0 G +STOUTLY S T AW1 T L IY0 +STOUTNESS S T AW1 T N AH0 S +STOVALL S T OW1 V AA0 L +STOVE S T OW1 V +STOVER S T OW1 V ER0 +STOVES S T OW1 V Z +STOW S T OW1 +STOWAWAY S T OW1 AH0 W EY2 +STOWAWAY'S S T OW1 AH0 W EY2 Z +STOWAWAYS S T OW1 AH0 W EY2 Z +STOWE S T OW1 +STOWED S T OW1 D +STOWELL S T AA1 W EH0 L +STOWER S T OW1 ER0 +STOWERS S T OW1 ER0 Z +STOWING S T OW1 W IH0 NG +STOY S T OY1 +STOYER S T OY1 ER0 +STRACENER S T R AE1 S IY0 N ER0 +STRACHAN S T R AE1 CH AH0 N +STRACK S T R AE1 K +STRACKE S T R AE1 K +STRADA S T R AA1 D AH0 +STRADDLE S T R AE1 D AH0 L +STRADDLED S T R AE1 D AH0 L D +STRADDLES S T R AE1 D AH0 L Z +STRADDLING S T R AE1 D L IH0 NG +STRADER S T R EY1 D ER0 +STRADFORD S T R AE1 D F ER0 D +STRADIVARIUS S T R AE2 D IH0 V EH1 R IY0 AH0 S +STRADLEY S T R AE1 D L IY0 +STRADLING S T R AE1 D L IH0 NG +STRAFE S T R EY1 F +STRAFING S T R EY1 F IH0 NG +STRAGGLE S T R AE1 G AH0 L +STRAGGLED S T R AE1 G AH0 L D +STRAGGLER S T R AE1 G L ER0 +STRAGGLERS S T R AE1 G L ER0 Z +STRAHAN S T R AE1 HH AH0 N +STRAHL S T R AA1 L +STRAHLE S T R EY1 HH AH0 L +STRAHLER S T R AA1 L ER0 +STRAHM S T R AA1 M +STRAIGHT S T R EY1 T +STRAIGHTAWAY S T R EY1 T AH0 W EY2 +STRAIGHTAWAYS S T R EY1 T AH0 W EY2 Z +STRAIGHTEDGE S T R EY1 T EH2 JH +STRAIGHTEN S T R EY1 T AH0 N +STRAIGHTENED S T R EY1 T AH0 N D +STRAIGHTENING S T R EY1 T AH0 N IH0 NG +STRAIGHTENING(1) S T R EY1 T N IH0 NG +STRAIGHTENS S T R EY1 T AH0 N Z +STRAIGHTER S T R EY1 T ER0 +STRAIGHTFORWARD S T R EY1 T F AO1 R W ER0 D +STRAIGHTFORWARDLY S T R EY2 T F AO1 R W ER0 D L IY0 +STRAIGHTS S T R EY1 T S +STRAIN S T R EY1 N +STRAINED S T R EY1 N D +STRAINING S T R EY1 N IH0 NG +STRAINS S T R EY1 N Z +STRAIT S T R EY1 T +STRAITJACKET S T R EY1 T JH AE2 K AH0 T +STRAITS S T R EY1 T S +STRAKA S T R AA1 K AH0 +STRAKER S T R EY1 K ER0 +STRALEY S T R AE1 L IY0 +STRAM S T R AE1 M +STRANAHAN S T R AE1 N AH0 HH AE0 N +STRAND S T R AE1 N D +STRANDBERG S T R AE1 N D B ER0 G +STRANDE S T R AE1 N D +STRANDED S T R AE1 N D IH0 D +STRANDING S T R AE1 N D IH0 NG +STRANDLINE S T R AE1 N D L AY2 N +STRANDLINE(1) S T R AE1 N L AY2 N +STRANDLINES S T R AE1 N D L AY2 N Z +STRANDLINES(1) S T R AE1 N L AY2 N Z +STRANDS S T R AE1 N D Z +STRANG S T R AE1 NG +STRANGE S T R EY1 N JH +STRANGELOVE S T R EY1 N JH L AH2 V +STRANGELY S T R EY1 N JH L IY0 +STRANGENESS S T R EY1 N JH N AH0 S +STRANGER S T R EY1 N JH ER0 +STRANGER'S S T R EY1 N JH ER0 Z +STRANGERS S T R EY1 N JH ER0 Z +STRANGEST S T R EY1 N JH IH0 S T +STRANGIS S T R AE1 N JH IH0 S +STRANGLE S T R AE1 NG G AH0 L +STRANGLED S T R AE1 NG G AH0 L D +STRANGLEHOLD S T R AE1 NG G AH0 L HH OW2 L D +STRANGLER S T R AE1 NG G L ER0 +STRANGLING S T R AE1 NG G AH0 L IH0 NG +STRANGLING(1) S T R AE1 NG G L IH0 NG +STRANGULATE S T R AE1 NG G Y AH0 L EY2 T +STRANGULATION S T R AE2 NG G Y AH0 L EY1 SH AH0 N +STRANGULATIONS S T R AE2 NG G Y AH0 L EY1 SH AH0 N Z +STRANGWAYES S T R AE1 NG W EY2 Z +STRANO S T R AA1 N OW0 +STRANSKY S T R AE1 N S K IY0 +STRAP S T R AE1 P +STRAPPED S T R AE1 P T +STRAPPING S T R AE1 P IH0 NG +STRAPS S T R AE1 P S +STRASBERG S T R AE1 S B ER0 G +STRASBOURG S T R AE1 S B AO2 R G +STRASBURG S T R AE1 S B ER0 G +STRASBURGER S T R AE1 S B ER0 G ER0 +STRASSBURG S T R AE1 S B ER0 G +STRASSBURGER S T R AE1 S B ER0 G ER0 +STRASSER S T R AE1 S ER0 +STRASSMAN S T R AE1 S M AH0 N +STRASSNER S T R AE1 S N ER0 +STRASZHEIM S T R AE1 S HH AY2 M +STRATA S T R AE1 T AH0 +STRATACOM S T R AE1 T AH0 K AA0 M +STRATAGEM S T R AE1 T AH0 JH AH0 M +STRATAGEMS S T R AE1 T AH0 JH AH0 M Z +STRATAS S T R AE1 T AH0 Z +STRATE S T R EY1 T +STRATEGEM S T R AE1 T IH0 JH EH0 M +STRATEGIC S T R AH0 T IY1 JH IH0 K +STRATEGICAL S T R AH0 T IY1 JH IH0 K AH0 L +STRATEGICALLY S T R AH0 T IY1 JH IH0 K L IY0 +STRATEGIES S T R AE1 T AH0 JH IY0 Z +STRATEGIST S T R AE1 T IH0 JH IH0 S T +STRATEGISTS S T R AE1 T IH0 JH IH0 S T S +STRATEGIZE S T R AE1 T AH0 JH AY0 Z +STRATEGIZING S T R AE1 T AH0 JH AY0 Z IH0 NG +STRATEGY S T R AE1 T AH0 JH IY0 +STRATEGY'S S T R AE1 T AH0 JH IY0 Z +STRATER S T R EY1 T ER0 +STRATFORD S T R AE1 T F ER0 D +STRATHMAN S T R AE1 TH M AH0 N +STRATIFICATION S T R AE2 T AH0 F IH0 K EY1 SH AH0 N +STRATIFIED S T R AE1 T AH0 F AY2 D +STRATIFY S T R AE1 T AH0 F AY2 +STRATIGRAPHIC S T R AE2 T AH0 G R AE1 F IH0 K +STRATMAN S T R AE1 T M AH0 N +STRATMANN S T R AE1 T M AH0 N +STRATOCASTER S T R AE1 T OW0 K AE2 S T ER0 +STRATOFLEX S T R AE1 T OW0 F L EH2 K S +STRATOSPHERE S T R AE1 T AH0 S F IH2 R +STRATOSPHERIC S T R AE2 T AH0 S F IH1 R IH0 K +STRATTON S T R AE1 T AH0 N +STRATUM S T R AE1 T AH0 M +STRATUS S T R AE1 T AH0 S +STRATUS'S S T R AE1 T AH0 S IH0 Z +STRAUB S T R AW1 B +STRAUBE S T R AW1 B +STRAUCH S T R AW1 K +STRAUGHAN S T R AO1 AH0 N +STRAUGHN S T R AO1 N +STRAUGHTER S T R AO1 T ER0 +STRAUM S T R AW1 M +STRAUM(1) S T R AA1 M +STRAUS S T R AW1 S +STRAUSBAUGH S T R AW1 S B AW0 +STRAUSE S T R AW1 S +STRAUSER S T R AW1 S ER0 +STRAUSS S T R AW1 S +STRAUSS'S S T R AW1 S IH0 Z +STRAUSSER S T R AW1 S ER0 +STRAVINSKY S T R AH0 V IH1 N S K IY0 +STRAVINSKY'S S T R AH0 V IH1 N S K IY0 Z +STRAW S T R AO1 +STRAWBERRIES S T R AO1 B EH2 R IY0 Z +STRAWBERRY S T R AO1 B EH2 R IY0 +STRAWBRIDGE S T R AO1 B R IH2 JH +STRAWDER S T R AO1 D ER0 +STRAWDERMAN S T R AO1 D ER0 M AH0 N +STRAWN S T R AO1 N +STRAWS S T R AO1 Z +STRAWSER S T R AO1 Z ER0 +STRAY S T R EY1 +STRAYED S T R EY1 D +STRAYER S T R EY1 ER0 +STRAYHORN S T R EY1 HH ER0 N +STRAYING S T R EY1 IH0 NG +STRAYS S T R EY1 Z +STREAK S T R IY1 K +STREAKED S T R IY1 K T +STREAKER S T R IY1 K ER0 +STREAKING S T R IY1 K IH0 NG +STREAKS S T R IY1 K S +STREAM S T R IY1 M +STREAMED S T R IY1 M D +STREAMER S T R IY1 M ER0 +STREAMERS S T R IY1 M ER0 Z +STREAMING S T R IY1 M IH0 NG +STREAMLINE S T R IY1 M L AY2 N +STREAMLINED S T R IY1 M L AY2 N D +STREAMLINING S T R IY1 M L AY2 N IH0 NG +STREAMS S T R IY1 M Z +STREATER S T R IY1 T ER0 +STREB S T R EH1 B +STREBE S T R IY1 B +STREBECK S T R IY1 B EH0 K +STREBEL S T R EH1 B AH0 L +STRECK S T R EH1 K +STRECKER S T R EH1 K ER0 +STREED S T R IY1 D +STREEP S T R IY1 P +STREEPER S T R IY1 P ER0 +STREET S T R IY1 T +STREET'S S T R IY1 T S +STREETCAR S T R IY1 T K AA2 R +STREETER S T R IY1 T ER0 +STREETERS S T R IY1 T ER0 Z +STREETMAN S T R IY1 T M AH0 N +STREETS S T R IY1 T S +STREETT S T R IY1 T +STREETWISE S T R IY1 T W AY2 Z +STREETY S T R IY1 T IY0 +STREFF S T R EH1 F +STREGE S T R IY1 JH +STREHL S T R EH1 L +STREHLE S T R EH1 L +STREHLOW S T R EH1 L OW0 +STREIB S T R AY1 B +STREIBER S T R AY1 B ER0 +STREICH S T R AY1 K +STREICHER S T R AY1 K ER0 +STREIFF S T R AY1 F +STREIGHT S T R EY1 T +STREIKER S T R AY1 K ER0 +STREISAND S T R AY1 Z AH0 N D +STREISAND(1) S T R AY1 S AE2 N D +STREISAND'S S T R AY1 Z AH0 N D Z +STREISAND'S(1) S T R AY1 S AE2 N D Z +STREIT S T R AY1 T +STREITMATTER S T R AY1 T M AH0 T ER0 +STRELOW S T R EH1 L OW0 +STRENG S T R EH1 NG +STRENGER S T R EH1 NG G ER0 +STRENGTH S T R EH1 NG K TH +STRENGTH(1) S T R EH1 NG TH +STRENGTHEN S T R EH1 NG TH AH0 N +STRENGTHENED S T R EH1 NG TH AH0 N D +STRENGTHENING S T R EH1 NG TH AH0 N IH0 NG +STRENGTHENS S T R EH1 NG TH AH0 N Z +STRENGTHS S T R EH1 NG K TH S +STRENGTHS(1) S T R EH1 NG TH S +STRENIO S T R IY1 N IY0 OW0 +STRENUOUS S T R EH1 N Y UW0 AH0 S +STRENUOUSLY S T R EH1 N Y UW0 AH0 S L IY0 +STREP S T R EH1 P +STREPS S T R EH1 P S +STREPTOCOCCUS S T R EH2 P T AH0 K AO1 K AH0 S +STREPTOKINASE S T R EH2 P T AH0 K AY1 N EY2 S +STREPTOKINASE(1) S T R EH2 P T OW0 K AY1 N EY2 Z +STRESS S T R EH1 S +STRESSED S T R EH1 S T +STRESSES S T R EH1 S AH0 Z +STRESSES(1) S T R EH1 S IH0 Z +STRESSFUL S T R EH1 S F AH0 L +STRESSING S T R EH1 S IH0 NG +STRESSOR S T R EH1 S ER0 +STRESSORS S T R EH1 S ER0 Z +STRETCH S T R EH1 CH +STRETCHED S T R EH1 CH T +STRETCHER S T R EH1 CH ER0 +STRETCHER-BEARER S T R EH1 CH ER0 B EH1 R ER0 +STRETCHER-BEARERS S T R EH1 CH ER0 B EH1 R ER0 Z +STRETCHERS S T R EH1 CH ER0 Z +STRETCHES S T R EH1 CH AH0 Z +STRETCHES(1) S T R EH1 CH IH0 Z +STRETCHING S T R EH1 CH IH0 NG +STRETTO S T R EH1 T OW2 +STREVIG S T R EH1 V IH0 G +STREW S T R UW1 +STREWN S T R UW1 N +STREY S T R EY1 +STRIAR S T R AY1 R +STRIBLING S T ER1 AH0 B AH0 L IH0 NG +STRIBLING(1) S T R IH1 B L IH0 NG +STRICK S T R IH1 K +STRICKEN S T R IH1 K AH0 N +STRICKER S T R IH1 K ER0 +STRICKLAND S T R IH1 K L AH0 N D +STRICKLEN S T R IH1 K AH0 L AH0 N +STRICKLER S T R IH1 K L ER0 +STRICKLIN S T R IH1 K L IH0 N +STRICKLING S T R IH1 K L IH0 NG +STRICT S T R IH1 K T +STRICTER S T R IH1 K T ER0 +STRICTEST S T R IH1 K T AH0 S T +STRICTLY S T R IH1 K T L IY0 +STRICTURE S T R IH1 K CH ER0 +STRICTURES S T R IH1 K CH ER0 Z +STRIDE S T R AY1 D +STRIDENCY S T R AY1 D AH0 N S IY0 +STRIDENT S T R AY1 D AH0 N T +STRIDENTLY S T R AY1 D AH0 N T L IY0 +STRIDER S T R AY1 D ER0 +STRIDES S T R AY1 D Z +STRIDING S T R AY1 D IH0 NG +STRIEBER S T R AY1 B ER0 +STRIEGEL S T R IY1 G AH0 L +STRIEKER S T R IY1 K ER0 +STRIEKER'S S T R IY1 K ER0 Z +STRIETER S T R IY1 T ER0 +STRIFE S T R AY1 F +STRIFES S T R AY1 F S +STRIKE S T R AY1 K +STRIKE'S S T R AY1 K S +STRIKEBREAKER S T R AY1 K B R EY2 K ER0 +STRIKEBREAKERS S T R AY1 K B R EY2 K ER0 Z +STRIKEOUT S T R AY1 K AW2 T +STRIKEOUTS S T R AY1 K AW2 T S +STRIKER S T R AY1 K ER0 +STRIKER'S S T R AY1 K ER0 Z +STRIKERS S T R AY1 K ER0 Z +STRIKERS' S T R AY1 K ER0 Z +STRIKES S T R AY1 K S +STRIKES' S T R AY1 K S +STRIKING S T R AY1 K IH0 NG +STRIKINGLY S T R AY1 K IH0 NG L IY0 +STRIMPLE S T R IH1 M P AH0 L +STRINDEN S T R IH1 N D AH0 N +STRINE S T R AY1 N +STRING S T R IH1 NG +STRINGED S T R IH1 NG D +STRINGENCY S T R IH1 N JH AH0 N S IY0 +STRINGENT S T R IH1 N JH AH0 N T +STRINGENTLY S T R IH1 N JH AH0 N T L IY0 +STRINGER S T R IH1 NG ER0 +STRINGERS S T R IH1 NG ER0 Z +STRINGFELLOW S T R IH1 NG F EH2 L OW0 +STRINGFIELD S T R IH1 NG F IY2 L D +STRINGHAM S T R IH1 NG HH AE2 M +STRINGING S T R IH1 NG IH0 NG +STRINGS S T R IH1 NG Z +STRINGY S T R IH1 NG IY0 +STRIP S T R IH1 P +STRIP'S S T R IH1 P S +STRIPE S T R AY1 P +STRIPED S T R AY1 P T +STRIPER S T R AY1 P ER0 +STRIPERS S T R AY1 P ER0 Z +STRIPES S T R AY1 P S +STRIPLIN S T R IH1 P L IH0 N +STRIPLING S T R IH1 P L IH0 NG +STRIPPED S T R IH1 P T +STRIPPER S T R IH1 P ER0 +STRIPPERS S T R IH1 P ER0 Z +STRIPPING S T R IH1 P IH0 NG +STRIPS S T R IH1 P S +STRIPTEASE S T R IH1 P T IY2 Z +STRITE S T R AY1 T +STRITTMATTER S T R IH1 T M AH0 T ER0 +STRIVE S T R AY1 V +STRIVEN S T R IH1 V AH0 N +STRIVES S T R AY1 V Z +STRIVING S T R AY1 V IH0 NG +STRIVINGS S T R AY1 V IH0 NG Z +STRNAD S T ER1 N AE0 D +STROBE S T R OW1 B +STROBEL S T R OW1 B AH0 L +STROBEL'S S T R OW1 B AH0 L Z +STROBER S T R OW1 B ER0 +STROBL S T R AA1 B AH0 L +STROBLE S T R OW1 B AH0 L +STROBRIDGE S T R AA1 B R IH0 JH +STROCK S T R AA1 K +STRODE S T R OW1 D +STRODER S T R OW1 D ER0 +STROEBEL S T R OW1 B AH0 L +STROESSNER S T R OW1 S N ER0 +STROGANOFF S T R OW1 G AH0 N AO2 F +STROH S T R OW1 +STROHECKER S T R OW1 IH0 K ER0 +STROHL S T R OW1 L +STROHM S T R OW1 M +STROHMAIER S T R OW1 M AY0 ER0 +STROHMAN S T R OW1 M AH0 N +STROHMEIER S T R OW1 M AY0 ER0 +STROHMEYER S T R OW1 M AY0 ER0 +STROIK S T R OY1 K +STROJNY S T R OW1 Y N IY0 +STROKE S T R OW1 K +STROKED S T R OW1 K T +STROKES S T R OW1 K S +STROKING S T R OW1 K IH0 NG +STROLE S T R OW1 L +STROLL S T R OW1 L +STROLLED S T R OW1 L D +STROLLER S T R OW1 L ER0 +STROLLERS S T R OW1 L ER0 Z +STROLLING S T R OW1 L IH0 NG +STROLLO S T R AA1 L OW0 +STROLLS S T R OW1 L Z +STROM S T R AA1 M +STROMA S T R OW1 M AH0 +STROMAIN S T R AA1 M AY0 N +STROMAN S T R OW1 M AH0 N +STROMBECK S T R AA1 M B EH2 K +STROMBERG S T R AA1 M B ER0 G +STROMBOLI S T R AA2 M B OW1 L IY0 +STROMBOLI'S S T R AA2 M B OW1 L IY0 Z +STROME S T R OW1 M +STROMER S T R OW1 M ER0 +STROMGREN S T R AA1 M G R EH0 N +STROMME S T R AA1 M +STROMMEN S T R AA1 M AH0 N +STROMQUIST S T R AA1 M K W IH2 S T +STRONACH S T R AA1 N AH0 K +STRONG S T R AO1 NG +STRONGER S T R AO1 NG G ER0 +STRONGEST S T R AO1 NG G AH0 S T +STRONGHOLD S T R AO1 NG HH OW2 L D +STRONGHOLDS S T R AO1 NG HH OW2 L D Z +STRONGLY S T R AO1 NG L IY0 +STRONGMAN S T R AO1 NG M AE2 N +STRONTIUM S T R AA1 N T IY0 AH0 M +STROOCK S T R UH1 K +STROOP S T R UW1 P +STROOPE S T R UW1 P +STROOT S T R UW1 T +STROPE S T R OW1 P +STROSCHEIN S T R AO1 SH AY0 N +STROSNIDER S T R AA1 S N AY0 D ER0 +STROSSEN S T R AO1 S EH0 N +STROSSEN(1) S T R AO1 S IH0 N +STROTHER S T R AA1 DH ER0 +STROTHERS S T R AH1 DH ER0 Z +STROTHMAN S T R AA1 TH M AH0 N +STROUD S T R AW1 D +STROUGH S T R AW1 +STROUP S T R UW1 P +STROUPE S T R UW1 P +STROUSE S T R AW1 S +STROUT S T R AW1 T +STROUTH S T R AW1 TH +STROVE S T R OW1 V +STROW S T R OW1 +STROZIER S T R OW1 Z IY0 ER0 +STRUB S T R AH1 B +STRUBBE S T R AH1 B +STRUBE S T R UW1 B +STRUBEL S T R UW1 B AH0 L +STRUBLE S T R UW1 B AH0 L +STRUCHEN S T R AH1 K AH0 N +STRUCK S T R AH1 K +STRUCKMAN S T R AH1 K M AH0 N +STRUCTURAL S T R AH1 K CH ER0 AH0 L +STRUCTURALLY S T R AH1 K CH ER0 AH0 L IY0 +STRUCTURE S T R AH1 K CH ER0 +STRUCTURE'S S T R AH1 K CH ER0 Z +STRUCTURED S T R AH1 K CH ER0 D +STRUCTURES S T R AH1 K CH ER0 Z +STRUCTURING S T R AH1 K CH ER0 IH0 NG +STRUEBING S T R UH1 B IH0 NG +STRUGGLE S T R AH1 G AH0 L +STRUGGLE'S S T R AH1 G AH0 L Z +STRUGGLED S T R AH1 G AH0 L D +STRUGGLES S T R AH1 G AH0 L Z +STRUGGLING S T R AH1 G AH0 L IH0 NG +STRUGGLING(1) S T R AH1 G L IH0 NG +STRUM S T R AH1 M +STRUMMING S T R AH1 M IH0 NG +STRUMS S T R AH1 M Z +STRUNG S T R AH1 NG +STRUNK S T R AH1 NG K +STRUNK'S S T R AH1 NG K S +STRUPP S T R AH1 P +STRUSS S T R AH1 S +STRUT S T R AH1 T +STRUTHERS S T R AH1 DH ER0 Z +STRUTS S T R AH1 T S +STRUTTING S T R AH1 T IH0 NG +STRUTTON S T R AH1 T AH0 N +STRUTZ S T R AH1 T S +STRUVE S T R UW1 V +STRYCHARZ S T R IH1 HH ER0 Z +STRYCHNINE S T R IH1 K N AY2 N +STRYKER S T R AY1 K ER0 +STRZELECKI S T R EH2 Z IH0 L EH1 T S K IY0 +STRZELECKI(1) S T ER2 Z IH0 L EH1 T S K IY0 +STU S T UW1 +STUARD S T UW1 ER0 D +STUART S T UW1 ER0 T +STUART(1) S T Y UW1 ER0 T +STUART(2) S T AO1 R T +STUART'S S T UW1 ER0 T S +STUART'S(1) S T Y UW1 ER0 T S +STUART'S(2) S T AO1 R T S +STUARTS S T UW1 ER0 T S +STUB S T AH1 B +STUBBE S T AH1 B +STUBBED S T AH1 B D +STUBBINS S T AH1 B IH0 N Z +STUBBLE S T AH1 B AH0 L +STUBBLEFIELD S T AH1 B AH0 L F IY2 L D +STUBBORN S T AH1 B ER0 N +STUBBORNLY S T AH1 B ER0 N L IY0 +STUBBORNNESS S T AH1 B ER0 N N AH0 S +STUBBORNNESS(1) S T AH1 B ER0 N AH0 S +STUBBS S T AH1 B Z +STUBBY S T AH1 B IY0 +STUBER S T UW1 B ER0 +STUBS S T AH1 B Z +STUCCO S T AH1 K OW0 +STUCCOED S T AH1 K OW0 D +STUCHELL S T AH1 K AH0 L +STUCK S T AH1 K +STUCKE S T AH1 K +STUCKER S T AH1 K ER0 +STUCKERT S T AH1 K ER0 T +STUCKEY S T AH1 K IY0 +STUCKI S T AH1 K IY0 +STUCKMAN S T AH1 K M AH0 N +STUCKY S T AH1 K IY0 +STUD S T AH1 D +STUDDARD S T AH1 D ER0 D +STUDDED S T AH1 D IH0 D +STUDDS S T AH1 D Z +STUDE S T UW1 D +STUDEBAKER S T UW1 D AH0 B EY2 K ER0 +STUDEMAN S T UW1 D M AH0 N +STUDEMAN(1) S T UW1 D AH0 M AH0 N +STUDENT S T UW1 D AH0 N T +STUDENT'S S T UW1 D AH0 N T S +STUDENTS S T UW1 D AH0 N T S +STUDENTS' S T UW1 D AH0 N T S +STUDER S T UW1 D ER0 +STUDIED S T AH1 D IY0 D +STUDIES S T AH1 D IY0 Z +STUDIO S T UW1 D IY0 OW2 +STUDIO'S S T UW1 D IY0 OW2 Z +STUDIOS S T UW1 D IY0 OW2 Z +STUDIOS' S T UW1 D IY0 OW2 Z +STUDIOUS S T UW1 D IY0 AH0 S +STUDIOUSLY S T UW1 D IY0 AH0 S L IY0 +STUDLEY S T AH1 D L IY0 +STUDNICKA S T AH0 D N IH1 S K AH0 +STUDS S T AH1 D Z +STUDSTILL S T AH1 D S T IH2 L +STUDT S T AH1 D T +STUDTGARD S T AH1 T G AA2 R D +STUDY S T AH1 D IY0 +STUDY'S S T AH1 D IY0 Z +STUDYING S T AH1 D IY0 IH0 NG +STUDZINSKI S T AH0 JH IH1 N S K IY0 +STUEBE S T UW1 B +STUEBER S T UH1 B ER0 +STUECK S T UW1 K +STUEVE S T UW1 V +STUEWE S T UW1 +STUFF S T AH1 F +STUFF'S S T AH1 F S +STUFF-IT S T AH1 F IH0 T +STUFF-IT'S S T AH1 F IH0 T S +STUFFED S T AH1 F T +STUFFER S T AH1 F ER0 +STUFFING S T AH1 F IH0 NG +STUFFLEBEAM S T AH1 F AH0 L B IY2 M +STUFFLEBEAN S T AH1 F AH0 L B IY2 N +STUFFS S T AH1 F S +STUFFY S T AH1 F IY0 +STUHLER S T UW1 L ER0 +STUHR S T ER1 +STUHR(1) S T UH1 R +STUKA S T UW1 K AH0 +STUKEL S T UW1 K AH0 L +STUKES S T UW1 K S +STUKEY S T AH1 K IY0 +STULL S T AH1 L +STULLER S T AH1 L ER0 +STULTIFY S T AH1 L T AH0 F AY2 +STULTIFYING S T AH1 L T AH0 F AY2 IH0 NG +STULTS S T AH1 L T S +STULTZ S T AH1 L T S +STUM S T AH1 M +STUMBAUGH S T AH1 M B AO2 +STUMBLE S T AH1 M B AH0 L +STUMBLED S T AH1 M B AH0 L D +STUMBLES S T AH1 M B AH0 L Z +STUMBLING S T AH1 M B AH0 L IH0 NG +STUMBLING(1) S T AH1 M B L IH0 NG +STUMBO S T AH1 M B OW2 +STUMM S T AH1 M +STUMP S T AH1 M P +STUMPAGE S T AH1 M P IH0 JH +STUMPE S T AH1 M P +STUMPED S T AH1 M P T +STUMPER S T AH1 M P ER0 +STUMPF S T AH1 M P F +STUMPFF S T AH1 M P F +STUMPH S T AH1 M F +STUMPING S T AH1 M P IH0 NG +STUMPO S T AH1 M P OW2 +STUMPP S T AH1 M P +STUMPS S T AH1 M P S +STUN S T AH1 N +STUNG S T AH1 NG +STUNK S T AH1 NG K +STUNNED S T AH1 N D +STUNNER S T AH1 N ER0 +STUNNING S T AH1 N IH0 NG +STUNNINGLY S T AH1 N IH0 NG L IY0 +STUNS S T AH1 N Z +STUNT S T AH1 N T +STUNTED S T AH1 N T IH0 D +STUNTS S T AH1 N T S +STUNTZ S T AH1 N T S +STUPA S T UW1 P AA2 +STUPAK S T UW1 P AA0 K +STUPAR S T UW1 P ER0 +STUPAY S T UW0 P EY1 +STUPENDOUS S T UW0 P EH1 N D AH0 S +STUPID S T UW1 P IH0 D +STUPIDER S T UW1 P IH0 D ER0 +STUPIDEST S T UW1 P IH0 D AH0 S T +STUPIDITY S T UW0 P IH1 D IH0 T IY2 +STUPIDLY S T UW1 P IH0 D L IY2 +STUPKA S T AH1 P K AA2 +STUPOR S T UW1 P ER0 +STUPP S T AH1 P +STUPSKI S T AH1 P S K IY2 +STURBRIDGE S T ER1 B R IH2 JH +STURC S T ER1 K +STURDEVANT S T ER1 D IH0 V AH0 N T +STURDHAL S T ER1 D AA0 L +STURDIER S T ER1 D IY0 ER0 +STURDINESS S T ER1 D IY0 N AH0 S 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S T AY1 V AH0 S AH0 N T +STY S T AY1 +STYER S T AY1 ER0 +STYERS S T AY1 ER0 Z +STYGIAN S T IH1 JH IY0 AH0 N +STYLE S T AY1 L +STYLED S T AY1 L D +STYLES S T AY1 L Z +STYLING S T AY1 L IH0 NG +STYLISH S T AY1 L IH0 SH +STYLISHLY S T AY1 L IH0 SH L IY0 +STYLIST S T AY1 L IH0 S T +STYLISTIC S T AY0 L IH1 S T IH0 K +STYLISTICALLY S T AY0 L IH1 S T IH0 K L IY0 +STYLISTS S T AY1 L IH0 S T S +STYLITES S T IH0 L AY1 T S +STYLIZE S T AY1 L AY2 Z +STYLIZE(1) S T AY1 AH0 L AY2 Z +STYLIZED S T AY1 L AY2 Z D +STYLUS S T AY1 L AH0 S +STYMIE S T AY1 M IY0 +STYMIED S T AY1 M IY0 D +STYMIES S T AY1 M IY0 Z +STYNE S T AY1 N +STYRENE S T AY1 R IY2 N +STYROFOAM S T AY1 R AH0 F OW2 M +STYRON S T AY1 R AO0 N +STYS S T IH1 S +STYX S T IH1 K S +ST_CHARLES S EY1 N T CH AA1 R AH0 L Z +ST_CLAIR S EY1 N T K L EH1 R +ST_CLAIRE S EY1 N T K L EH1 R +ST_CYR S EY1 N T K IH1 R +ST_CYR(1) S EY1 N T S IH1 R +ST_DENIS S EY1 N T D EH1 N IH0 S +ST_DENNIS S EY1 N T D EH1 N IH0 S +ST_GEORGE S EY1 N T JH AO1 R JH +ST_GERMAIN S EY1 N T JH ER2 M EY1 N +ST_GERMAINE S EY1 N T JH ER2 M EY1 N +ST_GERMAINE(1) S AA1 N ZH ER2 M EY1 N +ST_HILAIRE S EY1 N T HH IH0 L EY1 R +ST_JACQUES S EY1 N T JH AA1 K S +ST_JACQUES(1) S AA1 N ZH AA1 K S +ST_JAMES S EY1 N T JH EY1 M Z +ST_JEAN S EY1 N T JH IY1 N +ST_JOHN S EY1 N T JH AA1 N +ST_JOHNS S EY1 N T JH AA1 N Z +ST_JULIEN S EY1 N T JH UW1 L IY0 AH0 N +ST_LAURENT S EY1 N T L AO1 R AH0 N T +ST_LAURENT(1) S AA1 N L AO2 R AO1 N T +ST_LAWRENCE S EY1 N T L AO1 R AH0 N S +ST_LOUIS S EY1 N T L UW1 AH0 S +ST_LOUIS(1) S EY1 N T L UW1 IY0 +ST_LUCIA S EY1 N T L UW1 SH AH0 +ST_LUCIA(1) S EY1 N T L UW2 S IY1 AH0 +ST_MARIE S EY1 N T M ER0 IY1 +ST_MARTIN S EY1 N T M AA1 R T IH0 N +ST_MARY S EY1 N T M EH1 R IY0 +ST_PETER S EY1 N T P IY1 T ER0 +ST_PETERSBURG S EY1 N T P IY1 T ER0 Z B ER0 G +ST_PIERRE S EY1 N T P Y EH1 R +ST_THOMAS S EY1 N T AA1 M AH0 S +SU S UW1 +SUARD S UW1 AA0 R D +SUARD(1) S W AA1 R D +SUAREZ S W AA0 R EH1 Z +SUASION S W EY1 ZH AH0 N +SUATA S UW0 AA1 T AH0 +SUATA'S S UW0 AA1 T AH0 Z +SUAVE S W AA1 V +SUAZO S W AA1 Z OW0 +SUB S AH1 B +SUB'S S AH1 B Z +SUB-FOREMAN S AH0 B F AO1 R M AH0 N +SUB-WAY S AH1 B W EY2 +SUBA S UW1 B AH0 +SUBACUTE S AH1 B AH0 K Y UW1 T +SUBANDRIO S AH0 B AE1 N D R IY0 OW0 +SUBARU S UW1 B ER0 UW0 +SUBASSEMBLIES S AH2 B AH0 S EH1 M B L IY0 Z +SUBASSEMBLY S AH2 B AH0 S EH1 M B L IY0 +SUBATOMIC S AH2 B AH0 T AA1 M IH0 K +SUBBED S AH1 B D +SUBBING S AH1 B IH0 NG +SUBCHAPTER S AH1 B CH AE1 P T ER0 +SUBCOMMANDER S AH1 B K AH0 M AE2 N D ER0 +SUBCOMMANDER'S S AH1 B K AH0 M AE2 N D ER0 Z +SUBCOMMANDERS S AH1 B K AH0 M AE2 N D ER0 Z +SUBCOMMITTEE S AH1 B K AH0 M IH1 T IY0 +SUBCOMMITTEE'S S AH1 B K AH0 M IH1 T IY0 Z +SUBCOMMITTEES S AH1 B K AH0 M IH1 T IY0 Z +SUBCOMPACT S AH0 B K AA1 M P AE0 K T +SUBCOMPACTS S AH0 B K AA1 M P AE0 K T S +SUBCONSCIOUS S AH0 B K AA1 N SH AH0 S +SUBCONSCIOUSLY S AH0 B K AA1 N SH AH0 S L IY0 +SUBCONTINENT S AH0 B K AA1 N T IH0 N AH0 N T +SUBCONTINENTS S AH0 B K AA1 N T IH0 N AH0 N T S +SUBCONTRACT S AH0 B K AA1 N T R AE2 K T +SUBCONTRACTED S AH0 B K AA1 N T R AE0 K T IH0 D +SUBCONTRACTING S AH2 B K AH0 N T R AE1 K T IH0 NG +SUBCONTRACTOR S AH0 B K AA1 N T R AE2 K T ER0 +SUBCONTRACTORS S AH0 B K AA1 N T R AE0 K T ER0 Z +SUBCONTRACTS S AH0 B K AA1 N T R AE2 K T S +SUBCULTURE S AH1 B K AH2 L CH ER0 +SUBCULTURES S AH1 B K AH2 L CH ER0 Z +SUBCUTANEOUS S AH0 B K Y UW2 T EY1 N IY0 AH0 S +SUBDIVIDE S AH2 B D AH0 V AY1 D +SUBDIVIDED S AH2 B D IH0 V AY1 D IH0 D +SUBDIVISION S AH1 B D IH0 V IH2 ZH AH0 N +SUBDIVISIONS S AH1 B D IH0 V IH2 ZH AH0 N Z +SUBDUE S AH0 B D UW1 +SUBDUED S AH0 B D UW1 D +SUBDUING S AH0 B D UW1 IH0 NG +SUBER S UW1 B ER0 +SUBFAMILIES S AH1 B F AE2 M AH0 L IY0 Z +SUBFAMILY S AH1 B F AE2 M AH0 L IY0 +SUBGROUP S AH1 B G R UW2 P +SUBGROUPS S AH1 B G R UW2 P S +SUBHLOK S AH1 B L AA2 K +SUBHUMAN S AH2 B HH Y UW1 M AH0 N +SUBIA S UW0 B IY1 AH0 +SUBIC S UW1 B IH0 K +SUBJECT S AH0 B JH EH1 K T +SUBJECT(1) S AH1 B JH IH0 K T +SUBJECT'S S AH1 B JH IH0 K T S +SUBJECTED S AH0 B JH EH1 K T IH0 D +SUBJECTING S AH0 B JH EH1 K T IH0 NG +SUBJECTIVE S AH0 B JH EH1 K T IH0 V +SUBJECTIVITY S AH0 B JH EH0 K T IH1 V IH0 T IY0 +SUBJECTS S AH1 B JH IH0 K T S +SUBJECTS(1) S AH0 B JH EH1 K T S +SUBJECTS(2) S AH0 B JH EH1 K S +SUBJECTS' S AH1 B JH EH0 K T S +SUBJECTS'(1) S AH1 B JH EH0 K S +SUBJUGATE S AH1 B JH AH0 G EY2 T +SUBJUGATED S AH1 B JH AH0 G EY2 T IH0 D +SUBKINGDOM S AH0 B K IH1 NG D AH0 M +SUBLEASE S AH1 B L IY2 S +SUBLEASING S AH0 B L IY1 S IH0 NG +SUBLET S AH1 B L EH2 T +SUBLETT S UW1 B L IH0 T +SUBLIME S AH0 B L AY1 M +SUBLIMINAL S AH0 B L IH1 M IH0 N AH0 L +SUBLIMINALLY S AH0 B L IH1 M IH0 N AH0 L IY0 +SUBLUXATION S AH0 B L AH0 K S EY1 SH AH0 N +SUBLUXATIONS S AH0 B L AH0 K S EY1 SH AH0 N Z +SUBMACHINE S AH2 B M AH0 SH IY1 N +SUBMARINE S AH1 B M ER0 IY2 N +SUBMARINE(1) S AH2 B M ER0 IY1 N +SUBMARINE'S S AH1 B M ER0 IY2 N Z +SUBMARINE'S(1) S AH0 B M ER0 IY1 N Z +SUBMARINES S AH1 B M ER0 IY2 N Z +SUBMARINES(1) S AH0 B M ER0 IY1 N Z +SUBMARINES'S S AH1 B M ER0 IY2 N Z IH0 Z 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+SUBPOENAED S AH0 P IY1 N AH0 D +SUBPOENAING S AH0 P IY1 N AH0 IH0 NG +SUBPOENAS S AH0 P IY1 N AH0 Z +SUBPRINCIPAL S AH0 B P R IH1 N S AH0 P AH0 L +SUBPRINCIPALS S AH0 B P R IH1 N S AH0 P AH0 L Z +SUBRA S UW1 B R AH0 +SUBRAMANIAN S UW2 B R AH0 M AA1 N IY0 AH0 N +SUBROTO S UW0 B R OW1 T OW0 +SUBROUTINE S AH1 B R UW0 T IY2 N +SUBS S AH1 B Z +SUBS'S S AH1 B Z IH0 Z +SUBSAHARAN S AH2 B S AH0 HH EH1 R AH0 N +SUBSCRIBE S AH0 B S K R AY1 B +SUBSCRIBED S AH0 B S K R AY1 B D +SUBSCRIBER S AH0 B S K R AY1 B ER0 +SUBSCRIBER'S S AH0 B S K R AY1 B ER0 Z +SUBSCRIBERS S AH0 B S K R AY1 B ER0 Z +SUBSCRIBERS' S AH0 B S K R AY1 B ER0 Z +SUBSCRIBES S AH0 B S K R AY1 B Z +SUBSCRIBING S AH0 B S K R AY1 B IH0 NG +SUBSCRIPTION S AH0 B S K R IH1 P SH AH0 N +SUBSCRIPTIONS S AH0 B S K R IH1 P SH AH0 N Z +SUBSECTION S AH1 B S EH0 K SH AH0 N +SUBSEQUENT S AH1 B S AH0 K W AH0 N T +SUBSEQUENTLY S AH1 B S AH0 K W AH0 N T L IY0 +SUBSERVIENCE S AH0 B S ER1 V IY0 AH0 N S +SUBSERVIENT S AH0 B S ER1 V IY0 AH0 N T +SUBSET S AH1 B S EH2 T +SUBSETS S AH1 B S EH2 T S +SUBSIDE S AH0 B S AY1 D +SUBSIDED S AH0 B S AY1 D IH0 D +SUBSIDENCE S AH0 B S AY1 D AH0 N S +SUBSIDES S AH0 B S AY1 D Z +SUBSIDIARIES S AH0 B S IH1 D IY0 EH2 R IY0 Z +SUBSIDIARIES' S AH0 B S IH1 D IY0 EH2 R IY0 Z +SUBSIDIARY S AH0 B S IH1 D IY0 EH2 R IY0 +SUBSIDIARY'S S AH0 B S IH1 D IY0 EH2 R IY0 Z +SUBSIDIES S AH1 B S AH0 D IY0 Z +SUBSIDIES(1) S AH1 B S IH0 D IY0 Z +SUBSIDING S AH0 B S AY1 D IH0 NG +SUBSIDIZATION S AH2 B S IH0 D IH0 Z EY1 SH AH0 N +SUBSIDIZE S AH1 B S IH0 D AY2 Z +SUBSIDIZED S AH1 B S IH0 D AY2 Z D +SUBSIDIZES S AH1 B S IH0 D AY2 Z IH0 Z +SUBSIDIZING S AH1 B S IH0 D AY2 Z IH0 NG +SUBSIDY S AH1 B S IH0 D IY0 +SUBSIST S AH0 B S IH1 S T +SUBSISTENCE S AH0 B S IH1 S T AH0 N S +SUBSOIL S AH1 B S OY2 L +SUBSPACE S AH1 B S P EY2 S +SUBSPACES S AH1 B S P EY2 S IH0 S +SUBSPACING S AH1 B S P EY2 S IH0 NG +SUBSTANCE S AH1 B S T AH0 N S +SUBSTANCES S AH1 B S T AH0 N S AH0 Z +SUBSTANCES(1) S AH1 B S T AH0 N S IH0 Z +SUBSTANDARD S AH0 B 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T ER0 +SUMPTUOUS S AH1 M P CH W AH0 S +SUMPTUOUS(1) S AH1 M P CH UW0 AH0 S +SUMRALL S AH1 M R AH0 L +SUMRELL S UW0 M R EY1 L +SUMROW S AH1 M R OW2 +SUMS S AH1 M Z +SUMTER S AH1 M T ER0 +SUN S AH1 N +SUN'S S AH1 N Z +SUNAMERICA S AH1 N AH0 M EH1 R AH0 K AH0 +SUNAU S UW1 N AW0 +SUNBATH S AH1 N B AE2 TH +SUNBATHE S AH1 N B EY2 DH +SUNBATHING S AH1 N B EY2 DH IH0 NG +SUNBEAM S AH1 N B IY2 M +SUNBEAM'S S AH1 N B IY2 M Z +SUNBELT S AH1 N B EH2 L T +SUNBELT'S S AH1 N B EH2 L T S +SUNBIRD S AH1 N B ER2 D +SUNBIRDS S AH1 N B ER2 D Z +SUNBURN S AH1 N B ER2 N +SUNBURNED S AH1 N B ER2 N D +SUNCOAST S AH1 N K OW2 S T +SUNCOOK S AH1 N K UH2 K +SUNCOR S AH1 N K AO2 R +SUND S AH1 N D +SUNDAE S AH1 N D EY0 +SUNDAE'S S AH1 N D EY2 Z +SUNDAHL S AH1 N D AA2 L +SUNDAI S AH0 N D AY1 +SUNDANCE S AH1 N D AE2 N S +SUNDAR S UW1 N D AA0 R +SUNDARARAJAN S UW0 N D AA2 R AH0 R AA1 JH AH0 N +SUNDAY S AH1 N D EY2 +SUNDAY(1) S AH1 N D IY2 +SUNDAY'S S AH1 N D EY2 Z +SUNDAY'S(1) S AH1 N D IY2 Z +SUNDAYS S AH1 N D EY2 Z 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S T EY2 T S +SUNSWEET S AH1 N S W IY2 T +SUNSWEET'S S AH1 N S W IY2 T S +SUNTAN S AH1 N T AE2 N +SUNTER S AH1 N T ER0 +SUNTORY S AH1 N T AO1 R IY0 +SUNTRUST S AH1 N T R AH2 S T +SUNTRUST'S S AH1 N T R AH2 S T S +SUNUNU S AH0 N UW1 N UW0 +SUNUNU'S S AH0 N UW1 N UW0 Z +SUNUP S AH1 N AH0 P +SUNWARD S AH1 N W ER0 D +SUNWORLD S AH1 N W ER2 L D +SUNWORLD'S S AH1 N W ER2 L D Z +SUNY S UW1 N IY2 +SUON S UW1 AO0 N +SUP S AH1 P +SUPAK S UW1 P AH0 K +SUPAN S UW1 P AH0 N +SUPER S UW1 P ER0 +SUPER-IMPOSITION S UW2 P ER0 IH2 M P AH0 Z IH1 SH AH0 N +SUPER-POSITION S UW2 P ER0 P AH0 Z IH1 SH AH0 N +SUPERABRASIVE S UW2 P ER0 AH0 B R EY1 S IH0 V +SUPERABRASIVES S UW2 P ER0 AH0 B R EY1 S IH0 V Z +SUPERAMERICA S UW2 P ER0 AH0 M EH1 R IH0 K AH0 +SUPERB S UH0 P ER1 B +SUPERBAR S UW1 P ER0 B AA2 R +SUPERBLY S UW1 P ER0 B L IY0 +SUPERBOWL S UW1 P ER0 B OW2 L +SUPERBOWL'S S UW1 P ER0 B OW2 L Z +SUPERBOWLS S UW1 P ER0 B OW2 L Z +SUPERCALIFRAGILISTIC S UW2 P ER0 K AE2 L AH0 F R AE1 JH AH0 L IH2 S T IH0 K +SUPERCALIFRAGILISTICEXPIALIDOCIOUS S UW2 P ER0 K AE2 L AH0 F R AE1 JH AH0 L IH2 S T IH0 K EH2 K S P IY0 AE2 L AH0 D OW1 SH AH0 S +SUPERCENTER S UW1 P ER0 S EH2 N T ER0 +SUPERCENTERS S UW1 P ER0 S EH2 N T ER0 S +SUPERCHARGE S UW2 P ER0 CH AA1 R JH +SUPERCHARGED S UW2 P ER0 CH AA1 R JH D +SUPERCILIOUS S UW2 P ER0 S IH1 L IY0 AH0 S +SUPERCOLLIDER S UW0 P ER0 K AH0 L AY1 D ER0 +SUPERCOMPUTER S UW2 P ER0 K AH0 M P Y UW1 T ER0 +SUPERCOMPUTERS S UW2 P ER0 K AH0 M P Y UW1 T ER0 Z +SUPERCOMPUTING S UW0 P ER0 K AH0 M P Y UW1 T IH0 NG +SUPERCONDUCTING S UW1 P ER0 K AH0 N D AH2 K T IH0 NG +SUPERCONDUCTIVE S UW0 P ER0 K AH0 N D AH1 K T IH0 V +SUPERCONDUCTIVITY S UW2 P ER0 K AA2 N D AH2 K T IH1 V AH0 T IY0 +SUPERCONDUCTOR S UW1 P ER0 K AH0 N D AH2 K T ER0 +SUPERCONDUCTORS S UW1 P ER0 K AH0 N D AH2 K T ER0 Z +SUPERCOOL S UW2 P ER0 K UW1 L +SUPERCOOLED S UW2 P ER0 K UW1 L D +SUPERCUT S UW1 P ER0 K AH2 T +SUPERCUTS S UW1 P ER0 K AH2 T S +SUPERDELEGATE S UW0 P ER0 D EH1 L AH0 G AH0 T +SUPERDELEGATES S UW0 P ER0 D EH1 L AH0 G AH0 T S +SUPERDOME S UW2 P ER0 D OW1 M +SUPERDOT S UW1 P ER0 D AA2 T +SUPERDRUG S UW1 P ER0 D R AH2 G +SUPERFAMILY S UW1 P ER0 F AE2 M L IY0 +SUPERFAN S UW1 P ER0 F AE2 N +SUPERFAST S UW1 P ER0 F AE2 S T +SUPERFICIAL S UW2 P ER0 F IH1 SH AH0 L +SUPERFICIALLY S UW1 P ER0 F IH2 SH AH0 L IY0 +SUPERFLUIDITY S UW2 P ER0 F L UW2 IH1 D AH0 T IY0 +SUPERFLUOUS S UW1 P ER0 F L W AH2 S +SUPERFON S UW1 P ER0 F IH0 N +SUPERFREIGHTER S UW1 P ER0 F R EY2 T ER0 +SUPERFREIGHTERS S UW1 P ER0 F R EY2 T ER0 Z +SUPERFUND S UW2 P ER0 F AH1 N D +SUPERGIANT S UW1 P ER0 JH AY1 AH0 N T +SUPERGIANTS S UW2 P ER0 JH AY1 AH0 N T S +SUPERHEATED S UW2 P ER0 HH IY1 T IH0 D +SUPERHERO S UW2 P ER0 HH IY1 R OW0 +SUPERHEROES S UW2 P ER0 HH IY1 R OW0 Z +SUPERHETERODYNE S UW2 P ER0 HH EH1 T ER0 AH0 D AY2 N +SUPERHIGHWAY S UW2 P ER0 HH AY1 W EY2 +SUPERHIGHWAYS S UW2 P ER0 HH AY1 W EY2 Z +SUPERHUMAN S UW2 P ER0 HH Y UW1 M AH0 N +SUPERIMPOSE S UW2 P ER0 AH0 M P OW1 Z +SUPERIMPOSED S UW2 P ER0 AH0 M P OW1 Z D +SUPERINTENDANT S UW2 P ER0 AH0 N T EH1 N D AH0 N T +SUPERINTENDANT(1) S UW2 P ER0 IH0 N T EH1 N D AH0 N T +SUPERINTENDENT S UW2 P ER0 AH0 N T EH1 N D AH0 N T +SUPERINTENDENT(1) S UW2 P ER0 IH0 N T EH1 N D AH0 N T +SUPERINTENDENT'S S UW2 P ER0 IH0 N T EH1 N D AH0 N T S +SUPERINTENDENTS S UW2 P ER0 AH0 N T EH1 N D AH0 N T S +SUPERINTENDENTS(1) S UW2 P ER0 IH0 N T EH1 N D AH0 N T S +SUPERIOR S UW0 P IH1 R IY0 ER0 +SUPERIOR'S S UW0 P IY1 R IY0 ER0 Z +SUPERIORITY S UW2 P IH0 R IY0 AO1 R IH0 T IY0 +SUPERIORS S UW0 P IH1 R IY0 ER0 Z +SUPERLATIVE S UH0 P ER1 L AH0 T IH0 V +SUPERLATIVES S UH0 P ER1 L AH0 T IH0 V Z +SUPERMAC S UW1 P ER0 M AE2 K +SUPERMAJORITY S UW1 P ER0 M AH0 JH AO2 R IH0 T IY0 +SUPERMAN S UW1 P ER0 M AH0 N +SUPERMAN(1) S UW1 P ER0 M AE2 N +SUPERMAN'S S UW1 P ER0 M AE0 N Z +SUPERMARKET S UW1 P ER0 M AA2 R K IH0 T +SUPERMARKET'S S UW1 P ER0 M AA2 R K AH0 T S +SUPERMARKETS S UW1 P ER0 M AA2 R K IH0 T S +SUPERMASSIVE S UW2 P ER0 M AE1 S IH0 V +SUPERMINICOMPUTER S UW1 P ER0 M IH2 N IY0 K AH0 M P Y UW2 T ER0 +SUPERMINICOMPUTERS S UW1 P ER0 M IH2 N IY0 K AH0 M P Y UW2 T ER0 Z +SUPERMODEL S UW1 P ER0 M AA2 D AH0 L +SUPERMODELS S UW1 P ER0 M AA2 D AH0 L Z +SUPERNATURAL S UW2 P ER0 N AE1 CH ER0 AH0 L +SUPERNATURALISM S UW2 P ER0 N AE1 CH ER0 AH0 L IH2 Z AH0 M +SUPERNOVA S UW2 P ER0 N OW1 V AH0 +SUPEROXIDE S UW2 P ER0 AA1 K S AY2 D +SUPERPOWER S UW2 P ER0 P AW1 ER0 +SUPERPOWERS S UW2 P ER0 P AW1 ER0 Z +SUPERPOWERS' S UW1 P ER0 P AW2 R Z +SUPERPREMIUM S UW2 P ER0 P R IY1 M IY0 AH0 M +SUPERPREMIUM(1) S UW2 P ER0 P R IY1 M Y AH0 M +SUPERREGIONAL S UW2 P ER0 R IY1 JH AH0 N AH0 L +SUPERREGIONALS S UW2 P ER0 R IY1 JH AH0 N AH0 L Z +SUPERREGIONALS' S UW0 P ER0 R IY1 JH AH0 N AH0 L Z +SUPERS S UW1 P ER0 Z +SUPERSAVER S UW1 P ER0 S EY2 V ER0 +SUPERSECRET S UW1 P ER0 S IY2 K R IH0 T +SUPERSEDE S UW2 P ER0 S IY1 D +SUPERSEDED S UW2 P ER0 S IY1 D IH0 D +SUPERSEDES S UW2 P ER0 S IY1 D Z +SUPERSEDING S UW2 P ER0 S IY1 D IH0 NG +SUPERSONIC S UW2 P ER0 S AA1 N IH0 K 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S AH0 P L AY1 +SUPPLY'S S AH0 P L AY1 Z +SUPPLYING S AH0 P L AY1 IH0 NG +SUPPORT S AH0 P AO1 R T +SUPPORTABLE S AH0 P AO1 R T AH0 B AH0 L +SUPPORTED S AH0 P AO1 R T IH0 D +SUPPORTER S AH0 P AO1 R T ER0 +SUPPORTERS S AH0 P AO1 R T ER0 Z +SUPPORTING S AH0 P AO1 R T IH0 NG +SUPPORTIVE S AH0 P AO1 R T IH0 V +SUPPORTS S AH0 P AO1 R T S +SUPPOSE S AH0 P OW1 Z +SUPPOSED S AH0 P OW1 Z D +SUPPOSEDLY S AH0 P OW1 Z AH0 D L IY0 +SUPPOSES S AH0 P OW1 Z IH0 Z +SUPPOSING S AH0 P OW1 Z IH0 NG +SUPPOSITION S AH2 P AH0 Z IH1 SH AH0 N +SUPPOSITIONS S AH2 P AH0 Z IH1 SH AH0 N Z +SUPPRESS S AH0 P R EH1 S +SUPPRESSANT S AH0 P R EH1 S AH0 N T +SUPPRESSANTS S AH0 P R EH1 S AH0 N T S +SUPPRESSED S AH0 P R EH1 S T +SUPPRESSES S AH0 P R EH1 S IH0 Z +SUPPRESSING S AH0 P R EH1 S IH0 NG +SUPPRESSION S AH0 P R EH1 SH AH0 N +SUPPRESSOR S AH0 P R EH1 S ER0 +SUPRA S UW1 P R AH0 +SUPRANATIONAL S UW2 P R AH0 N AE1 SH AH0 N AH0 L +SUPREMACIST S UW0 P R EH1 M AH0 S IH0 S T +SUPREMACISTS S UW0 P R EH1 M AH0 S IH0 S T S +SUPREMACY S AH0 P R EH1 M AH0 S IY0 +SUPREME S AH0 P R IY1 M +SUPREME(1) S ER0 P R IY1 M +SUPREMELY S UW0 P R IY1 M AH0 L IY0 +SUPREMES S UW0 P R IY1 M Z +SUPRENANT S UW0 P R EY1 N AH0 N T +SUPRISINGLY S UW2 P R AY1 Z IH0 NG L IY0 +SUPRISINGLY(1) S ER2 P R AY1 Z IH0 NG L IY0 +SUR S ER1 +SURA S UH1 R AH0 +SURACE S UH0 R AA1 S EY0 +SURAT S ER0 AA1 T +SURAT'S S ER0 AA1 T S +SURBAUGH S ER1 B AO0 +SURBER S ER1 B ER0 +SURCEASE S ER2 S IY1 S +SURCHARGE S ER0 CH AA1 R JH +SURCHARGE(1) S ER1 CH AA2 R JH +SURCHARGES S ER1 CH AA2 R JH IH0 Z +SURE SH UH1 R +SURELY SH UH1 R L IY0 +SUREN S UH1 R AH0 N +SURER SH UH1 R ER0 +SURES SH UH1 R Z +SURESH S ER0 EH1 SH +SUREST SH UH1 R IH0 S T +SURETTE S ER0 EH1 T +SURETY SH UH1 R AH0 T IY0 +SURF S ER1 F +SURF'S S ER1 F S +SURFACE S ER1 F AH0 S +SURFACED S ER1 F IH0 S T +SURFACENESS S ER1 F AH0 S N AH0 S +SURFACES S ER1 F AH0 S AH0 Z +SURFACES(1) S ER1 F AH0 S IH0 Z +SURFACING S ER1 F AH0 S IH0 NG +SURFACTANT S ER0 F AE1 K T AH0 N T +SURFBOARD S ER1 F B AO2 R D +SURFBOARDS S ER1 F B AO2 R D Z +SURFED S ER1 F T +SURFEIT S ER1 F AH0 T +SURFER S ER1 F ER0 +SURFERS S ER1 F ER0 Z +SURFING S ER1 F IH0 NG +SURGE S ER1 JH +SURGED S ER1 JH D +SURGEON S ER1 JH AH0 N +SURGEON(1) S ER1 JH IH0 N +SURGEON'S S ER1 JH AH0 N Z +SURGEONS S ER1 JH AH0 N Z +SURGEONS' S ER1 JH IH0 N Z +SURGERIES S ER1 JH ER0 IY0 Z +SURGERY S ER1 JH ER0 IY0 +SURGES S ER1 JH AH0 Z +SURGES(1) S ER1 JH IH0 Z +SURGICAL S ER1 JH IH0 K AH0 L +SURGICAL'S S ER1 JH IH0 K AH0 L Z +SURGICALLY S ER1 JH IH0 K AH0 L IY0 +SURGICALLY(1) S ER1 JH IH0 K L IY0 +SURGING S ER1 JH IH0 NG +SURIANO S UH2 R IY0 AA1 N OW0 +SURINAM S UH2 R AH0 N AA1 M +SURINAME S ER1 IH0 N AA0 M +SURLES S AO1 R AH0 L Z +SURLY S ER1 L IY0 +SURMA S ER1 M AH0 +SURMAN S ER1 M AH0 N +SURMISE S ER0 M AY1 Z +SURMISED S ER0 M AY1 Z D +SURMISES S ER0 M AY1 Z IH0 Z +SURMOUNT S ER0 M AW1 N T +SURMOUNTED S ER0 M AW1 N T IH0 D +SURMOUNTING S ER0 M AW1 N T IH0 NG +SURNAME S ER1 N EY2 M +SURNAMES S ER1 N EY2 M Z +SUROWIEC S ER0 AW1 IY0 K +SURPASS S ER0 P AE1 S +SURPASSED S ER0 P AE1 S T +SURPASSES S ER0 P AE1 S IH0 Z +SURPASSING S ER0 P AE1 S IH0 NG +SURPLUS S ER1 P L AH0 S +SURPLUSES S ER1 P L AH0 S IH0 Z +SURPRENANT S ER1 P R IH0 N AH0 N T +SURPRISE S ER0 P R AY1 Z +SURPRISE(1) S AH0 P R AY1 Z +SURPRISED S ER0 P R AY1 Z D +SURPRISED(1) S AH0 P R AY1 Z D +SURPRISES S ER0 P R AY1 Z IH0 Z +SURPRISES(1) S AH0 P R AY1 Z IH0 Z +SURPRISING S ER0 P R AY1 Z IH0 NG +SURPRISING(1) S AH0 P R AY1 Z IH0 NG +SURPRISINGLY S ER0 P R AY1 Z IH0 NG L IY0 +SURPRISINGLY(1) S AH0 P R AY1 Z IH0 NG L IY0 +SURRATT S AO1 R AH0 T +SURREAL S ER0 IY1 L +SURREALISM S ER0 IY1 L IH0 Z AH0 M +SURREALISM(1) S ER0 IY1 AH0 L IH2 Z AH0 M +SURREALISM'S S ER0 IY1 L IH0 Z AH0 M Z +SURREALISM'S(1) S ER0 IY1 AH0 L IH2 Z AH0 M Z +SURREALISMS S ER0 IY1 L IH0 Z AH0 M Z +SURREALISMS(1) S ER0 IY1 AH0 L IH2 Z AH0 M Z +SURREALISTIC S ER0 IY2 L IH1 S T IH0 K +SURREALISTIC(1) S ER0 IY2 AH0 L IH1 S T IH0 K +SURREBUTTAL S ER1 IH0 B AH0 T AH0 L +SURREBUTTAL(1) S ER1 IY0 B AH0 T AH0 L +SURRELL S AO1 R AH0 L +SURRENCY S AO1 R AH0 N S IY0 +SURRENDER S ER0 EH1 N D ER0 +SURRENDERED S ER0 EH1 N D ER0 D +SURRENDERING S ER0 EH1 N D ER0 IH0 NG +SURRENDERS S ER0 EH1 N D ER0 Z +SURREPTITIOUS S ER2 AH0 P T IH1 SH AH0 S +SURREPTITIOUSLY S ER2 AH0 P T IH1 SH AH0 S L IY0 +SURRETT S AO1 R IH0 T +SURRETTE S ER0 EH1 T +SURREY S ER1 IY0 +SURROGACY S ER1 AH0 G AH0 S IY0 +SURROGATE S ER1 AH0 G AH0 T +SURROGATE(1) S ER1 AH0 G EY2 T +SURROGATES S ER1 AH0 G AH0 T S +SURROGATES(1) S ER1 AH0 G EY2 T S +SURROGATION S ER0 AH0 G EY1 SH AH0 N +SURROUND S ER0 AW1 N D +SURROUNDED S ER0 AW1 N D IH0 D +SURROUNDING S ER0 AW1 N D IH0 NG +SURROUNDINGS S ER0 AW1 N D IH0 NG Z +SURROUNDS S ER0 AW1 N D Z +SURRY S ER1 IY0 +SURTAX S ER1 T AE2 K S +SURTAXES S ER1 T AE2 K S IH0 Z +SURVEIL S ER0 V EY1 L +SURVEILLANCE S ER0 V EY1 L AH0 N S +SURVEILLING S ER0 V EY1 L IH0 NG +SURVEY S ER0 V EY1 +SURVEY(1) S ER1 V EY2 +SURVEY'S S ER0 V EY1 Z +SURVEY'S(1) S ER1 V EY2 Z +SURVEYED S ER0 V EY1 D +SURVEYED(1) S ER1 V EY2 D +SURVEYING S ER0 V EY1 IH0 NG +SURVEYING(1) S ER1 V EY2 IH0 NG +SURVEYOR S ER0 V EY1 ER0 +SURVEYOR(1) S ER1 V EY2 ER0 +SURVEYOR'S S ER0 V EY1 ER0 Z +SURVEYOR'S(1) S ER2 V EY2 ER0 Z +SURVEYORS S ER0 V EY1 ER0 Z +SURVEYORS(1) S ER2 V EY2 ER0 Z +SURVEYS S ER0 V EY1 Z +SURVEYS(1) S ER1 V EY2 Z +SURVIVABILITY S ER0 V AY2 V AH0 B IH1 L IH0 T IY0 +SURVIVABLE S ER0 V AY1 V AH0 B AH0 L +SURVIVAL S ER0 V AY1 V AH0 L +SURVIVALIST S ER0 V AY1 V AH0 L IH0 S T +SURVIVALISTS S ER0 V AY1 V AH0 L IH0 S T S +SURVIVE S ER0 V AY1 V +SURVIVED S ER0 V AY1 V D +SURVIVES S ER0 V AY1 V Z +SURVIVING S ER0 V AY1 V IH0 NG +SURVIVOR S ER0 V AY1 V ER0 +SURVIVOR'S S ER0 V AY1 V ER0 Z +SURVIVORS S ER0 V AY1 V ER0 Z +SUS S AH1 S +SUSA S UW1 S AH0 +SUSAN S UW1 Z AH0 N +SUSAN'S S UW1 Z AH0 N Z +SUSANA S UW0 S AA1 N AH0 +SUSANN S UW2 Z AE1 N +SUSANNA S UW0 Z AE1 N AH0 +SUSANNAH S UW2 S AE1 N AH0 +SUSANNE S UW2 Z AE1 N +SUSCEPTIBILITY S AH0 S EH2 P T AH0 B IH1 L AH0 T IY0 +SUSCEPTIBLE S AH0 S EH1 P T AH0 B AH0 L +SUSETTE S UW2 Z EH1 T +SUSHI S UW1 SH IY0 +SUSI S UW1 S IY0 +SUSIE S UW1 Z IY0 +SUSIE'S S UW1 Z IY0 Z +SUSKI S AH1 S K IY0 +SUSKIND S AH1 S K IH0 N D +SUSKO S AH1 S K OW0 +SUSMAN S AH1 S M AH0 N +SUSONG S AH1 S AO0 NG +SUSPECT S AH0 S P EH1 K T +SUSPECT(1) S AH1 S P EH2 K T +SUSPECT'S S AH0 S P EH1 K T S +SUSPECTED S AH0 S P EH1 K T IH0 D +SUSPECTING S AH0 S P EH1 K T IH0 NG +SUSPECTS S AH0 S P EH1 K T S +SUSPECTS(1) S AH1 S P EH2 K T S +SUSPECTS' S AH1 S P EH2 K T S +SUSPEND S AH0 S P EH1 N D +SUSPENDED S AH0 S P EH1 N D IH0 D +SUSPENDER S AH0 S P EH1 N D ER0 +SUSPENDERS S AH0 S P EH1 N D ER0 Z +SUSPENDING S AH0 S P EH1 N D IH0 NG +SUSPENDS S AH0 S P EH1 N D Z +SUSPENSE S AH0 S P EH1 N S +SUSPENSEFUL S AH0 S P EH1 N S F AH0 L +SUSPENSION S AH0 S P EH1 N SH AH0 N +SUSPENSIONS S AH0 S P EH1 N SH AH0 N Z +SUSPICION S AH0 S P IH1 SH AH0 N +SUSPICIONS S AH0 S P IH1 SH AH0 N Z +SUSPICIOUS S AH0 S P IH1 SH AH0 S +SUSPICIOUSLY S AH0 S P IH1 SH AH0 S L IY0 +SUSQUEHANNA S UW2 S K W EH0 HH AE1 N AH0 +SUSQUEHANNA'S S UW2 S K W EH0 HH AE1 N AH0 Z +SUSS S AH1 S +SUSSER S AH1 S ER0 +SUSSEX S AH1 S IH0 K S +SUSSKIND S AH1 S K IH0 N D +SUSSMAN S AH1 S M AH0 N +SUSSWEIN S AH1 S W IY2 N +SUSSWEIN(1) S AH1 S W AY2 N +SUSTAIN S AH0 S T EY1 N +SUSTAINABILITY S AH0 S T EY2 N AH0 B IH1 L IH0 T IY0 +SUSTAINABLE S AH0 S T EY1 N AH0 B AH0 L +SUSTAINED S AH0 S T EY1 N D +SUSTAINING S AH0 S T EY1 N IH0 NG +SUSTAINS S AH0 S T EY1 N Z +SUSTAITA S UW0 S T EY1 T AH0 +SUSTENANCE S AH1 S T AH0 N AH0 N S +SUSTEREN S AH0 S T EH1 R AH0 N +SUSUMU S UW2 S UW1 M UW0 +SUSY S UW1 Z IY0 +SUTCH S AH1 CH +SUTCLIFF S AH1 T K L IH0 F +SUTCLIFFE S AH1 T K L IH0 F +SUTER S UW1 T ER0 +SUTERA S UW0 T EH1 R AH0 +SUTFIN S AH1 T F IH0 N +SUTHARD S AH1 TH ER0 D +SUTHER S AH1 DH ER0 +SUTHERLAND S AH1 DH ER0 L AH0 N D +SUTHERLAND'S S AH1 DH ER0 L AH0 N D Z +SUTHERLIN S AH1 TH ER0 L IH0 N +SUTHERLIN(1) S AH1 DH ER0 L IH0 N +SUTHERS S AH1 DH ER0 Z +SUTLEY S AH1 T L IY0 +SUTLIFF S AH1 T L IH0 F +SUTNER S AH1 T N ER0 +SUTNICK S AH1 T N IH0 K +SUTO S UW1 T OW0 +SUTOR S UW1 T ER0 +SUTPHEN S AH1 T F AH0 N +SUTPHIN S AH1 T F IH0 N +SUTRO S UW1 T R OW0 +SUTRO'S S UW1 T R OW0 Z +SUTTER S AH1 T ER0 +SUTTLE S AH1 T AH0 L +SUTTLES S AH1 T AH0 L Z +SUTTMEIER S AH1 T M AY2 R +SUTTON S AH1 T AH0 N +SUTTON'S S AH1 T AH0 N Z +SUTURE S UW1 CH ER0 +SUTURED S UW1 CH ER0 D +SUTURES S UW1 CH ER0 Z +SUTURING S UW1 CH ER0 IH0 NG +SUU EH1 S Y UW1 Y UW1 +SUU(1) S UW1 +SUV EH2 S Y UW2 V IY1 +SUV'S EH2 S Y UW2 V IY1 Z +SUVA S UW1 V AH0 +SUVS EH2 S Y UW2 V IY1 Z +SUYDAM S AY1 D AH0 M +SUZANNA S UW2 Z AE1 N AH0 +SUZANNE S UW0 Z AE1 N +SUZETTE S UW2 Z EH1 T +SUZHOU S UW1 ZH UW2 +SUZIE S AH1 Z IY0 +SUZMAN S UW1 Z M AH0 N +SUZUANA S UW0 Z UW0 AA1 N AH0 +SUZUKI S AH0 Z UW1 K IY0 +SUZY S UW1 Z IY0 +SUZY'S S UW1 Z IY0 Z +SVEC S V EH1 K +SVEHLA S V EH1 L AH0 +SVELTE S V EH1 L T +SVEN S V EH1 N +SVENDSEN S V EH1 N D S AH0 N +SVENSK S V EH1 N S K +SVENSKA S V EH1 N S K AH0 +SVENSON S V EH1 N S AH0 N +SVENSSON S V EH1 N S AH0 N +SVERDLOVSK S V ER1 D L AA0 V S K +SVERIGE S V EH1 R IH0 JH +SVETLANA S V EH2 T L AA1 N AH0 +SVETLIK S V EH1 T L IH0 K +SVITAK S V IH1 T AH0 K +SVIZZERA S V IH0 Z EH1 R AH0 +SVOBODA S V OW0 B OW1 D AH0 +SVORAY S V AO1 R EY2 +SWAB S W AA1 B +SWABS S W AA1 B Z +SWABY S W AA1 B IY0 +SWACKHAMER S W AE1 K HH AE2 M ER0 +SWADER S W EY1 D ER0 +SWADLEY S W AA1 D L IY0 +SWAFFORD S W AA1 F ER0 D +SWAGER S W EY1 G ER0 +SWAGERTY S W AE1 JH ER0 T IY0 +SWAGGART S W AE1 G ER0 T +SWAGGER S W AE1 G ER0 +SWAGGERING S W AE1 G ER0 IH0 NG +SWAGGERTY S W AE1 G ER0 T IY0 +SWAHILI S W AA0 HH IY1 L IY0 +SWAILES S W EY1 L Z +SWAILS S W EY1 L Z +SWAIM S W EY1 M +SWAIN S W EY1 N +SWAINE S W EY1 N +SWAINSTON S W EY1 N S T AH0 N +SWALES S W EY1 L Z +SWALLEY S W AO1 L IY0 +SWALLOW S W AA1 L OW0 +SWALLOW(1) S W AO1 L OW0 +SWALLOWED S W AA1 L OW0 D +SWALLOWING S W AA1 L OW0 IH0 NG +SWALLOWS S W AA1 L OW0 Z +SWAM S W AE1 M +SWAMI S W AA1 M IY0 +SWAMINATHAN S W AA2 M IH0 N AA1 TH AH0 N +SWAMP S W AA1 M P +SWAMP(1) S W AO1 M P +SWAMPBUSTER S W AA1 M P B AH2 S T ER0 +SWAMPED S W AO1 M P T +SWAMPER S W AA1 M P ER0 +SWAMPERS S W AA1 M P ER0 Z +SWAMPING S W AA1 M P IH0 NG +SWAMPS S W AA1 M P S +SWAMPS(1) S W AO1 M P S +SWAMPY S W AA1 M P IY0 +SWAN S W AA1 N +SWAN(1) S W AO1 N +SWANBERG S W AA1 N B ER0 G +SWANDA S W AA1 N D AH0 +SWANDER S W AA1 N D ER0 +SWANEE S W AA1 N IY1 +SWANER S W AO1 N ER0 +SWANEY S W AO1 N IY0 +SWANGER S W AO1 NG ER0 +SWANGO S W AA1 NG G OW0 +SWANIGAN S W AA1 N IH0 G AH0 N +SWANK S W AE1 NG K +SWANKE S W AO1 NG K +SWANKY S W AA1 NG K IY0 +SWANN S W AA1 N +SWANN'S S W AA1 N Z +SWANNER S W AA1 N ER0 +SWANS S W AA1 N Z +SWANS(1) S W AO1 N Z +SWANSON S W AA1 N S AH0 N +SWANSTROM S W AA1 N S T R AH0 M +SWANTEK S W AO1 N T IH0 K +SWANTON S W AA1 N T AH0 N +SWANZY S W AA1 N Z IY0 +SWAP S W AA1 P +SWAPE S W EY1 P +SWAPES S W EY1 P S +SWAPO S W AA1 P OW0 +SWAPO'S S W AA1 P OW0 Z +SWAPP S W AA1 P +SWAPPED S W AA1 P T +SWAPPED(1) S W AO1 P T +SWAPPING S W AA1 P IH0 NG +SWAPS S W AA1 P S +SWARD S W AO1 R D +SWARINGEN S W EH1 R IH0 NG AH0 N +SWARM S W AO1 R M +SWARMED S W AO1 R M D +SWARMING S W AO1 R M IH0 NG +SWARMS S W AO1 R M Z +SWARNER S W AO1 R N ER0 +SWAROVSKI S W AA0 R AA1 V S K IY0 +SWART S W AO1 R T +SWARTHMORE S W AO1 R TH M AO2 R +SWARTHOUT S W AO1 R TH AW2 T +SWARTHY S W AO1 R DH IY0 +SWARTHY(1) S W AO1 R TH IY0 +SWARTLEY S W AO1 R T L IY0 +SWARTOUT S W AO1 R T AH0 T +SWARTS S W AO1 R T S +SWARTWOOD S W AO1 R T W UH2 D +SWARTWOUT S W AO1 R T W AW0 T +SWARTZ S W AO1 R T S +SWARTZ(1) SH W AO1 R T S +SWARTZBAUGH S W AO1 R T S B AA0 +SWARTZENDRUBER S W AO1 R T S AH0 N D R UW0 B ER0 +SWARTZENTRUBER S W AO1 R T S AH0 N T R UW0 B ER0 +SWARTZLANDER S W AO1 R T S L AE2 N D ER0 +SWARTZWELDER S W AO1 R T S W EH2 L D ER0 +SWASEY S W AA1 Z IY0 +SWASHBUCKLING S W AA1 SH B AH2 K L IH0 NG +SWASTIKA S W AA1 S T IH0 K AH0 +SWASTIKAS S W AA1 S T IH0 K AH0 Z +SWAT S W AA1 T +SWATCH S W AA1 CH +SWATCHED S W AA1 CH T +SWATCHES S W AA1 CH AH0 Z +SWATCHES(1) S W AA1 CH IH0 Z +SWATCHING S W AA1 CH IH0 NG +SWATEK S W AO1 T IH0 K +SWATH S W AA1 TH +SWATHE S W AA1 DH +SWATHE(1) S W EY1 DH +SWATHED S W AA1 DH D +SWATOW S W AA1 T OW2 +SWATTED S W AA1 T IH0 D +SWATZELL S W AO1 T Z AH0 L +SWAUGER S W AW1 G ER0 +SWAVELY S W EY1 V L IY0 +SWAY S W EY1 +SWAYED S W EY1 D +SWAYING S W EY1 IH0 NG +SWAYNE S W EY1 N +SWAYS S W EY1 Z +SWAYZE S W EY1 Z +SWAYZE(1) S W EY1 Z IY0 +SWAZI S W AA1 Z IY0 +SWAZILAND S W AA1 Z IH0 L AH0 N D +SWEANEY S W IY1 N IY0 +SWEANY S W IY1 N IY0 +SWEAR S W EH1 R +SWEARENGEN S W EH1 R IH0 N JH AH0 N +SWEARENGIN S W EH1 R IH0 N JH AH0 N +SWEARING S W EH1 R IH0 NG +SWEARINGEN S W EH1 R IH0 N JH AH0 N +SWEARINGIN S W EH1 R IH0 N JH AH0 N +SWEARS S W EH1 R Z +SWEAT S W EH1 T +SWEATED S W EH1 T IH0 D +SWEATER S W EH1 T ER0 +SWEATERS S W EH1 T ER0 Z +SWEATIN' S W EH1 T IH0 N +SWEATING S W EH1 T IH0 NG +SWEATMAN S W IY1 T M AH0 N +SWEATPANTS S W EH1 T P AE2 N T S +SWEATS S W EH1 T S +SWEATSHIRT S W EH1 T SH ER2 T +SWEATSHIRTS S W EH1 T SH ER2 T S +SWEATSHOP S W EH1 T SH AA2 P +SWEATSHOPS S W EH1 T SH AA2 P S +SWEATSUIT S W EH1 T S UW2 T +SWEATT S W IY1 T +SWEATY S W EH1 T IY0 +SWEAZY S W IY1 Z IY0 +SWECKER S W EH1 K ER0 +SWED S W EH1 D +SWEDA S W IY1 D AH0 +SWEDBERG S W EH1 D B ER0 G +SWEDE S W IY1 D +SWEDEN S W IY1 D AH0 N +SWEDEN'S S W IY1 D AH0 N Z +SWEDES S W IY1 D Z +SWEDISH S W IY1 D IH0 SH +SWEDLUND S W EH1 D L AH0 N D +SWEEDEN S W IY1 D AH0 N +SWEEN S W IY1 N +SWEENEY S W IY1 N IY0 +SWEENY S W IY1 N IY0 +SWEEP S W IY1 P +SWEEPER S W IY1 P ER0 +SWEEPERS S W IY1 P ER0 Z +SWEEPING S W IY1 P IH0 NG +SWEEPS S W IY1 P S +SWEEPSTAKE S W IY1 P S T EY2 K +SWEEPSTAKES S W IY1 P S T EY2 K S +SWEERS S W IH1 R Z +SWEET S W IY1 T +SWEETEN S W IY1 T AH0 N +SWEETENED S W IY1 T AH0 N D +SWEETENER S W IY1 T AH0 N ER0 +SWEETENER(1) S W IY1 T N ER0 +SWEETENERS S W IY1 T AH0 N ER0 Z +SWEETENERS(1) S W IY1 T N ER0 Z +SWEETENING S W IY1 T AH0 N IH0 NG +SWEETENING(1) S W IY1 T N IH0 NG +SWEETENS S W IY1 T AH0 N Z +SWEETER S W IY1 T ER0 +SWEETEST S W IY1 T AH0 S T +SWEETHEART S W IY1 T HH AA2 R T +SWEETHEARTS S W IY1 T HH AA2 R T S +SWEETIE S W IY1 T IY0 +SWEETING S W IY1 T IH0 NG +SWEETLAND S W IY1 T L AH0 N D +SWEETLY S W IY1 T L IY0 +SWEETMAN S W IY1 T M AH0 N +SWEETNESS S W IY1 T N AH0 S +SWEETON S W IY1 T AH0 N +SWEETS S W IY1 T S +SWEETSER S W IY1 T S ER0 +SWEETWATER S W IY1 T W AA2 T ER0 +SWEEZEY S W IY1 Z IY0 +SWEEZY S W IY1 Z IY0 +SWEGER S W IY1 G ER0 +SWEHLA S W EH1 L AH0 +SWEIG S W AY1 G +SWEIGARD S W AY1 G ER0 D +SWEIGART S W IY1 G AA0 R T +SWEIGERT S W AY1 G ER0 T +SWEITZER S W AY1 T Z ER0 +SWELL S W EH1 L +SWELLED S W EH1 L D +SWELLING S W EH1 L IH0 NG +SWELLS S W EH1 L Z +SWELTER S W EH1 L T ER0 +SWELTERED S W EH1 L T ER0 D +SWELTERING S W EH1 L T ER0 IH0 NG +SWELTERS S W EH1 L T ER0 Z +SWELTRY S W EH1 L T R IY0 +SWEM S W EH1 M +SWENDSEN S W EH1 N D S AH0 N +SWENET S W EH1 N AH0 T +SWENEY S W EH1 N IY0 +SWENSEN S W EH1 N S AH0 N +SWENSEN'S S W EH1 N S AH0 N Z +SWENSON S W EH1 N S AH0 N +SWEPT S W EH1 P T +SWERDLOW S W ER1 D L AW0 +SWERGOLD S W ER1 G OW2 L D +SWERLING S W ER1 L IH0 NG +SWERVE S W ER1 V +SWERVED S W ER1 V D +SWETE S W IY1 T +SWETLAND S W EH1 T L AH0 N D +SWETNAM S W EH1 T N AH0 M +SWETT S W EH1 T +SWETZ S W EH1 T S +SWEZEY S W EH1 Z IY0 +SWIATEK S V IY0 AA1 T EH0 K +SWIATKOWSKI S V IY0 AH0 T K AO1 F S K IY0 +SWICEGOOD S W IH1 S IH0 G UH0 D +SWICK S W IH1 K +SWICKARD S W IH1 K ER0 D +SWIDER S W AY1 D ER0 +SWIDERSKI S V IH0 D ER1 S K IY0 +SWIDERSKI(1) S W IH0 D ER1 S K IY0 +SWIECH S W IY1 CH +SWIER S W AY1 ER0 +SWIFT S W IH1 F T +SWIFT'S S W IH1 F T S +SWIFTER S W IH1 F T ER0 +SWIFTEST S W IH1 F T AH0 S T +SWIFTLY S W IH1 F T L IY0 +SWIFTNESS S W IH1 F T N AH0 S +SWIFTS S W IH1 F T S +SWIG S W IH1 G +SWIGART S W IH1 G AA2 R T +SWIGER S W AY1 G ER0 +SWIGERT S W IH1 G ER0 T +SWIGGUM S W IH1 G AH0 M +SWIHART S W IH1 HH AA0 R T +SWILL S W IH1 L +SWILLEY S W IH1 L IY0 +SWILLING S W IH1 L IH0 NG +SWILLINGER S W IH1 L IH0 NG ER0 +SWIM S W IH1 M +SWIMMER S W IH1 M ER0 +SWIMMERS S W IH1 M ER0 Z +SWIMMING S W IH1 M IH0 NG +SWIMS S W IH1 M Z +SWIMSUIT S W IH1 M S UW2 T +SWIMSUITS S W IH1 M S UW2 T S +SWIMWEAR S W IH1 M W EH2 R +SWINBURNE'S S W IH1 N B ER0 N Z +SWINBURNES S W IH1 N B ER0 N Z +SWINDALL S W IH1 N D AH0 L +SWINDELL S W IH1 N D AH0 L +SWINDLE S W IH1 N D AH0 L +SWINDLED S W IH1 N D AH0 L D +SWINDLEHURST S W IH1 N D AH0 L HH ER0 S T +SWINDLER S W IH1 N D AH0 L ER0 +SWINDLER(1) S W IH1 N D L ER0 +SWINDLERS S W IH1 N D L ER0 Z +SWINDLES S W IH1 N D AH0 L Z +SWINDLING S W IH1 N D L IH0 NG +SWINE S W AY1 N +SWINEFORD S W IH1 N IH0 F ER0 D +SWINEFORD(1) S W AY1 N IH0 F ER0 D +SWINEHART S W AY1 N HH AA2 R T +SWINEY S W AY1 N IY0 +SWINFORD S W IH1 N F ER0 D +SWING S W IH1 NG +SWINGER S W IH1 NG ER0 +SWINGERS S W IH1 NG ER0 Z +SWINGING S W IH1 NG IH0 NG +SWINGLE S W IH1 NG G AH0 L +SWINGLER S W IH1 NG G AH0 L ER0 +SWINGLER(1) S W IH1 NG G L ER0 +SWINGLEY S W IH1 NG G L IY0 +SWINGS S W IH1 NG Z +SWINK S W IH1 NG K +SWINNEY S W IH1 N IY0 +SWINSON S W IH1 N S AH0 N +SWINT S W IH1 N T +SWINTON S W IH1 N T AH0 N +SWIPE S W AY1 P +SWIPED S W AY1 P T +SWIPES S W AY1 P S +SWIPING S W AY1 P IH0 NG +SWIRE S W AY1 R +SWIRL S W ER1 L +SWIRLED S W ER1 L D +SWIRLING S W ER1 L IH0 NG +SWIRLS S W ER1 L Z +SWIRSKY S W ER1 S K IY0 +SWISH S W IH1 SH +SWISHED S W IH1 SH T +SWISHER S W IH1 SH ER0 +SWISHES S W IH1 SH IH0 Z +SWISS S W IH1 S +SWISSAIR S W IH0 S EH1 R +SWISSHELM S W IH1 SH IH0 L M +SWISSHELM(1) S W IH1 S HH EH0 L M +SWISTAK S W IH1 S T AH0 K +SWITAJ S W IH0 T AY1 +SWITALA S W IH0 T AA1 L AH0 +SWITALSKI S W IH0 T AA1 L S K IY0 +SWITCH S W IH1 CH +SWITCHBLADE S W IH1 CH B L EY2 D +SWITCHBLADES S W IH1 CH B L EY2 D Z +SWITCHBOARD S W IH1 CH B AO2 R D +SWITCHBOARDS S W IH1 CH B AO2 R D Z +SWITCHED S W IH1 CH T +SWITCHER S W IH1 CH ER0 +SWITCHERS S W IH1 CH ER0 Z +SWITCHES S W IH1 CH AH0 Z +SWITCHES(1) S W IH1 CH IH0 Z +SWITCHING S W IH1 CH IH0 NG +SWITZER S W IH1 T S ER0 +SWITZERLAND S W IH1 T S ER0 L AH0 N D +SWITZERLAND'S S W IH1 T S ER0 L AH0 N D Z +SWIVEL S W IH1 V AH0 L +SWIVELED S W IH1 V AH0 L D +SWIVELING S W IH1 V AH0 L IH0 NG +SWIVELING(1) S W IH1 V L IH0 NG +SWIVELS S W IH1 V AH0 L Z +SWOBODA S W OW0 B OW1 D AH0 +SWOFFORD S W AA1 F ER0 D +SWOGGER S W AA1 G ER0 +SWOLLEN S W OW1 L AH0 N +SWONGER S W AO1 NG ER0 +SWOON S W UW1 N +SWOONED S W UW1 N D +SWOONING S W UW1 N IH0 NG +SWOOP S W UW1 P +SWOOPE S W UW1 P +SWOOPED S W UW1 P T +SWOOPING S W UW1 P IH0 NG +SWOOPS S W UW1 P S +SWOOSH S W UW1 SH +SWOOSHED S W UW1 SH T +SWOPE S W OW1 P +SWOPES S W OW1 P S +SWOR S W ER1 +SWORD S AO1 R D +SWORDFISH S AO1 R D F IH2 SH +SWORDFISH'S S AO1 R D F IH2 SH IH0 Z +SWORDLIKE S AO1 R D L AY2 K +SWORDPLAY S AO1 R D P L EY2 +SWORDPLAYS S AO1 R D P L EY2 Z +SWORDS S AO1 R D Z +SWORE S W AO1 R +SWORN S W AO1 R N +SWOVELAND S W OW1 V L AH0 N D +SWOYER S W OY1 ER0 +SWUM S W AH1 M +SWUNG S W AH1 NG +SWYERS S W AY1 ER0 Z +SWYGERT S W IH1 G ER0 T +SWYTO S W IY1 T OW0 +SY S AY1 +SYBASE S AY1 B EY2 S +SYBASE'S S AY1 B EY1 S IH0 Z +SYBERT S IH1 B ER0 T +SYBIL S IH1 B IH0 L +SYBILLA S IH0 B IH1 L AH0 +SYBILLE S IH1 B IH0 L +SYBRON S IH1 B R AH0 N +SYCAMORE S IH1 K AH0 M AO2 R +SYCARA S IH0 K AA1 R AH0 +SYCOPHANTIC S IH2 K AH0 F AE1 N T IH0 K +SYD S IH1 D +SYDELL S AY2 D EH1 L +SYDERS S AY1 D ER0 Z +SYDERS' S AY1 D ER0 Z +SYDNEY S IH1 D N IY0 +SYDNEY'S S IH1 D N IY0 Z +SYDNOR S IH1 D N ER0 +SYDOW S IH1 D OW0 +SYED S AY1 D +SYERS S AY1 ER0 Z +SYFERT S IH1 F ER0 T +SYGMA S IH1 G M AH0 +SYKES S AY1 K S +SYKORA S IH0 K AO1 R AH0 +SYLER S AY1 L ER0 +SYLLA S IH1 L AH0 +SYLLABIC S AH0 L AE1 B IH0 K +SYLLABLE S IH1 L AH0 B AH0 L +SYLLABLES S IH1 L AH0 B AH0 L Z +SYLLABUS S IH1 L AH0 B AH0 S +SYLMAR S IH1 L M AA0 R +SYLPH S IH1 L F +SYLPHIDE S IH1 L F IH0 D +SYLVA S IH1 L V AH0 +SYLVAIN S IH0 L V EY1 N +SYLVAN S IH1 L V AH0 N +SYLVANA S IH0 L V AE1 N AH0 +SYLVANIA S IH0 L V EY1 N IY0 AH0 +SYLVANUS S IH1 L V AH0 N IH0 S +SYLVEST S IH0 L V EH1 S T +SYLVESTER S IH0 L V EH1 S T ER0 +SYLVESTRE S IH0 L V EH1 S T ER0 +SYLVIA S IH1 L V IY0 AH0 +SYLVIA'S S IH1 L V IY0 AH0 Z +SYLVIE S IH1 L V IY0 +SYLVIO S IH1 L V IY0 OW0 +SYLVIO'S S IH1 L V IY0 OW0 Z +SYLVITE S IH1 L V AY2 T +SYM S IH1 M +SYMANSKI S IH0 M AE1 N S K IY0 +SYMANTEC S IH0 M AE1 N T EH2 K +SYMANTEC'S S IH0 M AE1 N T EH2 K S +SYMBION S IH1 M B IY0 AH0 N +SYMBION'S S IH1 M B IY0 AH0 N Z +SYMBIOSIS S IH2 M B AY0 OW1 S AH0 S +SYMBIOTIC S IH2 M B IY0 AA1 T IH0 K +SYMBOL S IH1 M B AH0 L +SYMBOL'S S IH1 M B AH0 L Z +SYMBOLIC S IH0 M B AA1 L IH0 K +SYMBOLICALLY S IH0 M B AA1 L IH0 K AH0 L IY0 +SYMBOLICALLY(1) S IH0 M B AA1 L IH0 K L IY0 +SYMBOLICS S IH0 M B AA1 L IH0 K S +SYMBOLISM S IH1 M B AH0 L IH2 Z AH0 M +SYMBOLISTS S IH1 M B AH0 L AH0 S T S +SYMBOLISTS(1) S IH1 M B AH0 L IH0 S T S +SYMBOLIZE S IH1 M B AH0 L AY2 Z +SYMBOLIZED S IH1 M B AH0 L AY2 Z D +SYMBOLIZES S IH1 M B AH0 L AY2 Z IH0 Z +SYMBOLIZING S IH1 M B AH0 L AY2 Z IH0 NG +SYMBOLS S IH1 M B AH0 L Z +SYME S AY1 M +SYMES S AY1 M Z +SYMINGTON S IH1 M IH0 NG T AH0 N +SYMMES S IH1 M Z +SYMMETRIC S AH0 M EH1 T R IH0 K +SYMMETRICAL S AH0 M EH1 T R IH0 K AH0 L +SYMMETRICALLY S AH0 M EH1 T R IH0 K L IY0 +SYMMETRY S IH1 M AH0 T R IY0 +SYMMONDS S IH1 M AH0 N D Z +SYMMS S IH1 M Z +SYMON S IH1 M AH0 N +SYMONDS S IH1 M AH0 N D Z +SYMONS S IH1 M AH0 N Z +SYMPATHETIC S IH2 M P AH0 TH EH1 T IH0 K +SYMPATHETICALLY S IH2 M P AH0 TH EH1 T IH0 K AH0 L IY0 +SYMPATHETICALLY(1) S IH2 M P AH0 TH EH1 T IH0 K L IY0 +SYMPATHIES S IH1 M P AH0 TH IY0 Z +SYMPATHIZE S IH1 M P AH0 TH AY2 Z +SYMPATHIZED S IH1 M P AH0 TH AY2 Z D +SYMPATHIZER S IH1 M P AH0 TH AY2 Z ER0 +SYMPATHIZERS S IH1 M P AH0 TH AY2 Z ER0 Z +SYMPATHIZES S IH1 M P AH0 TH AY2 Z IH0 Z +SYMPATHIZING S IH1 M P AH0 TH AY2 Z IH0 NG +SYMPATHY S IH1 M P AH0 TH IY0 +SYMPHONIC S IH0 M F AA1 N IH0 K +SYMPHONIES S IH1 M F AH0 N IY0 Z +SYMPHONY S IH1 M F AH0 N IY0 +SYMPHONY'S S IH1 M F AH0 N IY0 Z +SYMPOSIUM S IH0 M P OW1 Z IY0 AH0 M +SYMPOSIUMS S IH0 M P OW1 Z IY0 AH0 M Z +SYMPSON S IH1 M P S AH0 N +SYMPTOM S IH1 M P T AH0 M +SYMPTOMATIC S IH2 M P T AH0 M AE1 T IH0 K +SYMPTOMS S IH1 M P T AH0 M Z +SYMS S IH1 M Z +SYMTRON S IH1 M T R AA2 N +SYN S IH1 N +SYNA S IH1 N AH0 +SYNAGOGUE S IH1 N AH0 G AO2 G +SYNAGOGUES S IH1 N AH0 G AO2 G Z +SYNALLOY S IH0 N AE1 L OY0 +SYNALLOY'S S IH0 N AE1 L OY0 Z +SYNAN S AY1 N AH0 N +SYNAPSE S IH1 N AE0 P S +SYNAPSES S IH2 N AE1 P S IH0 Z +SYNAPTIC S IH2 N AE1 P T IH0 K +SYNAR S IH1 N AA0 R +SYNAR(1) S AY1 N AA0 R +SYNBIOTICS S IH2 N B IY0 AA1 T IH0 K S +SYNBIOTICS(1) S IH2 M B IY0 AA1 T IH0 K S +SYNC S IH1 NG K +SYNCH S IH1 N CH +SYNCHRO S IH1 NG K R OW0 +SYNCHRONIC S IH0 NG K R AA1 N IH0 K +SYNCHRONICITY S IH0 NG K R AH0 N IH1 S IH0 T IY0 +SYNCHRONIZATION S IH2 NG K R AH0 N AH0 Z EY1 SH AH0 N +SYNCHRONIZE S IH1 NG K R AH0 N AY2 Z +SYNCHRONIZED S IH1 NG K R AH0 N AY2 Z D +SYNCHRONIZES S IH1 NG K R AH0 N AY2 Z IH0 Z +SYNCHRONIZING S IH1 NG K R AH0 N AY2 Z IH0 NG +SYNCHRONOUS S IH1 NG K R AH0 N AH0 S +SYNCOM S IH1 NG K AA0 M +SYNCOPAL S IH1 N K AH0 P AH2 +SYNCOPATE S IH1 NG K AH0 P EY2 T +SYNCOPATED S IH1 NG K AH0 P EY2 T IH0 D +SYNCOPATION S IH1 NG K AH0 P EY2 SH AH0 N +SYNCOPE S IH1 N K AH0 P IY2 +SYNCOR S IH1 N K AO2 R +SYNDER S IH1 N D ER0 +SYNDICATE S IH1 N D IH0 K AH0 T +SYNDICATE(1) S IH1 N D AH0 K EY2 T +SYNDICATE'S S IH1 N D IH0 K AH0 T S +SYNDICATED S IH1 N D IH0 K EY2 T IH0 D +SYNDICATES S IH1 N D IH0 K EY2 T S +SYNDICATES(1) S IH1 N D IH0 K AH0 T S +SYNDICATING S IH1 N D IH0 K EY2 T IH0 NG +SYNDICATION S IH2 N D IH0 K EY1 SH AH0 N +SYNDICATIONS S IH2 N D IH0 K EY1 SH AH0 N Z +SYNDICATOR S IH1 N D IH0 K EY2 T ER0 +SYNDICATORS S IH1 N D IH0 K EY2 T ER0 Z +SYNDICATS S IH1 N D IH0 K IH2 T S +SYNDRICH S IH1 D R IH0 CH +SYNDROME S IH1 N D R OW2 M +SYNDROMES S IH1 N D R OW2 M Z +SYNERGEN S IH1 N ER0 JH EH2 N +SYNERGEN'S S IH1 N ER0 JH EH2 N Z +SYNERGETIC S IH0 N ER0 JH EH1 T IH0 K +SYNERGIES S IH1 N ER0 JH IY0 Z +SYNERGISM S IH1 N ER0 JH IH2 Z AH0 M +SYNERGISTIC S IH2 N ER0 JH IH1 S T IH0 K +SYNERGY S IH1 N ER0 JH IY0 +SYNERGY'S S IH1 N ER0 JH IY0 Z +SYNGMAN S IH1 NG M AH0 N +SYNHORST S IH1 N HH AO2 R S T +SYNNOTT S IH1 N AH0 T +SYNOD S IH1 N AH0 D +SYNOD'S S IH1 N AH0 D Z +SYNONYM S IH1 N AH0 N IH2 M +SYNONYMOUS S AH0 N AA1 N AH0 M AH0 S +SYNONYMOUSLY S AH0 N AA1 N AH0 M AH0 S L IY0 +SYNONYMS S IH1 N AH0 N IH2 M S +SYNOPSIS S IH0 N AA1 P S IH0 S +SYNOPTIC S IH0 N AA1 P T IH0 K +SYNOPTICS S IH0 N AA1 P T IH0 K S +SYNOVUS S AH0 N OW1 V AH0 S +SYNOVUS(1) S AY2 N OW1 V AH0 S +SYNTACTIC S IH2 N T AE1 K T IH0 K +SYNTAX S IH1 N T AE2 K S +SYNTECH S IH1 N T EH2 K +SYNTEX S IH1 N T EH2 K S +SYNTEX'S S IH1 N T EH0 K S IH0 Z +SYNTHESES S IH1 N TH AH0 S IY2 S +SYNTHESIS S IH1 N TH AH0 S AH0 S +SYNTHESIZE S IH1 N TH AH0 S AY2 Z +SYNTHESIZED S IH1 N TH IH0 S AY2 Z D +SYNTHESIZER S IH1 N TH AH0 S AY2 Z ER0 +SYNTHESIZERS S IH1 N TH AH0 S AY2 Z ER0 Z +SYNTHESIZING S IH1 N TH AH0 S AY2 Z IH0 NG +SYNTHETIC S IH0 N TH EH1 T IH0 K +SYNTHETICALLY S IH0 N TH EH1 T IH0 K L IY0 +SYNTHETICS S IH0 N TH EH1 T IH0 K S +SYNTREX S IH1 N T R AH0 K S +SYP S AY1 P +SYP(1) EH1 S W AY1 P IY1 +SYPHER S IH1 F ER0 +SYPHERS S IH1 F ER0 Z +SYPHILIS S IH1 F AH0 L IH0 S +SYPHON S AY1 F AH0 N +SYPNIEWSKI S IH0 P N IY0 EH1 F S K IY0 +SYPNIEWSKI(1) S IH0 P N UW1 S K IY0 +SYPOLT S IH1 P OW0 L T +SYRACUSE S IH1 R AH0 K Y UW2 Z +SYREK S IH1 R IH0 K +SYRIA S IH1 R IY0 AH0 +SYRIA'S S IH1 R IY0 AH0 Z +SYRIAN S IH1 R IY0 AH0 N +SYRIANS S IH1 R IY0 AH0 N Z +SYRING S AY1 R IH0 NG +SYRINGE S ER0 IH1 N JH +SYRINGE(1) S IH1 R IH0 N JH +SYRINGES S ER0 IH1 N JH AH0 Z +SYRON S AY1 R AH0 N +SYRUP S ER1 AH0 P +SYRUP(1) S IH1 R AH0 P +SYRUPS S ER1 AH0 P S +SYSCO S IH1 S K OW0 +SYSCON S AY1 S K AH0 N +SYSCON'S S AY1 S K AH0 N Z +SYSTEM S IH1 S T AH0 M +SYSTEM'S S IH1 S T AH0 M Z +SYSTEMAT S IH1 S T AH0 M AE0 T +SYSTEMATIC S IH2 S T AH0 M AE1 T IH0 K +SYSTEMATICALLY S IH2 S T AH0 M AE1 T IH0 K L IY0 +SYSTEMATICS S IH2 S T AH0 M AE1 T IH0 K S +SYSTEMHOUSE S IH1 S T AH0 M HH AW2 S +SYSTEMHOUSE'S S IH1 S T AH0 M HH AW2 S IH0 Z +SYSTEMIC S IH0 S T EH1 M IH0 K +SYSTEMICALLY S AH0 S T EH1 M IH0 K L IY0 +SYSTEMIX S IH1 S T IH0 M IH0 K S +SYSTEMIX(1) S IH2 S T EH1 M IH0 K S +SYSTEMONE S IH1 S T AH0 M OW2 N +SYSTEMS S IH1 S T AH0 M Z +SYSTEMS' S IH1 S T AH0 M Z +SYSTEMWIDE S IH1 S T AH0 M W AY2 D +SYSTOLIC S IH0 S T AO1 L IH0 K +SYSTRAN S AY1 S T R AE2 N +SYSTRAN(1) S IH1 S T R AE2 N +SYTSMA S IH1 T S M AH0 +SYVERSON S IH1 V ER0 S AH0 N +SYVERTSEN S IH1 V ER0 T S AH0 N +SZABO SH AA1 B OW0 +SZAFRAN SH AA1 F R AH0 N +SZAFRANSKI SH AH0 F R AE1 N S K IY0 +SZALAY SH AA1 L AY0 +SZALKOWSKI SH AH0 L K AO1 F S K IY0 +SZANTO SH AE1 N T OW0 +SZAREK SH AA1 R EH0 K +SZATKOWSKI SH AH0 T K AO1 F S K IY0 +SZCZECH SH EH1 K +SZCZEPANIAK SH IH0 P AE1 N IY0 AE0 K +SZCZEPANIK SH IH0 P AE1 N IH0 K +SZCZEPANSKI SH IH0 P AE1 N S K IY0 +SZCZERBA SH ER1 B AH0 +SZCZESNIAK SH EH1 Z N IY0 AE0 K +SZCZESNY SH EH1 Z N IY0 +SZCZYGIEL SH IH0 G IY1 L +SZE SH IY1 +SZE(1) SH EY1 +SZE-DI SH EY1 D IY1 +SZEKELY SH IY1 K L IY0 +SZELIGA SH IH0 L AY1 G AH0 +SZETO SH IY1 T OW0 +SZEWCZYK SH UW1 CH IH0 K +SZILAGYI SH IH0 L AA1 G IY0 +SZILARD S IH1 L ER0 D +SZILARD(1) Z IH1 L ER0 D +SZOKE SH OW1 K +SZOSTAK SH AA1 S T AH0 K +SZOSTEK SH AA1 S T EH0 K +SZOT SH AA1 T +SZOTT SH AA1 T +SZUBA SH UW1 B AH0 +SZUCH SH AH1 CH +SZUCS SH AH1 K S +SZUMSKI SH AH1 M S K IY0 +SZWED SH V EH1 D +SZYDLOWSKI SH IH0 D L AO1 F S K IY0 +SZYMANOWSKI SH IH0 M AH0 N AO1 F S K IY0 +SZYMANSKI SH IH0 M AE1 N S K IY0 +SZYMBORSKI SH IH0 M B AO1 R S K IY0 +SZYMCZAK SH IH1 M CH AE0 K +T T IY1 +T'ANG T AE1 NG +T'S T IY1 Z +T-BONE T IY1 B OW2 N +T-LAM T IY1 L AE1 M +T-MOBILE T IY1 M OW2 B AH0 L +T-SHIRT T IY1 S ER2 T +T-SHIRTS T IY1 S ER2 T S +T. T IY1 +T.'S T IY1 Z +T.S T IY1 Z +TA T AA1 +TAAFFE T AA1 F +TAB T AE1 B +TABACALERA T AH0 B AE2 K AH0 L EH1 R AH0 +TABACHNECK T AH0 B AA1 CH N EH2 K +TABAK T AE1 B AE0 K +TABAK(1) T AH0 B AE1 K +TABAKA T AA0 B AA1 K AH0 +TABAR T AA0 B AA1 R +TABARES T AA0 B AA1 R EH0 S +TABASCO T AH0 B AE1 S K OW0 +TABB T AE1 B +TABBERT T AE1 B ER0 T +TABBING T AE1 B IH0 NG +TABBY T AE1 B IY0 +TABER T EY1 B ER0 +TABERNACLE T AE1 B ER0 N AE2 K AH0 L +TABITHA T AE1 B IH0 TH AH0 +TABLATURE T AE1 B L AH0 CH ER0 +TABLE T EY1 B AH0 L +TABLE'S T EY1 B AH0 L Z +TABLEAU T AH0 B L OW1 +TABLEAUX T AH0 B L OW1 +TABLECLOTH T EY1 B AH0 L K L AO2 TH +TABLECLOTHS T EY1 B AH0 L K L AO2 TH S +TABLED T EY1 B AH0 L D +TABLER T EY1 B AH0 L ER0 +TABLER(1) T EY1 B L ER0 +TABLES T EY1 B AH0 L Z +TABLESPOON T EY1 B AH0 L S P UW2 N +TABLESPOONS T EY1 B AH0 L S P UW2 N Z +TABLET T AE1 B L AH0 T +TABLETOP T EY1 B AH0 L T AA2 P +TABLETS T AE1 B L AH0 T S +TABLEWARE T EY1 B AH0 L W EH2 R +TABLING T EY1 B AH0 L IH0 NG +TABLING(1) T EY1 B L IH0 NG +TABLOID T AE1 B L OY0 D +TABLOIDIZATION T AE2 B L OY0 D AH0 Z EY1 SH AH0 N +TABLOIDS T AE1 B L OY0 D Z +TABONE T AA1 B OW0 N +TABOO T AE0 B UW1 +TABOOS T AE0 B UW1 Z +TABOR T EY1 B ER0 +TABOR'S T EY1 B ER0 Z +TABORN T AE1 B ER0 N +TABRON T AE1 B R AH0 N +TABS T AE1 B Z +TABUCHI T AA2 B UW1 CH IY0 +TABULATE T AE1 B Y AH0 L EY2 T +TABULATED T AE1 B Y AH0 L EY2 T IH0 D +TABULATING T AE1 B Y AH0 L EY2 T IH0 NG +TABULATION T AE2 B Y AH0 L EY1 SH AH0 N +TABULATIONS T AE2 B Y AH0 L EY1 SH AH0 N Z +TABULATURE T AE1 B Y AH0 L AH0 CH ER0 +TAC T AE1 K +TACEY T EY1 S IY0 +TACHYCARDIA T AA2 K IY0 K AA1 R D IY2 AH0 +TACIT T AE1 S IH0 T +TACITA T AA0 CH IY1 T AH0 +TACITLY T AE1 S IH0 T L IY0 +TACITURN T AE1 S IH0 T ER2 N +TACK T AE1 K +TACKE T AE1 K +TACKED T AE1 K T +TACKER T AE1 K ER0 +TACKETT T AE1 K IH0 T +TACKING T AE1 K IH0 NG +TACKITT T AE1 K IH0 T +TACKLE T AE1 K AH0 L +TACKLED T AE1 K AH0 L D +TACKLES T AE1 K AH0 L Z +TACKLING T AE1 K L IH0 NG +TACKLING(1) T AE1 K AH0 L IH0 NG +TACKS T AE1 K S +TACKY T AE1 K IY0 +TACO T AA1 K OW0 +TACOMA T AH0 K OW1 M AA0 +TACOMA'S T AH0 K OW1 M AA0 Z +TACOS T AA1 K OW0 Z +TACT T AE1 K T +TACTFUL T AE1 K T F AH0 L +TACTFULLY T AE1 K T F AH0 L IY0 +TACTIC T AE1 K T IH0 K +TACTICAL T AE1 K T IH0 K AH0 L +TACTICALLY T AE1 K T IH0 K AH0 L IY0 +TACTICIAN T AE0 K T IH1 SH AH0 N +TACTICIANS T AE0 K T IH1 SH AH0 N Z +TACTICS T AE1 K T IH0 K S +TACTILE T AE1 K T IH0 L +TACTILE(1) T AE1 K T AY2 L +TACTLESS T AE1 K T L AH0 S +TACY T EY1 S IY0 +TAD T AE1 D +TADA T AA1 D AH0 +TADASHI T AA2 D AA1 SH IY0 +TADD T AE1 D +TADDEI T AE1 D AY0 +TADDEO T AA1 D IY0 OW0 +TADDY T AE1 D IY0 +TADEUSZ T AE1 D IY0 UW0 Z +TADIC T AE1 D IH0 K +TADLOCK T AE1 D L AH0 K +TADPOLE T AE1 D P OW2 L +TADPOLES T AE1 D P OW2 L Z +TADROS T EY1 D R OW0 Z +TADYCH T AA1 D IH0 HH +TAE T EY1 +TAE(1) T AY1 +TAEGU T EY1 G UW0 +TAEKWONDO T AE1 K W AA2 N D OW1 +TAEKWONDO(1) T AY0 K W AA1 N D OW0 +TAEWOO T AY1 W UW0 +TAFARO T AH0 F AA1 R OW0 +TAFEL T AE1 F AH0 L +TAFF T AE1 F +TAFFE T AE1 F +TAFFEL T AE1 F AH0 L +TAFFETA T AE1 F AH0 T AH0 +TAFFY T AE1 F IY0 +TAFLINGER T EY1 F AH0 L IH0 NG ER0 +TAFLINGER(1) T EY1 F L IH0 NG ER0 +TAFOLLA T AH0 F AA1 L AH0 +TAFOYA T AA0 F OY1 AH0 +TAFT T AE1 F T +TAFT'S T AE1 F T S +TAG T AE1 G +TAGALOG T AE1 G AH0 L AA2 G +TAGAMET T AE1 G AH0 M EH1 T +TAGANKA T AH0 G AA1 NG K AH0 +TAGER T EY1 G ER0 +TAGG T AE1 G +TAGGART T AE1 G ER0 T +TAGGART'S T AE1 G ER0 T S +TAGGE T AE1 G +TAGGED T AE1 G D +TAGGERT T AE1 G ER0 T +TAGGING T AE1 G IH0 NG +TAGLE T EY1 G AH0 L +TAGLIAFERRI T AA0 G L Y AA0 F EH1 R IY0 +TAGLIERI T AA0 G L IH1 R IY0 +TAGLINE T AE1 G L AY2 N +TAGOUT T AE1 G AW2 T +TAGS T AE1 G Z +TAGUE T AA1 G +TAHER T EY1 ER0 +TAHITI T AH0 HH IY1 T IY0 +TAHMASSEBI T AA2 M AH0 S IY1 B IY0 +TAHOE T AE1 HH OW0 +TAI T AY1 +TAIBI T EY1 B IY0 +TAIKO T EY1 K OW0 +TAIL T EY1 L +TAILED T EY1 L D +TAILGATE T EY1 L G EY2 T +TAILHOOK T EY1 L HH UH2 K +TAILING T EY1 L IH0 NG +TAILINGS T EY1 L IH0 NG Z +TAILLON T EY1 L AH0 N +TAILOR T EY1 L ER0 +TAILORED T EY1 L ER0 D +TAILORING T EY1 L ER0 IH0 NG +TAILORS T EY1 L ER0 Z +TAILPIPE T EY1 L P AY2 P +TAILS T EY1 L Z +TAILSPIN T EY1 L S P IH2 N +TAIMA T AY1 M AH0 +TAINER T EY1 N ER0 +TAING T AA1 IH0 NG +TAINT T EY1 N T +TAINTED T EY1 N T IH0 D +TAINTER T EY1 N T ER0 +TAINTING T EY1 N T IH0 NG +TAINTS T EY1 N T S +TAIPEI T AY1 P EY2 +TAIPEI'S T AY1 P EY2 Z +TAIRA T AA0 IH1 R AH0 +TAISEI T EY1 S EY2 +TAISHO T EY1 SH OW0 +TAIT T EY1 T +TAITE T EY1 T +TAITT T EY1 T +TAIWAN T AY1 W AA1 N +TAIWAN'S T AY1 W AA1 N Z +TAIWANESE T AY1 W AA0 N IY1 Z +TAIYO T AY1 Y OW0 +TAJ T AA1 ZH +TAJIK T AA1 JH IH0 K +TAJIKISTAN T AA2 JH IY1 K IH0 S T AE2 N +TAJIKISTAN'S T AA2 JH IY1 K IH0 S T AE2 N Z +TAJIMA T AA2 JH IY1 M AH0 +TAK T AE1 K +TAKACH T AE1 K AH0 K +TAKACS T AE1 K AH0 K S +TAKAGI T AA0 K AA1 G IY0 +TAKAHASHI T AA0 K AA0 HH AA1 SH IY0 +TAKAKI T AA0 K AA1 K IY0 +TAKAKO T AA2 K AA1 K OW0 +TAKANASHI T AA2 K AA2 N AA1 SH IY0 +TAKAO T AA2 K AA1 OW0 +TAKARA T AA0 K AA1 R AH0 +TAKASAGO T AA2 K AA0 S AA1 G OW0 +TAKASHI T AA2 K AA1 SH IY0 +TAKASHIMA T AA2 K AA0 SH IY1 M AH0 +TAKASHIMAYA T AA2 K AA2 SH IH0 M AA1 Y AH0 +TAKATA T AA0 K AA1 T AH0 +TAKAYAMA T AA0 K AA0 Y AA1 M AH0 +TAKE T EY1 K +TAKECARE T EY1 K EH1 R +TAKEDA T AA0 K EY1 D AH0 +TAKEI T AA1 K EY2 +TAKEMOTO T AA0 K EY0 M OW1 T OW2 +TAKEMURA T AA2 K EY0 M UH1 R AA2 +TAKEN T EY1 K AH0 N +TAKEO T AA2 K EY1 OW0 +TAKEOFF T EY1 K AO2 F +TAKEOFFS T EY1 K AO2 F S +TAKEOUT T EY1 K AW2 T +TAKEOVER T EY1 K OW2 V ER0 +TAKEOVERS T EY1 K OW2 V ER0 Z +TAKER T EY1 K ER0 +TAKERS T EY1 K ER0 Z +TAKES T EY1 K S +TAKESHI T AH0 K EH1 SH IY0 +TAKESHIMA T AE2 K IH0 SH IY1 M AA2 +TAKESHITA T AA2 K AH0 SH IY1 T AA2 +TAKESHITA'S T AA2 K AH0 SH IY1 T AA0 Z +TAKETA T AA0 K EY1 T AA2 +TAKETH T EY1 K AH0 TH +TAKETOMI T AA2 K IH0 T OW1 M IY2 +TAKEUCHI T AA2 K EY0 UW1 CH IY2 +TAKI T AE1 K IY2 +TAKI'S T AE1 K IY2 Z +TAKIHYO T AH0 K IY1 HH Y OW2 +TAKIN' T EY1 K IH0 N +TAKING T EY1 K IH0 NG +TAKINGS T EY1 K IH0 NG Z +TAKLA-MAKAN T AE1 K L AH0 M EY1 K AH0 N +TAKOMA T AH0 K OW1 M AH0 +TAKOMA'S T AH0 K OW1 M AH0 Z +TAKOMAS T AH0 K OW1 M AH0 Z +TAKU T AA1 K UW2 +TAKUSHOKU T AA2 K AH0 SH OW1 K UW2 +TAL T AA1 L +TALAGA T AA0 L AA1 G AA2 +TALAL T AH0 L AA1 L +TALAMANTES T AA0 L AA0 M AA1 N T EH0 S +TALAMANTEZ T AA0 L AA0 M AA1 N T EH0 Z +TALAMO T AA0 L AA1 M OW2 +TALARICO T AA0 L AA0 R IY1 K OW2 +TALAVERA T AA0 L AA0 V EH1 R AA2 +TALBERT T AE1 L B ER0 T +TALBOT T AE1 L B AH0 T +TALBOT'S T AE1 L B AH0 T S +TALBOTS T AE1 L B AH0 T S +TALBOTT T AE1 L B AH0 T +TALBOTT'S T AE1 L B AH0 T S +TALC T AE1 L K +TALCOTT T AE1 L K AH0 T +TALCS T AE1 L K S +TALCUM T AE1 L K AH0 M +TALE T EY1 L +TALENT T AE1 L AH0 N T +TALENTED T AE1 L AH0 N T IH0 D +TALENTS T AE1 L AH0 N T S +TALERICO T AA0 L ER0 IY1 K OW0 +TALES T EY1 L Z +TALESE T AH0 L IY1 Z +TALESE(1) T AH0 L IY1 Z IY0 +TALFORD T AE1 L F ER0 D +TALIBAN T AE1 L IH0 B AE2 N +TALIBAN'S T AE1 L IH0 B AE2 N Z +TALIBANS T AE1 L IH0 B AE2 N Z +TALIGENT T AE1 L IH0 JH EH0 N T +TALISMAN T AE1 L IH0 S M AH0 N +TALITHA T AE1 L IH0 DH AH0 +TALK T AO1 K +TALK'S T AO1 K S +TALKABLE T AO1 K AH0 B AH0 L +TALKATIVE T AO1 K AH0 T IH0 V +TALKBACK T AO1 K B AE2 K +TALKED T AO1 K T +TALKER T AO1 K ER0 +TALKERS T AO1 K ER0 Z +TALKIE T AO1 K IY0 +TALKIES T AO1 K IY0 Z +TALKIN T AA1 K AH0 N +TALKIN' T AO1 K IH0 N +TALKING T AO1 K IH0 NG +TALKING'S T AO1 K IH0 NG Z +TALKINGTON T AO1 K IH0 NG T AH0 N +TALKS T AO1 K S +TALKY T AO1 K IY0 +TALL T AO1 L +TALLADEGA T AE2 L AH0 D EY1 G AH0 +TALLAHASSEAN T AE2 L AH0 HH AE1 S IY0 AH0 N +TALLAHASSEANS T AE2 L AH0 HH AE1 S IY0 AH0 N Z +TALLAHASSEE T AE2 L AH0 HH AE1 S IY0 +TALLAHASSEE'S T AE2 L AH0 HH AE1 S IY0 Z +TALLANT T AA1 L AH0 N T +TALLARICO T AA0 L AA0 R IY1 K OW0 +TALLENT T AA1 L AH0 N T +TALLER T AO1 L ER0 +TALLERICO T AA0 L ER0 IY1 K OW0 +TALLEST T AO1 L IH0 S T +TALLEY T AE1 L IY0 +TALLGRASS T AA1 L G R AE2 S +TALLIE T AO1 L IY0 +TALLIED T AE1 L IY0 D +TALLIES T AE1 L IY0 Z +TALLIL T AH0 L IH1 L +TALLMADGE T AE1 L M AE0 JH +TALLMAN T AO1 L M AH0 N +TALLO T AE1 L OW0 +TALLON T AE1 L AH0 N +TALLOW T AE1 L OW0 +TALLULA T AA0 L UW1 L AH0 +TALLULAH T AE2 L UW1 L AH0 +TALLY T AE1 L IY0 +TALLYHO T AE2 L IY0 HH OW1 +TALLYING T AE1 L IY0 IH0 NG +TALMADGE T AE1 L M AE0 JH +TALMAGE T AE1 L M IH0 JH +TALMAN T AE1 L M AH0 N +TALMOR T AE1 L M AO2 R +TALMUD T AE1 L M AH0 D +TALON T AE1 L AH0 N +TALONS T AE1 L AH0 N Z +TALSMA T AA1 L S M AH0 +TALTON T AE1 L T AH0 N +TALTOS T AA1 L T OW0 Z +TALTY T AO1 L T IY0 +TAM T AE1 M +TAMA T AA1 M AH0 +TAMALES T AH0 M AA1 L IY0 Z +TAMANAHA T AA0 M AA0 N AA1 HH AH0 +TAMARA T AH0 M AA1 R AH0 +TAMARAC T AE1 M ER0 AE0 K +TAMARGO T AA0 M AA1 R G OW0 +TAMARIN T AE1 M ER0 AH0 N +TAMARINS T AE1 M ER0 AH0 N Z +TAMARISK T AE1 M ER0 IH0 S K +TAMARISKS T AE1 M ER0 IH0 S K S +TAMAS T AA1 M AH0 Z +TAMASHIRO T AA0 M AA0 SH IH1 R OW0 +TAMAYO T AA0 M AA1 Y OW0 +TAMBLYN T AE1 M B L IH0 N +TAMBO T AE1 M B OW0 +TAMBOCOR T AE1 M B OW0 K AO2 R +TAMBOURINE T AE2 M B ER0 IY1 N +TAMBRANDS T AE1 M B R AE2 N D Z +TAMBS T AE1 M Z +TAMBURELLO T AA0 M B UH0 R EH1 L OW0 +TAMBURO T AA0 M B UH1 R OW0 +TAMBURRI T AA0 M B UH1 R IY0 +TAMBURRINO T AA0 M B UH0 R IY1 N OW0 +TAMBURRO T AA0 M B UH1 R OW0 +TAME T EY1 M +TAMED T EY1 M D +TAMER T EY1 M ER0 +TAMES T EY1 M Z +TAMEZ T AA0 M EH1 Z +TAMI T AE1 M IY0 +TAMIAMI T AE2 M IY0 AE1 M IY0 +TAMIL T AH0 M IH1 L +TAMIL(1) T AE1 M IH0 L +TAMILS T AH0 M IH1 L Z +TAMILS(1) T AE1 M IH0 L Z +TAMING T EY1 M IH0 NG +TAMKE T AE1 M K IY0 +TAMM T AE1 M +TAMMANY T AE1 M AH0 N IY0 +TAMMARO T AA0 M AA1 R OW0 +TAMMEN T AE1 M AH0 N +TAMMIE T AE1 M IY0 +TAMMINGA T AA0 M IY1 NG G AH0 +TAMMO T AE1 M OW0 +TAMMY T AE1 M IY0 +TAMOXIFEN T AE2 M AA1 K S AH0 F AH0 N +TAMP T AE1 M P +TAMPA T AE1 M P AH0 +TAMPA'S T AE1 M P AH0 Z +TAMPAX T AE1 M P AE2 K S +TAMPER T AE1 M P ER0 +TAMPERED T AE1 M P ER0 D +TAMPERING T AE1 M P ER0 IH0 NG +TAMPING T AE1 M P IH0 NG +TAMPLIN T AE1 M P L IH0 N +TAMPON T AE1 M P AA0 N +TAMPONS T AE1 M P AA0 N Z +TAMPOPO T AE2 M P OW1 P OW0 +TAMPOSI T AE2 M P OW1 S IY0 +TAMPS T AE1 M P S +TAMRAZ T AE1 M R AE0 Z +TAMRAZ'S T AE1 M R AE0 Z AH0 Z +TAMRES T AE1 M R EH0 Z +TAMURA T AA0 M UH1 R AH0 +TAN T AE1 N +TANABE T AA0 N AA1 B EY0 +TANAKA T AA0 N AA1 K AH0 +TANARTKIT T AE2 N AA1 R T K IH2 T +TANCREDI T AA0 N K R EH1 D IY0 +TANCREDO T AE2 N K R EY1 D OW0 +TANDEM T AE1 N D AH0 M +TANDEM'S T AE1 N D AH0 M Z +TANDON T AE1 N D AH0 N +TANDY T AE1 N D IY0 +TANDY'S T AE1 N D IY0 Z +TANDYCRAFT T AE1 N D IY0 K R AE2 F T +TANDYCRAFTS T AE1 N D IY0 K R AE2 F T S +TANEJA T AH0 N EY1 HH AH0 +TANEN T AE1 N AH0 N +TANENBAUM T AE1 N AH0 N B AW2 M +TANEY T EY1 N IY0 +TANG T AE1 NG +TANG(1) T AA1 NG +TANGE T AE1 N JH +TANGELO T AE1 N JH EH2 L OW0 +TANGEMAN T EY1 N JH M AH0 N +TANGEN T AE1 NG AH0 N +TANGENT T AE1 N JH AH0 N T +TANGENTIAL T AE0 N JH EH1 N SH AH0 L +TANGENTIALLY T AE0 N JH EH1 N SH AH0 L IY0 +TANGENTS T AE1 N JH AH0 N T S +TANGER T AE1 NG ER0 +TANGERINE T AE2 N JH ER0 IY1 N +TANGERINES T AE1 N JH ER0 IY2 N Z +TANGIBLE T AE1 N JH AH0 B AH0 L +TANGIBLES T AE1 N JH AH0 B AH0 L Z +TANGIBLY T AE1 N JH AH0 B L IY0 +TANGIERS T AE2 N JH IH1 R Z +TANGLE T AE1 NG G AH0 L +TANGLED T AE1 NG G AH0 L D +TANGLES T AE1 NG G AH0 L Z +TANGLEWOOD T AE1 NG G AH0 L W UH2 D +TANGLING T AE1 NG G L IH0 NG +TANGNEY T AE1 NG G N IY0 +TANGO T AE1 NG G OW0 +TANGOS T AE1 NG G OW0 Z +TANGQUI T AE1 NG K W IY1 +TANGREDI T AA0 NG G R EH1 D IY0 +TANGS T AE1 NG Z +TANGUAY T AE1 N G EY0 +TANGUMA T AA0 NG G UW1 M AH0 +TANI T AA1 N IY0 +TANIA T AA1 N Y AH0 +TANIGUCHI T AA2 N IH0 G UW1 CH IY0 +TANIMOTO T AA0 N IY0 M OW1 T OW0 +TANIMURA T AA2 N IH0 M UW1 R AH0 +TANIS T AE1 N IH0 S +TANJUG T AE1 N JH AH2 G +TANK T AE1 NG K +TANK'S T AE1 NG K S +TANKAN T AE1 NG K AH0 N +TANKARD T AE1 NG K ER0 D +TANKE T AE1 NG K +TANKED T AE1 NG K T +TANKER T AE1 NG K ER0 +TANKERS T AE1 NG K ER0 Z +TANKERSLEY T AE1 NG K ER0 S L IY0 +TANKING T AE1 NG K IH0 NG +TANKS T AE1 NG K S +TANKSLEY T AE1 NG K S L IY0 +TANN T AE1 N +TANNAHILL T AE1 N AH0 HH IH2 L +TANNED T AE1 N D +TANNEHILL T AE1 N IH0 HH IH0 L +TANNEN T AE1 N AH0 N +TANNENBAUM T AE1 N AH0 N B AW2 M +TANNER T AE1 N ER0 +TANNEST T AE1 N IH0 S T +TANNEY T AE1 N IY0 +TANNHAUSER T AE1 N HH AW2 Z ER0 +TANNING T AE1 N IH0 NG +TANQUERAY T AE1 NG K W ER0 EY2 +TANS T AE1 N Z +TANSEY T AE1 N Z IY0 +TANSKI T AE1 N S K IY2 +TANSU T AE1 N S UW2 +TANSY T AE1 N Z IY0 +TANT T AE1 N T +TANTALIZE T AE1 N T AH0 L AY2 Z +TANTALIZE(1) T AE1 N AH0 L AY2 Z +TANTALIZED T AE1 N T AH0 L AY2 Z D +TANTALIZED(1) T AE1 N AH0 L AY2 Z D +TANTALIZES T AE1 N T AH0 L AY2 Z IH0 Z +TANTALIZES(1) T AE1 N AH0 L AY2 Z AH0 Z +TANTALIZING T AE1 N T AH0 L AY2 Z IH0 NG +TANTALIZING(1) T AE1 N AH0 L AY2 Z IH0 NG +TANTALIZINGLY T AE1 N T AH0 L AY2 Z IH0 NG L IY0 +TANTALIZINGLY(1) T AE1 N AH0 L AY2 Z IH0 NG L IY0 +TANTALUM T AE1 N T AH0 L AH0 M +TANTALUS T AE1 N T AH0 L AH0 S +TANTAMOUNT T AE1 N T AH0 M AW2 N T +TANTILLO T AA0 N T IH1 L OW0 +TANTON T AE1 N T AH0 N +TANTRIC T AE1 N T R IH0 K +TANTRUM T AE1 N T R AH0 M +TANTRUMS T AE1 N T R AH0 M Z +TANU T AA1 N UW0 +TANYA T AA1 N Y AH0 +TANZANIA T AE0 N Z EY1 N IY0 AH0 +TANZANIA(1) T AE2 N Z AH0 N IY1 AH0 +TANZANIA(2) T AE2 N Z EY1 N Y AH0 +TANZANIA'S T AE0 N Z EY1 N IY0 AH0 Z +TANZANIA'S(1) T AE2 N Z AH0 N IY1 AH0 Z +TANZANIA'S(2) T AE2 N Z EY1 N Y AH0 Z +TANZANIAN T AE2 N Z EY1 N IY0 AH0 N +TANZANIAN(1) T AE2 N Z EY1 N Y AH0 N +TANZER T AE1 N Z ER0 +TANZI T AE1 N Z IY0 +TAO T AW1 +TAO(1) D AW1 +TAOISM D AW1 IH0 Z AH0 M +TAOIST D AW1 IH0 S T +TAOISTS D AW1 AH0 S T S +TAORMINA T AA0 AO0 R M IY1 N AH0 +TAOS T AW1 Z +TAP T AE1 P +TAPAS T AH1 P AH0 S +TAPE T EY1 P +TAPE'S T EY1 P S +TAPED T EY1 P T +TAPEIE T EY1 P IY0 EY0 +TAPEIE'S T EY1 P IY0 EY0 Z +TAPER T EY1 P ER0 +TAPERED T EY1 P ER0 D +TAPERING T EY1 P ER0 IH0 NG +TAPERS T EY1 P ER0 Z +TAPES T EY1 P S +TAPESTRIES T AE1 P AH0 S T R IY0 Z +TAPESTRY T AE1 P AH0 S T R IY0 +TAPIA T AA1 P IY0 AH0 +TAPIAS T AH0 P IY1 AH0 S +TAPIE T AE1 P IY0 +TAPING T EY1 P IH0 NG +TAPINGS T EY1 P IH0 NG Z +TAPLEY T AE1 P L IY0 +TAPLIN T AE1 P L IH0 N +TAPP T AE1 P +TAPPAN T AE1 P AH0 N +TAPPE T AE1 P +TAPPED T AE1 P T +TAPPEN T AE1 P AH0 N +TAPPER T AE1 P ER0 +TAPPET T AE1 P AH0 T +TAPPIN T AE1 P IH0 N +TAPPING T AE1 P IH0 NG +TAPS T AE1 P S +TAPSCOTT T AE1 P S K AH0 T +TAR T AA1 R +TARA T EH1 R AH0 +TARA(1) T AA1 R AH0 +TARA'S T EH1 R AH0 Z +TARA'S(1) T AA1 R AH0 Z +TARAHUMARA T AA0 R AH0 HH UW1 M AA0 R AH0 +TARALLO T ER0 AE1 L OW0 +TARANGO T AA0 R AA1 NG G OW0 +TARANTINO T AA0 R AA0 N T IY1 N OW0 +TARANTO T ER0 AE1 N T OW0 +TARANTO'S T ER0 AE1 N T OW0 Z +TARANTULA T AH0 R AE1 N CH UW0 L AH0 +TARANTULA(1) T AH0 R AE1 N CH AH0 L AH0 +TARANTULAS T AH0 R AE1 N CH UW0 L AH0 Z +TARANTULAS(1) T AH0 R AE1 N CH AH0 L AH0 Z +TARAS T AA1 R AH0 Z +TARASOFF T EH1 R IH0 S AO0 F +TARAVELLA T AE2 R AH0 V EH1 L AH0 +TARBELL T AA1 R B EH2 L +TARBERT T AA1 R B ER0 T +TARBET T AA1 R B IH0 T +TARBOX T AA1 R B AA2 K S +TARBUTTON T AA1 R B AH2 T AH0 N +TARDIF T AA1 R D IH0 F +TARDIFF T AA1 R D IH0 F +TARDINESS T AA1 R D IY0 N AH0 S +TARDITI T AA2 R D IH1 T IY0 +TARDY T AA1 R D IY0 +TARGET T AA1 R G AH0 T +TARGET(1) T ER1 G AH0 T +TARGET'S T AA1 R G AH0 T S +TARGETED T AA1 R G AH0 T IH0 D +TARGETING T AA1 R G AH0 T IH0 NG +TARGETS T AA1 R G AH0 T S +TARHEEL T AA1 R HH IY2 L +TARHEELS T AA1 R HH IY2 L Z +TARIFF T EH1 R AH0 F +TARIFFS T EH1 R AH0 F S +TARIN T AA1 R IY0 N +TARIQ T AA2 R IY1 K +TARKINGTON T AA1 R K IH0 NG T AH0 N +TARKOWSKI T ER0 K AO1 F S K IY0 +TARLETON T AA1 R L T AH0 N +TARLOW T AA1 R L OW2 +TARLTON T AA1 R L T AH0 N +TARMAC T AA1 R M AE2 K +TARMACS T AA1 R M AE2 K S +TARMAN T AA1 R M AH0 N +TARNISH T AA1 R N IH0 SH +TARNISHED T AA1 R N IH0 SH T +TARNISHING T AA1 R N IH0 SH IH0 NG +TARNOFF T AA1 R N AO2 F +TARNOFF'S T AA1 R N AO2 F S +TARNOW T AA1 R N OW0 +TARNOWER T AA1 R N AW0 ER0 +TARNOWSKI T ER0 N AO1 F S K IY0 +TARO T EH1 R OW0 +TAROM T EH1 R AH0 M +TAROT T AE2 R OW1 +TAROTS T AE2 R OW1 Z +TARP T AA1 R P +TARPEY T AA1 R P IY0 +TARPLEY T AA1 R P L IY0 +TARPON T AA1 R P AH0 N +TARPS T AA1 R P S +TARPY T AA1 R P IY0 +TARQUINIO T AA0 R K W IY1 N IY0 OW0 +TARR T AA1 R +TARRANCE T AA1 R AH0 N S +TARRANT T AA1 R AH0 N T +TARRED T AA1 R D +TARRING T AA1 R IH0 NG +TARRY T EH1 R IY0 +TARRYTOWN T EH1 R IY0 T AW2 N +TARSES T AA1 R S IH0 S +TARSUS T AA1 R S AH0 S +TART T AA1 R T +TARTAGLIA T AA0 R T AE1 G L IY0 AH0 +TARTAGLIONE T AA0 R T AE0 G L IY0 OW1 N IY0 +TARTAN T AA1 R T AH0 N +TARTAR T AA1 R T ER0 +TARTARS T AA1 R T ER0 Z +TARTE T AA1 R T +TARTER T AA1 R T ER0 +TARTIKOFF T AA1 R T IH0 K AO2 F +TARTIKOFF'S T AA1 R T IH0 K AO2 F S +TARTIKOFFS T AA1 R T IH0 K AO2 F S +TARTLY T AA1 R T L IY0 +TARTNESS T AA1 R T N AH0 S +TARTS T AA1 R T S +TARTT T AA1 R T +TARTU T AA2 R T UW1 +TARVER T AA1 R V ER0 +TARVIN T AA1 R V IH0 N +TARZAN T AA1 R Z AE2 N +TARZAN(1) T AA1 R Z AH0 N +TARZAN'S T AA1 R Z AE2 N Z +TARZAN'S(1) T AA1 R Z AH0 N Z +TASADAY T AE1 S AH0 D EY0 +TASCA T AA1 S K AH0 +TASCH T AE1 SH +TASCHNER T AE1 SH N ER0 +TASER T EY1 Z ER0 +TASH T AE1 SH +TASHA T AE1 SH AH0 +TASHIN T AE1 SH IH0 N +TASHIRO T AA0 SH IH1 R OW0 +TASHJIAN T AE1 SH JH IY0 AH0 N +TASHKENT T AE2 SH K EH1 N T +TASK T AE1 S K +TASKED T AE1 S K T +TASKER T AE1 S K ER0 +TASKFORCE T AE1 S K F AO2 R S +TASKING T AE1 S K IH0 NG +TASKMASTER T AE1 S K M AE2 S T ER0 +TASKS T AE1 S K S +TASM T AE1 S AH0 M +TASMAN T AE1 Z M AH0 N +TASMANIA T AE2 Z M EY1 N IY0 AH0 +TASMANIAN T AE2 Z M EY1 N IY0 AH0 N +TASS T AE1 S +TASSEL T AE1 S AH0 L +TASSELED T AE1 S AH0 L D +TASSI T AE1 S IY0 +TASSIN T AE1 S IH0 N +TASSINARI T AA0 S IY0 N AA1 R IY2 +TASSO T AE1 S OW2 +TASSONE T AA0 S OW1 N IY2 +TASTE T EY1 S T +TASTED T EY1 S T IH0 D +TASTEFUL T EY1 S T F AH0 L +TASTEFULLY T EY1 S T F AH0 L IY0 +TASTELESS T EY1 S T L AH0 S +TASTER T EY1 S T ER0 +TASTER'S T EY1 S T ER0 Z +TASTERS T EY1 S T ER0 Z +TASTES T EY1 S T S +TASTIER T EY1 S T IY0 ER0 +TASTINESS T EY1 S T IY0 N AH0 S +TASTING T EY1 S T IH0 NG +TASTINGS T EY1 S T IH0 NG Z +TASTY T EY1 S T IY0 +TAT T AE1 T +TATA T AA1 T AA0 +TATAR T AA2 T AA1 R +TATARS T AA2 T AA1 R Z +TATARSTAN T AA2 T AA1 R S T AA2 N +TATE T EY1 T +TATE'S T EY1 T S +TATEHO T AH0 T EY1 HH OW0 +TATEHO'S T AH0 T EY1 HH OW0 Z +TATEM T AE1 T IH0 M +TATER T EY1 T ER0 +TATERS T EY1 T ER0 Z +TATGE T EY1 T JH +TATHAM T AE1 TH AH0 M +TATIANA T AE2 T IY2 AE1 N AA2 +TATIANA(1) T AE2 T Y AA1 N AA2 +TATJANA T AE2 T Y AA1 N AA2 +TATLOCK T AE1 T L AA2 K +TATMAN T AE1 T M AH0 N +TATOM T AE1 T AH0 M +TATRA T AE1 T R AA2 +TATRO T AE1 T R OW2 +TATSCH T AE1 CH +TATSUKICHI T AH0 T S UW0 K IY1 CH IY2 +TATSUNO T AE2 T S UW1 N OW2 +TATTER T AE1 T ER0 +TATTERED T AE1 T ER0 D +TATTERS T AE1 T ER0 Z +TATTERSALL T AE1 T ER0 S AH0 L +TATTLE T AE1 T AH0 L +TATTLED T AE1 T AH0 L D +TATTLER T AE1 T L ER0 +TATTOO T AE2 T UW1 +TATTOOED T AE2 T UW1 D +TATTOOING T AE2 T UW1 IH0 NG +TATTOOS T AE2 T UW1 Z +TATTY T AE1 T IY2 +TATU T AA2 T UW1 +TATUM T EY1 T AH0 M +TATYANA T AA0 T Y AA1 N AA0 +TAUB T AW1 B +TAUBE T AO1 B +TAUBER T AW1 B ER0 +TAUBERT T AW1 B ER0 T +TAUBES T AW1 B Z +TAUBMAN T AW1 B M AH0 N +TAUCHER T AW1 K ER0 +TAUER T AW1 ER0 +TAUGHT T AO1 T +TAUKE T AW1 K +TAUL T AO1 L +TAULBEE T AO1 L B IY2 +TAUNT T AO1 N T +TAUNTED T AO1 N T IH0 D +TAUNTING T AO1 N T IH0 NG +TAUNTON T AO1 N T AH0 N +TAUNTS T AO1 N T S +TAURUS T AO1 R AH0 S +TAURUSES T AO1 R AH0 S AH0 Z +TAUSCH T AW1 SH +TAUSCHER T AW1 SH ER0 +TAUSSIG T AW1 S IH0 G +TAUT T AO1 T +TAUZIN T AW1 Z IH0 N +TAVANO T AA0 V AA1 N OW0 +TAVARES T AA0 V AA1 R EH0 S +TAVAREZ T AA0 V AA1 R EH0 Z +TAVEL T AA0 V EH1 L +TAVENNER T AE1 V IH0 N ER0 +TAVERA T AA0 V EH1 R AH0 +TAVERAS T AA0 V EH1 R AA0 Z +TAVERN T AE1 V ER0 N +TAVERNA T AA0 V EH1 R N AH0 +TAVERNA'S T AA0 V EH1 R N AH0 Z +TAVERNAS T AA0 V EH1 R N AH0 Z +TAVERNIER T AE1 V ER0 N IY0 ER0 +TAVERNS T AE1 V ER0 N Z +TAVES T EY1 V Z +TAVIE T EY1 V IY0 +TAVIS T AA1 V IH0 S +TAVISH T EY1 V IH0 SH +TAVIST T AE1 V IH0 S T +TAVLIN T AE1 V L IH0 N +TAVOULAREAS T AA0 V UW0 L EH1 R IY0 AH0 S +TAVY T EY1 V IY0 +TAWANA T AA2 W AA1 N AH0 +TAWDRY T AO1 D R IY0 +TAWES T AO1 Z +TAWFIQ T AA1 F IH0 K +TAWIL T AO1 AH0 L +TAWNEY T AO1 N IY0 +TAWNY T AA1 N IY0 +TAX T AE1 K S +TAX'S T AE1 K S IH0 Z +TAXABILITY T AE2 K S AH0 B IH1 L IH0 T IY0 +TAXABLE T AE1 K S AH0 B AH0 L +TAXABLES T AE1 K S AH0 B AH0 L Z +TAXATION T AE0 K S EY1 SH AH0 N +TAXCUT T AE1 K S K AH2 T +TAXED T AE1 K S T +TAXER T AE1 K S ER0 +TAXERS T AE1 K S ER0 Z +TAXES T AE1 K S AH0 Z +TAXES(1) T AE1 K S IH0 Z +TAXES' T AE1 K S IH0 Z +TAXI T AE1 K S IY0 +TAXI'S T AE1 K S IY0 Z +TAXICAB T AE1 K S IY0 K AE2 B +TAXICABS T AE1 K S IY0 K AE2 B Z +TAXIDERMIST T AE1 K S AH0 D ER2 M AH0 S T +TAXIDERMISTS T AE1 K S AH0 D ER2 M AH0 S T S +TAXIDERMISTS(1) T AE1 K S AH0 D ER2 M AH0 S +TAXIDERMY T AE1 K S AH0 D ER2 M IY0 +TAXIED T AE1 K S IY0 D +TAXIING T AE1 K S IY0 IH0 NG +TAXING T AE1 K S IH0 NG +TAXIS T AE1 K S IY0 Z +TAXIWAY T AE1 K S IY0 W EY0 +TAXOL T AE1 K S AA2 L +TAXONOMIES T AE2 K S AO1 N AH0 M IY2 Z +TAXONOMY T AE2 K S AO1 N AH0 M IY2 +TAXPAYER T AE1 K S P EY2 ER0 +TAXPAYER'S T AE1 K S P EY2 ER0 Z +TAXPAYERS T AE1 K S P EY2 ER0 Z +TAXPAYERS' T AE1 K S P EY2 ER0 Z +TAXPAYING T AE1 K S P EY2 IH0 NG +TAY T EY1 +TAYLER T EY1 L ER0 +TAYLOE T EY1 L OW0 +TAYLOR T EY1 L ER0 +TAYLOR'S T EY1 L ER0 Z +TAYLORS T EY1 L ER0 Z +TAYMAN T EY1 M AH0 N +TAYS T EY1 Z +TB T IY1 B IY1 +TBILISI T AH0 B IH0 L IY1 S IY0 +TBILISI(1) T AH0 B L IY1 S IY0 +TCAS T IY1 S IY1 EY1 EH1 S +TCHAIKOVSKY CH EY2 K AA1 V S K IY0 +TCHAIKOVSKY(1) CH AY2 K AA1 V S K IY0 +TCHAIKOVSKY(2) CH AY2 K AA1 F S K IY0 +TCHAIKOVSKY'S CH EY2 K AA1 V S K IY0 Z +TCHAIKOVSKY'S(1) CH AY2 K AA1 V S K IY0 Z +TCHAIKOVSKY'S(2) CH AY2 K AA1 F S K IY0 Z +TCHURUK CH UH1 R IH0 K +TE T IY1 +TEA T IY1 +TEAC T IY1 K +TEAC(1) T IY1 AE0 K +TEACH T IY1 CH +TEACHABLE T IY1 CH AH0 B AH0 L +TEACHER T IY1 CH ER0 +TEACHER'S T IY1 CH ER0 Z +TEACHERS T IY1 CH ER0 Z +TEACHERS' T IY1 CH ER0 Z +TEACHES T IY1 CH AH0 Z +TEACHES(1) T IY1 CH IH0 Z +TEACHEY T IY1 CH IY0 +TEACHING T IY1 CH IH0 NG +TEACHINGS T IY1 CH IH0 NG Z +TEACHOUT T IY1 CH AW2 T +TEACUP T IY1 K AH2 P +TEAFORD T IY1 F AO2 R D +TEAFORD(1) T IY1 F ER0 D +TEAGARDEN T IY1 G AA2 R D AH0 N +TEAGLE T IY1 G AH0 L +TEAGUE T IY1 G +TEAHAN T IY1 AH0 N +TEAK T IY1 K +TEAKAMP T IY1 K AE0 M P +TEAKWOOD T IY1 K W UH2 D +TEAL T IY1 L +TEALE T IY1 L +TEALL T IY1 L +TEAM T IY1 M +TEAM'S T IY1 M Z +TEAMED T IY1 M D +TEAMER T IY1 M ER0 +TEAMING T IY1 M IH0 NG +TEAMMATE T IY1 M EY2 T +TEAMMATES T IY1 M M EY2 T S +TEAMS T IY1 M Z +TEAMS' T IY1 M Z +TEAMSTER T IY1 M S T ER0 +TEAMSTER'S T IY1 M S T ER0 Z +TEAMSTERS T IY1 M S T ER0 Z +TEAMSTERS' T IY1 M S T ER0 Z +TEAMWORK T IY1 M W ER2 K +TEANECK T IY1 N EH2 K +TEANEY T IY1 N IY0 +TEAPOT T IY1 P AA2 T +TEAR T EH1 R +TEAR(1) T IH1 R +TEARE T IY1 R +TEARFUL T IH1 R F AH0 L +TEARFULLY T IH1 R F AH0 L IY0 +TEARING T EH1 R IH0 NG +TEARING(1) T IH1 R IH0 NG +TEARLE T AO1 R AH0 L +TEARS T EH1 R Z +TEARS(1) T IH1 R Z +TEARY T IH1 R IY0 +TEAS T IY1 Z +TEASDALE T IY1 Z D EY2 L +TEASE T IY1 Z +TEASED T IY1 Z D +TEASER T IY1 Z ER0 +TEASES T IY1 Z IH0 Z +TEASING T IY1 Z IH0 NG +TEASLEY T IY1 Z L IY0 +TEASON T IY1 S AO0 N +TEASPOON T IY1 S P UW2 N +TEASPOONFUL T IY1 S P UW2 N F AH0 L +TEASPOONS T IY1 S P UW2 N Z +TEAST T IY1 S T +TEASTER T IY1 S T ER0 +TEAT T IY1 T +TEATE T IY1 EY2 T +TEATER T IY1 T ER0 +TEATRO T IY1 T R OW0 +TEATS T IY1 T S +TEBBE T EH1 B +TEBBEN T EH1 B AH0 N +TEBBETTS T EH1 B IH0 T S +TEBBIT T EH1 B IH0 T +TEBBS T EH1 B Z +TEBEAU T IH0 B OW1 +TEBELSKIS T AH0 B EH1 L S K IY0 S +TEBO T EH1 B OW0 +TEBUTHIURON T EH2 B AH0 TH Y UW1 R AA0 N +TEC T EH1 K +TECH T EH1 K +TECH'S T EH1 K S +TECHIE T EH1 K IY0 +TECHIES T EH1 K IY0 Z +TECHINT T EH1 CH IH0 N T +TECHINT(1) T EH1 K IH2 N T +TECHNIC T EH1 K N IH0 K +TECHNICAL T EH1 K N IH0 K AH0 L +TECHNICAL'S T EH1 K N IH0 K AH0 L Z +TECHNICALITIES T EH2 K N IH0 K AE1 L AH0 T IY0 Z +TECHNICALITY T EH2 K N IH0 K AE1 L IH0 T IY0 +TECHNICALLY T EH1 K N IH0 K AH0 L IY0 +TECHNICALLY(1) T EH1 K N IH0 K L IY0 +TECHNICALS T EH1 K N IH0 K AH0 L Z +TECHNICIAN T EH0 K N IH1 SH AH0 N +TECHNICIAN'S T EH0 K N IH1 SH AH0 N Z +TECHNICIANS T EH0 K N IH1 SH AH0 N Z +TECHNICOLOR T EH1 K N IH0 K AH2 L ER0 +TECHNICON T EH1 K N IH0 K AA2 N +TECHNICS T EH1 K N IH0 K S +TECHNIQUE T EH0 K N IY1 K +TECHNIQUES T EH0 K N IY1 K S +TECHNITROL T EH1 K N IH0 T R OW2 L +TECHNO T EH1 K N OW0 +TECHNOCRAT T EH1 K N AH0 K R AE2 T +TECHNOCRATIC T EH2 K N AH0 K R AE1 T IH0 K +TECHNOCRATS T EH1 K N AH0 K R AE2 T S +TECHNODYNE T EH1 K N OW0 D AY2 N +TECHNOLOGIC T EH2 K N AH0 L AA1 JH IH0 K +TECHNOLOGICAL T EH2 K N AH0 L AA1 JH IH0 K AH0 L +TECHNOLOGICALLY T EH2 K N AH0 L AA1 JH IH0 K AH0 L IY0 +TECHNOLOGICALLY(1) T EH2 K N AH0 L AA1 JH IH0 K L IY0 +TECHNOLOGIES T EH0 K N AA1 L AH0 JH IY0 Z +TECHNOLOGIES' T EH2 K N AA1 L AH0 JH IY0 Z +TECHNOLOGIST T EH2 K N AA1 L AH0 JH IH0 S T +TECHNOLOGISTS T EH2 K N AA1 L AH0 JH IH0 S T S +TECHNOLOGY T EH0 K N AA1 L AH0 JH IY0 +TECHNOLOGY'S T EH0 K N AA1 L AH0 JH IY0 Z +TECHNOMIC T EH2 K N AA1 M IH0 K +TECHNOPHOBE T EH1 K N OW0 F OW2 B +TECHNOPHOBE'S T EH1 K N OW0 F OW2 B Z +TECHNOPHOBES T EH1 K N OW0 F OW2 B Z +TECHS T EH1 K S +TECHSYSTEM T EH1 K S IH2 S T AH0 M +TECHSYSTEMS T EH1 K S IH2 S T AH0 M Z +TECHY T EH1 CH IY0 +TECK T EH1 K +TECK'S T EH1 K S +TECLA T EH1 K L AH0 +TECO T IY1 K OW0 +TECOGEN T EH1 K OW0 G AH0 N +TECOGEN(1) T EH1 K OW0 JH EH0 N +TECOS T IY1 K OW0 S +TECTONIC T EH0 K T AA1 N IH0 K +TECTONICS T EH0 K T AA1 N IH0 K S +TECUMSEH T AH0 K AH1 M S AH0 +TED T EH1 D +TED'S T EH1 D Z +TEDDER T EH1 D ER0 +TEDDIE T EH1 D IY0 +TEDDY T EH1 D IY0 +TEDDY'S T EH1 D IY0 Z +TEDESCHI T EH0 D EH1 S K IY0 +TEDESCO T EH0 D EH1 S K OW0 +TEDESCO'S T EH0 D EH1 S K OW0 Z +TEDFORD T EH1 D F ER0 D +TEDIOUS T IY1 D IY0 AH0 S +TEDIOUSLY T IY1 D IY0 AH0 S L IY0 +TEDIUM T IY1 D IY0 AH0 M +TEDMAN T EH1 D M AH0 N +TEDMOND T EH1 D M AH0 N D +TEDMUND T EH1 D M AH0 N D +TEDRICK T EH1 D R IH0 K +TEDROW T EH1 D R OW2 +TEE T IY1 +TEED T IY1 D +TEEGARDEN T IY1 G AA2 R D AH0 N +TEEGARDIN T IY0 G AA1 R D IH0 N +TEEHAN T IY1 AH0 N +TEEING T IY1 IH0 NG +TEEL T IY1 L +TEELE T IY1 L +TEELEY T IY1 L IY0 +TEELING T IY1 L IH0 NG +TEEM T IY1 M +TEEMING T IY1 M IH0 NG +TEEMS T IY1 M Z +TEEN T IY1 N +TEENA T IY1 N AH0 +TEENAGE T IY1 N EY2 JH +TEENAGED T IY1 N EY2 JH D +TEENAGER T IY1 N EY2 JH ER0 +TEENAGER'S T IY1 N EY2 JH ER0 Z +TEENAGERS T IY1 N EY2 JH ER0 Z +TEENIE T IY1 N IY0 +TEENS T IY1 N Z +TEENSY T IY1 N S IY0 +TEENY T IY1 N IY0 +TEEPLE T IY1 P AH0 L +TEEPLES T IY1 P AH0 L Z +TEER T IH1 R +TEES T IY1 Z +TEET T IY1 T +TEETER T IY1 T ER0 +TEETER'S T IY1 T ER0 Z +TEETERED T IY1 T ER0 D +TEETERING T IY1 T ER0 IH0 NG +TEETERS T IY1 T ER0 Z +TEETH T IY1 TH +TEETHE T IY1 DH +TEETHING T IY1 DH IH0 NG +TEETOTALER T IY2 T OW2 T EY1 L ER0 +TEETS T IY1 T S +TEFFETELLER T EH1 F IH0 T EH2 L ER0 +TEFFT T EH1 F T +TEFLON T EH1 F L AH0 N +TEFRA T EH1 F R AH0 +TEGELER T EH1 G AH0 L ER0 +TEGETHOFF T EH1 G IH0 T AO2 F +TEGGE T EH1 G +TEGTMEIER T EH1 T M AY0 ER0 +TEGTMEYER T EH1 T M AY0 ER0 +TEGUCIGALPA T EH0 G UW0 S IY0 G AE1 L P AH0 +TEGUCIGALPA(1) T EH0 G UW0 CH IY0 G AA1 L P AH0 +TEHAN T EY1 AH0 N +TEHERAN T EH2 HH ER0 AA1 N +TEHERAN'S T EH2 HH ER0 AA1 N Z +TEHERANI T EH2 HH ER0 AA1 N IY0 +TEHERANI'S T EH2 HH ER0 AA1 N IY0 Z +TEHERANIS T EH2 HH ER0 AA1 N IY0 Z +TEHERANS T EH2 HH ER0 AA1 N Z +TEHRAN T EY2 R AA1 N +TEHRAN'S T EY2 R AA1 N Z +TEHRANI T EY2 R AA1 N IY0 +TEHRANI'S T EY2 R AA1 N IY0 Z +TEHRANIS T EY2 R AA1 N IY0 Z +TEHRANS T EY2 R AA1 N Z +TEICH T AY1 K +TEICHER T AY1 K ER0 +TEICHERT T AY1 K ER0 T +TEICHMAN T AY1 K M AH0 N +TEICHMANN T AY1 K M AH0 N +TEICHOLZ T AY1 K HH AO2 L T S +TEIG T IY1 G +TEIGE T AY1 JH +TEIGEN T AY1 G AH0 N +TEIKOKU T EY2 K OW1 K UW2 +TEITEL T AY1 T AH0 L +TEITELBAUM T AY1 T AH0 L B AW0 M +TEITELL T AY1 T EH2 L +TEIXEIRA T AH0 K S EH1 R AH0 +TEJADA T EY0 Y AA1 D AH0 +TEJAN T EY0 JH AH0 N +TEJANO T EY0 Y AA1 N OW0 +TEJAS T IY1 JH AH0 S +TEJEDA T EY0 Y EY1 D AH0 +TEJERA T EY0 IH1 R AH0 +TEJON T EH1 JH AA0 N +TEK T EH1 K +TEKNOWLEDGE T EH2 K N AA1 L EH0 JH +TEKTRONIX T EH2 K T R AA1 N IH0 K S +TEL T EH1 L +TELACTION T EH0 L AE1 K SH AH0 N +TELAMON T EH1 L AH0 M AH0 N +TELANDER T IY1 L AE0 N D ER0 +TELANDER(1) T IH0 L AE1 N D ER0 +TELCO T EH1 L K OW0 +TELE T EH1 L IY0 +TELE(1) T EH1 L AH0 +TELECABLE T EH1 L AH0 K EY2 B AH0 L +TELECARD T EH1 L AH0 K AA2 R D +TELECAST T EH1 L AH0 K AE2 S T +TELECASTS T EH1 L AH0 K AE2 S T S +TELECHARGE T EH1 L AH0 CH AA1 R JH +TELECHECK T EH1 L AH0 CH EH2 K +TELECOM T EH1 L AH0 K AA0 M +TELECOM'S T EH1 L AH0 K AA0 M Z +TELECOMMUNICATION T EH2 L AH0 K AH0 M Y UW2 N IH0 K EY1 SH AH0 N +TELECOMMUNICATIONS T EH2 L AH0 K AH0 M Y UW2 N AH0 K EY1 SH AH0 N Z +TELECOMMUNICATIONS' T EH2 L AH0 K AH0 M Y UW2 N AH0 K EY1 SH AH0 N Z +TELECOMMUTE T EH1 L AH0 K AH0 M Y UW2 T +TELECOMMUTER T EH1 L AH0 K AH0 M Y UW2 T ER0 +TELECOMMUTER'S T EH1 L AH0 K AH0 M Y UW2 T ER0 Z +TELECOMMUTERS T EH1 L AH0 K AH0 M Y UW2 T ER0 Z +TELECOMMUTING T EH0 L AH0 K AH0 M Y UW1 T IH0 NG +TELECOMS T EH1 L AH0 K AA0 M Z +TELECONFERENCE T EH2 L AH0 K AA1 N F R AH0 N S +TELECONFERENCING T EH2 L AH0 K AA1 N F R AH0 N S IH0 NG +TELECONNECT T EH2 L AH0 K AH0 N EH1 K T +TELECRAFTER T EH1 L AH0 K R AE2 F T ER0 +TELECREDIT T EH1 L AH0 K R EH2 D IH0 T +TELECTRON T EH1 L AH0 K T R AA0 N +TELECTRONIC T EH2 L AH0 K T R AA1 N IH0 K +TELECTRONICS T EH2 L AH0 K T R AA1 N IH0 K S +TELEDESIC T EH2 L AH0 D EH1 S IH0 K +TELEDYNE T EH1 L AH0 D AY2 N +TELEDYNE'S T EH1 L AH0 D AY2 N Z +TELEFLEX T EH1 L AH0 F L EH2 K S +TELEFON T EH1 L AH0 F AA2 N +TELEFONICA T EH2 L AH0 F AA1 N IH0 K AH0 +TELEFONOS T EH2 L EH0 F OW1 N OW0 S +TELEFUNKEN T EH2 L AH0 F AH1 NG K AH0 N +TELEGENIC T EH2 L AH0 JH EH1 N IH0 K +TELEGLOBE T EH1 L AH0 G L OW2 B +TELEGRAM T EH1 L AH0 G R AE2 M +TELEGRAMS T EH1 L AH0 G R AE2 M Z +TELEGRAPH T EH1 L AH0 G R AE2 F +TELEGRAPH'S T EH1 L AH0 G R AE2 F S +TELEGRAPHED T EH1 L AH0 G R AE2 F T +TELEKOM T EH1 L AH0 K AA0 M +TELEKOM'S T EH1 L AH0 K AA0 M Z +TELEMACHO T EH1 L AH0 M AA2 CH OW0 +TELEMANAGEMENT T EH1 L AH0 M AE2 N IH0 JH M AH0 N T +TELEMARKET T EH2 L AH0 M AA1 R K IH0 T +TELEMARKETER T EH2 L AH0 M AA1 R K IH0 T ER0 +TELEMARKETERS T EH2 L AH0 M AA1 R K IH0 T ER0 Z +TELEMARKETING T EH2 L AH0 M AA1 R K AH0 T IH0 NG +TELEMATIC T EH2 L AH0 M AE1 T IH0 K +TELEMATICS T EH2 L AH0 M AE1 T IH0 K S +TELEMECANIQUE T EH2 L AH0 M AH0 K AE1 N IH0 K +TELEMEDIA T EH2 L AH0 M IY1 D IY0 AH0 +TELEMEDICINE T EH2 L IH0 M EH1 D IH0 S AH0 N +TELEMETRY T AH0 L EH1 M AH0 T R IY0 +TELEMUNDO T EH2 L AH0 M UW1 N D OW0 +TELENET T EH1 L AH0 N EH2 T +TELEOLOGICAL T IY2 L IY0 AH0 L AO1 JH IH0 K AH0 L +TELEOLOGY T IY1 L IY0 AO2 L AH0 JH IY2 +TELEPATH T EH2 L AH0 P AE1 TH +TELEPATHIC T EH2 L AH0 P AE1 TH AH0 K +TELEPATHY T AH0 L EH1 P AH0 TH IY0 +TELEPHONE T EH1 L AH0 F OW2 N +TELEPHONE'S T EH1 L AH0 F OW2 N Z +TELEPHONED T EH1 L AH0 F OW2 N D +TELEPHONES T EH1 L AH0 F OW2 N Z +TELEPHONIC T EH2 L AH0 F AA1 N IH0 K +TELEPHONICS T EH2 L AH0 F AA1 N IH0 K S +TELEPHONING T EH1 L AH0 F OW2 N IH0 NG +TELEPHONIQUES T EH2 L AH0 F AA0 N IY1 K S +TELEPHONY T EH1 L AH0 F OW2 N IY0 +TELEPHOTO T EH1 L AH0 F OW2 T OW0 +TELEPICTURE T EH1 L AH0 P IH1 K CH ER0 +TELEPICTURES T EH1 L AH0 P IH1 K CH ER0 Z +TELEPORT T EH1 L AH0 P AO1 R T +TELEPORT'S T EH1 L AH0 P AO1 R T S +TELEPROBE T EH1 L AH0 P R OW1 B +TELEPROMPTER T EH1 L AH0 P R AA2 M P T ER0 +TELEQUEST T EH1 L AH0 K W EH1 S T +TELERATE T EH1 L ER0 EY1 T +TELESAT T EH1 L AH0 S AE0 T +TELESCIENCE T EH1 L AH0 S AY2 AH0 N S +TELESCIENCES T EH1 L AH0 S AY2 AH0 N S IH0 Z +TELESCO T EH0 L EH1 S K OW0 +TELESCOPE T EH1 L AH0 S K OW2 P +TELESCOPE'S T EH1 L AH0 S K OW2 P S +TELESCOPES T EH1 L AH0 S K OW2 P S +TELESCOPIC T EH2 L AH0 S K AO1 P IH0 K +TELESCRIPT T EH1 L AH0 S K R IH2 P T +TELESIS T EH1 L AH0 S IH0 S +TELESIS' T EH1 L AH0 S IH2 S +TELESIS'S T EH1 L AH0 S IH0 S IH0 Z +TELESPHERE T EH1 L AH0 S F IH2 R +TELESTRATOR T EH1 L AH0 S T R EY2 T ER0 +TELESYSTEM T EH1 L AH0 S IH2 S T AH0 M +TELETEXT T EH1 L AH0 T EH1 K S T +TELETHON T EH1 L AH0 TH AA0 N +TELETRON T EH1 L AH0 T R AA2 N +TELETTRA T EH1 L EH0 T R AH0 +TELETYPE T EH1 L AH0 T AY2 P +TELETYPES T EH1 L AH0 T AY2 P S +TELEVANGELIST T EH2 L AH0 V AE1 N JH AH0 L AH0 S T +TELEVANGELISTS T EH2 L AH0 V AE1 N JH AH0 L AH0 S T S +TELEVIDEO T EH2 L AH0 V IH1 D IY0 OW0 +TELEVISA T EH1 L AH0 V IY1 Z AH0 +TELEVISA'S T EH2 L AH0 V IY1 Z AH0 Z +TELEVISE T EH1 L AH0 V AY2 Z +TELEVISED T EH1 L AH0 V AY2 Z D +TELEVISING T EH1 L AH0 V AY2 Z IH0 NG +TELEVISION T EH1 L AH0 V IH2 ZH AH0 N +TELEVISION'S T EH1 L AH0 V IH2 ZH AH0 N Z +TELEVISIONS T EH1 L AH0 V IH2 ZH AH0 N Z +TELEVISON T EH1 L IH0 V IH0 ZH AH0 N +TELEWEST T EH1 L AH0 W EH1 S T +TELEX T EH1 L EH2 K S +TELEX'S T EH1 L EH2 K S IH0 Z +TELEXED T EH1 L EH2 K S T +TELEXES T EH1 L EH2 K S IH0 S +TELFAIR T EH1 L F EH2 R +TELFER T EH1 L F ER0 +TELFOR T EH1 L F ER0 +TELFORD T EH1 L F ER0 D +TELFOUR T EH1 L F ER0 +TELIT T EH1 L IH2 T +TELL T EH1 L +TELLABS T EH1 L AE2 B Z +TELLEFSEN T EH1 L IH0 F S AH0 N +TELLEP T EH1 L AH0 P +TELLER T EH1 L ER0 +TELLER'S T EH1 L ER0 Z +TELLERS T EH1 L ER0 Z +TELLES T EH1 L Z +TELLEZ T EY0 L EH1 Z +TELLIER T EH1 L IY0 ER0 +TELLIN' T EH1 L IH0 N +TELLING T EH1 L IH0 NG +TELLINGLY T EH1 L IH0 NG L IY0 +TELLIS T EH1 L IH0 S +TELLO T EH1 L OW0 +TELLS T EH1 L Z +TELLTALE T EH1 L T EY2 L +TELLTALES T EH1 L T EY2 L Z +TELLURIDE T EH1 L Y ER0 AY2 D +TELLURIDES T EH1 L Y ER0 AY2 D Z +TELLURIUM T EH0 L UH1 R IY0 AH0 M +TELLY T EH1 L IY0 +TELMEX T EH1 L M EH2 K S +TELMEX'S T EH1 L M EH2 K S IH0 Z +TELOMERASE T AH0 L OW1 M ER0 EY2 Z +TELOMERE T EH1 L AH0 M IY0 R +TELOMERES T EH1 L AH0 M IY0 R Z +TELOS T EH1 L OW0 S +TELSOURCE T EH1 L S AO2 R S +TELSTAR T EH1 L S T AA2 R +TELSTRA T EH1 L S T R AH0 +TELTSCHIK T EH1 L CH IH0 K +TELUGU T EH1 L UH0 G UW0 +TELUSTRATOR T EH1 L AH0 S T R EY2 T ER0 +TELUSTRATOR(1) T EH1 L Y AH0 S T R EY2 T ER0 +TELXON T EH1 L Z AA0 N +TELXON'S T EH1 L Z AH0 N Z +TELZROW T EH1 L Z R OW0 +TEL_AVIV T EH1 L AA0 V IY1 V +TEMBLOR T EH1 M B L ER0 +TEMBLORS T EH1 M B L ER0 Z +TEMCO T EH1 M K OW0 +TEMECULA T AH0 M EH1 K Y AH0 L AH0 +TEMERITY T AH0 M EH1 R AH0 T IY0 +TEMERLIN T EH1 M ER0 L IH0 N +TEMEROUS T EH1 M ER0 AH0 S +TEMKIN T EH1 M K IH0 N +TEMME T EH1 M +TEMP T EH1 M P +TEMPE T EH1 M P IY0 +TEMPEL T EH1 M P AH0 L +TEMPELSMAN T EH1 M P AH0 L Z M AH0 N +TEMPER T EH1 M P ER0 +TEMPERA T EH1 M P ER0 AH0 +TEMPERAMENT T EH1 M P R AH0 M AH0 N T +TEMPERAMENT(1) T EH1 M P ER0 M AH0 N T +TEMPERAMENTAL T EH2 M P R AH0 M EH1 N T AH0 L +TEMPERAMENTAL(1) T EH2 M P ER0 M EH1 N T AH0 L +TEMPERAMENTALLY T EH2 M P R AH0 M EH1 N T AH0 L IY0 +TEMPERAMENTALLY(1) T EH2 M P ER0 M EH1 N T AH0 L IY0 +TEMPERAMENTALLY(2) T EH2 M P R AH0 M EH1 N AH0 L IY0 +TEMPERAMENTALLY(3) T EH2 M P ER0 M EH1 N AH0 L IY0 +TEMPERAMENTS T EH1 M P R AH0 M AH0 N T S +TEMPERAMENTS(1) T EH1 M P ER0 M AH0 N T S +TEMPERANCE T EH1 M P ER0 AH0 N S +TEMPERANCE(1) T EH1 M P R AH0 N S +TEMPERATE T EH1 M P R AH0 T +TEMPERATE(1) T EH1 M P ER0 AH0 T +TEMPERATURE T EH1 M P R AH0 CH ER0 +TEMPERATURE(1) T EH1 M P ER0 AH0 CH ER0 +TEMPERATURES T EH1 M P R AH0 CH ER0 Z +TEMPERATURES(1) T EH1 M P ER0 AH0 CH ER0 Z +TEMPERED T EH1 M P ER0 D +TEMPERING T EH1 M P ER0 IH0 NG 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M P S +TEMPT T EH1 M P T +TEMPTATION T EH0 M T EY1 SH AH0 N +TEMPTATIONS T EH0 M T EY1 SH AH0 N Z +TEMPTED T EH1 M P T IH0 D +TEMPTING T EH1 M P T IH0 NG +TEMPTRESS T EH1 M P T R IH0 S +TEMPTS T EH1 M P T S +TEN T EH1 N +TEN'S T EH1 N Z +TENA T EH1 N AH0 +TENABLE T EH1 N AH0 B AH0 L +TENACIOUS T AH0 N EY1 SH AH0 S +TENACIOUSLY T AH0 N EY1 SH AH0 S L IY0 +TENACITY T AH0 N AE1 S IH0 T IY0 +TENAGLIA T EH0 N AA1 G L IY0 AH0 +TENANCY T EH1 N AH0 N S IY0 +TENANT T EH1 N AH0 N T +TENANT'S T EH1 N AH0 N T S +TENANTS T EH1 N AH0 N T S +TENANTS' T EH1 N AH0 N T S +TENBRINK T EH1 N B R IH2 NG K +TENCH T EH1 N CH +TENCZA T EH1 N CH AH0 +TEND T EH1 N D +TENDED T EH1 N D IH0 D +TENDENCIES T EH1 N D AH0 N S IY0 Z +TENDENCY T EH1 N D AH0 N S IY0 +TENDENTIOUS T EH2 N D EH1 N SH AH0 S +TENDER T EH1 N D ER0 +TENDERED T EH1 N D ER0 D +TENDERING T EH1 N D ER0 IH0 NG +TENDERLOIN T EH1 N D ER0 L OY2 N +TENDERLY T EH1 N D ER0 L IY0 +TENDERNESS T EH1 N D ER0 N AH0 S +TENDERS T EH1 N D ER0 Z +TENDING T EH1 N D IH0 NG +TENDLER T EH1 N D L ER0 +TENDON T EH1 N D AH0 N +TENDONS T EH1 N D AH0 N Z +TENDS T EH1 N D Z +TENEBROUS T EH1 N AH0 B R AH0 S +TENEMENT T EH1 N AH0 M AH0 N T +TENEMENTS T EH1 N AH0 M AH0 N T S +TENENBAUM T EH1 N AH0 N B AW2 M +TENER T EH1 N ER0 +TENERA T EH2 N EH1 R AH0 +TENET T EH1 N AH0 T +TENETS T EH1 N AH0 T S +TENEYCK T EH1 N IY0 K +TENFOLD T EH1 N F OW2 L D +TENG T EH1 NG +TENG-WEN T EH1 NG W EH1 N +TENGELMANN T EH1 NG G AH0 L M AH0 N +TENGIZ T EH1 NG G IH0 Z +TENGLEMANN T EH1 NG G AH0 L M AH0 N +TENN T EH1 N +TENNANT T EH1 N AH0 N T +TENNCARE T EH1 N K EH2 R +TENNCARE'S T EH1 N K EH2 R Z +TENNECO T EH1 N AH0 K OW0 +TENNECO'S T EH1 N AH0 K OW0 Z +TENNELL T EH1 N AH0 L +TENNENBAUM T EH1 N AH0 N B AW2 M +TENNENT T EH1 N AH0 N T +TENNER T EH1 N ER0 +TENNESSEAN T EH2 N IH0 S IY1 AH0 N +TENNESSEANS T EH2 N IH0 S IY1 AH0 N Z +TENNESSEE T EH2 N AH0 S IY1 +TENNESSEE'S T EH2 N AH0 S IY1 Z +TENNEY T EH1 N IY0 +TENNIS T EH1 N AH0 S +TENNIS(1) T EH1 N IH0 S +TENNIS'S T EH1 N AH0 S IH0 Z +TENNISON T EH1 N IH0 S AH0 N +TENNY T EH1 N IY0 +TENNYSON T EH1 N IH0 S AH0 N +TENOR T EH1 N ER0 +TENORE T EH1 N AO2 R +TENORIO T EH0 N AO1 R IY0 OW0 +TENORS T EH1 N ER0 Z +TENPAS T EH1 N P AH0 Z +TENPENNY T EH1 N P EH2 N IY0 +TENRECS T EH1 N R EH2 K S +TENS T EH1 N Z +TENSE T EH1 N S +TENSELY T EH1 N S L IY0 +TENSILE T EH1 N S AH0 L +TENSIOMETER T EH2 N S IY0 AA1 M IH0 T ER0 +TENSION T EH1 N SH AH0 N +TENSIONS T EH1 N CH AH0 N Z +TENSOR T EH1 N S ER0 +TENSORS T EH1 N S ER0 Z +TENT T EH1 N T +TENTACLE T EH1 N T AH0 K AH0 L +TENTACLES T EH1 N T AH0 K AH0 L Z +TENTATIVE T EH1 N T AH0 T IH0 V +TENTATIVELY T EH1 N T AH0 T IH0 V L IY0 +TENTH T EH1 N TH +TENTHS T EH1 N TH S +TENTING T EH1 N T IH0 NG +TENTS T EH1 N T S +TENUOUS T EH1 N Y AH0 W AH0 S +TENURE T EH1 N Y ER0 +TENURED T EH1 N Y ER0 D +TENURES T EH1 N Y ER0 Z +TENUTA T EH0 N UW1 T AH0 +TENZER T EH1 N Z ER0 +TEO T EY1 OW0 +TEODORO T IY2 OW0 D AO1 R OW0 +TEPE T IY1 P +TEPER T IY1 P ER0 +TEPID T EH1 P IH0 D +TEPLY T EH1 P L IY0 +TEPOZTLAN T IH0 P AO1 S T L AH0 N +TEPPER T EH1 P ER0 +TEPPERMAN T EH1 P ER0 M AH0 N +TEQUILA T AH0 K IY1 L AH0 +TEQUILIU T AH0 K IY1 L Y UW0 +TER T ER1 +TERABYTE T EH2 R AH0 B AY1 T +TERABYTES T EH2 R AH0 B AY1 T S +TERADA T ER0 AA1 D AH0 +TERADATA T EH2 R AH0 D AA1 T AH0 +TERADYNE T EH1 R AH0 D AY2 N +TERADYNE'S T EH1 R AH0 D AY2 N Z +TERAN T EH1 R AH0 N +TERASAWA T EH2 R AH0 S AA1 W AH0 +TERBUSH T ER1 B AH0 SH +TERBUSH(1) T ER1 B UH0 SH +TERCEL T ER1 S AH0 L +TERCERO T ER0 CH EH1 R OW0 +TERENCE T EH1 R AH0 N S +TERENCE'S T EH1 R AH0 N S IH0 Z +TERENTIA T ER0 EH1 N SH AH0 +TERESA T ER0 IY1 S AH0 +TERESA(1) T ER0 EY1 S AH0 +TERESA'S T ER0 IY1 S AH0 Z +TERESA'S(1) T ER0 EY1 S AH0 Z +TERESE T EH1 R IY0 Z +TERESI T ER0 EH1 S IY0 +TERESITA T ER0 EH0 S IY1 T AH0 +TERESSA T ER0 EH1 S AH0 +TEREX T EH1 R AH0 K S +TEREZA T ER0 EY1 Z AH0 +TEREZA'S T ER0 EY1 Z AH0 Z +TERHAAR T ER1 HH AA0 R +TERHORST T ER1 HH AO0 R S T +TERHUNE T ER0 HH Y UW1 N +TERI T EH1 R IY0 +TERIYAKI T EH2 R IH0 Y AA1 K IY0 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AH0 N +TILTS T IH1 L T S +TIM T IH1 M +TIM'S T IH1 M Z +TIMAN T AY1 M AH0 N +TIMBER T IH1 M B ER0 +TIMBERLAKE T IH1 M B ER0 L EY2 K +TIMBERLAND T IH1 M B ER0 L AE2 N D +TIMBERLANDS T IH1 M B ER0 L AE2 N D Z +TIMBERLINE T IH1 M B ER0 L AY2 N +TIMBERMAN T IH1 M B ER0 M AH0 N +TIMBERS T IH1 M B ER0 Z +TIMBLIN T IH1 M B L IH0 N +TIMBRE T IH1 M B ER0 +TIMBROOK T IH1 M B R UH2 K +TIMBS T IH1 M Z +TIMBUKTU T IH2 M B AH0 K T UW1 +TIME T AY1 M +TIME'S T AY1 M Z +TIME-OUT T AY1 M AW2 T +TIMED T AY1 M D +TIMEFRAME T AY1 M F R EY2 M +TIMELESS T AY1 M L AH0 S +TIMELINE T AY1 M L AY0 N +TIMELINES T AY1 M L AY0 N Z +TIMELINESS T AY1 M L IY0 N AH0 S +TIMELY T AY1 M L IY0 +TIMEOUT T AY1 M AW2 T +TIMEPIECE T AY1 M P IY2 S +TIMEPLEX T AY1 M P L EH2 K S +TIMER T AY1 M ER0 +TIMERS T AY1 M ER0 Z +TIMES T AY1 M Z +TIMES' T AY1 M Z +TIMES'S T AY1 M Z IH0 Z +TIMESHARE T AY1 M SH EH2 R +TIMETABLE T AY1 M T EY2 B AH0 L +TIMETABLES T AY1 M T EY2 B AH0 L Z +TIMEWISE T AY1 M W AY2 Z +TIMEX T AY1 M EH0 K S +TIMID T IH1 M IH0 D +TIMIDITY T AH0 M IH1 D AH0 T IY0 +TIMIDLY T IH1 M AH0 D L IY0 +TIMING T AY1 M IH0 NG +TIMISOARA T IH2 M AH0 S OW0 AA1 R AH0 +TIMISOARA(1) T IH2 M AH0 S W AA1 R AH0 +TIMKEN T IH1 M K AH0 N +TIMKO T IH1 M K OW0 +TIMLEN T IH1 M L AH0 N +TIMLIN T IH1 M L IH0 N +TIMM T IH1 M +TIMME T IH1 M +TIMMENY T IH1 M AH0 N IY0 +TIMMER T IH1 M ER0 +TIMMERMAN T IH1 M ER0 M AH0 N +TIMMERMANN T IH1 M ER0 M AH0 N +TIMMERS T IH1 M ER0 Z +TIMMIE T IH1 M IY0 +TIMMINS T IH1 M IH0 N Z +TIMMONS T IH1 M AH0 N Z +TIMMS T IH1 M Z +TIMMY T IH1 M IY0 +TIMON T AY1 M AH0 N +TIMONEY T IH1 M AH0 N IY0 +TIMOR T IY0 M AO1 R +TIMOR'S T IY0 M AO1 R Z +TIMORESE T IY2 M AO0 R IY1 Z +TIMOROUS T IH1 M ER0 AH0 S +TIMOTHEA T IH0 M AH0 DH IY1 AH0 +TIMOTHY T IH1 M AH0 TH IY0 +TIMPANI T IH1 M P AH0 N IY2 +TIMPE T IH1 M P +TIMPONE T IY0 M P OW1 N IY0 +TIMPSON T IH1 M P S AH0 N +TIMS T IH1 M Z +TIMSON T IH1 M S AH0 N +TIMUR T IH1 M ER0 +TIMURIAN T IH0 M UH1 R IY0 AH0 N +TIN T IH1 N +TINA T IY1 N AH0 +TINA'S T IY1 N AH0 Z 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+TORTS T AO1 R T S +TORTUOUS T AO1 R CH AH0 W AH0 S +TORTURE T AO1 R CH ER0 +TORTURED T AO1 R CH ER0 D +TORTURER T AO1 R CH ER0 ER0 +TORTURERS T AO1 R CH ER0 ER0 Z +TORTURES T AO1 R CH ER0 Z +TORTURING T AO1 R CH ER0 IH0 NG +TORTUROUS T AO1 R CH UW2 AH0 S +TORU T AO1 R UW0 +TORUMI T AO2 R UW1 M IY0 +TORUMI'S T AO2 R UW1 M IY0 Z +TORY T AO1 R IY0 +TOSCA T AO1 S K AH0 +TOSCANINI T AO2 S K AH0 N IY1 N IY0 +TOSCANINI'S T AH2 S K AH0 N IY1 N IY0 Z +TOSCANO T OW0 S K AA1 N OW0 +TOSCH T AO1 SH +TOSCO T AO1 S K OW0 +TOSH T AA1 SH +TOSHIBA T OW0 SH IY1 B AH0 +TOSHIBA'S T OW0 SH IY1 B AH0 Z +TOSHIHARU T OW2 SH IH0 HH AA1 R UW0 +TOSHIHIKO T OW2 SH IH0 HH IY1 K OW0 +TOSHIKI T OW0 SH IY1 K IY0 +TOSHIMITSU T OW0 SH IY0 M IY1 T S UW0 +TOSHIO T OW0 SH IY1 OW0 +TOSHIYUKI T OW2 SH IH0 Y UW1 K IY0 +TOSI T OW1 S IY0 +TOSO T OW1 S OW0 +TOSS T AO1 S +TOSSED T AO1 S T +TOSSES T AO1 S IH0 Z +TOSSING T AO1 S IH0 NG +TOSTADO T OW0 S T AA1 D OW0 +TOSTE T OW1 S T +TOSTENSON T AA1 S T IH0 N S AH0 N +TOSTI T AO1 S T IY0 +TOSTO T OW1 S T OW0 +TOT T AA1 T +TOTA T OW1 T AH0 +TOTAL T OW1 T AH0 L +TOTAL'S T OW1 T AH0 L Z +TOTALED T OW1 T AH0 L D +TOTALING T OW1 T AH0 L IH0 NG +TOTALITARIAN T OW2 T AE2 L IH0 T EH1 R IY0 AH0 N +TOTALITARIANISM T OW2 T AE2 L AH0 T EH1 R IY0 AH0 N IH2 Z AH0 M +TOTALITARIANS T OW0 T AE2 L AH0 T EH1 R IY0 AH0 N Z +TOTALITY T OW0 T AE1 L AH0 T IY0 +TOTALLED T OW1 T AH0 L D +TOTALLING T OW1 T AH0 L IH0 NG +TOTALLY T OW1 T AH0 L IY0 +TOTALS T OW1 T AH0 L Z +TOTARO T OW0 T AA1 R OW0 +TOTE T OW1 T +TOTED T OW1 T IH0 D +TOTEM T OW1 T AH0 M +TOTEMS T OW1 T AH0 M Z +TOTENBERG T OW1 T AH0 N B ER0 G +TOTES T OW1 T S +TOTH T AA1 TH +TOTHEROW T AH1 DH ER0 OW0 +TOTI T OW1 T IY0 +TOTING T OW1 T IH0 NG +TOTINO'S T AH0 T IY1 N OW0 Z +TOTMAN T AA1 T M AH0 N +TOTO T OW1 T OW0 +TOTS T AA1 T S +TOTTEN T AA1 T AH0 N +TOTTENBERG T AA1 T AH0 N B ER0 G +TOTTENHAM T AA1 T AH0 N AH0 M +TOTTENHAM(1) T AA1 T AH0 N HH AE2 M +TOTTER T AA1 T ER0 +TOTTERING T AA1 T ER0 IH0 NG +TOTTON T AA1 T AH0 N +TOTTY T AA1 T IY0 +TOTZKE T AA1 T S K IY0 +TOUAREG T UW1 ER0 AH0 G +TOUCH T AH1 CH +TOUCHABLE T AH1 CH AH0 B AH0 L +TOUCHDOWN T AH1 CH D AW2 N +TOUCHDOWNS T AH1 CH D AW2 N Z +TOUCHE T UW1 SH +TOUCHE(1) T UW1 SH EY2 +TOUCHED T AH1 CH T +TOUCHES T AH1 CH AH0 Z +TOUCHES(1) T AH1 CH IH0 Z +TOUCHET T UW0 SH EH1 T +TOUCHETTE T UW2 SH EH1 T +TOUCHING T AH1 CH IH0 NG +TOUCHSTONE T AH1 CH S T OW2 N +TOUCHTON T AH1 CH T AH0 N +TOUCHY T AH1 CH IY0 +TOUFEXIS T UW2 F EH1 K S IH0 S +TOUGALOO T UW1 G AH0 L UW2 +TOUGAS T AH1 G AH0 Z +TOUGH T AH1 F +TOUGHED T AH1 F T +TOUGHEN T AH1 F AH0 N +TOUGHENED T AH1 F AH0 N D +TOUGHENING T AH1 F AH0 N IH0 NG +TOUGHENS T AH1 F AH0 N Z +TOUGHER T AH1 F ER0 +TOUGHEST T AH1 F AH0 S T +TOUGHIE T AH1 F IY0 +TOUGHNESS T AH1 F N AH0 S +TOUGHS T AH1 F S +TOUHEY T AH1 HH IY0 +TOULOUSE T UW0 L UW1 Z +TOUPEE T UW2 P EY1 +TOUPIN T UW1 P IH0 N +TOUPS T UW1 P S +TOUR T UH1 R +TOUR'S T UH1 R Z +TOURANGEAU T UH1 R EY0 NG G OW0 +TOURED T UH1 R D +TOURETTE T ER0 EH1 T +TOURETTE'S T ER0 EH1 T S +TOURETZKY T ER0 EH1 T S K IY0 +TOURIGNY T UH1 R AY0 N IY0 +TOURING T UH1 R IH0 NG +TOURISM T UH1 R IH2 Z AH0 M +TOURIST T UH1 R AH0 S T +TOURIST(1) T UH1 R IH0 S T +TOURISTS T UH1 R AH0 S T S +TOURISTS(1) T UH1 R IH0 S T S +TOURMALINE T UH1 R M AH0 L IY2 N +TOURNAMENT T UH1 R N AH0 M AH0 N T +TOURNAMENT'S T UH1 R N AH0 M AH0 N T S +TOURNAMENTS T ER1 N AH0 M AH0 N T S +TOURNEDOS T UH1 R N AH0 D OW0 +TOURNEY T ER1 N IY0 +TOURNEYS T UW1 R N IY0 Z +TOURNIQUET T ER1 N IH2 K IH0 T +TOURNQUIST T UW1 R N K W IH0 S T +TOURO T UW1 R OW0 +TOURS T UH1 R Z +TOURS(1) T AO1 R Z +TOURTELOT T UH1 R T AH0 L AA0 T +TOURTELOT(1) T UH2 R T AH0 L OW1 +TOURVILLE T UH1 R V IH0 L +TOUSEY T AH1 S IY0 +TOUSIGNANT T UW1 S IH0 G N AH0 N T +TOUSLEY T AH1 S L IY0 +TOUSSAINT T UW0 S AE1 N +TOUSSAUD T UW1 S AA2 D +TOUSSAUD'S T UW1 S AA2 D Z +TOUSSIE T UW1 S IY0 +TOUT T AW1 T +TOUTANT T UW0 T AO1 N T +TOUTED T AW1 T IH0 D +TOUTING T AW1 T IH0 NG +TOUTS T AW1 T S +TOUVIER T UW2 V IY0 EY1 +TOUVIER'S T UW2 V IY0 EY1 Z +TOV T OW1 V +TOVAR T OW0 V AA1 R +TOVAZ T OW1 V AA2 Z +TOVEY T OW1 V IY0 +TOVIA T OW1 V IY0 AH0 +TOVIA(1) T OW1 V Y AH0 +TOW T OW1 +TOWARD T AH0 W AO1 R D +TOWARD(1) T AO1 R D +TOWARDS T AH0 W AO1 R D Z +TOWARDS(1) T AO1 R D Z +TOWBIN T OW1 B IH2 N +TOWBOAT T OW1 B OW2 T +TOWE T OW1 +TOWED T OW1 D +TOWEL T AW1 AH0 L +TOWEL(1) T AW1 L +TOWELING T AW1 AH0 L IH0 NG +TOWELING(1) T AW1 L IH0 NG +TOWELL T AA1 W EH0 L +TOWELS T AW1 AH0 L Z +TOWELS(1) T AW1 L Z +TOWER T AW1 ER0 +TOWER'S T AW1 ER0 Z +TOWERED T AW1 ER0 D +TOWERING T AW1 ER0 IH0 NG +TOWERING(1) T AW1 R IH0 NG +TOWERS T AW1 ER0 Z +TOWERS' T AW1 ER0 Z +TOWERY T OW0 ER1 IY0 +TOWEY T OW1 IY0 +TOWHEE T OW1 HH IY2 +TOWING T OW1 IH0 NG +TOWLE T AW1 L +TOWLE'S T AW1 L Z +TOWLER T OW1 L ER0 +TOWLES T OW1 AH0 L Z +TOWN T AW1 N +TOWN'S T AW1 N Z +TOWNE T AW1 N +TOWNER T AW1 N ER0 +TOWNERS T AW1 N ER0 Z +TOWNES T AW1 N Z +TOWNHOUSE T AW1 N HH AW2 S +TOWNHOUSES T AW1 N HH AW2 S IH0 Z +TOWNIE T AW1 N IY0 +TOWNLEY T AW1 N L IY0 +TOWNS T AW1 N Z +TOWNSEL T AW1 N S AH0 L +TOWNSELL T AW1 N S AH0 L +TOWNSEND T AW1 N Z AH0 N D +TOWNSEND'S T AW1 N Z AH0 N D Z +TOWNSFOLK T AW1 N Z F OW2 K +TOWNSHEND T AW1 N SH EH2 N D +TOWNSHIP T AW1 N SH IH0 P +TOWNSHIP'S T AW1 N SH IH2 P S +TOWNSHIPS T AW1 N SH IH0 P S +TOWNSLEY T AW1 N S L IY0 +TOWNSMAN T AW1 N Z M AH0 N +TOWNSON T AW1 N S AH0 N +TOWNSPEOPLE T AW1 N Z P IY2 P AH0 L +TOWRY T AO1 R IY0 +TOWS T OW1 Z +TOWSLEY T OW1 S L IY0 +TOWSON T OW1 S AH0 N +TOXIC T AA1 K S IH0 K +TOXICITY T AA0 K S IH1 S AH0 T IY0 +TOXICOLOGICAL T AA2 K S AH0 K AH0 L AA1 JH IH0 K AH0 L +TOXICOLOGIST T AA2 K S IH0 K AA1 L AH0 JH IH0 S T +TOXICOLOGISTS T AA2 K S IH0 K AA1 L AH0 JH IH0 S T S +TOXICOLOGY T AA2 K S IH0 K AA1 L AH0 JH IY0 +TOXICS T AA1 K S IH0 K S +TOXIN T AA1 K S AH0 N +TOXINS T AA1 K S AH0 N Z +TOY T OY1 +TOY'S T OY1 Z +TOYA T OY1 AH0 +TOYAMA T OW0 Y AA1 M AA2 +TOYBOY T OY1 B OY2 +TOYE T OY1 +TOYED T OY1 D +TOYING T OY1 IH0 NG +TOYKO T OY1 K OW0 +TOYMAKER T OY1 M EY2 K ER0 +TOYMAKERS T OY1 M EY2 K ER0 Z +TOYO T OW1 Y OW0 +TOYOBO T OW0 Y OW1 B OW0 +TOYODA T OW0 Y OW1 D AH0 +TOYOO T OY0 UW1 +TOYOTA T OW0 Y OW1 T AH0 +TOYOTA'S T OW0 Y OW1 T AH0 Z +TOYOTAS T OY2 OW1 T AH0 Z +TOYS T OY1 Z +TOYS' T OY1 Z +TOYSTORE T OY1 S T AO2 R +TOYSTORES T OY1 S T AO2 R Z +TOZER T OW1 Z ER0 +TOZIER T OW1 Z IY0 ER0 +TOZZI T AA1 Z IY0 +TRABER T R EY1 B ER0 +TRABERT T R AE1 B ER0 T +TRABUCCO T R AA0 B UW1 K OW0 +TRABUE T R AA1 B W EH0 +TRAC T R AE1 K +TRACE T R EY1 S +TRACEABLE T R EY1 S AH0 B AH0 L +TRACED T R EY1 S T +TRACER T R EY1 S ER0 +TRACERS T R EY1 S ER0 Z +TRACES T R EY1 S AH0 Z +TRACES(1) T R EY1 S IH0 Z +TRACEY T R EY1 S IY0 +TRACHEA T R EY1 K IY0 AH0 +TRACHEAL T R EY1 K IY0 AH0 L +TRACHEOPHYTE T R EY1 K IY0 AH0 F AY0 T +TRACHEOPHYTES T R EY1 K IY0 AH0 F AY0 T S +TRACHSEL T R AE1 K S AH0 L +TRACHT T R AE1 K T +TRACHTENBERG T R AE1 K T AH0 N B ER0 G +TRACI T R EY1 S IY0 +TRACIE T R EY1 S IY0 +TRACINDA T R AH0 S IH1 N D AH0 +TRACINDA'S T R AH0 S IH1 N D AH0 Z +TRACING T R EY1 S IH0 NG +TRACK T R AE1 K +TRACK'S T R AE1 K S +TRACKAGE T R AE1 K IH0 JH +TRACKBALL T R AE1 K B AO2 L +TRACKBALLS T R AE1 K B AO2 L Z +TRACKED T R AE1 K T +TRACKER T R AE1 K ER0 +TRACKERS T R AE1 K ER0 Z +TRACKING T R AE1 K IH0 NG +TRACKS T R AE1 K S +TRACOR T R EY1 S ER0 +TRACOR(1) T R EH1 K ER0 +TRACOR(2) T R EY1 K AO2 R +TRACOR(3) T R AE1 K AO2 R +TRACT T R AE1 K T +TRACTABLE T R AE1 K T AH0 B AH0 L +TRACTEBEL T R AE1 K T AH0 B AH0 L +TRACTION T R AE1 K SH AH0 N +TRACTOR T R AE1 K T ER0 +TRACTORS T R AE1 K T ER0 Z +TRACTS T R AE1 K T S +TRACY T R EY1 S IY0 +TRACY'S T R EY1 S IY0 Z +TRACZ T R AA1 CH +TRACZYK T R AA1 CH IH2 K +TRADABLE T R EY1 D AH0 B AH0 L +TRADE T R EY1 D +TRADE'S T R EY1 D Z +TRADE-OFF T R EY1 D AO2 F +TRADE-OFFS T R EY1 D AO2 F S +TRADEABLE T R EY1 D AH0 B AH0 L +TRADED T R EY1 D IH0 D +TRADEMARK T R EY1 D M AA2 R K +TRADEMARKED T R EY1 D M AA2 R K T +TRADEMARKS T R EY1 D M AA2 R K S +TRADEOFF T R EY1 D AO2 F +TRADEOFFS T R EY1 D AO2 F S +TRADER T R EY1 D ER0 +TRADER'S T R EY1 D ER0 Z +TRADERS T R EY1 D ER0 Z +TRADERS' T R EY1 D ER0 Z +TRADES T R EY1 D Z +TRADESMEN T R EY1 D Z M AH0 N +TRADING T R EY1 D IH0 NG +TRADING'S T R EY1 D IH0 NG Z +TRADINGS T R EY1 D IH0 NG Z +TRADITION T R AH0 D IH1 SH AH0 N +TRADITIONAL T R AH0 D IH1 SH AH0 N AH0 L +TRADITIONALIST T R AH0 D IH1 SH AH0 N AH0 L IH0 S T +TRADITIONALISTS T R AH0 D IH1 SH N AH0 L AH0 S T S +TRADITIONALLY T R AH0 D IH1 SH AH0 N AH0 L IY0 +TRADITIONALLY(1) T R AH0 D IH1 SH N AH0 L IY0 +TRADITIONS T R AH0 D IH1 SH AH0 N Z +TRAEGER T R EH1 G ER0 +TRAER T R EH1 R +TRAFALGAR T R AH0 F AE1 L G ER0 +TRAFFIC T R AE1 F IH0 K +TRAFFIC'S T R AE1 F IH0 K S +TRAFFICKER T R AE1 F IH0 K ER0 +TRAFFICKERS T R AE1 F IH0 K ER0 Z +TRAFFICKING T R AE1 F IH0 K IH0 NG +TRAFFORD T R AE1 F ER0 D +TRAFICANT T R AE1 F IH0 K AH0 N T +TRAFICANTE T R AA0 F IY0 K AA1 N T IY0 +TRAFICANTS T R AE1 F IH0 K AH0 N T S +TRAFILLIO T R AH0 F IY1 L IY0 OW0 +TRAFILLIO'S T R AH0 F IY1 L IY0 OW0 Z +TRAFTON T R AE1 F T AH0 N +TRAGEDIES T R AE1 JH AH0 D IY0 Z +TRAGEDY T R AE1 JH AH0 D IY0 +TRAGER T R EY1 G ER0 +TRAGESER T R AE1 G IY0 Z ER0 +TRAGIC T R AE1 JH IH0 K +TRAGICALLY T R AE1 JH IH0 K L IY0 +TRAGICOMIC T R AE2 JH IH0 K AA1 M IH0 K +TRAGOS T R AE1 G OW0 Z +TRAHAN T R AE1 HH AH0 N +TRAHERN T R AE1 HH ER0 N +TRAIL T R EY1 L +TRAILBLAZER T R EY1 L B L EY2 Z ER0 +TRAILBLAZERS T R EY1 L B L EY2 Z ER0 Z +TRAILED T R EY1 L D +TRAILER T R EY1 L ER0 +TRAILERS T R EY1 L ER0 Z +TRAILHEAD T R EY1 L HH EH2 D +TRAILING T R EY1 L IH0 NG +TRAILS T R EY1 L Z +TRAILS' T R EY1 L Z +TRAILWAYS T R EY1 L W EY2 Z +TRAILWAYS' T R EY1 L W EY2 Z +TRAIN T R EY1 N +TRAIN'S T R EY1 N Z +TRAINA T R EY1 N AH0 +TRAINABLE T R EY1 N AH0 B AH0 L +TRAINED T R EY1 N D +TRAINEE T R EY1 N IY1 +TRAINEES T R EY1 N IY1 Z +TRAINER T R EY1 N ER0 +TRAINERS T R EY1 N ER0 Z +TRAINING T R EY1 N IH0 NG +TRAINMEN T R EY1 N M AH0 N +TRAINOR T R EY1 N ER0 +TRAINS T R EY1 N Z +TRAIPSE T R EY1 P S +TRAIPSING T R EY1 P S IH0 NG +TRAISTER T R EY1 S T ER0 +TRAIT T R EY1 T +TRAITOR T R EY1 T ER0 +TRAITOROUS T R EY1 T ER0 AH0 S +TRAITORS T R EY1 T ER0 Z +TRAITS T R EY1 T S +TRAJAN T R EY1 JH AH0 N +TRAJAN'S T R EY1 JH AH0 N Z +TRAJECTORY T R AH0 JH EH1 K T ER0 IY0 +TRAK T R AE1 K +TRAKAS T R AA1 K AH0 Z +TRAM T R AE1 M +TRAMBLE T R AE1 M B AH0 L +TRAMCO T R AE1 M K OW0 +TRAMEL T R AE1 M AH0 L +TRAMELL T R AA0 M EY1 L +TRAMIEL T R AE1 M IY0 AH0 L +TRAMMEL T R AE1 M AH0 L +TRAMMELL T R AE1 M AH0 L +TRAMONTANA T R AA0 M OW0 N T AE1 N AH0 +TRAMONTANO T R AA0 M OW0 N T AA1 N OW0 +TRAMONTE T R AA0 M OW1 N T IY0 +TRAMONTIN T R AH0 M AA1 N T IH0 N +TRAMP T R AE1 M P +TRAMPE T R AE1 M P +TRAMPED T R AE1 M P T +TRAMPING T R AE1 M P IH0 NG +TRAMPLE T R AE1 M P AH0 L +TRAMPLED T R AE1 M P AH0 L D +TRAMPLES T R AE1 M P AH0 L Z +TRAMPLING T R AE1 M P L IH0 NG +TRAMPOLINE T R AE2 M P AH0 L IY1 N +TRAMPS T R AE1 M P Z +TRAMS T R AE1 M Z +TRAN T R AE1 N +TRANBERG T R AE1 N B ER0 G +TRANCE T R AE1 N S +TRANCHE T R AE1 N CH +TRANCHES T R AE1 N CH EH0 Z +TRANCHINA T R AA0 N K IY1 N AH0 +TRANE T R EY1 N +TRANG T R AE1 NG +TRANI T R AA1 N IY0 +TRANQUIL T R AE1 NG K W AH0 L +TRANQUIL(1) T R AE1 NG K W IH0 L +TRANQUILITY T R AE0 NG K W IH1 L IH0 T IY0 +TRANQUILIZE T R AE1 NG K W AH0 L AY2 Z +TRANQUILIZER T R AE1 NG K W AH0 L AY2 Z ER0 +TRANQUILIZERS T R AE1 NG K W AH0 L AY2 Z ER0 Z +TRANQUILIZING T R AE1 NG K W AH0 L AY2 Z IH0 NG +TRANQUILLITY T R AE0 NG K W IH1 L IH0 T IY0 +TRANS T R AE1 N Z +TRANSACT T R AE0 N Z AE1 K T +TRANSACTED T R AE0 N S AE1 K T IH0 D +TRANSACTED(1) T R AE0 N Z AE1 K T IH0 D +TRANSACTION T R AE0 N Z AE1 K SH AH0 N +TRANSACTION'S T R AE0 N Z AE1 K SH AH0 N Z +TRANSACTIONS T R AE0 N Z AE1 K SH AH0 N Z +TRANSAFRICA T R AE2 N Z AE1 F R IH0 K AH0 +TRANSALASKA T R AE2 N Z AH0 L AE1 S K AH0 +TRANSALTA T R AE2 N Z AO1 L T AH0 +TRANSAMERICA T R AE2 N S AH0 M EH1 R IH0 K AH0 +TRANSAMERICA'S T R AE2 N Z AH0 M EH1 R IH0 K AH0 Z +TRANSAMERICAN T R AE2 N Z AH0 M EH1 R IH0 K AH0 N +TRANSAMERICAN'S T R AE2 N Z AH0 M EH1 R IH0 K AH0 N Z +TRANSATLANTIC T R AE2 N Z AH0 T L AE1 N T IH0 K +TRANSATLANTIC(1) T R AE2 N Z AH0 T L AE1 N IH0 K +TRANSCANADA T R AE2 N Z K AE1 N AH0 T AH0 +TRANSCANADA'S T R AE2 N Z K AE1 N AH0 D AH0 Z +TRANSCAPITAL T R AE2 N Z K AE1 P IH0 T AH0 L +TRANSCEND T R AE0 N S EH1 N D +TRANSCENDED T R AE0 N S EH1 N D IH0 D +TRANSCENDENCE T R AE0 N S EH1 N D AH0 N S +TRANSCENDENT T R AE0 N S EH1 N D AH0 N T +TRANSCENDENTAL T R AE2 N S AH0 N D EH1 N T AH0 L +TRANSCENDENTAL(1) T R AE2 N S AH0 N D EH1 N AH0 L +TRANSCENDING T R AE0 N S EH1 N D IH0 NG +TRANSCENDS T R AE0 N S EH1 N D Z +TRANSCHANNEL T R AH1 N S CH AE1 N AH0 L +TRANSCHANNEL'S T R AH1 N S CH AE1 N AH0 L Z +TRANSCISCO T R AE2 N S IH1 S K OW0 +TRANSCO T R AE1 N S K OW0 +TRANSCON T R AE1 N Z K AA0 N +TRANSCONTINENTAL T R AE2 N Z K AA2 N T IH0 N EH1 N T AH0 L +TRANSCONTINENTAL(1) T R AE2 N Z K AA2 N IH0 N EH1 N T AH0 L +TRANSCONTINENTAL(2) T R AE2 N Z K AA2 N T IH0 N EH1 N AH0 L +TRANSCONTINENTAL(3) T R AE2 N Z K AA2 N IH0 N EH1 N AH0 L +TRANSCONTINENTAL'S T R AE2 N Z K AA2 N T IH0 N EH1 N T AH0 L Z +TRANSCONTINENTAL'S(1) T R AE2 N Z K AA2 N IH0 N EH1 N T AH0 L Z +TRANSCONTINENTAL'S(2) T R AE2 N Z K AA2 N T IH0 N EH1 N AH0 L Z +TRANSCONTINENTAL'S(3) T R AE2 N Z K AA2 N IH0 N EH1 N AH0 L Z +TRANSCRIBE T R AE0 N S K R AY1 B +TRANSCRIBED T R AE0 N S K R AY1 B D +TRANSCRIBER T R AE0 N S K R AY1 B ER0 +TRANSCRIBERS T R AE0 N S K R AY1 B ER0 Z +TRANSCRIBES T R AE0 N S K R AY1 B Z +TRANSCRIBING T R AE0 N S K R AY1 B IH0 NG +TRANSCRIPT T R AE1 N S K R IH2 P T +TRANSCRIPTION T R AE2 N S K R IH1 P SH AH0 N +TRANSCRIPTIONS T R AE2 N S K R IH1 P SH AH0 N Z +TRANSCRIPTS T R AE1 N S K R IH2 P T S +TRANSDUCER T R AE0 N S D UW1 S ER0 +TRANSDUCERS T R AE0 N S D UW1 S ER0 Z +TRANSECT T R AE1 N S EH2 K T +TRANSECTED T R AE1 N S EH2 K T IH0 D +TRANSECTION T R AE1 N S EH2 K SH AH0 N +TRANSFER T R AE0 N S F ER1 +TRANSFER(1) T R AE1 N S F ER0 +TRANSFERABILITY T R AE2 N S F ER0 AH0 B IH1 L IH0 T IY0 +TRANSFERABLE T R AE0 N S F ER1 AH0 B AH0 L +TRANSFERED T R AE0 N S F ER1 D +TRANSFERENCE T R AE0 N S F ER1 AH0 N S +TRANSFERING T R AE0 N S F ER1 IH0 NG +TRANSFERRABLE T R AE2 N S F ER1 AH0 B AH0 L +TRANSFERRED T R AE0 N S F ER1 D +TRANSFERRED(1) T R AE1 N S F ER0 D +TRANSFERRING T R AE0 N S F ER1 IH0 NG +TRANSFERS T R AE0 N S F ER1 Z +TRANSFERS(1) T R AE1 N S F ER0 Z +TRANSFIX T R AE0 N S F IH1 K S +TRANSFIXED T R AE0 N S F IH1 K S T +TRANSFORM T R AE0 N S F AO1 R M +TRANSFORM(1) T R AE1 N S F AO0 R M +TRANSFORMATION T R AE2 N S F ER0 M EY1 SH AH0 N +TRANSFORMATIONAL T R AE2 N S F ER0 M EY1 SH AH0 N AH0 L +TRANSFORMATIONS T R AE2 N S F ER0 M EY1 SH AH0 N Z +TRANSFORMATIVE T R AE2 N S F AO1 R M AA0 T IH2 V +TRANSFORMED T R AE0 N S F AO1 R M D +TRANSFORMER T R AE0 N S F AO1 R M ER0 +TRANSFORMERS T R AE0 N S F AO1 R M ER0 Z +TRANSFORMING T R AE0 N S F AO1 R M IH0 NG +TRANSFORMS T R AE0 N S F AO1 R M Z +TRANSFUSE T R AE0 N S F Y UW1 Z +TRANSFUSED T R AE0 N S F Y UW1 Z D +TRANSFUSION T R AE0 N S F Y UW1 ZH AH0 N +TRANSFUSIONS T R AE0 N S F Y UW1 ZH AH0 N Z +TRANSGENDER T R AE1 N Z JH EH1 N D ER0 +TRANSGENIC T R AE2 N Z JH EH1 N IH0 K +TRANSGRESS T R AE0 N Z G R EH1 S +TRANSGRESSED T R AE0 N Z G R EH1 S T +TRANSGRESSES T R AE0 N Z G R EH1 S IH0 S +TRANSGRESSING T R AE0 N Z G R EH1 S IH0 NG +TRANSGRESSION T R AE0 N Z G R EH1 SH AH0 N +TRANSGRESSIONS T R AE0 N Z G R EH1 SH AH0 N Z +TRANSGRESSOR T R AE0 N Z G R EH1 S ER0 +TRANSIENCE T R AE1 N Z IY0 AH0 N S +TRANSIENT T R AE1 N ZH AH0 N T +TRANSIENTS T R AE1 N Z IY0 AH0 N T S +TRANSILLUMINATION T R AE2 N Z AH0 L UW2 M AH0 N EY1 SH AH0 N +TRANSIMAGE T R AE2 N Z IH1 M IH0 JH +TRANSISTOR T R AE0 N Z IH1 S T ER0 +TRANSISTORS T R AE0 N Z IH1 S T ER0 Z +TRANSIT T R AE1 N Z IH0 T +TRANSITED T R AE1 N Z IH0 T IH0 D +TRANSITING T R AE1 N Z IH0 T IH0 NG +TRANSITION T R AE0 N Z IH1 SH AH0 N +TRANSITIONAL T R AE0 N S IH1 SH AH0 N AH0 L +TRANSITIONAL(1) T R AE0 N Z IH1 SH AH0 N AH0 L +TRANSITIONING T R AE0 N Z IH1 SH AH0 N IH0 NG +TRANSITIONS T R AE0 N Z IH1 SH AH0 N Z +TRANSITORY T R AE1 N Z AH0 T AO2 R IY0 +TRANSITS T R AE1 N Z IH0 T S +TRANSKEI T R AE1 N Z K EY2 +TRANSLATE T R AE0 N Z L EY1 T +TRANSLATE(1) T R AE0 N S L EY1 T +TRANSLATED T R AE0 N S L EY1 T IH0 D +TRANSLATES T R AE0 N Z L EY1 T S +TRANSLATES(1) T R AE1 N S L EY2 T S +TRANSLATING T R AE0 N Z L EY1 T IH0 NG +TRANSLATING(1) T R AE1 N S L EY2 T IH0 NG +TRANSLATION T R AE0 N Z L EY1 SH AH0 N +TRANSLATION(1) T R AE0 N S L EY1 SH AH0 N +TRANSLATIONS T R AE0 N Z L EY1 SH AH0 N Z +TRANSLATIONS(1) T R AE0 N S L EY1 SH AH0 N Z +TRANSLATOR T R AE0 N S L EY1 T ER0 +TRANSLATOR(1) T R AE0 N Z L EY1 T ER0 +TRANSLATORS T R AE0 N S L EY1 T ER0 Z +TRANSLATORS(1) T R AE0 N Z L EY1 T ER0 Z +TRANSLOGIC T R AE2 N Z L AA1 JH IH0 K +TRANSLUCENT T R AE0 N S L UW1 S AH0 N T +TRANSMARK T R AE1 N Z M AA2 R K +TRANSMEDIA T R AE2 N Z M IY1 D IY0 AH0 +TRANSMISSION T R AE0 N S M IH1 SH AH0 N +TRANSMISSION(1) T R AE0 N Z M IH1 SH AH0 N +TRANSMISSIONS T R AE0 N Z M IH1 SH AH0 N Z +TRANSMIT T R AE0 N Z M IH1 T +TRANSMITS T R AE0 N Z M IH1 T S +TRANSMITTABLE T R AE0 N Z M IH1 T AH0 B AH0 L +TRANSMITTAL T R AE0 N S M IH1 T AH0 L +TRANSMITTED T R AE0 N S M IH1 T IH0 D +TRANSMITTER T R AE0 N S M IH1 T ER0 +TRANSMITTER'S T R AE0 N S M IH1 T ER0 Z +TRANSMITTERS T R AE0 N S M IH1 T ER0 Z +TRANSMITTING T R AE0 N S M IH1 T IH0 NG +TRANSNATIONAL T R AE0 N S N AE1 SH AH0 N AH0 L +TRANSOCEANIC T R AE2 N Z OW0 SH IY0 AE1 N IH0 K +TRANSOHIO T R AE2 N Z OW0 HH AY1 OW0 +TRANSOM T R AE1 N S AH0 M +TRANSOMS T R AE1 N S AH0 M Z +TRANSOU T R AE1 N Z UW2 +TRANSPAC T R AE1 N Z P AE2 K +TRANSPACIFIC T R AE2 N S P AH0 S IH1 F IH0 K +TRANSPARENCIES T R AE0 N S P EH1 R AH0 N S IY0 Z +TRANSPARENCY T R AE0 N S P EH1 R AH0 N S IY0 +TRANSPARENT T R AE0 N S P EH1 R AH0 N T +TRANSPARENTLY T R AE0 N S P EH1 R AH0 N T L IY0 +TRANSPARK T R AE1 N S P AA1 R K +TRANSPIRE T R AE0 N S P AY1 ER0 +TRANSPIRED T R AE0 N S P AY1 ER0 D +TRANSPIRES T R AE0 N S P AY1 ER0 Z +TRANSPIRING T R AE0 N S P AY1 ER0 IH0 NG +TRANSPLANT T R AE0 N S P L AE1 N T +TRANSPLANTATION T R AE2 N Z P L AE0 N T EY1 SH AH0 N +TRANSPLANTED T R AE0 N S P L AE1 N T IH0 D +TRANSPLANTING T R AE0 N S P L AE1 N T IH0 NG +TRANSPLANTS T R AE0 N S P L AE1 N T S +TRANSPONDER T R AE0 N S P AA1 N D ER0 +TRANSPONDERS T R AE0 N S P AA1 N D ER0 Z +TRANSPORT T R AE0 N S P AO1 R T +TRANSPORT(1) T R AE1 N S P AO0 R T +TRANSPORTABLE T R AE0 N S P AO1 R T AH0 B AH0 L +TRANSPORTATION T R AE2 N S P ER0 T EY1 SH AH0 N +TRANSPORTATION'S T R AE2 N S P ER0 T EY1 SH AH0 N Z +TRANSPORTED T R AE0 N S P AO1 R T IH0 D +TRANSPORTER T R AE0 N S P AO1 R T ER0 +TRANSPORTERS T R AE0 N S P AO1 R T ER0 Z +TRANSPORTING T R AE0 N S P AO1 R T IH0 NG +TRANSPORTS T R AE0 N S P AO1 R T S +TRANSPORTS(1) T R AE1 N S P AO0 R T S +TRANSPOSE T R AE0 N S P OW1 Z +TRANSPOSED T R AE0 N S P OW1 Z D +TRANSRACIAL T R AE2 N Z R EY1 SH AH0 L +TRANSRAPID T R AE1 N Z R AE1 P IH0 D +TRANSSEXUAL T R AE0 N S EH1 K SH Y UW0 AH0 L +TRANSSEXUALS T R AE0 N S EH1 K SH Y UW0 AH0 L Z +TRANSTAR T R AE0 N S T AA1 R +TRANSTECHNOLOGY T R AE2 N Z T AH0 K N AA1 L AH0 JH IY0 +TRANSTECTOR T R AE2 N Z T EH1 K T ER0 +TRANSUE T R AE1 N Z UW0 +TRANSVAAL T R AE0 N Z V AA1 L +TRANSVERSE T R AE0 N Z V ER1 S +TRANSVESTITE T R AE0 N Z V EH1 S T AY0 T +TRANSVESTITES T R AE0 N Z V EH1 S T AY0 T S +TRANSWAY T R AE1 N Z W EY2 +TRANSWESTERN T R AE2 N Z W EH1 S T ER0 N +TRANSWORLD T R AE0 N S W ER1 L D +TRANSYLVANIA T R AE2 N Z IY0 L V EY1 N IY0 AH0 +TRANSYLVANIA(1) T R AE2 N S IH0 L V EY1 N Y AH0 +TRANT T R AE1 N T +TRANTER T R AE1 N T ER0 +TRANTHAM T R AE1 N TH AH0 M +TRANUM T R AE1 N AH0 M +TRANZONIC T R AE0 N Z AA1 N IH0 K +TRAP T R AE1 P +TRAPANI T R AA0 P AA1 N IY0 +TRAPASSO T R AA0 P AA1 S OW0 +TRAPELO T R AH0 P EH1 L OW0 +TRAPEZE T R AH0 P IY1 Z +TRAPHAGEN T R AE1 F AH0 G AH0 N +TRAPNELL T R AE1 P N AH0 L +TRAPP T R AE1 P +TRAPPE T R AE1 P +TRAPPED T R AE1 P T +TRAPPER T R AE1 P ER0 +TRAPPERS T R AE1 P ER0 Z +TRAPPING T R AE1 P IH0 NG +TRAPPINGS T R AE1 P IH0 NG Z +TRAPPIST T R AE1 P IH0 S T +TRAPS T R AE1 P S +TRASH T R AE1 SH +TRASHED T R AE1 SH T +TRASHES T R AE1 SH IH0 Z +TRASHING T R AE1 SH IH0 NG +TRASHY T R AE1 SH IY0 +TRASK T R AE1 S K +TRAUB T R AO1 B +TRAUDT T R AO1 D T +TRAUGER T R AW1 G ER0 +TRAUGH T R AO1 +TRAUGHBER T R AO1 B ER0 +TRAUGOTT T R AW1 G AH0 T +TRAUM T R AO1 M +TRAUMA T R AO1 M AH0 +TRAUMAS T R AO1 M AH0 Z +TRAUMATIC T R AO0 M AE1 T IH0 K +TRAUMATIZE T R AO1 M AH0 T AY2 Z +TRAUMATIZED T R AO1 M AH0 T AY2 Z D +TRAUSCH T R AW1 SH +TRAUT T R AO1 T +TRAUTH T R AO1 TH +TRAUTMAN T R AW1 T M AH0 N +TRAUTMANN T R AW1 T M AH0 N +TRAUTNER T R AW1 T N ER0 +TRAUTWEIN T R AW1 T W AY2 N +TRAVAGLINI T R AA0 V AA0 G L IY1 N IY0 +TRAVAIL T R AH0 V EY1 L +TRAVAILS T R AH0 V EY1 L Z +TRAVEL T R AE1 V AH0 L +TRAVELDAY T R AE1 V AH0 L D EY2 +TRAVELDAYS T R AE1 V AH0 L D EY2 Z +TRAVELED T R AE1 V AH0 L D +TRAVELER T R AE1 V AH0 L ER0 +TRAVELER(1) T R AE1 V L ER0 +TRAVELER'S T R AE1 V AH0 L ER0 Z +TRAVELERS T R AE1 V AH0 L ER0 Z +TRAVELERS(1) T R AE1 V L ER0 Z +TRAVELERS' T R AE1 V AH0 L ER0 Z +TRAVELGATE T R AE1 V AH0 L G EY2 T +TRAVELING T R AE1 V AH0 L IH0 NG +TRAVELING(1) T R AE1 V L IH0 NG +TRAVELLED T R AE1 V AH0 L D +TRAVELLER T R AE1 V AH0 L ER0 +TRAVELLERS T R AE1 V AH0 L ER0 Z +TRAVELLING T R AE1 V AH0 L IH0 NG +TRAVELLING(1) T R AE1 V L IH0 NG +TRAVELODGE T R AE1 V AH0 L AA1 JH +TRAVELOGUE T R AE1 V AH0 L AO2 G +TRAVELS T R AE1 V AH0 L Z +TRAVELSTEAD T R AE1 V AH0 L S T EH2 D +TRAVENOL T R AE1 V AH0 N AH0 L +TRAVER T R EY1 V ER0 +TRAVERS T R AE1 V ER0 Z +TRAVERSE T R AE1 V ER0 S +TRAVERSE(1) T R AH0 V ER1 S +TRAVERSED T R AE1 V ER0 S T +TRAVERSED(1) T R AH0 V ER1 S T +TRAVERSING T R AH0 V ER1 S IH0 NG +TRAVERSO T R AA0 V EH1 R S OW0 +TRAVESTIES T R AE1 V AH0 S T IY0 Z +TRAVESTY T R AE1 V AH0 S T IY0 +TRAVIATA T R AA0 V IY0 AA1 T AH0 +TRAVIESO T R AA0 V IY1 S OW0 +TRAVIS T R AE1 V IH0 S +TRAVISANO T R AE2 V IH0 S AA1 N OW0 +TRAVNIK T R AE1 V N IH0 K +TRAVOLTA T R AH0 V OW1 L T AH0 +TRAVOLTA'S T R AH0 V OW1 L T AH0 Z +TRAVOLTAS T R AH0 V OW1 L T AH0 Z +TRAWEEK T R AO1 IY2 K +TRAWICK T R AO1 IH0 K +TRAWLER T R AO1 L ER0 +TRAWLERS T R AO1 L ER0 Z +TRAX T R AE1 K S +TRAXLER T R AE1 K S L ER0 +TRAY T R EY1 +TRAYER T R EY1 ER0 +TRAYLOR T R EY1 L ER0 +TRAYNHAM T R EY1 N HH AH0 M +TRAYNOR T R EY1 N ER0 +TRAYS T R EY1 Z +TRAYWICK T R EY1 W IH2 K +TRBOVICH T ER0 B AA1 V IH0 CH +TRE T R EY1 +TREACHEROUS T R EH1 CH ER0 AH0 S +TREACHERY T R EH1 CH ER0 IY0 +TREACY T R EY1 S IY0 +TREAD T R EH1 D +TREADAWAY T R EH1 D AH0 W EY2 +TREADING T R EH1 D IH0 NG +TREADMILL T R EH1 D M IH2 L +TREADMILLS T R EH1 D M IH2 L Z +TREADS T R EH1 D Z +TREADSTONE T R EH1 D S T OW2 N +TREADWAY T R EH1 D W EY2 +TREADWELL T R EH1 D W EH2 L +TREADWHEEL T R EH1 D W IY2 L +TREANOR T R IY1 N ER0 +TREASE T R IY1 Z +TREASON T R IY1 Z AH0 N +TREASONOUS T R IY1 Z AH0 N AH2 S +TREASONS T R IY1 Z AH0 N S +TREASTER T R IY1 S T ER0 +TREASURE T R EH1 ZH ER0 +TREASURED T R EH1 ZH ER0 D +TREASURER T R EH1 ZH ER0 ER0 +TREASURER'S T R EH1 ZH ER0 ER0 Z +TREASURERS T R EH1 ZH ER0 ER0 Z +TREASURES T R EH1 ZH ER0 Z +TREASURIES T R EH1 ZH ER0 IY0 Z +TREASURY T R EH1 ZH ER0 IY0 +TREASURY'S T R EH1 ZH ER0 IY0 Z +TREASURYS T R EH1 ZH ER0 IY0 Z +TREAT T R IY1 T +TREATABLE T R IY1 T AH0 B AH0 L +TREATED T R IY1 T IH0 D +TREATER T R IY1 T ER0 +TREATERS T R IY1 T ER0 Z +TREATIES T R IY1 T IY0 Z +TREATING T R IY1 T IH0 NG +TREATISE T R IY1 T AH0 S +TREATISES T R IY1 T AH0 S AH0 Z +TREATMENT T R IY1 T M AH0 N T +TREATMENTS T R IY1 T M AH0 N T S +TREATS T R IY1 T S +TREATY T R IY1 T IY0 +TREATY'S T R IY1 T IY0 Z +TREBILCOCK T R IH0 B IH1 L K AH0 K +TREBLE T R EH1 B AH0 L +TREBLED T R EH1 B AH0 L D +TREBLINKA T R EH0 B L IH1 NG K ER0 +TREBLINKA(1) T R EH0 B L IH1 NG K AH0 +TRECKER T R EH1 K ER0 +TREDER T R IY1 D ER0 +TREDWAY T R EH1 D W EY2 +TREE T R IY1 +TREECE T R IY1 S +TREELESS T R IY1 L AH0 S +TREEN T R IY1 N +TREES T R IY1 Z +TREESE T R IY1 Z +TREESH T R IY1 SH +TREESWEET T R IY1 S W IY2 T +TREETOP T R IY1 T AO2 P +TREETOPS T R IY1 T AO2 P S +TREFETHEN T R EH1 F IH0 TH AH0 N +TREFGARNE T R EH1 F G AA0 R N +TREFRY T R EH1 F R IY0 +TREFZ T R EH1 F Z +TREGLIA T R EH1 G L IY0 AH0 +TREGO T R EH1 G OW0 +TREGONING T R EH1 G AH0 N IH0 NG +TREGRE T R EH1 G ER0 +TREGURTHA T R EH0 G ER1 TH AH0 +TREHARNE T R EH1 HH AA0 R N +TREIBER T R AY1 B ER0 +TREICHEL T R AY1 K AH0 +TREICHLER T R AY1 K AH0 L ER0 +TREICHLER(1) T R AY1 K L ER0 +TREINEN T R AY1 N AH0 N +TREJO T R EY1 Y OW0 +TREK T R EH1 K +TREKKED T R EH1 K T +TREKKING T R EH1 K IH0 NG +TREKS T R EH1 K S +TRELA T R EH1 L AH0 +TRELLA T R EH1 L AH0 +TRELLEBORG T R EH1 L AH0 B AO0 R G +TRELLEBORG'S T R EH1 L AH0 B AO0 R G Z +TRELLIS T R EH1 L AH0 S +TRELOAR T R EH1 L AO0 R +TREMAIN T R EH1 M AY0 N +TREMAINE T R IH0 M EY1 N +TREMAYNE T R EH1 M EY0 N +TREMBATH T R EH1 M B AH0 TH +TREMBLAY T R EH1 M B L EY0 +TREMBLE T R EH1 M B AH0 L +TREMBLED T R EH1 M B AH0 L D +TREMBLEY T R EH1 M B L IY0 +TREMBLING T R EH1 M B AH0 L IH0 NG +TREMBLING(1) T R EH1 M B L IH0 NG +TREMBLY T R EH1 M B L IY0 +TREMEL T R EH1 M AH0 L +TREMENDOUS T R AH0 M EH1 N D AH0 S +TREMENDOUS(1) T R IH0 M EH1 N D AH0 S +TREMENDOUSLY T R AH0 M EH1 N D AH0 S L IY0 +TREMENDOUSLY(1) T R IH0 M EH1 N D AH0 S L IY0 +TREMENS T R EH1 M AH0 N Z +TREML T R EH1 M AH0 L +TREMMEL T R EH1 M AH0 L +TREMONT T R EH1 M AH0 N T +TREMOR T R EH1 M ER0 +TREMORS T R EH1 M ER0 Z +TREMPER T R EH1 M P ER0 +TREMULOUS T R EH1 M Y AH0 L AH0 S +TREMULOUSLY T R EH1 M Y AH0 L AH0 S L IY0 +TRENARY T R EH1 N EH0 R IY0 +TRENCH T R EH1 N CH +TRENCHANT T R EH1 N CH AH0 N T +TRENCHARD T R EH1 NG K ER0 D +TRENCHER T R EH1 N CH ER0 +TRENCHES T R EH1 N CH IH0 Z +TREND T R EH1 N D +TRENDED T R EH1 N D IH0 D +TRENDIER T R EH1 N D Y ER0 +TRENDIER(1) T R EH1 N D IY0 ER0 +TRENDIEST T R EH0 N D IY1 S T +TRENDIEST(1) T R EH1 N D IY0 AH0 S T +TRENDING T R EH1 N D IH0 NG +TRENDLESS T R EH1 N D L AH0 S +TRENDLINE T R EH1 N D L AY2 N +TRENDS T R EH1 N D Z +TRENDS(1) T R EH1 N Z +TRENDSETTER T R EH1 N D S EH2 T ER0 +TRENDY T R EH1 N D IY0 +TRENHOLM T R EH1 N HH OW2 L M +TRENKAMP T R EH1 N K AE2 M P +TRENKLE T R EH1 NG K AH0 L +TRENT T R EH1 N T +TRENT'S T R EH1 N T S +TRENTE-ET-QUARANTE T R AA1 N T EY2 K AA2 R AA1 N T +TRENTHAM T R EH1 N TH AH0 M +TRENTMAN T R EH1 N T M AH0 N +TRENTON T R EH1 N T AH0 N +TRENTON'S T R EH1 N T AH0 N Z +TREON T R IY1 AH0 N +TREPAGNIER T R EH1 P AH0 G N IY2 ER0 +TREPANIER T R EH1 P AH0 N IY2 ER0 +TREPIDATION T R EH2 P IH0 D EY1 SH AH0 N +TREPPEL T R EH1 P AH0 L +TREPTOW T R EH1 P T OW0 +TRESCH T R EH1 SH +TRESCOTT T R EH1 S K AH0 T +TRESPASS T R EH1 S P AE2 S +TRESPASS(1) T R EH1 S P AH0 S +TRESPASSING T R EH1 S P AE2 S IH0 NG +TRESPASSING(1) T R EH1 S P AH0 S IH0 NG +TRESS T R EH1 S +TRESSEL T R EH1 S AH0 L +TRESSES T R EH1 S IH0 Z +TRESSLER T R EH1 S L ER0 +TREST T R EH1 S T +TRESTER T R EH1 S T ER0 +TRESTLE T R EH1 S AH0 L +TRETHEWEY T R EH1 TH Y UW0 IY0 +TRETINOIN T R EH1 T IH0 N OY2 N +TRETTEL T R EH1 T AH0 L +TRETTER T R EH1 T ER0 +TRETTIN T R EH1 T IH0 N +TREU T R UW1 +TREUHAND T R UW1 HH AE2 N D +TREUHANDANSTALT T R UW2 HH AE1 N D AH0 N S T AA2 L T +TREURNICHT T R UW1 R N IH0 K T +TREVATHAN T R EH1 V AH0 TH AH0 N +TREVELYAN T R AH0 V EH1 L Y AH0 N +TREVINO T R AH0 V IY1 N OW0 +TREVISO T R EH0 V IY1 S OW0 +TREVIZO T R EH0 V IY1 Z OW0 +TREVOR T R EH1 V ER0 +TREW T R UW1 +TREXLER T R EH1 K S L ER0 +TREY T R EY1 +TREYBIG T R EY1 B IH0 G +TREZISE T R EH1 Z AY0 Z +TREZZA T R EH1 Z AH0 +TRI T R AY1 +TRI-STATE T R AY1 S T EY1 T +TRIAD T R AY1 AE2 D +TRIAD'S T R AY1 AE2 D Z +TRIADS T R AY1 AE2 D Z +TRIAGE T R AY1 IH0 JH +TRIAL T R AY1 AH0 L +TRIAL(1) T R AY1 L +TRIAL'S T R AY1 AH0 L Z +TRIALS T R AY1 AH0 L Z +TRIALS(1) T R AY1 L Z +TRIANA T R IY0 AE1 N AH0 +TRIANGLE T R AY1 AE2 NG G AH0 L +TRIANGLE'S T R AY1 AE2 NG G AH0 L Z +TRIANGLES T R AY1 AE2 NG G AH0 L Z +TRIANGULAR T R AY0 AE1 NG G Y AH0 L ER0 +TRIANGULATION T R AY0 AE2 NG G Y UW0 L EY1 SH AH0 N +TRIANO T R IY0 AA1 N OW0 +TRIARC T R AY1 AA2 R K +TRIASSIC T R AY2 AE1 S IH2 K +TRIATHLON T R AY2 AE1 TH L AH0 N +TRIB T R IH1 B +TRIBAL T R AY1 B AH0 L +TRIBALISM T R AY1 B AH0 L IH0 Z M +TRIBALISM(1) T R AY1 B AH0 L IH0 Z AH0 M +TRIBASA T R AY1 B AE1 S AH0 +TRIBBETT T R IH1 B IH0 T +TRIBBEY T R IH1 B IY0 +TRIBBLE T R IH1 B AH0 L +TRIBBLES T R IH1 B AH0 L Z +TRIBBY T R IH1 B IY0 +TRIBE T R AY1 B +TRIBE'S T R AY1 B Z +TRIBECA T R IH0 B EH1 K AH0 +TRIBES T R AY1 B Z +TRIBESMAN T R AY1 B Z M AE0 N +TRIBESMEN T R AY1 B Z M IH0 N +TRIBLE T R IH1 B AH0 L +TRIBOROUGH T R AY1 B ER0 OW0 +TRIBULATION T R IH2 B Y AH0 L EY1 SH AH0 N +TRIBULATIONS T R IH2 B Y AH0 L EY1 SH AH0 N Z +TRIBULL T R IH1 B AH0 L +TRIBUNAL T R AH0 B Y UW1 N AH0 L +TRIBUNALS T R AY2 B Y UW1 N AH0 L Z +TRIBUNE T R IH1 B Y UW0 N +TRIBUNE'S T R IH1 B Y UW0 N Z +TRIBUTARIES T R IH1 B Y AH0 T EH2 R IY0 Z +TRIBUTARY T R IH1 B Y AH0 T EH2 R IY0 +TRIBUTE T R IH1 B Y UW0 T +TRIBUTE'S T R IH1 B Y UW0 T S +TRIBUTES T R IH1 B Y UW0 T S +TRICARICO T R IY0 K AA0 R IY1 K OW0 +TRICE T R AY1 S +TRICENTROL T R AY2 S EH1 N T R AA0 L +TRICENTROL'S T R AY2 S EH1 N T R AA0 L Z +TRICEPS T R AY1 S EH2 P S +TRICERATOPS T R AY2 S EH1 R AH0 T AO2 P S +TRICHE T R IH1 CH +TRICHET T R IH1 CH IH0 T +TRICIA T R IH1 SH AH0 +TRICIA'S T R IH1 SH AH0 Z +TRICIL T R IH1 S IH0 L +TRICK T R IH1 K +TRICKED T R IH1 K T +TRICKEL T R IH1 K AH0 L +TRICKERY T R IH1 K ER0 IY0 +TRICKETT T R IH1 K IH0 T +TRICKEY T R IH1 K IY0 +TRICKIER T R IH1 K IY0 ER0 +TRICKIEST T R IH1 K IY0 AH0 S T +TRICKING T R IH1 K IH0 NG +TRICKLE T R IH1 K AH0 L +TRICKLED T R IH1 K AH0 L D +TRICKLES T R IH1 K AH0 L Z +TRICKLING T R IH1 K L IH0 NG +TRICKS T R IH1 K S +TRICKSTER T R IH1 K S T ER0 +TRICKSTERS T R IH1 K S T ER0 Z +TRICKY T R IH1 K IY0 +TRICO T R IY1 K OW0 +TRICUSPID T R AY0 K AH1 S P IH0 D +TRICYCLE T R IH1 S IH0 K AH0 L +TRIDENT T R AY1 D AH0 N T +TRIDEX T R IH1 D EH2 K S +TRIE T R AY1 +TRIED T R AY1 D +TRIENNIAL T R AY0 EH1 N IY0 AH0 L +TRIER T R AY1 ER0 +TRIERWEILER T R IH1 R W AY0 L ER0 +TRIES T R AY1 Z +TRIESTE T R IY1 S T +TRIEU T R UW1 +TRIFARI T R IH0 F AA1 R IY0 +TRIFECTA T R AY0 F EH1 K T AH0 +TRIFLE T R AY1 F AH0 L +TRIFLES T R AY1 F AH0 L Z +TRIFLING T R AY1 F L IH0 NG +TRIG T R IH1 G +TRIGG T R IH1 G +TRIGGER T R IH1 G ER0 +TRIGGERED T R IH1 G ER0 D +TRIGGERING T R IH1 G ER0 IH0 NG +TRIGGERS T R IH1 G ER0 Z +TRIGGS T R IH1 G Z +TRIGLYCERIDE T R AY0 G L IH1 S ER0 AY2 D +TRIGLYCERIDES T R AY0 G L IH1 S ER0 AY2 D Z +TRIGO T R IY1 G OW0 +TRILATERAL T R AY0 L AE1 T ER0 AH0 L +TRILBY T R IH1 L B IY0 +TRILL T R IH1 L +TRILLIN T R IH1 L IH0 N +TRILLING T R IH1 L IH0 NG +TRILLION T R IH1 L Y AH0 N +TRILLIONS T R IH1 L Y AH0 N Z +TRILLO T R IH1 L OW0 +TRILOGY T R IH1 L AH0 JH IY0 +TRILON T R IH1 L AH0 N +TRIM T R IH1 M +TRIMAC T R IH1 M AE0 K +TRIMARCHI T R IY0 M AA1 R K IY0 +TRIMARCO T R IH0 M AA1 R K OW0 +TRIMAS T R IY1 M AH0 S +TRIMBLE T R IH1 M B AH0 L +TRIMBOLI T R IY0 M B OW1 L IY0 +TRIMEDYNE T R AY1 M D AY2 N +TRIMESTER T R AY0 M EH1 S T ER0 +TRIMETREXATE T R IH0 M EH1 T R AH0 K S EY2 T +TRIMM T R IH1 M +TRIMMED T R IH1 M D +TRIMMER T R IH1 M ER0 +TRIMMERS T R IH1 M ER0 Z +TRIMMING T R IH1 M IH0 NG +TRIMMINGS T R IH1 M IH0 NG Z +TRIMPE T R IH1 M P +TRIMS T R IH1 M Z +TRINCOMALEE T R IH0 NG K OW1 M AH0 L IY0 +TRINE T R AY1 N +TRINGALI T R IH0 NG G AA1 L IY0 +TRINH T R IH1 N +TRINIDAD T R IH1 N IH0 D AE2 D +TRINITY T R IH1 N AH0 T IY0 +TRINITY(1) T R IH1 N IH0 T IY0 +TRINITY'S T R IH1 N IH0 T IY0 Z +TRINKA T R IH1 NG K AH0 +TRINKET T R IH1 NG K AH0 T +TRINKETS T R IH1 NG K AH0 T S +TRINKLE T R IH1 NG K AH0 L +TRINOVA T R AY2 N OW1 V AH0 +TRINTEX T R IH1 N T EH2 K S +TRIO T R IY1 OW2 +TRIO'S T R IY1 OW2 Z +TRIOLA T R IY0 OW1 L AH0 +TRIOLO T R IY0 OW1 L OW0 +TRIOMPHE T R IY0 OW1 M F +TRIP T R IH1 P +TRIP'S T R IH1 P S +TRIPARTITE T R AY0 P AA1 R T AY2 T +TRIPE T R AY1 P +TRIPI T R IY1 P IY0 +TRIPLE T R IH1 P AH0 L +TRIPLECAST T R IH1 P AH0 L K AE2 S T +TRIPLED T R IH1 P AH0 L D +TRIPLES T R IH1 P AH0 L Z +TRIPLET T R IH1 P L AH0 T +TRIPLETS T R IH1 P L AH0 T S +TRIPLETT T R IH1 P L IH0 T +TRIPLEX T R IH0 P L EH1 K S +TRIPLICATE T R IH1 P L IH0 K AH0 T +TRIPLING T R IH1 P AH0 L IH0 NG +TRIPLING(1) T R IH1 P L IH0 NG +TRIPOD T R AY1 P AA2 D +TRIPODI T R IY0 P OW1 D IY0 +TRIPODS T R AY1 P AA2 D Z +TRIPOLI T R IH1 P AH0 L IY0 +TRIPOLI'S T R IH1 P AH0 L IY0 Z +TRIPP T R IH1 P +TRIPP'S T R IH1 P S +TRIPPE T R IH1 P +TRIPPED T R IH1 P T +TRIPPEL T R IH1 P AH0 L +TRIPPER T R IH1 P ER0 +TRIPPERS T R IH1 P ER0 Z +TRIPPETT T R IH1 P IH0 T +TRIPPIE T R IH1 P IY0 +TRIPPING T R IH1 P IH0 NG +TRIPPLE T R IH1 P AH0 L +TRIPPY T R IH1 P IY2 +TRIPS T R IH1 P S +TRIPTYCH T R IH1 P T IH0 K +TRIPTYCHS T R IH1 P T IH0 K S +TRIREME T R AY1 R IY2 M +TRIREMES T R AY1 R IY2 M Z +TRISH T R IH1 SH +TRISHA T R IH1 SH AH0 +TRISHA'S T R IH1 SH AH0 Z +TRISKA T R IH1 S K AH0 +TRISLER T R IH1 S AH0 L ER0 +TRISLER(1) T R IH1 S L ER0 +TRISM T R IH1 Z AH0 M +TRISTA T R IH1 S T AH0 +TRISTAN T R IH1 S T AE2 N +TRISTAR T R AY1 S T AA2 R +TRISTATE T R AY1 S T EY2 T +TRISTRAM T R IH1 S T R AH0 M +TRITCH T R IH1 CH +TRITE T R AY1 T +TRITES T R AY1 T S +TRITIUM T R IH1 T IY0 AH0 M +TRITON T R AY1 T AH0 N +TRITON'S T R AY1 T AH0 N Z +TRITSCH T R IH1 CH +TRITSCHLER T R IH1 CH L ER0 +TRITT T R IH1 T +TRITZ T R IH1 T S +TRIUMPH T R AY1 AH0 M F +TRIUMPHAL T R AY0 AH1 M F AH0 L +TRIUMPHANT T R AY0 AH1 M F AH0 N T +TRIUMPHANTLY T R AY0 AH1 M F AH0 N T L IY0 +TRIUMPHED T R AY1 AH0 M F T +TRIUMPHS T R AY1 AH0 M F S +TRIUMVIRATE T R AY0 AH1 M V ER0 AH0 T +TRIVEDI T R IY0 V EH1 D IY0 +TRIVEST T R IH1 V EH0 S T +TRIVEST(1) T R AY1 V EH2 S T +TRIVETT T R IH1 V IH0 T +TRIVETTE T R IH0 V EH1 T +TRIVIA T R IH1 V IY0 AH0 +TRIVIAL T R IH1 V IY0 AH0 L +TRIVIALITY T R IH2 V IY0 AE1 L AH0 T IY2 +TRIVIALIZE T R IH1 V IY0 AH0 L AY2 Z +TRIVIALIZED T R IH1 V IY0 AH0 L AY2 Z D +TRIVIALIZES T R IH1 V IY0 AH0 L AY2 Z IH0 Z +TRIVIALIZING T R IH1 V IY0 AH0 L AY2 Z IH0 NG +TRIXIE T R IH1 K S IY0 +TRIXY T R IH1 K S IY0 +TRIZEC T R IH1 Z AH0 K +TRIZEC'S T R IH1 Z EH0 K S +TRNKA T R IH1 NG K AH0 +TRNOPOLJE T EH2 R N AH0 P AO1 L Y EH0 +TROBAUGH T R AA1 B AO0 +TROCHE T R AA1 CH +TROCHMANN T R AA1 CH M AE0 N +TROCHMANN(1) T R AA1 K M AE0 N +TROCKI T R AA1 K IY0 +TROD T R AA1 D +TRODDEN T R AA1 D AH0 N +TROEGER T R OW1 G ER0 +TROENDLE T R OW1 N D AH0 L +TROESTER T R OW1 S T ER0 +TROGDON T R AA1 G D AH0 N +TROHA T R OW1 HH AH0 +TROIA T R OW1 Y AH0 +TROIANI T R OW0 Y AA1 N IY0 +TROIANO T R OW0 IY0 AA1 N OW0 +TROIKA T R OY1 K AH0 +TROIS T W AA1 +TROISE T R OY1 Z +TROISI T R OY1 S IY0 +TROJAN T R OW1 JH AH0 N +TROJANOWSKI T R AH0 Y AH0 N AO1 F S K IY0 +TROJANS T R OW1 JH AH0 N Z +TROKEL T R OW1 K AH0 L +TROLINGER T R OW1 L IH0 NG ER0 +TROLL T R OW1 L +TROLL'S T R OW1 L Z +TROLLEY T R AA1 L IY0 +TROLLEYS T R AA1 L IY0 Z +TROLLING T R OW1 L IH0 NG +TROLLINGER T R OW1 L IH0 NG ER0 +TROLLS T R OW1 L Z +TROMA T R OW1 M AH0 +TROMBINO T R OW0 M B IY1 N OW0 +TROMBLE T R AA1 M B AH0 L +TROMBLEY T R AA1 M B L IY0 +TROMBLY T R AA1 M B L IY0 +TROMBONE T R AA0 M B OW1 N +TROMBONES T R AA0 M B OW1 N Z +TROMBONIST T R AA2 M B OW1 N IH0 S T +TROMP T R AA1 M P +TROMPETER T R AA1 M P IY0 T ER0 +TRON T R AA1 N +TRONCOSO T R OW0 N K OW1 S OW0 +TRONE T R OW1 N +TRONIC T R AA1 N IH0 K +TROON T R UW1 N +TROOP T R UW1 P +TROOP'S T R UW1 P S +TROOPED T R UW1 P T +TROOPER T R UW1 P ER0 +TROOPER'S T R UW1 P ER0 Z +TROOPERS T R UW1 P ER0 Z +TROOPERS' T R UW1 P ER0 Z +TROOPING T R UW1 P IH0 NG +TROOPS T R UW1 P S +TROOPS' T R UW1 P S +TROOST T R UW1 S T +TROPEA T R OW1 P IY0 AH0 +TROPEANO T R OW2 P IY1 N OW0 +TROPHIES T R OW1 F IY0 Z +TROPHY T R OW1 F IY0 +TROPIC T R AA1 P IH0 K +TROPICAL T R AA1 P IH0 K AH0 L +TROPICANA T R AA2 P IH0 K AE1 N AH0 +TROPICANA'S T R AA2 P IH0 K AE1 N AH0 Z +TROPICS T R AA1 P IH0 K S +TROPOPAUSE T R AA1 P AH0 P AO2 Z +TROPP T R AA1 P +TROPWORLD T R AA1 P W ER0 L D +TROSCH T R AA1 SH +TROSCLAIR T R AH0 S K L EH1 R +TROSPER T R AA1 S P ER0 +TROST T R AA1 S T +TROSTEL T R AA1 S T AH0 L +TROSTLE T R AA1 S AH0 L +TROT T R AA1 T +TROTH T R OW1 TH +TROTH(1) T R AO1 TH +TROTMAN T R AA1 T M AH0 N +TROTS T R AA1 T S +TROTSKY T R AA1 T S K IY2 +TROTT T R AA1 T +TROTTED T R AA1 T IH0 D +TROTTEN T R AA1 T AH0 N +TROTTER T R AA1 T ER0 +TROTTIER T R AA1 T IY0 ER0 +TROTTING T R AA1 T IH0 NG +TROUBADOUR T R UW1 B AH0 D AO2 R +TROUBH T R UW1 B +TROUBLE T R AH1 B AH0 L +TROUBLED T R AH1 B AH0 L D +TROUBLEFIELD T R AH1 B AH0 L F IY2 L D +TROUBLEMAKER T R AH1 B AH0 L M EY2 K ER0 +TROUBLEMAKERS T R AH1 B AH0 L M EY2 K ER0 Z +TROUBLES T R AH1 B AH0 L Z +TROUBLESHOOT T R AH1 B AH0 L SH UW2 T +TROUBLESHOOTER T R AH1 B AH0 L SH UW2 T ER0 +TROUBLESHOOTING T R AH1 B AH0 L SH UW2 T IH0 NG +TROUBLESHOOTS T R AH1 B AH0 L SH UW2 T S +TROUBLESOME T R AH1 B AH0 L S AH0 M +TROUBLING T R AH1 B AH0 L IH0 NG +TROUBLING(1) T R AH1 B L IH0 NG +TROUDT T R AW1 D T +TROUGH T R AO1 F +TROUGHS T R AO1 F S +TROUNCE T R AW1 N S +TROUNCED T R AW1 N S T +TROUNCING T R AW1 N S IH0 NG +TROUNG T R AW1 NG +TROUP T R UW1 P +TROUPE T R UW1 P +TROUPE'S T R UW1 P S +TROUPES T R UW1 P S +TROUSDALE T ER1 AH0 S D EY0 L +TROUSER T R AW1 Z ER0 +TROUSERS T R AW1 Z ER0 Z +TROUT T R AW1 T +TROUT'S T R AW1 T S +TROUTMAN T R AW1 T M AH0 N +TROUTNER T R AW1 T N ER0 +TROUTT T R AW1 T +TROUTWINE T R AW1 T W AY2 N +TROVATO T R OW0 V AA1 T OW0 +TROVATORE T R OW1 V AH0 T AO2 R +TROVE T R OW1 V +TROW T R OW1 +TROWBRIDGE T R OW1 B R IH0 JH +TROWEL T R AW1 W EH0 L +TROWELL T R AA1 W EH0 L +TROWER T R AW1 ER0 +TROXEL T R AA1 K S AH0 L +TROXELL T R AA1 K S AH0 L +TROXLER T R AA1 K S L ER0 +TROY T R OY1 +TROYAN T R OY1 AH0 N +TROYANOS T R OY2 AA1 N OW0 S +TROYAT T R OY1 AE0 T +TROYER T R OY1 ER0 +TROYKA T R OY1 K AH0 +TROYU T R OY0 UW1 +TRUANCY T R UW1 AH0 N S IY0 +TRUANT T R UW1 AH0 N T +TRUAX T R UW1 AE0 K S +TRUBEY T R UW1 B IY0 +TRUBY T R UW1 B IY0 +TRUCCO T R UW1 K OW0 +TRUCE T R UW1 S +TRUCHAN T R AH1 CH AH0 N +TRUCK T R AH1 K +TRUCK'S T R AH1 K S +TRUCKED T R AH1 K T +TRUCKEE T R AH1 K IY0 +TRUCKER T R AH1 K ER0 +TRUCKERS T R AH1 K ER0 Z +TRUCKERS' T R AH1 K ER0 Z +TRUCKING T R AH1 K IH0 NG +TRUCKLOAD T R AH1 K L OW2 D +TRUCKLOADS T R AH1 K L OW2 D Z +TRUCKS T R AH1 K S +TRUCKS' T R AH1 K S +TRUCULENT T R AH1 K Y AH0 L AH0 N T +TRUDA T R UW1 D AH0 +TRUDE T R UW1 D +TRUDEAU T R UW0 D OW1 +TRUDEL T R UW1 D AH0 L +TRUDELL T R AH1 D AH0 L +TRUDGE T R AH1 JH +TRUDGED T R AH1 JH D +TRUDGEN T R AH1 JH AH0 N +TRUDGES T R AH1 JH IH0 Z +TRUDGING T R AH1 JH IH0 NG +TRUDIA T R UW1 D IY0 AH0 +TRUDIE T R UW1 D IY0 +TRUDO T R UW1 D OW0 +TRUDY T R UW1 D IY0 +TRUE T R UW1 +TRUE-VIEW T R UW1 V Y UW1 +TRUEBLOOD T R UW1 B L AH2 D +TRUELL T R UW1 AH0 L +TRUELOVE T R UW1 L AH2 V +TRUEMAN T R UH1 M AH0 N +TRUER T R UW1 ER0 +TRUESDALE T R UW1 Z D EY2 L +TRUESDELL T R UW1 Z D EH2 L +TRUEST T R UW1 IH0 S T +TRUETT T R UW1 T +TRUEX T R UW1 EH2 K S +TRUFFAUT T R UW0 F OW1 +TRUFFAUT'S T R UW0 F OW1 Z +TRUFFLE T R AH1 F AH0 L +TRUFFLES T R AH1 F AH0 L Z +TRUGLIO T R AH1 G L IY0 OW0 +TRUICKO T R UW1 K OW0 +TRUICKO(1) T R UW2 IY1 K OW0 +TRUISM T R UW1 IH0 Z AH0 M +TRUITT T R UW1 T +TRUJILLO T R UW0 HH IY1 OW0 +TRULL T R AH1 L +TRULLINGER T R AH1 L IH0 NG ER0 +TRULOCK T R AH1 L AH0 K +TRULOVE T R UW0 L OW1 V IY0 +TRULSON T R AH1 L S AH0 N +TRULUCK T R AH1 L AH0 K +TRULY T R UW1 L IY0 +TRUMAN T R UW1 M AH0 N +TRUMAN'S T R UW1 M AH0 N Z +TRUMBLE T R AH1 M B AH0 L +TRUMBO T R AH1 M B OW0 +TRUMBULL T R AH1 M B AH0 L +TRUMKA T R AH1 M K AH0 +TRUMP T R AH1 M P +TRUMP'S T R AH1 M P S +TRUMPED T R AH1 M P T +TRUMPET T R AH1 M P AH0 T +TRUMPETED T R AH1 M P AH0 T IH0 D +TRUMPETER T R AH1 M P AH0 T ER0 +TRUMPETING T R AH1 M P AH0 T IH0 NG +TRUMPETS T R AH1 M P AH0 T S +TRUMPOWER T R AH1 M P OW2 ER0 +TRUMPS T R AH1 M P S +TRUNCATE T R AH1 NG K EY2 T +TRUNCATED T R AH1 NG K EY2 T IH0 D +TRUNCATES T R AH1 NG K EY2 T S +TRUNCATING T R AH1 NG K EY2 T IH0 NG +TRUNCATION T R AH1 NG K EY2 SH AH0 N +TRUNCHEON T R AH1 N CH IH0 N +TRUNCHEONS T R AH1 N CH IH0 N Z +TRUNDLE T R AH1 N D AH0 L +TRUNDLED T R AH1 N D AH0 L D +TRUNK T R AH1 NG K +TRUNKLINE T R AH1 NG K L AY2 N +TRUNKS T R AH1 NG K S +TRUNNELL T R AH1 N AH0 L +TRUNZO T R AH1 N Z OW0 +TRUONG T R AO1 NG +TRUPIANO T R UW0 P IY0 AA1 N OW0 +TRUPIN T R UW1 P IH0 N +TRUPIN'S T R UW1 P IH0 N Z +TRUPP T R AH1 P +TRURO T R UW1 R OW0 +TRUS T R AH1 S +TRUSCOTT T R AH1 S K AH0 T +TRUSKOWSKI T R AH0 S K AO1 F S K IY0 +TRUSLER T R AH1 S AH0 L ER0 +TRUSLER(1) T R AH1 S L ER0 +TRUSLOW T R AH1 S L OW0 +TRUSS T R AH1 S +TRUSSELL T R AH1 S AH0 L +TRUSSES T R AH1 S IH0 Z +TRUST T R AH1 S T +TRUST'S T R AH1 S T S +TRUSTCO T R AH1 S T K OW0 +TRUSTCORP T R AH1 S T K AO0 R P +TRUSTED T R AH1 S T IH0 D +TRUSTEE T R AH2 S T IY1 +TRUSTEE'S T R AH2 S T IY1 Z +TRUSTEES T R AH2 S T IY1 Z +TRUSTEES' T R AH2 S T IY1 Z +TRUSTEESHIP T R AH2 S T IY1 SH IH2 P +TRUSTHOUSE T R AH1 S T HH AW2 S +TRUSTING T R AH1 S T IH0 NG +TRUSTS T R AH1 S T S +TRUSTS' T R AH1 S T S +TRUSTWORTHINESS T R AH1 S T W ER2 DH IY0 N AH0 S +TRUSTWORTHY T R AH1 S T W ER2 DH IY0 +TRUSTY T R AH1 S T IY0 +TRUSZKOWSKI T R AH0 SH K AO1 F S K IY0 +TRUTH T R UW1 TH +TRUTHFUL T R UW1 TH F AH0 L +TRUTHFULLY T R UW1 TH F AH0 L IY0 +TRUTHFULNESS T R UW1 TH F AH0 L N AH0 S +TRUTHINESS T R UW1 TH IY2 N AH0 S +TRUTHS T R UW1 TH S +TRUXAL T R AH1 K S AH0 L +TRUXILLO T R AH2 K S IH1 L OW0 +TRY T R AY1 +TRY-ON T R AY1 AA2 N +TRY-ONS T R AY1 AA2 N Z +TRYART T R AY1 AA2 R T +TRYBA T R IH1 B AH0 +TRYBUS T R IH1 B IH0 S +TRYGG T R IH1 G +TRYGSTAD T R IH1 G S T AH0 D +TRYGVE T R IH1 G V IY0 +TRYIN' T R AY1 IH0 N +TRYING T R AY1 IH0 NG +TRYING(1) T R AY1 NG +TRYON T R AY1 AH0 N +TRYOUT T R AY1 AW2 T +TRYOUTS T R AY1 AW2 T S +TRYPHENA T R IH1 F IH0 N AH0 +TRYST T R IH1 S T +TRYST(1) T R AY1 S T +TRZASKA T ER0 Z AA1 S K AH0 +TRZCINSKI T ER0 ZH IH1 N S K IY0 +TRZECIAK T ER0 Z EH1 CH IY0 AE0 K +TS T IY1 EH1 S +TSAI T S AY1 +TSAI(1) S AY1 +TSAI'S T S AY1 Z +TSAI'S(1) S AY1 Z +TSAKOS T S AA1 K OW0 S +TSANG T S AE1 NG +TSANG(1) S AE1 NG +TSAO T S AW1 +TSAO(1) S AW1 +TSAR Z AA1 R +TSAR(1) T S AA1 R +TSCHANTZ CH AE1 N T S +TSCHETTER CH EH1 T ER0 +TSCHIDA CH AY1 D AH0 +TSCHIRHART CH ER1 HH AA0 R T +TSCHOPP CH AA1 P +TSCHUDY CH UW1 D IY0 +TSCHUMI CH UW1 M IY0 +TSE T S IY1 +TSE(1) S IY1 +TSEMEL T S EH1 M AH0 L +TSENG T S EH1 NG 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UW1 D ER0 +TUDOR'S T UW1 D ER0 Z +TUE T UW1 +TUEL T UW1 L +TUELL T UW1 L +TUESDAY T UW1 Z D IY0 +TUESDAY(1) T UW1 Z D EY2 +TUESDAY(2) T Y UW1 Z D EY2 +TUESDAY'S T UW1 Z D IY0 Z +TUESDAY'S(1) T UW1 Z D EY2 Z +TUESDAY'S(2) T Y UW1 Z D EY2 Z +TUESDAYS T UW1 Z D EY2 Z +TUESDAYS(1) T UW1 Z D IY0 Z +TUESDAYS(2) T Y UW1 Z D EY2 Z +TUFA T UW1 F AH0 +TUFANO T UW0 F AA1 N OW0 +TUFF T AH1 F +TUFNEL T AH1 F N IH0 L +TUFO T UW1 F OW0 +TUFT T AH1 F T +TUFTE T AH1 F T +TUFTED T AH1 F T IH0 D +TUFTLIKE T AH1 F T L AY2 K +TUFTS T AH1 F T S +TUG T AH1 G +TUGBOAT T AH1 G B OW2 T +TUGBOATS T AH1 G B OW2 T S +TUGGED T AH1 G D +TUGGING T AH1 G IH0 NG +TUGGLE T AH1 G AH0 L +TUGMAN T AH1 G M AH0 N +TUGS T AH1 G Z +TUGWELL T AH1 G W EH2 L +TUHAN T UW2 HH AA1 N +TUINSTRA T UW0 IH1 N S T R AH0 +TUITE T UW1 T +TUITION T Y UW0 IH1 SH AH0 N +TUITIONS T UW0 IH1 SH AH0 N Z +TUK T UW1 K +TUKS T AH1 K S +TULA T UW1 L AH0 +TULANE T UW0 L EY1 N +TULEY T Y UW1 L IY0 +TULIP T UW1 L IH0 P +TULIP'S T UW1 L IH0 P S +TULIPS T UW1 L IH0 P S +TULL T AH1 L +TULLAR T AH1 L ER0 +TULLER T AH1 L ER0 +TULLEY T AH1 L IY0 +TULLIA T AH1 L IY2 AH0 +TULLIER T AH1 L IY2 ER0 +TULLIO T UW1 L IY2 OW0 +TULLIS T AH1 L IH0 S +TULLIUS T AH1 L IY2 IH0 S +TULLO T UW1 L OW0 +TULLOCH T AH1 L AH0 K +TULLOCK T AH1 L AH0 K +TULLOS T AH1 L OW0 Z +TULLY T AH1 L IY0 +TULSA T AH1 L S AH0 +TUMA T UW1 M AH0 +TUMACOCERI T UW2 M AH0 K OW1 CH ER0 IY0 +TUMAN CH UW1 M AH0 N +TUMAZOS T UW0 M AA1 Z OW0 S +TUMBLE T AH1 M B AH0 L +TUMBLED T AH1 M B AH0 L D +TUMBLER T AH1 M B L ER0 +TUMBLER'S T AH1 M B L ER0 Z +TUMBLERS T AH1 M B L ER0 Z +TUMBLES T AH1 M B AH0 L Z +TUMBLESON T AH1 M B AH0 L S AH0 N +TUMBLIN T AH1 M B L IH0 N +TUMBLING T AH1 M B AH0 L IH0 NG +TUMBLR T AH1 M B L ER0 +TUMBLR'S T AH1 M B L ER0 Z +TUMERIC T UW0 M EH1 R IH0 K +TUMESCENT T UW0 M EH1 S IH0 N T +TUMEY T UW1 M IY0 +TUMINELLO T UW0 M IY0 N EH1 L OW0 +TUMLIN T AH1 M L IH0 N +TUMLINSON T AH1 M L IH0 N S AH0 N +TUMMIES T AH1 M IY0 Z +TUMMINELLO T UW0 M IY0 N EH1 L OW0 +TUMMOND T AH1 M AH0 N D +TUMMY T AH1 M IY0 +TUMOLO T UW0 M OW1 L OW0 +TUMOR T UW1 M ER0 +TUMORS T UW1 M ER0 Z +TUMS T AH1 M Z +TUMS' T AH1 M Z +TUMULT T UW1 M AH0 L T +TUMULTUOUS T UW2 M AH1 L CH UW2 AH0 S +TUMULTY T UW1 M AH0 L T IY0 +TUNA T UW1 N AH0 +TUNABLE T UW1 N AH0 B AH0 L +TUNAFISH T UW1 N AH0 F IH0 SH +TUNAS T UW1 N AH0 Z +TUNDE T AH1 N D +TUNDRA T AH1 N D R AH0 +TUNE T UW1 N +TUNED T UW1 N D +TUNEFUL T UW1 N F AH0 L +TUNER T UW1 N ER0 +TUNES T UW1 N Z +TUNEUP T UW1 N AH2 P +TUNG T AH1 NG +TUNG'S T AH1 NG Z +TUNGATE T UW1 NG EY0 T +TUNGSRAM T AH1 NG Z R AE2 M +TUNGSROM T AH1 NG Z R AH0 M +TUNGSROM'S T AH1 NG Z R AH0 M Z +TUNGSTEN T AH1 NG S T AH0 N +TUNIC T UW1 N IH0 K +TUNICA T UW1 N IH0 K AH0 +TUNICA'S T UW1 N IH0 K AH0 Z +TUNICATE T UW1 N IH0 K AH0 T +TUNICK T AH1 N IH0 K +TUNING T UW1 N IH0 NG +TUNIS T UW1 N IH0 S +TUNIS(1) T UW2 N IY1 S +TUNISIA T UW2 N IY1 ZH AH0 +TUNISIAN T UW2 N IY1 ZH AH0 N +TUNISON T AH1 N IH0 S AH0 N +TUNISON(1) T UW1 N IH0 S AH0 N +TUNKELANG T AH2 NG K L AE1 NG +TUNKS T AH1 NG K S +TUNKU T AH1 NG K UW0 +TUNNEL T AH1 N AH0 L +TUNNEL'S T AH1 N AH0 L Z +TUNNELING T AH1 N AH0 L IH0 NG +TUNNELL T AH1 N AH0 L +TUNNELS T AH1 N AH0 L Z +TUNNEY T AH1 N IY0 +TUNNY T AH1 N IY0 +TUNSTALL T AH1 N S T AH0 L +TUOHEY T UW1 HH EY0 +TUOHY T UW1 IY0 +TUOLUMNE T W AO1 L UW0 M +TUOMI T W OW1 M IY0 +TUPA T UW1 P AH0 +TUPAC T UW1 P AO0 K +TUPELO T Y UW1 P AH0 L OW2 +TUPELO(1) T UW1 P AH0 L OW2 +TUPELOV T UW1 P AH0 L AA0 V +TUPPER T AH1 P ER0 +TUPPERWARE T AH1 P ER0 W EH2 R +TUPY T UW1 P IY0 +TURANDOT T ER0 AE1 N D AH0 T +TURANO T UH0 R AA1 N OW0 +TURBAN T ER1 B AH0 N +TURBANS T ER1 B AH0 N Z +TURBAS T ER1 B AH0 S +TURBEN T ER1 B AH0 N +TURBERVILLE T ER1 B ER0 V IH2 L +TURBETT T ER1 B IH0 T +TURBEVILLE T ER1 B V IH0 L +TURBID T ER1 B IH0 D +TURBIDITY T ER0 B IH1 D AH0 T IY0 +TURBIN T ER1 B IH0 N +TURBINE T ER1 B AY0 N +TURBINEN T ER1 B IH0 N AH0 N +TURBINES T ER1 B AY0 N Z +TURBO T ER1 B OW0 +TURBOCHARGE T ER1 B OW0 CH AA2 R JH +TURBOCHARGED T ER1 B OW0 CH AA2 R JH D +TURBOCHARGES T ER1 B OW0 CH AA2 R JH IH0 Z +TURBOCHARGING T ER1 B OW0 CH AA2 R JH IH0 NG +TURBOFAN T ER1 B OW0 F AE2 N +TURBOJET T ER1 B OW0 JH EH2 T +TURBOPROP T ER1 B OW0 P R AA2 P +TURBOPROPS T ER1 B OW0 P R AA2 P S +TURBOS T ER1 B OW0 Z +TURBOT T ER2 B OW1 +TURBOT(1) T ER1 B AH2 T +TURBOTAX T ER1 B OW0 T AE2 K S +TURBULENCE T ER1 B Y AH0 L AH0 N S +TURBULENT T ER1 B Y AH0 L AH0 N T +TURBYFILL T ER1 B IH0 F IH0 L +TURCHI T UH1 R K IY0 +TURCHIN T ER1 CH IH0 N +TURCHYN T ER1 CH IH0 N +TURCK T ER1 K +TURCO T ER1 K OW0 +TURCOTT T ER1 K AH0 T +TURCOTTE T ER0 K AO1 T +TURCOTTE'S T ER0 K AO1 T S +TURE T UH1 R +TUREK T Y UW1 R IH0 K +TURENNE T Y UW1 R IH0 N +TURF T ER1 F +TURGEON T ER1 JH IH0 N +TURGID T ER1 JH IH0 D +TURGUT T ER1 G AH0 T +TURI T UH1 R IY0 +TURIN T Y UH1 R IH0 N +TURIN(1) T UH1 R IH0 N +TURING T UH1 R IH0 NG +TURISMO T UH1 R IH0 S M OW0 +TURK T ER1 K +TURKEL T ER1 K AH0 L +TURKEY T ER1 K IY0 +TURKEY'S T ER1 K IY0 Z +TURKEYS T ER1 K IY0 Z +TURKIC T ER1 K IH0 K +TURKINGTON T ER1 K IH0 NG T AH0 N +TURKISH T ER1 K IH0 SH +TURKMEN T ER1 K M EH2 N +TURKMENISTAN T ER2 K M EH1 N IH0 S T AE2 N +TURKO T ER1 K OW0 +TURKOVICH T ER1 K AH0 V IH0 CH +TURKS T ER1 K S +TURLEY T ER1 L IY0 +TURLINGTON T ER1 L IH0 NG T AH0 N +TURLOUGH T ER1 L OW0 +TURLOUGH(1) T ER1 L AW0 +TURMAN T ER1 M AH0 N +TURMEL T ER1 M AH0 L +TURMERIC T ER1 M AH0 R IH2 K +TURMOIL T ER1 M OY2 L +TURN T ER1 N +TURN-OUT T ER1 N AW2 T +TURNABOUT T ER1 N AH0 B AW2 T +TURNAGE T ER1 N IH0 JH +TURNAROUND T ER1 N ER0 AW2 N D +TURNAROUNDS T ER1 N ER0 AW2 N D Z +TURNBAUGH T ER1 N B AO0 +TURNBO T UH1 R N B OW0 +TURNBOUGH T ER1 N B AW2 +TURNBOW T ER1 N B OW0 +TURNBRIDGE T ER1 N B R IH2 JH +TURNBULL T ER1 N B UH2 L +TURNCOAT T ER1 N K OW2 T +TURNDOWN T ER1 N D AW2 N +TURNED T ER1 N D +TURNER T ER1 N ER0 +TURNER'S T ER1 N ER0 Z +TURNEY T ER1 N IY0 +TURNHAM T ER1 N HH AH0 M +TURNING T ER1 N IH0 NG +TURNIP T ER1 N AH0 P +TURNIPS T ER1 N AH0 P S +TURNIPSEED T ER0 N IH1 P S IY0 D +TURNKEY T ER1 N K IY2 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UW1 Z IY0 Z +UZMACK UW1 Z M AE2 K +UZZELL UW0 Z EH1 L +UZZLE AH1 Z AH0 L +U_L Y UW1 EH1 L +U_S_M_C Y UW1 EH1 S EH1 M S IY1 +V V IY1 +V'S V IY1 Z +V. V IY1 +V.'S V IY1 Z +V.A. V IY2 EY1 +V.S V IY1 Z +VAAL V AA1 L +VAAPENFABRIKK V AA2 P EH1 N F AH0 B R IH0 K +VAAPENFABRIKK(1) V AA1 P AH0 N F AA2 B R IH0 K +VACA V AE1 K AH0 +VACANCIES V EY1 K AH0 N S IY0 Z +VACANCY V EY1 K AH0 N S IY0 +VACANT V EY1 K AH0 N T +VACANTI V AH0 K AE1 N T IY0 +VACATE V EY1 K EY0 T +VACATED V EY0 K EY1 T IH0 D +VACATED(1) V EY1 K EY0 T IH0 D +VACATING V EY1 K EY0 T IH0 NG +VACATION V EY0 K EY1 SH AH0 N +VACATIONED V EY0 K EY1 SH AH0 N D +VACATIONER V EY0 K EY1 SH AH0 N ER0 +VACATIONERS V EY0 K EY1 SH AH0 N ER0 Z +VACATIONERS' V EY0 K EY1 SH AH0 N ER0 Z +VACATIONING V EY0 K EY1 SH AH0 N IH0 NG +VACATIONING(1) V EY0 K EY1 SH N IH0 NG +VACATIONS V EY0 K EY1 SH AH0 N Z +VACAVILLE V AE1 K AH0 V IH2 L +VACCA V AE1 K AH0 +VACCARELLA V AA0 K ER0 EH1 L AH0 +VACCARO V AH0 K AA1 R OW0 +VACCINA V AE2 K S IY1 N AH0 +VACCINATE V AE1 K S AH0 N EY0 T +VACCINATED V AE1 K S AH0 N EY0 T IH0 D +VACCINATION V AE0 K S AH0 N EY1 SH AH0 N +VACCINATIONS V AE2 K S AH0 N EY1 SH AH0 N Z +VACCINE V AE2 K S IY1 N +VACCINE'S V AE2 K S IY1 N Z +VACCINES V AE2 K S IY1 N Z +VACCINIA V AH0 CH IY1 N IY0 AH0 +VACCO V AE1 K OW0 +VACEK V AA1 CH EH2 K +VACHA V AE1 CH AH0 +VACHON V AE1 CH AH0 N +VACILLATE V AE1 S AH0 L EY2 T +VACILLATED V AE1 S AH0 L EY0 T IH0 D +VACILLATES V AE1 S AH0 L EY2 T S +VACILLATING V AE1 S AH0 L EY2 T IH0 NG +VACILLATION V AE2 S AH0 L EY1 SH AH0 N +VACLAV V AE1 K L AA2 V +VACLAV(1) V AA1 K L AA2 V +VACLAVIK V AE1 K L AH0 V IH0 K +VACUOUS V AE1 K Y UW0 AH0 S +VACUTAINER V AE1 K Y UW0 T EY2 N ER0 +VACUUM V AE1 K Y UW0 M +VACUUMED V AE1 K Y UW0 M D +VACUUMING V AE1 K Y UW0 M IH0 NG +VACUUMS V AE1 K Y UW0 M Z +VADALA V AA0 D AA1 L AH0 +VADAS V AA1 D AA0 Z +VADEHRA V AH0 D EY1 R AH0 +VADEN V EY1 D AH0 N +VADER V EY1 D ER0 +VADIM V AA0 D IY1 M +VADNAIS V AH0 D N EY1 +VADNEY V AE1 D N IY0 +VAETH V IY1 TH +VAGABOND V AE1 G AH0 B AA0 N D +VAGABONDS V AE1 G AH0 B AA0 N D Z +VAGARIES V EY1 G ER0 IY0 Z +VAGARY V EY1 G ER0 IY0 +VAGELOS V AH0 JH EH1 L OW0 S +VAGINA V AH0 JH AY1 N AH0 +VAGINAL V AH0 JH AY1 N AH0 L +VAGRANCY V EY1 G R AH0 N S IY0 +VAGRANT V EY1 G R AH0 N T +VAGRANTS V EY1 G R AH0 N T S +VAGUE V EY1 G +VAGUELY V EY1 G L IY0 +VAGUENESS V EY1 G N IH0 S +VAGUER V EY1 G ER0 +VAGUEST V EY1 G IH0 S T +VAGUINE V AH0 G W IY1 N +VAHEY V AE1 HH EY2 +VAHID V AA0 HH IY1 D +VAHL V AA1 L +VAHLE V EY1 HH AH0 L +VAIL V EY1 L +VAILAB V EY1 L AE2 B +VAILE V EY1 L +VAILLANCOURT V EY1 L AH0 N K AO2 R T +VAIN V EY1 N +VAINLY V EY1 N L IY0 +VAJDA V AY1 D AH0 +VAJNA V AY1 N AH0 +VAKUF V AE1 K AH2 F +VAL V AE1 L +VALA V AA1 L AH0 +VALABLE V AE1 L AH0 B AH0 L +VALADE V AA0 L AA1 D EY0 +VALADEZ V AA0 L AA1 D EH0 Z +VALASEK V AH0 L AA1 S EH0 K +VALBORGA V AA0 L B AO1 R G AH0 +VALCOURT V AH0 L K AO1 R T +VALDA V AA1 L D AH0 +VALDEMAR V AA0 L D EY0 M AA1 R +VALDERRAMA V AA0 L D EH0 R AA1 M AH0 +VALDES V AE0 L D EH1 Z +VALDES-PEREZ V AE2 L D EH1 Z P ER0 EH1 Z +VALDESHARI V AE2 L D EH0 SH AA1 R IY0 +VALDEZ V AE0 L D EH1 Z +VALDIS V AE1 L D IH0 S +VALDIVIA V AA0 L D IY1 V IY0 AH0 +VALDOSTA V AE2 L D AO1 S T AH0 +VALDOVINOS V AA0 L D OW0 V IY1 N OW0 Z +VALE V EY1 L +VALEA V AH0 L IY1 AH0 +VALEDA V AA0 L EY1 D AH0 +VALEDICTORIAN V AE2 L AH0 D IH2 K T AO1 R IY0 AH0 N +VALEDICTORY V AE2 L AH0 D IH1 K T ER0 IY0 +VALEK V AA1 L EH0 K +VALENCE V EY1 L AH0 N S +VALENCIA V AH0 L EH1 N S IY0 AH0 +VALENCIA'S V AH0 L EH1 N S IY0 AH0 Z +VALENCIENNE V AH0 L EH1 N S IY0 EH2 N +VALENS V AE1 L AH0 N Z +VALENSUELA V AE2 L AH0 N Z W EY1 L AH0 +VALENSUELA'S V AE2 L AH0 N Z W EY1 L AH0 Z +VALENT V AE1 L AH0 N T +VALENTA V AH0 L EH1 N T AH2 +VALENTE V AA0 L EH1 N T IY2 +VALENTI V AA0 L EH1 N T IY2 +VALENTIA V AA0 L EH1 N SH AH0 +VALENTIN V AA2 L EH1 N T IY2 N +VALENTINA V AA2 L EH0 N T IY1 N AH0 +VALENTINE V AE1 L AH0 N T AY2 N +VALENTINE'S V AE1 L AH0 N T AY2 N Z +VALENTINES V AE1 L AH0 N T AY2 N Z +VALENTINI V AE2 L AH0 N T IY1 N IY0 +VALENTINO V AE2 L AH0 N T IY1 N OW0 +VALENTINO'S V AE2 L AH0 N T IY1 N OW0 Z +VALENZA V AH0 L EH1 N Z AH0 +VALENZANO V AE2 L EH0 N Z AA1 N OW0 +VALENZUELA V AA0 L EH0 N Z UW1 L AH0 +VALEO V AE1 L IY0 OW0 +VALERA V AH0 L EH1 R AH0 +VALERI V AA0 L EH1 R IY0 +VALERIA V AH0 L IY1 R IY0 AH0 +VALERIAN V AH0 L IH1 R IY0 AH0 N +VALERIANO V AA0 L ER0 IY0 AA1 N OW0 +VALERIE V AE1 L ER0 IY0 +VALERIO V AH0 L IY1 R IY0 OW0 +VALERO V AH0 L EH1 R OW0 +VALERY V AE1 L ER0 IY0 +VALES V EY1 L Z +VALESKA V AA0 L EY1 S K AH0 +VALET V AE0 L EY1 +VALHALLA V AE2 L HH AE1 L AH0 +VALHI V AE1 L HH IY0 +VALIA V AE1 L Y AH0 +VALIANT V AE1 L Y AH0 N T +VALIANTLY V AE1 L Y AH0 N T L IY0 +VALID V AE1 L IH0 D +VALIDA V AA0 L IY1 D AH0 +VALIDATE V AE1 L AH0 D EY0 T +VALIDATED V AE1 L AH0 D EY0 T IH0 D +VALIDATES V AE1 L AH0 D EY2 T S +VALIDATING V AE1 L AH0 D EY2 T IH0 NG +VALIDATION V AE2 L AH0 D EY1 SH AH0 N +VALIDED V AE1 L AH0 D IH0 D +VALIDITY V AH0 L IH1 D IH0 T IY0 +VALIDLY V AE1 L IH0 D L IY0 +VALIENTE V AA2 L IY0 EH1 N T IY2 +VALIN V AE1 L IH0 N +VALIQUETTE V AE1 L IH0 K EH2 T +VALIS V AE1 L IH0 S +VALIUM V AE1 L IY2 AH0 M +VALK V AO1 K +VALKO V AE1 L K OW0 +VALKYRIE V AE2 L K IY1 R IY2 AH0 +VALLA V AE1 L AH0 +VALLADARES V AA0 L AA0 D AA1 R EH0 S +VALLANCE V AE1 L AH0 N S +VALLANDINGHAM V AE0 L AH1 N D IH0 NG HH AE2 M +VALLARIO V AA0 L AA1 R IY0 OW0 +VALLARTA V AE2 L AA1 R T AA0 +VALLAS V AE1 L AH0 Z +VALLE V EY1 L +VALLEAU V AH0 L OW1 +VALLEE V AE1 L IY0 +VALLEGRANDE V AE2 L IY0 G R AE1 N D IY0 +VALLEGRANDE(1) V AE2 L IY0 G R AE1 N D +VALLEJO V AA0 L EY1 Y OW0 +VALLEJOS V AA0 L EY1 Y OW0 Z +VALLELY V EY1 L IY0 +VALLELY(1) V AE1 L IY0 +VALLERY V AE1 L ER0 IY0 +VALLES V EY1 L Z +VALLETTE V AE2 L EH1 T +VALLEY V AE1 L IY0 +VALLEY'S V AE1 L IY0 Z +VALLEYS V AE1 L IY0 Z +VALLEZ V AA0 L EH1 Z +VALLI V AE1 L IY0 +VALLIANT V AA0 L IY1 AH0 N T +VALLIE V AO1 L IY0 +VALLIER V AE1 L IY0 ER0 +VALLIERE V AE1 L IY0 EH0 R +VALLIS V AE1 L IH0 S +VALLO V AE1 L OW0 +VALLONE V AA0 L OW1 N IY0 +VALLOT V AE1 L AH0 T +VALLS V AO1 L Z +VALMEYER V AE1 L M AY0 ER0 +VALMONT V AO1 L M AA2 N T +VALOIS V AE0 L W AA1 +VALONE V AH0 L OW1 N +VALONIA V AH0 L OW1 N Y AH0 +VALOR V AE1 L ER0 +VALOREE V AE1 L ER0 IY1 +VALORES V AH0 L AO1 R EH0 Z +VALPARAISO V AE2 L P ER0 EY1 S OW0 +VALSELLA V AO0 L S EH1 L AH0 +VALSPAR V AE1 L Z P AA0 R +VALTEK V AO1 L T EH2 K +VALTIERRA V AA0 L T IH1 R AH0 +VALU V AE1 L Y UW0 +VALUABLE V AE1 L Y AH0 B AH0 L +VALUABLE(1) V AE1 L Y UW0 B AH0 L +VALUABLES V AE1 L Y AH0 B AH0 L Z +VALUABLES(1) V AE1 L Y UW0 B AH0 L Z +VALUATION V AE0 L Y UW0 EY1 SH AH0 N +VALUATIONS V AE0 L Y UW0 EY1 SH AH0 N Z +VALUE V AE1 L Y UW0 +VALUED V AE1 L Y UW0 D +VALUELESS V AE1 L Y UW0 L AH0 S +VALUEPOINT V AE1 L Y UW0 P OY2 N T +VALUES V AE1 L Y UW0 Z +VALUES' V AE1 L Y UW0 Z +VALUEVISION V AE1 L Y UW0 V IH2 ZH AH0 N +VALUING V AE1 L Y UW0 IH0 NG +VALUJET V AE1 L Y UW0 JH EH2 T +VALUJET'S V AE1 L Y UW0 JH EH2 T S +VALUKAS V AH0 L UW1 K AH0 S +VALVANO V AA0 L V AA1 N OW0 +VALVE V AE1 L V +VALVERDE V AA0 L V EH1 R D EY0 +VALVES V AE1 L V Z +VALVO V AA1 L V OW0 +VALVOLINE V AE1 L V AH0 L IY2 N +VAMOS V AA1 M OW0 Z +VAMP V AE1 M P +VAMPIRE V AE1 M P AY0 R +VAMPIRE'S V AE1 M P AY0 R Z +VAMPIRES V AE1 M P AY0 R Z +VAMPIRIC V AE0 M P IH1 R IH0 K +VAN V AE1 N +VANA V AE1 N AH0 +VANACKER V AE0 N AE1 K ER0 +VANACORE V AA0 N AA0 K AO1 R IY0 +VANADIUM V AH0 N EY1 D IY0 AH0 M +VANAKEN V AE1 N AH0 K AH0 N +VANALLEN V AH0 N AO1 L AH0 N +VANALSTINE V AE0 N AE1 L S T IY0 N +VANALSTYNE V AE1 N AH0 L S T AY2 N +VANAMAN V AE0 N AO1 M AH0 N +VANAMBURG V AE0 N AE1 M B ER0 G +VANAMBURGH V AE0 N AE1 M B ER0 G +VANANTWERP V AH0 N AE1 N T W ER0 P +VANARSDALE V AE1 N ER0 Z D EY2 L +VANARSDALL V AH0 N AA1 R S D AH0 L +VANASSE V AE0 N AE1 S +VANATTA V AA0 N AA1 T AH0 +VANATTER V AA0 N AE1 T ER0 +VANAUKEN V AE0 N AW1 K AH0 N +VANAUSDALL V AE0 N AW1 S D AH0 L +VANBEBBER V AE2 N B EH1 B ER0 +VANBEEK V AE2 N B IY1 K +VANBENSCHOTEN V AE0 N B EH1 N SH AH0 T AH0 N +VANBERGEN V AE0 N B ER1 G AH0 N +VANBIBBER V AE2 N B IH1 B ER0 +VANBIESBROUCK V AE2 N B IY1 AH0 S B R UW2 K +VANBLARCOM V AE2 N B L AA1 R K AH0 M +VANBLARICOM V AE2 N B L AE1 R IH0 K AH0 M +VANBROCKLIN V AE2 N B R AA1 K L IH0 N +VANBRUNT V AE2 N B R AH1 N T +VANBUREN V AE0 N B Y UW1 R AH0 N +VANBUSKIRK V AE2 N B AH1 S K ER0 K +VANCAMP V AE2 N K AE1 M P +VANCAMPEN V AE2 N K AE1 M P AH0 N +VANCE V AE1 N S +VANCIL V AE1 N S AH0 L +VANCISE V AA1 N CH AY0 S +VANCLEAVE V AE1 N K L AH0 V +VANCLEEF V AE2 N K L IY1 F +VANCLEVE V AE2 N K L IY1 V +VANCOMYCIN V AE2 N K OW0 M AY1 S IH0 N +VANCOTT V AH0 N K AA1 T +VANCOURT V AH0 N K AO1 R T +VANCOUVER V AE0 N K UW1 V ER0 +VANCOUVER'S V AE0 N K UW1 V ER0 Z +VANCURA V AA0 N K UH1 R AH0 +VANCUREN V AE0 N K Y UW1 R AH0 N +VANDAELE V AE0 N D EH1 L +VANDAGRIFF V AE2 N D AE1 G R IH0 F +VANDAGRIFF(1) V AE1 N D AH0 G R IH0 F +VANDAL V AE1 N D AH0 L +VANDALEN V AE2 N D AE1 L AH0 N +VANDALISM V AE1 N D AH0 L IH0 Z AH0 M +VANDALIZE V AE1 N D AH0 L AY2 Z +VANDALIZED V AE1 N D AH0 L AY2 Z D +VANDALIZING V AE1 N D AH0 L AY2 Z IH0 NG +VANDALL V AE2 N D AO1 L +VANDALS V AE1 N D AH0 L Z +VANDAM V AE2 N D AE1 M +VANDAMME V AE2 N D AE1 M +VANDE V AE1 N D +VANDEBERG V AE1 N D AH0 B ER0 G +VANDECAR V AE1 N D AH0 K AA2 R +VANDEGRIFT V AE1 N D AH0 G R IH0 F T +VANDEHEI V AE1 N D AH0 HH AY0 +VANDEHEY V AE1 N D IH0 HH IY0 +VANDELLA V AE2 N D EH1 L AH0 +VANDELLAS V AE2 N D EH1 L AH0 Z +VANDEMAN V AE1 N D AH0 M AH0 N +VANDEMARK V AE1 N D AH0 M AA2 R K +VANDEN V AE1 N D AH0 N +VANDENBERG V AE1 N D AH0 N B ER0 G +VANDENBERGH V AE1 N D AH0 N B ER0 G +VANDENBERGHE V AE1 N D AH0 N B ER0 G +VANDENBOOM V AE1 N D AH0 N B UW2 M +VANDENBOS V AE1 N D AH0 N B OW0 Z +VANDENBOSCH V AE1 N D AH0 N B AO2 SH +VANDENBRINK V AE1 N D AH0 N B R IH0 NG K +VANDENBURG V AE1 N D AH0 N B ER0 G +VANDENBURGH V AE1 N D AH0 N B ER0 G +VANDENHEUVEL V AE1 N D AH0 N HH OY0 V AH0 L +VANDER V AE1 N D ER0 +VANDERBECK V AE1 N D ER0 B EH2 K +VANDERBEEK V AE1 N D ER0 B IY2 K +VANDERBERG V AE1 N D ER0 B ER0 G +VANDERBILT V AE1 N D ER0 B IH0 L T +VANDERBURG V AE1 N D ER0 B ER0 G +VANDERBUSH V AE1 N D ER0 B UH0 SH +VANDERCOOK V AE1 N D ER0 K UH2 K +VANDERFORD V AE1 N D ER0 F ER0 D +VANDERGRIFF V AE1 N D ER0 G R IH0 F +VANDERGRIFT V AE1 N D ER0 G R IH0 F T +VANDERGRIFT'S V AE1 N D ER0 G R IH2 F T S +VANDERHEIDE V AE1 N D ER0 HH AY2 D +VANDERHEIDEN V AE1 N D ER0 HH AY0 D AH0 N +VANDERHEYDEN V AE1 N D ER0 HH EY0 D AH0 N +VANDERHOEF V AE1 N D ER0 HH OW2 F +VANDERHOFF V AE1 N D ER0 HH AO2 F +VANDERHOOF V AE1 N D ER0 HH UH2 F +VANDERHORST V AE1 N D ER0 HH AO2 R S T +VANDERKOLK V AE1 N D ER0 K OW2 K +VANDERKOOI V AE1 N D ER0 K UW2 IY0 +VANDERLAAN V AE1 N D ER0 L AA2 N +VANDERLEEST V AE1 N D ER0 AH0 L IY2 S T +VANDERLINDE V AE1 N D ER0 L IH2 N D +VANDERLINDEN V AE1 N D ER0 L IH2 N D AH0 N +VANDERLIP V AE1 N D ER0 L IH2 P +VANDERMARK V AE1 N D ER0 M AA2 R K +VANDERMEER V AE1 N D ER0 M IH2 R +VANDERMEULEN V AE1 N D ER0 M OY2 L AH0 N +VANDERMOLEN V AE1 N D ER0 M AA2 L AH0 N +VANDERPLOEG V AE1 N D ER0 P L OW2 G +VANDERPOEL V AE1 N D ER0 P OW2 L +VANDERPOL V AE1 N D ER0 P AO2 L +VANDERPOOL V AE1 N D ER0 P UW2 L +VANDERSCHAAF V AE1 N D ER0 SH AA2 F +VANDERSLICE V AE1 N D ER0 S L AY2 S +VANDERSLUIS V AE1 N D ER0 S L UW2 IH0 S +VANDERSLUIS(1) V AE1 N D ER0 S L UW2 S +VANDERVEEN V AE1 N D ER0 V IY2 N +VANDERVEER V AE1 N D ER0 V IH2 R +VANDERVELDE V AE1 N D ER0 V EH2 L D +VANDERVELDEN V AE1 N D ER0 V EH2 L D AH0 N +VANDERVLIET V AE1 N D ER0 V L IY2 T +VANDERVOORT V AE1 N D ER0 V UH2 R T +VANDERVORT V AE1 N D ER0 V AO2 R T +VANDERWAL V AE1 N D ER0 W AA2 L +VANDERWALL V AE1 N D ER0 W AA2 L +VANDERWEELE V AE1 N D ER0 W IY2 L +VANDERWEIDE V AE1 N D ER0 W AY2 D +VANDERWERF V AE1 N D ER0 W ER2 F +VANDERWERFF V AE1 N D ER0 W ER2 F +VANDERWILT V AE1 N D ER0 W IH2 L T +VANDERWOUDE V AE1 N D ER0 W AW2 D +VANDERZANDEN V AE1 N D ER0 Z AE2 N D AH0 N +VANDERZEE V AE1 N D ER0 Z IY2 +VANDEUSEN V AE0 N D OY1 S AH0 N +VANDEVANDER V AE1 N D AH0 V AE2 N D ER0 +VANDEVEER V AE1 N D AH0 V IH2 R +VANDEVELDE V AE1 N D AH0 V EH2 L D +VANDEVEN V AE1 N D AH0 V AH0 N +VANDEVENDER V AE1 N D AH0 V EH2 N D ER0 +VANDEVENTER V AE1 N D AH0 V AH0 N T ER0 +VANDEVER V AE2 N D IY1 V ER0 +VANDEVOORDE V AE1 N D AH0 V UH0 R D +VANDEVOORT V AE1 N D AH0 V UH0 R T +VANDEWALKER V AE1 N D AH0 W AO2 K ER0 +VANDEWALLE V AE0 N D UW1 EY0 L +VANDEWATER V AE1 N D AH0 W AO0 T ER0 +VANDEZANDE V AE1 N D AH0 Z IH0 N D +VANDINE V AE2 N D AY1 N +VANDIVER V AE1 N D AY2 V ER0 +VANDIVIER V AE0 N D AY1 V IY0 ER0 +VANDOREN V AE0 N D AO1 R AH0 N +VANDORN V AE0 N D AO1 R N +VANDRIEL V AE2 N D R IY1 L +VANDROSS V AE2 N D R AO1 S +VANDUNK V AE2 N D AH1 NG K +VANDUSEN V AE0 N D UW1 S AH0 N +VANDUYN V AE2 N D AY1 N +VANDUYNE V AE2 N D AY1 N +VANDUZER V AE2 N D UW1 Z ER0 +VANDYCK V AE0 N D IH1 K +VANDYK V AE1 N D IH0 K +VANDYKE V AE2 N D AY1 K +VANDYKEN V AE2 N D AY1 K AH0 N +VANDYNE V AE1 N D AY2 N +VANE V EY1 N +VANEATON V AE1 N AH0 T AA0 N +VANECEK V AE0 N EH1 S IH0 K +VANECK V AA1 N EH0 K +VANEGAS V AE0 N IY1 G AH0 Z +VANEK V AE0 N EH1 K +VANELLA V AH0 N EH1 L AH0 +VANENGEN V AE0 N EH1 NG AH0 N +VANEPPS V AE0 N EH1 P S +VANES V EY1 N Z +VANESS V AE1 N AH0 S +VANESSA V AH0 N EH1 S AH0 +VANESSEN V AA1 N IH0 S AH0 N +VANETTEN V AE1 N EH1 T AH0 N +VANEVERY V AH0 N EH1 V R IY0 +VANFLEET V AE2 N F L IY1 T +VANFOSSAN V AE0 N F AA1 S AH0 N +VANFOSSEN V AE0 N F AA1 S AH0 N +VANG V AE1 NG +VANGEL V EY1 NG G AH0 L +VANGELDER V EY1 NG G IH0 L D ER0 +VANGIE V AE1 NG IY0 +VANGIESON V AE1 NG G IY0 Z AH0 N +VANGILDER V AE1 NG G IH0 L D ER0 +VANGORDEN V AE1 NG G ER0 D AH0 N +VANGORDER V AE1 NG G ER0 D ER0 +VANGORP V AE1 NG G ER0 P +VANGUARD V AE1 N G AA2 R D +VANGUARD'S V AE1 N G AA2 R D Z +VANGUILDER V AE0 N G AY1 L D ER0 +VANGUNDY V AH0 NG G AH1 N D IY0 +VANGY V AE1 N JH IY0 +VANHALL V AE2 N HH AO1 L +VANHANDEL V AE2 N HH AE1 N D AH0 L +VANHECKE V AE2 N HH EH1 K +VANHEEL V AE2 N HH IY1 L +VANHISE V AE0 N HH AY1 Z +VANHOESEN V AE2 N HH OW1 S AH0 N +VANHOOK V AE2 N HH UH1 K +VANHOOSE V AE2 N HH UW1 S +VANHOOSER V AE2 N HH UW1 Z ER0 +VANHOOZER V AE2 N HH UW1 Z ER0 +VANHORN V AE0 N HH AO1 R N +VANHORNE V AE0 N HH AO1 R N +VANHOUSEN V AE1 N HH AW2 S AH0 N +VANHOUTEN V AE0 N HH AA1 UW0 T AH0 N +VANHOVE V AE0 N HH AH1 V +VANHOY V AE1 N HH OY0 +VANHUSS V AE2 N HH AH1 S +VANHYNING V AE2 N HH AY1 N IH0 NG +VANIA V AA1 N IY0 AH0 +VANIER V AE0 N IY1 ER0 +VANIK V AA1 N IH0 K +VANILLA V AH0 N IH1 L AH0 +VANILLI V AH0 N IH1 L IY0 +VANILLIN V AH0 N IH1 L IH0 N +VANISH V AE1 N IH0 SH +VANISHED V AE1 N IH0 SH T +VANISHES V AE1 N IH0 SH IH0 Z +VANISHING V AE1 N IH0 SH IH0 NG +VANITIES V AE1 N AH0 T IY0 Z +VANITY V AE1 N AH0 T IY0 +VANITY(1) V AE1 N IH0 T IY0 +VANKAMPEN V AE2 N K AE1 M P AH0 N +VANKEUREN V AE1 NG K OY0 R AH0 N +VANKIRK V AE1 NG K ER0 K +VANKLEECK V AE1 NG K L IY2 K +VANKUREN V AE1 NG K Y UW0 R AH0 N +VANLANDINGHAM V AE2 N L AE1 N D IH0 NG HH AE2 M +VANLANEN V AE2 N L AE1 N AH0 N +VANLANINGHAM V AE2 N L AE1 N IH0 NG HH AE2 M +VANLEER V AE0 N L IH1 R +VANLEEUWEN V AE0 N L UW1 AH0 N +VANLEUVEN V AE0 N L OY1 V AH0 N +VANLIERE V AE0 N L IH1 R +VANLIEW V AE1 N L IY0 UW0 +VANLOAN V AE1 N L OW2 N +VANLOO V AE1 N L UW2 +VANLUE V AE2 N L UW1 +VANLUVEN V AE2 N L UW1 V AH0 N +VANMAANEN V AE2 N M AA1 N AH0 N +VANMARTER V AE0 N M AA1 R T ER0 +VANMATRE V AE0 N M EY1 T ER0 +VANMETER V AE0 N M IY1 T ER0 +VANMETRE V AE0 N M IY1 T ER0 +VANN V AE1 N +VANNA V AE1 N AH0 +VANNAME V AE1 N AH0 M +VANNATER V AE0 N AE1 T ER0 +VANNATTA V AA0 N AA1 T AH0 +VANNATTER V AE0 N AE1 T ER0 +VANNATTER'S V AE0 N AE1 T ER0 Z +VANNELLI V AA0 N EH1 L IY0 +VANNESS V AE0 N IY1 S +VANNEST V AE0 N IY1 S T +VANNGUYEN V AE0 N G IY1 AH0 N +VANNGUYEN(1) V AE2 N UW0 Y EH1 N +VANNI V AE1 N IY0 +VANNICE V AE1 N IH0 S +VANNIE V AE1 N IY0 +VANNORMAN V AE0 N AO1 R M AH0 N +VANNORTWICK V AH0 N AO1 R T W IH0 K +VANNOSTRAND V AE0 N AA1 S T R AH0 N D +VANNOTE V AE0 N OW1 T +VANNOY V AE1 N OY0 +VANNUCCI V AA0 N UW1 CH IY0 +VANNY V AE1 N IY0 +VANO V AA1 N OW0 +VANORA V AE1 N ER0 AH0 +VANORDEN V AE0 N AO1 R D AH0 N +VANORDER V AE0 N AO1 R D ER0 +VANORMAN V AE0 N AO1 R M AH0 N +VANORNUM V AE0 N AO1 R N AH0 M +VANOSDOL V AE0 N AA1 S D AH0 L +VANOSS V AE0 N AA1 S +VANOSTRAND V AE0 N AA1 S T R AH0 N D +VANOUS V AE1 N AH0 S +VANOVER V AE1 N OW2 V ER0 +VANPATTEN V AE0 N P AE1 T AH0 N +VANPELT V AE2 N P EH1 L T +VANPUTTEN V AE0 N P AH1 T AH0 N +VANQUISH V AE1 NG K W IH0 SH +VANQUISHED V AE1 NG K W IH0 SH T +VANRIPER V AE2 N R AY1 P ER0 +VANROEKEL V AE2 N R OW1 K AH0 L +VANROSSUM V AE2 N R AA1 S AH0 M +VANRYN V AE2 N R IH1 N +VANS V AE1 N Z +VANSANDT V AE2 N S AE1 N T +VANSANT V AA1 N S AH0 N T +VANSCHAICK V AE0 N SH AY1 K +VANSCHOICK V AE2 N SH OY1 K +VANSCIVER V AE0 N S K AY1 V ER0 +VANSCOY V AE1 N S K OY2 +VANSCOYOC V AE2 N S K OY1 AA0 K +VANSCYOC V AE1 N S IY0 AA2 K +VANSELOW V AE1 N S IH0 L OW0 +VANSICKEL V AE2 N S IH1 K AH0 L +VANSICKLE V AE2 N S IH1 K AH0 L +VANSKIKE V AE2 N S K AY1 K +VANSKIVER V AE2 N S K AY1 V ER0 +VANSLOOTEN V AE2 N S L UW1 T AH0 N +VANSLYKE V AE2 N S L AY1 K +VANSTONE V AE2 N S T OW1 N +VANSTORY V AE2 N S T AO1 R IY0 +VANSTRATEN V AE2 N S T R EY1 T AH0 N +VANSYCKLE V AE1 N S AY0 K AH0 L +VANTAGE V AE1 N T AH0 JH +VANTAGE(1) V AE1 N T IH0 JH +VANTAGE'S V AE1 N T IH0 JH IH0 Z +VANTAGES V AE1 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V AE2 K S T EY1 SH AH0 N +VAYDA V EY1 D AH0 +VAZ V AE1 Z +VAZQUEZ V AE0 S K EH1 Z +VE V IY1 +VEACH V IY1 CH +VEAL V IY1 L +VEALE V IY1 L +VEALS V IY1 L Z +VEASEY V IY1 Z IY0 +VEASLEY V IY1 Z L IY0 +VEATCH V IY1 CH +VEAZEY V IY1 Z IY0 +VEAZIE V IY1 Z IY0 +VEBA V IY1 B AH0 +VECCHIARELLI V EH0 K IY0 AA0 R EH1 L IY0 +VECCHIO V EH1 K IY0 OW0 +VECCHIONE V EH2 K IY0 OW1 N IY0 +VECCI V EH1 CH IY0 +VECELLIO V EH0 CH EH1 L IY0 OW0 +VECTOR V EH1 K T ER0 +VECTORS V EH1 K T ER0 Z +VECTRA V EH1 K T R ER0 +VEDA V EY1 D AH0 +VEDDER V EH1 D ER0 +VEDETTA V IH2 D EH1 T AH0 +VEDETTE V IH0 D EH1 T +VEDIS V EY1 D IH0 S +VEDULA V EH2 D UW1 L AH0 +VEE V IY1 +VEECH V IY1 CH +VEECO V IY1 K OW0 +VEEDER V IY1 D ER0 +VEEGENAN V IY1 G AH0 N AH0 N +VEEN V IY1 N +VEENSTRA V IY1 N S T R AH0 +VEEP V IY1 P +VEER V IH1 R +VEERED V IH1 R D +VEERING V IH1 R IH0 NG +VEERS V IH1 R Z +VEES V IY1 Z +VEGA V EY1 G AH0 +VEGAN V EH1 G AH0 N +VEGANS V EH1 G AH0 N Z +VEGAS V EY1 G AH0 S +VEGEMITE V EH1 JH AH0 M AY2 T +VEGESNA V EH0 G EH1 S N AH0 +VEGETABLE V EH1 JH T AH0 B AH0 L +VEGETABLES V EH1 JH T AH0 B AH0 L Z +VEGETAL V EH1 JH AH0 T AH0 L +VEGETARIAN V EH2 JH AH0 T EH1 R IY2 AH0 N +VEGETARIANISM V EH2 JH AH0 T EH1 R IY2 AH0 N IH2 Z AH0 M +VEGETARIANS V EH2 JH AH0 T EH1 R IY2 AH0 N Z +VEGETATE V EH1 JH AH0 T EY2 T +VEGETATION V EH2 JH AH0 T EY1 SH AH0 N +VEGETATIVE V EH2 JH AH0 T EY1 T IH0 V +VEGGIE V EH1 JH IY0 +VEGGIES V EH1 JH IY0 Z +VEGH V EH1 G +VEGISNAX V AH0 G IH1 S N AE0 K S +VEHEMENCE V IY1 AH0 M AH0 N S +VEHEMENCE(1) V AH0 HH IY1 M AH0 N S +VEHEMENT V IY1 AH0 M AH0 N T +VEHEMENT(1) V AH0 HH IY1 M AH0 N T +VEHEMENTLY V IY1 AH0 M AH0 N T L IY0 +VEHEMENTLY(1) V AH0 HH IY1 M AH0 N T L IY0 +VEHICLE V IY1 HH IH0 K AH0 L +VEHICLE(1) V IY1 IH0 K AH0 L +VEHICLE'S V IY1 HH IH0 K AH0 L Z +VEHICLES V IY1 HH IH0 K AH0 L Z +VEHICLES(1) V IY1 IH0 K AH0 L Z +VEHICLES' V EH1 HH IH0 K AH0 L Z +VEHICULAR V IY0 HH IH1 K Y AH0 L ER0 +VEIGA V EY1 G AH0 +VEIGEL V AY1 G AH0 L +VEIL V EY1 L +VEILED V EY1 L D +VEILING V EY1 L IH0 NG +VEILLETTE V AH0 L EH1 T +VEILLEUX V AH0 L OW1 +VEILLEUX(1) V EY1 L OW0 +VEILLON V EY1 L AH0 N +VEILS V EY1 L Z +VEIN V EY1 N +VEINS V EY1 N Z +VEIRA V EY1 R AH0 +VEIT V IY1 T +VEITCH V AY1 CH +VEITH V IY1 TH +VELA V EH1 L AH0 +VELAGRANDE V EH2 L AH0 G R AA1 N D EY2 +VELAGRANDE'S V EH2 L AH0 G R AA1 N D EY2 Z +VELARDE V EH0 L AA1 R D IY0 +VELARDI V EH0 L AA1 R D IY0 +VELARDO V EY0 L AA1 R D OW0 +VELASCO V EH0 L AA1 S K OW0 +VELASQUEZ V EH0 L AE1 S K EH0 Z +VELAYATI V EH0 L AY2 AA1 T IY0 +VELAZCO V AH0 L AE1 S K OW0 +VELAZQUEZ V EH0 L AE1 S K EH0 Z +VELCRO V EH1 L K R OW0 +VELDA V EH1 L D AH0 +VELDHUIZEN V EH1 L D HH IH0 Z AH0 N +VELDMAN V EH1 L D M AH0 N +VELEY V EH1 L IY0 +VELEZ V EH0 L EH1 Z +VELIE V EH1 L IY0 +VELIKA V EH1 L IH0 K AH0 +VELIOTIS V EH0 L IY0 OW1 T IH0 S +VELIZ V EH1 L IH0 Z +VELLA V EH1 L AH0 +VELLUCCI V EH0 L UW1 CH IY0 +VELMA V EH1 L M AH0 +VELO V EH1 L OW0 +VELOBIND V EH1 L AH0 B IH0 N D +VELOBIND(1) V EH1 L OW0 B AY2 N D +VELOCIRAPTOR V AH0 L AO1 S AH0 R AE2 P T ER0 +VELOCITIES V AH0 L AA1 S AH0 T IY0 Z +VELOCITY V AH0 L AA1 S AH0 T IY0 +VELODROME V EH2 L OW0 D R OW1 M +VELODROMES V EH2 L OW0 D R OW1 M Z +VELOSO V EH2 L OW1 S OW0 +VELOTTA V EH0 L OW1 T AH0 +VELOUR V EH2 L UW1 R +VELOZ V EY1 L OW0 Z +VELSICOL V EH1 L S IH0 K AA2 L +VELTE V EH1 L T +VELTEN V EH1 L T AH0 N +VELTMAN V EH1 L T M AH0 N +VELTRE V EH1 L T ER0 +VELTRI V EH1 L T R IY0 +VELVEETA V EH0 L V IY1 T AH0 +VELVET V EH1 L V AH0 T +VELVETEEN V EH1 L V AH0 T IY2 N +VELVETY V EH1 L V AH0 T IY0 +VEMICH V EH1 M IH0 CH +VEMPALA V EH2 M P AA1 L AH0 +VENA V IY1 N AH0 +VENABLE V EH1 N AH0 B AH0 L +VENABLES V EH1 N AH0 B AH0 L Z +VENACURO V EH0 N AH0 K Y UH1 R OW0 +VENAL V IY1 N AH0 L +VENALITY V IH0 N AE1 L IH0 T IY0 +VENALUM V EH1 N AH0 L AH0 M +VENANGO V EH0 N AE1 NG G OW0 +VENARD V EH1 N ER0 D +VENCILL V EH1 N S IH0 L +VENCOR V EH1 N K AO2 R +VENDEE V EH1 N D IY1 +VENDELA V EH0 N D EH1 L AH0 +VENDETTA V EH0 N D EH1 T AH0 +VENDETTAS V EH0 N D EH1 T AH0 Z +VENDETTI V EH0 N D EH1 T IY0 +VENDING V EH1 N D IH0 NG +VENDITTI V EH0 N D IY1 T IY0 +VENDO V EH1 N D OW0 +VENDOME V EH0 N D OW1 M +VENDOME(1) V AA1 N D OW2 M +VENDOR V EH1 N D ER0 +VENDOR'S V EH1 N D ER0 Z +VENDORS V EH1 N D ER0 Z +VENDORS' V EH1 N D ER0 Z +VENEER V AH0 N IH1 R +VENEERS V AH0 N IH1 R Z +VENEGAS V EH1 N IH0 G AH0 Z +VENEMA V EH1 N IH0 M AH0 +VENERABLE V EH1 N ER0 AH0 B AH0 L +VENERATE V EH1 N ER0 EY2 T +VENERATED V EH1 N ER0 EY2 T IH0 D +VENERATES V EH1 N ER0 EY2 T S +VENERATING V EH1 N ER0 EY2 T IH0 NG +VENERATION V EH2 N ER0 EY1 SH AH0 N +VENEREAL V AH0 N IH1 R IY0 AH0 L +VENETIAN V AH0 N IY1 SH AH0 N +VENEY V EH1 N IY0 +VENEZIA V EH0 N EH1 Z IY0 AH0 +VENEZIANO V EH0 N EH0 Z IY0 AA1 N OW0 +VENEZUELA V EH2 N IH0 Z W EY1 L AH0 +VENEZUELA'S V EH2 N IH0 Z W EY1 L AH0 Z +VENEZUELAN V EH2 N IH0 Z W EY1 L AH0 N +VENEZUELANS V EH2 N IH0 Z W EY1 L AH0 N Z +VENGEANCE V EH1 N JH AH0 N S +VENGEFUL V EH1 N JH F AH0 L +VENICE V EH1 N AH0 S +VENICE(1) V EH1 N IH0 S +VENICE'S V EH1 N IH0 S IH0 Z +VENIER V IY1 N IY0 ER0 +VENISON V EH1 N AH0 S AH0 N +VENITA V EH0 N IY1 T AH0 +VENKATESH V EH2 N K AA0 T EH1 SH +VENN V EH1 N +VENNARD V EH1 N ER0 D +VENNE V EH1 N +VENNEMAN V EH1 N M AH0 N +VENNER V EH1 N ER0 +VENNICK V EH1 N IH0 K +VENNING V EH1 N IH0 NG +VENO V EY1 N OW0 +VENOM V EH1 N AH0 M +VENOMOUS V EH1 N AH0 M AH0 S +VENOUS V IY1 N AH0 S +VENSEL V EH1 N S AH0 L +VENSON V EH1 N S AH0 N +VENT V EH1 N T +VENTECH V EH1 N T EH2 K +VENTED V EH1 N T IH0 D +VENTER V EH1 N T ER0 +VENTERS V EH1 N T ER0 Z +VENTI V EH1 N T IY0 +VENTILATE V EH1 N T IH0 L EY2 T +VENTILATED V EH1 N T IH0 L EY2 T IH0 D +VENTILATING V EH1 N T IH0 L EY2 T IH0 NG +VENTILATION V EH2 N T IH0 L EY1 SH AH0 N +VENTILATOR V EH1 N T IH0 L EY2 T ER0 +VENTIMIGLIA V EH2 N T IH0 M IH1 G L IY0 AH0 +VENTING V EH1 N T IH0 NG +VENTNER V EH1 N T N ER0 +VENTO V EH1 N T OW0 +VENTOLA V EH0 N T OW1 L AH0 +VENTRAL V EH1 N T R AH0 L +VENTRE V EH1 N T ER0 +VENTRELLA V EH2 N T R EH1 L AH0 +VENTRES V EH1 N T ER0 Z +VENTRESCA V EH0 N T R EH1 S K 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AY2 Z D +WESTERNMOST W EH1 S T ER0 N M OW2 S T +WESTERNS W EH1 S T ER0 N Z +WESTERVELT W EH1 S T ER0 V IH0 L T +WESTFAELISCHES W EH1 S T F EY2 L IH0 SH IH0 Z +WESTFAHL W EH1 S T F AA2 L +WESTFALL W EH1 S T F AO2 L +WESTFED W EH1 S T F EH2 D +WESTFIELD W EH1 S T F IY0 L D +WESTFORD W EH1 S T F ER0 D +WESTGATE W EH1 S T G EY2 T +WESTHAMPTON W EH2 S T HH AE1 M P T AH0 N +WESTHEIMER W EH1 S T HH AY2 M ER0 +WESTHOFF W EH1 S T HH AO2 F +WESTIN W EH1 S T IH0 N +WESTINGHOUSE W EH1 S T IH0 NG HH AW2 S +WESTINGHOUSE'S W EH1 S T IH0 NG HH AW2 S IH0 Z +WESTLAKE W EH1 S T L EY2 K +WESTLAND W EH1 S T L AH0 N D +WESTLEIGH W EH1 S T L AY0 +WESTLEY W EH1 S T L IY0 +WESTLING W EH1 S T L IH0 NG +WESTLUND W EH1 S T L AH0 N D +WESTMAN W EH1 S T M AH0 N +WESTMARC W EH1 S T M AA2 R K +WESTMARK W EH1 S T M AA2 R K +WESTMARK'S W EH1 S T M AA2 R K S +WESTMIN W EH1 S T M IH0 N +WESTMINSTER W EH2 S T M IH1 N S T ER0 +WESTMORELAND W EH0 S T M AO1 R L AH0 N D +WESTON W EH1 S T AH0 N +WESTOVER W EH1 S T OW2 V ER0 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AO2 R TH +WEYGANDT W EY1 G AH0 N T +WEYHRAUCH W EY1 R AW2 K +WEYL W EY1 L +WEYLAND W EY1 L AH0 N D +WEYLIN W EY1 L IH0 N +WEYMAN W EY1 M AH0 N +WEYMER W EY1 M ER0 +WEYMOUTH W EY1 M AH0 TH +WEYRAUCH W EH1 R AW0 K +WEYRICH W EH1 R IH0 K +WEYRICK W EY1 R IH0 K +WHACK W AE1 K +WHACK(1) HH W AE1 K +WHACKED W AE1 K T +WHACKED(1) HH W AE1 K T +WHACKER W AE1 K ER0 +WHACKER(1) HH W AE1 K ER0 +WHACKING W AE1 K IH0 NG +WHACKING(1) HH W AE1 K IH0 NG +WHACKO W AE1 K OW0 +WHACKOS W AE1 K OW0 Z +WHACKS W AE1 K S +WHACKS(1) HH W AE1 K S +WHALE W EY1 L +WHALE(1) HH W EY1 L +WHALE'S W EY1 L Z +WHALE'S(1) HH W EY1 L Z +WHALEN W EY1 L AH0 N +WHALEN(1) HH W EY1 L AH0 N +WHALER W EY1 L ER0 +WHALER(1) HH W EY1 L ER0 +WHALERS W EY1 L ER0 Z +WHALERS(1) HH W EY1 L ER0 Z +WHALES W EY1 L Z +WHALES(1) HH W EY1 L Z +WHALEY W EY1 L IY0 +WHALEY(1) HH W EY1 L IY0 +WHALIN W AE1 L IH0 N +WHALING W EY1 L IH0 NG +WHALING(1) HH W EY1 L IH0 NG +WHALLEY W AE1 L IY0 +WHAM W AE1 M +WHAM(1) HH W AE1 M +WHAMMY W AE1 M IY0 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EH1 V ER0 +WHATSOEVER(1) HH W AH2 T S OW0 EH1 V ER0 +WHAY-YU W EY1 Y UW1 +WHAY-YU(1) HH W EY1 Y UW1 +WHEAT W IY1 T +WHEAT(1) HH W IY1 T +WHEATEN W IY1 T AH0 N +WHEATEN(1) HH W IY1 T AH0 N +WHEATIE W IY1 T IY0 +WHEATIE(1) HH W IY1 T IY0 +WHEATIES W IY1 T IY0 Z +WHEATIES(1) HH W IY1 T IY0 Z +WHEATLEY W IY1 T L IY0 +WHEATLEY(1) HH W IY1 T L IY0 +WHEATLY W IY1 T L IY0 +WHEATLY(1) HH W IY1 T L IY0 +WHEATON W IY1 T AH0 N +WHEATON(1) HH W IY1 T AH0 N +WHEDBEE W EH1 D B IY2 +WHEDBEE(1) HH W EH1 D B IY2 +WHEDON W EH1 D AH0 N +WHEDON(1) HH W EH1 D AH0 N +WHEEL W IY1 L +WHEEL(1) HH W IY1 L +WHEELABRATOR W IY2 L AH0 B R EY1 T ER0 +WHEELABRATOR(1) HH W IY2 L AH0 B R EY1 T ER0 +WHEELAN W IY1 L AH0 N +WHEELAN(1) HH W IY1 L AH0 N +WHEELAND W IY1 L AH0 N D +WHEELAND(1) HH W IY1 L AH0 N D +WHEELBARROW W IY1 L B EH2 R OW0 +WHEELBARROW(1) HH W IY1 L B EH2 R OW0 +WHEELBARROWS W IY1 L B EH2 R OW0 Z +WHEELBARROWS(1) HH W IY1 L B EH2 R OW0 Z +WHEELBASE W IY1 L B EY2 S +WHEELBASE(1) HH W IY1 L B EY2 S +WHEELCHAIR W IY1 L CH EH2 R +WHEELCHAIR(1) HH W IY1 L CH EH2 R +WHEELCHAIRS W IY1 L CH EH2 R Z +WHEELCHAIRS(1) HH W IY1 L CH EH2 R Z +WHEELDON W IY1 L D AH0 N +WHEELDON(1) HH W IY1 L D AH0 N +WHEELED W IY1 L D +WHEELED(1) HH W IY1 L D +WHEELER W IY1 L ER0 +WHEELER(1) HH W IY1 L ER0 +WHEELER'S W IY1 L ER0 Z +WHEELER'S(1) HH W IY1 L ER0 Z +WHEELERS W IY1 L ER0 Z +WHEELERS(1) HH W IY1 L ER0 Z +WHEELESS W IY1 L AH0 S +WHEELESS(1) HH W IY1 L AH0 S +WHEELING W IY1 L IH0 NG +WHEELING(1) HH W IY1 L IH0 NG +WHEELING'S W IY1 L IH0 NG Z +WHEELING'S(1) HH W IY1 L IH0 NG Z +WHEELIS W IY1 L IH0 S +WHEELIS(1) HH W IY1 L IH0 S +WHEELOCK W IY1 L AA2 K +WHEELOCK(1) HH W IY1 L AA2 K +WHEELON W IY1 L AH0 N +WHEELON(1) HH W IY1 L AH0 N +WHEELS W IY1 L Z +WHEELS(1) HH W IY1 L Z +WHEELUS W IY1 L AH0 S +WHEELUS(1) HH W IY1 L AH0 S +WHEELWRIGHT W IY1 L R AY2 T +WHEELWRIGHT(1) HH W IY1 L R AY2 T +WHEELWRITER W IY1 L R AY2 T ER0 +WHEELWRITER(1) HH W IY1 L R AY2 T ER0 +WHEEZE W IY1 Z +WHEEZE(1) HH W IY1 Z +WHEEZES W IY1 Z AH0 Z +WHEEZES(1) HH W IY1 Z AH0 Z +WHEEZES(2) W IY1 Z IH0 Z +WHEEZING W IY1 Z IH0 NG +WHEEZING(1) HH W IY1 Z IH0 NG +WHELAN W EH1 L AH0 N +WHELAN(1) HH W EH1 L AH0 N +WHELAN(2) HH W IY1 L AH0 N +WHELAN(3) W IY1 L AH0 N +WHELCHEL W EH1 L CH AH0 L +WHELCHEL(1) HH W EH1 L CH AH0 L +WHELESS W IY1 L IH0 S +WHELESS(1) HH W IY1 L IH0 S +WHELPLEY W EH1 L P L IY0 +WHELPLEY(1) HH W EH1 L P L IY0 +WHELTON W EH1 L T AH0 N +WHELTON(1) HH W EH1 L T AH0 N +WHEN W EH1 N +WHEN(1) HH W EH1 N +WHEN(2) W IH1 N +WHEN(3) HH W IH1 N +WHEN'LL W EH1 N AH0 L +WHEN'LL(1) HH W EH1 N AH0 L +WHEN'S W EH1 N Z +WHEN'S(1) HH W EH1 N Z +WHENCE W EH1 N S +WHENCE(1) HH W EH1 N S +WHENEVER W EH0 N EH1 V ER0 +WHENEVER(1) HH W EH0 N EH1 V ER0 +WHERE W EH1 R +WHERE(1) HH W EH1 R +WHERE'D W EH1 R D +WHERE'D(1) HH W EH1 R D +WHERE'RE W EH1 R ER0 +WHERE'S W EH1 R Z +WHERE'S(1) HH W EH1 R Z +WHERE'VE W EH1 R AH0 V +WHEREABOUTS W EH1 R AH0 B AW2 T S +WHEREABOUTS(1) HH W EH1 R AH0 B AW2 T S +WHEREAS W EH0 R AE1 Z +WHEREAS(1) HH W EH0 R AE1 Z +WHEREBY W EH0 R B AY1 +WHEREBY(1) HH W EH0 R B AY1 +WHEREFORE HH W EH1 R F AO2 R +WHEREIN W EH0 R IH1 N +WHEREIN(1) HH W EH0 R IH1 N +WHEREUPON W EH1 R AH0 P AA1 N +WHEREUPON(1) HH W EH1 R AH0 P AA1 N +WHEREVER W EH0 R EH1 V ER0 +WHEREVER(1) HH W EH0 R EH1 V ER0 +WHEREWITHAL W EH1 R W IH0 DH AO2 L +WHEREWITHAL(1) HH W EH1 R W IH0 DH AO2 L +WHERLEY W ER1 L IY0 +WHERLEY(1) HH W ER1 L IY0 +WHERRY W EH1 R IY0 +WHERRY(1) HH W EH1 R IY0 +WHET W EH1 T +WHET(1) HH W EH1 T +WHETHER W EH1 DH ER0 +WHETHER(1) HH W EH1 DH ER0 +WHETSEL W EH1 T S AH0 L +WHETSEL(1) HH W EH1 T S AH0 L +WHETSELL W EH1 T S AH0 L +WHETSELL(1) HH W EH1 T S AH0 L +WHETSTINE W EH1 T S T IY0 N +WHETSTINE(1) HH W EH1 T S T IY0 N +WHETSTONE W EH1 T S T OW2 N +WHETSTONE(1) HH W EH1 T S T OW2 N +WHETTED W EH1 T IH0 D +WHETTED(1) HH W EH1 T IH0 D +WHETZEL W EH1 T Z AH0 L +WHETZEL(1) HH W EH1 T Z AH0 L +WHEW W UW1 +WHEW(1) HH W UW1 +WHEW(2) HH Y UW1 +WHEY W EY1 +WHEY(1) HH W EY1 +WHICH W IH1 CH +WHICH(1) HH W IH1 CH +WHICH'RE W IH1 CH ER0 +WHICH'RE(1) HH W IH1 CH ER0 +WHICH'S W IH1 CH IH0 Z +WHICH'S(1) HH W IH1 CH IH0 Z +WHICHARD W IH1 CH ER0 D +WHICHARD(1) HH W IH1 CH ER0 D +WHICHEVER W IH0 CH EH1 V ER0 +WHICHEVER(1) HH W IH0 CH EH1 V ER0 +WHICKER W IH1 K ER0 +WHICKER(1) HH W IH1 K ER0 +WHIDBY W IH1 D B IY0 +WHIDBY(1) HH W IH1 D B IY0 +WHIDDEN W IH1 D AH0 N +WHIDDEN(1) HH W IH1 D AH0 N +WHIDDON W IH1 D AH0 N +WHIDDON(1) HH W IH1 D AH0 N +WHIFF W IH1 F +WHIFF(1) HH W IH1 F +WHIG W IH1 G +WHIG(1) HH W IH1 G +WHIGHAM W IH1 G AH0 M +WHIGHAM(1) HH W IH1 G AH0 M +WHIGS W IH1 G Z +WHIGS(1) HH W IH1 G Z +WHILDEN W AY1 L D AH0 N +WHILDEN(1) HH W AY1 L D AH0 N +WHILE W AY1 L +WHILE(1) HH W AY1 L +WHILES W AY1 L Z +WHILES(1) HH W AY1 L Z +WHILST W AY1 L S T +WHIM W IH1 M +WHIM(1) HH W IH1 M +WHIMPER W IH1 M P ER0 +WHIMPER(1) HH W IH1 M P ER0 +WHIMPERING W IH1 M P ER0 IH0 NG +WHIMPERING(1) HH W IH1 M P ER0 IH0 NG +WHIMS W IH1 M Z +WHIMS(1) HH W IH1 M Z +WHIMSICAL W IH1 M Z IH0 K AH0 L +WHIMSICAL(1) HH W IH1 M Z IH0 K AH0 L +WHIMSICALLY W IH1 M Z IH0 K L IY0 +WHIMSICALLY(1) HH W IH1 M Z IH0 K L IY0 +WHIMSY W IH1 M S IY0 +WHIMSY(1) HH W IH1 M S IY0 +WHINE W AY1 N +WHINE(1) HH W AY1 N +WHINER W AY1 N ER0 +WHINER(1) HH W AY1 N ER0 +WHINERS W AY1 N ER0 Z +WHINERS(1) HH W AY1 N ER0 Z +WHINERY W AY1 N ER0 IY0 +WHINERY(1) HH W AY1 N ER0 IY0 +WHINES W AY1 N Z +WHINES(1) HH W AY1 N Z +WHINING W AY1 N IH0 NG +WHINING(1) HH W AY1 N IH0 NG +WHINNERY W IH1 N ER0 IY0 +WHINNERY(1) HH W IH1 N ER0 IY0 +WHINNEY W IH1 N IY0 +WHINNEY(1) HH W IH1 N IY0 +WHINY W AY1 N IY0 +WHINY(1) HH W AY1 N IY0 +WHIP W IH1 P +WHIP(1) HH W IH1 P +WHIPKEY W IH1 P K IY2 +WHIPKEY(1) HH W IH1 P K IY2 +WHIPLASH W IH1 P L AE2 SH +WHIPLASH(1) HH W IH1 P L AE2 SH +WHIPLASHES W IH1 P L AE2 SH AH0 Z +WHIPLASHES(1) HH W IH1 P L AE2 SH AH0 Z +WHIPP W IH1 P +WHIPP(1) HH W IH1 P +WHIPPANY W IH1 P AH0 N IY0 +WHIPPANY(1) HH W IH1 P AH0 N IY0 +WHIPPED W IH1 P T +WHIPPED(1) HH W IH1 P T +WHIPPING W IH1 P IH0 NG +WHIPPING(1) HH W IH1 P IH0 NG +WHIPPLE W IH1 P AH0 L +WHIPPLE(1) HH W IH1 P AH0 L +WHIPPLE'S W IH1 P AH0 L Z +WHIPPLE'S(1) HH W IH1 P AH0 L Z +WHIPPOORWILLS W IH1 P ER0 W IH2 L Z +WHIPPOORWILLS(1) HH W IH1 P ER0 W IH2 L Z +WHIPPS W IH1 P S +WHIPPS(1) HH W IH1 P S +WHIPS W IH1 P S +WHIPS(1) HH W IH1 P S +WHIPSAW W IH1 P S AO2 +WHIPSAW(1) HH W IH1 P S AO2 +WHIPSAWED W IH1 P S AO2 D +WHIPSAWED(1) HH W IH1 P S AO2 D +WHIPSAWING W IH1 P S AO2 IH0 NG +WHIPSAWING(1) HH W IH1 P S AO2 IH0 NG +WHIRL W ER1 L +WHIRL(1) HH W ER1 L +WHIRLED W ER1 L D +WHIRLED(1) HH W ER1 L D +WHIRLEY W ER1 L IY0 +WHIRLEY(1) HH W ER1 L IY0 +WHIRLING W ER1 L IH0 NG +WHIRLING(1) HH W ER1 L IH0 NG +WHIRLPOOL W ER1 L P UW2 L +WHIRLPOOL(1) HH W ER1 L P UW2 L +WHIRLPOOL'S W ER1 L P UW2 L Z +WHIRLPOOL'S(1) HH W ER1 L P UW2 L Z +WHIRLPOOLS W ER1 L P UW2 L Z +WHIRLPOOLS(1) HH W ER1 L P UW2 L Z +WHIRLWIND W ER1 L W IH2 N D +WHIRLWIND(1) HH W ER1 L W IH2 N D +WHIRRING W ER1 IH0 NG +WHIRRING(1) HH W ER1 IH0 NG +WHISENAND W IH1 S IH0 N AE0 N D +WHISENAND(1) HH W IH1 S IH0 N AE0 N D +WHISENANT W IH1 S IH0 N AH0 N T +WHISENANT(1) HH W IH1 S IH0 N AH0 N T +WHISENHUNT W AY1 Z AH0 N HH AH2 N T +WHISENHUNT(1) HH W AY1 Z AH0 N HH AH2 N T +WHISK W IH1 S K +WHISK(1) HH W IH1 S K +WHISKED W IH1 S K T +WHISKED(1) HH W IH1 S K T +WHISKER W IH1 S K ER0 +WHISKER(1) HH W IH1 S K ER0 +WHISKERED W IH1 S K ER0 D +WHISKERS W IH1 S K ER0 Z +WHISKERS(1) HH W IH1 S K ER0 Z +WHISKEY W IH1 S K IY0 +WHISKEY(1) HH W IH1 S K IY0 +WHISKEYS W IH1 S K IY0 Z +WHISKEYS(1) HH W IH1 S K IY0 Z +WHISKS W IH1 S K S +WHISKS(1) HH W IH1 S K S +WHISKY W IH1 S K IY0 +WHISKY(1) HH W IH1 S K IY0 +WHISLER W IH1 S L ER0 +WHISLER(1) HH W IH1 S L ER0 +WHISMAN W IH1 S M AH0 N +WHISMAN(1) HH W IH1 S M AH0 N +WHISNANT W IH1 S N AH0 N T +WHISNANT(1) HH W IH1 S N AH0 N T +WHISNER W IH1 S N ER0 +WHISNER(1) HH W IH1 S N ER0 +WHISONANT W IH1 S AH0 N AH0 N T +WHISPER W IH1 S P ER0 +WHISPER(1) HH W IH1 S P ER0 +WHISPERED W IH1 S P ER0 D +WHISPERED(1) HH W IH1 S P ER0 D +WHISPERER W IH1 S P AH0 R ER2 +WHISPERER'S W IH1 S P AH0 R ER2 Z +WHISPERERS W IH1 S P AH0 R ER2 Z +WHISPERING W IH1 S P ER0 IH0 NG +WHISPERING(1) HH W IH1 S P ER0 IH0 NG +WHISPERS W IH1 S P ER0 Z +WHISPERS(1) HH W IH1 S P ER0 Z +WHISTLE W IH1 S AH0 L +WHISTLE(1) HH W IH1 S AH0 L +WHISTLEBLOWER W IH1 S AH0 L B L OW2 ER0 +WHISTLEBLOWER(1) HH W IH1 S AH0 L B L OW2 ER0 +WHISTLEBLOWERS W IH1 S AH0 L B L OW2 ER0 Z +WHISTLEBLOWERS(1) HH W IH1 S AH0 L B L OW2 ER0 Z +WHISTLED W IH1 S AH0 L D +WHISTLED(1) HH W IH1 S AH0 L D +WHISTLER W IH1 S L ER0 +WHISTLER(1) HH W IH1 S L ER0 +WHISTLERS W IH1 S L ER0 Z +WHISTLERS(1) HH W IH1 S L ER0 Z +WHISTLES W IH1 S AH0 L Z +WHISTLES(1) HH W IH1 S AH0 L Z +WHISTLING W IH1 S L IH0 NG +WHISTLING(1) HH W IH1 S L IH0 NG +WHISTON W IH1 S T AH0 N +WHISTON(1) HH W IH1 S T AH0 N +WHIT W IH1 T +WHIT(1) HH W IH1 T +WHITACRE W IH1 T AH0 K ER0 +WHITACRE(1) HH W IH1 T AH0 K ER0 +WHITAKER W IH1 T AH0 K ER0 +WHITAKER(1) HH W IH1 T AH0 K ER0 +WHITBECK W IH1 T B EH2 K +WHITBECK(1) HH W IH1 T B EH2 K +WHITBREAD W IH1 T B R EH2 D +WHITBREAD(1) HH W IH1 T B R EH2 D +WHITBY W IH1 T B IY0 +WHITBY(1) HH W IH1 T B IY0 +WHITCHER W IH1 CH ER0 +WHITCHER(1) HH W IH1 CH ER0 +WHITCHURCH W IH1 T CH ER2 CH +WHITCHURCH(1) HH W IH1 T CH ER2 CH +WHITCOMB W IH1 T K AH0 M +WHITCOMB(1) HH W IH1 T K AH0 M +WHITCRAFT W IH1 T K R AE2 F T +WHITCRAFT(1) HH W IH1 T K R AE2 F T +WHITE W AY1 T +WHITE(1) HH W AY1 T +WHITE'S W AY1 T S +WHITE'S(1) HH W AY1 T S +WHITEAKER W IH1 T AH0 K ER0 +WHITEAKER(1) HH W IH1 T AH0 K ER0 +WHITEBREAD W AY1 T B R EH2 D +WHITEBREAD(1) HH W AY1 T B R EH2 D +WHITECOTTON W AY1 T K AA2 T AH0 N +WHITECOTTON(1) HH W AY1 T K AA2 T AH0 N +WHITED W AY1 T IH0 D +WHITED(1) HH W AY1 T IH0 D +WHITEFIELD W AY1 T F IY2 L D +WHITEFIELD(1) HH W AY1 T F IY2 L D +WHITEFISH W AY1 T F IH2 SH +WHITEFISH(1) HH W AY1 T F IH2 SH +WHITEFORD W AY1 T F AO0 R D +WHITEFORD(1) HH W AY1 T F AO0 R D +WHITEHAIR W AY1 T HH EH1 R +WHITEHAIR(1) HH W AY1 T HH EH1 R +WHITEHALL W AY1 T HH AO2 L +WHITEHALL(1) HH W AY1 T HH AO2 L +WHITEHALL'S W AY1 T HH AO2 L Z +WHITEHALL'S(1) HH W AY1 T HH AO2 L Z +WHITEHEAD W AY1 T HH EH2 D +WHITEHEAD(1) HH W AY1 T HH EH2 D +WHITEHEAD'S W AY1 T HH EH2 D Z +WHITEHEAD'S(1) HH W AY1 T HH EH2 D Z +WHITEHILL W AY1 T HH IH2 L +WHITEHILL(1) HH W AY1 T HH IH2 L +WHITEHORN W AY1 T HH AO2 R N +WHITEHORN(1) HH W AY1 T HH AO2 R N +WHITEHORSE W AY1 T HH AO2 R S +WHITEHORSE(1) HH W AY1 T HH AO2 R S +WHITEHOUSE W AY1 T HH AW2 S +WHITEHOUSE(1) HH W AY1 T HH AW2 S +WHITEHURST W AY1 T HH ER2 S T +WHITEHURST(1) HH W AY1 T HH ER2 S T +WHITEHURST'S W AY1 T HH ER2 S T S +WHITELAW W AY1 T L AO2 +WHITELAW(1) HH W AY1 T L AO2 +WHITELEY W AY1 T L IY0 +WHITELEY(1) HH W AY1 T L IY0 +WHITELOCK W AY1 T L AA2 K +WHITELOCK(1) HH W AY1 T L AA2 K +WHITELY W AY1 T L IY0 +WHITELY(1) HH W AY1 T L IY0 +WHITEMAN W AY1 T M AH0 N +WHITEMAN(1) HH W AY1 T M AH0 N +WHITEMONT W AY1 T M AA2 N T +WHITEMONT(1) HH W AY1 T M AA2 N T +WHITEN W AY1 T AH0 N +WHITEN(1) HH W AY1 T AH0 N +WHITENACK W AY1 T N AE2 K +WHITENACK(1) HH W AY1 T N AE2 K +WHITENEIR W AY1 T N IH2 R +WHITENEIR(1) HH W AY1 T N IH2 R +WHITENER W AY1 T N ER0 +WHITENER(1) HH W AY1 T N ER0 +WHITENESS W AY1 T N AH0 S +WHITENESS(1) HH W AY1 T N AH0 S +WHITENIGHT W AY1 T N AY2 T +WHITENIGHT(1) HH W AY1 T N AY2 T +WHITENING W AY1 T IH0 N IH0 NG +WHITENING(1) W AY1 T N IH0 NG +WHITENING(2) HH W AY1 T IH0 N IH0 NG +WHITENING(3) HH W AY1 T N IH0 NG +WHITER W AY1 T ER0 +WHITER(1) HH W AY1 T ER0 +WHITES W AY1 T S +WHITES(1) HH W AY1 T S +WHITESCARVER W AY1 T S K AA2 R V ER0 +WHITESCARVER(1) HH W AY1 T S K AA2 R V ER0 +WHITESEL W AY1 T S EH2 L +WHITESEL(1) HH W AY1 T S EH2 L +WHITESELL W AY1 T S EH2 L +WHITESELL(1) HH W AY1 T S EH2 L +WHITESIDE W AY1 T S AY2 D +WHITESIDE(1) HH W AY1 T S AY2 D +WHITESIDES W AY1 T S AY2 D Z +WHITESIDES(1) HH W AY1 T S AY2 D Z +WHITEST W AY1 T IH0 S T +WHITEST(1) HH W AY1 T IH0 S T +WHITESTONE W AY1 T S T OW2 N +WHITESTONE(1) HH W AY1 T S T OW2 N +WHITETAIL W AY1 T T EY2 L +WHITETAIL(1) HH W AY1 T T EY2 L +WHITETAIL(2) HH W AY1 T EY2 L +WHITEWASH W AY1 T W AA2 SH +WHITEWASH(1) HH W AY1 T W AA2 SH +WHITEWASHED W AY1 T W AA2 SH T +WHITEWASHED(1) HH W AY1 T W AA2 SH T +WHITEWATER W AY1 T W AO2 T ER0 +WHITEWATER(1) HH W AY1 T W AO2 T ER0 +WHITEWATER'S W AY1 T W AO2 T ER0 Z +WHITEWATER'S(1) HH W AY1 T W AO2 T ER0 Z +WHITEY W AY1 T IY2 +WHITEY(1) HH W AY1 T IY2 +WHITEY(2) HH W AY1 T IY0 +WHITFIELD W IH1 T F IY0 L D +WHITFIELD(1) HH W IH1 T F IY0 L D +WHITFILL W IH1 T F IH2 L +WHITFILL(1) HH W IH1 T F IH2 L +WHITFORD W IH1 T F ER0 D +WHITFORD(1) HH W IH1 T F ER0 D +WHITHAM W IH1 TH AH0 M +WHITHAM(1) HH W IH1 TH AH0 M +WHITHAM(2) HH W IH1 T AH0 M +WHITHER W IH1 DH ER0 +WHITHER(1) HH W IH1 DH ER0 +WHITING W AY1 T IH0 NG +WHITING(1) HH W AY1 T IH0 NG +WHITINGS W AY1 T IH0 NG Z +WHITINGS(1) HH W AY1 T IH0 NG Z +WHITIS W AY1 T IH0 S +WHITIS(1) HH W AY1 T IH0 S +WHITISH W AY1 T IH0 SH +WHITISH(1) HH W AY1 T IH0 SH +WHITLATCH W IH1 T L AE2 CH +WHITLATCH(1) HH W IH1 T L AE2 CH +WHITLEDGE W IH1 T L EH2 JH +WHITLEDGE(1) HH W IH1 T L EH2 JH +WHITLEY W IH1 T L IY0 +WHITLEY(1) HH W IH1 T L IY0 +WHITLING W IH1 T L IH0 NG +WHITLING(1) HH W IH1 T L IH0 NG +WHITLOCK W IH1 T L AA2 K +WHITLOCK(1) HH W IH1 T L AA2 K +WHITLOW W IH1 T L OW2 +WHITLOW(1) HH W IH1 T L OW2 +WHITLY W IH1 T L IY0 +WHITLY(1) HH W IH1 T L IY0 +WHITMAN W IH1 T M AH0 N +WHITMAN(1) HH W IH1 T M AH0 N +WHITMAN'S W IH1 T M AH0 N Z +WHITMAN'S(1) HH W IH1 T M AH0 N Z +WHITMARSH W IH1 T M AA2 R SH +WHITMARSH(1) HH W IH1 T M AA2 R SH +WHITMER W IH1 T M ER0 +WHITMER(1) HH W IH1 T M ER0 +WHITMILL W IH1 T M IH2 L +WHITMILL(1) HH W IH1 T M IH2 L +WHITMIRE W IH1 T M AY2 R +WHITMIRE(1) HH W IH1 T M AY2 R +WHITMORE W IH1 T M AO0 R +WHITMORE(1) HH W IH1 T M AO0 R +WHITMOYER W IH1 T M OY2 ER0 +WHITMOYER(1) HH W IH1 T M OY2 ER0 +WHITMYER W IH1 T M AY2 ER0 +WHITMYER(1) HH W IH1 T M AY2 ER0 +WHITNER W IH1 T N ER0 +WHITNER(1) HH W IH1 T N ER0 +WHITNEY W IH1 T N IY0 +WHITNEY(1) HH W IH1 T N IY0 +WHITNEY'S W IH1 T N IY0 Z +WHITNEY'S(1) HH W IH1 T N IY0 Z +WHITON W IH1 T AH0 N +WHITON(1) HH W IH1 T AH0 N +WHITROW W IH1 T R OW2 +WHITROW(1) HH W IH1 T R OW2 +WHITSEL W IH1 T S AH0 L +WHITSEL(1) HH W IH1 T S AH0 L +WHITSELL W IH1 T S AH0 L +WHITSELL(1) HH W IH1 T S AH0 L +WHITSETT W IH1 T S IH0 T +WHITSETT(1) HH W IH1 T S IH0 T +WHITSITT W IH1 T S IH0 T +WHITSITT(1) HH W IH1 T S IH0 T +WHITSON W IH1 T S AH0 N +WHITSON(1) HH W IH1 T S AH0 N +WHITT W IH1 T +WHITT(1) HH W IH1 T +WHITTAKER W IH1 T AH0 K ER0 +WHITTAKER(1) HH W IH1 T AH0 K ER0 +WHITTED W IH1 T IH0 D +WHITTED(1) HH W IH1 T IH0 D +WHITTEMORE W IH1 T M AO0 R +WHITTEMORE(1) HH W IH1 T M AO0 R +WHITTEN W IH1 T AH0 N +WHITTEN(1) HH W IH1 T AH0 N +WHITTENBERG W IH1 T AH0 N B ER0 G +WHITTENBERG(1) HH W IH1 T AH0 N B ER0 G +WHITTENBURG W IH1 T AH0 N B ER0 G +WHITTENBURG(1) HH W IH1 T AH0 N B ER0 G +WHITTET W IH1 T IH0 T +WHITTET(1) HH W IH1 T IH0 T +WHITTIER W IH1 T IY0 ER0 +WHITTIER(1) HH W IH1 T IY0 ER0 +WHITTING W IH1 T IH0 NG +WHITTING(1) HH W IH1 T IH0 NG +WHITTINGHAM W IH1 T IH0 NG HH AE2 M +WHITTINGHAM(1) HH W IH1 T IH0 NG HH AE2 M +WHITTINGHILL W IH1 T IH0 NG HH IH2 L +WHITTINGHILL(1) HH W IH1 T IH0 NG HH IH2 L +WHITTINGTON W IH1 T IH0 NG T AH0 N +WHITTINGTON(1) HH W IH1 T IH0 NG T AH0 N +WHITTLE W IH1 T AH0 L +WHITTLE(1) HH W IH1 T AH0 L +WHITTLE'S W IH1 T AH0 L Z +WHITTLE'S(1) HH W IH1 T AH0 L Z +WHITTLED W IH1 T AH0 L D +WHITTLED(1) HH W IH1 T AH0 L D +WHITTLESEY W IH1 T AH0 L S IY0 +WHITTLESEY(1) HH W IH1 T AH0 L S IY0 +WHITTLING W IH1 T L IH0 NG +WHITTLING(1) HH W IH1 T L IH0 NG +WHITTON W IH1 T AH0 N +WHITTON(1) HH W IH1 T AH0 N +WHITTY W IH1 T IY0 +WHITTY(1) HH W IH1 T IY0 +WHITWAM W IH1 T W AA0 M +WHITWAM(1) HH W IH1 T W AA0 M +WHITWELL W IH1 T W EH2 L +WHITWELL(1) HH W IH1 T W EH2 L +WHITWORTH W IH1 T W ER2 TH +WHITWORTH(1) HH W IH1 T W ER2 TH +WHIZ W IH1 Z +WHIZ(1) HH W IH1 Z +WHIZ-ZIP-BANG W IH2 Z IH2 P B AE1 NG +WHIZZED W IH1 Z D +WHIZZED(1) HH W IH1 Z D +WHIZZER W IH1 Z ER0 +WHIZZER(1) HH W IH1 Z ER0 +WHIZZES W IH1 Z IH0 Z +WHIZZES(1) HH W IH1 Z IH0 Z +WHIZZING W IH1 Z IH0 NG +WHIZZING(1) HH W IH1 Z IH0 NG +WHO HH UW1 +WHO'D HH UW1 D +WHO'LL HH UW1 L +WHO'RE HH UW1 ER0 +WHO'S HH UW1 Z +WHO'VE HH UW0 V +WHOA W OW1 +WHOA(1) HH W OW1 +WHOA(2) HH OW1 +WHOBREY W AA1 B R IY0 +WHODUNIT HH UW0 D AH1 N IH0 T +WHODUNITS HH UW0 D AH1 N IH0 T S +WHOEVER HH UW0 EH1 V ER0 +WHOEVER'S HH UW0 EH1 V ER0 Z +WHOLE HH OW1 L +WHOLEHEARTED HH OW1 L HH AA2 R T IH0 D +WHOLEHEARTEDLY HH OW1 L HH AA0 R T IH0 D L IY0 +WHOLENESS HH OW1 L N IH0 S +WHOLES HH OW1 L Z +WHOLESALE HH OW1 L S EY2 L +WHOLESALER HH OW1 L S EY2 L ER0 +WHOLESALER'S HH OW1 L S EY2 L ER0 Z +WHOLESALERS HH OW1 L S EY2 L ER0 Z +WHOLESALERS' HH OW1 L S EY2 L ER0 Z +WHOLESALES HH OW1 L S EY2 L Z +WHOLESALING HH OW1 L S EY2 L IH0 NG +WHOLESOME HH OW1 L S AH0 M +WHOLESOMENESS HH OW1 L S AH0 M N AH0 S +WHOLEY HH AA1 L IY0 +WHOLLY HH OW1 L IY0 +WHOM HH UW1 M +WHOMEVER HH UW0 M EH1 V ER0 +WHOMSOEVER HH UW2 M S OW0 EH1 V ER0 +WHOO W UW1 +WHOOP W UW1 P +WHOOP(1) HH W UW1 P +WHOOPDEDOO W UH1 P D IY0 D UW0 +WHOOPDEDOO(1) HH W UH1 P D IY0 D UW0 +WHOOPED W UW1 P T +WHOOPED(1) HH W UW1 P T +WHOOPEE W UW1 P IY1 +WHOOPEE(1) HH W UW1 P IY1 +WHOOPI W UW1 P IY0 +WHOOPI(1) HH W UW1 P IY0 +WHOOPIE W UW1 P IY0 +WHOOPIE(1) HH W UW1 P IY0 +WHOOPING W UW1 P IH0 NG +WHOOPING(1) HH W UW1 P IH0 NG +WHOOPS W UW1 P S +WHOOPS(1) HH W UW1 P S +WHOOSH W UW1 SH +WHOOSH(1) HH W UW1 SH +WHOPPER W AA1 P ER0 +WHOPPER(1) HH W AA1 P ER0 +WHOPPERS W AA1 P ER0 Z +WHOPPERS(1) HH W AA1 P ER0 Z +WHOPPING W AA1 P IH0 NG +WHOPPING(1) HH W AA1 P IH0 NG +WHORE HH AO1 R +WHOREHOUSE HH AO1 R HH AW2 S +WHORES HH AO1 R Z +WHORL W ER1 L +WHORL(1) W AO1 R L +WHORL(2) HH W AO1 R L +WHORLEY HH AO1 R L IY0 +WHORLEY(1) W AO1 R L IY0 +WHORLEY(2) HH W AO1 R L IY0 +WHORLS W ER1 L Z +WHORLS(1) W AO1 R L Z +WHORLS(2) HH W AO1 R L Z +WHORTON HH AO1 R T AH0 N +WHOSE HH UW1 Z +WHOSOEVER HH UW2 S OW0 EH1 V ER0 +WHY W AY1 +WHY(1) HH W AY1 +WHY'D W AY1 D +WHY'D(1) HH W AY1 D +WHY'RE W AY1 ER0 +WHY'S W AY1 Z +WHY'S(1) HH W AY1 Z +WHYS W AY1 Z +WHYS(1) HH W AY1 Z +WHYTE W AY1 T +WHYTE(1) HH W AY1 T +WI-FI W AY1 F AY2 +WIACEK V AY1 AH0 CH EH2 K +WIAN W AY1 AH0 N +WIANT W AY1 AH0 N T +WIARD W AY1 AA0 R D +WIATER W AY1 AH0 T ER0 +WIATROWSKI V IY0 AH0 T R AO1 F S K IY2 +WIATT W AY1 AH0 T +WIBBELSMAN W IH1 B AH0 L Z M AH0 N +WIBBENMEYER W IH1 B IH0 N M AY2 ER0 +WIBERG W AY1 B ER0 G +WIBLE W AY1 B AH0 L +WICAT W IH1 K AE0 T +WICCA W IH1 K AH0 +WICCAN W IH1 K AH0 N +WICE W AY1 S +WICH W IH1 CH +WICHERN W IH1 K ER0 N +WICHERT W IH1 CH ER0 T +WICHITA W IH1 CH AH0 T AO2 +WICHITA'S W IH1 CH AH0 T AO2 Z +WICHMAN W IH1 CH M AH0 N +WICHMANN W IH1 CH M AH0 N +WICK W IH1 K +WICKARD W IH1 K ER0 D +WICKE W IH1 K +WICKED W IH1 K AH0 D +WICKEDLY W IH1 K IH0 D L IY0 +WICKEDNESS W IH1 K AH0 D N AH0 S +WICKENS W IH1 K AH0 N Z +WICKER W IH1 K ER0 +WICKER'S W IH1 K ER0 Z +WICKERHAM W IH1 K ER0 HH AE2 M +WICKERS W IH1 K ER0 Z +WICKERSHAM W IH1 K ER0 SH AE2 M +WICKERT W IH1 K ER0 T +WICKES W IH1 K S +WICKES'S W IH1 K S IH0 Z +WICKET W IH1 K AH0 T +WICKET(1) HH W IH1 K AH0 T +WICKETS W IH1 K AH0 T S +WICKETS(1) HH W IH1 K AH0 T S +WICKETT W IH1 K IH0 T +WICKEY W IH1 K IY0 +WICKHAM W IH1 K AH0 M +WICKIZER W IH1 K AY2 Z ER0 +WICKLAND W IH1 K L AH0 N D +WICKLANDER W IH1 K L AE2 N D ER0 +WICKLEY W IH1 K L IY0 +WICKLIFF W IH1 K L IH0 F +WICKLIFFE W IH1 K L IH0 F +WICKLINE W IH1 K L AY2 N +WICKLUND W IH1 K L AH0 N D +WICKMAN W IH1 K M AH0 N +WICKS W IH1 K S +WICKSTROM W IH1 K S T R AH0 M +WICKWARE W IH1 K W EH2 R +WICKWIRE W IH1 S K V AY0 R +WICOMICO W AY2 K AA1 M IH0 K OW2 +WICOR W AY1 K AO2 R +WIDDER W IH1 D ER0 +WIDDLE W IH1 D AH0 L +WIDDLED W IH1 D AH0 L D +WIDDLY W IH1 D L IY0 +WIDDOWS W IH1 D OW2 Z +WIDDOWSON W IH1 D AW0 S AH0 N +WIDE W AY1 D +WIDE'S W AY1 D Z +WIDEBODY W AY1 D B AA2 D IY0 +WIDELL W IH1 D AH0 L +WIDELY W AY1 D L IY0 +WIDEMAN W AY1 D M AH0 N +WIDEN W AY1 D AH0 N +WIDENED W AY1 D AH0 N D +WIDENER W IH1 D IY0 N ER0 +WIDENING W AY1 D AH0 N IH0 NG +WIDENS W AY1 D AH0 N Z +WIDER W AY1 D ER0 +WIDESPREAD W AY1 D S P R EH1 D +WIDEST W AY1 D AH0 S T +WIDGER W IH1 JH ER0 +WIDGET W IH1 JH IH0 T +WIDGETS W IH1 JH IH0 T S +WIDHALM W IH1 D HH AA0 M +WIDICK W IH1 D IH0 K +WIDING W AY1 D IH0 NG +WIDMAIER W IH1 D M AY0 ER0 +WIDMAN W IH1 D M AH0 N +WIDMANN W IH1 D M AH0 N +WIDMAR W IH1 D M ER0 +WIDMAYER W IH1 D M EY2 ER0 +WIDMER W IH1 D M ER0 +WIDNALL W IH1 D N AH0 L +WIDNER W IH1 D N ER0 +WIDOW W IH1 D OW0 +WIDOW'S W IH1 D OW0 Z +WIDOWED W IH1 D OW0 D +WIDOWER W IH1 D OW0 ER0 +WIDOWERS W IH1 D OW0 ER0 Z +WIDOWS W IH1 D OW0 Z +WIDRICK W IH1 D R IH0 K +WIDRIG W IH1 D R IH0 G +WIDTH W IH1 D TH +WIDTHS W IH1 D TH S +WIDURI W IH0 D UH1 R IY0 +WIEAND W IY1 AH0 N D +WIEBE W IY1 B +WIEBER W IY1 B ER0 +WIEBERG W IY1 B ER0 G +WIEBKE W IY1 B K IY0 +WIEBOLD W IY1 B OW2 L D +WIEBUSCH W IY1 B AH0 SH +WIECH W IY1 CH +WIECHERT W IY1 K ER0 T +WIECHMAN W IY1 K M AH0 N +WIECHMANN W IY1 K M AH0 N +WIECK W IY1 K +WIECZOREK V IY0 CH AO1 R EH0 K +WIED W IY1 D +WIEDEL W IY1 D AH0 L 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G AH0 +ZULUS Z UW1 L UW0 Z +ZUMBRO Z AH1 M B R OW0 +ZUMBRUN Z AH1 M B R AH0 N +ZUMEL Z UW2 M EH1 L +ZUMMO Z UW1 M OW0 +ZUMPANO Z UW0 M P AA1 N OW0 +ZUMSTEIN Z AH1 M S T IY2 N +ZUMSTEIN(1) Z AH1 M S T AY2 N +ZUMWALT Z AH1 M W AH0 L T +ZUNDEL Z AH1 N D AH0 L +ZUNGU Z AH2 NG UW1 +ZUNI Z UW1 N IY2 +ZUNIGA Z UW0 N IY1 G AH0 +ZUNINO Z UW0 N IY1 N OW0 +ZUNKER Z AH1 NG K ER0 +ZUPAN Z UW1 P AH0 N +ZUPANCIC Z AH0 P AE1 NG K IH0 K +ZUPANJA Z AH0 P AE1 N JH AH0 +ZUPKO Z AH1 P K OW0 +ZURAWSKI Z ER0 AA1 F S K IY0 +ZURCHER Z ER1 K ER0 +ZUREK Z UH1 R EH0 K +ZURFLUH Z ER1 F L UW0 +ZURI Z UH1 R IY0 +ZURICH Z UH1 R IH0 K +ZURICH'S Z UH1 R IH0 K S +ZURITA Z ER0 AY1 T AH0 +ZURKUHLEN Z ER0 K Y UW1 L AH0 N +ZURN Z ER1 N +ZUROWSKI Z UW2 R OW1 S K IY2 +ZURVE Z ER1 V +ZUVER Z UW1 V ER0 +ZUZANA Z UW2 Z AA1 N AH0 +ZUZU Z UW1 Z UW2 +ZVORNIK Z V AO1 R N IH0 K +ZWACK Z W AO1 K +ZWAHLEN Z W AA1 L AH0 N +ZWART Z W AO1 R T +ZWEBER Z W IY1 B ER0 +ZWEIBEL Z W AY1 B AH0 L +ZWEIFEL Z W AY1 F AH0 L +ZWEIG Z W AY1 G +ZWERDLING Z W ER1 D L IH0 NG +ZWERDLING'S Z W ER1 D L IH0 NG Z +ZWETCHKENBAUM Z W EH1 CH K AH0 N B AA0 M +ZWICK Z W IH1 K +ZWICKER Z W IH1 K ER0 +ZWICKY Z W IH1 K IY0 +ZWIEBEL Z W IY1 B AH0 L +ZWIEFELHOFER Z W IY1 F AH0 L HH AA2 F ER0 +ZWIEG Z W IY1 G +ZWILLING Z W IH1 L IH0 NG +ZWOLINSKI Z V AH0 L IH1 N S K IY0 +ZYCAD Z IH1 K AE2 D +ZYCH Z AY1 CH +ZYCHER Z IH1 K ER0 +ZYDECO Z AY1 D AH0 K OW2 +ZYGMUNT Z IH1 G M AH0 N T +ZYGOTE Z AY1 G OW0 T +ZYLA Z IH1 L AH0 +ZYLKA Z IH1 L K AH0 +ZYLSTRA Z IH1 L S T R AH0 +ZYMAN Z AY1 M AH0 N +ZYNDA Z IH1 N D AH0 +ZYSK Z IH1 S K +ZYSK(1) Z AY1 S K +ZYSKOWSKI Z IH0 S K AO1 F S K IY0 +ZYUGANOV Z Y UW1 G AA0 N AA0 V +ZYUGANOV(1) Z UW1 G AA0 N AA0 V +ZYUGANOV'S Z Y UW1 G AA0 N AA0 V Z +ZYUGANOV'S(1) Z UW1 G AA0 N AA0 V Z +ZYWICKI Z IH0 W IH1 K IY0 +{BRACE B R EY1 S +{LEFT-BRACE L EH1 F T B R EY1 S +{OPEN-BRACE OW1 P EH0 N B R EY1 S +}CLOSE-BRACE K L OW1 Z B R EY1 S +}RIGHT-BRACE R AY1 T B R EY1 S \ No newline at end of file diff --git a/examples/other/use_mfa/local/detect_oov.py b/examples/other/use_mfa/local/detect_oov.py new file mode 100644 index 00000000..f5ae728f --- /dev/null +++ b/examples/other/use_mfa/local/detect_oov.py @@ -0,0 +1,48 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +from collections import OrderedDict +from pathlib import Path +import logging + + +def detect_oov(corpus_dir, lexicon_path, transcription_pattern="*.lab"): + corpus_dir = Path(corpus_dir) + + lexicon = OrderedDict() + with open(lexicon_path, 'rt') as f: + for line in f: + syllable, phonemes = line.split(maxsplit=1) + lexicon[syllable] = phonemes + + for fp in corpus_dir.glob(transcription_pattern): + syllables = fp.read_text().strip().split() + for s in syllables: + if s not in lexicon: + logging.warning(f"{fp.relative_to(corpus_dir)} has OOV {s} .") + + +if __name__ == "__main__": + parser = argparse.ArgumentParser( + description="detect oov in a corpus given a lexicon") + parser.add_argument( + "corpus_dir", type=str, help="corpus dir for MFA alignment.") + parser.add_argument("lexicon_path", type=str, help="dictionary to use.") + parser.add_argument( + "--pattern", type=str, default="*.lab", help="dictionary to use.") + args = parser.parse_args() + print(args) + + detect_oov(args.corpus_dir, args.lexicon_path, args.pattern) diff --git a/examples/other/use_mfa/local/generate_lexicon.py b/examples/other/use_mfa/local/generate_lexicon.py new file mode 100644 index 00000000..b6e594ab --- /dev/null +++ b/examples/other/use_mfa/local/generate_lexicon.py @@ -0,0 +1,199 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Generate lexicon and symbols for Mandarin Chinese phonology. +The lexicon is used for Montreal Force Aligner. + +Note that syllables are used as word in this lexicon. Since syllables rather +than words are used in transcriptions produced by `reorganize_baker.py`. + +We make this choice to better leverage other software for chinese text to +pinyin tools like pypinyin. This is the convention for G2P in Chinese. +""" + +import re +import argparse +from collections import OrderedDict + +INITIALS = [ + 'b', 'p', 'm', 'f', 'd', 't', 'n', 'l', 'g', 'k', 'h', 'zh', 'ch', 'sh', + 'r', 'z', 'c', 's', 'j', 'q', 'x' +] + +FINALS = [ + 'a', 'ai', 'ao', 'an', 'ang', 'e', 'er', 'ei', 'en', 'eng', 'o', 'ou', + 'ong', 'ii', 'iii', 'i', 'ia', 'iao', 'ian', 'iang', 'ie', 'io', 'iou', + 'iong', 'in', 'ing', 'u', 'ua', 'uai', 'uan', 'uang', 'uei', 'uo', 'uen', + 'ueng', 'v', 've', 'van', 'vn' +] + +SPECIALS = ['sil', 'sp'] + + +def rule(C, V, R, T): + """Generate a syllable given the initial, the final, erhua indicator, and tone. + Orthographical rules for pinyin are applied. (special case for y, w, ui, un, iu) + + Note that in this system, 'ü' is alway written as 'v' when appeared in phoneme, but converted to + 'u' in syllables when certain conditions are satisfied. + + 'i' is distinguished when appeared in phonemes, and separated into 3 categories, 'i', 'ii' and 'iii'. + + Erhua is is possibly applied to every finals, except for finals that already ends with 'r'. + + When a syllable is impossible or does not have any characters with this pronunciation, return None + to filter it out. + """ + + # 不可拼的音节, ii 只能和 z, c, s 拼 + if V in ["ii"] and (C not in ['z', 'c', 's']): + return None + # iii 只能和 zh, ch, sh, r 拼 + if V in ['iii'] and (C not in ['zh', 'ch', 'sh', 'r']): + return None + + # 齐齿呼或者撮口呼不能和 f, g, k, h, zh, ch, sh, r, z, c, s + if (V not in ['ii', 'iii']) and V[0] in ['i', 'v'] and ( + C in ['f', 'g', 'k', 'h', 'zh', 'ch', 'sh', 'r', 'z', 'c', 's']): + return None + + # 撮口呼只能和 j, q, x l, n 拼 + if V.startswith("v"): + # v, ve 只能和 j ,q , x, n, l 拼 + if V in ['v', 've']: + if C not in ['j', 'q', 'x', 'n', 'l', '']: + return None + # 其他只能和 j, q, x 拼 + else: + if C not in ['j', 'q', 'x', '']: + return None + + # j, q, x 只能和齐齿呼或者撮口呼拼 + if (C in ['j', 'q', 'x']) and not ( + (V not in ['ii', 'iii']) and V[0] in ['i', 'v']): + return None + + # b, p ,m, f 不能和合口呼拼，除了 u 之外 + # bm p, m, f 不能和撮口呼拼 + if (C in ['b', 'p', 'm', 'f']) and ((V[0] in ['u', 'v'] and V != "u") or + V == 'ong'): + return None + + # ua, uai, uang 不能和 d, t, n, l, r, z, c, s 拼 + if V in ['ua', 'uai', + 'uang'] and C in ['d', 't', 'n', 'l', 'r', 'z', 'c', 's']: + return None + + # sh 和 ong 不能拼 + if V == 'ong' and C in ['sh']: + return None + + # o 和 gkh, zh ch sh r z c s 不能拼 + if V == "o" and C in [ + 'd', 't', 'n', 'g', 'k', 'h', 'zh', 'ch', 'sh', 'r', 'z', 'c', 's' + ]: + return None + + # ueng 只是 weng 这个 ad-hoc 其他情况下都是 ong + if V == 'ueng' and C != '': + return + + # 非儿化的 er 只能单独存在 + if V == 'er' and C != '': + return None + + if C == '': + if V in ["i", "in", "ing"]: + C = 'y' + elif V == 'u': + C = 'w' + elif V.startswith('i') and V not in ["ii", "iii"]: + C = 'y' + V = V[1:] + elif V.startswith('u'): + C = 'w' + V = V[1:] + elif V.startswith('v'): + C = 'yu' + V = V[1:] + else: + if C in ['j', 'q', 'x']: + if V.startswith('v'): + V = re.sub('v', 'u', V) + if V == 'iou': + V = 'iu' + elif V == 'uei': + V = 'ui' + elif V == 'uen': + V = 'un' + result = C + V + + # Filter er 不能再儿化 + if result.endswith('r') and R == 'r': + return None + + # ii and iii, change back to i + result = re.sub(r'i+', 'i', result) + + result = result + R + T + return result + + +def generate_lexicon(with_tone=False, with_erhua=False): + """Generate lexicon for Mandarin Chinese.""" + syllables = OrderedDict() + + for C in [''] + INITIALS: + for V in FINALS: + for R in [''] if not with_erhua else ['', 'r']: + for T in [''] if not with_tone else ['1', '2', '3', '4', '5']: + result = rule(C, V, R, T) + if result: + syllables[result] = f'{C} {V}{R}{T}' + return syllables + + +def generate_symbols(lexicon): + """Generate phoneme list for a lexicon.""" + symbols = set() + for p in SPECIALS: + symbols.add(p) + for syllable, phonemes in lexicon.items(): + phonemes = phonemes.split() + for p in phonemes: + symbols.add(p) + return sorted(list(symbols)) + + +if __name__ == "__main__": + parser = argparse.ArgumentParser( + description="Generate lexicon for Chinese pinyin to phoneme for MFA") + parser.add_argument("output", type=str, help="Path to save lexicon.") + parser.add_argument( + "--with-tone", action="store_true", help="whether to consider tone.") + parser.add_argument( + "--with-r", action="store_true", help="whether to consider erhua.") + args = parser.parse_args() + + lexicon = generate_lexicon(args.with_tone, args.with_r) + symbols = generate_symbols(lexicon) + + with open(args.output + ".lexicon", 'wt') as f: + for k, v in lexicon.items(): + f.write(f"{k} {v}\n") + + with open(args.output + ".symbols", 'wt') as f: + for s in symbols: + f.write(s + "\n") + + print("Done!") diff --git a/examples/other/use_mfa/local/reorganize_aishell3.py b/examples/other/use_mfa/local/reorganize_aishell3.py new file mode 100644 index 00000000..0ad30662 --- /dev/null +++ b/examples/other/use_mfa/local/reorganize_aishell3.py @@ -0,0 +1,94 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Script to reorganize AISHELL-3 dataset so as to use Montreal Force +Aligner to align transcription and audio. + +Please refer to https://montreal-forced-aligner.readthedocs.io/en/latest/data_prep.html +for more details about Montreal Force Aligner's requirements on cotpus. + +For scripts to reorganize other corpus, please refer to + https://github.com/MontrealCorpusTools/MFA-reorganization-scripts +for more details. +""" +import argparse +import os +from pathlib import Path +from typing import Union + + +def link_wav(root_dir: Union[str, Path], output_dir: Union[str, Path]): + for sub_set in {'train', 'test'}: + wav_dir = root_dir / sub_set / 'wav' + new_dir = output_dir / sub_set + new_dir.mkdir(parents=True, exist_ok=True) + + for spk_dir in os.listdir(wav_dir): + sub_dir = wav_dir / spk_dir + new_sub_dir = new_dir / spk_dir + os.symlink(sub_dir, new_sub_dir) + + +def write_lab(root_dir: Union[str, Path], + output_dir: Union[str, Path], + script_type='pinyin'): + for sub_set in {'train', 'test'}: + text_path = root_dir / sub_set / 'content.txt' + new_dir = output_dir / sub_set + + with open(text_path, 'r') as rf: + for line in rf: + wav_id, context = line.strip().split('\t') + spk_id = wav_id[:7] + transcript_name = wav_id.split('.')[0] + '.lab' + transcript_path = new_dir / spk_id / transcript_name + context_list = context.split() + word_list = context_list[0:-1:2] + pinyin_list = context_list[1::2] + wf = open(transcript_path, 'w') + if script_type == 'word': + # add space between chinese char + new_context = ' '.join(word_list) + elif script_type == 'pinyin': + new_context = ' '.join(pinyin_list) + wf.write(new_context + '\n') + + +def reorganize_aishell3(root_dir: Union[str, Path], + output_dir: Union[str, Path], + script_type='pinyin'): + output_dir.mkdir(parents=True, exist_ok=True) + link_wav(root_dir, output_dir) + write_lab(root_dir, output_dir, script_type) + + +if __name__ == "__main__": + parser = argparse.ArgumentParser( + description="Reorganize AISHELL-3 dataset for MFA") + parser.add_argument( + "--root-dir", type=str, default="", help="path to AISHELL-3 dataset.") + parser.add_argument( + "--output-dir", + type=str, + help="path to save outputs (audio and transcriptions)") + parser.add_argument( + "--script-type", + type=str, + default="pinyin", + help="type of lab ('word'/'pinyin')") + + args = parser.parse_args() + root_dir = Path(args.root_dir).expanduser() + output_dir = Path(args.output_dir).expanduser() + output_dir.mkdir(parents=True, exist_ok=True) + reorganize_aishell3(root_dir, output_dir, args.script_type) diff --git a/examples/other/use_mfa/local/reorganize_baker.py b/examples/other/use_mfa/local/reorganize_baker.py new file mode 100644 index 00000000..8adad834 --- /dev/null +++ b/examples/other/use_mfa/local/reorganize_baker.py @@ -0,0 +1,112 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Script to reorganize Baker dataset so as to use Montreal Force +Aligner to align transcription and audio. + +Please refer to https://montreal-forced-aligner.readthedocs.io/en/latest/data_prep.html +for more details about Montreal Force Aligner's requirements on cotpus. + +For scripts to reorganize other corpus, please refer to + https://github.com/MontrealCorpusTools/MFA-reorganization-scripts +for more details. +""" +import argparse +import os +import shutil +from concurrent.futures import ThreadPoolExecutor +from pathlib import Path +from typing import Union + +import librosa +import soundfile as sf +from tqdm import tqdm + + +def get_transcripts(path: Union[str, Path]): + transcripts = {} + + with open(path) as f: + lines = f.readlines() + + for i in range(0, len(lines), 2): + sentence_id = lines[i].split()[0] + transcription = lines[i + 1].strip() + # tones are dropped here + # since the lexicon does not consider tones, too + transcription = " ".join([item[:-1] for item in transcription.split()]) + transcripts[sentence_id] = transcription + + return transcripts + + +def resample_and_save(source, target, sr=16000): + wav, _ = librosa.load(str(source), sr=sr) + sf.write(str(target), wav, samplerate=sr, subtype='PCM_16') + return target + + +def reorganize_baker(root_dir: Union[str, Path], + output_dir: Union[str, Path]=None, + resample_audio=False): + root_dir = Path(root_dir).expanduser() + transcript_path = root_dir / "ProsodyLabeling" / "000001-010000.txt" + transcriptions = get_transcripts(transcript_path) + + wave_dir = root_dir / "Wave" + wav_paths = sorted(list(wave_dir.glob("*.wav"))) + output_dir = Path(output_dir).expanduser() + assert wave_dir != output_dir, "Don't use an the original wav's directory as output_dir" + + output_dir.mkdir(parents=True, exist_ok=True) + + if resample_audio: + with ThreadPoolExecutor(os.cpu_count()) as pool: + with tqdm(total=len(wav_paths), desc="resampling") as pbar: + futures = [] + for wav_path in wav_paths: + future = pool.submit(resample_and_save, wav_path, + output_dir / wav_path.name) + future.add_done_callback(lambda p: pbar.update()) + futures.append(future) + + results = [] + for ft in futures: + results.append(ft.result()) + else: + for wav_path in tqdm(wav_paths, desc="copying"): + shutil.copyfile(wav_path, output_dir / wav_path.name) + + for sentence_id, transcript in tqdm( + transcriptions.items(), desc="transcription process"): + with open(output_dir / (sentence_id + ".lab"), 'wt') as f: + f.write(transcript) + f.write('\n') + print("Done!") + + +if __name__ == "__main__": + parser = argparse.ArgumentParser( + description="Reorganize Baker dataset for MFA") + parser.add_argument("--root-dir", type=str, help="path to baker dataset.") + parser.add_argument( + "--output-dir", + type=str, + help="path to save outputs (audio and transcriptions)") + parser.add_argument( + "--resample-audio", + action="store_true", + help="To resample audio files or just copy them") + args = parser.parse_args() + + reorganize_baker(args.root_dir, args.output_dir, args.resample_audio) diff --git a/examples/other/use_mfa/local/reorganize_ljspeech.py b/examples/other/use_mfa/local/reorganize_ljspeech.py new file mode 100644 index 00000000..82b076d5 --- /dev/null +++ b/examples/other/use_mfa/local/reorganize_ljspeech.py @@ -0,0 +1,72 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Script to reorganize LJSpeech-1.1 dataset so as to use Montreal Force +Aligner to align transcription and audio. + +Please refer to https://montreal-forced-aligner.readthedocs.io/en/latest/data_prep.html +for more details about Montreal Force Aligner's requirements on cotpus. + +For scripts to reorganize other corpus, please refer to + https://github.com/MontrealCorpusTools/MFA-reorganization-scripts +for more details. +""" +import argparse +import os +from pathlib import Path +from typing import Union + + +def link_wav(root_dir: Union[str, Path], output_dir: Union[str, Path]): + wav_dir = root_dir / 'wavs' + for spk_dir in os.listdir(wav_dir): + sub_dir = wav_dir / spk_dir + new_sub_dir = output_dir / spk_dir + os.symlink(sub_dir, new_sub_dir) + + +def write_lab(root_dir: Union[str, Path], output_dir: Union[str, Path]): + + text_path = root_dir / 'metadata.csv' + with open(text_path, 'r') as rf: + for line in rf: + line_list = line.strip().split('|') + utt = line_list[0] + raw_text = line_list[-1] + transcript_name = utt + '.lab' + transcript_path = output_dir / transcript_name + with open(transcript_path, 'w') as wf: + wf.write(raw_text + '\n') + + +def reorganize_ljspeech(root_dir: Union[str, Path], + output_dir: Union[str, Path]): + + link_wav(root_dir, output_dir) + write_lab(root_dir, output_dir) + + +if __name__ == "__main__": + parser = argparse.ArgumentParser( + description="Reorganize LJSpeech-1.1 dataset for MFA") + parser.add_argument( + "--root-dir", type=str, help="path to LJSpeech-1.1 dataset.") + parser.add_argument( + "--output-dir", + type=str, + help="path to save outputs (audio and transcriptions)") + args = parser.parse_args() + root_dir = Path(args.root_dir).expanduser() + output_dir = Path(args.output_dir).expanduser() + output_dir.mkdir(parents=True, exist_ok=True) + reorganize_ljspeech(root_dir, output_dir) diff --git a/examples/other/use_mfa/local/reorganize_vctk.py b/examples/other/use_mfa/local/reorganize_vctk.py new file mode 100644 index 00000000..f008edd3 --- /dev/null +++ b/examples/other/use_mfa/local/reorganize_vctk.py @@ -0,0 +1,121 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Script to reorganize VCTK dataset so as to use Montreal Force +Aligner to align transcription and audio. + +Please refer to https://montreal-forced-aligner.readthedocs.io/en/latest/data_prep.html +for more details about Montreal Force Aligner's requirements on cotpus. + +For scripts to reorganize other corpus, please refer to + https://github.com/MontrealCorpusTools/MFA-reorganization-scripts +for more details. +""" +import argparse +import os +from concurrent.futures import ThreadPoolExecutor +from pathlib import Path +from typing import Union + +import librosa +import soundfile as sf +from tqdm import tqdm + + +def resample_and_save(source, target, sr=16000): + wav, _ = librosa.load(str(source), sr=sr) + sf.write(str(target), wav, samplerate=sr, subtype='PCM_16') + return target + + +def write_wav(root_dir: Union[str, Path], output_dir: Union[str, Path]): + wav_paths = [] + new_wav_paths = [] + + wav_dir = root_dir / 'wav48_silence_trimmed' + new_dir = output_dir + new_dir.mkdir(parents=True, exist_ok=True) + + for spk_dir in os.listdir(wav_dir): + # no txt for p315 + # no mic2 for p280 and p362 + if spk_dir not in {'log.txt', 'p315', 'p280', 'p362'}: + sub_dir = wav_dir / spk_dir + new_sub_dir = new_dir / spk_dir + new_sub_dir.mkdir(parents=True, exist_ok=True) + for wav_name in os.listdir(sub_dir): + # mic1 have very low frequency noises + pre_wav_name = "_".join(wav_name.split("_")[:2]) + if "mic2" in wav_name: + wav_paths.append(str(sub_dir / wav_name)) + # remove "_mic2" in wav_name and replace ".flac" with ".wav" + new_wav_name = pre_wav_name + ".wav" + new_wav_paths.append(str(new_sub_dir / new_wav_name)) + + assert len(new_wav_paths) == len(wav_paths) + + with ThreadPoolExecutor(os.cpu_count()) as pool: + with tqdm(total=len(wav_paths), desc="resampling") as pbar: + futures = [] + for i, wav_path in enumerate(wav_paths): + future = pool.submit(resample_and_save, wav_path, + new_wav_paths[i]) + future.add_done_callback(lambda p: pbar.update()) + futures.append(future) + + results = [] + for ft in futures: + results.append(ft.result()) + + +def write_txt(root_dir: Union[str, Path], output_dir: Union[str, Path]): + txt_dir = root_dir / 'txt' + + new_dir = output_dir + new_dir.mkdir(parents=True, exist_ok=True) + for spk_dir in os.listdir(txt_dir): + # no txt for p315 + if spk_dir not in {'log.txt', 'p315', 'p280', 'p362'}: + sub_dir = txt_dir / spk_dir + new_sub_dir = new_dir / spk_dir + for txt_name in os.listdir(sub_dir): + rf = open(sub_dir / txt_name, "r") + wf = open(new_sub_dir / txt_name, "w") + for line in rf: + wf.write(line) + + +def reorganize_vctk(root_dir: Union[str, Path], output_dir: Union[str, Path]): + output_dir.mkdir(parents=True, exist_ok=True) + write_wav(root_dir, output_dir) + write_txt(root_dir, output_dir) + + +if __name__ == "__main__": + parser = argparse.ArgumentParser( + description="Reorganize VCTK-Corpus-0.92 dataset for MFA") + parser.add_argument( + "--root-dir", + type=str, + default="", + help="path to VCTK-Corpus-0.92 dataset.") + parser.add_argument( + "--output-dir", + type=str, + help="path to save outputs (audio and transcriptions)") + + args = parser.parse_args() + root_dir = Path(args.root_dir).expanduser() + output_dir = Path(args.output_dir).expanduser() + output_dir.mkdir(parents=True, exist_ok=True) + reorganize_vctk(root_dir, output_dir) diff --git a/examples/other/use_mfa/run.sh b/examples/other/use_mfa/run.sh new file mode 100644 index 00000000..1fef58b4 --- /dev/null +++ b/examples/other/use_mfa/run.sh @@ -0,0 +1,49 @@ +EXP_DIR=exp + +mkdir -p $EXP_DIR +LEXICON_NAME='simple' +if [ ! -f "$EXP_DIR/$LEXICON_NAME.lexicon" ]; then + echo "generating lexicon..." + python local/generate_lexicon.py "$EXP_DIR/$LEXICON_NAME" --with-r + echo "lexicon done" +fi + +if [ ! -d $EXP_DIR/baker_corpus ]; then + echo "reorganizing baker corpus..." + python local/reorganize_baker.py --root-dir=~/datasets/BZNSYP --output-dir=$EXP_DIR/baker_corpus --resample-audio + echo "reorganization done. Check output in $EXP_DIR/baker_corpus." + echo "audio files are resampled to 16kHz" + echo "transcription for each audio file is saved with the same namd in $EXP_DIR/baker_corpus " +fi + +echo "detecting oov..." +python local/detect_oov.py $EXP_DIR/baker_corpus $EXP_DIR/"$LEXICON_NAME.lexicon" +echo "detecting oov done. you may consider regenerate lexicon if there is unexpected OOVs." + + +MFA_DOWNLOAD_DIR=local/ + +if [ ! -f "$MFA_DOWNLOAD_DIR/montreal-forced-aligner_linux.tar.gz" ]; then + echo "downloading mfa..." + (cd $MFA_DOWNLOAD_DIR && wget https://github.com/MontrealCorpusTools/Montreal-Forced-Aligner/releases/download/v1.0.1/montreal-forced-aligner_linux.tar.gz) + echo "download mfa done!" +fi + +if [ ! -d "$MFA_DOWNLOAD_DIR/montreal-forced-aligner" ]; then + echo "extracting mfa..." + (cd $MFA_DOWNLOAD_DIR && tar xvf "montreal-forced-aligner_linux.tar.gz") + echo "extraction done!" +fi + +export PATH="$MFA_DOWNLOAD_DIR/montreal-forced-aligner/bin" +if [ ! -d "$EXP_DIR/baker_alignment" ]; then + echo "Start MFA training..." + mfa_train_and_align $EXP_DIR/baker_corpus "$EXP_DIR/$LEXICON_NAME.lexicon" $EXP_DIR/baker_alignment -o $EXP_DIR/baker_model --clean --verbose --temp_directory exp/.mfa_train_and_align + echo "training done!" + echo "results: $EXP_DIR/baker_alignment" + echo "model: $EXP_DIR/baker_model" +fi + + + + diff --git a/examples/vctk/GANVocoder/README.md b/examples/vctk/GANVocoder/README.md new file mode 100644 index 00000000..3109be17 --- /dev/null +++ b/examples/vctk/GANVocoder/README.md @@ -0,0 +1 @@ +different GAN Vocoders have the same preprocess.py and normalize.py diff --git a/examples/vctk/GANVocoder/normalize.py b/examples/vctk/GANVocoder/normalize.py new file mode 100644 index 00000000..74d838ad --- /dev/null +++ b/examples/vctk/GANVocoder/normalize.py @@ -0,0 +1,133 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Normalize feature files and dump them.""" + +import argparse +import logging +from operator import itemgetter +from pathlib import Path + +import jsonlines +import numpy as np +from parakeet.datasets.data_table import DataTable +from sklearn.preprocessing import StandardScaler +from tqdm import tqdm + + +def main(): + """Run preprocessing process.""" + parser = argparse.ArgumentParser( + description="Normalize dumped raw features.") + parser.add_argument( + "--metadata", + type=str, + required=True, + help="directory including feature files to be normalized. " + "you need to specify either *-scp or rootdir.") + parser.add_argument( + "--dumpdir", + type=str, + required=True, + help="directory to dump normalized feature files.") + parser.add_argument( + "--stats", type=str, required=True, help="statistics file.") + parser.add_argument( + "--skip-wav-copy", + default=False, + action="store_true", + help="whether to skip the copy of wav files.") + parser.add_argument( + "--verbose", + type=int, + default=1, + help="logging level. higher is more logging. (default=1)") + args = parser.parse_args() + + # set logger + if args.verbose > 1: + logging.basicConfig( + level=logging.DEBUG, + format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s" + ) + elif args.verbose > 0: + logging.basicConfig( + level=logging.INFO, + format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s" + ) + else: + logging.basicConfig( + level=logging.WARN, + format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s" + ) + logging.warning('Skip DEBUG/INFO messages') + + dumpdir = Path(args.dumpdir).expanduser() + # use absolute path + dumpdir = dumpdir.resolve() + dumpdir.mkdir(parents=True, exist_ok=True) + + # get dataset + with jsonlines.open(args.metadata, 'r') as reader: + metadata = list(reader) + dataset = DataTable( + metadata, + fields=["utt_id", "wave", "feats"], + converters={ + 'utt_id': None, + 'wave': None if args.skip_wav_copy else np.load, + 'feats': np.load, + }) + logging.info(f"The number of files = {len(dataset)}.") + + # restore scaler + scaler = StandardScaler() + scaler.mean_ = np.load(args.stats)[0] + scaler.scale_ = np.load(args.stats)[1] + + # from version 0.23.0, this information is needed + scaler.n_features_in_ = scaler.mean_.shape[0] + + # process each file + output_metadata = [] + + for item in tqdm(dataset): + utt_id = item['utt_id'] + wave = item['wave'] + mel = item['feats'] + # normalize + mel = scaler.transform(mel) + + # save + mel_path = dumpdir / f"{utt_id}_feats.npy" + np.save(mel_path, mel.astype(np.float32), allow_pickle=False) + if not args.skip_wav_copy: + wav_path = dumpdir / f"{utt_id}_wave.npy" + np.save(wav_path, wave.astype(np.float32), allow_pickle=False) + else: + wav_path = wave + output_metadata.append({ + 'utt_id': utt_id, + 'wave': str(wav_path), + 'feats': str(mel_path), + }) + output_metadata.sort(key=itemgetter('utt_id')) + output_metadata_path = Path(args.dumpdir) / "metadata.jsonl" + with jsonlines.open(output_metadata_path, 'w') as writer: + for item in output_metadata: + writer.write(item) + logging.info(f"metadata dumped into {output_metadata_path}") + + +if __name__ == "__main__": + main() diff --git a/examples/vctk/GANVocoder/parallelwave_gan/baker/README.md b/examples/vctk/GANVocoder/parallelwave_gan/baker/README.md new file mode 100644 index 00000000..a58fd922 --- /dev/null +++ b/examples/vctk/GANVocoder/parallelwave_gan/baker/README.md @@ -0,0 +1,136 @@ +# Parallel WaveGAN with CSMSC +This example contains code used to train a [parallel wavegan](http://arxiv.org/abs/1910.11480) model with [Chinese Standard Mandarin Speech Copus](https://www.data-baker.com/open_source.html). +## Preprocess the dataset +### Download and Extract the datasaet +Download CSMSC from the [official website](https://www.data-baker.com/data/index/source) and extract it to `~/datasets`. Then the dataset is in directory `~/datasets/BZNSYP`. + +### Get MFA results for silence trim +We use [MFA](https://github.com/MontrealCorpusTools/Montreal-Forced-Aligner) results to cut silence in the edge of audio. +You can download from here [baker_alignment_tone.tar.gz](https://paddlespeech.bj.bcebos.com/MFA/BZNSYP/with_tone/baker_alignment_tone.tar.gz), or train your own MFA model reference to [use_mfa example](https://github.com/PaddlePaddle/Parakeet/tree/develop/examples/use_mfa) of our repo. + +### Preprocess the dataset +Assume the path to the dataset is `~/datasets/BZNSYP`. +Assume the path to the MFA result of CSMSC is `./baker_alignment_tone`. +Run the command below to preprocess the dataset. +```bash +./preprocess.sh +``` +When it is done. A `dump` folder is created in the current directory. The structure of the dump folder is listed below. + +```text +dump +├── dev +│ ├── norm +│ └── raw +├── test +│ ├── norm +│ └── raw +└── train + ├── norm + ├── raw + └── feats_stats.npy +``` + +The dataset is split into 3 parts, namely `train`, `dev` and `test`, each of which contains a `norm` and `raw` subfolder. The `raw` folder contains log magnitude of mel spectrogram of each utterances, while the norm folder contains normalized spectrogram. The statistics used to normalize the spectrogram is computed from the training set, which is located in `dump/train/feats_stats.npy`. + +Also there is a `metadata.jsonl` in each subfolder. It is a table-like file which contains id and paths to spectrogam of each utterance. + +## Train the model + +`./run.sh` calls `../train.py`. +```bash +./run.sh +``` +Here's the complete help message. + +```text +usage: train.py [-h] [--config CONFIG] [--train-metadata TRAIN_METADATA] + [--dev-metadata DEV_METADATA] [--output-dir OUTPUT_DIR] + [--device DEVICE] [--nprocs NPROCS] [--verbose VERBOSE] + [--batch-size BATCH_SIZE] [--max-iter MAX_ITER] + [--run-benchmark RUN_BENCHMARK] + [--profiler_options PROFILER_OPTIONS] + +Train a ParallelWaveGAN model. + +optional arguments: + -h, --help show this help message and exit + --config CONFIG config file to overwrite default config. + --train-metadata TRAIN_METADATA + training data. + --dev-metadata DEV_METADATA + dev data. + --output-dir OUTPUT_DIR + output dir. + --device DEVICE device type to use. + --nprocs NPROCS number of processes. + --verbose VERBOSE verbose. + +benchmark: + arguments related to benchmark. + + --batch-size BATCH_SIZE + batch size. + --max-iter MAX_ITER train max steps. + --run-benchmark RUN_BENCHMARK + runing benchmark or not, if True, use the --batch-size + and --max-iter. + --profiler_options PROFILER_OPTIONS + The option of profiler, which should be in format + "key1=value1;key2=value2;key3=value3". +``` + +1. `--config` is a config file in yaml format to overwrite the default config, which can be found at `conf/default.yaml`. +2. `--train-metadata` and `--dev-metadata` should be the metadata file in the normalized subfolder of `train` and `dev` in the `dump` folder. +3. `--output-dir` is the directory to save the results of the experiment. Checkpoints are save in `checkpoints/` inside this directory. +4. `--device` is the type of the device to run the experiment, 'cpu' or 'gpu' are supported. +5. `--nprocs` is the number of processes to run in parallel, note that nprocs > 1 is only supported when `--device` is 'gpu'. + +## Pretrained Models + +Pretrained models can be downloaded here: +1. Parallel WaveGAN checkpoint. [pwg_baker_ckpt_0.4.zip](https://paddlespeech.bj.bcebos.com/Parakeet/pwg_baker_ckpt_0.4.zip), which is used as a vocoder in the end-to-end inference script. + +Parallel WaveGAN checkpoint contains files listed below. + +```text +pwg_baker_ckpt_0.4 +├── pwg_default.yaml # default config used to train parallel wavegan +├── pwg_snapshot_iter_400000.pdz # generator parameters of parallel wavegan +└── pwg_stats.npy # statistics used to normalize spectrogram when training parallel wavegan +``` + +## Synthesize + +`synthesize.sh` calls `../synthesize.py `, which can synthesize waveform from `metadata.jsonl`. +```bash +./synthesize.sh +``` +```text +usage: synthesize.py [-h] [--config CONFIG] [--checkpoint CHECKPOINT] + [--test-metadata TEST_METADATA] [--output-dir OUTPUT_DIR] + [--device DEVICE] [--verbose VERBOSE] + +Synthesize with parallel wavegan. + +optional arguments: + -h, --help show this help message and exit + --config CONFIG parallel wavegan config file. + --checkpoint CHECKPOINT + snapshot to load. + --test-metadata TEST_METADATA + dev data. + --output-dir OUTPUT_DIR + output dir. + --device DEVICE device to run. + --verbose VERBOSE verbose. +``` + +1. `--config` parallel wavegan config file. You should use the same config with which the model is trained. +2. `--checkpoint` is the checkpoint to load. Pick one of the checkpoints from `checkpoints` inside the training output directory. If you use the pretrained model, use the `pwg_snapshot_iter_400000.pdz`. +3. `--test-metadata` is the metadata of the test dataset. Use the `metadata.jsonl` in the `dev/norm` subfolder from the processed directory. +4. `--output-dir` is the directory to save the synthesized audio files. +5. `--device` is the type of device to run synthesis, 'cpu' and 'gpu' are supported. + +## Acknowledgement +We adapted some code from https://github.com/kan-bayashi/ParallelWaveGAN. diff --git a/examples/vctk/GANVocoder/parallelwave_gan/baker/conf/default.yaml b/examples/vctk/GANVocoder/parallelwave_gan/baker/conf/default.yaml new file mode 100644 index 00000000..5628b7f7 --- /dev/null +++ b/examples/vctk/GANVocoder/parallelwave_gan/baker/conf/default.yaml @@ -0,0 +1,122 @@ +# This is the hyperparameter configuration file for Parallel WaveGAN. +# Please make sure this is adjusted for the CSMSC dataset. If you want to +# apply to the other dataset, you might need to carefully change some parameters. +# This configuration requires 12 GB GPU memory and takes ~3 days on RTX TITAN. + +########################################################### +# FEATURE EXTRACTION SETTING # +########################################################### +fs: 24000 # Sampling rate. +n_fft: 2048 # FFT size. (in samples) +n_shift: 300 # Hop size. (in samples) +win_length: 1200 # Window length. (in samples) + # If set to null, it will be the same as fft_size. +window: "hann" # Window function. +n_mels: 80 # Number of mel basis. +fmin: 80 # Minimum freq in mel basis calculation. (Hz) +fmax: 7600 # Maximum frequency in mel basis calculation. (Hz) + + +########################################################### +# GENERATOR NETWORK ARCHITECTURE SETTING # +########################################################### +generator_params: + in_channels: 1 # Number of input channels. + out_channels: 1 # Number of output channels. + kernel_size: 3 # Kernel size of dilated convolution. + layers: 30 # Number of residual block layers. + stacks: 3 # Number of stacks i.e., dilation cycles. + residual_channels: 64 # Number of channels in residual conv. + gate_channels: 128 # Number of channels in gated conv. + skip_channels: 64 # Number of channels in skip conv. + aux_channels: 80 # Number of channels for auxiliary feature conv. + # Must be the same as num_mels. + aux_context_window: 2 # Context window size for auxiliary feature. + # If set to 2, previous 2 and future 2 frames will be considered. + dropout: 0.0 # Dropout rate. 0.0 means no dropout applied. + bias: true # use bias in residual blocks + use_weight_norm: true # Whether to use weight norm. + # If set to true, it will be applied to all of the conv layers. + use_causal_conv: false # use causal conv in residual blocks and upsample layers + upsample_scales: [4, 5, 3, 5] # Upsampling scales. Prodcut of these must be the same as hop size. + interpolate_mode: "nearest" # upsample net interpolate mode + freq_axis_kernel_size: 1 # upsamling net: convolution kernel size in frequencey axis + nonlinear_activation: null + nonlinear_activation_params: {} + +########################################################### +# DISCRIMINATOR NETWORK ARCHITECTURE SETTING # +########################################################### +discriminator_params: + in_channels: 1 # Number of input channels. + out_channels: 1 # Number of output channels. + kernel_size: 3 # Number of output channels. + layers: 10 # Number of conv layers. + conv_channels: 64 # Number of chnn layers. + bias: true # Whether to use bias parameter in conv. + use_weight_norm: true # Whether to use weight norm. + # If set to true, it will be applied to all of the conv layers. + nonlinear_activation: "LeakyReLU" # Nonlinear function after each conv. + nonlinear_activation_params: # Nonlinear function parameters + negative_slope: 0.2 # Alpha in LeakyReLU. + +########################################################### +# STFT LOSS SETTING # +########################################################### +stft_loss_params: + fft_sizes: [1024, 2048, 512] # List of FFT size for STFT-based loss. + hop_sizes: [120, 240, 50] # List of hop size for STFT-based loss + win_lengths: [600, 1200, 240] # List of window length for STFT-based loss. + window: "hann" # Window function for STFT-based loss + +########################################################### +# ADVERSARIAL LOSS SETTING # +########################################################### +lambda_adv: 4.0 # Loss balancing coefficient. + +########################################################### +# DATA LOADER SETTING # +########################################################### +batch_size: 8 # Batch size. +batch_max_steps: 25500 # Length of each audio in batch. Make sure dividable by hop_size. +pin_memory: true # Whether to pin memory in Pytorch DataLoader. +num_workers: 4 # Number of workers in Pytorch DataLoader. +remove_short_samples: true # Whether to remove samples the length of which are less than batch_max_steps. +allow_cache: true # Whether to allow cache in dataset. If true, it requires cpu memory. + +########################################################### +# OPTIMIZER & SCHEDULER SETTING # +########################################################### +generator_optimizer_params: + epsilon: 1.0e-6 # Generator's epsilon. + weight_decay: 0.0 # Generator's weight decay coefficient. +generator_scheduler_params: + learning_rate: 0.0001 # Generator's learning rate. + step_size: 200000 # Generator's scheduler step size. + gamma: 0.5 # Generator's scheduler gamma. + # At each step size, lr will be multiplied by this parameter. +generator_grad_norm: 10 # Generator's gradient norm. +discriminator_optimizer_params: + epsilon: 1.0e-6 # Discriminator's epsilon. + weight_decay: 0.0 # Discriminator's weight decay coefficient. +discriminator_scheduler_params: + learning_rate: 0.00005 # Discriminator's learning rate. + step_size: 200000 # Discriminator's scheduler step size. + gamma: 0.5 # Discriminator's scheduler gamma. + # At each step size, lr will be multiplied by this parameter. +discriminator_grad_norm: 1 # Discriminator's gradient norm. + +########################################################### +# INTERVAL SETTING # +########################################################### +discriminator_train_start_steps: 100000 # Number of steps to start to train discriminator. +train_max_steps: 400000 # Number of training steps. +save_interval_steps: 5000 # Interval steps to save checkpoint. +eval_interval_steps: 1000 # Interval steps to evaluate the network. + +########################################################### +# OTHER SETTING # +########################################################### +num_save_intermediate_results: 4 # Number of results to be saved as intermediate results. +num_snapshots: 10 # max number of snapshots to keep while training +seed: 42 # random seed for paddle, random, and np.random diff --git a/examples/vctk/GANVocoder/parallelwave_gan/baker/preprocess.sh b/examples/vctk/GANVocoder/parallelwave_gan/baker/preprocess.sh new file mode 100755 index 00000000..df5b7d22 --- /dev/null +++ b/examples/vctk/GANVocoder/parallelwave_gan/baker/preprocess.sh @@ -0,0 +1,54 @@ +#!/bin/bash + +stage=0 +stop_stage=100 + +export MAIN_ROOT=`realpath ${PWD}/../../../../` + +if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then + # get durations from MFA's result + echo "Generate durations.txt from MFA results ..." + python3 ${MAIN_ROOT}/utils/gen_duration_from_textgrid.py \ + --inputdir=./baker_alignment_tone \ + --output=durations.txt \ + --config=conf/default.yaml +fi + +if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then + echo "Extract features ..." + python3 ../../preprocess.py \ + --rootdir=~/datasets/BZNSYP/ \ + --dataset=baker \ + --dumpdir=dump \ + --dur-file=durations.txt \ + --config=conf/default.yaml \ + --cut-sil=True \ + --num-cpu=20 +fi + +if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then + # get features' stats(mean and std) + echo "Get features' stats ..." + python3 ${MAIN_ROOT}/utils/compute_statistics.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --field-name="feats" +fi + +if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then + # normalize, dev and test should use train's stats + echo "Normalize ..." + + python3 ../../normalize.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --dumpdir=dump/train/norm \ + --stats=dump/train/feats_stats.npy + python3 ../../normalize.py \ + --metadata=dump/dev/raw/metadata.jsonl \ + --dumpdir=dump/dev/norm \ + --stats=dump/train/feats_stats.npy + + python3 ../../normalize.py \ + --metadata=dump/test/raw/metadata.jsonl \ + --dumpdir=dump/test/norm \ + --stats=dump/train/feats_stats.npy +fi diff --git a/examples/vctk/GANVocoder/parallelwave_gan/baker/run.sh b/examples/vctk/GANVocoder/parallelwave_gan/baker/run.sh new file mode 100755 index 00000000..df8cefd8 --- /dev/null +++ b/examples/vctk/GANVocoder/parallelwave_gan/baker/run.sh @@ -0,0 +1,10 @@ +#!/bin/bash + +FLAGS_cudnn_exhaustive_search=true \ +FLAGS_conv_workspace_size_limit=4000 \ +python ../train.py \ + --train-metadata=dump/train/norm/metadata.jsonl \ + --dev-metadata=dump/dev/norm/metadata.jsonl \ + --config=conf/default.yaml \ + --output-dir=exp/default \ + --nprocs=1 diff --git a/examples/vctk/GANVocoder/parallelwave_gan/baker/synthesize.sh b/examples/vctk/GANVocoder/parallelwave_gan/baker/synthesize.sh new file mode 100755 index 00000000..e95b0da8 --- /dev/null +++ b/examples/vctk/GANVocoder/parallelwave_gan/baker/synthesize.sh @@ -0,0 +1,8 @@ +#!/bin/bash +FLAGS_allocator_strategy=naive_best_fit \ +FLAGS_fraction_of_gpu_memory_to_use=0.01 \ +python3 ../synthesize.py \ + --config=conf/default.yaml \ + --checkpoint=exp/default/checkpoints/snapshot_iter_400000.pdz\ + --test-metadata=dump/test/norm/metadata.jsonl \ + --output-dir=exp/default/test diff --git a/examples/vctk/GANVocoder/parallelwave_gan/baker/synthesize_from_wav.py b/examples/vctk/GANVocoder/parallelwave_gan/baker/synthesize_from_wav.py new file mode 100644 index 00000000..f20f0a72 --- /dev/null +++ b/examples/vctk/GANVocoder/parallelwave_gan/baker/synthesize_from_wav.py @@ -0,0 +1,124 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +import os +import logging +from pathlib import Path + +import librosa +import numpy as np +import paddle +import soundfile as sf +import yaml +from parakeet.data.get_feats import LogMelFBank +from parakeet.models.parallel_wavegan import PWGGenerator +from parakeet.models.parallel_wavegan import PWGInference +from parakeet.modules.normalizer import ZScore +from yacs.config import CfgNode as Configuration + + +def get_cfg_default(): + config_path = (Path(__file__).parent / "conf" / "default.yaml").resolve() + with open(config_path, 'rt') as f: + _C = yaml.safe_load(f) + _C = Configuration(_C) + config = _C.clone() + return config + + +def evaluate(args, config): + # dataloader has been too verbose + logging.getLogger("DataLoader").disabled = True + + vocoder = PWGGenerator(**config["generator_params"]) + state_dict = paddle.load(args.checkpoint) + vocoder.set_state_dict(state_dict["generator_params"]) + vocoder.remove_weight_norm() + vocoder.eval() + print("model done!") + + stat = np.load(args.stat) + mu, std = stat + mu = paddle.to_tensor(mu) + std = paddle.to_tensor(std) + normalizer = ZScore(mu, std) + + pwg_inference = PWGInference(normalizer, vocoder) + + input_dir = Path(args.input_dir) + output_dir = Path(args.output_dir) + output_dir.mkdir(parents=True, exist_ok=True) + + mel_extractor = LogMelFBank( + sr=config.fs, + n_fft=config.n_fft, + hop_length=config.n_shift, + win_length=config.win_length, + window=config.window, + n_mels=config.n_mels, + fmin=config.fmin, + fmax=config.fmax) + + for utt_name in os.listdir(input_dir): + wav, _ = librosa.load(str(input_dir / utt_name), sr=config.fs) + # extract mel feats + mel = mel_extractor.get_log_mel_fbank(wav) + mel = paddle.to_tensor(mel) + with paddle.no_grad(): + gen_wav = pwg_inference(mel) + sf.write( + str(output_dir / ("gen_" + utt_name)), + gen_wav.numpy(), + samplerate=config.fs) + print(f"{utt_name} done!") + + +def main(): + # parse args and config and redirect to train_sp + parser = argparse.ArgumentParser( + description="Synthesize with parallel wavegan.") + + parser.add_argument( + "--config", type=str, help="config file to overwrite default config.") + parser.add_argument("--checkpoint", type=str, help="snapshot to load.") + parser.add_argument( + "--stat", + type=str, + help="mean and standard deviation used to normalize spectrogram when training parallel wavegan." + ) + parser.add_argument("--input-dir", type=str, help="input dir of wavs.") + parser.add_argument("--output-dir", type=str, help="output dir.") + parser.add_argument( + "--device", type=str, default="gpu", help="device to run.") + parser.add_argument("--verbose", type=int, default=1, help="verbose.") + + args = parser.parse_args() + + paddle.set_device(args.device) + + config = get_cfg_default() + if args.config: + config.merge_from_file(args.config) + + print("========Args========") + print(yaml.safe_dump(vars(args))) + print("========Config========") + print(config) + + evaluate(args, config) + + +if __name__ == "__main__": + main() diff --git a/examples/vctk/GANVocoder/parallelwave_gan/ljspeech/README.md b/examples/vctk/GANVocoder/parallelwave_gan/ljspeech/README.md new file mode 100644 index 00000000..5b54ef5a --- /dev/null +++ b/examples/vctk/GANVocoder/parallelwave_gan/ljspeech/README.md @@ -0,0 +1,136 @@ +# Parallel WaveGAN with the LJSpeech-1.1 dataset + +This example contains code used to train a [parallel wavegan](http://arxiv.org/abs/1910.11480) model with [LJSpeech-1.1](https://keithito.com/LJ-Speech-Dataset/). + +## Preprocess the dataset + +### Download and Extract the datasaet +Download LJSpeech-1.1 from the [official website](https://keithito.com/LJ-Speech-Dataset/). + +### Get MFA results for silence trim +We use [MFA](https://github.com/MontrealCorpusTools/Montreal-Forced-Aligner) results to cut silence in the edge of audio. +You can download from here [ljspeech_alignment.tar.gz](https://paddlespeech.bj.bcebos.com/MFA/LJSpeech-1.1/ljspeech_alignment.tar.gz), or train your own MFA model reference to [use_mfa example](https://github.com/PaddlePaddle/Parakeet/tree/develop/examples/use_mfa) of our repo. + +### Preprocess the dataset +Assume the path to the dataset is `~/datasets/LJSpeech-1.1`. +Assume the path to the MFA result of LJSpeech-1.1 is `./ljspeech_alignment`. +Run the command below to preprocess the dataset. +```bash +./preprocess.sh +``` +When it is done. A `dump` folder is created in the current directory. The structure of the dump folder is listed below. + +```text +dump +├── dev +│ ├── norm +│ └── raw +├── test +│ ├── norm +│ └── raw +└── train + ├── norm + ├── raw + └── feats_stats.npy +``` + +The dataset is split into 3 parts, namely `train`, `dev` and `test`, each of which contains a `norm` and `raw` subfolder. The `raw` folder contains log magnitude of mel spectrogram of each utterances, while the norm folder contains normalized spectrogram. The statistics used to normalize the spectrogram is computed from the training set, which is located in `dump/train/feats_stats.npy`. + +Also there is a `metadata.jsonl` in each subfolder. It is a table-like file which contains id and paths to spectrogam of each utterance. + +## Train the model +`./run.sh` calls `../train.py`. +```bash +./run.sh +``` +Here's the complete help message. + +```text +usage: train.py [-h] [--config CONFIG] [--train-metadata TRAIN_METADATA] + [--dev-metadata DEV_METADATA] [--output-dir OUTPUT_DIR] + [--device DEVICE] [--nprocs NPROCS] [--verbose VERBOSE] + [--batch-size BATCH_SIZE] [--max-iter MAX_ITER] + [--run-benchmark RUN_BENCHMARK] + [--profiler_options PROFILER_OPTIONS] + +Train a ParallelWaveGAN model. + +optional arguments: + -h, --help show this help message and exit + --config CONFIG config file to overwrite default config. + --train-metadata TRAIN_METADATA + training data. + --dev-metadata DEV_METADATA + dev data. + --output-dir OUTPUT_DIR + output dir. + --device DEVICE device type to use. + --nprocs NPROCS number of processes. + --verbose VERBOSE verbose. + +benchmark: + arguments related to benchmark. + + --batch-size BATCH_SIZE + batch size. + --max-iter MAX_ITER train max steps. + --run-benchmark RUN_BENCHMARK + runing benchmark or not, if True, use the --batch-size + and --max-iter. + --profiler_options PROFILER_OPTIONS + The option of profiler, which should be in format + "key1=value1;key2=value2;key3=value3". +``` + +1. `--config` is a config file in yaml format to overwrite the default config, which can be found at `conf/default.yaml`. +2. `--train-metadata` and `--dev-metadata` should be the metadata file in the normalized subfolder of `train` and `dev` in the `dump` folder. +3. `--output-dir` is the directory to save the results of the experiment. Checkpoints are save in `checkpoints/` inside this directory. +4. `--device` is the type of the device to run the experiment, 'cpu' or 'gpu' are supported. +5. `--nprocs` is the number of processes to run in parallel, note that nprocs > 1 is only supported when `--device` is 'gpu'. + +## Pretrained Models +Pretrained models can be downloaded here: +1. Parallel WaveGAN checkpoint. [pwg_ljspeech_ckpt_0.5.zip](https://paddlespeech.bj.bcebos.com/Parakeet/pwg_ljspeech_ckpt_0.5.zip), which is used as a vocoder in the end-to-end inference script. + +Parallel WaveGAN checkpoint contains files listed below. + +```text +pwg_ljspeech_ckpt_0.5 +├── pwg_default.yaml # default config used to train parallel wavegan +├── pwg_snapshot_iter_400000.pdz # generator parameters of parallel wavegan +└── pwg_stats.npy # statistics used to normalize spectrogram when training parallel wavegan +``` + +## Synthesize +`synthesize.sh` calls `../synthesize.py `, which can synthesize waveform from `metadata.jsonl`. +```bash +./synthesize.sh +``` +```text +usage: synthesize.py [-h] [--config CONFIG] [--checkpoint CHECKPOINT] + [--test-metadata TEST_METADATA] [--output-dir OUTPUT_DIR] + [--device DEVICE] [--verbose VERBOSE] + +Synthesize with parallel wavegan. + +optional arguments: + -h, --help show this help message and exit + --config CONFIG parallel wavegan config file. + --checkpoint CHECKPOINT + snapshot to load. + --test-metadata TEST_METADATA + dev data. + --output-dir OUTPUT_DIR + output dir. + --device DEVICE device to run. + --verbose VERBOSE verbose. +``` + +1. `--config` parallel wavegan config file. You should use the same config with which the model is trained. +2. `--checkpoint` is the checkpoint to load. Pick one of the checkpoints from `checkpoints` inside the training output directory. If you use the pretrained model, use the `pwg_snapshot_iter_400000.pdz`. +3. `--test-metadata` is the metadata of the test dataset. Use the `metadata.jsonl` in the `dev/norm` subfolder from the processed directory. +4. `--output-dir` is the directory to save the synthesized audio files. +5. `--device` is the type of device to run synthesis, 'cpu' and 'gpu' are supported. + +## Acknowledgement +We adapted some code from https://github.com/kan-bayashi/ParallelWaveGAN. diff --git a/examples/vctk/GANVocoder/parallelwave_gan/ljspeech/conf/default.yaml b/examples/vctk/GANVocoder/parallelwave_gan/ljspeech/conf/default.yaml new file mode 100644 index 00000000..2edec3b9 --- /dev/null +++ b/examples/vctk/GANVocoder/parallelwave_gan/ljspeech/conf/default.yaml @@ -0,0 +1,115 @@ +# This is the hyperparameter configuration file for Parallel WaveGAN. +# Please make sure this is adjusted for the LJSpeech dataset. If you want to +# apply to the other dataset, you might need to carefully change some parameters. +# This configuration requires 12 GB GPU memory and takes ~3 days on TITAN V. + +########################################################### +# FEATURE EXTRACTION SETTING # +########################################################### +fs: 22050 # Sampling rate. +n_fft: 1024 # FFT size. (in samples) +n_shift: 256 # Hop size. (in samples) +win_length: null # Window length. (in samples) + # If set to null, it will be the same as fft_size. +window: "hann" # Window function. +n_mels: 80 # Number of mel basis. +fmin: 80 # Minimum freq in mel basis calculation. (Hz) +fmax: 7600 # Maximum frequency in mel basis calculation. (Hz) + +########################################################### +# GENERATOR NETWORK ARCHITECTURE SETTING # +########################################################### +generator_params: + in_channels: 1 # Number of input channels. + out_channels: 1 # Number of output channels. + kernel_size: 3 # Kernel size of dilated convolution. + layers: 30 # Number of residual block layers. + stacks: 3 # Number of stacks i.e., dilation cycles. + residual_channels: 64 # Number of channels in residual conv. + gate_channels: 128 # Number of channels in gated conv. + skip_channels: 64 # Number of channels in skip conv. + aux_channels: 80 # Number of channels for auxiliary feature conv. + # Must be the same as num_mels. + aux_context_window: 2 # Context window size for auxiliary feature. + # If set to 2, previous 2 and future 2 frames will be considered. + dropout: 0.0 # Dropout rate. 0.0 means no dropout applied. + use_weight_norm: true # Whether to use weight norm. + # If set to true, it will be applied to all of the conv layers. + upsample_scales: [4, 4, 4, 4] # Upsampling scales. Prodcut of these must be the same as hop size. + +########################################################### +# DISCRIMINATOR NETWORK ARCHITECTURE SETTING # +########################################################### +discriminator_params: + in_channels: 1 # Number of input channels. + out_channels: 1 # Number of output channels. + kernel_size: 3 # Number of output channels. + layers: 10 # Number of conv layers. + conv_channels: 64 # Number of chnn layers. + bias: true # Whether to use bias parameter in conv. + use_weight_norm: true # Whether to use weight norm. + # If set to true, it will be applied to all of the conv layers. + nonlinear_activation: "LeakyReLU" # Nonlinear function after each conv. + nonlinear_activation_params: # Nonlinear function parameters + negative_slope: 0.2 # Alpha in LeakyReLU. + +########################################################### +# STFT LOSS SETTING # +########################################################### +stft_loss_params: + fft_sizes: [1024, 2048, 512] # List of FFT size for STFT-based loss. + hop_sizes: [120, 240, 50] # List of hop size for STFT-based loss + win_lengths: [600, 1200, 240] # List of window length for STFT-based loss. + window: "hann" # Window function for STFT-based loss + +########################################################### +# ADVERSARIAL LOSS SETTING # +########################################################### +lambda_adv: 4.0 # Loss balancing coefficient. + +########################################################### +# DATA LOADER SETTING # +########################################################### +batch_size: 8 # Batch size. +batch_max_steps: 25600 # Length of each audio in batch. Make sure dividable by hop_size. +pin_memory: true # Whether to pin memory in Pytorch DataLoader. +num_workers: 4 # Number of workers in Pytorch DataLoader. +remove_short_samples: true # Whether to remove samples the length of which are less than batch_max_steps. +allow_cache: true # Whether to allow cache in dataset. If true, it requires cpu memory. + +########################################################### +# OPTIMIZER & SCHEDULER SETTING # +########################################################### +generator_optimizer_params: + epsilon: 1.0e-6 # Generator's epsilon. + weight_decay: 0.0 # Generator's weight decay coefficient. +generator_scheduler_params: + learning_rate: 0.0001 # Generator's learning rate. + step_size: 200000 # Generator's scheduler step size. + gamma: 0.5 # Generator's scheduler gamma. + # At each step size, lr will be multiplied by this parameter. +generator_grad_norm: 10 # Generator's gradient norm. +discriminator_optimizer_params: + epsilon: 1.0e-6 # Discriminator's epsilon. + weight_decay: 0.0 # Discriminator's weight decay coefficient. +discriminator_scheduler_params: + learning_rate: 0.00005 # Discriminator's learning rate. + step_size: 200000 # Discriminator's scheduler step size. + gamma: 0.5 # Discriminator's scheduler gamma. + # At each step size, lr will be multiplied by this parameter. +discriminator_grad_norm: 1 # Discriminator's gradient norm. + +########################################################### +# INTERVAL SETTING # +########################################################### +discriminator_train_start_steps: 100000 # Number of steps to start to train discriminator. +train_max_steps: 400000 # Number of training steps. +save_interval_steps: 5000 # Interval steps to save checkpoint. +eval_interval_steps: 1000 # Interval steps to evaluate the network. + +########################################################### +# OTHER SETTING # +########################################################### +num_save_intermediate_results: 4 # Number of results to be saved as intermediate results. +num_snapshots: 10 # max number of snapshots to keep while training +seed: 42 # random seed for paddle, random, and np.random \ No newline at end of file diff --git a/examples/vctk/GANVocoder/parallelwave_gan/ljspeech/preprocess.sh b/examples/vctk/GANVocoder/parallelwave_gan/ljspeech/preprocess.sh new file mode 100755 index 00000000..d88d2989 --- /dev/null +++ b/examples/vctk/GANVocoder/parallelwave_gan/ljspeech/preprocess.sh @@ -0,0 +1,55 @@ +#!/bin/bash + +stage=0 +stop_stage=100 + +export MAIN_ROOT=`realpath ${PWD}/../../../../` + +if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then + # get durations from MFA's result + echo "Generate durations.txt from MFA results ..." + python3 ${MAIN_ROOT}/utils/gen_duration_from_textgrid.py \ + --inputdir=./ljspeech_alignment \ + --output=durations.txt \ + --config=conf/default.yaml +fi + +if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then + # extract features + echo "Extract features ..." + python3 ../../preprocess.py \ + --rootdir=~/datasets/LJSpeech-1.1/ \ + --dataset=ljspeech \ + --dumpdir=dump \ + --dur-file=durations.txt \ + --config=conf/default.yaml \ + --cut-sil=True \ + --num-cpu=20 +fi + +if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then + # get features' stats(mean and std) + echo "Get features' stats ..." + python3 ${MAIN_ROOT}/utils/compute_statistics.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --field-name="feats" +fi + +if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then + # normalize, dev and test should use train's stats + echo "Normalize ..." + + python3 ../../normalize.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --dumpdir=dump/train/norm \ + --stats=dump/train/feats_stats.npy + python3 ../../normalize.py \ + --metadata=dump/dev/raw/metadata.jsonl \ + --dumpdir=dump/dev/norm \ + --stats=dump/train/feats_stats.npy + + python3 ../../normalize.py \ + --metadata=dump/test/raw/metadata.jsonl \ + --dumpdir=dump/test/norm \ + --stats=dump/train/feats_stats.npy +fi diff --git a/examples/vctk/GANVocoder/parallelwave_gan/ljspeech/run.sh b/examples/vctk/GANVocoder/parallelwave_gan/ljspeech/run.sh new file mode 100755 index 00000000..df8cefd8 --- /dev/null +++ b/examples/vctk/GANVocoder/parallelwave_gan/ljspeech/run.sh @@ -0,0 +1,10 @@ +#!/bin/bash + +FLAGS_cudnn_exhaustive_search=true \ +FLAGS_conv_workspace_size_limit=4000 \ +python ../train.py \ + --train-metadata=dump/train/norm/metadata.jsonl \ + --dev-metadata=dump/dev/norm/metadata.jsonl \ + --config=conf/default.yaml \ + --output-dir=exp/default \ + --nprocs=1 diff --git a/examples/vctk/GANVocoder/parallelwave_gan/ljspeech/synthesize.sh b/examples/vctk/GANVocoder/parallelwave_gan/ljspeech/synthesize.sh new file mode 100755 index 00000000..e95b0da8 --- /dev/null +++ b/examples/vctk/GANVocoder/parallelwave_gan/ljspeech/synthesize.sh @@ -0,0 +1,8 @@ +#!/bin/bash +FLAGS_allocator_strategy=naive_best_fit \ +FLAGS_fraction_of_gpu_memory_to_use=0.01 \ +python3 ../synthesize.py \ + --config=conf/default.yaml \ + --checkpoint=exp/default/checkpoints/snapshot_iter_400000.pdz\ + --test-metadata=dump/test/norm/metadata.jsonl \ + --output-dir=exp/default/test diff --git a/examples/vctk/GANVocoder/parallelwave_gan/synthesize.py b/examples/vctk/GANVocoder/parallelwave_gan/synthesize.py new file mode 100644 index 00000000..e57ddf88 --- /dev/null +++ b/examples/vctk/GANVocoder/parallelwave_gan/synthesize.py @@ -0,0 +1,97 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +import os +from pathlib import Path +from timer import timer + +import jsonlines +import numpy as np +import paddle +import soundfile as sf +import yaml +from paddle import distributed as dist +from parakeet.datasets.data_table import DataTable +from parakeet.models.parallel_wavegan import PWGGenerator +from yacs.config import CfgNode + + +def main(): + parser = argparse.ArgumentParser( + description="Synthesize with parallel wavegan.") + parser.add_argument( + "--config", type=str, help="parallel wavegan config file.") + parser.add_argument("--checkpoint", type=str, help="snapshot to load.") + parser.add_argument("--test-metadata", type=str, help="dev data.") + parser.add_argument("--output-dir", type=str, help="output dir.") + parser.add_argument( + "--device", type=str, default="gpu", help="device to run.") + parser.add_argument("--verbose", type=int, default=1, help="verbose.") + + args = parser.parse_args() + + with open(args.config) as f: + config = CfgNode(yaml.safe_load(f)) + + print("========Args========") + print(yaml.safe_dump(vars(args))) + print("========Config========") + print(config) + print( + f"master see the word size: {dist.get_world_size()}, from pid: {os.getpid()}" + ) + + paddle.set_device(args.device) + generator = PWGGenerator(**config["generator_params"]) + state_dict = paddle.load(args.checkpoint) + generator.set_state_dict(state_dict["generator_params"]) + + generator.remove_weight_norm() + generator.eval() + with jsonlines.open(args.test_metadata, 'r') as reader: + metadata = list(reader) + + test_dataset = DataTable( + metadata, + fields=['utt_id', 'feats'], + converters={ + 'utt_id': None, + 'feats': np.load, + }) + output_dir = Path(args.output_dir) + output_dir.mkdir(parents=True, exist_ok=True) + + N = 0 + T = 0 + for example in test_dataset: + utt_id = example['utt_id'] + mel = example['feats'] + mel = paddle.to_tensor(mel) # (T, C) + with timer() as t: + with paddle.no_grad(): + wav = generator.inference(c=mel) + wav = wav.numpy() + N += wav.size + T += t.elapse + speed = wav.size / t.elapse + print( + f"{utt_id}, mel: {mel.shape}, wave: {wav.shape}, time: {t.elapse}s, Hz: {speed}, RTF: {config.fs / speed}." + ) + sf.write(str(output_dir / (utt_id + ".wav")), wav, samplerate=config.fs) + print(f"generation speed: {N / T}Hz, RTF: {config.fs / (N / T) }") + + +if __name__ == "__main__": + main() diff --git a/examples/vctk/GANVocoder/parallelwave_gan/train.py b/examples/vctk/GANVocoder/parallelwave_gan/train.py new file mode 100644 index 00000000..7e6aa9a6 --- /dev/null +++ b/examples/vctk/GANVocoder/parallelwave_gan/train.py @@ -0,0 +1,273 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +import logging +import os +import shutil + +import jsonlines +import numpy as np +import paddle +import yaml +from paddle import DataParallel +from paddle import distributed as dist +from paddle import nn +from paddle.io import DataLoader +from paddle.io import DistributedBatchSampler +from paddle.optimizer import Adam # No RAdaom +from paddle.optimizer.lr import StepDecay +from parakeet.datasets.data_table import DataTable +from parakeet.datasets.vocoder_batch_fn import Clip +from parakeet.models.parallel_wavegan import PWGGenerator +from parakeet.models.parallel_wavegan import PWGDiscriminator +from parakeet.models.parallel_wavegan import PWGUpdater +from parakeet.models.parallel_wavegan import PWGEvaluator +from parakeet.modules.stft_loss import MultiResolutionSTFTLoss +from parakeet.training.extensions.snapshot import Snapshot +from parakeet.training.extensions.visualizer import VisualDL +from parakeet.training.seeding import seed_everything +from parakeet.training.trainer import Trainer +from pathlib import Path +from visualdl import LogWriter +from yacs.config import CfgNode + + +def train_sp(args, config): + # decides device type and whether to run in parallel + # setup running environment correctly + world_size = paddle.distributed.get_world_size() + if not paddle.is_compiled_with_cuda(): + paddle.set_device("cpu") + else: + paddle.set_device("gpu") + if world_size > 1: + paddle.distributed.init_parallel_env() + + # set the random seed, it is a must for multiprocess training + seed_everything(config.seed) + + print( + f"rank: {dist.get_rank()}, pid: {os.getpid()}, parent_pid: {os.getppid()}", + ) + + # dataloader has been too verbose + logging.getLogger("DataLoader").disabled = True + + # construct dataset for training and validation + with jsonlines.open(args.train_metadata, 'r') as reader: + train_metadata = list(reader) + train_dataset = DataTable( + data=train_metadata, + fields=["wave", "feats"], + converters={ + "wave": np.load, + "feats": np.load, + }, ) + with jsonlines.open(args.dev_metadata, 'r') as reader: + dev_metadata = list(reader) + dev_dataset = DataTable( + data=dev_metadata, + fields=["wave", "feats"], + converters={ + "wave": np.load, + "feats": np.load, + }, ) + + # collate function and dataloader + train_sampler = DistributedBatchSampler( + train_dataset, + batch_size=config.batch_size, + shuffle=True, + drop_last=True) + dev_sampler = DistributedBatchSampler( + dev_dataset, + batch_size=config.batch_size, + shuffle=False, + drop_last=False) + print("samplers done!") + + train_batch_fn = Clip( + batch_max_steps=config.batch_max_steps, + hop_size=config.n_shift, + aux_context_window=config.generator_params.aux_context_window) + + train_dataloader = DataLoader( + train_dataset, + batch_sampler=train_sampler, + collate_fn=train_batch_fn, + num_workers=config.num_workers) + + dev_dataloader = DataLoader( + dev_dataset, + batch_sampler=dev_sampler, + collate_fn=train_batch_fn, + num_workers=config.num_workers) + print("dataloaders done!") + + generator = PWGGenerator(**config["generator_params"]) + discriminator = PWGDiscriminator(**config["discriminator_params"]) + if world_size > 1: + generator = DataParallel(generator) + discriminator = DataParallel(discriminator) + print("models done!") + + criterion_stft = MultiResolutionSTFTLoss(**config["stft_loss_params"]) + criterion_mse = nn.MSELoss() + print("criterions done!") + + lr_schedule_g = StepDecay(**config["generator_scheduler_params"]) + gradient_clip_g = nn.ClipGradByGlobalNorm(config["generator_grad_norm"]) + optimizer_g = Adam( + learning_rate=lr_schedule_g, + grad_clip=gradient_clip_g, + parameters=generator.parameters(), + **config["generator_optimizer_params"]) + lr_schedule_d = StepDecay(**config["discriminator_scheduler_params"]) + gradient_clip_d = nn.ClipGradByGlobalNorm(config["discriminator_grad_norm"]) + optimizer_d = Adam( + learning_rate=lr_schedule_d, + grad_clip=gradient_clip_d, + parameters=discriminator.parameters(), + **config["discriminator_optimizer_params"]) + print("optimizers done!") + + output_dir = Path(args.output_dir) + output_dir.mkdir(parents=True, exist_ok=True) + if dist.get_rank() == 0: + config_name = args.config.split("/")[-1] + # copy conf to output_dir + shutil.copyfile(args.config, output_dir / config_name) + + updater = PWGUpdater( + models={ + "generator": generator, + "discriminator": discriminator, + }, + optimizers={ + "generator": optimizer_g, + "discriminator": optimizer_d, + }, + criterions={ + "stft": criterion_stft, + "mse": criterion_mse, + }, + schedulers={ + "generator": lr_schedule_g, + "discriminator": lr_schedule_d, + }, + dataloader=train_dataloader, + discriminator_train_start_steps=config.discriminator_train_start_steps, + lambda_adv=config.lambda_adv, + output_dir=output_dir) + + evaluator = PWGEvaluator( + models={ + "generator": generator, + "discriminator": discriminator, + }, + criterions={ + "stft": criterion_stft, + "mse": criterion_mse, + }, + dataloader=dev_dataloader, + lambda_adv=config.lambda_adv, + output_dir=output_dir) + trainer = Trainer( + updater, + stop_trigger=(config.train_max_steps, "iteration"), + out=output_dir, + profiler_options=args.profiler_options) + + if dist.get_rank() == 0: + trainer.extend( + evaluator, trigger=(config.eval_interval_steps, 'iteration')) + writer = LogWriter(str(trainer.out)) + trainer.extend(VisualDL(writer), trigger=(1, 'iteration')) + trainer.extend( + Snapshot(max_size=config.num_snapshots), + trigger=(config.save_interval_steps, 'iteration')) + + # print(trainer.extensions.keys()) + print("Trainer Done!") + trainer.run() + + +def main(): + # parse args and config and redirect to train_sp + def str2bool(str): + return True if str.lower() == 'true' else False + + parser = argparse.ArgumentParser( + description="Train a ParallelWaveGAN model.") + parser.add_argument( + "--config", type=str, help="config file to overwrite default config.") + parser.add_argument("--train-metadata", type=str, help="training data.") + parser.add_argument("--dev-metadata", type=str, help="dev data.") + parser.add_argument("--output-dir", type=str, help="output dir.") + parser.add_argument( + "--device", type=str, default="gpu", help="device type to use.") + parser.add_argument( + "--nprocs", type=int, default=1, help="number of processes.") + parser.add_argument("--verbose", type=int, default=1, help="verbose.") + + benchmark_group = parser.add_argument_group( + 'benchmark', 'arguments related to benchmark.') + benchmark_group.add_argument( + "--batch-size", type=int, default=8, help="batch size.") + benchmark_group.add_argument( + "--max-iter", type=int, default=400000, help="train max steps.") + + benchmark_group.add_argument( + "--run-benchmark", + type=str2bool, + default=False, + help="runing benchmark or not, if True, use the --batch-size and --max-iter." + ) + benchmark_group.add_argument( + "--profiler_options", + type=str, + default=None, + help="The option of profiler, which should be in format \"key1=value1;key2=value2;key3=value3\"." + ) + + args = parser.parse_args() + if args.device == "cpu" and args.nprocs > 1: + raise RuntimeError("Multiprocess training on CPU is not supported.") + + with open(args.config, 'rt') as f: + config = CfgNode(yaml.safe_load(f)) + + # 增加 --batch_size --max_iter 用于 benchmark 调用 + if args.run_benchmark: + config.batch_size = args.batch_size + config.train_max_steps = args.max_iter + + print("========Args========") + print(yaml.safe_dump(vars(args))) + print("========Config========") + print(config) + print( + f"master see the word size: {dist.get_world_size()}, from pid: {os.getpid()}" + ) + + # dispatch + if args.nprocs > 1: + dist.spawn(train_sp, (args, config), nprocs=args.nprocs) + else: + train_sp(args, config) + + +if __name__ == "__main__": + main() diff --git a/examples/vctk/GANVocoder/parallelwave_gan/vctk/README.md b/examples/vctk/GANVocoder/parallelwave_gan/vctk/README.md new file mode 100644 index 00000000..29538dc4 --- /dev/null +++ b/examples/vctk/GANVocoder/parallelwave_gan/vctk/README.md @@ -0,0 +1,128 @@ +# Parallel WaveGAN with VCTK +This example contains code used to train a [parallel wavegan](http://arxiv.org/abs/1910.11480) model with [VCTK](https://datashare.ed.ac.uk/handle/10283/3443). +## Preprocess the dataset +### Download and Extract the datasaet +Download VCTK-0.92 from the [official website](https://datashare.ed.ac.uk/handle/10283/3443) and extract it to `~/datasets`. Then the dataset is in directory `~/datasets/VCTK-Corpus-0.92`. + +### Get MFA results for silence trim +We use [MFA](https://github.com/MontrealCorpusTools/Montreal-Forced-Aligner) results to cut silence in the edge of audio. +You can download from here [vctk_alignment.tar.gz](https://paddlespeech.bj.bcebos.com/MFA/VCTK-Corpus-0.92/vctk_alignment.tar.gz), or train your own MFA model reference to [use_mfa example](https://github.com/PaddlePaddle/Parakeet/tree/develop/examples/use_mfa) of our repo. +ps: we remove three speakers in VCTK-0.92 (see [reorganize_vctk.py](https://github.com/PaddlePaddle/Parakeet/tree/develop/examples/use_mfa/local/reorganize_vctk.py)): +1. `p315`, because no txt for it. +2. `p280` and `p362`, because no *_mic2.flac (which is better than *_mic1.flac) for them. + +### Preprocess the dataset +Assume the path to the dataset is `~/datasets/VCTK-Corpus-0.92`. +Assume the path to the MFA result of VCTK is `./vctk_alignment`. +Run the command below to preprocess the dataset. +```bash +./preprocess.sh +``` +When it is done. A `dump` folder is created in the current directory. The structure of the dump folder is listed below. + +```text +dump +├── dev +│ ├── norm +│ └── raw +├── test +│ ├── norm +│ └── raw +└── train + ├── norm + ├── raw + └── feats_stats.npy +``` + +The dataset is split into 3 parts, namely `train`, `dev` and `test`, each of which contains a `norm` and `raw` subfolder. The `raw` folder contains log magnitude of mel spectrogram of each utterances, while the norm folder contains normalized spectrogram. The statistics used to normalize the spectrogram is computed from the training set, which is located in `dump/train/feats_stats.npy`. + +Also there is a `metadata.jsonl` in each subfolder. It is a table-like file which contains id and paths to spectrogam of each utterance. + +## Train the model + +`./run.sh` calls `../train.py`. +```bash +./run.sh +``` +Here's the complete help message. + +```text +usage: train.py [-h] [--config CONFIG] [--train-metadata TRAIN_METADATA] + [--dev-metadata DEV_METADATA] [--output-dir OUTPUT_DIR] + [--device DEVICE] [--nprocs NPROCS] [--verbose VERBOSE] + [--batch-size BATCH_SIZE] [--max-iter MAX_ITER] + [--run-benchmark RUN_BENCHMARK] + [--profiler_options PROFILER_OPTIONS] + +Train a ParallelWaveGAN model. + +optional arguments: + -h, --help show this help message and exit + --config CONFIG config file to overwrite default config. + --train-metadata TRAIN_METADATA + training data. + --dev-metadata DEV_METADATA + dev data. + --output-dir OUTPUT_DIR + output dir. + --device DEVICE device type to use. + --nprocs NPROCS number of processes. + --verbose VERBOSE verbose. + +benchmark: + arguments related to benchmark. + + --batch-size BATCH_SIZE + batch size. + --max-iter MAX_ITER train max steps. + --run-benchmark RUN_BENCHMARK + runing benchmark or not, if True, use the --batch-size + and --max-iter. + --profiler_options PROFILER_OPTIONS + The option of profiler, which should be in format + "key1=value1;key2=value2;key3=value3". +``` + +1. `--config` is a config file in yaml format to overwrite the default config, which can be found at `conf/default.yaml`. +2. `--train-metadata` and `--dev-metadata` should be the metadata file in the normalized subfolder of `train` and `dev` in the `dump` folder. +3. `--output-dir` is the directory to save the results of the experiment. Checkpoints are save in `checkpoints/` inside this directory. +4. `--device` is the type of the device to run the experiment, 'cpu' or 'gpu' are supported. +5. `--nprocs` is the number of processes to run in parallel, note that nprocs > 1 is only supported when `--device` is 'gpu'. + +## Pretrained Models + + +## Synthesize + +`synthesize.sh` calls `../synthesize.py `, which can synthesize waveform from `metadata.jsonl`. +```bash +./synthesize.sh +``` +```text +usage: synthesize.py [-h] [--config CONFIG] [--checkpoint CHECKPOINT] + [--test-metadata TEST_METADATA] [--output-dir OUTPUT_DIR] + [--device DEVICE] [--verbose VERBOSE] + +Synthesize with parallel wavegan. + +optional arguments: + -h, --help show this help message and exit + --config CONFIG parallel wavegan config file. + --checkpoint CHECKPOINT + snapshot to load. + --test-metadata TEST_METADATA + dev data. + --output-dir OUTPUT_DIR + output dir. + --device DEVICE device to run. + --verbose VERBOSE verbose. +``` + +1. `--config` parallel wavegan config file. You should use the same config with which the model is trained. +2. `--checkpoint` is the checkpoint to load. Pick one of the checkpoints from `checkpoints` inside the training output directory. If you use the pretrained model, use the `pwg_snapshot_iter_400000.pdz`. +3. `--test-metadata` is the metadata of the test dataset. Use the `metadata.jsonl` in the `dev/norm` subfolder from the processed directory. +4. `--output-dir` is the directory to save the synthesized audio files. +5. `--device` is the type of device to run synthesis, 'cpu' and 'gpu' are supported. + +## Acknowledgement +We adapted some code from https://github.com/kan-bayashi/ParallelWaveGAN. diff --git a/examples/vctk/GANVocoder/parallelwave_gan/vctk/conf/default.yaml b/examples/vctk/GANVocoder/parallelwave_gan/vctk/conf/default.yaml new file mode 100644 index 00000000..ba2d9f2e --- /dev/null +++ b/examples/vctk/GANVocoder/parallelwave_gan/vctk/conf/default.yaml @@ -0,0 +1,115 @@ +# This is the hyperparameter configuration file for Parallel WaveGAN. +# Please make sure this is adjusted for the VCTK corpus. If you want to +# apply to the other dataset, you might need to carefully change some parameters. +# This configuration requires 12 GB GPU memory and takes ~3 days on RTX TITAN. + +########################################################### +# FEATURE EXTRACTION SETTING # +########################################################### +fs: 24000 # Sampling rate. +n_fft: 2048 # FFT size. (in samples) +n_shift: 300 # Hop size. (in samples) +win_length: 1200 # Window length. (in samples) + # If set to null, it will be the same as fft_size. +window: "hann" # Window function. +n_mels: 80 # Number of mel basis. +fmin: 80 # Minimum freq in mel basis calculation. (Hz) +fmax: 7600 # Maximum frequency in mel basis calculation. (Hz) + +########################################################### +# GENERATOR NETWORK ARCHITECTURE SETTING # +########################################################### +generator_params: + in_channels: 1 # Number of input channels. + out_channels: 1 # Number of output channels. + kernel_size: 3 # Kernel size of dilated convolution. + layers: 30 # Number of residual block layers. + stacks: 3 # Number of stacks i.e., dilation cycles. + residual_channels: 64 # Number of channels in residual conv. + gate_channels: 128 # Number of channels in gated conv. + skip_channels: 64 # Number of channels in skip conv. + aux_channels: 80 # Number of channels for auxiliary feature conv. + # Must be the same as num_mels. + aux_context_window: 2 # Context window size for auxiliary feature. + # If set to 2, previous 2 and future 2 frames will be considered. + dropout: 0.0 # Dropout rate. 0.0 means no dropout applied. + use_weight_norm: true # Whether to use weight norm. + # If set to true, it will be applied to all of the conv layers. + upsample_scales: [4, 5, 3, 5] # Upsampling scales. Prodcut of these must be the same as hop size. + +########################################################### +# DISCRIMINATOR NETWORK ARCHITECTURE SETTING # +########################################################### +discriminator_params: + in_channels: 1 # Number of input channels. + out_channels: 1 # Number of output channels. + kernel_size: 3 # Number of output channels. + layers: 10 # Number of conv layers. + conv_channels: 64 # Number of chnn layers. + bias: true # Whether to use bias parameter in conv. + use_weight_norm: true # Whether to use weight norm. + # If set to true, it will be applied to all of the conv layers. + nonlinear_activation: "LeakyReLU" # Nonlinear function after each conv. + nonlinear_activation_params: # Nonlinear function parameters + negative_slope: 0.2 # Alpha in LeakyReLU. + +########################################################### +# STFT LOSS SETTING # +########################################################### +stft_loss_params: + fft_sizes: [1024, 2048, 512] # List of FFT size for STFT-based loss. + hop_sizes: [120, 240, 50] # List of hop size for STFT-based loss + win_lengths: [600, 1200, 240] # List of window length for STFT-based loss. + window: "hann" # Window function for STFT-based loss + +########################################################### +# ADVERSARIAL LOSS SETTING # +########################################################### +lambda_adv: 4.0 # Loss balancing coefficient. + +########################################################### +# DATA LOADER SETTING # +########################################################### +batch_size: 8 # Batch size. +batch_max_steps: 24000 # Length of each audio in batch. Make sure dividable by hop_size. +pin_memory: true # Whether to pin memory in Pytorch DataLoader. +num_workers: 4 # Number of workers in Pytorch DataLoader. +remove_short_samples: true # Whether to remove samples the length of which are less than batch_max_steps. +allow_cache: true # Whether to allow cache in dataset. If true, it requires cpu memory. + +########################################################### +# OPTIMIZER & SCHEDULER SETTING # +########################################################### +generator_optimizer_params: + epsilon: 1.0e-6 # Generator's epsilon. + weight_decay: 0.0 # Generator's weight decay coefficient. +generator_scheduler_params: + learning_rate: 0.0001 # Generator's learning rate. + step_size: 200000 # Generator's scheduler step size. + gamma: 0.5 # Generator's scheduler gamma. + # At each step size, lr will be multiplied by this parameter. +generator_grad_norm: 10 # Generator's gradient norm. +discriminator_optimizer_params: + epsilon: 1.0e-6 # Discriminator's epsilon. + weight_decay: 0.0 # Discriminator's weight decay coefficient. +discriminator_scheduler_params: + learning_rate: 0.00005 # Discriminator's learning rate. + step_size: 200000 # Discriminator's scheduler step size. + gamma: 0.5 # Discriminator's scheduler gamma. + # At each step size, lr will be multiplied by this parameter. +discriminator_grad_norm: 1 # Discriminator's gradient norm. + +########################################################### +# INTERVAL SETTING # +########################################################### +discriminator_train_start_steps: 100000 # Number of steps to start to train discriminator. +train_max_steps: 1000000 # Number of training steps. +save_interval_steps: 5000 # Interval steps to save checkpoint. +eval_interval_steps: 1000 # Interval steps to evaluate the network. + +########################################################### +# OTHER SETTING # +########################################################### +num_save_intermediate_results: 4 # Number of results to be saved as intermediate results. +num_snapshots: 10 # max number of snapshots to keep while training +seed: 42 # random seed for paddle, random, and np.random diff --git a/examples/vctk/GANVocoder/parallelwave_gan/vctk/preprocess.sh b/examples/vctk/GANVocoder/parallelwave_gan/vctk/preprocess.sh new file mode 100755 index 00000000..3ed4c0cc --- /dev/null +++ b/examples/vctk/GANVocoder/parallelwave_gan/vctk/preprocess.sh @@ -0,0 +1,54 @@ +#!/bin/bash + +stage=0 +stop_stage=100 + +export MAIN_ROOT=`realpath ${PWD}/../../../../` + +if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then + # get durations from MFA's result + echo "Generate durations.txt from MFA results ..." + python3 ${MAIN_ROOT}/utils/gen_duration_from_textgrid.py \ + --inputdir=./vctk_alignment \ + --output=durations.txt \ + --config=conf/default.yaml +fi + +if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then + echo "Extract features ..." + python3 ../../preprocess.py \ + --rootdir=~/datasets/VCTK-Corpus-0.92/ \ + --dataset=vctk \ + --dumpdir=dump \ + --dur-file=durations.txt \ + --config=conf/default.yaml \ + --cut-sil=True \ + --num-cpu=20 +fi + +if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then + # get features' stats(mean and std) + echo "Get features' stats ..." + python3 ${MAIN_ROOT}/utils/compute_statistics.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --field-name="feats" +fi + +if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then + # normalize, dev and test should use train's stats + echo "Normalize ..." + + python3 ../../normalize.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --dumpdir=dump/train/norm \ + --stats=dump/train/feats_stats.npy + python3 ../../normalize.py \ + --metadata=dump/dev/raw/metadata.jsonl \ + --dumpdir=dump/dev/norm \ + --stats=dump/train/feats_stats.npy + + python3 ../../normalize.py \ + --metadata=dump/test/raw/metadata.jsonl \ + --dumpdir=dump/test/norm \ + --stats=dump/train/feats_stats.npy +fi diff --git a/examples/vctk/GANVocoder/parallelwave_gan/vctk/run.sh b/examples/vctk/GANVocoder/parallelwave_gan/vctk/run.sh new file mode 100755 index 00000000..df8cefd8 --- /dev/null +++ b/examples/vctk/GANVocoder/parallelwave_gan/vctk/run.sh @@ -0,0 +1,10 @@ +#!/bin/bash + +FLAGS_cudnn_exhaustive_search=true \ +FLAGS_conv_workspace_size_limit=4000 \ +python ../train.py \ + --train-metadata=dump/train/norm/metadata.jsonl \ + --dev-metadata=dump/dev/norm/metadata.jsonl \ + --config=conf/default.yaml \ + --output-dir=exp/default \ + --nprocs=1 diff --git a/examples/vctk/GANVocoder/parallelwave_gan/vctk/synthesize.sh b/examples/vctk/GANVocoder/parallelwave_gan/vctk/synthesize.sh new file mode 100755 index 00000000..42213058 --- /dev/null +++ b/examples/vctk/GANVocoder/parallelwave_gan/vctk/synthesize.sh @@ -0,0 +1,7 @@ +#!/bin/bash + +python3 ../synthesize.py \ + --config=conf/default.yaml \ + --checkpoint=exp/default/checkpoints/snapshot_iter_35000.pdz_bak\ + --test-metadata=dump/test/norm/metadata.jsonl \ + --output-dir=exp/default/test diff --git a/examples/vctk/GANVocoder/preprocess.py b/examples/vctk/GANVocoder/preprocess.py new file mode 100644 index 00000000..e9f18286 --- /dev/null +++ b/examples/vctk/GANVocoder/preprocess.py @@ -0,0 +1,280 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +import os +from operator import itemgetter +from typing import Any +from typing import Dict +from typing import List + +import jsonlines +import librosa +import numpy as np +import tqdm +import yaml +from concurrent.futures import ThreadPoolExecutor +from parakeet.data.get_feats import LogMelFBank +from parakeet.datasets.preprocess_utils import get_phn_dur +from parakeet.datasets.preprocess_utils import merge_silence +from pathlib import Path +from yacs.config import CfgNode + + +def process_sentence(config: Dict[str, Any], + fp: Path, + sentences: Dict, + output_dir: Path, + mel_extractor=None, + cut_sil: bool=True): + utt_id = fp.stem + # for vctk + if utt_id.endswith("_mic2"): + utt_id = utt_id[:-5] + record = None + if utt_id in sentences: + # reading, resampling may occur + y, _ = librosa.load(str(fp), sr=config.fs) + if len(y.shape) != 1 or np.abs(y).max() > 1.0: + return record + assert len(y.shape) == 1, f"{utt_id} is not a mono-channel audio." + assert np.abs(y).max( + ) <= 1.0, f"{utt_id} is seems to be different that 16 bit PCM." + phones = sentences[utt_id][0] + durations = sentences[utt_id][1] + speaker = sentences[utt_id][2] + d_cumsum = np.pad(np.array(durations).cumsum(0), (1, 0), 'constant') + # little imprecise than use *.TextGrid directly + times = librosa.frames_to_time( + d_cumsum, sr=config.fs, hop_length=config.n_shift) + if cut_sil: + start = 0 + end = d_cumsum[-1] + if phones[0] == "sil" and len(durations) > 1: + start = times[1] + durations = durations[1:] + phones = phones[1:] + if phones[-1] == 'sil' and len(durations) > 1: + end = times[-2] + durations = durations[:-1] + phones = phones[:-1] + sentences[utt_id][0] = phones + sentences[utt_id][1] = durations + start, end = librosa.time_to_samples([start, end], sr=config.fs) + y = y[start:end] + + # extract mel feats + logmel = mel_extractor.get_log_mel_fbank(y) + + # adjust time to make num_samples == num_frames * hop_length + num_frames = logmel.shape[0] + if y.size < num_frames * config.n_shift: + y = np.pad( + y, (0, num_frames * config.n_shift - y.size), mode="reflect") + else: + y = y[:num_frames * config.n_shift] + num_sample = y.shape[0] + + mel_path = output_dir / (utt_id + "_feats.npy") + wav_path = output_dir / (utt_id + "_wave.npy") + np.save(wav_path, y) # (num_samples, ) + np.save(mel_path, logmel) # (num_frames, n_mels) + record = { + "utt_id": utt_id, + "num_samples": num_sample, + "num_frames": num_frames, + "feats": str(mel_path), + "wave": str(wav_path), + } + return record + + +def process_sentences(config, + fps: List[Path], + sentences: Dict, + output_dir: Path, + mel_extractor=None, + nprocs: int=1, + cut_sil: bool=True): + if nprocs == 1: + results = [] + for fp in tqdm.tqdm(fps, total=len(fps)): + record = process_sentence(config, fp, sentences, output_dir, + mel_extractor, cut_sil) + if record: + results.append(record) + else: + with ThreadPoolExecutor(nprocs) as pool: + futures = [] + with tqdm.tqdm(total=len(fps)) as progress: + for fp in fps: + future = pool.submit(process_sentence, config, fp, + sentences, output_dir, mel_extractor, + cut_sil) + future.add_done_callback(lambda p: progress.update()) + futures.append(future) + + results = [] + for ft in futures: + record = ft.result() + if record: + results.append(record) + + results.sort(key=itemgetter("utt_id")) + with jsonlines.open(output_dir / "metadata.jsonl", 'w') as writer: + for item in results: + writer.write(item) + print("Done") + + +def main(): + # parse config and args + parser = argparse.ArgumentParser( + description="Preprocess audio and then extract features .") + parser.add_argument( + "--dataset", + default="baker", + type=str, + help="name of dataset, should in {baker, ljspeech, vctk} now") + parser.add_argument( + "--rootdir", default=None, type=str, help="directory to dataset.") + parser.add_argument( + "--dumpdir", + type=str, + required=True, + help="directory to dump feature files.") + parser.add_argument("--config", type=str, help="vocoder config file.") + parser.add_argument( + "--verbose", + type=int, + default=1, + help="logging level. higher is more logging. (default=1)") + parser.add_argument( + "--num-cpu", type=int, default=1, help="number of process.") + parser.add_argument( + "--dur-file", default=None, type=str, help="path to durations.txt.") + + def str2bool(str): + return True if str.lower() == 'true' else False + + parser.add_argument( + "--cut-sil", + type=str2bool, + default=True, + help="whether cut sil in the edge of audio") + args = parser.parse_args() + + rootdir = Path(args.rootdir).expanduser() + dumpdir = Path(args.dumpdir).expanduser() + # use absolute path + dumpdir = dumpdir.resolve() + dumpdir.mkdir(parents=True, exist_ok=True) + dur_file = Path(args.dur_file).expanduser() + + assert rootdir.is_dir() + assert dur_file.is_file() + + with open(args.config, 'rt') as f: + config = CfgNode(yaml.safe_load(f)) + + if args.verbose > 1: + print(vars(args)) + print(config) + + sentences, speaker_set = get_phn_dur(dur_file) + merge_silence(sentences) + + # split data into 3 sections + if args.dataset == "baker": + wav_files = sorted(list((rootdir / "Wave").rglob("*.wav"))) + num_train = 9800 + num_dev = 100 + train_wav_files = wav_files[:num_train] + dev_wav_files = wav_files[num_train:num_train + num_dev] + test_wav_files = wav_files[num_train + num_dev:] + + elif args.dataset == "ljspeech": + wav_files = sorted(list((rootdir / "wavs").rglob("*.wav"))) + # split data into 3 sections + num_train = 12900 + num_dev = 100 + train_wav_files = wav_files[:num_train] + dev_wav_files = wav_files[num_train:num_train + num_dev] + test_wav_files = wav_files[num_train + num_dev:] + elif args.dataset == "vctk": + sub_num_dev = 5 + wav_dir = rootdir / "wav48_silence_trimmed" + train_wav_files = [] + dev_wav_files = [] + test_wav_files = [] + for speaker in os.listdir(wav_dir): + wav_files = sorted(list((wav_dir / speaker).rglob("*_mic2.flac"))) + if len(wav_files) > 100: + train_wav_files += wav_files[:-sub_num_dev * 2] + dev_wav_files += wav_files[-sub_num_dev * 2:-sub_num_dev] + test_wav_files += wav_files[-sub_num_dev:] + else: + train_wav_files += wav_files + else: + print("dataset should in {baker, ljspeech, vctk} now!") + + train_dump_dir = dumpdir / "train" / "raw" + train_dump_dir.mkdir(parents=True, exist_ok=True) + dev_dump_dir = dumpdir / "dev" / "raw" + dev_dump_dir.mkdir(parents=True, exist_ok=True) + test_dump_dir = dumpdir / "test" / "raw" + test_dump_dir.mkdir(parents=True, exist_ok=True) + + mel_extractor = LogMelFBank( + sr=config.fs, + n_fft=config.n_fft, + hop_length=config.n_shift, + win_length=config.win_length, + window=config.window, + n_mels=config.n_mels, + fmin=config.fmin, + fmax=config.fmax) + + # process for the 3 sections + if train_wav_files: + process_sentences( + config, + train_wav_files, + sentences, + train_dump_dir, + mel_extractor=mel_extractor, + nprocs=args.num_cpu, + cut_sil=args.cut_sil) + if dev_wav_files: + process_sentences( + config, + dev_wav_files, + sentences, + dev_dump_dir, + mel_extractor=mel_extractor, + nprocs=args.num_cpu, + cut_sil=args.cut_sil) + if test_wav_files: + process_sentences( + config, + test_wav_files, + sentences, + test_dump_dir, + mel_extractor=mel_extractor, + nprocs=args.num_cpu, + cut_sil=args.cut_sil) + + +if __name__ == "__main__": + main() diff --git a/examples/vctk/fastspeech2/aishell3/README.md b/examples/vctk/fastspeech2/aishell3/README.md new file mode 100644 index 00000000..c5624285 --- /dev/null +++ b/examples/vctk/fastspeech2/aishell3/README.md @@ -0,0 +1,227 @@ +# FastSpeech2 with AISHELL-3 +This example contains code used to train a [Fastspeech2](https://arxiv.org/abs/2006.04558) model with [AISHELL-3](http://www.aishelltech.com/aishell_3). + +AISHELL-3 is a large-scale and high-fidelity multi-speaker Mandarin speech corpus which could be used to train multi-speaker Text-to-Speech (TTS) systems. + +We use AISHELL-3 to train a multi-speaker fastspeech2 model here. +## Dataset +### Download and Extract the datasaet +Download AISHELL-3. +```bash +wget https://www.openslr.org/resources/93/data_aishell3.tgz +``` +Extract AISHELL-3. +```bash +mkdir data_aishell3 +tar zxvf data_aishell3.tgz -C data_aishell3 +``` +### Get MFA result of AISHELL-3 and Extract it +We use [MFA2.x](https://github.com/MontrealCorpusTools/Montreal-Forced-Aligner) to get durations for aishell3_fastspeech2. +You can download from here [aishell3_alignment_tone.tar.gz](https://paddlespeech.bj.bcebos.com/MFA/AISHELL-3/with_tone/aishell3_alignment_tone.tar.gz), or train your own MFA model reference to [use_mfa example](https://github.com/PaddlePaddle/Parakeet/tree/develop/examples/use_mfa) (use MFA1.x now) of our repo. +### Preprocess the dataset +Assume the path to the dataset is `~/datasets/data_aishell3`. +Assume the path to the MFA result of AISHELL-3 is `./aishell3_alignment_tone`. +Run the command below to preprocess the dataset. +```bash +./preprocess.sh +``` +When it is done. A `dump` folder is created in the current directory. The structure of the dump folder is listed below. +```text +dump +├── dev +│ ├── norm +│ └── raw +├── phone_id_map.txt +├── speaker_id_map.txt +├── test +│ ├── norm +│ └── raw +└── train + ├── energy_stats.npy + ├── norm + ├── pitch_stats.npy + ├── raw + └── speech_stats.npy +``` +The dataset is split into 3 parts, namely `train`, `dev` and` test`, each of which contains a `norm` and `raw` sub folder. The raw folder contains speech、pitch and energy features of each utterances, while the norm folder contains normalized ones. The statistics used to normalize features are computed from the training set, which is located in `dump/train/*_stats.npy`. + +Also there is a `metadata.jsonl` in each subfolder. It is a table-like file which contains phones, text_lengths, speech_lengths, durations, path of speech features, path of pitch features, path of energy features, speaker and id of each utterance. + +## Train the model +`./run.sh` calls `../train.py`. +```bash +./run.sh +``` +Here's the complete help message. +```text +usage: train.py [-h] [--config CONFIG] [--train-metadata TRAIN_METADATA] + [--dev-metadata DEV_METADATA] [--output-dir OUTPUT_DIR] + [--device DEVICE] [--nprocs NPROCS] [--verbose VERBOSE] + [--phones-dict PHONES_DICT] [--speaker-dict SPEAKER_DICT] + +Train a FastSpeech2 model. + +optional arguments: + -h, --help show this help message and exit + --config CONFIG fastspeech2 config file. + --train-metadata TRAIN_METADATA + training data. + --dev-metadata DEV_METADATA + dev data. + --output-dir OUTPUT_DIR + output dir. + --device DEVICE device type to use. + --nprocs NPROCS number of processes. + --verbose VERBOSE verbose. + --phones-dict PHONES_DICT + phone vocabulary file. + --speaker-dict SPEAKER_DICT + speaker id map file for multiple speaker model. +``` +1. `--config` is a config file in yaml format to overwrite the default config, which can be found at `conf/default.yaml`. +2. `--train-metadata` and `--dev-metadata` should be the metadata file in the normalized subfolder of `train` and `dev` in the `dump` folder. +3. `--output-dir` is the directory to save the results of the experiment. Checkpoints are save in `checkpoints/` inside this directory. +4. `--device` is the type of the device to run the experiment, 'cpu' or 'gpu' are supported. +5. `--nprocs` is the number of processes to run in parallel, note that nprocs > 1 is only supported when `--device` is 'gpu'. +6. `--phones-dict` is the path of the phone vocabulary file. +7. `--speaker-dict`is the path of the speaker id map file when training a multi-speaker FastSpeech2. +## Pretrained Model +Pretrained FastSpeech2 model with no silence in the edge of audios. [fastspeech2_nosil_aishell3_ckpt_0.4.zip](https://paddlespeech.bj.bcebos.com/Parakeet/fastspeech2_nosil_aishell3_ckpt_0.4.zip) + +FastSpeech2 checkpoint contains files listed below. + +```text +fastspeech2_nosil_aishell3_ckpt_0.4 +├── default.yaml # default config used to train fastspeech2 +├── phone_id_map.txt # phone vocabulary file when training fastspeech2 +├── snapshot_iter_96400.pdz # model parameters and optimizer states +├── speaker_id_map.txt # speaker id map file when training a multi-speaker fastspeech2 +└── speech_stats.npy # statistics used to normalize spectrogram when training fastspeech2 +``` +## Synthesize +We use [parallel wavegan](https://github.com/PaddlePaddle/Parakeet/tree/develop/examples/parallelwave_gan/baker) as the neural vocoder. +Download pretrained parallel wavegan model from [pwg_baker_ckpt_0.4.zip](https://paddlespeech.bj.bcebos.com/Parakeet/pwg_baker_ckpt_0.4.zip) and unzip it. +```bash +unzip pwg_baker_ckpt_0.4.zip +``` +Parallel WaveGAN checkpoint contains files listed below. +```text +pwg_baker_ckpt_0.4 +├── pwg_default.yaml # default config used to train parallel wavegan +├── pwg_snapshot_iter_400000.pdz # model parameters of parallel wavegan +└── pwg_stats.npy # statistics used to normalize spectrogram when training parallel wavegan +``` +`synthesize.sh` calls `synthesize.py`, which can synthesize waveform from `metadata.jsonl`. +```bash +./synthesize.sh +``` +```text +usage: synthesize.py [-h] [--fastspeech2-config FASTSPEECH2_CONFIG] + [--fastspeech2-checkpoint FASTSPEECH2_CHECKPOINT] + [--fastspeech2-stat FASTSPEECH2_STAT] + [--pwg-config PWG_CONFIG] + [--pwg-checkpoint PWG_CHECKPOINT] [--pwg-stat PWG_STAT] + [--phones-dict PHONES_DICT] [--speaker-dict SPEAKER_DICT] + [--test-metadata TEST_METADATA] [--output-dir OUTPUT_DIR] + [--device DEVICE] [--verbose VERBOSE] + +Synthesize with fastspeech2 & parallel wavegan. + +optional arguments: + -h, --help show this help message and exit + --fastspeech2-config FASTSPEECH2_CONFIG + fastspeech2 config file. + --fastspeech2-checkpoint FASTSPEECH2_CHECKPOINT + fastspeech2 checkpoint to load. + --fastspeech2-stat FASTSPEECH2_STAT + mean and standard deviation used to normalize + spectrogram when training fastspeech2. + --pwg-config PWG_CONFIG + parallel wavegan config file. + --pwg-checkpoint PWG_CHECKPOINT + parallel wavegan generator parameters to load. + --pwg-stat PWG_STAT mean and standard deviation used to normalize + spectrogram when training parallel wavegan. + --phones-dict PHONES_DICT + phone vocabulary file. + --speaker-dict SPEAKER_DICT + speaker id map file for multiple speaker model. + --test-metadata TEST_METADATA + test metadata. + --output-dir OUTPUT_DIR + output dir. + --device DEVICE device type to use. + --verbose VERBOSE verbose. +``` + +`synthesize_e2e.sh` calls `synthesize_e2e.py`, which can synthesize waveform from text file. + +```bash +./synthesize_e2e.sh +``` +```text +usage: synthesize_e2e.py [-h] [--fastspeech2-config FASTSPEECH2_CONFIG] + [--fastspeech2-checkpoint FASTSPEECH2_CHECKPOINT] + [--fastspeech2-stat FASTSPEECH2_STAT] + [--pwg-config PWG_CONFIG] + [--pwg-checkpoint PWG_CHECKPOINT] + [--pwg-stat PWG_STAT] [--phones-dict PHONES_DICT] + [--speaker-dict SPEAKER_DICT] [--text TEXT] + [--output-dir OUTPUT_DIR] [--device DEVICE] + [--verbose VERBOSE] + +Synthesize with fastspeech2 & parallel wavegan. + +optional arguments: + -h, --help show this help message and exit + --fastspeech2-config FASTSPEECH2_CONFIG + fastspeech2 config file. + --fastspeech2-checkpoint FASTSPEECH2_CHECKPOINT + fastspeech2 checkpoint to load. + --fastspeech2-stat FASTSPEECH2_STAT + mean and standard deviation used to normalize + spectrogram when training fastspeech2. + --pwg-config PWG_CONFIG + parallel wavegan config file. + --pwg-checkpoint PWG_CHECKPOINT + parallel wavegan generator parameters to load. + --pwg-stat PWG_STAT mean and standard deviation used to normalize + spectrogram when training parallel wavegan. + --phones-dict PHONES_DICT + phone vocabulary file. + --speaker-dict SPEAKER_DICT + speaker id map file. + --text TEXT text to synthesize, a 'utt_id sentence' pair per line. + --output-dir OUTPUT_DIR + output dir. + --device DEVICE device type to use. + --verbose VERBOSE verbose. +``` +1. `--fastspeech2-config`, `--fastspeech2-checkpoint`, `--fastspeech2-stat`, `--phones-dict` and `--speaker-dict` are arguments for fastspeech2, which correspond to the 5 files in the fastspeech2 pretrained model. +2. `--pwg-config`, `--pwg-checkpoint`, `--pwg-stat` are arguments for parallel wavegan, which correspond to the 3 files in the parallel wavegan pretrained model. +3. `--test-metadata` should be the metadata file in the normalized subfolder of `test` in the `dump` folder. +4. `--text` is the text file, which contains sentences to synthesize. +5. `--output-dir` is the directory to save synthesized audio files. +6. `--device` is the type of device to run synthesis, 'cpu' and 'gpu' are supported. 'gpu' is recommended for faster synthesis. + +You can use the following scripts to synthesize for `../sentences.txt` using pretrained fastspeech2 and parallel wavegan models. +```bash +FLAGS_allocator_strategy=naive_best_fit \ +FLAGS_fraction_of_gpu_memory_to_use=0.01 \ +python3 synthesize_e2e.py \ + --fastspeech2-config=fastspeech2_nosil_aishell3_ckpt_0.4/default.yaml \ + --fastspeech2-checkpoint=fastspeech2_nosil_aishell3_ckpt_0.4/snapshot_iter_96400.pdz \ + --fastspeech2-stat=fastspeech2_nosil_aishell3_ckpt_0.4/speech_stats.npy \ + --pwg-config=pwg_baker_ckpt_0.4/pwg_default.yaml \ + --pwg-checkpoint=pwg_baker_ckpt_0.4/pwg_snapshot_iter_400000.pdz \ + --pwg-stat=pwg_baker_ckpt_0.4/pwg_stats.npy \ + --text=../sentences.txt \ + --output-dir=exp/default/test_e2e \ + --device="gpu" \ + --phones-dict=fastspeech2_nosil_aishell3_ckpt_0.4/phone_id_map.txt \ + --speaker-dict=fastspeech2_nosil_aishell3_ckpt_0.4/speaker_id_map.txt + +``` + +## Future work +A multi-speaker vocoder is needed. diff --git a/examples/vctk/fastspeech2/aishell3/conf/default.yaml b/examples/vctk/fastspeech2/aishell3/conf/default.yaml new file mode 100644 index 00000000..90816e7d --- /dev/null +++ b/examples/vctk/fastspeech2/aishell3/conf/default.yaml @@ -0,0 +1,106 @@ +########################################################### +# FEATURE EXTRACTION SETTING # +########################################################### + +fs: 24000 # sr +n_fft: 2048 # FFT size. +n_shift: 300 # Hop size. +win_length: 1200 # Window length. + # If set to null, it will be the same as fft_size. +window: "hann" # Window function. + +# Only used for feats_type != raw + +fmin: 80 # Minimum frequency of Mel basis. +fmax: 7600 # Maximum frequency of Mel basis. +n_mels: 80 # The number of mel basis. + +# Only used for the model using pitch features (e.g. FastSpeech2) +f0min: 80 # Maximum f0 for pitch extraction. +f0max: 400 # Minimum f0 for pitch extraction. + + +########################################################### +# DATA SETTING # +########################################################### +batch_size: 64 +num_workers: 4 + + +########################################################### +# MODEL SETTING # +########################################################### +model: + adim: 384 # attention dimension + aheads: 2 # number of attention heads + elayers: 4 # number of encoder layers + eunits: 1536 # number of encoder ff units + dlayers: 4 # number of decoder layers + dunits: 1536 # number of decoder ff units + positionwise_layer_type: conv1d # type of position-wise layer + positionwise_conv_kernel_size: 3 # kernel size of position wise conv layer + duration_predictor_layers: 2 # number of layers of duration predictor + duration_predictor_chans: 256 # number of channels of duration predictor + duration_predictor_kernel_size: 3 # filter size of duration predictor + postnet_layers: 5 # number of layers of postnset + postnet_filts: 5 # filter size of conv layers in postnet + postnet_chans: 256 # number of channels of conv layers in postnet + use_masking: True # whether to apply masking for padded part in loss calculation + use_scaled_pos_enc: True # whether to use scaled positional encoding + encoder_normalize_before: True # whether to perform layer normalization before the input + decoder_normalize_before: True # whether to perform layer normalization before the input + reduction_factor: 1 # reduction factor + init_type: xavier_uniform # initialization type + init_enc_alpha: 1.0 # initial value of alpha of encoder scaled position encoding + init_dec_alpha: 1.0 # initial value of alpha of decoder scaled position encoding + transformer_enc_dropout_rate: 0.2 # dropout rate for transformer encoder layer + transformer_enc_positional_dropout_rate: 0.2 # dropout rate for transformer encoder positional encoding + transformer_enc_attn_dropout_rate: 0.2 # dropout rate for transformer encoder attention layer + transformer_dec_dropout_rate: 0.2 # dropout rate for transformer decoder layer + transformer_dec_positional_dropout_rate: 0.2 # dropout rate for transformer decoder positional encoding + transformer_dec_attn_dropout_rate: 0.2 # dropout rate for transformer decoder attention layer + pitch_predictor_layers: 5 # number of conv layers in pitch predictor + pitch_predictor_chans: 256 # number of channels of conv layers in pitch predictor + pitch_predictor_kernel_size: 5 # kernel size of conv leyers in pitch predictor + pitch_predictor_dropout: 0.5 # dropout rate in pitch predictor + pitch_embed_kernel_size: 1 # kernel size of conv embedding layer for pitch + pitch_embed_dropout: 0.0 # dropout rate after conv embedding layer for pitch + stop_gradient_from_pitch_predictor: true # whether to stop the gradient from pitch predictor to encoder + energy_predictor_layers: 2 # number of conv layers in energy predictor + energy_predictor_chans: 256 # number of channels of conv layers in energy predictor + energy_predictor_kernel_size: 3 # kernel size of conv leyers in energy predictor + energy_predictor_dropout: 0.5 # dropout rate in energy predictor + energy_embed_kernel_size: 1 # kernel size of conv embedding layer for energy + energy_embed_dropout: 0.0 # dropout rate after conv embedding layer for energy + stop_gradient_from_energy_predictor: false # whether to stop the gradient from energy predictor to encoder + spk_embed_dim: 256 # speaker embedding dimension + spk_embed_integration_type: concat # speaker embedding integration type + + + +########################################################### +# UPDATER SETTING # +########################################################### +updater: + use_masking: True # whether to apply masking for padded part in loss calculation + + + +########################################################### +# OPTIMIZER SETTING # +########################################################### +optimizer: + optim: adam # optimizer type + learning_rate: 0.001 # learning rate + +########################################################### +# TRAINING SETTING # +########################################################### +max_epoch: 200 +num_snapshots: 5 + + +########################################################### +# OTHER SETTING # +########################################################### +seed: 10086 diff --git a/examples/vctk/fastspeech2/aishell3/preprocess.sh b/examples/vctk/fastspeech2/aishell3/preprocess.sh new file mode 100755 index 00000000..281abee0 --- /dev/null +++ b/examples/vctk/fastspeech2/aishell3/preprocess.sh @@ -0,0 +1,75 @@ +#!/bin/bash + +stage=0 +stop_stage=100 + +export MAIN_ROOT=`realpath ${PWD}/../../../` + +if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then + # get durations from MFA's result + echo "Generate durations.txt from MFA results ..." + python3 ${MAIN_ROOT}/utils/gen_duration_from_textgrid.py \ + --inputdir=./aishell3_alignment_tone \ + --output durations.txt \ + --config=conf/default.yaml +fi + +if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then + # extract features + echo "Extract features ..." + python3 ../preprocess.py \ + --dataset=aishell3 \ + --rootdir=~/datasets/data_aishell3/ \ + --dumpdir=dump \ + --dur-file=durations.txt \ + --config=conf/default.yaml \ + --num-cpu=20 \ + --cut-sil=True +fi + +if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then + # get features' stats(mean and std) + echo "Get features' stats ..." + python3 ${MAIN_ROOT}/utils/compute_statistics.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --field-name="speech" + + python3 ${MAIN_ROOT}/utils/compute_statistics.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --field-name="pitch" + + python3 ${MAIN_ROOT}/utils/compute_statistics.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --field-name="energy" +fi + +if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then + # normalize and covert phone/speaker to id, dev and test should use train's stats + echo "Normalize ..." + python3 ../normalize.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --dumpdir=dump/train/norm \ + --speech-stats=dump/train/speech_stats.npy \ + --pitch-stats=dump/train/pitch_stats.npy \ + --energy-stats=dump/train/energy_stats.npy \ + --phones-dict=dump/phone_id_map.txt \ + --speaker-dict=dump/speaker_id_map.txt + + python3 ../normalize.py \ + --metadata=dump/dev/raw/metadata.jsonl \ + --dumpdir=dump/dev/norm \ + --speech-stats=dump/train/speech_stats.npy \ + --pitch-stats=dump/train/pitch_stats.npy \ + --energy-stats=dump/train/energy_stats.npy \ + --phones-dict=dump/phone_id_map.txt \ + --speaker-dict=dump/speaker_id_map.txt + + python3 ../normalize.py \ + --metadata=dump/test/raw/metadata.jsonl \ + --dumpdir=dump/test/norm \ + --speech-stats=dump/train/speech_stats.npy \ + --pitch-stats=dump/train/pitch_stats.npy \ + --energy-stats=dump/train/energy_stats.npy \ + --phones-dict=dump/phone_id_map.txt \ + --speaker-dict=dump/speaker_id_map.txt +fi diff --git a/examples/vctk/fastspeech2/aishell3/run.sh b/examples/vctk/fastspeech2/aishell3/run.sh new file mode 100755 index 00000000..d4f06da9 --- /dev/null +++ b/examples/vctk/fastspeech2/aishell3/run.sh @@ -0,0 +1,10 @@ +#!/bin/bash + +python3 ../train.py \ + --train-metadata=dump/train/norm/metadata.jsonl \ + --dev-metadata=dump/dev/norm/metadata.jsonl \ + --config=conf/default.yaml \ + --output-dir=exp/default \ + --nprocs=2 \ + --phones-dict=dump/phone_id_map.txt \ + --speaker-dict=dump/speaker_id_map.txt diff --git a/examples/vctk/fastspeech2/aishell3/synthesize.sh b/examples/vctk/fastspeech2/aishell3/synthesize.sh new file mode 100755 index 00000000..950b2077 --- /dev/null +++ b/examples/vctk/fastspeech2/aishell3/synthesize.sh @@ -0,0 +1,15 @@ +#!/bin/bash +FLAGS_allocator_strategy=naive_best_fit \ +FLAGS_fraction_of_gpu_memory_to_use=0.01 \ +python3 ../synthesize.py \ + --fastspeech2-config=conf/default.yaml \ + --fastspeech2-checkpoint=exp/default/checkpoints/snapshot_iter_96400.pdz \ + --fastspeech2-stat=dump/train/speech_stats.npy \ + --pwg-config=pwg_baker_ckpt_0.4/pwg_default.yaml \ + --pwg-checkpoint=pwg_baker_ckpt_0.4/pwg_snapshot_iter_400000.pdz \ + --pwg-stat=pwg_baker_ckpt_0.4/pwg_stats.npy \ + --test-metadata=dump/test/norm/metadata.jsonl \ + --output-dir=exp/default/test \ + --device="gpu" \ + --phones-dict=dump/phone_id_map.txt \ + --speaker-dict=dump/speaker_id_map.txt diff --git a/examples/vctk/fastspeech2/aishell3/synthesize_e2e.py b/examples/vctk/fastspeech2/aishell3/synthesize_e2e.py new file mode 100644 index 00000000..13f59bfd --- /dev/null +++ b/examples/vctk/fastspeech2/aishell3/synthesize_e2e.py @@ -0,0 +1,170 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +import logging +from pathlib import Path + +import numpy as np +import paddle +import soundfile as sf +import yaml +from parakeet.frontend.zh_frontend import Frontend +from parakeet.models.fastspeech2 import FastSpeech2 +from parakeet.models.fastspeech2 import FastSpeech2Inference +from parakeet.models.parallel_wavegan import PWGGenerator +from parakeet.models.parallel_wavegan import PWGInference +from parakeet.modules.normalizer import ZScore +from yacs.config import CfgNode + + +def evaluate(args, fastspeech2_config, pwg_config): + # dataloader has been too verbose + logging.getLogger("DataLoader").disabled = True + + # construct dataset for evaluation + sentences = [] + with open(args.text, 'rt') as f: + for line in f: + utt_id, sentence = line.strip().split() + sentences.append((utt_id, sentence)) + + with open(args.phones_dict, "r") as f: + phn_id = [line.strip().split() for line in f.readlines()] + vocab_size = len(phn_id) + print("vocab_size:", vocab_size) + with open(args.speaker_dict, 'rt') as f: + spk_id = [line.strip().split() for line in f.readlines()] + num_speakers = len(spk_id) + print("num_speakers:", num_speakers) + + odim = fastspeech2_config.n_mels + model = FastSpeech2( + idim=vocab_size, + odim=odim, + num_speakers=num_speakers, + **fastspeech2_config["model"]) + + model.set_state_dict( + paddle.load(args.fastspeech2_checkpoint)["main_params"]) + model.eval() + + vocoder = PWGGenerator(**pwg_config["generator_params"]) + vocoder.set_state_dict(paddle.load(args.pwg_checkpoint)["generator_params"]) + vocoder.remove_weight_norm() + vocoder.eval() + print("model done!") + + frontend = Frontend(phone_vocab_path=args.phones_dict) + print("frontend done!") + + stat = np.load(args.fastspeech2_stat) + mu, std = stat + mu = paddle.to_tensor(mu) + std = paddle.to_tensor(std) + fastspeech2_normalizer = ZScore(mu, std) + + stat = np.load(args.pwg_stat) + mu, std = stat + mu = paddle.to_tensor(mu) + std = paddle.to_tensor(std) + pwg_normalizer = ZScore(mu, std) + + fastspeech2_inference = FastSpeech2Inference(fastspeech2_normalizer, model) + pwg_inference = PWGInference(pwg_normalizer, vocoder) + + output_dir = Path(args.output_dir) + output_dir.mkdir(parents=True, exist_ok=True) + # only test the number 0 speaker + spk_id = 0 + for utt_id, sentence in sentences: + input_ids = frontend.get_input_ids(sentence, merge_sentences=True) + phone_ids = input_ids["phone_ids"] + flags = 0 + for part_phone_ids in phone_ids: + with paddle.no_grad(): + mel = fastspeech2_inference( + part_phone_ids, spk_id=paddle.to_tensor(spk_id)) + temp_wav = pwg_inference(mel) + if flags == 0: + wav = temp_wav + flags = 1 + else: + wav = paddle.concat([wav, temp_wav]) + sf.write( + str(output_dir / (str(spk_id) + "_" + utt_id + ".wav")), + wav.numpy(), + samplerate=fastspeech2_config.fs) + print(f"{spk_id}_{utt_id} done!") + + +def main(): + # parse args and config and redirect to train_sp + parser = argparse.ArgumentParser( + description="Synthesize with fastspeech2 & parallel wavegan.") + parser.add_argument( + "--fastspeech2-config", type=str, help="fastspeech2 config file.") + parser.add_argument( + "--fastspeech2-checkpoint", + type=str, + help="fastspeech2 checkpoint to load.") + parser.add_argument( + "--fastspeech2-stat", + type=str, + help="mean and standard deviation used to normalize spectrogram when training fastspeech2." + ) + parser.add_argument( + "--pwg-config", type=str, help="parallel wavegan config file.") + parser.add_argument( + "--pwg-checkpoint", + type=str, + help="parallel wavegan generator parameters to load.") + parser.add_argument( + "--pwg-stat", + type=str, + help="mean and standard deviation used to normalize spectrogram when training parallel wavegan." + ) + parser.add_argument( + "--phones-dict", type=str, default=None, help="phone vocabulary file.") + parser.add_argument( + "--speaker-dict", type=str, default=None, help="speaker id map file.") + parser.add_argument( + "--text", + type=str, + help="text to synthesize, a 'utt_id sentence' pair per line.") + parser.add_argument("--output-dir", type=str, help="output dir.") + parser.add_argument( + "--device", type=str, default="gpu", help="device type to use.") + parser.add_argument("--verbose", type=int, default=1, help="verbose.") + + args = parser.parse_args() + + paddle.set_device(args.device) + + with open(args.fastspeech2_config) as f: + fastspeech2_config = CfgNode(yaml.safe_load(f)) + with open(args.pwg_config) as f: + pwg_config = CfgNode(yaml.safe_load(f)) + + print("========Args========") + print(yaml.safe_dump(vars(args))) + print("========Config========") + print(fastspeech2_config) + print(pwg_config) + + evaluate(args, fastspeech2_config, pwg_config) + + +if __name__ == "__main__": + main() diff --git a/examples/vctk/fastspeech2/aishell3/synthesize_e2e.sh b/examples/vctk/fastspeech2/aishell3/synthesize_e2e.sh new file mode 100755 index 00000000..31533714 --- /dev/null +++ b/examples/vctk/fastspeech2/aishell3/synthesize_e2e.sh @@ -0,0 +1,15 @@ +#!/bin/bash +FLAGS_allocator_strategy=naive_best_fit \ +FLAGS_fraction_of_gpu_memory_to_use=0.01 \ +python3 synthesize_e2e.py \ + --fastspeech2-config=conf/default.yaml \ + --fastspeech2-checkpoint=exp/default/checkpoints/snapshot_iter_96400.pdz \ + --fastspeech2-stat=dump/train/speech_stats.npy \ + --pwg-config=pwg_baker_ckpt_0.4/pwg_default.yaml \ + --pwg-checkpoint=pwg_baker_ckpt_0.4/pwg_snapshot_iter_400000.pdz \ + --pwg-stat=pwg_baker_ckpt_0.4/pwg_stats.npy \ + --text=../sentences.txt \ + --output-dir=exp/default/test_e2e \ + --device="gpu" \ + --phones-dict=dump/phone_id_map.txt \ + --speaker-dict=dump/speaker_id_map.txt diff --git a/examples/vctk/fastspeech2/baker/README.md b/examples/vctk/fastspeech2/baker/README.md new file mode 100644 index 00000000..a9f0fc8b --- /dev/null +++ b/examples/vctk/fastspeech2/baker/README.md @@ -0,0 +1,209 @@ +# FastSpeech2 with CSMSC +This example contains code used to train a [Fastspeech2](https://arxiv.org/abs/2006.04558) model with [Chinese Standard Mandarin Speech Copus](https://www.data-baker.com/open_source.html). + +## Dataset +### Download and Extract the datasaet +Download CSMSC from it's [Official Website](https://test.data-baker.com/data/index/source). + +### Get MFA result of CSMSC and Extract it +We use [MFA](https://github.com/MontrealCorpusTools/Montreal-Forced-Aligner) to get durations for fastspeech2. +You can download from here [baker_alignment_tone.tar.gz](https://paddlespeech.bj.bcebos.com/MFA/BZNSYP/with_tone/baker_alignment_tone.tar.gz), or train your own MFA model reference to [use_mfa example](https://github.com/PaddlePaddle/Parakeet/tree/develop/examples/use_mfa) of our repo. + +### Preprocess the dataset +Assume the path to the dataset is `~/datasets/BZNSYP`. +Assume the path to the MFA result of CSMSC is `./baker_alignment_tone`. +Run the command below to preprocess the dataset. + +```bash +./preprocess.sh +``` +When it is done. A `dump` folder is created in the current directory. The structure of the dump folder is listed below. + +```text +dump +├── dev +│ ├── norm +│ └── raw +├── phone_id_map.txt +├── speaker_id_map.txt +├── test +│ ├── norm +│ └── raw +└── train + ├── energy_stats.npy + ├── norm + ├── pitch_stats.npy + ├── raw + └── speech_stats.npy +``` +The dataset is split into 3 parts, namely `train`, `dev` and` test`, each of which contains a `norm` and `raw` sub folder. The raw folder contains speech、pitch and energy features of each utterances, while the norm folder contains normalized ones. The statistics used to normalize features are computed from the training set, which is located in `dump/train/*_stats.npy`. + +Also there is a `metadata.jsonl` in each subfolder. It is a table-like file which contains phones, text_lengths, speech_lengths, durations, path of speech features, path of pitch features, path of energy features, speaker and id of each utterance. + +## Train the model +`./run.sh` calls `../train.py`. +```bash +./run.sh +``` +Here's the complete help message. +```text +usage: train.py [-h] [--config CONFIG] [--train-metadata TRAIN_METADATA] + [--dev-metadata DEV_METADATA] [--output-dir OUTPUT_DIR] + [--device DEVICE] [--nprocs NPROCS] [--verbose VERBOSE] + [--phones-dict PHONES_DICT] [--speaker-dict SPEAKER_DICT] + +Train a FastSpeech2 model. + +optional arguments: + -h, --help show this help message and exit + --config CONFIG fastspeech2 config file. + --train-metadata TRAIN_METADATA + training data. + --dev-metadata DEV_METADATA + dev data. + --output-dir OUTPUT_DIR + output dir. + --device DEVICE device type to use. + --nprocs NPROCS number of processes. + --verbose VERBOSE verbose. + --phones-dict PHONES_DICT + phone vocabulary file. + --speaker-dict SPEAKER_DICT + speaker id map file for multiple speaker model. +``` +1. `--config` is a config file in yaml format to overwrite the default config, which can be found at `conf/default.yaml`. +2. `--train-metadata` and `--dev-metadata` should be the metadata file in the normalized subfolder of `train` and `dev` in the `dump` folder. +3. `--output-dir` is the directory to save the results of the experiment. Checkpoints are save in `checkpoints/` inside this directory. +4. `--device` is the type of the device to run the experiment, 'cpu' or 'gpu' are supported. +5. `--nprocs` is the number of processes to run in parallel, note that nprocs > 1 is only supported when `--device` is 'gpu'. +6. `--phones-dict` is the path of the phone vocabulary file. + +## Pretrained Model +Pretrained FastSpeech2 model with no silence in the edge of audios. [fastspeech2_nosil_baker_ckpt_0.4.zip](https://paddlespeech.bj.bcebos.com/Parakeet/fastspeech2_nosil_baker_ckpt_0.4.zip) + +FastSpeech2 checkpoint contains files listed below. +```text +fastspeech2_nosil_baker_ckpt_0.4 +├── default.yaml # default config used to train fastspeech2 +├── phone_id_map.txt # phone vocabulary file when training fastspeech2 +├── snapshot_iter_76000.pdz # model parameters and optimizer states +└── speech_stats.npy # statistics used to normalize spectrogram when training fastspeech2 +``` +## Synthesize +We use [parallel wavegan](https://github.com/PaddlePaddle/Parakeet/tree/develop/examples/parallelwave_gan/baker) as the neural vocoder. +Download pretrained parallel wavegan model from [pwg_baker_ckpt_0.4.zip](https://paddlespeech.bj.bcebos.com/Parakeet/pwg_baker_ckpt_0.4.zip) and unzip it. +```bash +unzip pwg_baker_ckpt_0.4.zip +``` +Parallel WaveGAN checkpoint contains files listed below. +```text +pwg_baker_ckpt_0.4 +├── pwg_default.yaml # default config used to train parallel wavegan +├── pwg_snapshot_iter_400000.pdz # model parameters of parallel wavegan +└── pwg_stats.npy # statistics used to normalize spectrogram when training parallel wavegan +``` +`synthesize.sh` calls `../synthesize.py`, which can synthesize waveform from `metadata.jsonl`. +```bash +./synthesize.sh +``` +```text +usage: synthesize.py [-h] [--fastspeech2-config FASTSPEECH2_CONFIG] + [--fastspeech2-checkpoint FASTSPEECH2_CHECKPOINT] + [--fastspeech2-stat FASTSPEECH2_STAT] + [--pwg-config PWG_CONFIG] + [--pwg-checkpoint PWG_CHECKPOINT] [--pwg-stat PWG_STAT] + [--phones-dict PHONES_DICT] [--speaker-dict SPEAKER_DICT] + [--test-metadata TEST_METADATA] [--output-dir OUTPUT_DIR] + [--device DEVICE] [--verbose VERBOSE] + +Synthesize with fastspeech2 & parallel wavegan. + +optional arguments: + -h, --help show this help message and exit + --fastspeech2-config FASTSPEECH2_CONFIG + fastspeech2 config file. + --fastspeech2-checkpoint FASTSPEECH2_CHECKPOINT + fastspeech2 checkpoint to load. + --fastspeech2-stat FASTSPEECH2_STAT + mean and standard deviation used to normalize + spectrogram when training fastspeech2. + --pwg-config PWG_CONFIG + parallel wavegan config file. + --pwg-checkpoint PWG_CHECKPOINT + parallel wavegan generator parameters to load. + --pwg-stat PWG_STAT mean and standard deviation used to normalize + spectrogram when training parallel wavegan. + --phones-dict PHONES_DICT + phone vocabulary file. + --speaker-dict SPEAKER_DICT + speaker id map file for multiple speaker model. + --test-metadata TEST_METADATA + test metadata. + --output-dir OUTPUT_DIR + output dir. + --device DEVICE device type to use. + --verbose VERBOSE verbose. +``` +`synthesize_e2e.sh` calls `synthesize_e2e.py`, which can synthesize waveform from text file. +```bash +./synthesize_e2e.sh +``` +```text +usage: synthesize_e2e.py [-h] [--fastspeech2-config FASTSPEECH2_CONFIG] + [--fastspeech2-checkpoint FASTSPEECH2_CHECKPOINT] + [--fastspeech2-stat FASTSPEECH2_STAT] + [--pwg-config PWG_CONFIG] + [--pwg-checkpoint PWG_CHECKPOINT] + [--pwg-stat PWG_STAT] [--phones-dict PHONES_DICT] + [--text TEXT] [--output-dir OUTPUT_DIR] + [--device DEVICE] [--verbose VERBOSE] + +Synthesize with fastspeech2 & parallel wavegan. + +optional arguments: + -h, --help show this help message and exit + --fastspeech2-config FASTSPEECH2_CONFIG + fastspeech2 config file. + --fastspeech2-checkpoint FASTSPEECH2_CHECKPOINT + fastspeech2 checkpoint to load. + --fastspeech2-stat FASTSPEECH2_STAT + mean and standard deviation used to normalize + spectrogram when training fastspeech2. + --pwg-config PWG_CONFIG + parallel wavegan config file. + --pwg-checkpoint PWG_CHECKPOINT + parallel wavegan generator parameters to load. + --pwg-stat PWG_STAT mean and standard deviation used to normalize + spectrogram when training parallel wavegan. + --phones-dict PHONES_DICT + phone vocabulary file. + --text TEXT text to synthesize, a 'utt_id sentence' pair per line. + --output-dir OUTPUT_DIR + output dir. + --device DEVICE device type to use. + --verbose VERBOSE verbose. +``` + +1. `--fastspeech2-config`, `--fastspeech2-checkpoint`, `--fastspeech2-stat` and `--phones-dict` are arguments for fastspeech2, which correspond to the 4 files in the fastspeech2 pretrained model. +2. `--pwg-config`, `--pwg-checkpoint`, `--pwg-stat` are arguments for parallel wavegan, which correspond to the 3 files in the parallel wavegan pretrained model. +3. `--test-metadata` should be the metadata file in the normalized subfolder of `test` in the `dump` folder. +4. `--text` is the text file, which contains sentences to synthesize. +5. `--output-dir` is the directory to save synthesized audio files. +6. `--device is` the type of device to run synthesis, 'cpu' and 'gpu' are supported. 'gpu' is recommended for faster synthesis. + +You can use the following scripts to synthesize for `../sentences.txt` using pretrained fastspeech2 and parallel wavegan models. +```bash +FLAGS_allocator_strategy=naive_best_fit \ +FLAGS_fraction_of_gpu_memory_to_use=0.01 \ +python3 synthesize_e2e.py \ + --fastspeech2-config=fastspeech2_nosil_baker_ckpt_0.4/default.yaml \ + --fastspeech2-checkpoint=fastspeech2_nosil_baker_ckpt_0.4/snapshot_iter_76000.pdz \ + --fastspeech2-stat=fastspeech2_nosil_baker_ckpt_0.4/speech_stats.npy \ + --pwg-config=pwg_baker_ckpt_0.4/pwg_default.yaml \ + --pwg-checkpoint=pwg_baker_ckpt_0.4/pwg_snapshot_iter_400000.pdz \ + --pwg-stat=pwg_baker_ckpt_0.4/pwg_stats.npy \ + --text=../sentences.txt \ + --output-dir=exp/default/test_e2e \ + --device="gpu" \ + --phones-dict=fastspeech2_nosil_baker_ckpt_0.4/phone_id_map.txt +``` diff --git a/examples/vctk/fastspeech2/baker/conf/default.yaml b/examples/vctk/fastspeech2/baker/conf/default.yaml new file mode 100644 index 00000000..32e58c4c --- /dev/null +++ b/examples/vctk/fastspeech2/baker/conf/default.yaml @@ -0,0 +1,104 @@ +########################################################### +# FEATURE EXTRACTION SETTING # +########################################################### + +fs: 24000 # sr +n_fft: 2048 # FFT size. +n_shift: 300 # Hop size. +win_length: 1200 # Window length. + # If set to null, it will be the same as fft_size. +window: "hann" # Window function. + +# Only used for feats_type != raw + +fmin: 80 # Minimum frequency of Mel basis. +fmax: 7600 # Maximum frequency of Mel basis. +n_mels: 80 # The number of mel basis. + +# Only used for the model using pitch features (e.g. FastSpeech2) +f0min: 80 # Maximum f0 for pitch extraction. +f0max: 400 # Minimum f0 for pitch extraction. + + +########################################################### +# DATA SETTING # +########################################################### +batch_size: 64 +num_workers: 4 + + +########################################################### +# MODEL SETTING # +########################################################### +model: + adim: 384 # attention dimension + aheads: 2 # number of attention heads + elayers: 4 # number of encoder layers + eunits: 1536 # number of encoder ff units + dlayers: 4 # number of decoder layers + dunits: 1536 # number of decoder ff units + positionwise_layer_type: conv1d # type of position-wise layer + positionwise_conv_kernel_size: 3 # kernel size of position wise conv layer + duration_predictor_layers: 2 # number of layers of duration predictor + duration_predictor_chans: 256 # number of channels of duration predictor + duration_predictor_kernel_size: 3 # filter size of duration predictor + postnet_layers: 5 # number of layers of postnset + postnet_filts: 5 # filter size of conv layers in postnet + postnet_chans: 256 # number of channels of conv layers in postnet + use_masking: True # whether to apply masking for padded part in loss calculation + use_scaled_pos_enc: True # whether to use scaled positional encoding + encoder_normalize_before: True # whether to perform layer normalization before the input + decoder_normalize_before: True # whether to perform layer normalization before the input + reduction_factor: 1 # reduction factor + init_type: xavier_uniform # initialization type + init_enc_alpha: 1.0 # initial value of alpha of encoder scaled position encoding + init_dec_alpha: 1.0 # initial value of alpha of decoder scaled position encoding + transformer_enc_dropout_rate: 0.2 # dropout rate for transformer encoder layer + transformer_enc_positional_dropout_rate: 0.2 # dropout rate for transformer encoder positional encoding + transformer_enc_attn_dropout_rate: 0.2 # dropout rate for transformer encoder attention layer + transformer_dec_dropout_rate: 0.2 # dropout rate for transformer decoder layer + transformer_dec_positional_dropout_rate: 0.2 # dropout rate for transformer decoder positional encoding + transformer_dec_attn_dropout_rate: 0.2 # dropout rate for transformer decoder attention layer + pitch_predictor_layers: 5 # number of conv layers in pitch predictor + pitch_predictor_chans: 256 # number of channels of conv layers in pitch predictor + pitch_predictor_kernel_size: 5 # kernel size of conv leyers in pitch predictor + pitch_predictor_dropout: 0.5 # dropout rate in pitch predictor + pitch_embed_kernel_size: 1 # kernel size of conv embedding layer for pitch + pitch_embed_dropout: 0.0 # dropout rate after conv embedding layer for pitch + stop_gradient_from_pitch_predictor: true # whether to stop the gradient from pitch predictor to encoder + energy_predictor_layers: 2 # number of conv layers in energy predictor + energy_predictor_chans: 256 # number of channels of conv layers in energy predictor + energy_predictor_kernel_size: 3 # kernel size of conv leyers in energy predictor + energy_predictor_dropout: 0.5 # dropout rate in energy predictor + energy_embed_kernel_size: 1 # kernel size of conv embedding layer for energy + energy_embed_dropout: 0.0 # dropout rate after conv embedding layer for energy + stop_gradient_from_energy_predictor: false # whether to stop the gradient from energy predictor to encoder + + + +########################################################### +# UPDATER SETTING # +########################################################### +updater: + use_masking: True # whether to apply masking for padded part in loss calculation + + + +########################################################### +# OPTIMIZER SETTING # +########################################################### +optimizer: + optim: adam # optimizer type + learning_rate: 0.001 # learning rate + +########################################################### +# TRAINING SETTING # +########################################################### +max_epoch: 1000 +num_snapshots: 5 + + +########################################################### +# OTHER SETTING # +########################################################### +seed: 10086 diff --git a/examples/vctk/fastspeech2/baker/preprocess.sh b/examples/vctk/fastspeech2/baker/preprocess.sh new file mode 100755 index 00000000..dff3e349 --- /dev/null +++ b/examples/vctk/fastspeech2/baker/preprocess.sh @@ -0,0 +1,75 @@ +#!/bin/bash + +stage=0 +stop_stage=100 + +export MAIN_ROOT=`realpath ${PWD}/../../../` + +if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then + # get durations from MFA's result + echo "Generate durations.txt from MFA results ..." + python3 ${MAIN_ROOT}/utils/gen_duration_from_textgrid.py \ + --inputdir=./baker_alignment_tone \ + --output=durations.txt \ + --config=conf/default.yaml +fi + +if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then + # extract features + echo "Extract features ..." + python3 ../preprocess.py \ + --dataset=baker \ + --rootdir=~/datasets/BZNSYP/ \ + --dumpdir=dump \ + --dur-file=durations.txt \ + --config=conf/default.yaml \ + --num-cpu=20 \ + --cut-sil=True +fi + +if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then + # get features' stats(mean and std) + echo "Get features' stats ..." + python3 ${MAIN_ROOT}/utils/compute_statistics.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --field-name="speech" + + python3 ${MAIN_ROOT}/utils/compute_statistics.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --field-name="pitch" + + python3 ${MAIN_ROOT}/utils/compute_statistics.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --field-name="energy" +fi + +if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then + # normalize and covert phone/speaker to id, dev and test should use train's stats + echo "Normalize ..." + python3 ../normalize.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --dumpdir=dump/train/norm \ + --speech-stats=dump/train/speech_stats.npy \ + --pitch-stats=dump/train/pitch_stats.npy \ + --energy-stats=dump/train/energy_stats.npy \ + --phones-dict=dump/phone_id_map.txt \ + --speaker-dict=dump/speaker_id_map.txt + + python3 ../normalize.py \ + --metadata=dump/dev/raw/metadata.jsonl \ + --dumpdir=dump/dev/norm \ + --speech-stats=dump/train/speech_stats.npy \ + --pitch-stats=dump/train/pitch_stats.npy \ + --energy-stats=dump/train/energy_stats.npy \ + --phones-dict=dump/phone_id_map.txt \ + --speaker-dict=dump/speaker_id_map.txt + + python3 ../normalize.py \ + --metadata=dump/test/raw/metadata.jsonl \ + --dumpdir=dump/test/norm \ + --speech-stats=dump/train/speech_stats.npy \ + --pitch-stats=dump/train/pitch_stats.npy \ + --energy-stats=dump/train/energy_stats.npy \ + --phones-dict=dump/phone_id_map.txt \ + --speaker-dict=dump/speaker_id_map.txt +fi diff --git a/examples/vctk/fastspeech2/baker/run.sh b/examples/vctk/fastspeech2/baker/run.sh new file mode 100755 index 00000000..3e9a5e22 --- /dev/null +++ b/examples/vctk/fastspeech2/baker/run.sh @@ -0,0 +1,9 @@ +#!/bin/bash + +python3 ../train.py \ + --train-metadata=dump/train/norm/metadata.jsonl \ + --dev-metadata=dump/dev/norm/metadata.jsonl \ + --config=conf/default.yaml \ + --output-dir=exp/default \ + --nprocs=1 \ + --phones-dict=dump/phone_id_map.txt \ No newline at end of file diff --git a/examples/vctk/fastspeech2/baker/simple.lexicon b/examples/vctk/fastspeech2/baker/simple.lexicon new file mode 100644 index 00000000..1a4e0cdf --- /dev/null +++ b/examples/vctk/fastspeech2/baker/simple.lexicon @@ -0,0 +1,4590 @@ +a1 a1 +a2 a2 +a3 a3 +a4 a4 +a5 a5 +ar1 ar1 +ar2 ar2 +ar3 ar3 +ar4 ar4 +ar5 ar5 +ai1 ai1 +ai2 ai2 +ai3 ai3 +ai4 ai4 +ai5 ai5 +air1 air1 +air2 air2 +air3 air3 +air4 air4 +air5 air5 +ao1 ao1 +ao2 ao2 +ao3 ao3 +ao4 ao4 +ao5 ao5 +aor1 aor1 +aor2 aor2 +aor3 aor3 +aor4 aor4 +aor5 aor5 +an1 an1 +an2 an2 +an3 an3 +an4 an4 +an5 an5 +anr1 anr1 +anr2 anr2 +anr3 anr3 +anr4 anr4 +anr5 anr5 +ang1 ang1 +ang2 ang2 +ang3 ang3 +ang4 ang4 +ang5 ang5 +angr1 angr1 +angr2 angr2 +angr3 angr3 +angr4 angr4 +angr5 angr5 +e1 e1 +e2 e2 +e3 e3 +e4 e4 +e5 e5 +er1 er1 +er2 er2 +er3 er3 +er4 er4 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+xingr1 x ingr1 +xingr2 x ingr2 +xingr3 x ingr3 +xingr4 x ingr4 +xingr5 x ingr5 +xu1 x v1 +xu2 x v2 +xu3 x v3 +xu4 x v4 +xu5 x v5 +xur1 x vr1 +xur2 x vr2 +xur3 x vr3 +xur4 x vr4 +xur5 x vr5 +xue1 x ve1 +xue2 x ve2 +xue3 x ve3 +xue4 x ve4 +xue5 x ve5 +xuer1 x ver1 +xuer2 x ver2 +xuer3 x ver3 +xuer4 x ver4 +xuer5 x ver5 +xuan1 x van1 +xuan2 x van2 +xuan3 x van3 +xuan4 x van4 +xuan5 x van5 +xuanr1 x vanr1 +xuanr2 x vanr2 +xuanr3 x vanr3 +xuanr4 x vanr4 +xuanr5 x vanr5 +xun1 x vn1 +xun2 x vn2 +xun3 x vn3 +xun4 x vn4 +xun5 x vn5 +xunr1 x vnr1 +xunr2 x vnr2 +xunr3 x vnr3 +xunr4 x vnr4 +xunr5 x vnr5 diff --git a/examples/vctk/fastspeech2/baker/synthesize.sh b/examples/vctk/fastspeech2/baker/synthesize.sh new file mode 100755 index 00000000..535ebdba --- /dev/null +++ b/examples/vctk/fastspeech2/baker/synthesize.sh @@ -0,0 +1,14 @@ +#!/bin/bash +FLAGS_allocator_strategy=naive_best_fit \ +FLAGS_fraction_of_gpu_memory_to_use=0.01 \ +python3 ../synthesize.py \ + --fastspeech2-config=conf/default.yaml \ + --fastspeech2-checkpoint=exp/default/checkpoints/snapshot_iter_76000.pdz \ + --fastspeech2-stat=dump/train/speech_stats.npy \ + --pwg-config=pwg_baker_ckpt_0.4/pwg_default.yaml \ + --pwg-checkpoint=pwg_baker_ckpt_0.4/pwg_snapshot_iter_400000.pdz \ + --pwg-stat=pwg_baker_ckpt_0.4/pwg_stats.npy \ + --test-metadata=dump/test/norm/metadata.jsonl \ + --output-dir=exp/default/test \ + --device="gpu" \ + --phones-dict=dump/phone_id_map.txt diff --git a/examples/vctk/fastspeech2/baker/synthesize_e2e.py b/examples/vctk/fastspeech2/baker/synthesize_e2e.py new file mode 100644 index 00000000..75e06edf --- /dev/null +++ b/examples/vctk/fastspeech2/baker/synthesize_e2e.py @@ -0,0 +1,161 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +import logging +from pathlib import Path + +import numpy as np +import paddle +import soundfile as sf +import yaml +from parakeet.frontend.zh_frontend import Frontend +from parakeet.models.fastspeech2 import FastSpeech2 +from parakeet.models.fastspeech2 import FastSpeech2Inference +from parakeet.models.parallel_wavegan import PWGGenerator +from parakeet.models.parallel_wavegan import PWGInference +from parakeet.modules.normalizer import ZScore +from yacs.config import CfgNode + + +def evaluate(args, fastspeech2_config, pwg_config): + # dataloader has been too verbose + logging.getLogger("DataLoader").disabled = True + + # construct dataset for evaluation + sentences = [] + with open(args.text, 'rt') as f: + for line in f: + utt_id, sentence = line.strip().split() + sentences.append((utt_id, sentence)) + + with open(args.phones_dict, "r") as f: + phn_id = [line.strip().split() for line in f.readlines()] + vocab_size = len(phn_id) + print("vocab_size:", vocab_size) + odim = fastspeech2_config.n_mels + model = FastSpeech2( + idim=vocab_size, odim=odim, **fastspeech2_config["model"]) + + model.set_state_dict( + paddle.load(args.fastspeech2_checkpoint)["main_params"]) + model.eval() + + vocoder = PWGGenerator(**pwg_config["generator_params"]) + vocoder.set_state_dict(paddle.load(args.pwg_checkpoint)["generator_params"]) + vocoder.remove_weight_norm() + vocoder.eval() + print("model done!") + + frontend = Frontend(phone_vocab_path=args.phones_dict) + print("frontend done!") + + stat = np.load(args.fastspeech2_stat) + mu, std = stat + mu = paddle.to_tensor(mu) + std = paddle.to_tensor(std) + fastspeech2_normalizer = ZScore(mu, std) + + stat = np.load(args.pwg_stat) + mu, std = stat + mu = paddle.to_tensor(mu) + std = paddle.to_tensor(std) + pwg_normalizer = ZScore(mu, std) + + fastspeech2_inference = FastSpeech2Inference(fastspeech2_normalizer, model) + pwg_inference = PWGInference(pwg_normalizer, vocoder) + + output_dir = Path(args.output_dir) + output_dir.mkdir(parents=True, exist_ok=True) + + for utt_id, sentence in sentences: + input_ids = frontend.get_input_ids(sentence, merge_sentences=True) + phone_ids = input_ids["phone_ids"] + flags = 0 + for part_phone_ids in phone_ids: + with paddle.no_grad(): + mel = fastspeech2_inference(part_phone_ids) + temp_wav = pwg_inference(mel) + if flags == 0: + wav = temp_wav + flags = 1 + else: + wav = paddle.concat([wav, temp_wav]) + sf.write( + str(output_dir / (utt_id + ".wav")), + wav.numpy(), + samplerate=fastspeech2_config.fs) + print(f"{utt_id} done!") + + +def main(): + # parse args and config and redirect to train_sp + parser = argparse.ArgumentParser( + description="Synthesize with fastspeech2 & parallel wavegan.") + parser.add_argument( + "--fastspeech2-config", type=str, help="fastspeech2 config file.") + parser.add_argument( + "--fastspeech2-checkpoint", + type=str, + help="fastspeech2 checkpoint to load.") + parser.add_argument( + "--fastspeech2-stat", + type=str, + help="mean and standard deviation used to normalize spectrogram when training fastspeech2." + ) + parser.add_argument( + "--pwg-config", type=str, help="parallel wavegan config file.") + parser.add_argument( + "--pwg-checkpoint", + type=str, + help="parallel wavegan generator parameters to load.") + parser.add_argument( + "--pwg-stat", + type=str, + help="mean and standard deviation used to normalize spectrogram when training parallel wavegan." + ) + parser.add_argument( + "--phones-dict", + type=str, + default="phone_id_map.txt", + help="phone vocabulary file.") + parser.add_argument( + "--text", + type=str, + help="text to synthesize, a 'utt_id sentence' pair per line.") + parser.add_argument("--output-dir", type=str, help="output dir.") + parser.add_argument( + "--device", type=str, default="gpu", help="device type to use.") + parser.add_argument("--verbose", type=int, default=1, help="verbose.") + + args = parser.parse_args() + + paddle.set_device(args.device) + + with open(args.fastspeech2_config) as f: + fastspeech2_config = CfgNode(yaml.safe_load(f)) + with open(args.pwg_config) as f: + pwg_config = CfgNode(yaml.safe_load(f)) + + print("========Args========") + print(yaml.safe_dump(vars(args))) + print("========Config========") + print(fastspeech2_config) + print(pwg_config) + + evaluate(args, fastspeech2_config, pwg_config) + + +if __name__ == "__main__": + main() diff --git a/examples/vctk/fastspeech2/baker/synthesize_e2e.sh b/examples/vctk/fastspeech2/baker/synthesize_e2e.sh new file mode 100755 index 00000000..a2deec14 --- /dev/null +++ b/examples/vctk/fastspeech2/baker/synthesize_e2e.sh @@ -0,0 +1,14 @@ +#!/bin/bash +FLAGS_allocator_strategy=naive_best_fit \ +FLAGS_fraction_of_gpu_memory_to_use=0.01 \ +python3 synthesize_e2e.py \ + --fastspeech2-config=conf/default.yaml \ + --fastspeech2-checkpoint=exp/default/checkpoints/snapshot_iter_153.pdz \ + --fastspeech2-stat=dump/train/speech_stats.npy \ + --pwg-config=pwg_baker_ckpt_0.4/pwg_default.yaml \ + --pwg-checkpoint=pwg_baker_ckpt_0.4/pwg_snapshot_iter_400000.pdz \ + --pwg-stat=pwg_baker_ckpt_0.4/pwg_stats.npy \ + --text=../sentences.txt \ + --output-dir=exp/default/test_e2e \ + --device="gpu" \ + --phones-dict=dump/phone_id_map.txt diff --git a/examples/vctk/fastspeech2/ljspeech/README.md b/examples/vctk/fastspeech2/ljspeech/README.md new file mode 100644 index 00000000..ed905bea --- /dev/null +++ b/examples/vctk/fastspeech2/ljspeech/README.md @@ -0,0 +1,209 @@ +# FastSpeech2 with the LJSpeech-1.1 +This example contains code used to train a [Fastspeech2](https://arxiv.org/abs/2006.04558) model with [LJSpeech-1.1](https://keithito.com/LJ-Speech-Dataset/). + +## Dataset +### Download and Extract the datasaet +Download LJSpeech-1.1 from the [official website](https://keithito.com/LJ-Speech-Dataset/). + +### Get MFA result of LJSpeech-1.1 and Extract it +We use [MFA](https://github.com/MontrealCorpusTools/Montreal-Forced-Aligner) to get durations for fastspeech2. +You can download from here [ljspeech_alignment.tar.gz](https://paddlespeech.bj.bcebos.com/MFA/LJSpeech-1.1/ljspeech_alignment.tar.gz), or train your own MFA model reference to [use_mfa example](https://github.com/PaddlePaddle/Parakeet/tree/develop/examples/use_mfa) of our repo. + +### Preprocess the dataset +Assume the path to the dataset is `~/datasets/LJSpeech-1.1`. +Assume the path to the MFA result of LJSpeech-1.1 is `./ljspeech_alignment`. +Run the command below to preprocess the dataset. + +```bash +./preprocess.sh +``` +When it is done. A `dump` folder is created in the current directory. The structure of the dump folder is listed below. + +```text +dump +├── dev +│ ├── norm +│ └── raw +├── phone_id_map.txt +├── speaker_id_map.txt +├── test +│ ├── norm +│ └── raw +└── train + ├── energy_stats.npy + ├── norm + ├── pitch_stats.npy + ├── raw + └── speech_stats.npy +``` +The dataset is split into 3 parts, namely `train`, `dev` and` test`, each of which contains a `norm` and `raw` sub folder. The raw folder contains speech、pitch and energy features of each utterances, while the norm folder contains normalized ones. The statistics used to normalize features are computed from the training set, which is located in `dump/train/*_stats.npy`. + +Also there is a `metadata.jsonl` in each subfolder. It is a table-like file which contains phones, text_lengths, speech_lengths, durations, path of speech features, path of pitch features, path of energy features, speaker and id of each utterance. + +## Train the model +`./run.sh` calls `../train.py`. +```bash +./run.sh +``` +Here's the complete help message. +```text +usage: train.py [-h] [--config CONFIG] [--train-metadata TRAIN_METADATA] + [--dev-metadata DEV_METADATA] [--output-dir OUTPUT_DIR] + [--device DEVICE] [--nprocs NPROCS] [--verbose VERBOSE] + [--phones-dict PHONES_DICT] [--speaker-dict SPEAKER_DICT] + +Train a FastSpeech2 model. + +optional arguments: + -h, --help show this help message and exit + --config CONFIG fastspeech2 config file. + --train-metadata TRAIN_METADATA + training data. + --dev-metadata DEV_METADATA + dev data. + --output-dir OUTPUT_DIR + output dir. + --device DEVICE device type to use. + --nprocs NPROCS number of processes. + --verbose VERBOSE verbose. + --phones-dict PHONES_DICT + phone vocabulary file. + --speaker-dict SPEAKER_DICT + speaker id map file for multiple speaker model. +``` +1. `--config` is a config file in yaml format to overwrite the default config, which can be found at `conf/default.yaml`. +2. `--train-metadata` and `--dev-metadata` should be the metadata file in the normalized subfolder of `train` and `dev` in the `dump` folder. +3. `--output-dir` is the directory to save the results of the experiment. Checkpoints are save in `checkpoints/` inside this directory. +4. `--device` is the type of the device to run the experiment, 'cpu' or 'gpu' are supported. +5. `--nprocs` is the number of processes to run in parallel, note that nprocs > 1 is only supported when `--device` is 'gpu'. +6. `--phones-dict` is the path of the phone vocabulary file. + +## Pretrained Model +Pretrained FastSpeech2 model with no silence in the edge of audios. [fastspeech2_nosil_ljspeech_ckpt_0.5.zip](https://paddlespeech.bj.bcebos.com/Parakeet/fastspeech2_nosil_ljspeech_ckpt_0.5.zip) + +FastSpeech2 checkpoint contains files listed below. +```text +fastspeech2_nosil_ljspeech_ckpt_0.5 +├── default.yaml # default config used to train fastspeech2 +├── phone_id_map.txt # phone vocabulary file when training fastspeech2 +├── snapshot_iter_100000.pdz # model parameters and optimizer states +└── speech_stats.npy # statistics used to normalize spectrogram when training fastspeech2 +``` +## Synthesize +We use [parallel wavegan](https://github.com/PaddlePaddle/Parakeet/tree/develop/examples/parallelwave_gan/ljspeech/) as the neural vocoder. +Download pretrained parallel wavegan model from [pwg_ljspeech_ckpt_0.5.zip](https://paddlespeech.bj.bcebos.com/Parakeet/pwg_ljspeech_ckpt_0.5.zip) and unzip it. +```bash +unzip pwg_ljspeech_ckpt_0.5.zip +``` +Parallel WaveGAN checkpoint contains files listed below. +```text +pwg_ljspeech_ckpt_0.5 +├── pwg_default.yaml # default config used to train parallel wavegan +├── pwg_snapshot_iter_400000.pdz # generator parameters of parallel wavegan +└── pwg_stats.npy # statistics used to normalize spectrogram when training parallel wavegan +``` +`synthesize.sh` calls `../synthesize.py`, which can synthesize waveform from `metadata.jsonl`. +```bash +./synthesize.sh +``` +```text +usage: synthesize.py [-h] [--fastspeech2-config FASTSPEECH2_CONFIG] + [--fastspeech2-checkpoint FASTSPEECH2_CHECKPOINT] + [--fastspeech2-stat FASTSPEECH2_STAT] + [--pwg-config PWG_CONFIG] + [--pwg-checkpoint PWG_CHECKPOINT] [--pwg-stat PWG_STAT] + [--phones-dict PHONES_DICT] [--speaker-dict SPEAKER_DICT] + [--test-metadata TEST_METADATA] [--output-dir OUTPUT_DIR] + [--device DEVICE] [--verbose VERBOSE] + +Synthesize with fastspeech2 & parallel wavegan. + +optional arguments: + -h, --help show this help message and exit + --fastspeech2-config FASTSPEECH2_CONFIG + fastspeech2 config file. + --fastspeech2-checkpoint FASTSPEECH2_CHECKPOINT + fastspeech2 checkpoint to load. + --fastspeech2-stat FASTSPEECH2_STAT + mean and standard deviation used to normalize + spectrogram when training fastspeech2. + --pwg-config PWG_CONFIG + parallel wavegan config file. + --pwg-checkpoint PWG_CHECKPOINT + parallel wavegan generator parameters to load. + --pwg-stat PWG_STAT mean and standard deviation used to normalize + spectrogram when training parallel wavegan. + --phones-dict PHONES_DICT + phone vocabulary file. + --speaker-dict SPEAKER_DICT + speaker id map file for multiple speaker model. + --test-metadata TEST_METADATA + test metadata. + --output-dir OUTPUT_DIR + output dir. + --device DEVICE device type to use. + --verbose VERBOSE verbose. +``` +`synthesize_e2e.sh` calls `synthesize_e2e.py`, which can synthesize waveform from text file. +```bash +./synthesize_e2e.sh +``` +```text +usage: synthesize_e2e.py [-h] [--fastspeech2-config FASTSPEECH2_CONFIG] + [--fastspeech2-checkpoint FASTSPEECH2_CHECKPOINT] + [--fastspeech2-stat FASTSPEECH2_STAT] + [--pwg-config PWG_CONFIG] + [--pwg-checkpoint PWG_CHECKPOINT] + [--pwg-stat PWG_STAT] [--phones-dict PHONES_DICT] + [--text TEXT] [--output-dir OUTPUT_DIR] + [--device DEVICE] [--verbose VERBOSE] + +Synthesize with fastspeech2 & parallel wavegan. + +optional arguments: + -h, --help show this help message and exit + --fastspeech2-config FASTSPEECH2_CONFIG + fastspeech2 config file. + --fastspeech2-checkpoint FASTSPEECH2_CHECKPOINT + fastspeech2 checkpoint to load. + --fastspeech2-stat FASTSPEECH2_STAT + mean and standard deviation used to normalize + spectrogram when training fastspeech2. + --pwg-config PWG_CONFIG + parallel wavegan config file. + --pwg-checkpoint PWG_CHECKPOINT + parallel wavegan generator parameters to load. + --pwg-stat PWG_STAT mean and standard deviation used to normalize + spectrogram when training parallel wavegan. + --phones-dict PHONES_DICT + phone vocabulary file. + --text TEXT text to synthesize, a 'utt_id sentence' pair per line. + --output-dir OUTPUT_DIR + output dir. + --device DEVICE device type to use. + --verbose VERBOSE verbose. +``` + +1. `--fastspeech2-config`, `--fastspeech2-checkpoint`, `--fastspeech2-stat` and `--phones-dict` are arguments for fastspeech2, which correspond to the 4 files in the fastspeech2 pretrained model. +2. `--pwg-config`, `--pwg-checkpoint`, `--pwg-stat` are arguments for parallel wavegan, which correspond to the 3 files in the parallel wavegan pretrained model. +3. `--test-metadata` should be the metadata file in the normalized subfolder of `test` in the `dump` folder. +4. `--text` is the text file, which contains sentences to synthesize. +5. `--output-dir` is the directory to save synthesized audio files. +6. `--device is` the type of device to run synthesis, 'cpu' and 'gpu' are supported. 'gpu' is recommended for faster synthesis. + +You can use the following scripts to synthesize for `../sentences_en.txt` using pretrained fastspeech2 and parallel wavegan models. +```bash +FLAGS_allocator_strategy=naive_best_fit \ +FLAGS_fraction_of_gpu_memory_to_use=0.01 \ +python3 synthesize_e2e.py \ + --fastspeech2-config=fastspeech2_nosil_ljspeech_ckpt_0.5/default.yaml \ + --fastspeech2-checkpoint=fastspeech2_nosil_ljspeech_ckpt_0.5/snapshot_iter_100000.pdz \ + --fastspeech2-stat=fastspeech2_nosil_ljspeech_ckpt_0.5/speech_stats.npy \ + --pwg-config=pwg_ljspeech_ckpt_0.5/pwg_default.yaml \ + --pwg-checkpoint=pwg_ljspeech_ckpt_0.5/pwg_snapshot_iter_400000.pdz \ + --pwg-stat=pwg_ljspeech_ckpt_0.5/pwg_stats.npy \ + --text=../sentences_en.txt \ + --output-dir=exp/default/test_e2e \ + --device="gpu" \ + --phones-dict=fastspeech2_nosil_ljspeech_ckpt_0.5/phone_id_map.txt +``` diff --git a/examples/vctk/fastspeech2/ljspeech/conf/default.yaml b/examples/vctk/fastspeech2/ljspeech/conf/default.yaml new file mode 100644 index 00000000..cabcca80 --- /dev/null +++ b/examples/vctk/fastspeech2/ljspeech/conf/default.yaml @@ -0,0 +1,104 @@ +########################################################### +# FEATURE EXTRACTION SETTING # +########################################################### + +fs: 22050 # sr +n_fft: 1024 # FFT size. +n_shift: 256 # Hop size. +win_length: null # Window length. + # If set to null, it will be the same as fft_size. +window: "hann" # Window function. + +# Only used for feats_type != raw + +fmin: 80 # Minimum frequency of Mel basis. +fmax: 7600 # Maximum frequency of Mel basis. +n_mels: 80 # The number of mel basis. + +# Only used for the model using pitch features (e.g. FastSpeech2) +f0min: 80 # Maximum f0 for pitch extraction. +f0max: 400 # Minimum f0 for pitch extraction. + + +########################################################### +# DATA SETTING # +########################################################### +batch_size: 64 +num_workers: 4 + + +########################################################### +# MODEL SETTING # +########################################################### +model: + adim: 384 # attention dimension + aheads: 2 # number of attention heads + elayers: 4 # number of encoder layers + eunits: 1536 # number of encoder ff units + dlayers: 4 # number of decoder layers + dunits: 1536 # number of decoder ff units + positionwise_layer_type: conv1d # type of position-wise layer + positionwise_conv_kernel_size: 3 # kernel size of position wise conv layer + duration_predictor_layers: 2 # number of layers of duration predictor + duration_predictor_chans: 256 # number of channels of duration predictor + duration_predictor_kernel_size: 3 # filter size of duration predictor + postnet_layers: 5 # number of layers of postnset + postnet_filts: 5 # filter size of conv layers in postnet + postnet_chans: 256 # number of channels of conv layers in postnet + use_masking: True # whether to apply masking for padded part in loss calculation + use_scaled_pos_enc: True # whether to use scaled positional encoding + encoder_normalize_before: True # whether to perform layer normalization before the input + decoder_normalize_before: True # whether to perform layer normalization before the input + reduction_factor: 1 # reduction factor + init_type: xavier_uniform # initialization type + init_enc_alpha: 1.0 # initial value of alpha of encoder scaled position encoding + init_dec_alpha: 1.0 # initial value of alpha of decoder scaled position encoding + transformer_enc_dropout_rate: 0.2 # dropout rate for transformer encoder layer + transformer_enc_positional_dropout_rate: 0.2 # dropout rate for transformer encoder positional encoding + transformer_enc_attn_dropout_rate: 0.2 # dropout rate for transformer encoder attention layer + transformer_dec_dropout_rate: 0.2 # dropout rate for transformer decoder layer + transformer_dec_positional_dropout_rate: 0.2 # dropout rate for transformer decoder positional encoding + transformer_dec_attn_dropout_rate: 0.2 # dropout rate for transformer decoder attention layer + pitch_predictor_layers: 5 # number of conv layers in pitch predictor + pitch_predictor_chans: 256 # number of channels of conv layers in pitch predictor + pitch_predictor_kernel_size: 5 # kernel size of conv leyers in pitch predictor + pitch_predictor_dropout: 0.5 # dropout rate in pitch predictor + pitch_embed_kernel_size: 1 # kernel size of conv embedding layer for pitch + pitch_embed_dropout: 0.0 # dropout rate after conv embedding layer for pitch + stop_gradient_from_pitch_predictor: true # whether to stop the gradient from pitch predictor to encoder + energy_predictor_layers: 2 # number of conv layers in energy predictor + energy_predictor_chans: 256 # number of channels of conv layers in energy predictor + energy_predictor_kernel_size: 3 # kernel size of conv leyers in energy predictor + energy_predictor_dropout: 0.5 # dropout rate in energy predictor + energy_embed_kernel_size: 1 # kernel size of conv embedding layer for energy + energy_embed_dropout: 0.0 # dropout rate after conv embedding layer for energy + stop_gradient_from_energy_predictor: false # whether to stop the gradient from energy predictor to encoder + + + +########################################################### +# UPDATER SETTING # +########################################################### +updater: + use_masking: True # whether to apply masking for padded part in loss calculation + + + +########################################################### +# OPTIMIZER SETTING # +########################################################### +optimizer: + optim: adam # optimizer type + learning_rate: 0.001 # learning rate + +########################################################### +# TRAINING SETTING # +########################################################### +max_epoch: 1000 +num_snapshots: 5 + + +########################################################### +# OTHER SETTING # +########################################################### +seed: 10086 diff --git a/examples/vctk/fastspeech2/ljspeech/preprocess.sh b/examples/vctk/fastspeech2/ljspeech/preprocess.sh new file mode 100755 index 00000000..ff2e765d --- /dev/null +++ b/examples/vctk/fastspeech2/ljspeech/preprocess.sh @@ -0,0 +1,75 @@ +#!/bin/bash + +stage=0 +stop_stage=100 + +export MAIN_ROOT=`realpath ${PWD}/../../../` + +if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then + # get durations from MFA's result + echo "Generate durations.txt from MFA results ..." + python3 ${MAIN_ROOT}/utils/gen_duration_from_textgrid.py \ + --inputdir=./ljspeech_alignment \ + --output=durations.txt \ + --config=conf/default.yaml +fi + +if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then + # extract features + echo "Extract features ..." + python3 ../preprocess.py \ + --dataset=ljspeech \ + --rootdir=~/datasets/LJSpeech-1.1/ \ + --dumpdir=dump \ + --dur-file=durations.txt \ + --config=conf/default.yaml \ + --num-cpu=8 \ + --cut-sil=True +fi + +if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then + # get features' stats(mean and std) + echo "Get features' stats ..." + python3 ${MAIN_ROOT}/utils/compute_statistics.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --field-name="speech" + + python3 ${MAIN_ROOT}/utils/compute_statistics.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --field-name="pitch" + + python3 ${MAIN_ROOT}/utils/compute_statistics.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --field-name="energy" +fi + +if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then + # normalize and covert phone/speaker to id, dev and test should use train's stats + echo "Normalize ..." + python3 ../normalize.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --dumpdir=dump/train/norm \ + --speech-stats=dump/train/speech_stats.npy \ + --pitch-stats=dump/train/pitch_stats.npy \ + --energy-stats=dump/train/energy_stats.npy \ + --phones-dict=dump/phone_id_map.txt \ + --speaker-dict=dump/speaker_id_map.txt + + python3 ../normalize.py \ + --metadata=dump/dev/raw/metadata.jsonl \ + --dumpdir=dump/dev/norm \ + --speech-stats=dump/train/speech_stats.npy \ + --pitch-stats=dump/train/pitch_stats.npy \ + --energy-stats=dump/train/energy_stats.npy \ + --phones-dict=dump/phone_id_map.txt \ + --speaker-dict=dump/speaker_id_map.txt + + python3 ../normalize.py \ + --metadata=dump/test/raw/metadata.jsonl \ + --dumpdir=dump/test/norm \ + --speech-stats=dump/train/speech_stats.npy \ + --pitch-stats=dump/train/pitch_stats.npy \ + --energy-stats=dump/train/energy_stats.npy \ + --phones-dict=dump/phone_id_map.txt \ + --speaker-dict=dump/speaker_id_map.txt +fi diff --git a/examples/vctk/fastspeech2/ljspeech/run.sh b/examples/vctk/fastspeech2/ljspeech/run.sh new file mode 100755 index 00000000..fd5e2c68 --- /dev/null +++ b/examples/vctk/fastspeech2/ljspeech/run.sh @@ -0,0 +1,9 @@ +#!/bin/bash + +python3 ../train.py \ + --train-metadata=dump/train/norm/metadata.jsonl \ + --dev-metadata=dump/dev/norm/metadata.jsonl \ + --config=conf/default.yaml \ + --output-dir=exp/default \ + --nprocs=1 \ + --phones-dict=dump/phone_id_map.txt diff --git a/examples/vctk/fastspeech2/ljspeech/synthesize.sh b/examples/vctk/fastspeech2/ljspeech/synthesize.sh new file mode 100755 index 00000000..0f8225e4 --- /dev/null +++ b/examples/vctk/fastspeech2/ljspeech/synthesize.sh @@ -0,0 +1,15 @@ + +#!/bin/bash +FLAGS_allocator_strategy=naive_best_fit \ +FLAGS_fraction_of_gpu_memory_to_use=0.01 \ +python3 ../synthesize.py \ + --fastspeech2-config=conf/default.yaml \ + --fastspeech2-checkpoint=exp/default/checkpoints/snapshot_iter_100000.pdz \ + --fastspeech2-stat=dump/train/speech_stats.npy \ + --pwg-config=pwg_ljspeech_ckpt_0.5/pwg_default.yaml \ + --pwg-checkpoint=pwg_ljspeech_ckpt_0.5/pwg_snapshot_iter_400000.pdz \ + --pwg-stat=pwg_ljspeech_ckpt_0.5/pwg_stats.npy \ + --test-metadata=dump/test/norm/metadata.jsonl \ + --output-dir=exp/default/test \ + --device="gpu" \ + --phones-dict=dump/phone_id_map.txt diff --git a/examples/vctk/fastspeech2/ljspeech/synthesize_e2e.py b/examples/vctk/fastspeech2/ljspeech/synthesize_e2e.py new file mode 100644 index 00000000..6732aa40 --- /dev/null +++ b/examples/vctk/fastspeech2/ljspeech/synthesize_e2e.py @@ -0,0 +1,170 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +import logging +from pathlib import Path + +import numpy as np +import paddle +import soundfile as sf +import yaml +from yacs.config import CfgNode +from parakeet.frontend import English +from parakeet.models.fastspeech2 import FastSpeech2 +from parakeet.models.fastspeech2 import FastSpeech2Inference +from parakeet.models.parallel_wavegan import PWGGenerator +from parakeet.models.parallel_wavegan import PWGInference +from parakeet.modules.normalizer import ZScore + + +def evaluate(args, fastspeech2_config, pwg_config): + # dataloader has been too verbose + logging.getLogger("DataLoader").disabled = True + + # construct dataset for evaluation + sentences = [] + with open(args.text, 'rt') as f: + for line in f: + line_list = line.strip().split() + utt_id = line_list[0] + sentence = " ".join(line_list[1:]) + sentences.append((utt_id, sentence)) + + with open(args.phones_dict, "r") as f: + phn_id = [line.strip().split() for line in f.readlines()] + vocab_size = len(phn_id) + phone_id_map = {} + for phn, id in phn_id: + phone_id_map[phn] = int(id) + print("vocab_size:", vocab_size) + odim = fastspeech2_config.n_mels + model = FastSpeech2( + idim=vocab_size, odim=odim, **fastspeech2_config["model"]) + + model.set_state_dict( + paddle.load(args.fastspeech2_checkpoint)["main_params"]) + model.eval() + + vocoder = PWGGenerator(**pwg_config["generator_params"]) + vocoder.set_state_dict(paddle.load(args.pwg_checkpoint)["generator_params"]) + vocoder.remove_weight_norm() + vocoder.eval() + print("model done!") + + frontend = English() + punc = "：，；。？！“”‘’':,;.?!" + print("frontend done!") + + stat = np.load(args.fastspeech2_stat) + mu, std = stat + mu = paddle.to_tensor(mu) + std = paddle.to_tensor(std) + fastspeech2_normalizer = ZScore(mu, std) + + stat = np.load(args.pwg_stat) + mu, std = stat + mu = paddle.to_tensor(mu) + std = paddle.to_tensor(std) + pwg_normalizer = ZScore(mu, std) + + fastspeech2_inference = FastSpeech2Inference(fastspeech2_normalizer, model) + pwg_inference = PWGInference(pwg_normalizer, vocoder) + + output_dir = Path(args.output_dir) + output_dir.mkdir(parents=True, exist_ok=True) + + for utt_id, sentence in sentences: + phones = frontend.phoneticize(sentence) + # remove start_symbol and end_symbol + phones = phones[1:-1] + phones = [phn for phn in phones if not phn.isspace()] + phones = [ + phn if (phn in phone_id_map and phn not in punc) else "sp" + for phn in phones + ] + phone_ids = [phone_id_map[phn] for phn in phones] + phone_ids = paddle.to_tensor(phone_ids) + + with paddle.no_grad(): + mel = fastspeech2_inference(phone_ids) + wav = pwg_inference(mel) + + sf.write( + str(output_dir / (utt_id + ".wav")), + wav.numpy(), + samplerate=fastspeech2_config.fs) + print(f"{utt_id} done!") + + +def main(): + # parse args and config and redirect to train_sp + parser = argparse.ArgumentParser( + description="Synthesize with fastspeech2 & parallel wavegan.") + parser.add_argument( + "--fastspeech2-config", type=str, help="fastspeech2 config file.") + parser.add_argument( + "--fastspeech2-checkpoint", + type=str, + help="fastspeech2 checkpoint to load.") + parser.add_argument( + "--fastspeech2-stat", + type=str, + help="mean and standard deviation used to normalize spectrogram when training fastspeech2." + ) + parser.add_argument( + "--pwg-config", type=str, help="parallel wavegan config file.") + parser.add_argument( + "--pwg-checkpoint", + type=str, + help="parallel wavegan generator parameters to load.") + parser.add_argument( + "--pwg-stat", + type=str, + help="mean and standard deviation used to normalize spectrogram when training parallel wavegan." + ) + parser.add_argument( + "--phones-dict", + type=str, + default="phone_id_map.txt", + help="phone vocabulary file.") + parser.add_argument( + "--text", + type=str, + help="text to synthesize, a 'utt_id sentence' pair per line.") + parser.add_argument("--output-dir", type=str, help="output dir.") + parser.add_argument( + "--device", type=str, default="gpu", help="device type to use.") + parser.add_argument("--verbose", type=int, default=1, help="verbose.") + + args = parser.parse_args() + + paddle.set_device(args.device) + + with open(args.fastspeech2_config) as f: + fastspeech2_config = CfgNode(yaml.safe_load(f)) + with open(args.pwg_config) as f: + pwg_config = CfgNode(yaml.safe_load(f)) + + print("========Args========") + print(yaml.safe_dump(vars(args))) + print("========Config========") + print(fastspeech2_config) + print(pwg_config) + + evaluate(args, fastspeech2_config, pwg_config) + + +if __name__ == "__main__": + main() diff --git a/examples/vctk/fastspeech2/ljspeech/synthesize_e2e.sh b/examples/vctk/fastspeech2/ljspeech/synthesize_e2e.sh new file mode 100755 index 00000000..158d4483 --- /dev/null +++ b/examples/vctk/fastspeech2/ljspeech/synthesize_e2e.sh @@ -0,0 +1,15 @@ + +#!/bin/bash +FLAGS_allocator_strategy=naive_best_fit \ +FLAGS_fraction_of_gpu_memory_to_use=0.01 \ +python3 synthesize_e2e.py \ + --fastspeech2-config=conf/default.yaml \ + --fastspeech2-checkpoint=exp/default/checkpoints/snapshot_iter_100000.pdz \ + --fastspeech2-stat=dump/train/speech_stats.npy \ + --pwg-config=pwg_ljspeech_ckpt_0.5/pwg_default.yaml \ + --pwg-checkpoint=pwg_ljspeech_ckpt_0.5/pwg_snapshot_iter_400000.pdz \ + --pwg-stat=pwg_ljspeech_ckpt_0.5/pwg_stats.npy \ + --text=../sentences_en.txt \ + --output-dir=exp/default/test_e2e \ + --device="gpu" \ + --phones-dict=dump/phone_id_map.txt diff --git a/examples/vctk/fastspeech2/normalize.py b/examples/vctk/fastspeech2/normalize.py new file mode 100644 index 00000000..2d40bdf3 --- /dev/null +++ b/examples/vctk/fastspeech2/normalize.py @@ -0,0 +1,180 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Normalize feature files and dump them.""" + +import argparse +import logging +from operator import itemgetter +from pathlib import Path + +import jsonlines +import numpy as np +from parakeet.datasets.data_table import DataTable +from sklearn.preprocessing import StandardScaler +from tqdm import tqdm + + +def main(): + """Run preprocessing process.""" + parser = argparse.ArgumentParser( + description="Normalize dumped raw features (See detail in parallel_wavegan/bin/normalize.py)." + ) + parser.add_argument( + "--metadata", + type=str, + required=True, + help="directory including feature files to be normalized. " + "you need to specify either *-scp or rootdir.") + + parser.add_argument( + "--dumpdir", + type=str, + required=True, + help="directory to dump normalized feature files.") + parser.add_argument( + "--speech-stats", + type=str, + required=True, + help="speech statistics file.") + parser.add_argument( + "--pitch-stats", type=str, required=True, help="pitch statistics file.") + parser.add_argument( + "--energy-stats", + type=str, + required=True, + help="energy statistics file.") + parser.add_argument( + "--phones-dict", type=str, default=None, help="phone vocabulary file.") + parser.add_argument( + "--speaker-dict", type=str, default=None, help="speaker id map file.") + parser.add_argument( + "--verbose", + type=int, + default=1, + help="logging level. higher is more logging. (default=1)") + args = parser.parse_args() + + # set logger + if args.verbose > 1: + logging.basicConfig( + level=logging.DEBUG, + format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s" + ) + elif args.verbose > 0: + logging.basicConfig( + level=logging.INFO, + format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s" + ) + else: + logging.basicConfig( + level=logging.WARN, + format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s" + ) + logging.warning('Skip DEBUG/INFO messages') + + dumpdir = Path(args.dumpdir).expanduser() + # use absolute path + dumpdir = dumpdir.resolve() + dumpdir.mkdir(parents=True, exist_ok=True) + + # get dataset + with jsonlines.open(args.metadata, 'r') as reader: + metadata = list(reader) + dataset = DataTable( + metadata, + converters={ + "speech": np.load, + "pitch": np.load, + "energy": np.load, + }) + logging.info(f"The number of files = {len(dataset)}.") + + # restore scaler + speech_scaler = StandardScaler() + speech_scaler.mean_ = np.load(args.speech_stats)[0] + speech_scaler.scale_ = np.load(args.speech_stats)[1] + speech_scaler.n_features_in_ = speech_scaler.mean_.shape[0] + + pitch_scaler = StandardScaler() + pitch_scaler.mean_ = np.load(args.pitch_stats)[0] + pitch_scaler.scale_ = np.load(args.pitch_stats)[1] + pitch_scaler.n_features_in_ = pitch_scaler.mean_.shape[0] + + energy_scaler = StandardScaler() + energy_scaler.mean_ = np.load(args.energy_stats)[0] + energy_scaler.scale_ = np.load(args.energy_stats)[1] + energy_scaler.n_features_in_ = energy_scaler.mean_.shape[0] + + vocab_phones = {} + with open(args.phones_dict, 'rt') as f: + phn_id = [line.strip().split() for line in f.readlines()] + for phn, id in phn_id: + vocab_phones[phn] = int(id) + + vocab_speaker = {} + with open(args.speaker_dict, 'rt') as f: + spk_id = [line.strip().split() for line in f.readlines()] + for spk, id in spk_id: + vocab_speaker[spk] = int(id) + + # process each file + output_metadata = [] + + for item in tqdm(dataset): + utt_id = item['utt_id'] + speech = item['speech'] + pitch = item['pitch'] + energy = item['energy'] + # normalize + speech = speech_scaler.transform(speech) + speech_dir = dumpdir / "data_speech" + speech_dir.mkdir(parents=True, exist_ok=True) + speech_path = speech_dir / f"{utt_id}_speech.npy" + np.save(speech_path, speech.astype(np.float32), allow_pickle=False) + + pitch = pitch_scaler.transform(pitch) + pitch_dir = dumpdir / "data_pitch" + pitch_dir.mkdir(parents=True, exist_ok=True) + pitch_path = pitch_dir / f"{utt_id}_pitch.npy" + np.save(pitch_path, pitch.astype(np.float32), allow_pickle=False) + + energy = energy_scaler.transform(energy) + energy_dir = dumpdir / "data_energy" + energy_dir.mkdir(parents=True, exist_ok=True) + energy_path = energy_dir / f"{utt_id}_energy.npy" + np.save(energy_path, energy.astype(np.float32), allow_pickle=False) + phone_ids = [vocab_phones[p] for p in item['phones']] + spk_id = vocab_speaker[item["speaker"]] + record = { + "utt_id": item['utt_id'], + "spk_id": spk_id, + "text": phone_ids, + "text_lengths": item['text_lengths'], + "speech_lengths": item['speech_lengths'], + "durations": item['durations'], + "speech": str(speech_path), + "pitch": str(pitch_path), + "energy": str(energy_path) + } + output_metadata.append(record) + output_metadata.sort(key=itemgetter('utt_id')) + output_metadata_path = Path(args.dumpdir) / "metadata.jsonl" + with jsonlines.open(output_metadata_path, 'w') as writer: + for item in output_metadata: + writer.write(item) + logging.info(f"metadata dumped into {output_metadata_path}") + + +if __name__ == "__main__": + main() diff --git a/examples/vctk/fastspeech2/preprocess.py b/examples/vctk/fastspeech2/preprocess.py new file mode 100644 index 00000000..ee2b3f91 --- /dev/null +++ b/examples/vctk/fastspeech2/preprocess.py @@ -0,0 +1,345 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +import os +from concurrent.futures import ThreadPoolExecutor +from operator import itemgetter +from pathlib import Path +from typing import Any +from typing import Dict +from typing import List + +import jsonlines +import librosa +import numpy as np +import tqdm +import yaml +from parakeet.data.get_feats import Energy +from parakeet.data.get_feats import LogMelFBank +from parakeet.data.get_feats import Pitch +from parakeet.datasets.preprocess_utils import compare_duration_and_mel_length +from parakeet.datasets.preprocess_utils import get_input_token +from parakeet.datasets.preprocess_utils import get_phn_dur +from parakeet.datasets.preprocess_utils import get_spk_id_map +from parakeet.datasets.preprocess_utils import merge_silence +from yacs.config import CfgNode + + +def process_sentence(config: Dict[str, Any], + fp: Path, + sentences: Dict, + output_dir: Path, + mel_extractor=None, + pitch_extractor=None, + energy_extractor=None, + cut_sil: bool=True): + utt_id = fp.stem + # for vctk + if utt_id.endswith("_mic2"): + utt_id = utt_id[:-5] + record = None + if utt_id in sentences: + # reading, resampling may occur + wav, _ = librosa.load(str(fp), sr=config.fs) + if len(wav.shape) != 1 or np.abs(wav).max() > 1.0: + return record + assert len(wav.shape) == 1, f"{utt_id} is not a mono-channel audio." + assert np.abs(wav).max( + ) <= 1.0, f"{utt_id} is seems to be different that 16 bit PCM." + phones = sentences[utt_id][0] + durations = sentences[utt_id][1] + speaker = sentences[utt_id][2] + d_cumsum = np.pad(np.array(durations).cumsum(0), (1, 0), 'constant') + # little imprecise than use *.TextGrid directly + times = librosa.frames_to_time( + d_cumsum, sr=config.fs, hop_length=config.n_shift) + if cut_sil: + start = 0 + end = d_cumsum[-1] + if phones[0] == "sil" and len(durations) > 1: + start = times[1] + durations = durations[1:] + phones = phones[1:] + if phones[-1] == 'sil' and len(durations) > 1: + end = times[-2] + durations = durations[:-1] + phones = phones[:-1] + sentences[utt_id][0] = phones + sentences[utt_id][1] = durations + start, end = librosa.time_to_samples([start, end], sr=config.fs) + wav = wav[start:end] + # extract mel feats + logmel = mel_extractor.get_log_mel_fbank(wav) + # change duration according to mel_length + compare_duration_and_mel_length(sentences, utt_id, logmel) + phones = sentences[utt_id][0] + durations = sentences[utt_id][1] + num_frames = logmel.shape[0] + assert sum(durations) == num_frames + mel_dir = output_dir / "data_speech" + mel_dir.mkdir(parents=True, exist_ok=True) + mel_path = mel_dir / (utt_id + "_speech.npy") + np.save(mel_path, logmel) + # extract pitch and energy + f0 = pitch_extractor.get_pitch(wav, duration=np.array(durations)) + assert f0.shape[0] == len(durations) + f0_dir = output_dir / "data_pitch" + f0_dir.mkdir(parents=True, exist_ok=True) + f0_path = f0_dir / (utt_id + "_pitch.npy") + np.save(f0_path, f0) + energy = energy_extractor.get_energy(wav, duration=np.array(durations)) + assert energy.shape[0] == len(durations) + energy_dir = output_dir / "data_energy" + energy_dir.mkdir(parents=True, exist_ok=True) + energy_path = energy_dir / (utt_id + "_energy.npy") + np.save(energy_path, energy) + record = { + "utt_id": utt_id, + "phones": phones, + "text_lengths": len(phones), + "speech_lengths": num_frames, + "durations": durations, + "speech": str(mel_path), + "pitch": str(f0_path), + "energy": str(energy_path), + "speaker": speaker + } + return record + + +def process_sentences(config, + fps: List[Path], + sentences: Dict, + output_dir: Path, + mel_extractor=None, + pitch_extractor=None, + energy_extractor=None, + nprocs: int=1, + cut_sil: bool=True): + if nprocs == 1: + results = [] + for fp in fps: + record = process_sentence(config, fp, sentences, output_dir, + mel_extractor, pitch_extractor, + energy_extractor, cut_sil) + if record: + results.append(record) + else: + with ThreadPoolExecutor(nprocs) as pool: + futures = [] + with tqdm.tqdm(total=len(fps)) as progress: + for fp in fps: + future = pool.submit(process_sentence, config, fp, + sentences, output_dir, mel_extractor, + pitch_extractor, energy_extractor, + cut_sil) + future.add_done_callback(lambda p: progress.update()) + futures.append(future) + + results = [] + for ft in futures: + record = ft.result() + if record: + results.append(record) + + results.sort(key=itemgetter("utt_id")) + with jsonlines.open(output_dir / "metadata.jsonl", 'w') as writer: + for item in results: + writer.write(item) + print("Done") + + +def main(): + # parse config and args + parser = argparse.ArgumentParser( + description="Preprocess audio and then extract features.") + + parser.add_argument( + "--dataset", + default="baker", + type=str, + help="name of dataset, should in {baker, aishell3, ljspeech, vctk} now") + + parser.add_argument( + "--rootdir", default=None, type=str, help="directory to dataset.") + + parser.add_argument( + "--dumpdir", + type=str, + required=True, + help="directory to dump feature files.") + parser.add_argument( + "--dur-file", default=None, type=str, help="path to durations.txt.") + + parser.add_argument("--config", type=str, help="fastspeech2 config file.") + + parser.add_argument( + "--verbose", + type=int, + default=1, + help="logging level. higher is more logging. (default=1)") + parser.add_argument( + "--num-cpu", type=int, default=1, help="number of process.") + + def str2bool(str): + return True if str.lower() == 'true' else False + + parser.add_argument( + "--cut-sil", + type=str2bool, + default=True, + help="whether cut sil in the edge of audio") + + args = parser.parse_args() + + rootdir = Path(args.rootdir).expanduser() + dumpdir = Path(args.dumpdir).expanduser() + # use absolute path + dumpdir = dumpdir.resolve() + dumpdir.mkdir(parents=True, exist_ok=True) + dur_file = Path(args.dur_file).expanduser() + + assert rootdir.is_dir() + assert dur_file.is_file() + + with open(args.config, 'rt') as f: + config = CfgNode(yaml.safe_load(f)) + + if args.verbose > 1: + print(vars(args)) + print(config) + + sentences, speaker_set = get_phn_dur(dur_file) + + merge_silence(sentences) + phone_id_map_path = dumpdir / "phone_id_map.txt" + speaker_id_map_path = dumpdir / "speaker_id_map.txt" + get_input_token(sentences, phone_id_map_path, args.dataset) + get_spk_id_map(speaker_set, speaker_id_map_path) + + if args.dataset == "baker": + wav_files = sorted(list((rootdir / "Wave").rglob("*.wav"))) + # split data into 3 sections + num_train = 9800 + num_dev = 100 + train_wav_files = wav_files[:num_train] + dev_wav_files = wav_files[num_train:num_train + num_dev] + test_wav_files = wav_files[num_train + num_dev:] + elif args.dataset == "aishell3": + sub_num_dev = 5 + wav_dir = rootdir / "train" / "wav" + train_wav_files = [] + dev_wav_files = [] + test_wav_files = [] + for speaker in os.listdir(wav_dir): + wav_files = sorted(list((wav_dir / speaker).rglob("*.wav"))) + if len(wav_files) > 100: + train_wav_files += wav_files[:-sub_num_dev * 2] + dev_wav_files += wav_files[-sub_num_dev * 2:-sub_num_dev] + test_wav_files += wav_files[-sub_num_dev:] + else: + train_wav_files += wav_files + elif args.dataset == "ljspeech": + wav_files = sorted(list((rootdir / "wavs").rglob("*.wav"))) + # split data into 3 sections + num_train = 12900 + num_dev = 100 + train_wav_files = wav_files[:num_train] + dev_wav_files = wav_files[num_train:num_train + num_dev] + test_wav_files = wav_files[num_train + num_dev:] + elif args.dataset == "vctk": + sub_num_dev = 5 + wav_dir = rootdir / "wav48_silence_trimmed" + train_wav_files = [] + dev_wav_files = [] + test_wav_files = [] + for speaker in os.listdir(wav_dir): + wav_files = sorted(list((wav_dir / speaker).rglob("*_mic2.flac"))) + if len(wav_files) > 100: + train_wav_files += wav_files[:-sub_num_dev * 2] + dev_wav_files += wav_files[-sub_num_dev * 2:-sub_num_dev] + test_wav_files += wav_files[-sub_num_dev:] + else: + train_wav_files += wav_files + + else: + print("dataset should in {baker, aishell3, ljspeech, vctk} now!") + + train_dump_dir = dumpdir / "train" / "raw" + train_dump_dir.mkdir(parents=True, exist_ok=True) + dev_dump_dir = dumpdir / "dev" / "raw" + dev_dump_dir.mkdir(parents=True, exist_ok=True) + test_dump_dir = dumpdir / "test" / "raw" + test_dump_dir.mkdir(parents=True, exist_ok=True) + + # Extractor + mel_extractor = LogMelFBank( + sr=config.fs, + n_fft=config.n_fft, + hop_length=config.n_shift, + win_length=config.win_length, + window=config.window, + n_mels=config.n_mels, + fmin=config.fmin, + fmax=config.fmax) + pitch_extractor = Pitch( + sr=config.fs, + hop_length=config.n_shift, + f0min=config.f0min, + f0max=config.f0max) + energy_extractor = Energy( + sr=config.fs, + n_fft=config.n_fft, + hop_length=config.n_shift, + win_length=config.win_length, + window=config.window) + + # process for the 3 sections + if train_wav_files: + process_sentences( + config, + train_wav_files, + sentences, + train_dump_dir, + mel_extractor, + pitch_extractor, + energy_extractor, + nprocs=args.num_cpu, + cut_sil=args.cut_sil) + if dev_wav_files: + process_sentences( + config, + dev_wav_files, + sentences, + dev_dump_dir, + mel_extractor, + pitch_extractor, + energy_extractor, + cut_sil=args.cut_sil) + if test_wav_files: + process_sentences( + config, + test_wav_files, + sentences, + test_dump_dir, + mel_extractor, + pitch_extractor, + energy_extractor, + nprocs=args.num_cpu, + cut_sil=args.cut_sil) + + +if __name__ == "__main__": + main() diff --git a/examples/vctk/fastspeech2/sentences.txt b/examples/vctk/fastspeech2/sentences.txt new file mode 100644 index 00000000..3aa5376b --- /dev/null +++ b/examples/vctk/fastspeech2/sentences.txt @@ -0,0 +1,16 @@ +001 凯莫瑞安联合体的经济崩溃，迫在眉睫。 +002 对于所有想要离开那片废土，去寻找更美好生活的人来说。 +003 克哈，是你们所有人安全的港湾。 +004 为了保护尤摩扬人民不受异虫的残害，我所做的，比他们自己的领导委员会都多。 +005 无论他们如何诽谤我，我将继续为所有泰伦人的最大利益，而努力奋斗。 +006 身为你们的元首，我带领泰伦人实现了人类统治领地和经济的扩张。 +007 我们将继续成长，用行动回击那些只会说风凉话，不愿意和我们相向而行的害群之马。 +008 帝国武装力量，无数的优秀儿女，正时刻守卫着我们的家园大门，但是他们孤木难支。 +009 凡是今天应征入伍者，所获的所有刑罚罪责，减半。 +010 激进分子和异见者希望你们一听见枪声，就背弃多年的和平与繁荣。 +011 他们没有勇气和能力，带领人类穿越一个充满危险的星系。 +012 法治是我们的命脉，然而它却受到前所未有的挑战。 +013 我将恢复我们帝国的荣光，绝不会向任何外星势力低头。 +014 我已经驯服了异虫，荡平了星灵。如今它们的创造者，想要夺走我们拥有的一切。 +015 永远记住，谁才是最能保护你们的人。 +016 不要听信别人的谗言，我不是什么克隆人。 \ No newline at end of file diff --git a/examples/vctk/fastspeech2/sentences_en.txt b/examples/vctk/fastspeech2/sentences_en.txt new file mode 100644 index 00000000..36b73a52 --- /dev/null +++ b/examples/vctk/fastspeech2/sentences_en.txt @@ -0,0 +1,9 @@ +001 Life was like a box of chocolates, you never know what you're gonna get. +002 With great power there must come great responsibility. +003 To be or not to be, that’s a question. +004 A man can be destroyed but not defeated +005 Do not, for one repulse, give up the purpose that you resolved to effort. +006 Death is just a part of life, something we're all destined to do. +007 I think it's hard winning a war with words. +008 Don’t argue with the people of strong determination, because they may change the fact! +009 Love you three thousand times. \ No newline at end of file diff --git a/examples/vctk/fastspeech2/synthesize.py b/examples/vctk/fastspeech2/synthesize.py new file mode 100644 index 00000000..c1329f8d --- /dev/null +++ b/examples/vctk/fastspeech2/synthesize.py @@ -0,0 +1,170 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +import logging +from pathlib import Path + +import jsonlines +import numpy as np +import paddle +import soundfile as sf +import yaml +from yacs.config import CfgNode +from parakeet.datasets.data_table import DataTable +from parakeet.models.fastspeech2 import FastSpeech2 +from parakeet.models.fastspeech2 import FastSpeech2Inference +from parakeet.models.parallel_wavegan import PWGGenerator +from parakeet.models.parallel_wavegan import PWGInference +from parakeet.modules.normalizer import ZScore + + +def evaluate(args, fastspeech2_config, pwg_config): + # dataloader has been too verbose + logging.getLogger("DataLoader").disabled = True + + # construct dataset for evaluation + with jsonlines.open(args.test_metadata, 'r') as reader: + test_metadata = list(reader) + + fields = ["utt_id", "text"] + + if args.speaker_dict is not None: + print("multiple speaker fastspeech2!") + with open(args.speaker_dict, 'rt') as f: + spk_id = [line.strip().split() for line in f.readlines()] + num_speakers = len(spk_id) + fields += ["spk_id"] + else: + print("single speaker fastspeech2!") + num_speakers = None + print("num_speakers:", num_speakers) + + test_dataset = DataTable(data=test_metadata, fields=fields) + + odim = fastspeech2_config.n_mels + with open(args.phones_dict, "r") as f: + phn_id = [line.strip().split() for line in f.readlines()] + vocab_size = len(phn_id) + print("vocab_size:", vocab_size) + + model = FastSpeech2( + idim=vocab_size, + odim=odim, + num_speakers=num_speakers, + **fastspeech2_config["model"]) + + model.set_state_dict( + paddle.load(args.fastspeech2_checkpoint)["main_params"]) + model.eval() + + vocoder = PWGGenerator(**pwg_config["generator_params"]) + vocoder.set_state_dict(paddle.load(args.pwg_checkpoint)["generator_params"]) + vocoder.remove_weight_norm() + vocoder.eval() + print("model done!") + + stat = np.load(args.fastspeech2_stat) + mu, std = stat + mu = paddle.to_tensor(mu) + std = paddle.to_tensor(std) + fastspeech2_normalizer = ZScore(mu, std) + + stat = np.load(args.pwg_stat) + mu, std = stat + mu = paddle.to_tensor(mu) + std = paddle.to_tensor(std) + pwg_normalizer = ZScore(mu, std) + + fastspeech2_inference = FastSpeech2Inference(fastspeech2_normalizer, model) + pwg_inference = PWGInference(pwg_normalizer, vocoder) + + output_dir = Path(args.output_dir) + output_dir.mkdir(parents=True, exist_ok=True) + + for datum in test_dataset: + utt_id = datum["utt_id"] + text = paddle.to_tensor(datum["text"]) + if "spk_id" in datum: + spk_id = paddle.to_tensor(datum["spk_id"]) + else: + spk_id = None + with paddle.no_grad(): + wav = pwg_inference(fastspeech2_inference(text, spk_id=spk_id)) + sf.write( + str(output_dir / (utt_id + ".wav")), + wav.numpy(), + samplerate=fastspeech2_config.fs) + print(f"{utt_id} done!") + + +def main(): + # parse args and config and redirect to train_sp + parser = argparse.ArgumentParser( + description="Synthesize with fastspeech2 & parallel wavegan.") + parser.add_argument( + "--fastspeech2-config", type=str, help="fastspeech2 config file.") + parser.add_argument( + "--fastspeech2-checkpoint", + type=str, + help="fastspeech2 checkpoint to load.") + parser.add_argument( + "--fastspeech2-stat", + type=str, + help="mean and standard deviation used to normalize spectrogram when training fastspeech2." + ) + parser.add_argument( + "--pwg-config", type=str, help="parallel wavegan config file.") + parser.add_argument( + "--pwg-checkpoint", + type=str, + help="parallel wavegan generator parameters to load.") + parser.add_argument( + "--pwg-stat", + type=str, + help="mean and standard deviation used to normalize spectrogram when training parallel wavegan." + ) + parser.add_argument( + "--phones-dict", type=str, default=None, help="phone vocabulary file.") + parser.add_argument( + "--speaker-dict", + type=str, + default=None, + help="speaker id map file for multiple speaker model.") + parser.add_argument("--test-metadata", type=str, help="test metadata.") + parser.add_argument("--output-dir", type=str, help="output dir.") + parser.add_argument( + "--device", type=str, default="gpu", help="device type to use.") + parser.add_argument("--verbose", type=int, default=1, help="verbose.") + + args = parser.parse_args() + + paddle.set_device(args.device) + + with open(args.fastspeech2_config) as f: + fastspeech2_config = CfgNode(yaml.safe_load(f)) + with open(args.pwg_config) as f: + pwg_config = CfgNode(yaml.safe_load(f)) + + print("========Args========") + print(yaml.safe_dump(vars(args))) + print("========Config========") + print(fastspeech2_config) + print(pwg_config) + + evaluate(args, fastspeech2_config, pwg_config) + + +if __name__ == "__main__": + main() diff --git a/examples/vctk/fastspeech2/train.py b/examples/vctk/fastspeech2/train.py new file mode 100644 index 00000000..1ea2c561 --- /dev/null +++ b/examples/vctk/fastspeech2/train.py @@ -0,0 +1,214 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +import logging +import os +import shutil + +import jsonlines +import numpy as np +import paddle +import yaml +from paddle import DataParallel +from paddle import distributed as dist +from paddle.io import DataLoader +from paddle.io import DistributedBatchSampler +from parakeet.datasets.data_table import DataTable +from parakeet.datasets.am_batch_fn import fastspeech2_single_spk_batch_fn +from parakeet.datasets.am_batch_fn import fastspeech2_multi_spk_batch_fn +from parakeet.models.fastspeech2 import FastSpeech2 +from parakeet.models.fastspeech2 import FastSpeech2Evaluator +from parakeet.models.fastspeech2 import FastSpeech2Updater +from parakeet.training.extensions.snapshot import Snapshot +from parakeet.training.extensions.visualizer import VisualDL +from parakeet.training.optimizer import build_optimizers +from parakeet.training.seeding import seed_everything +from parakeet.training.trainer import Trainer +from pathlib import Path +from visualdl import LogWriter +from yacs.config import CfgNode + + +def train_sp(args, config): + # decides device type and whether to run in parallel + # setup running environment correctly + if not paddle.is_compiled_with_cuda(): + paddle.set_device("cpu") + else: + paddle.set_device("gpu") + world_size = paddle.distributed.get_world_size() + if world_size > 1: + paddle.distributed.init_parallel_env() + + # set the random seed, it is a must for multiprocess training + seed_everything(config.seed) + + print( + f"rank: {dist.get_rank()}, pid: {os.getpid()}, parent_pid: {os.getppid()}", + ) + fields = [ + "text", "text_lengths", "speech", "speech_lengths", "durations", + "pitch", "energy" + ] + if args.speaker_dict is not None: + print("multiple speaker fastspeech2!") + collate_fn = fastspeech2_multi_spk_batch_fn + with open(args.speaker_dict, 'rt') as f: + spk_id = [line.strip().split() for line in f.readlines()] + num_speakers = len(spk_id) + fields += ["spk_id"] + else: + print("single speaker fastspeech2!") + collate_fn = fastspeech2_single_spk_batch_fn + num_speakers = None + print("num_speakers:", num_speakers) + + # dataloader has been too verbose + logging.getLogger("DataLoader").disabled = True + + # construct dataset for training and validation + with jsonlines.open(args.train_metadata, 'r') as reader: + train_metadata = list(reader) + train_dataset = DataTable( + data=train_metadata, + fields=fields, + converters={"speech": np.load, + "pitch": np.load, + "energy": np.load}, ) + with jsonlines.open(args.dev_metadata, 'r') as reader: + dev_metadata = list(reader) + dev_dataset = DataTable( + data=dev_metadata, + fields=fields, + converters={"speech": np.load, + "pitch": np.load, + "energy": np.load}, ) + + # collate function and dataloader + + train_sampler = DistributedBatchSampler( + train_dataset, + batch_size=config.batch_size, + shuffle=True, + drop_last=True) + + print("samplers done!") + + train_dataloader = DataLoader( + train_dataset, + batch_sampler=train_sampler, + collate_fn=collate_fn, + num_workers=config.num_workers) + + dev_dataloader = DataLoader( + dev_dataset, + shuffle=False, + drop_last=False, + batch_size=config.batch_size, + collate_fn=collate_fn, + num_workers=config.num_workers) + print("dataloaders done!") + + with open(args.phones_dict, "r") as f: + phn_id = [line.strip().split() for line in f.readlines()] + vocab_size = len(phn_id) + print("vocab_size:", vocab_size) + + odim = config.n_mels + model = FastSpeech2( + idim=vocab_size, + odim=odim, + num_speakers=num_speakers, + **config["model"]) + if world_size > 1: + model = DataParallel(model) + print("model done!") + + optimizer = build_optimizers(model, **config["optimizer"]) + print("optimizer done!") + + output_dir = Path(args.output_dir) + output_dir.mkdir(parents=True, exist_ok=True) + if dist.get_rank() == 0: + config_name = args.config.split("/")[-1] + # copy conf to output_dir + shutil.copyfile(args.config, output_dir / config_name) + + updater = FastSpeech2Updater( + model=model, + optimizer=optimizer, + dataloader=train_dataloader, + output_dir=output_dir, + **config["updater"]) + + trainer = Trainer(updater, (config.max_epoch, 'epoch'), output_dir) + + evaluator = FastSpeech2Evaluator( + model, dev_dataloader, output_dir=output_dir, **config["updater"]) + + if dist.get_rank() == 0: + trainer.extend(evaluator, trigger=(1, "epoch")) + writer = LogWriter(str(output_dir)) + trainer.extend(VisualDL(writer), trigger=(1, "iteration")) + trainer.extend( + Snapshot(max_size=config.num_snapshots), trigger=(1, 'epoch')) + # print(trainer.extensions) + trainer.run() + + +def main(): + # parse args and config and redirect to train_sp + parser = argparse.ArgumentParser(description="Train a FastSpeech2 model.") + parser.add_argument("--config", type=str, help="fastspeech2 config file.") + parser.add_argument("--train-metadata", type=str, help="training data.") + parser.add_argument("--dev-metadata", type=str, help="dev data.") + parser.add_argument("--output-dir", type=str, help="output dir.") + parser.add_argument( + "--device", type=str, default="gpu", help="device type to use.") + parser.add_argument( + "--nprocs", type=int, default=1, help="number of processes.") + parser.add_argument("--verbose", type=int, default=1, help="verbose.") + parser.add_argument( + "--phones-dict", type=str, default=None, help="phone vocabulary file.") + parser.add_argument( + "--speaker-dict", + type=str, + default=None, + help="speaker id map file for multiple speaker model.") + + args = parser.parse_args() + if args.device == "cpu" and args.nprocs > 1: + raise RuntimeError("Multiprocess training on CPU is not supported.") + + with open(args.config) as f: + config = CfgNode(yaml.safe_load(f)) + + print("========Args========") + print(yaml.safe_dump(vars(args))) + print("========Config========") + print(config) + print( + f"master see the word size: {dist.get_world_size()}, from pid: {os.getpid()}" + ) + + # dispatch + if args.nprocs > 1: + dist.spawn(train_sp, (args, config), nprocs=args.nprocs) + else: + train_sp(args, config) + + +if __name__ == "__main__": + main() diff --git a/examples/vctk/fastspeech2/vctk/README.md b/examples/vctk/fastspeech2/vctk/README.md new file mode 100644 index 00000000..8dc939d8 --- /dev/null +++ b/examples/vctk/fastspeech2/vctk/README.md @@ -0,0 +1,181 @@ +# FastSpeech2 with the VCTK +This example contains code used to train a [Fastspeech2](https://arxiv.org/abs/2006.04558) model with [VCTK](https://datashare.ed.ac.uk/handle/10283/3443). + +## Dataset +### Download and Extract the datasaet +Download VCTK-0.92 from the [official website](https://datashare.ed.ac.uk/handle/10283/3443). + +### Get MFA result of VCTK and Extract it +We use [MFA](https://github.com/MontrealCorpusTools/Montreal-Forced-Aligner) to get durations for fastspeech2. +You can download from here [vctk_alignment.tar.gz](https://paddlespeech.bj.bcebos.com/MFA/VCTK-Corpus-0.92/vctk_alignment.tar.gz), or train your own MFA model reference to [use_mfa example](https://github.com/PaddlePaddle/Parakeet/tree/develop/examples/use_mfa) of our repo. +ps: we remove three speakers in VCTK-0.92 (see [reorganize_vctk.py](https://github.com/PaddlePaddle/Parakeet/tree/develop/examples/use_mfa/local/reorganize_vctk.py)): +1. `p315`, because no txt for it. +2. `p280` and `p362`, because no *_mic2.flac (which is better than *_mic1.flac) for them. + +### Preprocess the dataset +Assume the path to the dataset is `~/datasets/VCTK-Corpus-0.92`. +Assume the path to the MFA result of VCTK is `./vctk_alignment`. +Run the command below to preprocess the dataset. + +```bash +./preprocess.sh +``` +When it is done. A `dump` folder is created in the current directory. The structure of the dump folder is listed below. + +```text +dump +├── dev +│ ├── norm +│ └── raw +├── phone_id_map.txt +├── speaker_id_map.txt +├── test +│ ├── norm +│ └── raw +└── train + ├── energy_stats.npy + ├── norm + ├── pitch_stats.npy + ├── raw + └── speech_stats.npy +``` +The dataset is split into 3 parts, namely `train`, `dev` and` test`, each of which contains a `norm` and `raw` sub folder. The raw folder contains speech、pitch and energy features of each utterances, while the norm folder contains normalized ones. The statistics used to normalize features are computed from the training set, which is located in `dump/train/*_stats.npy`. + +Also there is a `metadata.jsonl` in each subfolder. It is a table-like file which contains phones, text_lengths, speech_lengths, durations, path of speech features, path of pitch features, path of energy features, speaker and id of each utterance. + +## Train the model +`./run.sh` calls `../train.py`. +```bash +./run.sh +``` +Here's the complete help message. +```text +usage: train.py [-h] [--config CONFIG] [--train-metadata TRAIN_METADATA] + [--dev-metadata DEV_METADATA] [--output-dir OUTPUT_DIR] + [--device DEVICE] [--nprocs NPROCS] [--verbose VERBOSE] + [--phones-dict PHONES_DICT] [--speaker-dict SPEAKER_DICT] + +Train a FastSpeech2 model. + +optional arguments: + -h, --help show this help message and exit + --config CONFIG fastspeech2 config file. + --train-metadata TRAIN_METADATA + training data. + --dev-metadata DEV_METADATA + dev data. + --output-dir OUTPUT_DIR + output dir. + --device DEVICE device type to use. + --nprocs NPROCS number of processes. + --verbose VERBOSE verbose. + --phones-dict PHONES_DICT + phone vocabulary file. + --speaker-dict SPEAKER_DICT + speaker id map file for multiple speaker model. +``` +1. `--config` is a config file in yaml format to overwrite the default config, which can be found at `conf/default.yaml`. +2. `--train-metadata` and `--dev-metadata` should be the metadata file in the normalized subfolder of `train` and `dev` in the `dump` folder. +3. `--output-dir` is the directory to save the results of the experiment. Checkpoints are save in `checkpoints/` inside this directory. +4. `--device` is the type of the device to run the experiment, 'cpu' or 'gpu' are supported. +5. `--nprocs` is the number of processes to run in parallel, note that nprocs > 1 is only supported when `--device` is 'gpu'. +6. `--phones-dict` is the path of the phone vocabulary file. + +## Pretrained Model + +## Synthesize + +``` +`synthesize.sh` calls `../synthesize.py`, which can synthesize waveform from `metadata.jsonl`. +```bash +./synthesize.sh +``` +```text +usage: synthesize.py [-h] [--fastspeech2-config FASTSPEECH2_CONFIG] + [--fastspeech2-checkpoint FASTSPEECH2_CHECKPOINT] + [--fastspeech2-stat FASTSPEECH2_STAT] + [--pwg-config PWG_CONFIG] + [--pwg-checkpoint PWG_CHECKPOINT] [--pwg-stat PWG_STAT] + [--phones-dict PHONES_DICT] [--speaker-dict SPEAKER_DICT] + [--test-metadata TEST_METADATA] [--output-dir OUTPUT_DIR] + [--device DEVICE] [--verbose VERBOSE] + +Synthesize with fastspeech2 & parallel wavegan. + +optional arguments: + -h, --help show this help message and exit + --fastspeech2-config FASTSPEECH2_CONFIG + fastspeech2 config file. + --fastspeech2-checkpoint FASTSPEECH2_CHECKPOINT + fastspeech2 checkpoint to load. + --fastspeech2-stat FASTSPEECH2_STAT + mean and standard deviation used to normalize + spectrogram when training fastspeech2. + --pwg-config PWG_CONFIG + parallel wavegan config file. + --pwg-checkpoint PWG_CHECKPOINT + parallel wavegan generator parameters to load. + --pwg-stat PWG_STAT mean and standard deviation used to normalize + spectrogram when training parallel wavegan. + --phones-dict PHONES_DICT + phone vocabulary file. + --speaker-dict SPEAKER_DICT + speaker id map file for multiple speaker model. + --test-metadata TEST_METADATA + test metadata. + --output-dir OUTPUT_DIR + output dir. + --device DEVICE device type to use. + --verbose VERBOSE verbose. +``` +`synthesize_e2e.sh` calls `synthesize_e2e.py`, which can synthesize waveform from text file. +```bash +./synthesize_e2e.sh +``` +```text +usage: synthesize_e2e.py [-h] [--fastspeech2-config FASTSPEECH2_CONFIG] + [--fastspeech2-checkpoint FASTSPEECH2_CHECKPOINT] + [--fastspeech2-stat FASTSPEECH2_STAT] + [--pwg-config PWG_CONFIG] + [--pwg-checkpoint PWG_CHECKPOINT] + [--pwg-stat PWG_STAT] [--phones-dict PHONES_DICT] + [--text TEXT] [--output-dir OUTPUT_DIR] + [--device DEVICE] [--verbose VERBOSE] + +Synthesize with fastspeech2 & parallel wavegan. + +optional arguments: + -h, --help show this help message and exit + --fastspeech2-config FASTSPEECH2_CONFIG + fastspeech2 config file. + --fastspeech2-checkpoint FASTSPEECH2_CHECKPOINT + fastspeech2 checkpoint to load. + --fastspeech2-stat FASTSPEECH2_STAT + mean and standard deviation used to normalize + spectrogram when training fastspeech2. + --pwg-config PWG_CONFIG + parallel wavegan config file. + --pwg-checkpoint PWG_CHECKPOINT + parallel wavegan generator parameters to load. + --pwg-stat PWG_STAT mean and standard deviation used to normalize + spectrogram when training parallel wavegan. + --phones-dict PHONES_DICT + phone vocabulary file. + --text TEXT text to synthesize, a 'utt_id sentence' pair per line. + --output-dir OUTPUT_DIR + output dir. + --device DEVICE device type to use. + --verbose VERBOSE verbose. +``` + +1. `--fastspeech2-config`, `--fastspeech2-checkpoint`, `--fastspeech2-stat` and `--phones-dict` are arguments for fastspeech2, which correspond to the 4 files in the fastspeech2 pretrained model. +2. `--pwg-config`, `--pwg-checkpoint`, `--pwg-stat` are arguments for parallel wavegan, which correspond to the 3 files in the parallel wavegan pretrained model. +3. `--test-metadata` should be the metadata file in the normalized subfolder of `test` in the `dump` folder. +4. `--text` is the text file, which contains sentences to synthesize. +5. `--output-dir` is the directory to save synthesized audio files. +6. `--device is` the type of device to run synthesis, 'cpu' and 'gpu' are supported. 'gpu' is recommended for faster synthesis. + +You can use the following scripts to synthesize for `../sentences_en.txt` using pretrained fastspeech2 and parallel wavegan models. +```bash + +``` diff --git a/examples/vctk/fastspeech2/vctk/conf/default.yaml b/examples/vctk/fastspeech2/vctk/conf/default.yaml new file mode 100644 index 00000000..09bd3483 --- /dev/null +++ b/examples/vctk/fastspeech2/vctk/conf/default.yaml @@ -0,0 +1,105 @@ +########################################################### +# FEATURE EXTRACTION SETTING # +########################################################### + +fs: 24000 # sr +n_fft: 2048 # FFT size. +n_shift: 300 # Hop size. +win_length: 1200 # Window length. + # If set to null, it will be the same as fft_size. +window: "hann" # Window function. + +# Only used for feats_type != raw + +fmin: 80 # Minimum frequency of Mel basis. +fmax: 7600 # Maximum frequency of Mel basis. +n_mels: 80 # The number of mel basis. + +# Only used for the model using pitch features (e.g. FastSpeech2) +f0min: 80 # Maximum f0 for pitch extraction. +f0max: 400 # Minimum f0 for pitch extraction. + + +########################################################### +# DATA SETTING # +########################################################### +batch_size: 64 +num_workers: 4 + + +########################################################### +# MODEL SETTING # +########################################################### +model: + adim: 384 # attention dimension + aheads: 2 # number of attention heads + elayers: 4 # number of encoder layers + eunits: 1536 # number of encoder ff units + dlayers: 4 # number of decoder layers + dunits: 1536 # number of decoder ff units + positionwise_layer_type: conv1d # type of position-wise layer + positionwise_conv_kernel_size: 3 # kernel size of position wise conv layer + duration_predictor_layers: 2 # number of layers of duration predictor + duration_predictor_chans: 256 # number of channels of duration predictor + duration_predictor_kernel_size: 3 # filter size of duration predictor + postnet_layers: 5 # number of layers of postnset + postnet_filts: 5 # filter size of conv layers in postnet + postnet_chans: 256 # number of channels of conv layers in postnet + use_masking: True # whether to apply masking for padded part in loss calculation + use_scaled_pos_enc: True # whether to use scaled positional encoding + encoder_normalize_before: True # whether to perform layer normalization before the input + decoder_normalize_before: True # whether to perform layer normalization before the input + reduction_factor: 1 # reduction factor + init_type: xavier_uniform # initialization type + init_enc_alpha: 1.0 # initial value of alpha of encoder scaled position encoding + init_dec_alpha: 1.0 # initial value of alpha of decoder scaled position encoding + transformer_enc_dropout_rate: 0.2 # dropout rate for transformer encoder layer + transformer_enc_positional_dropout_rate: 0.2 # dropout rate for transformer encoder positional encoding + transformer_enc_attn_dropout_rate: 0.2 # dropout rate for transformer encoder attention layer + transformer_dec_dropout_rate: 0.2 # dropout rate for transformer decoder layer + transformer_dec_positional_dropout_rate: 0.2 # dropout rate for transformer decoder positional encoding + transformer_dec_attn_dropout_rate: 0.2 # dropout rate for transformer decoder attention layer + pitch_predictor_layers: 5 # number of conv layers in pitch predictor + pitch_predictor_chans: 256 # number of channels of conv layers in pitch predictor + pitch_predictor_kernel_size: 5 # kernel size of conv leyers in pitch predictor + pitch_predictor_dropout: 0.5 # dropout rate in pitch predictor + pitch_embed_kernel_size: 1 # kernel size of conv embedding layer for pitch + pitch_embed_dropout: 0.0 # dropout rate after conv embedding layer for pitch + stop_gradient_from_pitch_predictor: true # whether to stop the gradient from pitch predictor to encoder + energy_predictor_layers: 2 # number of conv layers in energy predictor + energy_predictor_chans: 256 # number of channels of conv layers in energy predictor + energy_predictor_kernel_size: 3 # kernel size of conv leyers in energy predictor + energy_predictor_dropout: 0.5 # dropout rate in energy predictor + energy_embed_kernel_size: 1 # kernel size of conv embedding layer for energy + energy_embed_dropout: 0.0 # dropout rate after conv embedding layer for energy + stop_gradient_from_energy_predictor: false # whether to stop the gradient from energy predictor to encoder + spk_embed_dim: 256 # speaker embedding dimension + spk_embed_integration_type: concat # speaker embedding integration type + + + +########################################################### +# UPDATER SETTING # +########################################################### +updater: + use_masking: True # whether to apply masking for padded part in loss calculation + + +########################################################### +# OPTIMIZER SETTING # +########################################################### +optimizer: + optim: adam # optimizer type + learning_rate: 0.001 # learning rate + +########################################################### +# TRAINING SETTING # +########################################################### +max_epoch: 200 +num_snapshots: 5 + + +########################################################### +# OTHER SETTING # +########################################################### +seed: 10086 diff --git a/examples/vctk/fastspeech2/vctk/preprocess.sh b/examples/vctk/fastspeech2/vctk/preprocess.sh new file mode 100755 index 00000000..df4b634a --- /dev/null +++ b/examples/vctk/fastspeech2/vctk/preprocess.sh @@ -0,0 +1,75 @@ +#!/bin/bash + +stage=1 +stop_stage=100 + +export MAIN_ROOT=`realpath ${PWD}/../../../` + +if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then + # get durations from MFA's result + echo "Generate durations.txt from MFA results ..." + python3 ${MAIN_ROOT}/utils/gen_duration_from_textgrid.py \ + --inputdir=./vctk_alignment \ + --output durations.txt \ + --config=conf/default.yaml +fi + +if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then + # extract features + echo "Extract features ..." + python3 ../preprocess.py \ + --dataset=vctk \ + --rootdir=~/datasets/VCTK-Corpus-0.92/ \ + --dumpdir=dump \ + --dur-file=durations.txt \ + --config=conf/default.yaml \ + --num-cpu=20 \ + --cut-sil=True +fi + +if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then + # get features' stats(mean and std) + echo "Get features' stats ..." + python3 ${MAIN_ROOT}/utils/compute_statistics.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --field-name="speech" + + python3 ${MAIN_ROOT}/utils/compute_statistics.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --field-name="pitch" + + python3 ${MAIN_ROOT}/utils/compute_statistics.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --field-name="energy" +fi + +if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then + # normalize and covert phone/speaker to id, dev and test should use train's stats + echo "Normalize ..." + python3 ../normalize.py \ + --metadata=dump/train/raw/metadata.jsonl \ + --dumpdir=dump/train/norm \ + --speech-stats=dump/train/speech_stats.npy \ + --pitch-stats=dump/train/pitch_stats.npy \ + --energy-stats=dump/train/energy_stats.npy \ + --phones-dict=dump/phone_id_map.txt \ + --speaker-dict=dump/speaker_id_map.txt + + python3 ../normalize.py \ + --metadata=dump/dev/raw/metadata.jsonl \ + --dumpdir=dump/dev/norm \ + --speech-stats=dump/train/speech_stats.npy \ + --pitch-stats=dump/train/pitch_stats.npy \ + --energy-stats=dump/train/energy_stats.npy \ + --phones-dict=dump/phone_id_map.txt \ + --speaker-dict=dump/speaker_id_map.txt + + python3 ../normalize.py \ + --metadata=dump/test/raw/metadata.jsonl \ + --dumpdir=dump/test/norm \ + --speech-stats=dump/train/speech_stats.npy \ + --pitch-stats=dump/train/pitch_stats.npy \ + --energy-stats=dump/train/energy_stats.npy \ + --phones-dict=dump/phone_id_map.txt \ + --speaker-dict=dump/speaker_id_map.txt +fi diff --git a/examples/vctk/fastspeech2/vctk/run.sh b/examples/vctk/fastspeech2/vctk/run.sh new file mode 100755 index 00000000..d4f06da9 --- /dev/null +++ b/examples/vctk/fastspeech2/vctk/run.sh @@ -0,0 +1,10 @@ +#!/bin/bash + +python3 ../train.py \ + --train-metadata=dump/train/norm/metadata.jsonl \ + --dev-metadata=dump/dev/norm/metadata.jsonl \ + --config=conf/default.yaml \ + --output-dir=exp/default \ + --nprocs=2 \ + --phones-dict=dump/phone_id_map.txt \ + --speaker-dict=dump/speaker_id_map.txt diff --git a/examples/vctk/fastspeech2/vctk/synthesize.sh b/examples/vctk/fastspeech2/vctk/synthesize.sh new file mode 100755 index 00000000..329fc9e1 --- /dev/null +++ b/examples/vctk/fastspeech2/vctk/synthesize.sh @@ -0,0 +1,15 @@ +#!/bin/bash +FLAGS_allocator_strategy=naive_best_fit \ +FLAGS_fraction_of_gpu_memory_to_use=0.01 \ +python3 ../synthesize.py \ + --fastspeech2-config=conf/default.yaml \ + --fastspeech2-checkpoint=exp/default/checkpoints/snapshot_iter_32769.pdz_bak\ + --fastspeech2-stat=dump/train/speech_stats.npy \ + --pwg-config=pwg_baker_ckpt_0.4/pwg_default.yaml \ + --pwg-checkpoint=pwg_baker_ckpt_0.4/pwg_snapshot_iter_400000.pdz \ + --pwg-stat=pwg_baker_ckpt_0.4/pwg_stats.npy \ + --test-metadata=dump/test/norm/metadata.jsonl \ + --output-dir=exp/default/test \ + --device="gpu" \ + --phones-dict=dump/phone_id_map.txt \ + --speaker-dict=dump/speaker_id_map.txt diff --git a/examples/vctk/fastspeech2/vctk/synthesize_e2e.py b/examples/vctk/fastspeech2/vctk/synthesize_e2e.py new file mode 100644 index 00000000..65a927b4 --- /dev/null +++ b/examples/vctk/fastspeech2/vctk/synthesize_e2e.py @@ -0,0 +1,179 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +import logging +from pathlib import Path + +import numpy as np +import paddle +import soundfile as sf +import yaml +from parakeet.frontend import English +from parakeet.models.fastspeech2 import FastSpeech2 +from parakeet.models.fastspeech2 import FastSpeech2Inference +from parakeet.models.parallel_wavegan import PWGGenerator +from parakeet.models.parallel_wavegan import PWGInference +from parakeet.modules.normalizer import ZScore +from yacs.config import CfgNode + + +def evaluate(args, fastspeech2_config, pwg_config): + # dataloader has been too verbose + logging.getLogger("DataLoader").disabled = True + + # construct dataset for evaluation + sentences = [] + with open(args.text, 'rt') as f: + for line in f: + line_list = line.strip().split() + utt_id = line_list[0] + sentence = " ".join(line_list[1:]) + sentences.append((utt_id, sentence)) + + with open(args.phones_dict, "r") as f: + phn_id = [line.strip().split() for line in f.readlines()] + vocab_size = len(phn_id) + phone_id_map = {} + for phn, id in phn_id: + phone_id_map[phn] = int(id) + print("vocab_size:", vocab_size) + with open(args.speaker_dict, 'rt') as f: + spk_id = [line.strip().split() for line in f.readlines()] + num_speakers = len(spk_id) + print("num_speakers:", num_speakers) + + odim = fastspeech2_config.n_mels + model = FastSpeech2( + idim=vocab_size, + odim=odim, + num_speakers=num_speakers, + **fastspeech2_config["model"]) + + model.set_state_dict( + paddle.load(args.fastspeech2_checkpoint)["main_params"]) + model.eval() + + vocoder = PWGGenerator(**pwg_config["generator_params"]) + vocoder.set_state_dict(paddle.load(args.pwg_checkpoint)["generator_params"]) + vocoder.remove_weight_norm() + vocoder.eval() + print("model done!") + + frontend = English() + punc = "：，；。？！“”‘’':,;.?!" + print("frontend done!") + + stat = np.load(args.fastspeech2_stat) + mu, std = stat + mu = paddle.to_tensor(mu) + std = paddle.to_tensor(std) + fastspeech2_normalizer = ZScore(mu, std) + + stat = np.load(args.pwg_stat) + mu, std = stat + mu = paddle.to_tensor(mu) + std = paddle.to_tensor(std) + pwg_normalizer = ZScore(mu, std) + + fastspeech2_inference = FastSpeech2Inference(fastspeech2_normalizer, model) + pwg_inference = PWGInference(pwg_normalizer, vocoder) + + output_dir = Path(args.output_dir) + output_dir.mkdir(parents=True, exist_ok=True) + # only test the number 0 speaker + spk_id = 0 + for utt_id, sentence in sentences: + phones = frontend.phoneticize(sentence) + # remove start_symbol and end_symbol + phones = phones[1:-1] + phones = [phn for phn in phones if not phn.isspace()] + phones = [ + phn if (phn in phone_id_map and phn not in punc) else "sp" + for phn in phones + ] + phone_ids = [phone_id_map[phn] for phn in phones] + phone_ids = paddle.to_tensor(phone_ids) + + with paddle.no_grad(): + mel = fastspeech2_inference( + phone_ids, spk_id=paddle.to_tensor(spk_id)) + wav = pwg_inference(mel) + + sf.write( + str(output_dir / (str(spk_id) + "_" + utt_id + ".wav")), + wav.numpy(), + samplerate=fastspeech2_config.fs) + print(f"{spk_id}_{utt_id} done!") + + +def main(): + # parse args and config and redirect to train_sp + parser = argparse.ArgumentParser( + description="Synthesize with fastspeech2 & parallel wavegan.") + parser.add_argument( + "--fastspeech2-config", type=str, help="fastspeech2 config file.") + parser.add_argument( + "--fastspeech2-checkpoint", + type=str, + help="fastspeech2 checkpoint to load.") + parser.add_argument( + "--fastspeech2-stat", + type=str, + help="mean and standard deviation used to normalize spectrogram when training fastspeech2." + ) + parser.add_argument( + "--pwg-config", type=str, help="parallel wavegan config file.") + parser.add_argument( + "--pwg-checkpoint", + type=str, + help="parallel wavegan generator parameters to load.") + parser.add_argument( + "--pwg-stat", + type=str, + help="mean and standard deviation used to normalize spectrogram when training parallel wavegan." + ) + parser.add_argument( + "--phones-dict", type=str, default=None, help="phone vocabulary file.") + parser.add_argument( + "--speaker-dict", type=str, default=None, help="speaker id map file.") + parser.add_argument( + "--text", + type=str, + help="text to synthesize, a 'utt_id sentence' pair per line.") + parser.add_argument("--output-dir", type=str, help="output dir.") + parser.add_argument( + "--device", type=str, default="gpu", help="device type to use.") + parser.add_argument("--verbose", type=int, default=1, help="verbose.") + + args = parser.parse_args() + + paddle.set_device(args.device) + + with open(args.fastspeech2_config) as f: + fastspeech2_config = CfgNode(yaml.safe_load(f)) + with open(args.pwg_config) as f: + pwg_config = CfgNode(yaml.safe_load(f)) + + print("========Args========") + print(yaml.safe_dump(vars(args))) + print("========Config========") + print(fastspeech2_config) + print(pwg_config) + + evaluate(args, fastspeech2_config, pwg_config) + + +if __name__ == "__main__": + main() diff --git a/examples/vctk/fastspeech2/vctk/synthesize_e2e.sh b/examples/vctk/fastspeech2/vctk/synthesize_e2e.sh new file mode 100755 index 00000000..446e3363 --- /dev/null +++ b/examples/vctk/fastspeech2/vctk/synthesize_e2e.sh @@ -0,0 +1,15 @@ +#!/bin/bash +FLAGS_allocator_strategy=naive_best_fit \ +FLAGS_fraction_of_gpu_memory_to_use=0.01 \ +python3 synthesize_e2e.py \ + --fastspeech2-config=conf/default.yaml \ + --fastspeech2-checkpoint=exp/default/checkpoints/snapshot_iter_32769.pdz_bak \ + --fastspeech2-stat=dump/train/speech_stats.npy \ + --pwg-config=pwg_baker_ckpt_0.4/pwg_default.yaml \ + --pwg-checkpoint=pwg_baker_ckpt_0.4/pwg_snapshot_iter_400000.pdz \ + --pwg-stat=pwg_baker_ckpt_0.4/pwg_stats.npy \ + --text=../sentences_en.txt \ + --output-dir=exp/default/test_e2e \ + --device="gpu" \ + --phones-dict=dump/phone_id_map.txt \ + --speaker-dict=dump/speaker_id_map.txt diff --git a/examples/voxceleb/README.md b/examples/voxceleb/README.md new file mode 100644 index 00000000..9512ac09 --- /dev/null +++ b/examples/voxceleb/README.md @@ -0,0 +1,3 @@ +# Voxceleb + +* spk0 - ge2e diff --git a/examples/voxceleb/spk0/local/ge2e/README.md b/examples/voxceleb/spk0/local/ge2e/README.md new file mode 100644 index 00000000..b05786a1 --- /dev/null +++ b/examples/voxceleb/spk0/local/ge2e/README.md @@ -0,0 +1,129 @@ +# Speaker Encoder + +This experiment trains a speaker encoder with speaker verification as its task. It is done as a part of the experiment of transfer learning from speaker verification to multispeaker text-to-speech synthesis, which can be found at [tacotron2_aishell3](../tacotron2_shell3). The trained speaker encoder is used to extract utterance embeddings from utterances. + +## Model + +The model used in this experiment is the speaker encoder with text independent speaker verification task in [GENERALIZED END-TO-END LOSS FOR SPEAKER VERIFICATION](https://arxiv.org/pdf/1710.10467.pdf). GE2E-softmax loss is used. + +## File Structure + +```text +ge2e +├── README.md +├── README_cn.md +├── audio_processor.py +├── config.py +├── dataset_processors.py +├── inference.py +├── preprocess.py +├── random_cycle.py +├── speaker_verification_dataset.py +└── train.py +``` + +## Download Datasets + +Currently supported datasets are Librispeech-other-500, VoxCeleb, VoxCeleb2,ai-datatang-200zh, magicdata, which can be downloaded from corresponding webpage. + +1. Librispeech/train-other-500 + + An English multispeaker dataset，[URL](https://www.openslr.org/resources/12/train-other-500.tar.gz)，only the `train-other-500` subset is used. + +2. VoxCeleb1 + + An English multispeaker dataset，[URL](https://www.robots.ox.ac.uk/~vgg/data/voxceleb/vox1.html) , Audio Files from Dev A to Dev D should be downloaded, combined and extracted. + +3. VoxCeleb2 + + An English multispeaker dataset，[URL](https://www.robots.ox.ac.uk/~vgg/data/voxceleb/vox1.html) , Audio Files from Dev A to Dev H should be downloaded, combined and extracted. + +4. Aidatatang-200zh + + A Mandarin Chinese multispeaker dataset ，[URL](https://www.openslr.org/62/) . + +5. magicdata + + A Mandarin Chinese multispeaker dataset ，[URL](https://www.openslr.org/68/) . + +If you want to use other datasets, you can also download and preprocess it as long as it meets the requirements described below. + +## Preprocess Datasets + +Multispeaker datasets are used as training data, though the transcriptions are not used. To enlarge the amount of data used for training, several multispeaker datasets are combined. The preporcessed datasets are organized in a file structure described below. The mel spectrogram of each utterance is save in `.npy` format. The dataset is 2-stratified (speaker-utterance). Since multiple datasets are combined, to avoid conflict in speaker id, dataset name is prepended to the speake ids. + +```text +dataset_root +├── dataset01_speaker01/ +│   ├── utterance01.npy +│   ├── utterance02.npy +│   └── utterance03.npy +├── dataset01_speaker02/ +│   ├── utterance01.npy +│   ├── utterance02.npy +│   └── utterance03.npy +├── dataset02_speaker01/ +│   ├── utterance01.npy +│   ├── utterance02.npy +│   └── utterance03.npy +└── dataset02_speaker02/ +    ├── utterance01.npy +    ├── utterance02.npy +    └── utterance03.npy +``` + +Run the command to preprocess datasets. + +```bash +python preprocess.py --datasets_root= --output_dir= --dataset_names= +``` + +Here `--datasets_root` is the directory that contains several extracted dataset; `--output_dir` is the directory to save the preprocessed dataset; `--dataset_names` is the dataset to preprocess. If there are multiple datasets in `--datasets_root` to preprocess, the names can be joined with comma. Currently supported dataset names are librispeech_other, voxceleb1, voxceleb2, aidatatang_200zh and magicdata. + +## Training + +When preprocessing is done, run the command below to train the mdoel. + +```bash +python train.py --data= --output= --device="gpu" --nprocs=1 +``` + +- `--data` is the path to the preprocessed dataset. +- `--output` is the directory to save results，usually a subdirectory of `runs`.It contains visualdl log files, text log files, config file and a `checkpoints` directory, which contains parameter file and optimizer state file. If `--output` already has some training results in it, the most recent parameter file and optimizer state file is loaded before training. +- `--device` is the device type to run the training, 'cpu' and 'gpu' are supported. +- `--nprocs` is the number of replicas to run in multiprocessing based parallel training。Currently multiprocessing based parallel training is only enabled when using 'gpu' as the devicde. `CUDA_VISIBLE_DEVICES` can be used to specify visible devices with cuda. + +Other options are described below. + +- `--config` is a `.yaml` config file used to override the default config(which is coded in `config.py`). +- `--opts` is command line options to further override config files. It should be the last comman line options passed with multiple key-value pairs separated by spaces. +- `--checkpoint_path` specifies the checkpoiont to load before training, extension is not included. A parameter file ( `.pdparams`) and an optimizer state file ( `.pdopt`) with the same name is used. This option has a higher priority than auto-resuming from the `--output` directory. + +## Pretrained Model + +The pretrained model is first trained to 1560k steps at Librispeech-other-500 and voxceleb1. Then trained at aidatatang_200h and magic_data to 3000k steps. + +Download URL [ge2e_ckpt_0.3.zip](https://paddlespeech.bj.bcebos.com/Parakeet/ge2e_ckpt_0.3.zip). + +## Inference + +When training is done, run the command below to generate utterance embedding for each utterance in a dataset. + +```bash +python inference.py --input= --output= --checkpoint_path= --device="gpu" +``` + +`--input` is the path of the dataset used for inference. + +`--output` is the directory to save the processed results. It has the same file structure as the input dataset. Each utterance in the dataset has a corrsponding utterance embedding file in `*.npy` format. + +`--checkpoint_path` is the path of the checkpoint to use, extension not included. + +`--pattern` is the wildcard pattern to filter audio files for inference, defaults to `*.wav`. + +`--device` and `--opts` have the same meaning as in the training script. + +## References + +1. [Generalized End-to-end Loss for Speaker Verification](https://arxiv.org/pdf/1710.10467.pdf) +2. [Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis](https://arxiv.org/pdf/1806.04558.pdf) diff --git a/examples/voxceleb/spk0/local/ge2e/README_cn.md b/examples/voxceleb/spk0/local/ge2e/README_cn.md new file mode 100644 index 00000000..7777e4dd --- /dev/null +++ b/examples/voxceleb/spk0/local/ge2e/README_cn.md @@ -0,0 +1,124 @@ +# Speaker Encoder + +本实验是的在多说话人数据集上以 Speaker Verification 为任务训练一个 speaker encoder, 这是作为 transfer learning from speaker verification to multispeaker text-to-speech synthesis 实验的一部分, 可以在 [tacotron2_aishell3](../tacotron2_aishell3) 中找到。用训练好的模型来提取音频的 utterance embedding. + +## 模型 + +本实验使用的模型是 [GENERALIZED END-TO-END LOSS FOR SPEAKER VERIFICATION](https://arxiv.org/pdf/1710.10467.pdf) 中的 speaker encoder text independent 模型。使用的是 GE2E softmax 损失函数。 + +## 目录结构 + +```text +ge2e +├── README_cn.md +├── audio_processor.py +├── config.py +├── dataset_processors.py +├── inference.py +├── preprocess.py +├── random_cycle.py +├── speaker_verification_dataset.py +└── train.py +``` + +## 数据集下载 + +本实验支持了 Librispeech-other-500, VoxCeleb, VoxCeleb2,ai-datatang-200zh, magicdata 数据集。可以在对应的页面下载。 + +1. Librispeech/train-other-500 + + 英文多说话人数据集，[下载链接](https://www.openslr.org/resources/12/train-other-500.tar.gz)，我们的实验中仅用到了 train-other-500 这个子集。 + +2. VoxCeleb1 + + 英文多说话人数据集，[下载链接](https://www.robots.ox.ac.uk/~vgg/data/voxceleb/vox1.html)，需要下载其中的 Audio Files 中的 Dev A 到 Dev D 四个压缩文件并合并解压。 + +3. VoxCeleb2 + + 英文多说话人数据集，[下载链接](https://www.robots.ox.ac.uk/~vgg/data/voxceleb/vox2.html)，需要下载其中的 Audio Files 中的 Dev A 到 Dev H 八个压缩文件并合并解压。 + +4. Aidatatang-200zh + + 中文多说话人数据集，[下载链接](https://www.openslr.org/62/)。 + +5. magicdata + + 中文多说话人数据集，[下载链接](https://www.openslr.org/68/)。 + +如果用户需要使用其他的数据集，也可以自行下载并进行数据处理，只要符合如下的要求。 + +## 数据集预处理 + +训练中使用的数据集是多说话人数据集，transcription 并不会被使用。为了扩大数据的量，训练过程可以将多个数据集合并为一个。处理后的文件结果组织方式如下，每个句子的频谱存储为 `.npy` 格式。以 speaker-utterance 的两层目录结构存储。因为合并数据集的原因，为了避免 speaker id 冲突，dataset 名会被添加到 speaker id 前面。 + +```text +dataset_root +├── dataset01_speaker01/ +│   ├── utterance01.npy +│   ├── utterance02.npy +│   └── utterance03.npy +├── dataset01_speaker02/ +│   ├── utterance01.npy +│   ├── utterance02.npy +│   └── utterance03.npy +├── dataset02_speaker01/ +│   ├── utterance01.npy +│   ├── utterance02.npy +│   └── utterance03.npy +└── dataset02_speaker02/ +    ├── utterance01.npy +    ├── utterance02.npy +    └── utterance03.npy +``` + +运行数据处理脚本 + +```bash +python preprocess.py --datasets_root= --output_dir= --dataset_names= +``` + +其中 datasets_root 是包含多个原始数据集的路径，--output_dir 是多个数据集合并后输出的路径，dataset_names 是数据集的名称，多个数据集可以用逗号分割，比如 'librispeech_other, voxceleb1'. 目前支持的数据集有 librispeech_other, voxceleb1, voxceleb2, aidatatang_200zh, magicdata. + +## 训练 + +数据处理完成后，使用如下的脚本训练。 + +```bash +python train.py --data= --output= --device="gpu" --nprocs=1 +``` + +- `--data` 是处理后的数据集路径。 +- `--output` 是训练结果的保存路径，一般使用 runs 下的一个子目录。保存结果包含 visualdl 的 log 文件，文本 log 记录，运行 config 备份，以及 checkpoints 目录，里面包含参数文件和优化器状态文件。如果指定的 output 路径包含此前的训练结果，训练前会自动加载最近的参数文件和优化器状态文件。 +- `--device` 是运行设备，目前支持 'cpu' 和 'gpu'. +- `--nprocs` 是指定运行进程数。目前仅在使用 'gpu' 是支持多进程训练。可以配合 `CUDA_VISIBLE_DEVICES` 环境变量指定可见卡号。 + +另外还有几个选项。 + +- `--config` 是用于覆盖默认配置（默认配置可以查看 `config.py`) 的配置文件，为 `.yaml` 文件。 +- `--opts` 是用命令行参数进一步覆盖配置。这是最后一个传入的命令行选项，用多组空格分隔的 KEY VALUE 对的方式传入。 +- `--checkpoint_path` 指定从中恢复的 checkpoint, 不需要包含扩展名。同名的参数文件( `.pdparams`) 和优化器文件( `.pdopt`)会被加载以恢复训练。这个参数指定的恢复训练优先级高于自动从 `output` 文件夹中恢复训练。 + +## 预训练模型 + +预训练模型是在 Librispeech-other-500 和 voxceleb1 上训练到 1560k steps 后用 aidatatang_200h 和 magic_data 训练到 3000k 的结果。 + +下载链接 [ge2e_ckpt_0.3.zip](https://paddlespeech.bj.bcebos.com/Parakeet/ge2e_ckpt_0.3.zip) + +## 预测 + +使用训练好的模型进行预测，对一个数据集中的所有 utterance 生成一个 embedding. + +```bash +python inference.py --input= --output= --checkpoint_path= --device="gpu" +``` + +- `--input` 是需要处理的数据集的路径。 +- `--output` 是处理的结果，它会保持和 `--input` 相同的文件夹结构，对应 input 中的每一个音频文件会有一个同名的 `*.npy` 文件，是从这个音频文件中提取到的 utterance embedding. +- `--checkpoint_path` 为用于预测的参数文件路径，不包含扩展名。 +- `--pattern` 是用于筛选数据集中需要处理的音频文件的通配符模式，默认为 `*.wav`. +- `--device` 和 `--opts` 的语义和训练脚本一致。 + +## 参考文献 + +1. [GENERALIZED END-TO-END LOSS FOR SPEAKER VERIFICATION](https://arxiv.org/pdf/1710.10467.pdf) +2. [Transfer Learning from Speaker Verification toMultispeaker Text-To-Speech Synthesis](https://arxiv.org/pdf/1806.04558.pdf) diff --git a/examples/voxceleb/spk0/local/ge2e/audio_processor.py b/examples/voxceleb/spk0/local/ge2e/audio_processor.py new file mode 100644 index 00000000..921e9990 --- /dev/null +++ b/examples/voxceleb/spk0/local/ge2e/audio_processor.py @@ -0,0 +1,246 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from pathlib import Path +from warnings import warn +import struct + +from scipy.ndimage.morphology import binary_dilation +import numpy as np +import librosa + +try: + import webrtcvad +except ModuleNotFoundError: + warn("Unable to import 'webrtcvad'." + "This package enables noise removal and is recommended.") + webrtcvad = None + +INT16_MAX = (2**15) - 1 + + +def normalize_volume(wav, target_dBFS, increase_only=False, + decrease_only=False): + # this function implements Loudness normalization, instead of peak + # normalization, See https://en.wikipedia.org/wiki/Audio_normalization + # dBFS: Decibels relative to full scale + # See https://en.wikipedia.org/wiki/DBFS for more details + # for 16Bit PCM audio, minimal level is -96dB + # compute the mean dBFS and adjust to target dBFS, with by increasing + # or decreasing + if increase_only and decrease_only: + raise ValueError("Both increase only and decrease only are set") + dBFS_change = target_dBFS - 10 * np.log10(np.mean(wav**2)) + if dBFS_change < 0 and increase_only: + return wav + if dBFS_change > 0 and decrease_only: + return wav + gain = 10**(dBFS_change / 20) + return wav * gain + + +def trim_long_silences(wav, + vad_window_length: int, + vad_moving_average_width: int, + vad_max_silence_length: int, + sampling_rate: int): + """ + Ensures that segments without voice in the waveform remain no longer than a + threshold determined by the VAD parameters in params.py. + Parameters + ---------- + wav : np.array + the raw waveform as a numpy array of floats + Returns + ---------- + np.array + the same waveform with silences trimmed away (length <= original wav length) + """ + # Compute the voice detection window size + samples_per_window = (vad_window_length * sampling_rate) // 1000 + + # Trim the end of the audio to have a multiple of the window size + wav = wav[:len(wav) - (len(wav) % samples_per_window)] + + # Convert the float waveform to 16-bit mono PCM + pcm_wave = struct.pack("%dh" % len(wav), + *(np.round(wav * INT16_MAX)).astype(np.int16)) + + # Perform voice activation detection + voice_flags = [] + vad = webrtcvad.Vad(mode=3) + for window_start in range(0, len(wav), samples_per_window): + window_end = window_start + samples_per_window + voice_flags.append( + vad.is_speech( + pcm_wave[window_start * 2:window_end * 2], + sample_rate=sampling_rate)) + voice_flags = np.array(voice_flags) + + # Smooth the voice detection with a moving average + def moving_average(array, width): + array_padded = np.concatenate((np.zeros((width - 1) // 2), array, + np.zeros(width // 2))) + ret = np.cumsum(array_padded, dtype=float) + ret[width:] = ret[width:] - ret[:-width] + return ret[width - 1:] / width + + audio_mask = moving_average(voice_flags, vad_moving_average_width) + audio_mask = np.round(audio_mask).astype(np.bool) + + # Dilate the voiced regions + audio_mask = binary_dilation(audio_mask, + np.ones(vad_max_silence_length + 1)) + audio_mask = np.repeat(audio_mask, samples_per_window) + + return wav[audio_mask] + + +def compute_partial_slices(n_samples: int, + partial_utterance_n_frames: int, + hop_length: int, + min_pad_coverage: float=0.75, + overlap: float=0.5): + """ + Computes where to split an utterance waveform and its corresponding mel spectrogram to obtain + partial utterances of each. Both the waveform and the mel + spectrogram slices are returned, so as to make each partial utterance waveform correspond to + its spectrogram. This function assumes that the mel spectrogram parameters used are those + defined in params_data.py. + + The returned ranges may be indexing further than the length of the waveform. It is + recommended that you pad the waveform with zeros up to wave_slices[-1].stop. + Parameters + ---------- + n_samples : int + the number of samples in the waveform. + partial_utterance_n_frames : int + the number of mel spectrogram frames in each partial utterance. + + min_pad_coverage : int + when reaching the last partial utterance, it may or may not have enough frames. + If at least of are present, + then the last partial utterance will be considered, as if we padded the audio. Otherwise, + it will be discarded, as if we trimmed the audio. If there aren't enough frames for 1 partial + utterance, this parameter is ignored so that the function always returns at least 1 slice. + overlap : float + by how much the partial utterance should overlap. If set to 0, the partial utterances are entirely disjoint. + Returns + ---------- + the waveform slices and mel spectrogram slices as lists of array slices. + Index respectively the waveform and the mel spectrogram with these slices to obtain the partialutterances. + """ + assert 0 <= overlap < 1 + assert 0 < min_pad_coverage <= 1 + + # librosa's function to compute num_frames from num_samples + n_frames = int(np.ceil((n_samples + 1) / hop_length)) + # frame shift between ajacent partials + frame_step = max(1, + int(np.round(partial_utterance_n_frames * (1 - overlap)))) + + # Compute the slices + wav_slices, mel_slices = [], [] + steps = max(1, n_frames - partial_utterance_n_frames + frame_step + 1) + for i in range(0, steps, frame_step): + mel_range = np.array([i, i + partial_utterance_n_frames]) + wav_range = mel_range * hop_length + mel_slices.append(slice(*mel_range)) + wav_slices.append(slice(*wav_range)) + + # Evaluate whether extra padding is warranted or not + last_wav_range = wav_slices[-1] + coverage = (n_samples - last_wav_range.start) / ( + last_wav_range.stop - last_wav_range.start) + if coverage < min_pad_coverage and len(mel_slices) > 1: + mel_slices = mel_slices[:-1] + wav_slices = wav_slices[:-1] + + return wav_slices, mel_slices + + +class SpeakerVerificationPreprocessor(object): + def __init__(self, + sampling_rate: int, + audio_norm_target_dBFS: float, + vad_window_length, + vad_moving_average_width, + vad_max_silence_length, + mel_window_length, + mel_window_step, + n_mels, + partial_n_frames: int, + min_pad_coverage: float=0.75, + partial_overlap_ratio: float=0.5): + self.sampling_rate = sampling_rate + self.audio_norm_target_dBFS = audio_norm_target_dBFS + + self.vad_window_length = vad_window_length + self.vad_moving_average_width = vad_moving_average_width + self.vad_max_silence_length = vad_max_silence_length + + self.n_fft = int(mel_window_length * sampling_rate / 1000) + self.hop_length = int(mel_window_step * sampling_rate / 1000) + self.n_mels = n_mels + + self.partial_n_frames = partial_n_frames + self.min_pad_coverage = min_pad_coverage + self.partial_overlap_ratio = partial_overlap_ratio + + def preprocess_wav(self, fpath_or_wav, source_sr=None): + # Load the wav from disk if needed + if isinstance(fpath_or_wav, (str, Path)): + wav, source_sr = librosa.load(str(fpath_or_wav), sr=None) + else: + wav = fpath_or_wav + + # Resample if numpy.array is passed and sr does not match + if source_sr is not None and source_sr != self.sampling_rate: + wav = librosa.resample(wav, source_sr, self.sampling_rate) + + # loudness normalization + wav = normalize_volume( + wav, self.audio_norm_target_dBFS, increase_only=True) + + # trim long silence + if webrtcvad: + wav = trim_long_silences( + wav, self.vad_window_length, self.vad_moving_average_width, + self.vad_max_silence_length, self.sampling_rate) + return wav + + def melspectrogram(self, wav): + mel = librosa.feature.melspectrogram( + wav, + sr=self.sampling_rate, + n_fft=self.n_fft, + hop_length=self.hop_length, + n_mels=self.n_mels) + mel = mel.astype(np.float32).T + return mel + + def extract_mel_partials(self, wav): + wav_slices, mel_slices = compute_partial_slices( + len(wav), self.partial_n_frames, self.hop_length, + self.min_pad_coverage, self.partial_overlap_ratio) + + # pad audio if needed + max_wave_length = wav_slices[-1].stop + if max_wave_length >= len(wav): + wav = np.pad(wav, (0, max_wave_length - len(wav)), "constant") + + # Split the utterance into partials + frames = self.melspectrogram(wav) + frames_batch = np.array([frames[s] for s in mel_slices]) + return frames_batch # [B, T, C] diff --git a/examples/voxceleb/spk0/local/ge2e/config.py b/examples/voxceleb/spk0/local/ge2e/config.py new file mode 100644 index 00000000..b8d748aa --- /dev/null +++ b/examples/voxceleb/spk0/local/ge2e/config.py @@ -0,0 +1,62 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from yacs.config import CfgNode + +_C = CfgNode() + +data_config = _C.data = CfgNode() + +## Audio volume normalization +data_config.audio_norm_target_dBFS = -30 + +## Audio sample rate +data_config.sampling_rate = 16000 # Hz + +## Voice Activation Detection +# Window size of the VAD. Must be either 10, 20 or 30 milliseconds. +# This sets the granularity of the VAD. Should not need to be changed. +data_config.vad_window_length = 30 # In milliseconds +# Number of frames to average together when performing the moving average smoothing. +# The larger this value, the larger the VAD variations must be to not get smoothed out. +data_config.vad_moving_average_width = 8 +# Maximum number of consecutive silent frames a segment can have. +data_config.vad_max_silence_length = 6 + +## Mel-filterbank +data_config.mel_window_length = 25 # In milliseconds +data_config.mel_window_step = 10 # In milliseconds +data_config.n_mels = 40 # mel bands + +# Number of spectrogram frames in a partial utterance +data_config.partial_n_frames = 160 # 1600 ms +data_config.min_pad_coverage = 0.75 # at least 75% of the audio is valid in a partial +data_config.partial_overlap_ratio = 0.5 # overlap ratio between ajancent partials + +model_config = _C.model = CfgNode() +model_config.num_layers = 3 +model_config.hidden_size = 256 +model_config.embedding_size = 256 # output size + +training_config = _C.training = CfgNode() +training_config.learning_rate_init = 1e-4 +training_config.speakers_per_batch = 64 +training_config.utterances_per_speaker = 10 +training_config.max_iteration = 1560000 +training_config.save_interval = 10000 +training_config.valid_interval = 10000 + + +def get_cfg_defaults(): + return _C.clone() diff --git a/examples/voxceleb/spk0/local/ge2e/dataset_processors.py b/examples/voxceleb/spk0/local/ge2e/dataset_processors.py new file mode 100644 index 00000000..50a8f3e7 --- /dev/null +++ b/examples/voxceleb/spk0/local/ge2e/dataset_processors.py @@ -0,0 +1,174 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from functools import partial +from typing import List +from pathlib import Path +import multiprocessing as mp + +import numpy as np +from tqdm import tqdm + +from audio_processor import SpeakerVerificationPreprocessor + + +def _process_utterance(path_pair, processor: SpeakerVerificationPreprocessor): + # Load and preprocess the waveform + input_path, output_path = path_pair + wav = processor.preprocess_wav(input_path) + if len(wav) == 0: + return + + # Create the mel spectrogram, discard those that are too short + frames = processor.melspectrogram(wav) + if len(frames) < processor.partial_n_frames: + return + + np.save(output_path, frames) + + +def _process_speaker(speaker_dir: Path, + processor: SpeakerVerificationPreprocessor, + datasets_root: Path, + output_dir: Path, + pattern: str, + skip_existing: bool=False): + # datastes root: a reference path to compute speaker_name + # we prepand dataset name to speaker_id becase we are mixing serveal + # multispeaker datasets together + speaker_name = "_".join(speaker_dir.relative_to(datasets_root).parts) + speaker_output_dir = output_dir / speaker_name + speaker_output_dir.mkdir(parents=True, exist_ok=True) + + # load exsiting file set + sources_fpath = speaker_output_dir / "_sources.txt" + if sources_fpath.exists(): + try: + with sources_fpath.open("rt") as sources_file: + existing_names = {line.split(",")[0] for line in sources_file} + except Exception as e: + existing_names = {} + else: + existing_names = {} + + sources_file = sources_fpath.open("at" if skip_existing else "wt") + for in_fpath in speaker_dir.rglob(pattern): + out_name = "_".join( + in_fpath.relative_to(speaker_dir).with_suffix(".npy").parts) + if skip_existing and out_name in existing_names: + continue + out_fpath = speaker_output_dir / out_name + _process_utterance((in_fpath, out_fpath), processor) + sources_file.write(f"{out_name},{in_fpath}\n") + + sources_file.close() + + +def _process_dataset(processor: SpeakerVerificationPreprocessor, + datasets_root: Path, + speaker_dirs: List[Path], + dataset_name: str, + output_dir: Path, + pattern: str, + skip_existing: bool=False): + print( + f"{dataset_name}: Preprocessing data for {len(speaker_dirs)} speakers.") + + _func = partial( + _process_speaker, + processor=processor, + datasets_root=datasets_root, + output_dir=output_dir, + pattern=pattern, + skip_existing=skip_existing) + + with mp.Pool(16) as pool: + list( + tqdm( + pool.imap(_func, speaker_dirs), + dataset_name, + len(speaker_dirs), + unit="speakers")) + print(f"Done preprocessing {dataset_name}.") + + +def process_librispeech(processor, + datasets_root, + output_dir, + skip_existing=False): + dataset_name = "LibriSpeech/train-other-500" + dataset_root = datasets_root / dataset_name + speaker_dirs = list(dataset_root.glob("*")) + _process_dataset(processor, datasets_root, speaker_dirs, dataset_name, + output_dir, "*.flac", skip_existing) + + +def process_voxceleb1(processor, datasets_root, output_dir, + skip_existing=False): + dataset_name = "VoxCeleb1" + dataset_root = datasets_root / dataset_name + + anglophone_nationalites = ["australia", "canada", "ireland", "uk", "usa"] + with dataset_root.joinpath("vox1_meta.csv").open("rt") as metafile: + metadata = [line.strip().split("\t") for line in metafile][1:] + + # speaker id -> nationality + nationalities = {line[0]: line[3] for line in metadata if line[-1] == "dev"} + keep_speaker_ids = [ + speaker_id for speaker_id, nationality in nationalities.items() + if nationality.lower() in anglophone_nationalites + ] + print( + "VoxCeleb1: using samples from {} (presumed anglophone) speakers out of {}." + .format(len(keep_speaker_ids), len(nationalities))) + + speaker_dirs = list((dataset_root / "wav").glob("*")) + speaker_dirs = [ + speaker_dir for speaker_dir in speaker_dirs + if speaker_dir.name in keep_speaker_ids + ] + _process_dataset(processor, datasets_root, speaker_dirs, dataset_name, + output_dir, "*.wav", skip_existing) + + +def process_voxceleb2(processor, datasets_root, output_dir, + skip_existing=False): + dataset_name = "VoxCeleb2" + dataset_root = datasets_root / dataset_name + # There is no nationality in meta data for VoxCeleb2 + speaker_dirs = list((dataset_root / "wav").glob("*")) + _process_dataset(processor, datasets_root, speaker_dirs, dataset_name, + output_dir, "*.wav", skip_existing) + + +def process_aidatatang_200zh(processor, + datasets_root, + output_dir, + skip_existing=False): + dataset_name = "aidatatang_200zh/train" + dataset_root = datasets_root / dataset_name + + speaker_dirs = list((dataset_root).glob("*")) + _process_dataset(processor, datasets_root, speaker_dirs, dataset_name, + output_dir, "*.wav", skip_existing) + + +def process_magicdata(processor, datasets_root, output_dir, + skip_existing=False): + dataset_name = "magicdata/train" + dataset_root = datasets_root / dataset_name + + speaker_dirs = list((dataset_root).glob("*")) + _process_dataset(processor, datasets_root, speaker_dirs, dataset_name, + output_dir, "*.wav", skip_existing) diff --git a/examples/voxceleb/spk0/local/ge2e/inference.py b/examples/voxceleb/spk0/local/ge2e/inference.py new file mode 100644 index 00000000..1cca132d --- /dev/null +++ b/examples/voxceleb/spk0/local/ge2e/inference.py @@ -0,0 +1,140 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +from pathlib import Path + +import tqdm +import paddle +import numpy as np + +from parakeet.models.lstm_speaker_encoder import LSTMSpeakerEncoder + +from audio_processor import SpeakerVerificationPreprocessor +from config import get_cfg_defaults + + +def embed_utterance(processor, model, fpath_or_wav): + # audio processor + wav = processor.preprocess_wav(fpath_or_wav) + mel_partials = processor.extract_mel_partials(wav) + + model.eval() + # speaker encoder + with paddle.no_grad(): + mel_partials = paddle.to_tensor(mel_partials) + with paddle.no_grad(): + embed = model.embed_utterance(mel_partials) + embed = embed.numpy() + return embed + + +def _process_utterance(ifpath: Path, + input_dir: Path, + output_dir: Path, + processor: SpeakerVerificationPreprocessor, + model: LSTMSpeakerEncoder): + rel_path = ifpath.relative_to(input_dir) + ofpath = (output_dir / rel_path).with_suffix(".npy") + ofpath.parent.mkdir(parents=True, exist_ok=True) + embed = embed_utterance(processor, model, ifpath) + np.save(ofpath, embed) + + +def main(config, args): + paddle.set_device(args.device) + + # load model + model = LSTMSpeakerEncoder(config.data.n_mels, config.model.num_layers, + config.model.hidden_size, + config.model.embedding_size) + weights_fpath = str(Path(args.checkpoint_path).expanduser()) + model_state_dict = paddle.load(weights_fpath + ".pdparams") + model.set_state_dict(model_state_dict) + model.eval() + print(f"Loaded encoder {weights_fpath}") + + # create audio processor + c = config.data + processor = SpeakerVerificationPreprocessor( + sampling_rate=c.sampling_rate, + audio_norm_target_dBFS=c.audio_norm_target_dBFS, + vad_window_length=c.vad_window_length, + vad_moving_average_width=c.vad_moving_average_width, + vad_max_silence_length=c.vad_max_silence_length, + mel_window_length=c.mel_window_length, + mel_window_step=c.mel_window_step, + n_mels=c.n_mels, + partial_n_frames=c.partial_n_frames, + min_pad_coverage=c.min_pad_coverage, + partial_overlap_ratio=c.min_pad_coverage, ) + + # input output preparation + input_dir = Path(args.input).expanduser() + ifpaths = list(input_dir.rglob(args.pattern)) + print(f"{len(ifpaths)} utterances in total") + output_dir = Path(args.output).expanduser() + output_dir.mkdir(parents=True, exist_ok=True) + + for ifpath in tqdm.tqdm(ifpaths, unit="utterance"): + _process_utterance(ifpath, input_dir, output_dir, processor, model) + + +if __name__ == "__main__": + config = get_cfg_defaults() + parser = argparse.ArgumentParser(description="compute utterance embed.") + parser.add_argument( + "--config", + metavar="FILE", + help="path of the config file to overwrite to default config with.") + parser.add_argument( + "--input", type=str, help="path of the audio_file folder.") + parser.add_argument( + "--pattern", + type=str, + default="*.wav", + help="pattern to filter audio files.") + parser.add_argument( + "--output", + metavar="OUTPUT_DIR", + help="path to save checkpoint and logs.") + + # load from saved checkpoint + parser.add_argument( + "--checkpoint_path", type=str, help="path of the checkpoint to load") + + # running + parser.add_argument( + "--device", + type=str, + choices=["cpu", "gpu"], + help="device type to use, cpu and gpu are supported.") + + # overwrite extra config and default config + parser.add_argument( + "--opts", + nargs=argparse.REMAINDER, + help="options to overwrite --config file and the default config, passing in KEY VALUE pairs" + ) + + args = parser.parse_args() + if args.config: + config.merge_from_file(args.config) + if args.opts: + config.merge_from_list(args.opts) + config.freeze() + print(config) + print(args) + + main(config, args) diff --git a/examples/voxceleb/spk0/local/ge2e/preprocess.py b/examples/voxceleb/spk0/local/ge2e/preprocess.py new file mode 100644 index 00000000..b1e59460 --- /dev/null +++ b/examples/voxceleb/spk0/local/ge2e/preprocess.py @@ -0,0 +1,101 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import argparse +from pathlib import Path +from config import get_cfg_defaults +from audio_processor import SpeakerVerificationPreprocessor +from dataset_processors import (process_librispeech, process_voxceleb1, + process_voxceleb2, process_aidatatang_200zh, + process_magicdata) + +if __name__ == "__main__": + parser = argparse.ArgumentParser( + description="preprocess dataset for speaker verification task") + parser.add_argument( + "--datasets_root", + type=Path, + help="Path to the directory containing your LibriSpeech, LibriTTS and VoxCeleb datasets." + ) + parser.add_argument( + "--output_dir", type=Path, help="Path to save processed dataset.") + parser.add_argument( + "--dataset_names", + type=str, + default="librispeech_other,voxceleb1,voxceleb2", + help="comma-separated list of names of the datasets you want to preprocess. only " + "the train set of these datastes will be used. Possible names: librispeech_other, " + "voxceleb1, voxceleb2, aidatatang_200zh, magicdata.") + parser.add_argument( + "--skip_existing", + action="store_true", + help="Whether to skip ouput files with the same name. Useful if this script was interrupted." + ) + parser.add_argument( + "--no_trim", + action="store_true", + help="Preprocess audio without trimming silences (not recommended).") + + args = parser.parse_args() + + if not args.no_trim: + try: + import webrtcvad + print(webrtcvad.__version__) + except Exception as e: + raise ModuleNotFoundError( + "Package 'webrtcvad' not found. This package enables " + "noise removal and is recommended. Please install and " + "try again. If installation fails, " + "use --no_trim to disable this error message.") + del args.no_trim + + args.datasets = [item.strip() for item in args.dataset_names.split(",")] + if not hasattr(args, "output_dir"): + args.output_dir = args.dataset_root / "SV2TTS" / "encoder" + + args.output_dir = args.output_dir.expanduser() + args.datasets_root = args.datasets_root.expanduser() + assert args.datasets_root.exists() + args.output_dir.mkdir(exist_ok=True, parents=True) + + config = get_cfg_defaults() + print(args) + + c = config.data + processor = SpeakerVerificationPreprocessor( + sampling_rate=c.sampling_rate, + audio_norm_target_dBFS=c.audio_norm_target_dBFS, + vad_window_length=c.vad_window_length, + vad_moving_average_width=c.vad_moving_average_width, + vad_max_silence_length=c.vad_max_silence_length, + mel_window_length=c.mel_window_length, + mel_window_step=c.mel_window_step, + n_mels=c.n_mels, + partial_n_frames=c.partial_n_frames, + min_pad_coverage=c.min_pad_coverage, + partial_overlap_ratio=c.min_pad_coverage, ) + + preprocess_func = { + "librispeech_other": process_librispeech, + "voxceleb1": process_voxceleb1, + "voxceleb2": process_voxceleb2, + "aidatatang_200zh": process_aidatatang_200zh, + "magicdata": process_magicdata, + } + + for dataset in args.datasets: + print("Preprocessing %s" % dataset) + preprocess_func[dataset](processor, args.datasets_root, args.output_dir, + args.skip_existing) diff --git a/examples/voxceleb/spk0/local/ge2e/random_cycle.py b/examples/voxceleb/spk0/local/ge2e/random_cycle.py new file mode 100644 index 00000000..4a201581 --- /dev/null +++ b/examples/voxceleb/spk0/local/ge2e/random_cycle.py @@ -0,0 +1,39 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import random + + +def cycle(iterable): + # cycle('ABCD') --> A B C D A B C D A B C D ... + saved = [] + for element in iterable: + yield element + saved.append(element) + while saved: + for element in saved: + yield element + + +def random_cycle(iterable): + # cycle('ABCD') --> A B C D B C D A A D B C ... + saved = [] + for element in iterable: + yield element + saved.append(element) + random.shuffle(saved) + while saved: + for element in saved: + yield element + random.shuffle(saved) diff --git a/examples/voxceleb/spk0/local/ge2e/speaker_verification_dataset.py b/examples/voxceleb/spk0/local/ge2e/speaker_verification_dataset.py new file mode 100644 index 00000000..c9cfda29 --- /dev/null +++ b/examples/voxceleb/spk0/local/ge2e/speaker_verification_dataset.py @@ -0,0 +1,131 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import random +from pathlib import Path + +import numpy as np +from paddle.io import Dataset, BatchSampler + +from random_cycle import random_cycle + + +class MultiSpeakerMelDataset(Dataset): + """A 2 layer directory thatn contains mel spectrograms in *.npy format. + An Example file structure tree is shown below. We prefer to preprocess + raw datasets and organized them like this. + + dataset_root/ + speaker1/ + utterance1.npy + utterance2.npy + utterance3.npy + speaker2/ + utterance1.npy + utterance2.npy + utterance3.npy + """ + + def __init__(self, dataset_root: Path): + self.root = Path(dataset_root).expanduser() + speaker_dirs = [f for f in self.root.glob("*") if f.is_dir()] + + speaker_utterances = { + speaker_dir: list(speaker_dir.glob("*.npy")) + for speaker_dir in speaker_dirs + } + + self.speaker_dirs = speaker_dirs + self.speaker_to_utterances = speaker_utterances + + # meta data + self.num_speakers = len(self.speaker_dirs) + self.num_utterances = np.sum( + len(utterances) + for speaker, utterances in self.speaker_to_utterances.items()) + + def get_example_by_index(self, speaker_index, utterance_index): + speaker_dir = self.speaker_dirs[speaker_index] + fpath = self.speaker_to_utterances[speaker_dir][utterance_index] + return self[fpath] + + def __getitem__(self, fpath): + return np.load(fpath) + + def __len__(self): + return int(self.num_utterances) + + +class MultiSpeakerSampler(BatchSampler): + """A multi-stratal sampler designed for speaker verification task. + First, N speakers from all speakers are sampled randomly. Then, for each + speaker, randomly sample M utterances from their corresponding utterances. + """ + + def __init__(self, + dataset: MultiSpeakerMelDataset, + speakers_per_batch: int, + utterances_per_speaker: int): + self._speakers = list(dataset.speaker_dirs) + self._speaker_to_utterances = dataset.speaker_to_utterances + + self.speakers_per_batch = speakers_per_batch + self.utterances_per_speaker = utterances_per_speaker + + def __iter__(self): + # yield list of Paths + speaker_generator = iter(random_cycle(self._speakers)) + speaker_utterances_generator = { + s: iter(random_cycle(us)) + for s, us in self._speaker_to_utterances.items() + } + + while True: + speakers = [] + for _ in range(self.speakers_per_batch): + speakers.append(next(speaker_generator)) + + utterances = [] + for s in speakers: + us = speaker_utterances_generator[s] + for _ in range(self.utterances_per_speaker): + utterances.append(next(us)) + yield utterances + + +class RandomClip(object): + def __init__(self, frames): + self.frames = frames + + def __call__(self, spec): + # spec [T, C] + T = spec.shape[0] + start = random.randint(0, T - self.frames) + return spec[start:start + self.frames, :] + + +class Collate(object): + def __init__(self, num_frames): + self.random_crop = RandomClip(num_frames) + + def __call__(self, examples): + frame_clips = [self.random_crop(mel) for mel in examples] + batced_clips = np.stack(frame_clips) + return batced_clips + + +if __name__ == "__main__": + mydataset = MultiSpeakerMelDataset( + Path("/home/chenfeiyu/datasets/SV2TTS/encoder")) + print(mydataset.get_example_by_index(0, 10)) diff --git a/examples/voxceleb/spk0/local/ge2e/train.py b/examples/voxceleb/spk0/local/ge2e/train.py new file mode 100644 index 00000000..950d486d --- /dev/null +++ b/examples/voxceleb/spk0/local/ge2e/train.py @@ -0,0 +1,125 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import time + +from paddle import distributed as dist +from paddle.optimizer import Adam +from paddle import DataParallel +from paddle.io import DataLoader +from paddle.nn.clip import ClipGradByGlobalNorm + +from parakeet.models.lstm_speaker_encoder import LSTMSpeakerEncoder +from parakeet.training import ExperimentBase +from parakeet.training import default_argument_parser + +from speaker_verification_dataset import MultiSpeakerMelDataset +from speaker_verification_dataset import MultiSpeakerSampler +from speaker_verification_dataset import Collate +from config import get_cfg_defaults + + +class Ge2eExperiment(ExperimentBase): + def setup_model(self): + config = self.config + model = LSTMSpeakerEncoder(config.data.n_mels, config.model.num_layers, + config.model.hidden_size, + config.model.embedding_size) + optimizer = Adam( + config.training.learning_rate_init, + parameters=model.parameters(), + grad_clip=ClipGradByGlobalNorm(3)) + self.model = DataParallel(model) if self.parallel else model + self.model_core = model + self.optimizer = optimizer + + def setup_dataloader(self): + config = self.config + train_dataset = MultiSpeakerMelDataset(self.args.data) + sampler = MultiSpeakerSampler(train_dataset, + config.training.speakers_per_batch, + config.training.utterances_per_speaker) + train_loader = DataLoader( + train_dataset, + batch_sampler=sampler, + collate_fn=Collate(config.data.partial_n_frames), + num_workers=16) + + self.train_dataset = train_dataset + self.train_loader = train_loader + + def train_batch(self): + start = time.time() + batch = self.read_batch() + data_loader_time = time.time() - start + + self.optimizer.clear_grad() + self.model.train() + specs = batch + loss, eer = self.model(specs, self.config.training.speakers_per_batch) + loss.backward() + self.model_core.do_gradient_ops() + self.optimizer.step() + iteration_time = time.time() - start + + # logging + loss_value = float(loss) + msg = "Rank: {}, ".format(dist.get_rank()) + msg += "step: {}, ".format(self.iteration) + msg += "time: {:>.3f}s/{:>.3f}s, ".format(data_loader_time, + iteration_time) + msg += 'loss: {:>.6f} err: {:>.6f}'.format(loss_value, eer) + self.logger.info(msg) + + if dist.get_rank() == 0: + self.visualizer.add_scalar("train/loss", loss_value, self.iteration) + self.visualizer.add_scalar("train/eer", eer, self.iteration) + self.visualizer.add_scalar("param/w", + float(self.model_core.similarity_weight), + self.iteration) + self.visualizer.add_scalar("param/b", + float(self.model_core.similarity_bias), + self.iteration) + + def valid(self): + pass + + +def main_sp(config, args): + exp = Ge2eExperiment(config, args) + exp.setup() + exp.resume_or_load() + exp.run() + + +def main(config, args): + if args.nprocs > 1 and args.device == "gpu": + dist.spawn(main_sp, args=(config, args), nprocs=args.nprocs) + else: + main_sp(config, args) + + +if __name__ == "__main__": + config = get_cfg_defaults() + parser = default_argument_parser() + args = parser.parse_args() + if args.config: + config.merge_from_file(args.config) + if args.opts: + config.merge_from_list(args.opts) + config.freeze() + print(config) + print(args) + + main(config, args) diff --git a/examples/voxceleb/spk0/run.sh b/examples/voxceleb/spk0/run.sh new file mode 100644 index 00000000..e69de29b diff --git a/parakeet/__init__.py b/parakeet/__init__.py new file mode 100644 index 00000000..8b99260e --- /dev/null +++ b/parakeet/__init__.py @@ -0,0 +1,23 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +__version__ = "0.0.0" +import logging +from . import data +from . import datasets +from . import frontend +from . import models +from . import modules +from . import training +from . import utils diff --git a/parakeet/audio/__init__.py b/parakeet/audio/__init__.py new file mode 100644 index 00000000..23e378fd --- /dev/null +++ b/parakeet/audio/__init__.py @@ -0,0 +1,17 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from .audio import AudioProcessor +from .spec_normalizer import LogMagnitude +from .spec_normalizer import NormalizerBase diff --git a/parakeet/audio/audio.py b/parakeet/audio/audio.py new file mode 100644 index 00000000..ab9a45d3 --- /dev/null +++ b/parakeet/audio/audio.py @@ -0,0 +1,102 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import librosa +import numpy as np +import soundfile as sf + +__all__ = ["AudioProcessor"] + + +class AudioProcessor(object): + def __init__(self, + sample_rate: int, + n_fft: int, + win_length: int, + hop_length: int, + n_mels: int=80, + fmin: int=0, + fmax: int=None, + window="hann", + center=True, + pad_mode="reflect", + normalize=True): + # read & write + self.sample_rate = sample_rate + self.normalize = normalize + + # stft + self.n_fft = n_fft + self.win_length = win_length + self.hop_length = hop_length + self.window = window + self.center = center + self.pad_mode = pad_mode + + # mel + self.n_mels = n_mels + self.fmin = fmin + self.fmax = fmax + + self.mel_filter = self._create_mel_filter() + self.inv_mel_filter = np.linalg.pinv(self.mel_filter) + + def _create_mel_filter(self): + mel_filter = librosa.filters.mel( + self.sample_rate, + self.n_fft, + n_mels=self.n_mels, + fmin=self.fmin, + fmax=self.fmax) + return mel_filter + + def read_wav(self, filename): + # resampling may occur + wav, _ = librosa.load(filename, sr=self.sample_rate) + + # normalize the volume + if self.normalize: + wav = wav / np.max(np.abs(wav)) * 0.999 + return wav + + def write_wav(self, path, wav): + sf.write(path, wav, samplerate=self.sample_rate) + + def stft(self, wav): + D = librosa.core.stft( + wav, + n_fft=self.n_fft, + hop_length=self.hop_length, + win_length=self.win_length, + window=self.window, + center=self.center, + pad_mode=self.pad_mode) + return D + + def istft(self, D): + wav = librosa.core.istft( + D, + hop_length=self.hop_length, + win_length=self.win_length, + window=self.window, + center=self.center) + return wav + + def spectrogram(self, wav): + D = self.stft(wav) + return np.abs(D) + + def mel_spectrogram(self, wav): + S = self.spectrogram(wav) + mel = np.dot(self.mel_filter, S) + return mel diff --git a/parakeet/audio/spec_normalizer.py b/parakeet/audio/spec_normalizer.py new file mode 100644 index 00000000..d8cd67a2 --- /dev/null +++ b/parakeet/audio/spec_normalizer.py @@ -0,0 +1,74 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" +This modules contains normalizers for spectrogram magnitude. +Normalizers are invertible transformations. They can be used to process +magnitude of spectrogram before training and can also be used to recover from +the generated spectrogram so as to be used with vocoders like griffin lim. + +The base class describe the interface. `transform` is used to perform +transformation and `inverse` is used to perform the inverse transformation. + +check issues: +https://github.com/mozilla/TTS/issues/377 +""" +import numpy as np + +__all__ = ["NormalizerBase", "LogMagnitude", "UnitMagnitude"] + + +class NormalizerBase(object): + def transform(self, spec): + raise NotImplementedError("transform must be implemented") + + def inverse(self, normalized): + raise NotImplementedError("inverse must be implemented") + + +class LogMagnitude(NormalizerBase): + """ + This is a simple normalizer used in Waveglow, Waveflow, tacotron2... + """ + + def __init__(self, min=1e-5): + self.min = min + + def transform(self, x): + x = np.maximum(x, self.min) + x = np.log(x) + return x + + def inverse(self, x): + return np.exp(x) + + +class UnitMagnitude(NormalizerBase): + # dbscale and (0, 1) normalization + """ + This is the normalizer used in the + """ + + def __init__(self, min=1e-5): + self.min = min + + def transform(self, x): + db_scale = 20 * np.log10(np.maximum(self.min, x)) - 20 + normalized = (db_scale + 100) / 100 + clipped = np.clip(normalized, 0, 1) + return clipped + + def inverse(self, x): + denormalized = np.clip(x, 0, 1) * 100 - 100 + out = np.exp((denormalized + 20) / 20 * np.log(10)) + return out diff --git a/parakeet/data/__init__.py b/parakeet/data/__init__.py new file mode 100644 index 00000000..6f15dbbe --- /dev/null +++ b/parakeet/data/__init__.py @@ -0,0 +1,18 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Parakeet's infrastructure for data processing. +""" + +from .dataset import * +from .batch import * diff --git a/parakeet/data/batch.py b/parakeet/data/batch.py new file mode 100644 index 00000000..515074d1 --- /dev/null +++ b/parakeet/data/batch.py @@ -0,0 +1,189 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" +Utility functions to create batch for arrays which satisfy some conditions. +Batch functions for text sequences, audio and spectrograms are provided. +""" +import numpy as np + +__all__ = [ + "batch_text_id", + "batch_wav", + "batch_spec", + "TextIDBatcher", + "WavBatcher", + "SpecBatcher", +] + + +class TextIDBatcher(object): + """A wrapper class for `batch_text_id`.""" + + def __init__(self, pad_id=0, dtype=np.int64): + self.pad_id = pad_id + self.dtype = dtype + + def __call__(self, minibatch): + out = batch_text_id(minibatch, pad_id=self.pad_id, dtype=self.dtype) + return out + + +def batch_text_id(minibatch, pad_id=0, dtype=np.int64): + """Pad sequences to text_ids to the largest length and batch them. + + Args: + minibatch (List[np.ndarray]): list of rank-1 arrays, shape(T,), dtype np.int64, text_ids. + pad_id (int, optional): the id which correspond to the special pad token. Defaults to 0. + dtype (np.dtype, optional): the data dtype of the output. Defaults to np.int64. + + Returns: + np.ndarray: rank-2 array of text_ids, shape(B, T), B stands for batch_size, T stands for length. The output batch. + """ + peek_example = minibatch[0] + assert len(peek_example.shape) == 1, "text example is an 1D tensor" + + lengths = [example.shape[0] for example in minibatch + ] # assume (channel, n_samples) or (n_samples, ) + max_len = np.max(lengths) + + batch = [] + for example in minibatch: + pad_len = max_len - example.shape[0] + batch.append( + np.pad( + example, [(0, pad_len)], + mode='constant', + constant_values=pad_id)) + + return np.array(batch, dtype=dtype), np.array(lengths, dtype=np.int64) + + +class WavBatcher(object): + """A wrapper class for `batch_wav`.""" + + def __init__(self, pad_value=0., dtype=np.float32): + self.pad_value = pad_value + self.dtype = dtype + + def __call__(self, minibatch): + out = batch_wav(minibatch, pad_value=self.pad_value, dtype=self.dtype) + return out + + +def batch_wav(minibatch, pad_value=0., dtype=np.float32): + """pad audios to the largest length and batch them. + + Args: + minibatch (List[np.ndarray]): list of rank-1 float arrays(mono-channel audio, shape(T,)), dtype float. + pad_value (float, optional): the pad value. Defaults to 0.. + dtype (np.dtype, optional): the data type of the output. Defaults to np.float32. + + Returns: + np.ndarray: shape(B, T), the output batch. + """ + + peek_example = minibatch[0] + assert len(peek_example.shape) == 1, "we only handles mono-channel wav" + + # assume (channel, n_samples) or (n_samples, ) + lengths = [example.shape[-1] for example in minibatch] + max_len = np.max(lengths) + + batch = [] + for example in minibatch: + pad_len = max_len - example.shape[-1] + batch.append( + np.pad( + example, [(0, pad_len)], + mode='constant', + constant_values=pad_value)) + return np.array(batch, dtype=dtype), np.array(lengths, dtype=np.int64) + + +class SpecBatcher(object): + """A wrapper class for `batch_spec`""" + + def __init__(self, pad_value=0., time_major=False, dtype=np.float32): + self.pad_value = pad_value + self.dtype = dtype + self.time_major = time_major + + def __call__(self, minibatch): + out = batch_spec( + minibatch, + pad_value=self.pad_value, + time_major=self.time_major, + dtype=self.dtype) + return out + + +def batch_spec(minibatch, pad_value=0., time_major=False, dtype=np.float32): + """Pad spectra to the largest length and batch them. + + Args: + minibatch (List[np.ndarray]): list of rank-2 arrays of shape(F, T) for mono-channel spectrograms, or list of rank-3 arrays of shape(C, F, T) for multi-channel spectrograms(F stands for frequency bands.), dtype float. + pad_value (float, optional): the pad value. Defaults to 0.. + dtype (np.dtype, optional): data type of the output. Defaults to np.float32. + + Returns: + np.ndarray: a rank-3 array of shape(B, F, T) or (B, T, F). + """ + # assume (F, T) or (T, F) + peek_example = minibatch[0] + assert len( + peek_example.shape) == 2, "we only handles mono channel spectrogram" + + # assume (F, n_frame) or (n_frame, F) + time_idx = 0 if time_major else -1 + lengths = [example.shape[time_idx] for example in minibatch] + max_len = np.max(lengths) + + batch = [] + for example in minibatch: + pad_len = max_len - example.shape[time_idx] + if time_major: + batch.append( + np.pad( + example, [(0, pad_len), (0, 0)], + mode='constant', + constant_values=pad_value)) + else: + batch.append( + np.pad( + example, [(0, 0), (0, pad_len)], + mode='constant', + constant_values=pad_value)) + return np.array(batch, dtype=dtype), np.array(lengths, dtype=np.int64) + + +def batch_sequences(sequences, axis=0, pad_value=0): + # import pdb; pdb.set_trace() + seq = sequences[0] + ndim = seq.ndim + if axis < 0: + axis += ndim + dtype = seq.dtype + pad_value = dtype.type(pad_value) + seq_lengths = [seq.shape[axis] for seq in sequences] + max_length = np.max(seq_lengths) + + padded_sequences = [] + for seq, length in zip(sequences, seq_lengths): + padding = [(0, 0)] * axis + [(0, max_length - length)] + [(0, 0)] * ( + ndim - axis - 1) + padded_seq = np.pad( + seq, padding, mode='constant', constant_values=pad_value) + padded_sequences.append(padded_seq) + batch = np.stack(padded_sequences) + return batch diff --git a/parakeet/data/dataset.py b/parakeet/data/dataset.py new file mode 100644 index 00000000..2d6c03cb --- /dev/null +++ b/parakeet/data/dataset.py @@ -0,0 +1,261 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import six +from paddle.io import Dataset + +__all__ = [ + "split", + "TransformDataset", + "CacheDataset", + "TupleDataset", + "DictDataset", + "SliceDataset", + "SubsetDataset", + "FilterDataset", + "ChainDataset", +] + + +def split(dataset, first_size): + """A utility function to split a dataset into two datasets.""" + first = SliceDataset(dataset, 0, first_size) + second = SliceDataset(dataset, first_size, len(dataset)) + return first, second + + +class TransformDataset(Dataset): + def __init__(self, dataset, transform): + """Dataset which is transformed from another with a transform. + + Args: + dataset (Dataset): the base dataset. + transform (callable): the transform which takes an example of the base dataset as parameter and return a new example. + """ + self._dataset = dataset + self._transform = transform + + def __len__(self): + return len(self._dataset) + + def __getitem__(self, i): + in_data = self._dataset[i] + return self._transform(in_data) + + +class CacheDataset(Dataset): + def __init__(self, dataset): + """A lazy cache of the base dataset. + + Args: + dataset (Dataset): the base dataset to cache. + """ + self._dataset = dataset + self._cache = dict() + + def __len__(self): + return len(self._dataset) + + def __getitem__(self, i): + if i not in self._cache: + self._cache[i] = self._dataset[i] + return self._cache[i] + + +class TupleDataset(Dataset): + def __init__(self, *datasets): + """A compound dataset made from several datasets of the same length. An example of the `TupleDataset` is a tuple of examples from the constituent datasets. + + Args: + datasets: tuple[Dataset], the constituent datasets. + """ + if not datasets: + raise ValueError("no datasets are given") + length = len(datasets[0]) + for i, dataset in enumerate(datasets): + if len(dataset) != length: + raise ValueError("all the datasets should have the same length." + "dataset {} has a different length".format(i)) + self._datasets = datasets + self._length = length + + def __getitem__(self, index): + # SOA + batches = [dataset[index] for dataset in self._datasets] + if isinstance(index, slice): + length = len(batches[0]) + # AOS + return [ + tuple([batch[i] for batch in batches]) + for i in six.moves.range(length) + ] + else: + return tuple(batches) + + def __len__(self): + return self._length + + +class DictDataset(Dataset): + def __init__(self, **datasets): + """ + A compound dataset made from several datasets of the same length. An + example of the `DictDataset` is a dict of examples from the constituent + datasets. + + WARNING: paddle does not have a good support for DictDataset, because + every batch yield from a DataLoader is a list, but it cannot be a dict. + So you have to provide a collate function because you cannot use the + default one. + + Args: + datasets: Dict[Dataset], the constituent datasets. + """ + if not datasets: + raise ValueError("no datasets are given") + length = None + for key, dataset in six.iteritems(datasets): + if length is None: + length = len(dataset) + elif len(dataset) != length: + raise ValueError( + "all the datasets should have the same length." + "dataset {} has a different length".format(key)) + self._datasets = datasets + self._length = length + + def __getitem__(self, index): + batches = { + key: dataset[index] + for key, dataset in six.iteritems(self._datasets) + } + if isinstance(index, slice): + length = len(six.next(six.itervalues(batches))) + return [{key: batch[i] + for key, batch in six.iteritems(batches)} + for i in six.moves.range(length)] + else: + return batches + + def __len__(self): + return self._length + + +class SliceDataset(Dataset): + def __init__(self, dataset, start, finish, order=None): + """A Dataset which is a slice of the base dataset. + + Args: + dataset (Dataset): the base dataset. + start (int): the start of the slice. + finish (int): the end of the slice, not inclusive. + order (List[int], optional): the order, it is a permutation of the valid example ids of the base dataset. If `order` is provided, the slice is taken in `order`. Defaults to None. + """ + if start < 0 or finish > len(dataset): + raise ValueError("subset overruns the dataset.") + self._dataset = dataset + self._start = start + self._finish = finish + self._size = finish - start + + if order is not None and len(order) != len(dataset): + raise ValueError( + "order should have the same length as the dataset" + "len(order) = {} which does not euqals len(dataset) = {} ". + format(len(order), len(dataset))) + self._order = order + + def __len__(self): + return self._size + + def __getitem__(self, i): + if i >= 0: + if i >= self._size: + raise IndexError('dataset index out of range') + index = self._start + i + else: + if i < -self._size: + raise IndexError('dataset index out of range') + index = self._finish + i + + if self._order is not None: + index = self._order[index] + return self._dataset[index] + + +class SubsetDataset(Dataset): + def __init__(self, dataset, indices): + """A Dataset which is a subset of the base dataset. + + Args: + dataset (Dataset): the base dataset. + indices (Iterable[int]): the indices of the examples to pick. + """ + self._dataset = dataset + if len(indices) > len(dataset): + raise ValueError("subset's size larger that dataset's size!") + self._indices = indices + self._size = len(indices) + + def __len__(self): + return self._size + + def __getitem__(self, i): + index = self._indices[i] + return self._dataset[index] + + +class FilterDataset(Dataset): + def __init__(self, dataset, filter_fn): + """A filtered dataset. + + Args: + dataset (Dataset): the base dataset. + filter_fn (callable): a callable which takes an example of the base dataset and return a boolean. + """ + self._dataset = dataset + self._indices = [ + i for i in range(len(dataset)) if filter_fn(dataset[i]) + ] + self._size = len(self._indices) + + def __len__(self): + return self._size + + def __getitem__(self, i): + index = self._indices[i] + return self._dataset[index] + + +class ChainDataset(Dataset): + def __init__(self, *datasets): + """A concatenation of the several datasets which the same structure. + + Args: + datasets (Iterable[Dataset]): datasets to concat. + """ + self._datasets = datasets + + def __len__(self): + return sum(len(dataset) for dataset in self._datasets) + + def __getitem__(self, i): + if i < 0: + raise IndexError("ChainDataset doesnot support negative indexing.") + + for dataset in self._datasets: + if i < len(dataset): + return dataset[i] + i -= len(dataset) + + raise IndexError("dataset index out of range") diff --git a/parakeet/data/get_feats.py b/parakeet/data/get_feats.py new file mode 100644 index 00000000..d7ab7640 --- /dev/null +++ b/parakeet/data/get_feats.py @@ -0,0 +1,220 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import librosa +import numpy as np +import pyworld +from scipy.interpolate import interp1d + + +class LogMelFBank(): + def __init__(self, + sr=24000, + n_fft=2048, + hop_length=300, + win_length=None, + window="hann", + n_mels=80, + fmin=80, + fmax=7600, + eps=1e-10): + self.sr = sr + # stft + self.n_fft = n_fft + self.win_length = win_length + self.hop_length = hop_length + self.window = window + self.center = True + self.pad_mode = "reflect" + + # mel + self.n_mels = n_mels + self.fmin = 0 if fmin is None else fmin + self.fmax = sr / 2 if fmax is None else fmax + + self.mel_filter = self._create_mel_filter() + + def _create_mel_filter(self): + mel_filter = librosa.filters.mel( + sr=self.sr, + n_fft=self.n_fft, + n_mels=self.n_mels, + fmin=self.fmin, + fmax=self.fmax) + return mel_filter + + def _stft(self, wav): + D = librosa.core.stft( + wav, + n_fft=self.n_fft, + hop_length=self.hop_length, + win_length=self.win_length, + window=self.window, + center=self.center, + pad_mode=self.pad_mode) + return D + + def _spectrogram(self, wav): + D = self._stft(wav) + return np.abs(D) + + def _mel_spectrogram(self, wav): + S = self._spectrogram(wav) + mel = np.dot(self.mel_filter, S) + return mel + + # We use different definition for log-spec between TTS and ASR + # TTS: log_10(abs(stft)) + # ASR: log_e(power(stft)) + + def get_log_mel_fbank(self, wav, base='10'): + mel = self._mel_spectrogram(wav) + mel = np.clip(mel, a_min=1e-10, a_max=float("inf")) + if base == '10': + mel = np.log10(mel.T) + elif base == 'e': + mel = np.log(mel.T) + # (num_frames, n_mels) + return mel + + +class Pitch(): + def __init__(self, sr=24000, hop_length=300, f0min=80, f0max=7600): + + self.sr = sr + self.hop_length = hop_length + self.f0min = f0min + self.f0max = f0max + + def _convert_to_continuous_f0(self, f0: np.array) -> np.array: + if (f0 == 0).all(): + print("All frames seems to be unvoiced.") + return f0 + + # padding start and end of f0 sequence + start_f0 = f0[f0 != 0][0] + end_f0 = f0[f0 != 0][-1] + start_idx = np.where(f0 == start_f0)[0][0] + end_idx = np.where(f0 == end_f0)[0][-1] + f0[:start_idx] = start_f0 + f0[end_idx:] = end_f0 + + # get non-zero frame index + nonzero_idxs = np.where(f0 != 0)[0] + + # perform linear interpolation + interp_fn = interp1d(nonzero_idxs, f0[nonzero_idxs]) + f0 = interp_fn(np.arange(0, f0.shape[0])) + + return f0 + + def _calculate_f0(self, + input: np.array, + use_continuous_f0=True, + use_log_f0=True) -> np.array: + input = input.astype(np.float) + frame_period = 1000 * self.hop_length / self.sr + f0, timeaxis = pyworld.dio( + input, + fs=self.sr, + f0_floor=self.f0min, + f0_ceil=self.f0max, + frame_period=frame_period) + f0 = pyworld.stonemask(input, f0, timeaxis, self.sr) + if use_continuous_f0: + f0 = self._convert_to_continuous_f0(f0) + if use_log_f0: + nonzero_idxs = np.where(f0 != 0)[0] + f0[nonzero_idxs] = np.log(f0[nonzero_idxs]) + return f0.reshape(-1) + + def _average_by_duration(self, input: np.array, d: np.array) -> np.array: + d_cumsum = np.pad(d.cumsum(0), (1, 0), 'constant') + arr_list = [] + for start, end in zip(d_cumsum[:-1], d_cumsum[1:]): + arr = input[start:end] + mask = arr == 0 + arr[mask] = 0 + avg_arr = np.mean(arr, axis=0) if len(arr) != 0 else np.array(0) + arr_list.append(avg_arr) + # shape (T,1) + arr_list = np.expand_dims(np.array(arr_list), 0).T + + return arr_list + + def get_pitch(self, + wav, + use_continuous_f0=True, + use_log_f0=True, + use_token_averaged_f0=True, + duration=None): + f0 = self._calculate_f0(wav, use_continuous_f0, use_log_f0) + if use_token_averaged_f0 and duration is not None: + f0 = self._average_by_duration(f0, duration) + return f0 + + +class Energy(): + def __init__(self, + sr=24000, + n_fft=2048, + hop_length=300, + win_length=None, + window="hann", + center=True, + pad_mode="reflect"): + + self.sr = sr + self.n_fft = n_fft + self.win_length = win_length + self.hop_length = hop_length + self.window = window + self.center = center + self.pad_mode = pad_mode + + def _stft(self, wav): + D = librosa.core.stft( + wav, + n_fft=self.n_fft, + hop_length=self.hop_length, + win_length=self.win_length, + window=self.window, + center=self.center, + pad_mode=self.pad_mode) + return D + + def _calculate_energy(self, input): + input = input.astype(np.float32) + input_stft = self._stft(input) + input_power = np.abs(input_stft)**2 + energy = np.sqrt( + np.clip( + np.sum(input_power, axis=0), a_min=1.0e-10, a_max=float('inf'))) + return energy + + def _average_by_duration(self, input: np.array, d: np.array) -> np.array: + d_cumsum = np.pad(d.cumsum(0), (1, 0), 'constant') + arr_list = [] + for start, end in zip(d_cumsum[:-1], d_cumsum[1:]): + arr = input[start:end] + avg_arr = np.mean(arr, axis=0) if len(arr) != 0 else np.array(0) + arr_list.append(avg_arr) + # shape (T,1) + arr_list = np.expand_dims(np.array(arr_list), 0).T + return arr_list + + def get_energy(self, wav, use_token_averaged_energy=True, duration=None): + energy = self._calculate_energy(wav) + if use_token_averaged_energy and duration is not None: + energy = self._average_by_duration(energy, duration) + return energy diff --git a/parakeet/datasets/__init__.py b/parakeet/datasets/__init__.py new file mode 100644 index 00000000..cbdcdfa4 --- /dev/null +++ b/parakeet/datasets/__init__.py @@ -0,0 +1,16 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from .common import * +from .ljspeech import * diff --git a/parakeet/datasets/am_batch_fn.py b/parakeet/datasets/am_batch_fn.py new file mode 100644 index 00000000..42d5babd --- /dev/null +++ b/parakeet/datasets/am_batch_fn.py @@ -0,0 +1,174 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import numpy as np +import paddle + +from parakeet.data.batch import batch_sequences + + +def speedyspeech_batch_fn(examples): + # fields = ["phones", "tones", "num_phones", "num_frames", "feats", "durations"] + phones = [np.array(item["phones"], dtype=np.int64) for item in examples] + tones = [np.array(item["tones"], dtype=np.int64) for item in examples] + feats = [np.array(item["feats"], dtype=np.float32) for item in examples] + durations = [ + np.array(item["durations"], dtype=np.int64) for item in examples + ] + num_phones = [ + np.array(item["num_phones"], dtype=np.int64) for item in examples + ] + num_frames = [ + np.array(item["num_frames"], dtype=np.int64) for item in examples + ] + + phones = batch_sequences(phones) + tones = batch_sequences(tones) + feats = batch_sequences(feats) + durations = batch_sequences(durations) + + # convert each batch to paddle.Tensor + phones = paddle.to_tensor(phones) + tones = paddle.to_tensor(tones) + feats = paddle.to_tensor(feats) + durations = paddle.to_tensor(durations) + num_phones = paddle.to_tensor(num_phones) + num_frames = paddle.to_tensor(num_frames) + batch = { + "phones": phones, + "tones": tones, + "num_phones": num_phones, + "num_frames": num_frames, + "feats": feats, + "durations": durations, + } + return batch + + +def fastspeech2_single_spk_batch_fn(examples): + # fields = ["text", "text_lengths", "speech", "speech_lengths", "durations", "pitch", "energy"] + text = [np.array(item["text"], dtype=np.int64) for item in examples] + speech = [np.array(item["speech"], dtype=np.float32) for item in examples] + pitch = [np.array(item["pitch"], dtype=np.float32) for item in examples] + energy = [np.array(item["energy"], dtype=np.float32) for item in examples] + durations = [ + np.array(item["durations"], dtype=np.int64) for item in examples + ] + + text_lengths = [ + np.array(item["text_lengths"], dtype=np.int64) for item in examples + ] + speech_lengths = [ + np.array(item["speech_lengths"], dtype=np.int64) for item in examples + ] + + text = batch_sequences(text) + pitch = batch_sequences(pitch) + speech = batch_sequences(speech) + durations = batch_sequences(durations) + energy = batch_sequences(energy) + + # convert each batch to paddle.Tensor + text = paddle.to_tensor(text) + pitch = paddle.to_tensor(pitch) + speech = paddle.to_tensor(speech) + durations = paddle.to_tensor(durations) + energy = paddle.to_tensor(energy) + text_lengths = paddle.to_tensor(text_lengths) + speech_lengths = paddle.to_tensor(speech_lengths) + + batch = { + "text": text, + "text_lengths": text_lengths, + "durations": durations, + "speech": speech, + "speech_lengths": speech_lengths, + "pitch": pitch, + "energy": energy + } + return batch + + +def fastspeech2_multi_spk_batch_fn(examples): + # fields = ["text", "text_lengths", "speech", "speech_lengths", "durations", "pitch", "energy", "spk_id"] + text = [np.array(item["text"], dtype=np.int64) for item in examples] + speech = [np.array(item["speech"], dtype=np.float32) for item in examples] + pitch = [np.array(item["pitch"], dtype=np.float32) for item in examples] + energy = [np.array(item["energy"], dtype=np.float32) for item in examples] + durations = [ + np.array(item["durations"], dtype=np.int64) for item in examples + ] + text_lengths = [ + np.array(item["text_lengths"], dtype=np.int64) for item in examples + ] + speech_lengths = [ + np.array(item["speech_lengths"], dtype=np.int64) for item in examples + ] + spk_id = [np.array(item["spk_id"], dtype=np.int64) for item in examples] + + text = batch_sequences(text) + pitch = batch_sequences(pitch) + speech = batch_sequences(speech) + durations = batch_sequences(durations) + energy = batch_sequences(energy) + + # convert each batch to paddle.Tensor + text = paddle.to_tensor(text) + pitch = paddle.to_tensor(pitch) + speech = paddle.to_tensor(speech) + durations = paddle.to_tensor(durations) + energy = paddle.to_tensor(energy) + text_lengths = paddle.to_tensor(text_lengths) + speech_lengths = paddle.to_tensor(speech_lengths) + spk_id = paddle.to_tensor(spk_id) + + batch = { + "text": text, + "text_lengths": text_lengths, + "durations": durations, + "speech": speech, + "speech_lengths": speech_lengths, + "pitch": pitch, + "energy": energy, + "spk_id": spk_id + } + return batch + + +def transformer_single_spk_batch_fn(examples): + # fields = ["text", "text_lengths", "speech", "speech_lengths"] + text = [np.array(item["text"], dtype=np.int64) for item in examples] + speech = [np.array(item["speech"], dtype=np.float32) for item in examples] + text_lengths = [ + np.array(item["text_lengths"], dtype=np.int64) for item in examples + ] + speech_lengths = [ + np.array(item["speech_lengths"], dtype=np.int64) for item in examples + ] + + text = batch_sequences(text) + speech = batch_sequences(speech) + + # convert each batch to paddle.Tensor + text = paddle.to_tensor(text) + speech = paddle.to_tensor(speech) + text_lengths = paddle.to_tensor(text_lengths) + speech_lengths = paddle.to_tensor(speech_lengths) + + batch = { + "text": text, + "text_lengths": text_lengths, + "speech": speech, + "speech_lengths": speech_lengths, + } + return batch diff --git a/parakeet/datasets/common.py b/parakeet/datasets/common.py new file mode 100644 index 00000000..d6fa3a84 --- /dev/null +++ b/parakeet/datasets/common.py @@ -0,0 +1,92 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from pathlib import Path +from typing import List + +import librosa +import numpy as np +from paddle.io import Dataset + +__all__ = ["AudioSegmentDataset", "AudioDataset", "AudioFolderDataset"] + + +class AudioSegmentDataset(Dataset): + """A simple dataset adaptor for audio files to train vocoders. + Read -> trim silence -> normalize -> extract a segment + """ + + def __init__(self, + file_paths: List[Path], + sample_rate: int, + length: int, + top_db: float): + self.file_paths = file_paths + self.sr = sample_rate + self.top_db = top_db + self.length = length # samples in the clip + + def __getitem__(self, i): + fpath = self.file_paths[i] + y, sr = librosa.load(fpath, self.sr) + y, _ = librosa.effects.trim(y, top_db=self.top_db) + y = librosa.util.normalize(y) + y = y.astype(np.float32) + + # pad or trim + if y.size <= self.length: + y = np.pad(y, [0, self.length - len(y)], mode='constant') + else: + start = np.random.randint(0, 1 + len(y) - self.length) + y = y[start:start + self.length] + return y + + def __len__(self): + return len(self.file_paths) + + +class AudioDataset(Dataset): + """A simple dataset adaptor for the audio files. + Read -> trim silence -> normalize + """ + + def __init__(self, + file_paths: List[Path], + sample_rate: int, + top_db: float=60): + self.file_paths = file_paths + self.sr = sample_rate + self.top_db = top_db + + def __getitem__(self, i): + fpath = self.file_paths[i] + y, sr = librosa.load(fpath, self.sr) + y, _ = librosa.effects.trim(y, top_db=self.top_db) + y = librosa.util.normalize(y) + y = y.astype(np.float32) + return y + + def __len__(self): + return len(self.file_paths) + + +class AudioFolderDataset(AudioDataset): + def __init__( + self, + root, + sample_rate, + top_db=60, + extension=".wav", ): + root = Path(root).expanduser() + file_paths = sorted(list(root.rglob("*{}".format(extension)))) + super().__init__(file_paths, sample_rate, top_db) diff --git a/parakeet/datasets/data_table.py b/parakeet/datasets/data_table.py new file mode 100644 index 00000000..b0e4c891 --- /dev/null +++ b/parakeet/datasets/data_table.py @@ -0,0 +1,151 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from multiprocessing import Manager +from typing import Any +from typing import Callable +from typing import Dict +from typing import List + +from paddle.io import Dataset + + +class DataTable(Dataset): + """Dataset to load and convert data for general purpose. + + Parameters + ---------- + data : List[Dict[str, Any]] + Metadata, a list of meta datum, each of which is composed of + several fields + fields : List[str], optional + Fields to use, if not specified, all the fields in the data are + used, by default None + converters : Dict[str, Callable], optional + Converters used to process each field, by default None + use_cache : bool, optional + Whether to use cache, by default False + + Raises + ------ + ValueError + If there is some field that does not exist in data. + ValueError + If there is some field in converters that does not exist in fields. + """ + + def __init__(self, + data: List[Dict[str, Any]], + fields: List[str]=None, + converters: Dict[str, Callable]=None, + use_cache: bool=False): + # metadata + self.data = data + assert len(data) > 0, "This dataset has no examples" + + # peak an example to get existing fields. + first_example = self.data[0] + fields_in_data = first_example.keys() + + # check all the requested fields exist + if fields is None: + self.fields = fields_in_data + else: + for field in fields: + if field not in fields_in_data: + raise ValueError( + f"The requested field ({field}) is not found" + f"in the data. Fields in the data is {fields_in_data}") + self.fields = fields + + # check converters + if converters is None: + self.converters = {} + else: + for field in converters.keys(): + if field not in self.fields: + raise ValueError( + f"The converter has a non existing field ({field})") + self.converters = converters + + self.use_cache = use_cache + if use_cache: + self._initialize_cache() + + def _initialize_cache(self): + self.manager = Manager() + self.caches = self.manager.list() + self.caches += [None for _ in range(len(self))] + + def _get_metadata(self, idx: int) -> Dict[str, Any]: + """Return a meta-datum given an index.""" + return self.data[idx] + + def _convert(self, meta_datum: Dict[str, Any]) -> Dict[str, Any]: + """Convert a meta datum to an example by applying the corresponding + converters to each fields requested. + + Parameters + ---------- + meta_datum : Dict[str, Any] + Meta datum + + Returns + ------- + Dict[str, Any] + Converted example + """ + example = {} + for field in self.fields: + converter = self.converters.get(field, None) + meta_datum_field = meta_datum[field] + if converter is not None: + converted_field = converter(meta_datum_field) + else: + converted_field = meta_datum_field + example[field] = converted_field + return example + + def __getitem__(self, idx: int) -> Dict[str, Any]: + """Get an example given an index. + + Parameters + ---------- + idx : int + Index of the example to get + + Returns + ------- + Dict[str, Any] + A converted example + """ + if self.use_cache and self.caches[idx] is not None: + return self.caches[idx] + + meta_datum = self._get_metadata(idx) + example = self._convert(meta_datum) + + if self.use_cache: + self.caches[idx] = example + + return example + + def __len__(self) -> int: + """Returns the size of the dataset. + + Returns + ------- + int + The length of the dataset + """ + return len(self.data) diff --git a/parakeet/datasets/ljspeech.py b/parakeet/datasets/ljspeech.py new file mode 100644 index 00000000..85cc3c18 --- /dev/null +++ b/parakeet/datasets/ljspeech.py @@ -0,0 +1,39 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from pathlib import Path + +from paddle.io import Dataset + +__all__ = ["LJSpeechMetaData"] + + +class LJSpeechMetaData(Dataset): + def __init__(self, root): + self.root = Path(root).expanduser() + wav_dir = self.root / "wavs" + csv_path = self.root / "metadata.csv" + records = [] + speaker_name = "ljspeech" + with open(str(csv_path), 'rt', encoding='utf-8') as f: + for line in f: + filename, _, normalized_text = line.strip().split("|") + filename = str(wav_dir / (filename + ".wav")) + records.append([filename, normalized_text, speaker_name]) + self.records = records + + def __getitem__(self, i): + return self.records[i] + + def __len__(self): + return len(self.records) diff --git a/parakeet/datasets/preprocess_utils.py b/parakeet/datasets/preprocess_utils.py new file mode 100644 index 00000000..ddbedf5c --- /dev/null +++ b/parakeet/datasets/preprocess_utils.py @@ -0,0 +1,187 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import re + + +# speaker|utt_id|phn dur phn dur ... +def get_phn_dur(file_name): + ''' + read MFA duration.txt + Parameters + ---------- + file_name : str or Path + path of gen_duration_from_textgrid.py's result + Returns + ---------- + Dict + sentence: {'utt': ([char], [int])} + ''' + f = open(file_name, 'r') + sentence = {} + speaker_set = set() + for line in f: + line_list = line.strip().split('|') + utt = line_list[0] + speaker = line_list[1] + p_d = line_list[-1] + speaker_set.add(speaker) + phn_dur = p_d.split() + phn = phn_dur[::2] + dur = phn_dur[1::2] + assert len(phn) == len(dur) + sentence[utt] = (phn, [int(i) for i in dur], speaker) + f.close() + return sentence, speaker_set + + +def merge_silence(sentence): + ''' + merge silences + Parameters + ---------- + sentence : Dict + sentence: {'utt': (([char], [int]), str)} + ''' + for utt in sentence: + cur_phn, cur_dur, speaker = sentence[utt] + new_phn = [] + new_dur = [] + + # merge sp and sil + for i, p in enumerate(cur_phn): + if i > 0 and 'sil' == p and cur_phn[i - 1] in {"sil", "sp"}: + new_dur[-1] += cur_dur[i] + new_phn[-1] = 'sil' + else: + new_phn.append(p) + new_dur.append(cur_dur[i]) + + for i, (p, d) in enumerate(zip(new_phn, new_dur)): + if p in {"sp"}: + if d < 14: + new_phn[i] = 'sp' + else: + new_phn[i] = 'spl' + + assert len(new_phn) == len(new_dur) + sentence[utt] = [new_phn, new_dur, speaker] + + +def get_input_token(sentence, output_path, dataset="baker"): + ''' + get phone set from training data and save it + Parameters + ---------- + sentence : Dict + sentence: {'utt': ([char], [int])} + output_path : str or path + path to save phone_id_map + ''' + phn_token = set() + for utt in sentence: + for phn in sentence[utt][0]: + phn_token.add(phn) + phn_token = list(phn_token) + phn_token.sort() + phn_token = ["", ""] + phn_token + if dataset in {"baker", "aishell3"}: + phn_token += ["，", "。", "？", "！"] + else: + phn_token += [",", ".", "?", "!"] + phn_token += [""] + + with open(output_path, 'w') as f: + for i, phn in enumerate(phn_token): + f.write(phn + ' ' + str(i) + '\n') + + +def get_phones_tones(sentence, + phones_output_path, + tones_output_path, + dataset="baker"): + ''' + get phone set and tone set from training data and save it + Parameters + ---------- + sentence : Dict + sentence: {'utt': ([char], [int])} + phones_output_path : str or path + path to save phone_id_map + tones_output_path : str or path + path to save tone_id_map + ''' + phn_token = set() + tone_token = set() + for utt in sentence: + for label in sentence[utt][0]: + # split tone from finals + match = re.match(r'^(\w+)([012345])$', label) + if match: + phn_token.add(match.group(1)) + tone_token.add(match.group(2)) + else: + phn_token.add(label) + tone_token.add('0') + phn_token = list(phn_token) + tone_token = list(tone_token) + phn_token.sort() + tone_token.sort() + phn_token = ["", ""] + phn_token + if dataset in {"baker", "aishell3"}: + phn_token += ["，", "。", "？", "！"] + else: + phn_token += [",", ".", "?", "!"] + phn_token += [""] + + with open(phones_output_path, 'w') as f: + for i, phn in enumerate(phn_token): + f.write(phn + ' ' + str(i) + '\n') + with open(tones_output_path, 'w') as f: + for i, tone in enumerate(tone_token): + f.write(tone + ' ' + str(i) + '\n') + + +def get_spk_id_map(speaker_set, output_path): + speakers = sorted(list(speaker_set)) + with open(output_path, 'w') as f: + for i, spk in enumerate(speakers): + f.write(spk + ' ' + str(i) + '\n') + + +def compare_duration_and_mel_length(sentences, utt, mel): + ''' + check duration error, correct sentences[utt] if possible, else pop sentences[utt] + Parameters + ---------- + sentences : Dict + sentences[utt] = [phones_list ,durations_list] + utt : str + utt_id + mel : np.ndarry + features (num_frames, n_mels) + ''' + + if utt in sentences: + len_diff = mel.shape[0] - sum(sentences[utt][1]) + if len_diff != 0: + if len_diff > 0: + sentences[utt][1][-1] += len_diff + elif sentences[utt][1][-1] + len_diff > 0: + sentences[utt][1][-1] += len_diff + elif sentences[utt][1][0] + len_diff > 0: + sentences[utt][1][0] += len_diff + else: + print("the len_diff is unable to correct:", len_diff) + sentences.pop(utt) diff --git a/parakeet/datasets/vocoder_batch_fn.py b/parakeet/datasets/vocoder_batch_fn.py new file mode 100644 index 00000000..925303b5 --- /dev/null +++ b/parakeet/datasets/vocoder_batch_fn.py @@ -0,0 +1,118 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import numpy as np +import paddle + + +class Clip(object): + """Collate functor for training vocoders. + """ + + def __init__( + self, + batch_max_steps=20480, + hop_size=256, + aux_context_window=0, ): + """Initialize customized collater for DataLoader. + + Parameters + ---------- + batch_max_steps : int + The maximum length of input signal in batch. + hop_size : int + Hop size of auxiliary features. + aux_context_window : int + Context window size for auxiliary feature conv. + + """ + if batch_max_steps % hop_size != 0: + batch_max_steps += -(batch_max_steps % hop_size) + assert batch_max_steps % hop_size == 0 + self.batch_max_steps = batch_max_steps + self.batch_max_frames = batch_max_steps // hop_size + self.hop_size = hop_size + self.aux_context_window = aux_context_window + + # set useful values in random cutting + self.start_offset = aux_context_window + self.end_offset = -(self.batch_max_frames + aux_context_window) + self.mel_threshold = self.batch_max_frames + 2 * aux_context_window + + def __call__(self, examples): + """Convert into batch tensors. + + Parameters + ---------- + batch : list + list of tuple of the pair of audio and features. Audio shape (T, ), features shape(T', C). + + Returns + ---------- + Tensor + Auxiliary feature batch (B, C, T'), where + T = (T' - 2 * aux_context_window) * hop_size. + Tensor + Target signal batch (B, 1, T). + + """ + # check length + examples = [ + self._adjust_length(b['wave'], b['feats']) for b in examples + if b['feats'].shape[0] > self.mel_threshold + ] + xs, cs = [b[0] for b in examples], [b[1] for b in examples] + + # make batch with random cut + c_lengths = [c.shape[0] for c in cs] + start_frames = np.array([ + np.random.randint(self.start_offset, cl + self.end_offset) + for cl in c_lengths + ]) + x_starts = start_frames * self.hop_size + x_ends = x_starts + self.batch_max_steps + + c_starts = start_frames - self.aux_context_window + c_ends = start_frames + self.batch_max_frames + self.aux_context_window + y_batch = np.stack( + [x[start:end] for x, start, end in zip(xs, x_starts, x_ends)]) + c_batch = np.stack( + [c[start:end] for c, start, end in zip(cs, c_starts, c_ends)]) + + # convert each batch to tensor, asuume that each item in batch has the same length + y_batch = paddle.to_tensor( + y_batch, dtype=paddle.float32).unsqueeze(1) # (B, 1, T) + c_batch = paddle.to_tensor( + c_batch, dtype=paddle.float32).transpose([0, 2, 1]) # (B, C, T') + + return y_batch, c_batch + + def _adjust_length(self, x, c): + """Adjust the audio and feature lengths. + + Note + ------- + Basically we assume that the length of x and c are adjusted + through preprocessing stage, but if we use other library processed + features, this process will be needed. + + """ + if len(x) < c.shape[1] * self.hop_size: + x = np.pad(x, (0, c.shape[1] * self.hop_size - len(x)), mode="edge") + + # check the legnth is valid + assert len(x) == c.shape[ + 0] * self.hop_size, f"wave length: ({len(x)}), mel length: ({c.shape[0]})" + + return x, c diff --git a/parakeet/exps/__init__.py b/parakeet/exps/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/parakeet/exps/fastspeech2/__init__.py b/parakeet/exps/fastspeech2/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/parakeet/exps/gan_vocoder/__init__.py b/parakeet/exps/gan_vocoder/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/parakeet/exps/gan_vocoder/pwgan/__init__.py b/parakeet/exps/gan_vocoder/pwgan/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/parakeet/frontend/__init__.py b/parakeet/frontend/__init__.py new file mode 100644 index 00000000..b8779b65 --- /dev/null +++ b/parakeet/frontend/__init__.py @@ -0,0 +1,21 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from .zh_normalization import * +from .generate_lexicon import * +from .normalizer import * +from .phonectic import * +from .punctuation import * +from .tone_sandhi import * +from .vocab import * diff --git a/parakeet/frontend/arpabet.py b/parakeet/frontend/arpabet.py new file mode 100644 index 00000000..ae9212b2 --- /dev/null +++ b/parakeet/frontend/arpabet.py @@ -0,0 +1,302 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from parakeet.frontend.phonectic import Phonetics +""" +A phonology system with ARPABET symbols and limited punctuations. The G2P +conversion is done by g2p_en. + +Note that g2p_en does not handle words with hypen well. So make sure the input +sentence is first normalized. +""" +from parakeet.frontend.vocab import Vocab +from g2p_en import G2p + + +class ARPABET(Phonetics): + """A phonology for English that uses ARPABET as the phoneme vocabulary. + See http://www.speech.cs.cmu.edu/cgi-bin/cmudict for more details. + Phoneme Example Translation + ------- ------- ----------- + AA odd AA D + AE at AE T + AH hut HH AH T + AO ought AO T + AW cow K AW + AY hide HH AY D + B be B IY + CH cheese CH IY Z + D dee D IY + DH thee DH IY + EH Ed EH D + ER hurt HH ER T + EY ate EY T + F fee F IY + G green G R IY N + HH he HH IY + IH it IH T + IY eat IY T + JH gee JH IY + K key K IY + L lee L IY + M me M IY + N knee N IY + NG ping P IH NG + OW oat OW T + OY toy T OY + P pee P IY + R read R IY D + S sea S IY + SH she SH IY + T tea T IY + TH theta TH EY T AH + UH hood HH UH D + UW two T UW + V vee V IY + W we W IY + Y yield Y IY L D + Z zee Z IY + ZH seizure S IY ZH ER + """ + phonemes = [ + 'AA', 'AE', 'AH', 'AO', 'AW', 'AY', 'B', 'CH', 'D', 'DH', 'EH', 'ER', + 'EY', 'F', 'G', 'HH', 'IH', 'IY', 'JH', 'K', 'L', 'M', 'N', 'NG', 'OW', + 'OY', 'P', 'R', 'S', 'SH', 'T', 'TH', 'UW', 'UH', 'V', 'W', 'Y', 'Z', + 'ZH' + ] + punctuations = [',', '.', '?', '!'] + symbols = phonemes + punctuations + _stress_to_no_stress_ = { + 'AA0': 'AA', + 'AA1': 'AA', + 'AA2': 'AA', + 'AE0': 'AE', + 'AE1': 'AE', + 'AE2': 'AE', + 'AH0': 'AH', + 'AH1': 'AH', + 'AH2': 'AH', + 'AO0': 'AO', + 'AO1': 'AO', + 'AO2': 'AO', + 'AW0': 'AW', + 'AW1': 'AW', + 'AW2': 'AW', + 'AY0': 'AY', + 'AY1': 'AY', + 'AY2': 'AY', + 'EH0': 'EH', + 'EH1': 'EH', + 'EH2': 'EH', + 'ER0': 'ER', + 'ER1': 'ER', + 'ER2': 'ER', + 'EY0': 'EY', + 'EY1': 'EY', + 'EY2': 'EY', + 'IH0': 'IH', + 'IH1': 'IH', + 'IH2': 'IH', + 'IY0': 'IY', + 'IY1': 'IY', + 'IY2': 'IY', + 'OW0': 'OW', + 'OW1': 'OW', + 'OW2': 'OW', + 'OY0': 'OY', + 'OY1': 'OY', + 'OY2': 'OY', + 'UH0': 'UH', + 'UH1': 'UH', + 'UH2': 'UH', + 'UW0': 'UW', + 'UW1': 'UW', + 'UW2': 'UW' + } + + def __init__(self): + self.backend = G2p() + self.vocab = Vocab(self.phonemes + self.punctuations) + + def _remove_vowels(self, phone): + return self._stress_to_no_stress_.get(phone, phone) + + def phoneticize(self, sentence, add_start_end=False): + """ Normalize the input text sequence and convert it into pronunciation sequence. + + Parameters + ----------- + sentence: str + The input text sequence. + + Returns + ---------- + List[str] + The list of pronunciation sequence. + """ + phonemes = [ + self._remove_vowels(item) for item in self.backend(sentence) + ] + if add_start_end: + start = self.vocab.start_symbol + end = self.vocab.end_symbol + phonemes = [start] + phonemes + [end] + phonemes = [item for item in phonemes if item in self.vocab.stoi] + return phonemes + + def numericalize(self, phonemes): + """ Convert pronunciation sequence into pronunciation id sequence. + + Parameters + ----------- + phonemes: List[str] + The list of pronunciation sequence. + + Returns + ---------- + List[int] + The list of pronunciation id sequence. + """ + ids = [self.vocab.lookup(item) for item in phonemes] + return ids + + def reverse(self, ids): + """ Reverse the list of pronunciation id sequence to a list of pronunciation sequence. + + Parameters + ----------- + ids: List[int] + The list of pronunciation id sequence. + + Returns + ---------- + List[str] + The list of pronunciation sequence. + """ + return [self.vocab.reverse(i) for i in ids] + + def __call__(self, sentence, add_start_end=False): + """ Convert the input text sequence into pronunciation id sequence. + + Parameters + ----------- + sentence: str + The input text sequence. + + Returns + ---------- + List[str] + The list of pronunciation id sequence. + """ + return self.numericalize( + self.phoneticize(sentence, add_start_end=add_start_end)) + + @property + def vocab_size(self): + """ Vocab size. + """ + # 47 = 39 phones + 4 punctuations + 4 special tokens + return len(self.vocab) + + +class ARPABETWithStress(Phonetics): + phonemes = [ + 'AA0', 'AA1', 'AA2', 'AE0', 'AE1', 'AE2', 'AH0', 'AH1', 'AH2', 'AO0', + 'AO1', 'AO2', 'AW0', 'AW1', 'AW2', 'AY0', 'AY1', 'AY2', 'B', 'CH', 'D', + 'DH', 'EH0', 'EH1', 'EH2', 'ER0', 'ER1', 'ER2', 'EY0', 'EY1', 'EY2', + 'F', 'G', 'HH', 'IH0', 'IH1', 'IH2', 'IY0', 'IY1', 'IY2', 'JH', 'K', + 'L', 'M', 'N', 'NG', 'OW0', 'OW1', 'OW2', 'OY0', 'OY1', 'OY2', 'P', 'R', + 'S', 'SH', 'T', 'TH', 'UH0', 'UH1', 'UH2', 'UW0', 'UW1', 'UW2', 'V', + 'W', 'Y', 'Z', 'ZH' + ] + punctuations = [',', '.', '?', '!'] + symbols = phonemes + punctuations + + def __init__(self): + self.backend = G2p() + self.vocab = Vocab(self.phonemes + self.punctuations) + + def phoneticize(self, sentence, add_start_end=False): + """ Normalize the input text sequence and convert it into pronunciation sequence. + + Parameters + ----------- + sentence: str + The input text sequence. + + Returns + ---------- + List[str] + The list of pronunciation sequence. + """ + phonemes = self.backend(sentence) + if add_start_end: + start = self.vocab.start_symbol + end = self.vocab.end_symbol + phonemes = [start] + phonemes + [end] + phonemes = [item for item in phonemes if item in self.vocab.stoi] + return phonemes + + def numericalize(self, phonemes): + """ Convert pronunciation sequence into pronunciation id sequence. + + Parameters + ----------- + phonemes: List[str] + The list of pronunciation sequence. + + Returns + ---------- + List[int] + The list of pronunciation id sequence. + """ + ids = [self.vocab.lookup(item) for item in phonemes] + return ids + + def reverse(self, ids): + """ Reverse the list of pronunciation id sequence to a list of pronunciation sequence. + + Parameters + ----------- + ids: List[int] + The list of pronunciation id sequence. + + Returns + ---------- + List[str] + The list of pronunciation sequence. + """ + return [self.vocab.reverse(i) for i in ids] + + def __call__(self, sentence, add_start_end=False): + """ Convert the input text sequence into pronunciation id sequence. + + Parameters + ----------- + sentence: str + The input text sequence. + + Returns + ---------- + List[str] + The list of pronunciation id sequence. + """ + return self.numericalize( + self.phoneticize(sentence, add_start_end=add_start_end)) + + @property + def vocab_size(self): + """ Vocab size. + """ + # 77 = 69 phones + 4 punctuations + 4 special tokens + return len(self.vocab) diff --git a/parakeet/frontend/generate_lexicon.py b/parakeet/frontend/generate_lexicon.py new file mode 100644 index 00000000..155e1591 --- /dev/null +++ b/parakeet/frontend/generate_lexicon.py @@ -0,0 +1,157 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Generate lexicon and symbols for Mandarin Chinese phonology. +The lexicon is used for Montreal Force Aligner. +Note that syllables are used as word in this lexicon. Since syllables rather +than words are used in transcriptions produced by `reorganize_baker.py`. +We make this choice to better leverage other software for chinese text to +pinyin tools like pypinyin. This is the convention for G2P in Chinese. +""" +import re +from collections import OrderedDict + +INITIALS = [ + 'b', 'p', 'm', 'f', 'd', 't', 'n', 'l', 'g', 'k', 'h', 'zh', 'ch', 'sh', + 'r', 'z', 'c', 's', 'j', 'q', 'x' +] + +FINALS = [ + 'a', 'ai', 'ao', 'an', 'ang', 'e', 'er', 'ei', 'en', 'eng', 'o', 'ou', + 'ong', 'ii', 'iii', 'i', 'ia', 'iao', 'ian', 'iang', 'ie', 'io', 'iou', + 'iong', 'in', 'ing', 'u', 'ua', 'uai', 'uan', 'uang', 'uei', 'uo', 'uen', + 'ueng', 'v', 've', 'van', 'vn' +] + +SPECIALS = ['sil', 'sp'] + + +def rule(C, V, R, T): + """Generate a syllable given the initial, the final, erhua indicator, and tone. + Orthographical rules for pinyin are applied. (special case for y, w, ui, un, iu) + + Note that in this system, 'ü' is alway written as 'v' when appeared in phoneme, but converted to + 'u' in syllables when certain conditions are satisfied. + + 'i' is distinguished when appeared in phonemes, and separated into 3 categories, 'i', 'ii' and 'iii'. + Erhua is is possibly applied to every finals, except for finals that already ends with 'r'. + When a syllable is impossible or does not have any characters with this pronunciation, return None + to filter it out. + """ + + # 不可拼的音节, ii 只能和 z, c, s 拼 + if V in ["ii"] and (C not in ['z', 'c', 's']): + return None + # iii 只能和 zh, ch, sh, r 拼 + if V in ['iii'] and (C not in ['zh', 'ch', 'sh', 'r']): + return None + + # 齐齿呼或者撮口呼不能和 f, g, k, h, zh, ch, sh, r, z, c, s + if (V not in ['ii', 'iii']) and V[0] in ['i', 'v'] and ( + C in ['f', 'g', 'k', 'h', 'zh', 'ch', 'sh', 'r', 'z', 'c', 's']): + return None + + # 撮口呼只能和 j, q, x l, n 拼 + if V.startswith("v"): + # v, ve 只能和 j ,q , x, n, l 拼 + if V in ['v', 've']: + if C not in ['j', 'q', 'x', 'n', 'l', '']: + return None + # 其他只能和 j, q, x 拼 + else: + if C not in ['j', 'q', 'x', '']: + return None + + # j, q, x 只能和齐齿呼或者撮口呼拼 + if (C in ['j', 'q', 'x']) and not ( + (V not in ['ii', 'iii']) and V[0] in ['i', 'v']): + return None + + # b, p ,m, f 不能和合口呼拼，除了 u 之外 + # bm p, m, f 不能和撮口呼拼 + if (C in ['b', 'p', 'm', 'f']) and ((V[0] in ['u', 'v'] and V != "u") or + V == 'ong'): + return None + + # ua, uai, uang 不能和 d, t, n, l, r, z, c, s 拼 + if V in ['ua', 'uai', + 'uang'] and C in ['d', 't', 'n', 'l', 'r', 'z', 'c', 's']: + return None + + # sh 和 ong 不能拼 + if V == 'ong' and C in ['sh']: + return None + + # o 和 gkh, zh ch sh r z c s 不能拼 + if V == "o" and C in [ + 'd', 't', 'n', 'g', 'k', 'h', 'zh', 'ch', 'sh', 'r', 'z', 'c', 's' + ]: + return None + + # ueng 只是 weng 这个 ad-hoc 其他情况下都是 ong + if V == 'ueng' and C != '': + return + + # 非儿化的 er 只能单独存在 + if V == 'er' and C != '': + return None + + if C == '': + if V in ["i", "in", "ing"]: + C = 'y' + elif V == 'u': + C = 'w' + elif V.startswith('i') and V not in ["ii", "iii"]: + C = 'y' + V = V[1:] + elif V.startswith('u'): + C = 'w' + V = V[1:] + elif V.startswith('v'): + C = 'yu' + V = V[1:] + else: + if C in ['j', 'q', 'x']: + if V.startswith('v'): + V = re.sub('v', 'u', V) + if V == 'iou': + V = 'iu' + elif V == 'uei': + V = 'ui' + elif V == 'uen': + V = 'un' + result = C + V + + # Filter er 不能再儿化 + if result.endswith('r') and R == 'r': + return None + + # ii and iii, change back to i + result = re.sub(r'i+', 'i', result) + + result = result + R + T + return result + + +def generate_lexicon(with_tone=False, with_erhua=False): + """Generate lexicon for Mandarin Chinese.""" + syllables = OrderedDict() + + for C in [''] + INITIALS: + for V in FINALS: + for R in [''] if not with_erhua else ['', 'r']: + for T in [''] if not with_tone else ['1', '2', '3', '4', '5']: + result = rule(C, V, R, T) + if result: + syllables[result] = f'{C} {V}{R}{T}' + return syllables diff --git a/parakeet/frontend/normalizer/__init__.py b/parakeet/frontend/normalizer/__init__.py new file mode 100644 index 00000000..37fd5806 --- /dev/null +++ b/parakeet/frontend/normalizer/__init__.py @@ -0,0 +1,16 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from parakeet.frontend.normalizer.normalizer import * +from parakeet.frontend.normalizer.numbers import * diff --git a/parakeet/frontend/normalizer/abbrrviation.py b/parakeet/frontend/normalizer/abbrrviation.py new file mode 100644 index 00000000..abf198b9 --- /dev/null +++ b/parakeet/frontend/normalizer/abbrrviation.py @@ -0,0 +1,13 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/parakeet/frontend/normalizer/acronyms.py b/parakeet/frontend/normalizer/acronyms.py new file mode 100644 index 00000000..abf198b9 --- /dev/null +++ b/parakeet/frontend/normalizer/acronyms.py @@ -0,0 +1,13 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/parakeet/frontend/normalizer/normalizer.py b/parakeet/frontend/normalizer/normalizer.py new file mode 100644 index 00000000..795607e5 --- /dev/null +++ b/parakeet/frontend/normalizer/normalizer.py @@ -0,0 +1,34 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import re +import unicodedata +from builtins import str as unicode + +from parakeet.frontend.normalizer.numbers import normalize_numbers + + +def normalize(sentence): + """ Normalize English text. + """ + # preprocessing + sentence = unicode(sentence) + sentence = normalize_numbers(sentence) + sentence = ''.join( + char for char in unicodedata.normalize('NFD', sentence) + if unicodedata.category(char) != 'Mn') # Strip accents + sentence = sentence.lower() + sentence = re.sub(r"[^ a-z'.,?!\-]", "", sentence) + sentence = sentence.replace("i.e.", "that is") + sentence = sentence.replace("e.g.", "for example") + return sentence diff --git a/parakeet/frontend/normalizer/numbers.py b/parakeet/frontend/normalizer/numbers.py new file mode 100644 index 00000000..564fb9b6 --- /dev/null +++ b/parakeet/frontend/normalizer/numbers.py @@ -0,0 +1,86 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# number expansion is not that easy +import re + +import inflect + +_inflect = inflect.engine() +_comma_number_re = re.compile(r'([0-9][0-9\,]+[0-9])') +_decimal_number_re = re.compile(r'([0-9]+\.[0-9]+)') +_pounds_re = re.compile(r'£([0-9\,]*[0-9]+)') +_dollars_re = re.compile(r'\$([0-9\.\,]*[0-9]+)') +_ordinal_re = re.compile(r'[0-9]+(st|nd|rd|th)') +_number_re = re.compile(r'[0-9]+') + + +def _remove_commas(m): + return m.group(1).replace(',', '') + + +def _expand_decimal_point(m): + return m.group(1).replace('.', ' point ') + + +def _expand_dollars(m): + match = m.group(1) + parts = match.split('.') + if len(parts) > 2: + return match + ' dollars' # Unexpected format + dollars = int(parts[0]) if parts[0] else 0 + cents = int(parts[1]) if len(parts) > 1 and parts[1] else 0 + if dollars and cents: + dollar_unit = 'dollar' if dollars == 1 else 'dollars' + cent_unit = 'cent' if cents == 1 else 'cents' + return '%s %s, %s %s' % (dollars, dollar_unit, cents, cent_unit) + elif dollars: + dollar_unit = 'dollar' if dollars == 1 else 'dollars' + return '%s %s' % (dollars, dollar_unit) + elif cents: + cent_unit = 'cent' if cents == 1 else 'cents' + return '%s %s' % (cents, cent_unit) + else: + return 'zero dollars' + + +def _expand_ordinal(m): + return _inflect.number_to_words(m.group(0)) + + +def _expand_number(m): + num = int(m.group(0)) + if num > 1000 and num < 3000: + if num == 2000: + return 'two thousand' + elif num > 2000 and num < 2010: + return 'two thousand ' + _inflect.number_to_words(num % 100) + elif num % 100 == 0: + return _inflect.number_to_words(num // 100) + ' hundred' + else: + return _inflect.number_to_words( + num, andword='', zero='oh', group=2).replace(', ', ' ') + else: + return _inflect.number_to_words(num, andword='') + + +def normalize_numbers(text): + """ Normalize numbers in English text. + """ + text = re.sub(_comma_number_re, _remove_commas, text) + text = re.sub(_pounds_re, r'\1 pounds', text) + text = re.sub(_dollars_re, _expand_dollars, text) + text = re.sub(_decimal_number_re, _expand_decimal_point, text) + text = re.sub(_ordinal_re, _expand_ordinal, text) + text = re.sub(_number_re, _expand_number, text) + return text diff --git a/parakeet/frontend/normalizer/width.py b/parakeet/frontend/normalizer/width.py new file mode 100644 index 00000000..d655e927 --- /dev/null +++ b/parakeet/frontend/normalizer/width.py @@ -0,0 +1,40 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + + +def full2half_width(ustr): + half = [] + for u in ustr: + num = ord(u) + if num == 0x3000: # 全角空格变半角 + num = 32 + elif 0xFF01 <= num <= 0xFF5E: + num -= 0xfee0 + u = chr(num) + half.append(u) + return ''.join(half) + + +def half2full_width(ustr): + full = [] + for u in ustr: + num = ord(u) + if num == 32: # 半角空格变全角 + num = 0x3000 + elif 0x21 <= num <= 0x7E: + num += 0xfee0 + u = chr(num) # to unicode + full.append(u) + + return ''.join(full) diff --git a/parakeet/frontend/phonectic.py b/parakeet/frontend/phonectic.py new file mode 100644 index 00000000..23662254 --- /dev/null +++ b/parakeet/frontend/phonectic.py @@ -0,0 +1,314 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from abc import ABC +from abc import abstractmethod + +from g2p_en import G2p +from g2pM import G2pM + +from parakeet.frontend.vocab import Vocab +from parakeet.frontend.normalizer.normalizer import normalize +from parakeet.frontend.punctuation import get_punctuations + +# discard opencc untill we find an easy solution to install it on windows +# from opencc import OpenCC + +__all__ = ["Phonetics", "English", "EnglishCharacter", "Chinese"] + + +class Phonetics(ABC): + @abstractmethod + def __call__(self, sentence): + pass + + @abstractmethod + def phoneticize(self, sentence): + pass + + @abstractmethod + def numericalize(self, phonemes): + pass + + +class English(Phonetics): + """ Normalize the input text sequence and convert into pronunciation id sequence. + """ + + def __init__(self): + self.backend = G2p() + self.phonemes = list(self.backend.phonemes) + self.punctuations = get_punctuations("en") + self.vocab = Vocab(self.phonemes + self.punctuations) + + def phoneticize(self, sentence): + """ Normalize the input text sequence and convert it into pronunciation sequence. + + Parameters + ----------- + sentence: str + The input text sequence. + + Returns + ---------- + List[str] + The list of pronunciation sequence. + """ + start = self.vocab.start_symbol + end = self.vocab.end_symbol + phonemes = ([] if start is None else [start]) \ + + self.backend(sentence) \ + + ([] if end is None else [end]) + phonemes = [item for item in phonemes if item in self.vocab.stoi] + return phonemes + + def numericalize(self, phonemes): + """ Convert pronunciation sequence into pronunciation id sequence. + + Parameters + ----------- + phonemes: List[str] + The list of pronunciation sequence. + + Returns + ---------- + List[int] + The list of pronunciation id sequence. + """ + ids = [ + self.vocab.lookup(item) for item in phonemes + if item in self.vocab.stoi + ] + return ids + + def reverse(self, ids): + """ Reverse the list of pronunciation id sequence to a list of pronunciation sequence. + + Parameters + ----------- + ids: List[int] + The list of pronunciation id sequence. + + Returns + ---------- + List[str] + The list of pronunciation sequence. + """ + return [self.vocab.reverse(i) for i in ids] + + def __call__(self, sentence): + """ Convert the input text sequence into pronunciation id sequence. + + Parameters + ----------- + sentence: str + The input text sequence. + + Returns + ---------- + List[str] + The list of pronunciation id sequence. + """ + return self.numericalize(self.phoneticize(sentence)) + + @property + def vocab_size(self): + """ Vocab size. + """ + return len(self.vocab) + + +class EnglishCharacter(Phonetics): + """ Normalize the input text sequence and convert it into character id sequence. + """ + + def __init__(self): + self.backend = G2p() + self.graphemes = list(self.backend.graphemes) + self.punctuations = get_punctuations("en") + self.vocab = Vocab(self.graphemes + self.punctuations) + + def phoneticize(self, sentence): + """ Normalize the input text sequence. + + Parameters + ----------- + sentence: str + The input text sequence. + + Returns + ---------- + str + A text sequence after normalize. + """ + words = normalize(sentence) + return words + + def numericalize(self, sentence): + """ Convert a text sequence into ids. + + Parameters + ----------- + sentence: str + The input text sequence. + + Returns + ---------- + List[int] + List of a character id sequence. + """ + ids = [ + self.vocab.lookup(item) for item in sentence + if item in self.vocab.stoi + ] + return ids + + def reverse(self, ids): + """ Convert a character id sequence into text. + + Parameters + ----------- + ids: List[int] + List of a character id sequence. + + Returns + ---------- + str + The input text sequence. + + """ + return [self.vocab.reverse(i) for i in ids] + + def __call__(self, sentence): + """ Normalize the input text sequence and convert it into character id sequence. + Parameters + ----------- + sentence: str + The input text sequence. + + Returns + ---------- + List[int] + List of a character id sequence. + """ + return self.numericalize(self.phoneticize(sentence)) + + @property + def vocab_size(self): + """ Vocab size. + """ + return len(self.vocab) + + +class Chinese(Phonetics): + """Normalize Chinese text sequence and convert it into ids. + """ + + def __init__(self): + # self.opencc_backend = OpenCC('t2s.json') + self.backend = G2pM() + self.phonemes = self._get_all_syllables() + self.punctuations = get_punctuations("cn") + self.vocab = Vocab(self.phonemes + self.punctuations) + + def _get_all_syllables(self): + all_syllables = set([ + syllable for k, v in self.backend.cedict.items() for syllable in v + ]) + return list(all_syllables) + + def phoneticize(self, sentence): + """ Normalize the input text sequence and convert it into pronunciation sequence. + + Parameters + ----------- + sentence: str + The input text sequence. + + Returns + ---------- + List[str] + The list of pronunciation sequence. + """ + # simplified = self.opencc_backend.convert(sentence) + simplified = sentence + phonemes = self.backend(simplified) + start = self.vocab.start_symbol + end = self.vocab.end_symbol + phonemes = ([] if start is None else [start]) \ + + phonemes \ + + ([] if end is None else [end]) + return self._filter_symbols(phonemes) + + def _filter_symbols(self, phonemes): + cleaned_phonemes = [] + for item in phonemes: + if item in self.vocab.stoi: + cleaned_phonemes.append(item) + else: + for char in item: + if char in self.vocab.stoi: + cleaned_phonemes.append(char) + return cleaned_phonemes + + def numericalize(self, phonemes): + """ Convert pronunciation sequence into pronunciation id sequence. + + Parameters + ----------- + phonemes: List[str] + The list of pronunciation sequence. + + Returns + ---------- + List[int] + The list of pronunciation id sequence. + """ + ids = [self.vocab.lookup(item) for item in phonemes] + return ids + + def __call__(self, sentence): + """ Convert the input text sequence into pronunciation id sequence. + + Parameters + ----------- + sentence: str + The input text sequence. + + Returns + ---------- + List[str] + The list of pronunciation id sequence. + """ + return self.numericalize(self.phoneticize(sentence)) + + @property + def vocab_size(self): + """ Vocab size. + """ + return len(self.vocab) + + def reverse(self, ids): + """ Reverse the list of pronunciation id sequence to a list of pronunciation sequence. + + Parameters + ----------- + ids: List[int] + The list of pronunciation id sequence. + + Returns + ---------- + List[str] + The list of pronunciation sequence. + """ + return [self.vocab.reverse(i) for i in ids] diff --git a/parakeet/frontend/pinyin.py b/parakeet/frontend/pinyin.py new file mode 100644 index 00000000..503bfd5d --- /dev/null +++ b/parakeet/frontend/pinyin.py @@ -0,0 +1,333 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" +A Simple Chinese Phonology using pinyin symbols. +The G2P conversion converts pinyin string to symbols. Also it can handle string +in Chinese chracters, but due to the complexity of chinese G2P, we can leave +text -> pinyin to other part of a TTS system. Other NLP techniques may be used +(e.g. tokenization, tagging, NER...) +""" +import re +from itertools import product + +from pypinyin.contrib.neutral_tone import NeutralToneWith5Mixin +from pypinyin.core import DefaultConverter +from pypinyin.core import Pinyin +from pypinyin.core import Style + +from parakeet.frontend.phonectic import Phonetics +from parakeet.frontend.vocab import Vocab + +_punctuations = ['，', '。', '？', '！'] +_initials = [ + 'b', 'p', 'm', 'f', 'd', 't', 'n', 'l', 'g', 'k', 'h', 'j', 'q', 'x', 'zh', + 'ch', 'sh', 'r', 'z', 'c', 's' +] +_finals = [ + 'ii', 'iii', 'a', 'o', 'e', 'ea', 'ai', 'ei', 'ao', 'ou', 'an', 'en', 'ang', + 'eng', 'er', 'i', 'ia', 'io', 'ie', 'iai', 'iao', 'iou', 'ian', 'ien', + 'iang', 'ieng', 'u', 'ua', 'uo', 'uai', 'uei', 'uan', 'uen', 'uang', 'ueng', + 'v', 've', 'van', 'ven', 'veng' +] +_ernized_symbol = ['&r'] +_phones = _initials + _finals + _ernized_symbol + _punctuations +_tones = ['0', '1', '2', '3', '4', '5'] + +_toned_finals = [final + tone for final, tone in product(_finals, _tones[1:])] +_toned_phonems = _initials + _toned_finals + _ernized_symbol + _punctuations + + +class ParakeetConverter(NeutralToneWith5Mixin, DefaultConverter): + pass + + +class ParakeetPinyin(Phonetics): + def __init__(self): + self.vocab_phonemes = Vocab(_phones) + self.vocab_tones = Vocab(_tones) + self.pinyin_backend = Pinyin(ParakeetConverter()) + + def convert_pypinyin_tone3(self, syllables, add_start_end=False): + phonemes, tones = _convert_to_parakeet_style_pinyin(syllables) + + if add_start_end: + start = self.vocab_phonemes.start_symbol + end = self.vocab_phonemes.end_symbol + phonemes = [start] + phonemes + [end] + + start = self.vocab_tones.start_symbol + end = self.vocab_tones.end_symbol + phonemes = [start] + tones + [end] + + phonemes = [ + item for item in phonemes if item in self.vocab_phonemes.stoi + ] + tones = [item for item in tones if item in self.vocab_tones.stoi] + return phonemes, tones + + def phoneticize(self, sentence, add_start_end=False): + """ Normalize the input text sequence and convert it into pronunciation sequence. + + Parameters + ----------- + sentence: str + The input text sequence. + + Returns + ---------- + List[str] + The list of pronunciation sequence. + """ + syllables = self.pinyin_backend.lazy_pinyin( + sentence, style=Style.TONE3, strict=True) + phonemes, tones = self.convert_pypinyin_tone3( + syllables, add_start_end=add_start_end) + return phonemes, tones + + def numericalize(self, phonemes, tones): + """ Convert pronunciation sequence into pronunciation id sequence. + + Parameters + ----------- + phonemes: List[str] + The list of pronunciation sequence. + + Returns + ---------- + List[int] + The list of pronunciation id sequence. + """ + phoneme_ids = [self.vocab_phonemes.lookup(item) for item in phonemes] + tone_ids = [self.vocab_tones.lookup(item) for item in tones] + return phoneme_ids, tone_ids + + def __call__(self, sentence, add_start_end=False): + """ Convert the input text sequence into pronunciation id sequence. + + Parameters + ----------- + sentence: str + The input text sequence. + + Returns + ---------- + List[str] + The list of pronunciation id sequence. + """ + phonemes, tones = self.phoneticize( + sentence, add_start_end=add_start_end) + phoneme_ids, tone_ids = self.numericalize(phonemes, tones) + return phoneme_ids, tone_ids + + @property + def vocab_size(self): + """ Vocab size. + """ + # 70 = 62 phones + 4 punctuations + 4 special tokens + return len(self.vocab_phonemes) + + @property + def tone_vocab_size(self): + # 10 = 1 non tone + 5 tone + 4 special tokens + return len(self.vocab_tones) + + +class ParakeetPinyinWithTone(Phonetics): + def __init__(self): + self.vocab = Vocab(_toned_phonems) + self.pinyin_backend = Pinyin(ParakeetConverter()) + + def convert_pypinyin_tone3(self, syllables, add_start_end=False): + phonemes = _convert_to_parakeet_style_pinyin_with_tone(syllables) + + if add_start_end: + start = self.vocab_phonemes.start_symbol + end = self.vocab_phonemes.end_symbol + phonemes = [start] + phonemes + [end] + + phonemes = [item for item in phonemes if item in self.vocab.stoi] + return phonemes + + def phoneticize(self, sentence, add_start_end=False): + """ Normalize the input text sequence and convert it into pronunciation sequence. + + Parameters + ----------- + sentence: str + The input text sequence. + + Returns + ---------- + List[str] + The list of pronunciation sequence. + """ + syllables = self.pinyin_backend.lazy_pinyin( + sentence, style=Style.TONE3, strict=True) + phonemes = self.convert_pypinyin_tone3( + syllables, add_start_end=add_start_end) + return phonemes + + def numericalize(self, phonemes): + """ Convert pronunciation sequence into pronunciation id sequence. + + Parameters + ----------- + phonemes: List[str] + The list of pronunciation sequence. + + Returns + ---------- + List[int] + The list of pronunciation id sequence. + """ + phoneme_ids = [self.vocab.lookup(item) for item in phonemes] + return phoneme_ids + + def __call__(self, sentence, add_start_end=False): + """ Convert the input text sequence into pronunciation id sequence. + + Parameters + ----------- + sentence: str + The input text sequence. + + Returns + ---------- + List[str] + The list of pronunciation id sequence. + """ + phonemes = self.phoneticize(sentence, add_start_end=add_start_end) + phoneme_ids = self.numericalize(phonemes) + return phoneme_ids + + @property + def vocab_size(self): + """ Vocab size. + """ + # 230 = 222 phones + 4 punctuations + 4 special tokens + return len(self.vocab) + + +def _convert_to_parakeet_convension(syllable): + # from pypinyin.Style.TONE3 to parakeet convension + tone = syllable[-1] + syllable = syllable[:-1] + + # expansion of o -> uo + syllable = re.sub(r"([bpmf])o$", r"\1uo", syllable) + + # expansion for iong, ong + syllable = syllable.replace("iong", "veng").replace("ong", "ueng") + + # expansion for ing, in + syllable = syllable.replace("ing", "ieng").replace("in", "ien") + + # expansion for un, ui, iu + syllable = syllable.replace("un", "uen") \ + .replace("ui", "uei") \ + .replace("iu", "iou") + + # rule for variants of i + syllable = syllable.replace("zi", "zii") \ + .replace("ci", "cii") \ + .replace("si", "sii") \ + .replace("zhi", "zhiii") \ + .replace("chi", "chiii") \ + .replace("shi", "shiii") \ + .replace("ri", "riii") + + # rule for y preceding i, u + syllable = syllable.replace("yi", "i").replace("yu", "v").replace("y", "i") + + # rule for w + syllable = syllable.replace("wu", "u").replace("w", "u") + + # rule for v following j, q, x + syllable = syllable.replace("ju", "jv") \ + .replace("qu", "qv") \ + .replace("xu", "xv") + + return syllable + tone + + +def _split_syllable(syllable: str): + global _punctuations + + if syllable in _punctuations: + # syllables, tones + return [syllable], ['0'] + + syllable = _convert_to_parakeet_convension(syllable) + + tone = syllable[-1] + syllable = syllable[:-1] + + phones = [] + tones = [] + + global _initials + if syllable[:2] in _initials: + phones.append(syllable[:2]) + tones.append('0') + phones.append(syllable[2:]) + tones.append(tone) + elif syllable[0] in _initials: + phones.append(syllable[0]) + tones.append('0') + phones.append(syllable[1:]) + tones.append(tone) + else: + phones.append(syllable) + tones.append(tone) + return phones, tones + + +def _convert_to_parakeet_style_pinyin(syllables): + phones, tones = [], [] + for syllable in syllables: + p, t = _split_syllable(syllable) + phones.extend(p) + tones.extend(t) + return phones, tones + + +def _split_syllable_with_tone(syllable: str): + global _punctuations + + if syllable in _punctuations: + # syllables + return [syllable] + + syllable = _convert_to_parakeet_convension(syllable) + + phones = [] + + global _initials + if syllable[:2] in _initials: + phones.append(syllable[:2]) + phones.append(syllable[2:]) + elif syllable[0] in _initials: + phones.append(syllable[0]) + phones.append(syllable[1:]) + else: + phones.append(syllable) + return phones + + +def _convert_to_parakeet_style_pinyin_with_tone(syllables): + phones = [] + for syllable in syllables: + p = _split_syllable_with_tone(syllable) + phones.extend(p) + return phones diff --git a/parakeet/frontend/punctuation.py b/parakeet/frontend/punctuation.py new file mode 100644 index 00000000..23636dc5 --- /dev/null +++ b/parakeet/frontend/punctuation.py @@ -0,0 +1,36 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +__all__ = ["get_punctuations"] + +EN_PUNCT = [ + " ", + "-", + "...", + ",", + ".", + "?", + "!", +] + +CN_PUNCT = ["、", "，", "；", "：", "。", "？", "！"] + + +def get_punctuations(lang): + if lang == "en": + return EN_PUNCT + elif lang == "cn": + return CN_PUNCT + else: + raise ValueError(f"language {lang} Not supported") diff --git a/parakeet/frontend/tone_sandhi.py b/parakeet/frontend/tone_sandhi.py new file mode 100644 index 00000000..6ba567bb --- /dev/null +++ b/parakeet/frontend/tone_sandhi.py @@ -0,0 +1,343 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from typing import List +from typing import Tuple + +import jieba +from pypinyin import lazy_pinyin +from pypinyin import Style + + +class ToneSandhi(): + def __init__(self): + self.must_neural_tone_words = { + '麻烦', '麻利', '鸳鸯', '高粱', '骨头', '骆驼', '马虎', '首饰', '馒头', '馄饨', '风筝', + '难为', '队伍', '阔气', '闺女', '门道', '锄头', '铺盖', '铃铛', '铁匠', '钥匙', '里脊', + '里头', '部分', '那么', '道士', '造化', '迷糊', '连累', '这么', '这个', '运气', '过去', + '软和', '转悠', '踏实', '跳蚤', '跟头', '趔趄', '财主', '豆腐', '讲究', '记性', '记号', + '认识', '规矩', '见识', '裁缝', '补丁', '衣裳', '衣服', '衙门', '街坊', '行李', '行当', + '蛤蟆', '蘑菇', '薄荷', '葫芦', '葡萄', '萝卜', '荸荠', '苗条', '苗头', '苍蝇', '芝麻', + '舒服', '舒坦', '舌头', '自在', '膏药', '脾气', '脑袋', '脊梁', '能耐', '胳膊', '胭脂', + '胡萝', '胡琴', '胡同', '聪明', '耽误', '耽搁', '耷拉', '耳朵', '老爷', '老实', '老婆', + '老头', '老太', '翻腾', '罗嗦', '罐头', '编辑', '结实', '红火', '累赘', '糨糊', '糊涂', + '精神', '粮食', '簸箕', '篱笆', '算计', '算盘', '答应', '笤帚', '笑语', '笑话', '窟窿', + '窝囊', '窗户', '稳当', '稀罕', '称呼', '秧歌', '秀气', '秀才', '福气', '祖宗', '砚台', + '码头', '石榴', '石头', '石匠', '知识', '眼睛', '眯缝', '眨巴', '眉毛', '相声', '盘算', + '白净', '痢疾', '痛快', '疟疾', '疙瘩', '疏忽', '畜生', '生意', '甘蔗', '琵琶', '琢磨', + '琉璃', '玻璃', '玫瑰', '玄乎', '狐狸', '状元', '特务', '牲口', '牙碜', '牌楼', '爽快', + '爱人', '热闹', '烧饼', '烟筒', '烂糊', '点心', '炊帚', '灯笼', '火候', '漂亮', '滑溜', + '溜达', '温和', '清楚', '消息', '浪头', '活泼', '比方', '正经', '欺负', '模糊', '槟榔', + '棺材', '棒槌', '棉花', '核桃', '栅栏', '柴火', '架势', '枕头', '枇杷', '机灵', '本事', + '木头', '木匠', '朋友', '月饼', '月亮', '暖和', '明白', '时候', '新鲜', '故事', '收拾', + '收成', '提防', '挖苦', '挑剔', '指甲', '指头', '拾掇', '拳头', '拨弄', '招牌', '招呼', + '抬举', '护士', '折腾', '扫帚', '打量', '打算', '打点', '打扮', '打听', '打发', '扎实', + '扁担', '戒指', '懒得', '意识', '意思', '情形', '悟性', '怪物', '思量', '怎么', '念头', + '念叨', '快活', '忙活', '志气', '心思', '得罪', '张罗', '弟兄', '开通', '应酬', '庄稼', + '干事', '帮手', '帐篷', '希罕', '师父', '师傅', '巴结', '巴掌', '差事', '工夫', '岁数', + '屁股', '尾巴', '少爷', '小气', '小伙', '将就', '对头', '对付', '寡妇', '家伙', '客气', + '实在', '官司', '学问', '学生', '字号', '嫁妆', '媳妇', '媒人', '婆家', '娘家', '委屈', + '姑娘', '姐夫', '妯娌', '妥当', '妖精', '奴才', '女婿', '头发', '太阳', '大爷', '大方', + '大意', '大夫', '多少', '多么', '外甥', '壮实', '地道', '地方', '在乎', '困难', '嘴巴', + '嘱咐', '嘟囔', '嘀咕', '喜欢', '喇嘛', '喇叭', '商量', '唾沫', '哑巴', '哈欠', '哆嗦', + '咳嗽', '和尚', '告诉', '告示', '含糊', '吓唬', '后头', '名字', '名堂', '合同', '吆喝', + '叫唤', '口袋', '厚道', '厉害', '千斤', '包袱', '包涵', '匀称', '勤快', '动静', '动弹', + '功夫', '力气', '前头', '刺猬', '刺激', '别扭', '利落', '利索', '利害', '分析', '出息', + '凑合', '凉快', '冷战', '冤枉', '冒失', '养活', '关系', '先生', '兄弟', '便宜', '使唤', + '佩服', '作坊', '体面', '位置', '似的', '伙计', '休息', '什么', '人家', '亲戚', '亲家', + '交情', '云彩', '事情', '买卖', '主意', '丫头', '丧气', '两口', '东西', '东家', '世故', + '不由', '不在', '下水', '下巴', '上头', '上司', '丈夫', '丈人', '一辈', '那个', '菩萨', + '父亲', '母亲', '咕噜', '邋遢', '费用', '冤家', '甜头', '介绍', '荒唐', '大人', '泥鳅', + '幸福', '熟悉', '计划', '扑腾', '蜡烛', '姥爷', '照顾', '喉咙', '吉他', '弄堂', '蚂蚱', + '凤凰', '拖沓', '寒碜', '糟蹋', '倒腾', '报复', '逻辑', '盘缠', '喽啰', '牢骚', '咖喱', + '扫把', '惦记' + } + self.must_not_neural_tone_words = { + "男子", "女子", "分子", "原子", "量子", "莲子", "石子", "瓜子", "电子" + } + + # the meaning of jieba pos tag: https://blog.csdn.net/weixin_44174352/article/details/113731041 + # e.g. + # word: "家里" + # pos: "s" + # finals: ['ia1', 'i3'] + def _neural_sandhi(self, word: str, pos: str, + finals: List[str]) -> List[str]: + + # reduplication words for n. and v. e.g. 奶奶, 试试, 旺旺 + for j, item in enumerate(word): + if j - 1 >= 0 and item == word[j - 1] and pos[0] in {"n", "v", "a"}: + finals[j] = finals[j][:-1] + "5" + ge_idx = word.find("个") + if len(word) >= 1 and word[-1] in "吧呢哈啊呐噻嘛吖嗨呐哦哒额滴哩哟喽啰耶喔诶": + finals[-1] = finals[-1][:-1] + "5" + elif len(word) >= 1 and word[-1] in "的地得": + finals[-1] = finals[-1][:-1] + "5" + # e.g. 走了, 看着, 去过 + elif len(word) == 1 and word in "了着过" and pos in {"ul", "uz", "ug"}: + finals[-1] = finals[-1][:-1] + "5" + elif len(word) > 1 and word[-1] in "们子" and pos in { + "r", "n" + } and word not in self.must_not_neural_tone_words: + finals[-1] = finals[-1][:-1] + "5" + # e.g. 桌上, 地下, 家里 + elif len(word) > 1 and word[-1] in "上下里" and pos in {"s", "l", "f"}: + finals[-1] = finals[-1][:-1] + "5" + # e.g. 上来, 下去 + elif len(word) > 1 and word[-1] in "来去" and word[-2] in "上下进出回过起开": + finals[-1] = finals[-1][:-1] + "5" + # 个做量词 + elif (ge_idx >= 1 and + (word[ge_idx - 1].isnumeric() or + word[ge_idx - 1] in "几有两半多各整每做是")) or word == '个': + finals[ge_idx] = finals[ge_idx][:-1] + "5" + else: + if word in self.must_neural_tone_words or word[ + -2:] in self.must_neural_tone_words: + finals[-1] = finals[-1][:-1] + "5" + + word_list = self._split_word(word) + finals_list = [finals[:len(word_list[0])], finals[len(word_list[0]):]] + for i, word in enumerate(word_list): + # conventional neural in Chinese + if word in self.must_neural_tone_words or word[ + -2:] in self.must_neural_tone_words: + finals_list[i][-1] = finals_list[i][-1][:-1] + "5" + finals = sum(finals_list, []) + return finals + + def _bu_sandhi(self, word: str, finals: List[str]) -> List[str]: + # e.g. 看不懂 + if len(word) == 3 and word[1] == "不": + finals[1] = finals[1][:-1] + "5" + else: + for i, char in enumerate(word): + # "不" before tone4 should be bu2, e.g. 不怕 + if char == "不" and i + 1 < len(word) and finals[i + + 1][-1] == "4": + finals[i] = finals[i][:-1] + "2" + return finals + + def _yi_sandhi(self, word: str, finals: List[str]) -> List[str]: + # "一" in number sequences, e.g. 一零零, 二一零 + if word.find("一") != -1 and all( + [item.isnumeric() for item in word if item != "一"]): + return finals + # "一" between reduplication words shold be yi5, e.g. 看一看 + elif len(word) == 3 and word[1] == "一" and word[0] == word[-1]: + finals[1] = finals[1][:-1] + "5" + # when "一" is ordinal word, it should be yi1 + elif word.startswith("第一"): + finals[1] = finals[1][:-1] + "1" + else: + for i, char in enumerate(word): + if char == "一" and i + 1 < len(word): + # "一" before tone4 should be yi2, e.g. 一段 + if finals[i + 1][-1] == "4": + finals[i] = finals[i][:-1] + "2" + # "一" before non-tone4 should be yi4, e.g. 一天 + else: + finals[i] = finals[i][:-1] + "4" + return finals + + def _split_word(self, word: str) -> List[str]: + word_list = jieba.cut_for_search(word) + word_list = sorted(word_list, key=lambda i: len(i), reverse=False) + first_subword = word_list[0] + first_begin_idx = word.find(first_subword) + if first_begin_idx == 0: + second_subword = word[len(first_subword):] + new_word_list = [first_subword, second_subword] + else: + second_subword = word[:-len(first_subword)] + new_word_list = [second_subword, first_subword] + return new_word_list + + def _three_sandhi(self, word: str, finals: List[str]) -> List[str]: + if len(word) == 2 and self._all_tone_three(finals): + finals[0] = finals[0][:-1] + "2" + elif len(word) == 3: + word_list = self._split_word(word) + if self._all_tone_three(finals): + # disyllabic + monosyllabic, e.g. 蒙古/包 + if len(word_list[0]) == 2: + finals[0] = finals[0][:-1] + "2" + finals[1] = finals[1][:-1] + "2" + # monosyllabic + disyllabic, e.g. 纸/老虎 + elif len(word_list[0]) == 1: + finals[1] = finals[1][:-1] + "2" + else: + finals_list = [ + finals[:len(word_list[0])], finals[len(word_list[0]):] + ] + if len(finals_list) == 2: + for i, sub in enumerate(finals_list): + # e.g. 所有/人 + if self._all_tone_three(sub) and len(sub) == 2: + finals_list[i][0] = finals_list[i][0][:-1] + "2" + # e.g. 好/喜欢 + elif i == 1 and not self._all_tone_three(sub) and finals_list[i][0][-1] == "3" and \ + finals_list[0][-1][-1] == "3": + + finals_list[0][-1] = finals_list[0][-1][:-1] + "2" + finals = sum(finals_list, []) + # split idiom into two words who's length is 2 + elif len(word) == 4: + finals_list = [finals[:2], finals[2:]] + finals = [] + for sub in finals_list: + if self._all_tone_three(sub): + sub[0] = sub[0][:-1] + "2" + finals += sub + + return finals + + def _all_tone_three(self, finals: List[str]) -> bool: + return all(x[-1] == "3" for x in finals) + + # merge "不" and the word behind it + # if don't merge, "不" sometimes appears alone according to jieba, which may occur sandhi error + def _merge_bu(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: + new_seg = [] + last_word = "" + for word, pos in seg: + if last_word == "不": + word = last_word + word + if word != "不": + new_seg.append((word, pos)) + last_word = word[:] + if last_word == "不": + new_seg.append((last_word, 'd')) + last_word = "" + return new_seg + + # function 1: merge "一" and reduplication words in it's left and right, e.g. "听","一","听" ->"听一听" + # function 2: merge single "一" and the word behind it + # if don't merge, "一" sometimes appears alone according to jieba, which may occur sandhi error + # e.g. + # input seg: [('听', 'v'), ('一', 'm'), ('听', 'v')] + # output seg: [['听一听', 'v']] + def _merge_yi(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: + new_seg = [] + # function 1 + for i, (word, pos) in enumerate(seg): + if i - 1 >= 0 and word == "一" and i + 1 < len(seg) and seg[i - 1][ + 0] == seg[i + 1][0] and seg[i - 1][1] == "v": + new_seg[i - 1][0] = new_seg[i - 1][0] + "一" + new_seg[i - 1][0] + else: + if i - 2 >= 0 and seg[i - 1][0] == "一" and seg[i - 2][ + 0] == word and pos == "v": + continue + else: + new_seg.append([word, pos]) + seg = new_seg + new_seg = [] + # function 2 + for i, (word, pos) in enumerate(seg): + if new_seg and new_seg[-1][0] == "一": + new_seg[-1][0] = new_seg[-1][0] + word + else: + new_seg.append([word, pos]) + return new_seg + + # the first and the second words are all_tone_three + def _merge_continuous_three_tones( + self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: + new_seg = [] + sub_finals_list = [ + lazy_pinyin( + word, neutral_tone_with_five=True, style=Style.FINALS_TONE3) + for (word, pos) in seg + ] + assert len(sub_finals_list) == len(seg) + merge_last = [False] * len(seg) + for i, (word, pos) in enumerate(seg): + if i - 1 >= 0 and self._all_tone_three( + sub_finals_list[i - 1]) and self._all_tone_three( + sub_finals_list[i]) and not merge_last[i - 1]: + # if the last word is reduplication, not merge, because reduplication need to be _neural_sandhi + if not self._is_reduplication(seg[i - 1][0]) and len( + seg[i - 1][0]) + len(seg[i][0]) <= 3: + new_seg[-1][0] = new_seg[-1][0] + seg[i][0] + merge_last[i] = True + else: + new_seg.append([word, pos]) + else: + new_seg.append([word, pos]) + + return new_seg + + def _is_reduplication(self, word: str) -> bool: + return len(word) == 2 and word[0] == word[1] + + # the last char of first word and the first char of second word is tone_three + def _merge_continuous_three_tones_2( + self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: + new_seg = [] + sub_finals_list = [ + lazy_pinyin( + word, neutral_tone_with_five=True, style=Style.FINALS_TONE3) + for (word, pos) in seg + ] + assert len(sub_finals_list) == len(seg) + merge_last = [False] * len(seg) + for i, (word, pos) in enumerate(seg): + if i - 1 >= 0 and sub_finals_list[i - 1][-1][-1] == "3" and sub_finals_list[i][0][-1] == "3" and not \ + merge_last[i - 1]: + # if the last word is reduplication, not merge, because reduplication need to be _neural_sandhi + if not self._is_reduplication(seg[i - 1][0]) and len( + seg[i - 1][0]) + len(seg[i][0]) <= 3: + new_seg[-1][0] = new_seg[-1][0] + seg[i][0] + merge_last[i] = True + else: + new_seg.append([word, pos]) + else: + new_seg.append([word, pos]) + return new_seg + + def _merge_er(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: + new_seg = [] + for i, (word, pos) in enumerate(seg): + if i - 1 >= 0 and word == "儿": + new_seg[-1][0] = new_seg[-1][0] + seg[i][0] + else: + new_seg.append([word, pos]) + return new_seg + + def _merge_reduplication( + self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: + new_seg = [] + for i, (word, pos) in enumerate(seg): + if new_seg and word == new_seg[-1][0]: + new_seg[-1][0] = new_seg[-1][0] + seg[i][0] + else: + new_seg.append([word, pos]) + return new_seg + + def pre_merge_for_modify( + self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: + seg = self._merge_bu(seg) + seg = self._merge_yi(seg) + seg = self._merge_reduplication(seg) + seg = self._merge_continuous_three_tones(seg) + seg = self._merge_continuous_three_tones_2(seg) + seg = self._merge_er(seg) + return seg + + def modified_tone(self, word: str, pos: str, + finals: List[str]) -> List[str]: + finals = self._bu_sandhi(word, finals) + finals = self._yi_sandhi(word, finals) + finals = self._neural_sandhi(word, pos, finals) + finals = self._three_sandhi(word, finals) + return finals diff --git a/parakeet/frontend/vocab.py b/parakeet/frontend/vocab.py new file mode 100644 index 00000000..9ef6b137 --- /dev/null +++ b/parakeet/frontend/vocab.py @@ -0,0 +1,130 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from collections import OrderedDict +from typing import Iterable + +__all__ = ["Vocab"] + + +class Vocab(object): + """ Vocabulary. + + Parameters + ----------- + symbols: Iterable[str] + Common symbols. + + padding_symbol: str, optional + Symbol for pad. Defaults to "". + + unk_symbol: str, optional + Symbol for unknow. Defaults to "" + + start_symbol: str, optional + Symbol for start. Defaults to "" + + end_symbol: str, optional + Symbol for end. Defaults to "" + """ + + def __init__(self, + symbols: Iterable[str], + padding_symbol="", + unk_symbol="", + start_symbol="", + end_symbol=""): + self.special_symbols = OrderedDict() + for i, item in enumerate( + [padding_symbol, unk_symbol, start_symbol, end_symbol]): + if item: + self.special_symbols[item] = len(self.special_symbols) + + self.padding_symbol = padding_symbol + self.unk_symbol = unk_symbol + self.start_symbol = start_symbol + self.end_symbol = end_symbol + + self.stoi = OrderedDict() + self.stoi.update(self.special_symbols) + + for i, s in enumerate(symbols): + if s not in self.stoi: + self.stoi[s] = len(self.stoi) + self.itos = {v: k for k, v in self.stoi.items()} + + def __len__(self): + return len(self.stoi) + + @property + def num_specials(self): + """ The number of special symbols. + """ + return len(self.special_symbols) + + # special tokens + @property + def padding_index(self): + """ The index of padding symbol + """ + return self.stoi.get(self.padding_symbol, -1) + + @property + def unk_index(self): + """The index of unknow symbol. + """ + return self.stoi.get(self.unk_symbol, -1) + + @property + def start_index(self): + """The index of start symbol. + """ + return self.stoi.get(self.start_symbol, -1) + + @property + def end_index(self): + """ The index of end symbol. + """ + return self.stoi.get(self.end_symbol, -1) + + def __repr__(self): + fmt = "Vocab(size: {},\nstoi:\n{})" + return fmt.format(len(self), self.stoi) + + def __str__(self): + return self.__repr__() + + def lookup(self, symbol): + """ The index that symbol correspond. + """ + return self.stoi[symbol] + + def reverse(self, index): + """ The symbol thar index cottespond. + """ + return self.itos[index] + + def add_symbol(self, symbol): + """ Add a new symbol in vocab. + """ + if symbol in self.stoi: + return + N = len(self.stoi) + self.stoi[symbol] = N + self.itos[N] = symbol + + def add_symbols(self, symbols): + """ Add multiple symbols in vocab. + """ + for symbol in symbols: + self.add_symbol(symbol) diff --git a/parakeet/frontend/zh_frontend.py b/parakeet/frontend/zh_frontend.py new file mode 100644 index 00000000..8a0c1668 --- /dev/null +++ b/parakeet/frontend/zh_frontend.py @@ -0,0 +1,254 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import re +from typing import Dict +from typing import List + +import jieba.posseg as psg +import numpy as np +import paddle +from g2pM import G2pM +from pypinyin import lazy_pinyin +from pypinyin import Style + +from parakeet.frontend.zh_normalization.text_normlization import TextNormalizer +from parakeet.frontend.generate_lexicon import generate_lexicon +from parakeet.frontend.tone_sandhi import ToneSandhi + + +class Frontend(): + def __init__(self, + g2p_model="pypinyin", + phone_vocab_path=None, + tone_vocab_path=None): + self.tone_modifier = ToneSandhi() + self.text_normalizer = TextNormalizer() + self.punc = "：，；。？！“”‘’':,;.?!" + # g2p_model can be pypinyin and g2pM + self.g2p_model = g2p_model + if self.g2p_model == "g2pM": + self.g2pM_model = G2pM() + self.pinyin2phone = generate_lexicon( + with_tone=True, with_erhua=False) + self.must_erhua = {"小院儿", "胡同儿", "范儿", "老汉儿", "撒欢儿", "寻老礼儿", "妥妥儿"} + self.not_erhua = { + "虐儿", "为儿", "护儿", "瞒儿", "救儿", "替儿", "有儿", "一儿", "我儿", "俺儿", "妻儿", + "拐儿", "聋儿", "乞儿", "患儿", "幼儿", "孤儿", "婴儿", "婴幼儿", "连体儿", "脑瘫儿", + "流浪儿", "体弱儿", "混血儿", "蜜雪儿", "舫儿", "祖儿", "美儿", "应采儿", "可儿", "侄儿", + "孙儿", "侄孙儿", "女儿", "男儿", "红孩儿", "花儿", "虫儿", "马儿", "鸟儿", "猪儿", "猫儿", + "狗儿" + } + self.vocab_phones = {} + self.vocab_tones = {} + if phone_vocab_path: + with open(phone_vocab_path, 'rt') as f: + phn_id = [line.strip().split() for line in f.readlines()] + for phn, id in phn_id: + self.vocab_phones[phn] = int(id) + if tone_vocab_path: + with open(tone_vocab_path, 'rt') as f: + tone_id = [line.strip().split() for line in f.readlines()] + for tone, id in tone_id: + self.vocab_tones[tone] = int(id) + + def _get_initials_finals(self, word: str) -> List[List[str]]: + initials = [] + finals = [] + if self.g2p_model == "pypinyin": + orig_initials = lazy_pinyin( + word, neutral_tone_with_five=True, style=Style.INITIALS) + orig_finals = lazy_pinyin( + word, neutral_tone_with_five=True, style=Style.FINALS_TONE3) + for c, v in zip(orig_initials, orig_finals): + if re.match(r'i\d', v): + if c in ['z', 'c', 's']: + v = re.sub('i', 'ii', v) + elif c in ['zh', 'ch', 'sh', 'r']: + v = re.sub('i', 'iii', v) + initials.append(c) + finals.append(v) + elif self.g2p_model == "g2pM": + pinyins = self.g2pM_model(word, tone=True, char_split=False) + for pinyin in pinyins: + pinyin = pinyin.replace("u:", "v") + if pinyin in self.pinyin2phone: + initial_final_list = self.pinyin2phone[pinyin].split(" ") + if len(initial_final_list) == 2: + initials.append(initial_final_list[0]) + finals.append(initial_final_list[1]) + elif len(initial_final_list) == 1: + initials.append('') + finals.append(initial_final_list[1]) + else: + # If it's not pinyin (possibly punctuation) or no conversion is required + initials.append(pinyin) + finals.append(pinyin) + return initials, finals + + # if merge_sentences, merge all sentences into one phone sequence + def _g2p(self, + sentences: List[str], + merge_sentences: bool=True, + with_erhua: bool=True) -> List[List[str]]: + segments = sentences + phones_list = [] + for seg in segments: + phones = [] + seg_cut = psg.lcut(seg) + initials = [] + finals = [] + seg_cut = self.tone_modifier.pre_merge_for_modify(seg_cut) + for word, pos in seg_cut: + if pos == 'eng': + continue + sub_initials, sub_finals = self._get_initials_finals(word) + sub_finals = self.tone_modifier.modified_tone(word, pos, + sub_finals) + if with_erhua: + sub_initials, sub_finals = self._merge_erhua( + sub_initials, sub_finals, word, pos) + initials.append(sub_initials) + finals.append(sub_finals) + # assert len(sub_initials) == len(sub_finals) == len(word) + initials = sum(initials, []) + finals = sum(finals, []) + + for c, v in zip(initials, finals): + # NOTE: post process for pypinyin outputs + # we discriminate i, ii and iii + if c and c not in self.punc: + phones.append(c) + if v and v not in self.punc: + phones.append(v) + # add sp between sentence (replace the last punc with sp) + if initials[-1] in self.punc: + phones.append('sp') + phones_list.append(phones) + if merge_sentences: + merge_list = sum(phones_list, []) + phones_list = [] + phones_list.append(merge_list) + return phones_list + + def _merge_erhua(self, + initials: List[str], + finals: List[str], + word: str, + pos: str) -> List[List[str]]: + if word not in self.must_erhua and (word in self.not_erhua or + pos in {"a", "j", "nr"}): + return initials, finals + new_initials = [] + new_finals = [] + assert len(finals) == len(word) + for i, phn in enumerate(finals): + if i == len(finals) - 1 and word[i] == "儿" and phn in { + "er2", "er5" + } and word[-2:] not in self.not_erhua and new_finals: + new_finals[-1] = new_finals[-1][:-1] + "r" + new_finals[-1][-1] + else: + new_finals.append(phn) + new_initials.append(initials[i]) + return new_initials, new_finals + + def _p2id(self, phonemes: List[str]) -> np.array: + # replace unk phone with sp + phonemes = [ + phn if phn in self.vocab_phones else "sp" for phn in phonemes + ] + phone_ids = [self.vocab_phones[item] for item in phonemes] + return np.array(phone_ids, np.int64) + + def _t2id(self, tones: List[str]) -> np.array: + # replace unk phone with sp + tones = [tone if tone in self.vocab_tones else "0" for tone in tones] + tone_ids = [self.vocab_tones[item] for item in tones] + return np.array(tone_ids, np.int64) + + def _get_phone_tone(self, phonemes: List[str], + get_tone_ids: bool=False) -> List[List[str]]: + phones = [] + tones = [] + if get_tone_ids and self.vocab_tones: + for full_phone in phonemes: + # split tone from finals + match = re.match(r'^(\w+)([012345])$', full_phone) + if match: + phone = match.group(1) + tone = match.group(2) + # if the merged erhua not in the vocab + # assume that the input is ['iaor3'] and 'iaor' not in self.vocab_phones, we split 'iaor' into ['iao','er'] + # and the tones accordingly change from ['3'] to ['3','2'], while '2' is the tone of 'er2' + if len(phone) >= 2 and phone != "er" and phone[ + -1] == 'r' and phone not in self.vocab_phones and phone[: + -1] in self.vocab_phones: + phones.append(phone[:-1]) + phones.append("er") + tones.append(tone) + tones.append("2") + else: + phones.append(phone) + tones.append(tone) + else: + phones.append(full_phone) + tones.append('0') + else: + for phone in phonemes: + # if the merged erhua not in the vocab + # assume that the input is ['iaor3'] and 'iaor' not in self.vocab_phones, change ['iaor3'] to ['iao3','er2'] + if len(phone) >= 3 and phone[:-1] != "er" and phone[ + -2] == 'r' and phone not in self.vocab_phones and ( + phone[:-2] + phone[-1]) in self.vocab_phones: + phones.append((phone[:-2] + phone[-1])) + phones.append("er2") + else: + phones.append(phone) + return phones, tones + + def get_phonemes(self, + sentence: str, + merge_sentences: bool=True, + with_erhua: bool=True) -> List[List[str]]: + sentences = self.text_normalizer.normalize(sentence) + phonemes = self._g2p( + sentences, merge_sentences=merge_sentences, with_erhua=with_erhua) + return phonemes + + def get_input_ids( + self, + sentence: str, + merge_sentences: bool=True, + get_tone_ids: bool=False) -> Dict[str, List[paddle.Tensor]]: + phonemes = self.get_phonemes(sentence, merge_sentences=merge_sentences) + result = {} + phones = [] + tones = [] + temp_phone_ids = [] + temp_tone_ids = [] + for part_phonemes in phonemes: + phones, tones = self._get_phone_tone( + part_phonemes, get_tone_ids=get_tone_ids) + if tones: + tone_ids = self._t2id(tones) + tone_ids = paddle.to_tensor(tone_ids) + temp_tone_ids.append(tone_ids) + if phones: + phone_ids = self._p2id(phones) + phone_ids = paddle.to_tensor(phone_ids) + temp_phone_ids.append(phone_ids) + if temp_tone_ids: + result["tone_ids"] = temp_tone_ids + if temp_phone_ids: + result["phone_ids"] = temp_phone_ids + return result diff --git a/parakeet/frontend/zh_normalization/README.md b/parakeet/frontend/zh_normalization/README.md new file mode 100644 index 00000000..92eea9f5 --- /dev/null +++ b/parakeet/frontend/zh_normalization/README.md @@ -0,0 +1,16 @@ +## Supported NSW (Non-Standard-Word) Normalization + +|NSW type|raw|normalized| +|:--|:-|:-| +|serial number|电影中梁朝伟扮演的陈永仁的编号27149|电影中梁朝伟扮演的陈永仁的编号二七一四九| +|cardinal|这块黄金重达324.75克
    我们班的最高总分为583分|这块黄金重达三百二十四点七五克
    我们班的最高总分为五百八十三分| +|numeric range |12\~23
    -1.5\~2|十二到二十三
    负一点五到二| +|date|她出生于86年8月18日，她弟弟出生于1995年3月1日|她出生于八六年八月十八日， 她弟弟出生于一九九五年三月一日| +|time|等会请在12:05请通知我|等会请在十二点零五分请通知我 +|temperature|今天的最低气温达到-10°C|今天的最低气温达到零下十度 +|fraction|现场有7/12的观众投出了赞成票|现场有十二分之七的观众投出了赞成票| +|percentage|明天有62％的概率降雨|明天有百分之六十二的概率降雨| +|money|随便来几个价格12块5，34.5元，20.1万|随便来几个价格十二块五，三十四点五元，二十点一万| +|telephone|这是固话0421-33441122
    这是手机+86 18544139121|这是固话零四二一三三四四一一二二
    这是手机八六一八五四四一三九一二一| +## References +[Pull requests #658 of DeepSpeech](https://github.com/PaddlePaddle/DeepSpeech/pull/658/files) diff --git a/parakeet/frontend/zh_normalization/__init__.py b/parakeet/frontend/zh_normalization/__init__.py new file mode 100644 index 00000000..77e10ebb --- /dev/null +++ b/parakeet/frontend/zh_normalization/__init__.py @@ -0,0 +1,15 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from parakeet.frontend.zh_normalization.text_normlization import * diff --git a/parakeet/frontend/zh_normalization/char_convert.py b/parakeet/frontend/zh_normalization/char_convert.py new file mode 100644 index 00000000..22462a0c --- /dev/null +++ b/parakeet/frontend/zh_normalization/char_convert.py @@ -0,0 +1,46 @@ +# coding=utf-8 +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Traditional and simplified Chinese conversion, a simplified character may correspond to multiple traditional characters. +""" +simplified_charcters = 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+ +traditional_characters = 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鐔鐗馗鐙鐝鐠鐡鐦鐨鐩鐫鐬鐱鐳鐶鐻鐽鐿鑀鑅鑌鑐鑕鑚鑛鑢鑤鑥鑪鑭鑯鑱鑴鑵鑷钁钃镻閆閈閌閎閒閔閗閟閡関閤閤閧閬閲閹閺閻閼閽閿闇闉闋闐闑闒闓闘闚闞闟闠闤闥阞阢阤阨阬阯阹阼阽陁陑陔陛陜陡陥陬騭陴険陼陾隂隃隈隒隗隞隠隣隤隩隮隰顴隳隷隹雂雈雉雊雎雑雒雗雘雚雝雟雩雰雱驛霂霅霈霊霑霒霓霙霝霢霣霤霨霩霪霫霮靁靆靉靑靚靣靦靪靮靰靳靷靸靺靼靿鞀鞃鞄鞌鞗鞙鞚鞝鞞鞡鞣鞨鞫鞬鞮鞶鞹鞾韃韅韉馱韍韎韔韖韘韝韞韡韣韭韮韱韹韺頀颳頄頇頊頍頎頏頒頖頞頠頫頬顱頯頲頴頼顇顋顑顒顓顔顕顚顜顢顣顬顳颭颮颱颶颸颺颻颽颾颿飀飂飈飌飜飡飣飤飥飩飫飮飱飶餀餂餄餎餇餈餑餔餕餖餗餚餛餜餟餠餤餧餩餪餫餬餮餱餲餳餺餻餼餽餿饁饅饇饉饊饍饎饐饘饟饢馘馥馝馡馣騮騾馵馹駃駄駅駆駉駋駑駓駔駗駘駙駜駡駢駪駬駰駴駸駹駽駾騂騄騅騆騉騋騍騏驎騑騒験騕騖騠騢騣騤騧驤騵騶騸騺驀驂驃驄驆驈驊驌驍驎驏驒驔驖驙驦驩驫骺鯁骫骭骯骱骴骶骷髏骾髁髂髄髆髈髐髑髕髖髙髝髞髟髡髣髧髪髫髭髯髲髳髹髺髽髾鬁鬃鬅鬈鬋鬎鬏鬐鬑鬒鬖鬗鬘鬙鬠鬣鬪鬫鬬鬮鬯鬰鬲鬵鬷魆魈魊魋魍魎魑魖鰾魛魟魣魦魨魬魴魵魸鮀鮁鮆鮌鮎鮑鮒鮓鮚鮞鮟鱇鮠鮦鮨鮪鮭鮶鮸鮿鯀鯄鯆鯇鯈鯔鯕鯖鯗鯙鯠鯤鯥鯫鯰鯷鯸鯿鰂鰆鶼鰉鰋鰐鰒鰕鰛鰜鰣鰤鰥鰦鰨鰩鰮鰳鰶鰷鱺鰼鰽鱀鱄鱅鱆鱈鱎鱐鱓鱔鱖鱘鱟鱠鱣鱨鱭鱮鱲鱵鱻鲅鳦鳧鳯鳲鳷鳻鴂鴃鴄鴆鴈鴎鴒鴔鴗鴛鴦鴝鵒鴟鴠鴢鴣鴥鴯鶓鴳鴴鴷鴽鵀鵁鵂鵓鵖鵙鵜鶘鵞鵟鵩鵪鵫鵵鵷鵻鵾鶂鶊鶏鶒鶖鶗鶡鶤鶦鶬鶱鶲鶵鶸鶹鶺鶿鷀鷁鷃鷄鷇鷈鷉鷊鷏鷓鷕鷖鷙鷞鷟鷥鷦鷯鷩鷫鷭鷳鷴鷽鷾鷿鸂鸇鸊鸏鸑鸒鸓鸕鸛鸜鸝鹸鹹鹺麀麂麃麄麇麋麌麐麑麒麚麛麝麤麩麪麫麮麯麰麺麾黁黈黌黢黒黓黕黙黝黟黥黦黧黮黰黱黲黶黹黻黼黽黿鼂鼃鼅鼈鼉鼏鼐鼒鼕鼖鼙鼚鼛鼡鼩鼱鼪鼫鼯鼷鼽齁齆齇齈齉齌齎齏齔齕齗齙齚齜齞齟齬齠齢齣齧齩齮齯齰齱齵齾龎龑龒龔龖龘龝龡龢龤' + +assert len(simplified_charcters) == len(simplified_charcters) + +s2t_dict = {} +t2s_dict = {} +for i, item in enumerate(simplified_charcters): + s2t_dict[item] = traditional_characters[i] + t2s_dict[traditional_characters[i]] = item + + +def tranditional_to_simplified(text: str) -> str: + return "".join( + [t2s_dict[item] if item in t2s_dict else item for item in text]) + + +def simplified_to_traditional(text: str) -> str: + return "".join( + [s2t_dict[item] if item in s2t_dict else item for item in text]) + + +if __name__ == "__main__": + text = "一般是指存取一個應用程式啟動時始終顯示在網站或網頁瀏覽器中的一個或多個初始網頁等畫面存在的站點" + print(text) + text_simple = tranditional_to_simplified(text) + print(text_simple) + text_traditional = simplified_to_traditional(text_simple) + print(text_traditional) diff --git a/parakeet/frontend/zh_normalization/chronology.py b/parakeet/frontend/zh_normalization/chronology.py new file mode 100644 index 00000000..b8d71156 --- /dev/null +++ b/parakeet/frontend/zh_normalization/chronology.py @@ -0,0 +1,108 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import re + +from .num import DIGITS +from .num import num2str +from .num import verbalize_cardinal +from .num import verbalize_digit + + +def _time_num2str(num_string: str) -> str: + """A special case for verbalizing number in time.""" + result = num2str(num_string.lstrip('0')) + if num_string.startswith('0'): + result = DIGITS['0'] + result + return result + + +# 时刻表达式 +RE_TIME = re.compile(r'([0-1]?[0-9]|2[0-3])' + r':([0-5][0-9])' + r'(:([0-5][0-9]))?') + + +def replace_time(match) -> str: + """ + Parameters + ---------- + match : re.Match + Returns + ---------- + str + """ + hour = match.group(1) + minute = match.group(2) + second = match.group(4) + + result = f"{num2str(hour)}点" + if minute.lstrip('0'): + result += f"{_time_num2str(minute)}分" + if second and second.lstrip('0'): + result += f"{_time_num2str(second)}秒" + return result + + +RE_DATE = re.compile(r'(\d{4}|\d{2})年' + r'((0?[1-9]|1[0-2])月)?' + r'(((0?[1-9])|((1|2)[0-9])|30|31)([日号]))?') + + +def replace_date(match) -> str: + """ + Parameters + ---------- + match : re.Match + Returns + ---------- + str + """ + year = match.group(1) + month = match.group(3) + day = match.group(5) + result = "" + if year: + result += f"{verbalize_digit(year)}年" + if month: + result += f"{verbalize_cardinal(month)}月" + if day: + result += f"{verbalize_cardinal(day)}{match.group(9)}" + return result + + +# 用 / 或者 - 分隔的 YY/MM/DD 或者 YY-MM-DD 日期 +RE_DATE2 = re.compile( + r'(\d{4})([- /.])(0[1-9]|1[012])\2(0[1-9]|[12][0-9]|3[01])') + + +def replace_date2(match) -> str: + """ + Parameters + ---------- + match : re.Match + Returns + ---------- + str + """ + year = match.group(1) + month = match.group(3) + day = match.group(4) + result = "" + if year: + result += f"{verbalize_digit(year)}年" + if month: + result += f"{verbalize_cardinal(month)}月" + if day: + result += f"{verbalize_cardinal(day)}日" + return result diff --git a/parakeet/frontend/zh_normalization/constants.py b/parakeet/frontend/zh_normalization/constants.py new file mode 100644 index 00000000..5d2b0b34 --- /dev/null +++ b/parakeet/frontend/zh_normalization/constants.py @@ -0,0 +1,62 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import re +import string + +from pypinyin.constants import SUPPORT_UCS4 + +# 全角半角转换 +# 英文字符全角 -> 半角映射表 (num: 52) +F2H_ASCII_LETTERS = { + chr(ord(char) + 65248): char + for char in string.ascii_letters +} + +# 英文字符半角 -> 全角映射表 +H2F_ASCII_LETTERS = {value: key for key, value in F2H_ASCII_LETTERS.items()} + +# 数字字符全角 -> 半角映射表 (num: 10) +F2H_DIGITS = {chr(ord(char) + 65248): char for char in string.digits} +# 数字字符半角 -> 全角映射表 +H2F_DIGITS = {value: key for key, value in F2H_DIGITS.items()} + +# 标点符号全角 -> 半角映射表 (num: 32) +F2H_PUNCTUATIONS = {chr(ord(char) + 65248): char for char in string.punctuation} +# 标点符号半角 -> 全角映射表 +H2F_PUNCTUATIONS = {value: key for key, value in F2H_PUNCTUATIONS.items()} + +# 空格 (num: 1) +F2H_SPACE = {'\u3000': ' '} +H2F_SPACE = {' ': '\u3000'} + +# 非"有拼音的汉字"的字符串，可用于NSW提取 +if SUPPORT_UCS4: + RE_NSW = re.compile(r'(?:[^' + r'\u3007' # 〇 + r'\u3400-\u4dbf' # CJK扩展A:[3400-4DBF] + r'\u4e00-\u9fff' # CJK基本:[4E00-9FFF] + r'\uf900-\ufaff' # CJK兼容:[F900-FAFF] + r'\U00020000-\U0002A6DF' # CJK扩展B:[20000-2A6DF] + r'\U0002A703-\U0002B73F' # CJK扩展C:[2A700-2B73F] + r'\U0002B740-\U0002B81D' # CJK扩展D:[2B740-2B81D] + r'\U0002F80A-\U0002FA1F' # CJK兼容扩展:[2F800-2FA1F] + r'])+') +else: + RE_NSW = re.compile( # pragma: no cover + r'(?:[^' + r'\u3007' # 〇 + r'\u3400-\u4dbf' # CJK扩展A:[3400-4DBF] + r'\u4e00-\u9fff' # CJK基本:[4E00-9FFF] + r'\uf900-\ufaff' # CJK兼容:[F900-FAFF] + r'])+') diff --git a/parakeet/frontend/zh_normalization/num.py b/parakeet/frontend/zh_normalization/num.py new file mode 100644 index 00000000..1e575c08 --- /dev/null +++ b/parakeet/frontend/zh_normalization/num.py @@ -0,0 +1,249 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" +Rules to verbalize numbers into Chinese characters. +https://zh.wikipedia.org/wiki/中文数字#現代中文 +""" +import re +from collections import OrderedDict +from typing import List + +DIGITS = {str(i): tran for i, tran in enumerate('零一二三四五六七八九')} +UNITS = OrderedDict({ + 1: '十', + 2: '百', + 3: '千', + 4: '万', + 8: '亿', +}) + +COM_QUANTIFIERS = '(朵|匹|张|座|回|场|尾|条|个|首|阙|阵|网|炮|顶|丘|棵|只|支|袭|辆|挑|担|颗|壳|窠|曲|墙|群|腔|砣|座|客|贯|扎|捆|刀|令|打|手|罗|坡|山|岭|江|溪|钟|队|单|双|对|出|口|头|脚|板|跳|枝|件|贴|针|线|管|名|位|身|堂|课|本|页|家|户|层|丝|毫|厘|分|钱|两|斤|担|铢|石|钧|锱|忽|(千|毫|微)克|毫|厘|(公)分|分|寸|尺|丈|里|寻|常|铺|程|(千|分|厘|毫|微)米|米|撮|勺|合|升|斗|石|盘|碗|碟|叠|桶|笼|盆|盒|杯|钟|斛|锅|簋|篮|盘|桶|罐|瓶|壶|卮|盏|箩|箱|煲|啖|袋|钵|年|月|日|季|刻|时|周|天|秒|分|旬|纪|岁|世|更|夜|春|夏|秋|冬|代|伏|辈|丸|泡|粒|颗|幢|堆|条|根|支|道|面|片|张|颗|块|元|(亿|千万|百万|万|千|百)|(亿|千万|百万|万|千|百|美|)元|(亿|千万|百万|万|千|百|)块|角|毛|分)' + +# 分数表达式 +RE_FRAC = re.compile(r'(-?)(\d+)/(\d+)') + + +def replace_frac(match) -> str: + """ + Parameters + ---------- + match : re.Match + Returns + ---------- + str + """ + sign = match.group(1) + nominator = match.group(2) + denominator = match.group(3) + sign: str = "负" if sign else "" + nominator: str = num2str(nominator) + denominator: str = num2str(denominator) + result = f"{sign}{denominator}分之{nominator}" + return result + + +# 百分数表达式 +RE_PERCENTAGE = re.compile(r'(-?)(\d+(\.\d+)?)%') + + +def replace_percentage(match) -> str: + """ + Parameters + ---------- + match : re.Match + Returns + ---------- + str + """ + sign = match.group(1) + percent = match.group(2) + sign: str = "负" if sign else "" + percent: str = num2str(percent) + result = f"{sign}百分之{percent}" + return result + + +# 整数表达式 +# 带负号的整数 -10 +RE_INTEGER = re.compile(r'(-)' r'(\d+)') + + +def replace_negative_num(match) -> str: + """ + Parameters + ---------- + match : re.Match + Returns + ---------- + str + """ + sign = match.group(1) + number = match.group(2) + sign: str = "负" if sign else "" + number: str = num2str(number) + result = f"{sign}{number}" + return result + + +# 编号-无符号整形 +# 00078 +RE_DEFAULT_NUM = re.compile(r'\d{3}\d*') + + +def replace_default_num(match): + """ + Parameters + ---------- + match : re.Match + Returns + ---------- + str + """ + number = match.group(0) + return verbalize_digit(number) + + +# 数字表达式 +# 纯小数 +RE_DECIMAL_NUM = re.compile(r'(-?)((\d+)(\.\d+))' r'|(\.(\d+))') +# 正整数 + 量词 +RE_POSITIVE_QUANTIFIERS = re.compile(r"(\d+)([多余几])?" + COM_QUANTIFIERS) +RE_NUMBER = re.compile(r'(-?)((\d+)(\.\d+)?)' r'|(\.(\d+))') + + +def replace_positive_quantifier(match) -> str: + """ + Parameters + ---------- + match : re.Match + Returns + ---------- + str + """ + number = match.group(1) + match_2 = match.group(2) + match_2: str = match_2 if match_2 else "" + quantifiers: str = match.group(3) + number: str = num2str(number) + result = f"{number}{match_2}{quantifiers}" + return result + + +def replace_number(match) -> str: + """ + Parameters + ---------- + match : re.Match + Returns + ---------- + str + """ + sign = match.group(1) + number = match.group(2) + pure_decimal = match.group(5) + if pure_decimal: + result = num2str(pure_decimal) + else: + sign: str = "负" if sign else "" + number: str = num2str(number) + result = f"{sign}{number}" + return result + + +# 范围表达式 +# match.group(1) and match.group(8) are copy from RE_NUMBER +RE_RANGE = re.compile( + r'((-?)((\d+)(\.\d+)?)|(\.(\d+)))[-~]((-?)((\d+)(\.\d+)?)|(\.(\d+)))') + + +def replace_range(match) -> str: + """ + Parameters + ---------- + match : re.Match + Returns + ---------- + str + """ + first, second = match.group(1), match.group(8) + first = RE_NUMBER.sub(replace_number, first) + second = RE_NUMBER.sub(replace_number, second) + result = f"{first}到{second}" + return result + + +def _get_value(value_string: str, use_zero: bool=True) -> List[str]: + stripped = value_string.lstrip('0') + if len(stripped) == 0: + return [] + elif len(stripped) == 1: + if use_zero and len(stripped) < len(value_string): + return [DIGITS['0'], DIGITS[stripped]] + else: + return [DIGITS[stripped]] + else: + largest_unit = next( + power for power in reversed(UNITS.keys()) if power < len(stripped)) + first_part = value_string[:-largest_unit] + second_part = value_string[-largest_unit:] + return _get_value(first_part) + [UNITS[largest_unit]] + _get_value( + second_part) + + +def verbalize_cardinal(value_string: str) -> str: + if not value_string: + return '' + + # 000 -> '零' , 0 -> '零' + value_string = value_string.lstrip('0') + if len(value_string) == 0: + return DIGITS['0'] + + result_symbols = _get_value(value_string) + # verbalized number starting with '一十*' is abbreviated as `十*` + if len(result_symbols) >= 2 and result_symbols[0] == DIGITS[ + '1'] and result_symbols[1] == UNITS[1]: + result_symbols = result_symbols[1:] + return ''.join(result_symbols) + + +def verbalize_digit(value_string: str, alt_one=False) -> str: + result_symbols = [DIGITS[digit] for digit in value_string] + result = ''.join(result_symbols) + if alt_one: + result.replace("一", "幺") + return result + + +def num2str(value_string: str) -> str: + integer_decimal = value_string.split('.') + if len(integer_decimal) == 1: + integer = integer_decimal[0] + decimal = '' + elif len(integer_decimal) == 2: + integer, decimal = integer_decimal + else: + raise ValueError( + f"The value string: '${value_string}' has more than one point in it." + ) + + result = verbalize_cardinal(integer) + + decimal = decimal.rstrip('0') + if decimal: + # '.22' is verbalized as '零点二二' + # '3.20' is verbalized as '三点二 + result = result if result else "零" + result += '点' + verbalize_digit(decimal) + return result diff --git a/parakeet/frontend/zh_normalization/phonecode.py b/parakeet/frontend/zh_normalization/phonecode.py new file mode 100644 index 00000000..be159c23 --- /dev/null +++ b/parakeet/frontend/zh_normalization/phonecode.py @@ -0,0 +1,64 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import re + +from .num import verbalize_digit + +# 规范化固话/手机号码 +# 手机 +# http://www.jihaoba.com/news/show/13680 +# 移动：139、138、137、136、135、134、159、158、157、150、151、152、188、187、182、183、184、178、198 +# 联通：130、131、132、156、155、186、185、176 +# 电信：133、153、189、180、181、177 +RE_MOBILE_PHONE = re.compile( + r"(? str: + if mobile: + sp_parts = phone_string.strip('+').split() + result = ''.join( + [verbalize_digit(part, alt_one=True) for part in sp_parts]) + return result + else: + sil_parts = phone_string.split('-') + result = ''.join( + [verbalize_digit(part, alt_one=True) for part in sil_parts]) + return result + + +def replace_phone(match) -> str: + """ + Parameters + ---------- + match : re.Match + Returns + ---------- + str + """ + return phone2str(match.group(0), mobile=False) + + +def replace_mobile(match) -> str: + """ + Parameters + ---------- + match : re.Match + Returns + ---------- + str + """ + return phone2str(match.group(0)) diff --git a/parakeet/frontend/zh_normalization/quantifier.py b/parakeet/frontend/zh_normalization/quantifier.py new file mode 100644 index 00000000..d3805a32 --- /dev/null +++ b/parakeet/frontend/zh_normalization/quantifier.py @@ -0,0 +1,39 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import re + +from .num import num2str + +# 温度表达式，温度会影响负号的读法 +# -3°C 零下三度 +RE_TEMPERATURE = re.compile(r'(-?)(\d+(\.\d+)?)(°C|℃|度|摄氏度)') + + +def replace_temperature(match) -> str: + """ + Parameters + ---------- + match : re.Match + Returns + ---------- + str + """ + sign = match.group(1) + temperature = match.group(2) + unit = match.group(3) + sign: str = "零下" if sign else "" + temperature: str = num2str(temperature) + unit: str = "摄氏度" if unit == "摄氏度" else "度" + result = f"{sign}{temperature}{unit}" + return result diff --git a/parakeet/frontend/zh_normalization/text_normlization.py b/parakeet/frontend/zh_normalization/text_normlization.py new file mode 100644 index 00000000..e25e9901 --- /dev/null +++ b/parakeet/frontend/zh_normalization/text_normlization.py @@ -0,0 +1,98 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import re +from typing import List + +from .char_convert import tranditional_to_simplified +from .chronology import RE_DATE +from .chronology import RE_DATE2 +from .chronology import RE_TIME +from .chronology import replace_date +from .chronology import replace_date2 +from .chronology import replace_time +from .constants import F2H_ASCII_LETTERS +from .constants import F2H_DIGITS +from .constants import F2H_SPACE +from .num import RE_DECIMAL_NUM +from .num import RE_DEFAULT_NUM +from .num import RE_FRAC +from .num import RE_INTEGER +from .num import RE_NUMBER +from .num import RE_PERCENTAGE +from .num import RE_POSITIVE_QUANTIFIERS +from .num import RE_RANGE +from .num import replace_default_num +from .num import replace_frac +from .num import replace_negative_num +from .num import replace_number +from .num import replace_percentage +from .num import replace_positive_quantifier +from .num import replace_range +from .phonecode import RE_MOBILE_PHONE +from .phonecode import RE_TELEPHONE +from .phonecode import replace_mobile +from .phonecode import replace_phone +from .quantifier import RE_TEMPERATURE +from .quantifier import replace_temperature + + +class TextNormalizer(): + def __init__(self): + self.SENTENCE_SPLITOR = re.compile(r'([：，；。？！,;?!][”’]?)') + + def _split(self, text: str) -> List[str]: + """Split long text into sentences with sentence-splitting punctuations. + Parameters + ---------- + text : str + The input text. + Returns + ------- + List[str] + Sentences. + """ + text = self.SENTENCE_SPLITOR.sub(r'\1\n', text) + text = text.strip() + sentences = [sentence.strip() for sentence in re.split(r'\n+', text)] + return sentences + + def normalize_sentence(self, sentence: str) -> str: + # basic character conversions + sentence = tranditional_to_simplified(sentence) + sentence = sentence.translate(F2H_ASCII_LETTERS).translate( + F2H_DIGITS).translate(F2H_SPACE) + + # number related NSW verbalization + sentence = RE_DATE.sub(replace_date, sentence) + sentence = RE_DATE2.sub(replace_date2, sentence) + sentence = RE_TIME.sub(replace_time, sentence) + sentence = RE_TEMPERATURE.sub(replace_temperature, sentence) + sentence = RE_FRAC.sub(replace_frac, sentence) + sentence = RE_PERCENTAGE.sub(replace_percentage, sentence) + sentence = RE_MOBILE_PHONE.sub(replace_mobile, sentence) + sentence = RE_TELEPHONE.sub(replace_phone, sentence) + sentence = RE_RANGE.sub(replace_range, sentence) + sentence = RE_INTEGER.sub(replace_negative_num, sentence) + sentence = RE_DECIMAL_NUM.sub(replace_number, sentence) + sentence = RE_POSITIVE_QUANTIFIERS.sub(replace_positive_quantifier, + sentence) + sentence = RE_DEFAULT_NUM.sub(replace_default_num, sentence) + sentence = RE_NUMBER.sub(replace_number, sentence) + + return sentence + + def normalize(self, text: str) -> List[str]: + sentences = self._split(text) + sentences = [self.normalize_sentence(sent) for sent in sentences] + return sentences diff --git a/parakeet/models/__init__.py b/parakeet/models/__init__.py new file mode 100644 index 00000000..e943def7 --- /dev/null +++ b/parakeet/models/__init__.py @@ -0,0 +1,18 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from .fastspeech2 import * +from .tacotron2 import * +from .transformer_tts import * +from .waveflow import * diff --git a/parakeet/models/fastspeech2/__init__.py b/parakeet/models/fastspeech2/__init__.py new file mode 100644 index 00000000..83479d6f --- /dev/null +++ b/parakeet/models/fastspeech2/__init__.py @@ -0,0 +1,16 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from .fastspeech2 import * +from .fastspeech2_updater import * diff --git a/parakeet/models/fastspeech2/fastspeech2.py b/parakeet/models/fastspeech2/fastspeech2.py new file mode 100644 index 00000000..019979b9 --- /dev/null +++ b/parakeet/models/fastspeech2/fastspeech2.py @@ -0,0 +1,812 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Fastspeech2 related modules for paddle""" +from typing import Dict +from typing import Sequence +from typing import Tuple + +import paddle +import paddle.nn.functional as F +from paddle import nn +from typeguard import check_argument_types + +from parakeet.modules.fastspeech2_predictor.duration_predictor import DurationPredictor +from parakeet.modules.fastspeech2_predictor.duration_predictor import DurationPredictorLoss +from parakeet.modules.fastspeech2_predictor.length_regulator import LengthRegulator +from parakeet.modules.fastspeech2_predictor.variance_predictor import VariancePredictor +from parakeet.modules.fastspeech2_transformer.embedding import PositionalEncoding +from parakeet.modules.fastspeech2_transformer.embedding import ScaledPositionalEncoding +from parakeet.modules.fastspeech2_transformer.encoder import Encoder as TransformerEncoder +from parakeet.modules.tacotron2.decoder import Postnet +from parakeet.modules.nets_utils import initialize +from parakeet.modules.nets_utils import make_non_pad_mask +from parakeet.modules.nets_utils import make_pad_mask + + +class FastSpeech2(nn.Layer): + """FastSpeech2 module. + + This is a module of FastSpeech2 described in `FastSpeech 2: Fast and + High-Quality End-to-End Text to Speech`_. Instead of quantized pitch and + energy, we use token-averaged value introduced in `FastPitch: Parallel + Text-to-speech with Pitch Prediction`_. + + .. _`FastSpeech 2: Fast and High-Quality End-to-End Text to Speech`: + https://arxiv.org/abs/2006.04558 + .. _`FastPitch: Parallel Text-to-speech with Pitch Prediction`: + https://arxiv.org/abs/2006.06873 + + """ + + def __init__( + self, + # network structure related + idim: int, + odim: int, + adim: int=384, + aheads: int=4, + elayers: int=6, + eunits: int=1536, + dlayers: int=6, + dunits: int=1536, + postnet_layers: int=5, + postnet_chans: int=512, + postnet_filts: int=5, + positionwise_layer_type: str="conv1d", + positionwise_conv_kernel_size: int=1, + use_scaled_pos_enc: bool=True, + use_batch_norm: bool=True, + encoder_normalize_before: bool=True, + decoder_normalize_before: bool=True, + encoder_concat_after: bool=False, + decoder_concat_after: bool=False, + reduction_factor: int=1, + encoder_type: str="transformer", + decoder_type: str="transformer", + # duration predictor + duration_predictor_layers: int=2, + duration_predictor_chans: int=384, + duration_predictor_kernel_size: int=3, + # energy predictor + energy_predictor_layers: int=2, + energy_predictor_chans: int=384, + energy_predictor_kernel_size: int=3, + energy_predictor_dropout: float=0.5, + energy_embed_kernel_size: int=9, + energy_embed_dropout: float=0.5, + stop_gradient_from_energy_predictor: bool=False, + # pitch predictor + pitch_predictor_layers: int=2, + pitch_predictor_chans: int=384, + pitch_predictor_kernel_size: int=3, + pitch_predictor_dropout: float=0.5, + pitch_embed_kernel_size: int=9, + pitch_embed_dropout: float=0.5, + stop_gradient_from_pitch_predictor: bool=False, + # spk emb + num_speakers: int=None, + spk_embed_dim: int=None, + spk_embed_integration_type: str="add", + # tone emb + num_tones: int=None, + tone_embed_dim: int=None, + tone_embed_integration_type: str="add", + # training related + transformer_enc_dropout_rate: float=0.1, + transformer_enc_positional_dropout_rate: float=0.1, + transformer_enc_attn_dropout_rate: float=0.1, + transformer_dec_dropout_rate: float=0.1, + transformer_dec_positional_dropout_rate: float=0.1, + transformer_dec_attn_dropout_rate: float=0.1, + duration_predictor_dropout_rate: float=0.1, + postnet_dropout_rate: float=0.5, + init_type: str="xavier_uniform", + init_enc_alpha: float=1.0, + init_dec_alpha: float=1.0, + use_masking: bool=False, + use_weighted_masking: bool=False, ): + """Initialize FastSpeech2 module.""" + assert check_argument_types() + super().__init__() + + # store hyperparameters + self.idim = idim + self.odim = odim + self.eos = idim - 1 + self.reduction_factor = reduction_factor + self.encoder_type = encoder_type + self.decoder_type = decoder_type + self.stop_gradient_from_pitch_predictor = stop_gradient_from_pitch_predictor + self.stop_gradient_from_energy_predictor = stop_gradient_from_energy_predictor + self.use_scaled_pos_enc = use_scaled_pos_enc + + self.spk_embed_dim = spk_embed_dim + if self.spk_embed_dim is not None: + self.spk_embed_integration_type = spk_embed_integration_type + + self.tone_embed_dim = tone_embed_dim + if self.tone_embed_dim is not None: + self.tone_embed_integration_type = tone_embed_integration_type + + # use idx 0 as padding idx + self.padding_idx = 0 + + # initialize parameters + initialize(self, init_type) + + if self.spk_embed_dim is not None: + self.spk_embedding_table = nn.Embedding( + num_embeddings=num_speakers, + embedding_dim=self.spk_embed_dim, + padding_idx=self.padding_idx) + + if self.tone_embed_dim is not None: + self.tone_embedding_table = nn.Embedding( + num_embeddings=num_tones, + embedding_dim=self.tone_embed_dim, + padding_idx=self.padding_idx) + + # get positional encoding class + pos_enc_class = (ScaledPositionalEncoding + if self.use_scaled_pos_enc else PositionalEncoding) + + # define encoder + encoder_input_layer = nn.Embedding( + num_embeddings=idim, + embedding_dim=adim, + padding_idx=self.padding_idx) + + if encoder_type == "transformer": + self.encoder = TransformerEncoder( + idim=idim, + attention_dim=adim, + attention_heads=aheads, + linear_units=eunits, + num_blocks=elayers, + input_layer=encoder_input_layer, + dropout_rate=transformer_enc_dropout_rate, + positional_dropout_rate=transformer_enc_positional_dropout_rate, + attention_dropout_rate=transformer_enc_attn_dropout_rate, + pos_enc_class=pos_enc_class, + normalize_before=encoder_normalize_before, + concat_after=encoder_concat_after, + positionwise_layer_type=positionwise_layer_type, + positionwise_conv_kernel_size=positionwise_conv_kernel_size, ) + else: + raise ValueError(f"{encoder_type} is not supported.") + + # define additional projection for speaker embedding + if self.spk_embed_dim is not None: + if self.spk_embed_integration_type == "add": + self.spk_projection = nn.Linear(self.spk_embed_dim, adim) + else: + self.spk_projection = nn.Linear(adim + self.spk_embed_dim, adim) + + # define additional projection for tone embedding + if self.tone_embed_dim is not None: + if self.tone_embed_integration_type == "add": + self.tone_projection = nn.Linear(self.tone_embed_dim, adim) + else: + self.tone_projection = nn.Linear(adim + self.tone_embed_dim, + adim) + + # define duration predictor + self.duration_predictor = DurationPredictor( + idim=adim, + n_layers=duration_predictor_layers, + n_chans=duration_predictor_chans, + kernel_size=duration_predictor_kernel_size, + dropout_rate=duration_predictor_dropout_rate, ) + + # define pitch predictor + self.pitch_predictor = VariancePredictor( + idim=adim, + n_layers=pitch_predictor_layers, + n_chans=pitch_predictor_chans, + kernel_size=pitch_predictor_kernel_size, + dropout_rate=pitch_predictor_dropout, ) + # We use continuous pitch + FastPitch style avg + self.pitch_embed = nn.Sequential( + nn.Conv1D( + in_channels=1, + out_channels=adim, + kernel_size=pitch_embed_kernel_size, + padding=(pitch_embed_kernel_size - 1) // 2, ), + nn.Dropout(pitch_embed_dropout), ) + + # define energy predictor + self.energy_predictor = VariancePredictor( + idim=adim, + n_layers=energy_predictor_layers, + n_chans=energy_predictor_chans, + kernel_size=energy_predictor_kernel_size, + dropout_rate=energy_predictor_dropout, ) + # We use continuous enegy + FastPitch style avg + self.energy_embed = nn.Sequential( + nn.Conv1D( + in_channels=1, + out_channels=adim, + kernel_size=energy_embed_kernel_size, + padding=(energy_embed_kernel_size - 1) // 2, ), + nn.Dropout(energy_embed_dropout), ) + + # define length regulator + self.length_regulator = LengthRegulator() + + # define decoder + # NOTE: we use encoder as decoder + # because fastspeech's decoder is the same as encoder + if decoder_type == "transformer": + self.decoder = TransformerEncoder( + idim=0, + attention_dim=adim, + attention_heads=aheads, + linear_units=dunits, + num_blocks=dlayers, + # in decoder, don't need layer before pos_enc_class (we use embedding here in encoder) + input_layer=None, + dropout_rate=transformer_dec_dropout_rate, + positional_dropout_rate=transformer_dec_positional_dropout_rate, + attention_dropout_rate=transformer_dec_attn_dropout_rate, + pos_enc_class=pos_enc_class, + normalize_before=decoder_normalize_before, + concat_after=decoder_concat_after, + positionwise_layer_type=positionwise_layer_type, + positionwise_conv_kernel_size=positionwise_conv_kernel_size, ) + else: + raise ValueError(f"{decoder_type} is not supported.") + + # define final projection + self.feat_out = nn.Linear(adim, odim * reduction_factor) + + # define postnet + self.postnet = (None if postnet_layers == 0 else Postnet( + idim=idim, + odim=odim, + n_layers=postnet_layers, + n_chans=postnet_chans, + n_filts=postnet_filts, + use_batch_norm=use_batch_norm, + dropout_rate=postnet_dropout_rate, )) + + nn.initializer.set_global_initializer(None) + + self._reset_parameters( + init_enc_alpha=init_enc_alpha, + init_dec_alpha=init_dec_alpha, ) + + def forward( + self, + text: paddle.Tensor, + text_lengths: paddle.Tensor, + speech: paddle.Tensor, + speech_lengths: paddle.Tensor, + durations: paddle.Tensor, + pitch: paddle.Tensor, + energy: paddle.Tensor, + tone_id: paddle.Tensor=None, + spembs: paddle.Tensor=None, + spk_id: paddle.Tensor=None + ) -> Tuple[paddle.Tensor, Dict[str, paddle.Tensor], paddle.Tensor]: + """Calculate forward propagation. + + Parameters + ---------- + text : Tensor(int64) + Batch of padded token ids (B, Tmax). + text_lengths : Tensor(int64) + Batch of lengths of each input (B,). + speech : Tensor + Batch of padded target features (B, Lmax, odim). + speech_lengths : Tensor(int64) + Batch of the lengths of each target (B,). + durations : Tensor(int64) + Batch of padded durations (B, Tmax). + pitch : Tensor + Batch of padded token-averaged pitch (B, Tmax, 1). + energy : Tensor + Batch of padded token-averaged energy (B, Tmax, 1). + tone_id : Tensor, optional(int64) + Batch of padded tone ids (B, Tmax). + spembs : Tensor, optional + Batch of speaker embeddings (B, spk_embed_dim). + spk_id : Tnesor, optional(int64) + Batch of speaker ids (B,) + + Returns + ---------- + Tensor + mel outs before postnet + Tensor + mel outs after postnet + Tensor + duration predictor's output + Tensor + pitch predictor's output + Tensor + energy predictor's output + Tensor + speech + Tensor + speech_lengths, modified if reduction_factor > 1 + """ + # input of embedding must be int64 + xs = paddle.cast(text, 'int64') + ilens = paddle.cast(text_lengths, 'int64') + ds = paddle.cast(durations, 'int64') + olens = paddle.cast(speech_lengths, 'int64') + ys = speech + ps = pitch + es = energy + if spk_id is not None: + spk_id = paddle.cast(spk_id, 'int64') + if tone_id is not None: + tone_id = paddle.cast(tone_id, 'int64') + # forward propagation + before_outs, after_outs, d_outs, p_outs, e_outs = self._forward( + xs, + ilens, + olens, + ds, + ps, + es, + is_inference=False, + spembs=spembs, + spk_id=spk_id, + tone_id=tone_id) + # modify mod part of groundtruth + if self.reduction_factor > 1: + olens = paddle.to_tensor( + [olen - olen % self.reduction_factor for olen in olens.numpy()]) + max_olen = max(olens) + ys = ys[:, :max_olen] + + return before_outs, after_outs, d_outs, p_outs, e_outs, ys, olens + + def _forward(self, + xs: paddle.Tensor, + ilens: paddle.Tensor, + olens: paddle.Tensor=None, + ds: paddle.Tensor=None, + ps: paddle.Tensor=None, + es: paddle.Tensor=None, + is_inference: bool=False, + alpha: float=1.0, + spembs=None, + spk_id=None, + tone_id=None) -> Sequence[paddle.Tensor]: + # forward encoder + x_masks = self._source_mask(ilens) + + # (B, Tmax, adim) + hs, _ = self.encoder(xs, x_masks) + + # integrate speaker embedding + if self.spk_embed_dim is not None: + if spembs is not None: + hs = self._integrate_with_spk_embed(hs, spembs) + elif spk_id is not None: + spembs = self.spk_embedding_table(spk_id) + hs = self._integrate_with_spk_embed(hs, spembs) + + # integrate tone embedding + if self.tone_embed_dim is not None: + if tone_id is not None: + tone_embs = self.tone_embedding_table(tone_id) + hs = self._integrate_with_tone_embed(hs, tone_embs) + + # forward duration predictor and variance predictors + d_masks = make_pad_mask(ilens) + + if self.stop_gradient_from_pitch_predictor: + p_outs = self.pitch_predictor(hs.detach(), d_masks.unsqueeze(-1)) + else: + p_outs = self.pitch_predictor(hs, d_masks.unsqueeze(-1)) + if self.stop_gradient_from_energy_predictor: + e_outs = self.energy_predictor(hs.detach(), d_masks.unsqueeze(-1)) + else: + e_outs = self.energy_predictor(hs, d_masks.unsqueeze(-1)) + + if is_inference: + # (B, Tmax) + d_outs = self.duration_predictor.inference(hs, d_masks) + # use prediction in inference + # (B, Tmax, 1) + p_embs = self.pitch_embed(p_outs.transpose((0, 2, 1))).transpose( + (0, 2, 1)) + e_embs = self.energy_embed(e_outs.transpose((0, 2, 1))).transpose( + (0, 2, 1)) + hs = hs + e_embs + p_embs + # (B, Lmax, adim) + hs = self.length_regulator(hs, d_outs, alpha) + else: + d_outs = self.duration_predictor(hs, d_masks) + # use groundtruth in training + p_embs = self.pitch_embed(ps.transpose((0, 2, 1))).transpose( + (0, 2, 1)) + e_embs = self.energy_embed(es.transpose((0, 2, 1))).transpose( + (0, 2, 1)) + hs = hs + e_embs + p_embs + # (B, Lmax, adim) + hs = self.length_regulator(hs, ds) + + # forward decoder + if olens is not None and not is_inference: + if self.reduction_factor > 1: + olens_in = paddle.to_tensor( + [olen // self.reduction_factor for olen in olens.numpy()]) + else: + olens_in = olens + h_masks = self._source_mask(olens_in) + else: + h_masks = None + # (B, Lmax, adim) + zs, _ = self.decoder(hs, h_masks) + # (B, Lmax, odim) + before_outs = self.feat_out(zs).reshape((zs.shape[0], -1, self.odim)) + + # postnet -> (B, Lmax//r * r, odim) + if self.postnet is None: + after_outs = before_outs + else: + after_outs = before_outs + self.postnet( + before_outs.transpose((0, 2, 1))).transpose((0, 2, 1)) + + return before_outs, after_outs, d_outs, p_outs, e_outs + + def inference( + self, + text: paddle.Tensor, + speech: paddle.Tensor=None, + durations: paddle.Tensor=None, + pitch: paddle.Tensor=None, + energy: paddle.Tensor=None, + alpha: float=1.0, + use_teacher_forcing: bool=False, + spembs=None, + spk_id=None, + tone_id=None, + ) -> Tuple[paddle.Tensor, paddle.Tensor, paddle.Tensor]: + """Generate the sequence of features given the sequences of characters. + + Parameters + ---------- + text : Tensor(int64) + Input sequence of characters (T,). + speech : Tensor, optional + Feature sequence to extract style (N, idim). + durations : Tensor, optional (int64) + Groundtruth of duration (T,). + pitch : Tensor, optional + Groundtruth of token-averaged pitch (T, 1). + energy : Tensor, optional + Groundtruth of token-averaged energy (T, 1). + alpha : float, optional + Alpha to control the speed. + use_teacher_forcing : bool, optional + Whether to use teacher forcing. + If true, groundtruth of duration, pitch and energy will be used. + spembs : Tensor, optional + peaker embedding vector (spk_embed_dim,). + spk_id : Tensor, optional(int64) + Speaker embedding vector (spk_embed_dim). + tone_id : Tensor, optional(int64) + Batch of padded tone ids (B, Tmax). + + Returns + ---------- + Tensor + Output sequence of features (L, odim). + """ + # input of embedding must be int64 + x = paddle.cast(text, 'int64') + y = speech + spemb = spembs + if durations: + d = paddle.cast(durations, 'int64') + p, e = pitch, energy + # setup batch axis + ilens = paddle.to_tensor( + [x.shape[0]], dtype=paddle.int64, place=x.place) + xs, ys = x.unsqueeze(0), None + + if y is not None: + ys = y.unsqueeze(0) + + if spemb is not None: + spembs = spemb.unsqueeze(0) + else: + spembs = None + + if use_teacher_forcing: + # use groundtruth of duration, pitch, and energy + ds, ps, es = d.unsqueeze(0), p.unsqueeze(0), e.unsqueeze(0) + # (1, L, odim) + _, outs, *_ = self._forward( + xs, + ilens, + ys, + ds=ds, + ps=ps, + es=es, + spembs=spembs, + spk_id=spk_id, + tone_id=tone_id) + else: + # (1, L, odim) + _, outs, *_ = self._forward( + xs, + ilens, + ys, + is_inference=True, + alpha=alpha, + spembs=spembs, + spk_id=spk_id, + tone_id=tone_id) + + return outs[0] + + def _integrate_with_spk_embed(self, hs, spembs): + """Integrate speaker embedding with hidden states. + + Parameters + ---------- + hs : Tensor + Batch of hidden state sequences (B, Tmax, adim). + spembs : Tensor + Batch of speaker embeddings (B, spk_embed_dim). + + Returns + ---------- + Tensor + Batch of integrated hidden state sequences (B, Tmax, adim) + """ + if self.spk_embed_integration_type == "add": + # apply projection and then add to hidden states + spembs = self.spk_projection(F.normalize(spembs)) + hs = hs + spembs.unsqueeze(1) + elif self.spk_embed_integration_type == "concat": + # concat hidden states with spk embeds and then apply projection + spembs = F.normalize(spembs).unsqueeze(1).expand( + shape=[-1, hs.shape[1], -1]) + hs = self.spk_projection(paddle.concat([hs, spembs], axis=-1)) + else: + raise NotImplementedError("support only add or concat.") + + return hs + + def _integrate_with_tone_embed(self, hs, tone_embs): + """Integrate speaker embedding with hidden states. + + Parameters + ---------- + hs : Tensor + Batch of hidden state sequences (B, Tmax, adim). + tone_embs : Tensor + Batch of speaker embeddings (B, Tmax, tone_embed_dim). + + Returns + ---------- + Tensor + Batch of integrated hidden state sequences (B, Tmax, adim) + """ + if self.tone_embed_integration_type == "add": + # apply projection and then add to hidden states + tone_embs = self.tone_projection(F.normalize(tone_embs)) + hs = hs + tone_embs + + elif self.tone_embed_integration_type == "concat": + # concat hidden states with tone embeds and then apply projection + tone_embs = F.normalize(tone_embs).expand( + shape=[-1, hs.shape[1], -1]) + hs = self.tone_projection(paddle.concat([hs, tone_embs], axis=-1)) + else: + raise NotImplementedError("support only add or concat.") + return hs + + def _source_mask(self, ilens: paddle.Tensor) -> paddle.Tensor: + """Make masks for self-attention. + + Parameters + ---------- + ilens : Tensor + Batch of lengths (B,). + + Returns + ------- + Tensor + Mask tensor for self-attention. + dtype=paddle.bool + + Examples + ------- + >>> ilens = [5, 3] + >>> self._source_mask(ilens) + tensor([[[1, 1, 1, 1, 1], + [1, 1, 1, 0, 0]]]) bool + + """ + x_masks = make_non_pad_mask(ilens) + return x_masks.unsqueeze(-2) + + def _reset_parameters(self, init_enc_alpha: float, init_dec_alpha: float): + + # initialize alpha in scaled positional encoding + if self.encoder_type == "transformer" and self.use_scaled_pos_enc: + init_enc_alpha = paddle.to_tensor(init_enc_alpha) + self.encoder.embed[-1].alpha = paddle.create_parameter( + shape=init_enc_alpha.shape, + dtype=str(init_enc_alpha.numpy().dtype), + default_initializer=paddle.nn.initializer.Assign( + init_enc_alpha)) + if self.decoder_type == "transformer" and self.use_scaled_pos_enc: + init_dec_alpha = paddle.to_tensor(init_dec_alpha) + self.decoder.embed[-1].alpha = paddle.create_parameter( + shape=init_dec_alpha.shape, + dtype=str(init_dec_alpha.numpy().dtype), + default_initializer=paddle.nn.initializer.Assign( + init_dec_alpha)) + + +class FastSpeech2Inference(nn.Layer): + def __init__(self, normalizer, model): + super().__init__() + self.normalizer = normalizer + self.acoustic_model = model + + def forward(self, text, spk_id=None): + normalized_mel = self.acoustic_model.inference(text, spk_id=spk_id) + logmel = self.normalizer.inverse(normalized_mel) + return logmel + + +class FastSpeech2Loss(nn.Layer): + """Loss function module for FastSpeech2.""" + + def __init__(self, use_masking: bool=True, + use_weighted_masking: bool=False): + """Initialize feed-forward Transformer loss module. + + Parameters + ---------- + use_masking : bool + Whether to apply masking for padded part in loss calculation. + use_weighted_masking : bool + Whether to weighted masking in loss calculation. + """ + assert check_argument_types() + super().__init__() + + assert (use_masking != use_weighted_masking) or not use_masking + self.use_masking = use_masking + self.use_weighted_masking = use_weighted_masking + + # define criterions + reduction = "none" if self.use_weighted_masking else "mean" + self.l1_criterion = nn.L1Loss(reduction=reduction) + self.mse_criterion = nn.MSELoss(reduction=reduction) + self.duration_criterion = DurationPredictorLoss(reduction=reduction) + + def forward( + self, + after_outs: paddle.Tensor, + before_outs: paddle.Tensor, + d_outs: paddle.Tensor, + p_outs: paddle.Tensor, + e_outs: paddle.Tensor, + ys: paddle.Tensor, + ds: paddle.Tensor, + ps: paddle.Tensor, + es: paddle.Tensor, + ilens: paddle.Tensor, + olens: paddle.Tensor, + ) -> Tuple[paddle.Tensor, paddle.Tensor, paddle.Tensor, paddle.Tensor]: + """Calculate forward propagation. + + Parameters + ---------- + after_outs : Tensor + Batch of outputs after postnets (B, Lmax, odim). + before_outs : Tensor + Batch of outputs before postnets (B, Lmax, odim). + d_outs : Tensor + Batch of outputs of duration predictor (B, Tmax). + p_outs : Tensor + Batch of outputs of pitch predictor (B, Tmax, 1). + e_outs : Tensor + Batch of outputs of energy predictor (B, Tmax, 1). + ys : Tensor + Batch of target features (B, Lmax, odim). + ds : Tensor + Batch of durations (B, Tmax). + ps : Tensor + Batch of target token-averaged pitch (B, Tmax, 1). + es : Tensor + Batch of target token-averaged energy (B, Tmax, 1). + ilens : Tensor + Batch of the lengths of each input (B,). + olens : Tensor + Batch of the lengths of each target (B,). + + Returns + ---------- + Tensor + L1 loss value. + Tensor + Duration predictor loss value. + Tensor + Pitch predictor loss value. + Tensor + Energy predictor loss value. + + """ + # apply mask to remove padded part + if self.use_masking: + out_masks = make_non_pad_mask(olens).unsqueeze(-1) + before_outs = before_outs.masked_select( + out_masks.broadcast_to(before_outs.shape)) + if after_outs is not None: + after_outs = after_outs.masked_select( + out_masks.broadcast_to(after_outs.shape)) + ys = ys.masked_select(out_masks.broadcast_to(ys.shape)) + duration_masks = make_non_pad_mask(ilens) + d_outs = d_outs.masked_select( + duration_masks.broadcast_to(d_outs.shape)) + ds = ds.masked_select(duration_masks.broadcast_to(ds.shape)) + pitch_masks = make_non_pad_mask(ilens).unsqueeze(-1) + p_outs = p_outs.masked_select( + pitch_masks.broadcast_to(p_outs.shape)) + e_outs = e_outs.masked_select( + pitch_masks.broadcast_to(e_outs.shape)) + ps = ps.masked_select(pitch_masks.broadcast_to(ps.shape)) + es = es.masked_select(pitch_masks.broadcast_to(es.shape)) + + # calculate loss + l1_loss = self.l1_criterion(before_outs, ys) + if after_outs is not None: + l1_loss += self.l1_criterion(after_outs, ys) + duration_loss = self.duration_criterion(d_outs, ds) + pitch_loss = self.mse_criterion(p_outs, ps) + energy_loss = self.mse_criterion(e_outs, es) + + # make weighted mask and apply it + if self.use_weighted_masking: + out_masks = make_non_pad_mask(olens).unsqueeze(-1) + out_weights = out_masks.cast(dtype=paddle.float32) / out_masks.cast( + dtype=paddle.float32).sum( + axis=1, keepdim=True) + out_weights /= ys.shape[0] * ys.shape[2] + duration_masks = make_non_pad_mask(ilens) + duration_weights = (duration_masks.cast(dtype=paddle.float32) / + duration_masks.cast(dtype=paddle.float32).sum( + axis=1, keepdim=True)) + duration_weights /= ds.shape[0] + + # apply weight + + l1_loss = l1_loss.multiply(out_weights) + l1_loss = l1_loss.masked_select( + out_masks.broadcast_to(l1_loss.shape)).sum() + duration_loss = (duration_loss.multiply(duration_weights) + .masked_select(duration_masks).sum()) + pitch_masks = duration_masks.unsqueeze(-1) + pitch_weights = duration_weights.unsqueeze(-1) + pitch_loss = pitch_loss.multiply(pitch_weights) + pitch_loss = pitch_loss.masked_select( + pitch_masks.broadcast_to(pitch_loss.shape)).sum() + energy_loss = energy_loss.multiply(pitch_weights) + energy_loss = energy_loss.masked_select( + pitch_masks.broadcast_to(energy_loss.shape)).sum() + + return l1_loss, duration_loss, pitch_loss, energy_loss diff --git a/parakeet/models/fastspeech2/fastspeech2_updater.py b/parakeet/models/fastspeech2/fastspeech2_updater.py new file mode 100644 index 00000000..789965f4 --- /dev/null +++ b/parakeet/models/fastspeech2/fastspeech2_updater.py @@ -0,0 +1,166 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import logging + +from paddle import distributed as dist +from parakeet.models.fastspeech2 import FastSpeech2Loss +from parakeet.training.extensions.evaluator import StandardEvaluator +from parakeet.training.reporter import report +from parakeet.training.updaters.standard_updater import StandardUpdater +logging.basicConfig( + format='%(asctime)s [%(levelname)s] [%(filename)s:%(lineno)d] %(message)s', + datefmt='[%Y-%m-%d %H:%M:%S]') +logger = logging.getLogger(__name__) +logger.setLevel(logging.INFO) + + +class FastSpeech2Updater(StandardUpdater): + def __init__(self, + model, + optimizer, + dataloader, + init_state=None, + use_masking=False, + use_weighted_masking=False, + output_dir=None): + super().__init__(model, optimizer, dataloader, init_state=None) + self.use_masking = use_masking + self.use_weighted_masking = use_weighted_masking + + self.criterion = FastSpeech2Loss( + use_masking=self.use_masking, + use_weighted_masking=self.use_weighted_masking) + + log_file = output_dir / 'worker_{}.log'.format(dist.get_rank()) + self.filehandler = logging.FileHandler(str(log_file)) + logger.addHandler(self.filehandler) + self.logger = logger + self.msg = "" + + def update_core(self, batch): + self.msg = "Rank: {}, ".format(dist.get_rank()) + losses_dict = {} + # spk_id!=None in multiple spk fastspeech2 + spk_id = batch["spk_id"] if "spk_id" in batch else None + + before_outs, after_outs, d_outs, p_outs, e_outs, ys, olens = self.model( + text=batch["text"], + text_lengths=batch["text_lengths"], + speech=batch["speech"], + speech_lengths=batch["speech_lengths"], + durations=batch["durations"], + pitch=batch["pitch"], + energy=batch["energy"], + spk_id=spk_id) + + l1_loss, duration_loss, pitch_loss, energy_loss = self.criterion( + after_outs=after_outs, + before_outs=before_outs, + d_outs=d_outs, + p_outs=p_outs, + e_outs=e_outs, + ys=ys, + ds=batch["durations"], + ps=batch["pitch"], + es=batch["energy"], + ilens=batch["text_lengths"], + olens=olens) + + loss = l1_loss + duration_loss + pitch_loss + energy_loss + + optimizer = self.optimizer + optimizer.clear_grad() + loss.backward() + optimizer.step() + + report("train/loss", float(loss)) + report("train/l1_loss", float(l1_loss)) + report("train/duration_loss", float(duration_loss)) + report("train/pitch_loss", float(pitch_loss)) + report("train/energy_loss", float(energy_loss)) + + losses_dict["l1_loss"] = float(l1_loss) + losses_dict["duration_loss"] = float(duration_loss) + losses_dict["pitch_loss"] = float(pitch_loss) + losses_dict["energy_loss"] = float(energy_loss) + losses_dict["loss"] = float(loss) + self.msg += ', '.join('{}: {:>.6f}'.format(k, v) + for k, v in losses_dict.items()) + + +class FastSpeech2Evaluator(StandardEvaluator): + def __init__(self, + model, + dataloader, + use_masking=False, + use_weighted_masking=False, + output_dir=None): + super().__init__(model, dataloader) + self.use_masking = use_masking + self.use_weighted_masking = use_weighted_masking + + log_file = output_dir / 'worker_{}.log'.format(dist.get_rank()) + self.filehandler = logging.FileHandler(str(log_file)) + logger.addHandler(self.filehandler) + self.logger = logger + self.msg = "" + + self.criterion = FastSpeech2Loss( + use_masking=self.use_masking, + use_weighted_masking=self.use_weighted_masking) + + def evaluate_core(self, batch): + self.msg = "Evaluate: " + losses_dict = {} + # spk_id!=None in multiple spk fastspeech2 + spk_id = batch["spk_id"] if "spk_id" in batch else None + + before_outs, after_outs, d_outs, p_outs, e_outs, ys, olens = self.model( + text=batch["text"], + text_lengths=batch["text_lengths"], + speech=batch["speech"], + speech_lengths=batch["speech_lengths"], + durations=batch["durations"], + pitch=batch["pitch"], + energy=batch["energy"], + spk_id=spk_id) + + l1_loss, duration_loss, pitch_loss, energy_loss = self.criterion( + after_outs=after_outs, + before_outs=before_outs, + d_outs=d_outs, + p_outs=p_outs, + e_outs=e_outs, + ys=ys, + ds=batch["durations"], + ps=batch["pitch"], + es=batch["energy"], + ilens=batch["text_lengths"], + olens=olens, ) + loss = l1_loss + duration_loss + pitch_loss + energy_loss + + report("eval/loss", float(loss)) + report("eval/l1_loss", float(l1_loss)) + report("eval/duration_loss", float(duration_loss)) + report("eval/pitch_loss", float(pitch_loss)) + report("eval/energy_loss", float(energy_loss)) + + losses_dict["l1_loss"] = float(l1_loss) + losses_dict["duration_loss"] = float(duration_loss) + losses_dict["pitch_loss"] = float(pitch_loss) + losses_dict["energy_loss"] = float(energy_loss) + losses_dict["loss"] = float(loss) + self.msg += ', '.join('{}: {:>.6f}'.format(k, v) + for k, v in losses_dict.items()) + self.logger.info(self.msg) diff --git a/parakeet/models/lstm_speaker_encoder.py b/parakeet/models/lstm_speaker_encoder.py new file mode 100644 index 00000000..3372b212 --- /dev/null +++ b/parakeet/models/lstm_speaker_encoder.py @@ -0,0 +1,147 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import numpy as np +import paddle +from paddle import nn +from paddle.nn import functional as F +from paddle.nn import initializer as I +from scipy.interpolate import interp1d +from scipy.optimize import brentq +from sklearn.metrics import roc_curve + + +class LSTMSpeakerEncoder(nn.Layer): + def __init__(self, n_mels, num_layers, hidden_size, output_size): + super().__init__() + self.lstm = nn.LSTM(n_mels, hidden_size, num_layers) + self.linear = nn.Linear(hidden_size, output_size) + self.similarity_weight = self.create_parameter( + [1], default_initializer=I.Constant(10.)) + self.similarity_bias = self.create_parameter( + [1], default_initializer=I.Constant(-5.)) + + def forward(self, utterances, num_speakers, initial_states=None): + normalized_embeds = self.embed_sequences(utterances, initial_states) + embeds = normalized_embeds.reshape([num_speakers, -1, num_speakers]) + loss, eer = self.loss(embeds) + return loss, eer + + def embed_sequences(self, utterances, initial_states=None, reduce=False): + out, (h, c) = self.lstm(utterances, initial_states) + embeds = F.relu(self.linear(h[-1])) + normalized_embeds = F.normalize(embeds) + if reduce: + embed = paddle.mean(normalized_embeds, 0) + embed = F.normalize(embed, axis=0) + return embed + return normalized_embeds + + def embed_utterance(self, utterances, initial_states=None): + # utterances: [B, T, C] -> embed [C'] + embed = self.embed_sequences(utterances, initial_states, reduce=True) + return embed + + def similarity_matrix(self, embeds): + # (N, M, C) + speakers_per_batch, utterances_per_speaker, embed_dim = embeds.shape + + # Inclusive centroids (1 per speaker). Cloning is needed for reverse differentiation + centroids_incl = paddle.mean(embeds, axis=1) + centroids_incl_norm = paddle.norm( + centroids_incl, p=2, axis=1, keepdim=True) + normalized_centroids_incl = centroids_incl / centroids_incl_norm + + # Exclusive centroids (1 per utterance) + centroids_excl = paddle.broadcast_to( + paddle.sum(embeds, axis=1, keepdim=True), embeds.shape) - embeds + centroids_excl /= (utterances_per_speaker - 1) + centroids_excl_norm = paddle.norm( + centroids_excl, p=2, axis=2, keepdim=True) + normalized_centroids_excl = centroids_excl / centroids_excl_norm + + p1 = paddle.matmul( + embeds.reshape([-1, embed_dim]), + normalized_centroids_incl, + transpose_y=True) # (NMN) + p1 = p1.reshape([-1]) + # print("p1: ", p1.shape) + p2 = paddle.bmm( + embeds.reshape([-1, 1, embed_dim]), + normalized_centroids_excl.reshape([-1, embed_dim, 1])) # (NM, 1, 1) + p2 = p2.reshape([-1]) # （NM) + + # begin: alternative implementation for scatter + with paddle.no_grad(): + index = paddle.arange( + 0, speakers_per_batch * utterances_per_speaker, + dtype="int64").reshape( + [speakers_per_batch, utterances_per_speaker]) + index = index * speakers_per_batch + paddle.arange( + 0, speakers_per_batch, dtype="int64").unsqueeze(-1) + index = paddle.reshape(index, [-1]) + ones = paddle.ones( + [speakers_per_batch * utterances_per_speaker * speakers_per_batch]) + zeros = paddle.zeros_like(index, dtype=ones.dtype) + mask_p1 = paddle.scatter(ones, index, zeros) + p = p1 * mask_p1 + (1 - mask_p1) * paddle.scatter(ones, index, p2) + # end: alternative implementation for scatter + # p = paddle.scatter(p1, index, p2) + + p = p * self.similarity_weight + self.similarity_bias # neg + p = p.reshape( + [speakers_per_batch * utterances_per_speaker, speakers_per_batch]) + return p, p1, p2 + + def do_gradient_ops(self): + for p in [self.similarity_weight, self.similarity_bias]: + g = p._grad_ivar() + g[...] = g * 0.01 + + def inv_argmax(self, i, num): + return np.eye(1, num, i, dtype=np.int)[0] + + def loss(self, embeds): + """ + Computes the softmax loss according the section 2.1 of GE2E. + + :param embeds: the embeddings as a tensor of shape (speakers_per_batch, + utterances_per_speaker, embedding_size) + :return: the loss and the EER for this batch of embeddings. + """ + speakers_per_batch, utterances_per_speaker = embeds.shape[:2] + + # Loss + sim_matrix, *_ = self.similarity_matrix(embeds) + sim_matrix = sim_matrix.reshape( + [speakers_per_batch * utterances_per_speaker, speakers_per_batch]) + target = paddle.arange( + 0, speakers_per_batch, dtype="int64").unsqueeze(-1) + target = paddle.expand(target, + [speakers_per_batch, utterances_per_speaker]) + target = paddle.reshape(target, [-1]) + + loss = nn.CrossEntropyLoss()(sim_matrix, target) + + # EER (not backpropagated) + with paddle.no_grad(): + ground_truth = target.numpy() + labels = np.array( + [self.inv_argmax(i, speakers_per_batch) for i in ground_truth]) + preds = sim_matrix.numpy() + + # Snippet from https://yangcha.github.io/EER-ROC/ + fpr, tpr, thresholds = roc_curve(labels.flatten(), preds.flatten()) + eer = brentq(lambda x: 1. - x - interp1d(fpr, tpr)(x), 0., 1.) + + return loss, eer diff --git a/parakeet/models/parallel_wavegan/__init__.py b/parakeet/models/parallel_wavegan/__init__.py new file mode 100644 index 00000000..89403c0e --- /dev/null +++ b/parakeet/models/parallel_wavegan/__init__.py @@ -0,0 +1,16 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from .parallel_wavegan import * +from .parallel_wavegan_updater import * diff --git a/parakeet/models/parallel_wavegan/parallel_wavegan.py b/parakeet/models/parallel_wavegan/parallel_wavegan.py new file mode 100644 index 00000000..bb214653 --- /dev/null +++ b/parakeet/models/parallel_wavegan/parallel_wavegan.py @@ -0,0 +1,775 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import math +from typing import Any +from typing import Dict +from typing import List +from typing import Optional + +import numpy as np +import paddle +from paddle import nn +from paddle.nn import functional as F + + +class Stretch2D(nn.Layer): + def __init__(self, w_scale: int, h_scale: int, mode: str="nearest"): + """Strech an image (or image-like object) with some interpolation. + + Parameters + ---------- + w_scale : int + Scalar of width. + h_scale : int + Scalar of the height. + mode : str, optional + Interpolation mode, modes suppored are "nearest", "bilinear", + "trilinear", "bicubic", "linear" and "area",by default "nearest" + + For more details about interpolation, see + `paddle.nn.functional.interpolate `_. + """ + super().__init__() + self.w_scale = w_scale + self.h_scale = h_scale + self.mode = mode + + def forward(self, x): + """ + Parameters + ---------- + x : Tensor + Shape (N, C, H, W) + + Returns + ------- + Tensor + Shape (N, C, H', W'), where ``H'=h_scale * H``, ``W'=w_scale * W``. + The stretched image. + """ + out = F.interpolate( + x, scale_factor=(self.h_scale, self.w_scale), mode=self.mode) + return out + + +class UpsampleNet(nn.Layer): + """A Layer to upsample spectrogram by applying consecutive stretch and + convolutions. + + Parameters + ---------- + upsample_scales : List[int] + Upsampling factors for each strech. + nonlinear_activation : Optional[str], optional + Activation after each convolution, by default None + nonlinear_activation_params : Dict[str, Any], optional + Parameters passed to construct the activation, by default {} + interpolate_mode : str, optional + Interpolation mode of the strech, by default "nearest" + freq_axis_kernel_size : int, optional + Convolution kernel size along the frequency axis, by default 1 + use_causal_conv : bool, optional + Whether to use causal padding before convolution, by default False + + If True, Causal padding is used along the time axis, i.e. padding + amount is ``receptive field - 1`` and 0 for before and after, + respectively. + + If False, "same" padding is used along the time axis. + """ + + def __init__(self, + upsample_scales: List[int], + nonlinear_activation: Optional[str]=None, + nonlinear_activation_params: Dict[str, Any]={}, + interpolate_mode: str="nearest", + freq_axis_kernel_size: int=1, + use_causal_conv: bool=False): + super().__init__() + self.use_causal_conv = use_causal_conv + self.up_layers = nn.LayerList() + for scale in upsample_scales: + stretch = Stretch2D(scale, 1, interpolate_mode) + assert freq_axis_kernel_size % 2 == 1 + freq_axis_padding = (freq_axis_kernel_size - 1) // 2 + kernel_size = (freq_axis_kernel_size, scale * 2 + 1) + if use_causal_conv: + padding = (freq_axis_padding, scale * 2) + else: + padding = (freq_axis_padding, scale) + conv = nn.Conv2D( + 1, 1, kernel_size, padding=padding, bias_attr=False) + self.up_layers.extend([stretch, conv]) + if nonlinear_activation is not None: + nonlinear = getattr( + nn, nonlinear_activation)(**nonlinear_activation_params) + self.up_layers.append(nonlinear) + + def forward(self, c): + """ + Parameters + ---------- + c : Tensor + Shape (N, F, T), spectrogram + + Returns + ------- + Tensor + Shape (N, F, T'), where ``T' = upsample_factor * T``, upsampled + spectrogram + """ + c = c.unsqueeze(1) + for f in self.up_layers: + if self.use_causal_conv and isinstance(f, nn.Conv2D): + c = f(c)[:, :, :, c.shape[-1]] + else: + c = f(c) + return c.squeeze(1) + + +class ConvInUpsampleNet(nn.Layer): + """A Layer to upsample spectrogram composed of a convolution and an + UpsampleNet. + + Parameters + ---------- + upsample_scales : List[int] + Upsampling factors for each strech. + nonlinear_activation : Optional[str], optional + Activation after each convolution, by default None + nonlinear_activation_params : Dict[str, Any], optional + Parameters passed to construct the activation, by default {} + interpolate_mode : str, optional + Interpolation mode of the strech, by default "nearest" + freq_axis_kernel_size : int, optional + Convolution kernel size along the frequency axis, by default 1 + aux_channels : int, optional + Feature size of the input, by default 80 + aux_context_window : int, optional + Context window of the first 1D convolution applied to the input. It + related to the kernel size of the convolution, by default 0 + + If use causal convolution, the kernel size is ``window + 1``, else + the kernel size is ``2 * window + 1``. + use_causal_conv : bool, optional + Whether to use causal padding before convolution, by default False + + If True, Causal padding is used along the time axis, i.e. padding + amount is ``receptive field - 1`` and 0 for before and after, + respectively. + + If False, "same" padding is used along the time axis. + """ + + def __init__(self, + upsample_scales: List[int], + nonlinear_activation: Optional[str]=None, + nonlinear_activation_params: Dict[str, Any]={}, + interpolate_mode: str="nearest", + freq_axis_kernel_size: int=1, + aux_channels: int=80, + aux_context_window: int=0, + use_causal_conv: bool=False): + super().__init__() + self.aux_context_window = aux_context_window + self.use_causal_conv = use_causal_conv and aux_context_window > 0 + kernel_size = aux_context_window + 1 if use_causal_conv else 2 * aux_context_window + 1 + self.conv_in = nn.Conv1D( + aux_channels, + aux_channels, + kernel_size=kernel_size, + bias_attr=False) + self.upsample = UpsampleNet( + upsample_scales=upsample_scales, + nonlinear_activation=nonlinear_activation, + nonlinear_activation_params=nonlinear_activation_params, + interpolate_mode=interpolate_mode, + freq_axis_kernel_size=freq_axis_kernel_size, + use_causal_conv=use_causal_conv) + + def forward(self, c): + """ + Parameters + ---------- + c : Tensor + Shape (N, F, T), spectrogram + + Returns + ------- + Tensors + Shape (N, F, T'), where ``T' = upsample_factor * T``, upsampled + spectrogram + """ + c_ = self.conv_in(c) + c = c_[:, :, :-self.aux_context_window] if self.use_causal_conv else c_ + return self.upsample(c) + + +class ResidualBlock(nn.Layer): + """A gated activation unit composed of an 1D convolution, a gated tanh + unit and parametric redidual and skip connections. For more details, + refer to `WaveNet: A Generative Model for Raw Audio `_. + + Parameters + ---------- + kernel_size : int, optional + Kernel size of the 1D convolution, by default 3 + residual_channels : int, optional + Feature size of the resiaudl output(and also the input), by default 64 + gate_channels : int, optional + Output feature size of the 1D convolution, by default 128 + skip_channels : int, optional + Feature size of the skip output, by default 64 + aux_channels : int, optional + Feature size of the auxiliary input (e.g. spectrogram), by default 80 + dropout : float, optional + Probability of the dropout before the 1D convolution, by default 0. + dilation : int, optional + Dilation of the 1D convolution, by default 1 + bias : bool, optional + Whether to use bias in the 1D convolution, by default True + use_causal_conv : bool, optional + Whether to use causal padding for the 1D convolution, by default False + """ + + def __init__(self, + kernel_size: int=3, + residual_channels: int=64, + gate_channels: int=128, + skip_channels: int=64, + aux_channels: int=80, + dropout: float=0., + dilation: int=1, + bias: bool=True, + use_causal_conv: bool=False): + super().__init__() + self.dropout = dropout + if use_causal_conv: + padding = (kernel_size - 1) * dilation + else: + assert kernel_size % 2 == 1 + padding = (kernel_size - 1) // 2 * dilation + self.use_causal_conv = use_causal_conv + + self.conv = nn.Conv1D( + residual_channels, + gate_channels, + kernel_size, + padding=padding, + dilation=dilation, + bias_attr=bias) + if aux_channels is not None: + self.conv1x1_aux = nn.Conv1D( + aux_channels, gate_channels, kernel_size=1, bias_attr=False) + else: + self.conv1x1_aux = None + + gate_out_channels = gate_channels // 2 + self.conv1x1_out = nn.Conv1D( + gate_out_channels, residual_channels, kernel_size=1, bias_attr=bias) + self.conv1x1_skip = nn.Conv1D( + gate_out_channels, skip_channels, kernel_size=1, bias_attr=bias) + + def forward(self, x, c): + """ + Parameters + ---------- + x : Tensor + Shape (N, C_res, T), the input features. + c : Tensor + Shape (N, C_aux, T), the auxiliary input. + + Returns + ------- + res : Tensor + Shape (N, C_res, T), the residual output, which is used as the + input of the next ResidualBlock in a stack of ResidualBlocks. + skip : Tensor + Shape (N, C_skip, T), the skip output, which is collected among + each layer in a stack of ResidualBlocks. + """ + x_input = x + x = F.dropout(x, self.dropout, training=self.training) + x = self.conv(x) + x = x[:, :, x_input.shape[-1]] if self.use_causal_conv else x + if c is not None: + c = self.conv1x1_aux(c) + x += c + + a, b = paddle.chunk(x, 2, axis=1) + x = paddle.tanh(a) * F.sigmoid(b) + + skip = self.conv1x1_skip(x) + res = (self.conv1x1_out(x) + x_input) * math.sqrt(0.5) + return res, skip + + +class PWGGenerator(nn.Layer): + """Wave Generator for Parallel WaveGAN + + Parameters + ---------- + in_channels : int, optional + Number of channels of the input waveform, by default 1 + out_channels : int, optional + Number of channels of the output waveform, by default 1 + kernel_size : int, optional + Kernel size of the residual blocks inside, by default 3 + layers : int, optional + Number of residual blocks inside, by default 30 + stacks : int, optional + The number of groups to split the residual blocks into, by default 3 + + Within each group, the dilation of the residual block grows + exponentially. + residual_channels : int, optional + Residual channel of the residual blocks, by default 64 + gate_channels : int, optional + Gate channel of the residual blocks, by default 128 + skip_channels : int, optional + Skip channel of the residual blocks, by default 64 + aux_channels : int, optional + Auxiliary channel of the residual blocks, by default 80 + aux_context_window : int, optional + The context window size of the first convolution applied to the + auxiliary input, by default 2 + dropout : float, optional + Dropout of the residual blocks, by default 0. + bias : bool, optional + Whether to use bias in residual blocks, by default True + use_weight_norm : bool, optional + Whether to use weight norm in all convolutions, by default True + use_causal_conv : bool, optional + Whether to use causal padding in the upsample network and residual + blocks, by default False + upsample_scales : List[int], optional + Upsample scales of the upsample network, by default [4, 4, 4, 4] + nonlinear_activation : Optional[str], optional + Non linear activation in upsample network, by default None + nonlinear_activation_params : Dict[str, Any], optional + Parameters passed to the linear activation in the upsample network, + by default {} + interpolate_mode : str, optional + Interpolation mode of the upsample network, by default "nearest" + freq_axis_kernel_size : int, optional + Kernel size along the frequency axis of the upsample network, by default 1 + """ + + def __init__(self, + in_channels: int=1, + out_channels: int=1, + kernel_size: int=3, + layers: int=30, + stacks: int=3, + residual_channels: int=64, + gate_channels: int=128, + skip_channels: int=64, + aux_channels: int=80, + aux_context_window: int=2, + dropout: float=0., + bias: bool=True, + use_weight_norm: bool=True, + use_causal_conv: bool=False, + upsample_scales: List[int]=[4, 4, 4, 4], + nonlinear_activation: Optional[str]=None, + nonlinear_activation_params: Dict[str, Any]={}, + interpolate_mode: str="nearest", + freq_axis_kernel_size: int=1): + super().__init__() + self.in_channels = in_channels + self.out_channels = out_channels + self.aux_channels = aux_channels + self.aux_context_window = aux_context_window + self.layers = layers + self.stacks = stacks + self.kernel_size = kernel_size + + assert layers % stacks == 0 + layers_per_stack = layers // stacks + + self.first_conv = nn.Conv1D( + in_channels, residual_channels, 1, bias_attr=True) + self.upsample_net = ConvInUpsampleNet( + upsample_scales=upsample_scales, + nonlinear_activation=nonlinear_activation, + nonlinear_activation_params=nonlinear_activation_params, + interpolate_mode=interpolate_mode, + freq_axis_kernel_size=freq_axis_kernel_size, + aux_channels=aux_channels, + aux_context_window=aux_context_window, + use_causal_conv=use_causal_conv) + self.upsample_factor = np.prod(upsample_scales) + + self.conv_layers = nn.LayerList() + for layer in range(layers): + dilation = 2**(layer % layers_per_stack) + conv = ResidualBlock( + kernel_size=kernel_size, + residual_channels=residual_channels, + gate_channels=gate_channels, + skip_channels=skip_channels, + aux_channels=aux_channels, + dilation=dilation, + dropout=dropout, + bias=bias, + use_causal_conv=use_causal_conv) + self.conv_layers.append(conv) + + self.last_conv_layers = nn.Sequential(nn.ReLU(), + nn.Conv1D( + skip_channels, + skip_channels, + 1, + bias_attr=True), + nn.ReLU(), + nn.Conv1D( + skip_channels, + out_channels, + 1, + bias_attr=True)) + + if use_weight_norm: + self.apply_weight_norm() + + def forward(self, x, c): + """Generate waveform. + + Parameters + ---------- + x : Tensor + Shape (N, C_in, T), The input waveform. + c : Tensor + Shape (N, C_aux, T'). The auxiliary input (e.g. spectrogram). It + is upsampled to match the time resolution of the input. + + Returns + ------- + Tensor + Shape (N, C_out, T), the generated waveform. + """ + c = self.upsample_net(c) + assert c.shape[-1] == x.shape[-1] + + x = self.first_conv(x) + skips = 0 + for f in self.conv_layers: + x, s = f(x, c) + skips += s + skips *= math.sqrt(1.0 / len(self.conv_layers)) + + x = self.last_conv_layers(skips) + return x + + def apply_weight_norm(self): + """Recursively apply weight normalization to all the Convolution layers + in the sublayers. + """ + + def _apply_weight_norm(layer): + if isinstance(layer, (nn.Conv1D, nn.Conv2D)): + nn.utils.weight_norm(layer) + + self.apply(_apply_weight_norm) + + def remove_weight_norm(self): + """Recursively remove weight normalization from all the Convolution + layers in the sublayers. + """ + + def _remove_weight_norm(layer): + try: + nn.utils.remove_weight_norm(layer) + except ValueError: + pass + + self.apply(_remove_weight_norm) + + def inference(self, c=None): + """Waveform generation. This function is used for single instance + inference. + + Parameters + ---------- + c : Tensor, optional + Shape (T', C_aux), the auxiliary input, by default None + x : Tensor, optional + Shape (T, C_in), the noise waveform, by default None + If not provided, a sample is drawn from a gaussian distribution. + + Returns + ------- + Tensor + Shape (T, C_out), the generated waveform + """ + x = paddle.randn( + [1, self.in_channels, paddle.shape(c)[0] * self.upsample_factor]) + c = paddle.transpose(c, [1, 0]).unsqueeze(0) # pseudo batch + c = nn.Pad1D(self.aux_context_window, mode='replicate')(c) + out = self(x, c).squeeze(0).transpose([1, 0]) + return out + + +class PWGDiscriminator(nn.Layer): + """A convolutional discriminator for audio. + + Parameters + ---------- + in_channels : int, optional + Number of channels of the input audio, by default 1 + out_channels : int, optional + Output feature size, by default 1 + kernel_size : int, optional + Kernel size of convolutional sublayers, by default 3 + layers : int, optional + Number of layers, by default 10 + conv_channels : int, optional + Feature size of the convolutional sublayers, by default 64 + dilation_factor : int, optional + The factor with which dilation of each convolutional sublayers grows + exponentially if it is greater than 1, else the dilation of each + convolutional sublayers grows linearly, by default 1 + nonlinear_activation : str, optional + The activation after each convolutional sublayer, by default "LeakyReLU" + nonlinear_activation_params : Dict[str, Any], optional + The parameters passed to the activation's initializer, by default + {"negative_slope": 0.2} + bias : bool, optional + Whether to use bias in convolutional sublayers, by default True + use_weight_norm : bool, optional + Whether to use weight normalization at all convolutional sublayers, + by default True + """ + + def __init__( + self, + in_channels: int=1, + out_channels: int=1, + kernel_size: int=3, + layers: int=10, + conv_channels: int=64, + dilation_factor: int=1, + nonlinear_activation: str="LeakyReLU", + nonlinear_activation_params: Dict[str, Any]={"negative_slope": 0.2}, + bias: bool=True, + use_weight_norm: bool=True): + super().__init__() + assert kernel_size % 2 == 1 + assert dilation_factor > 0 + conv_layers = [] + conv_in_channels = in_channels + for i in range(layers - 1): + if i == 0: + dilation = 1 + else: + dilation = i if dilation_factor == 1 else dilation_factor**i + conv_in_channels = conv_channels + padding = (kernel_size - 1) // 2 * dilation + conv_layer = nn.Conv1D( + conv_in_channels, + conv_channels, + kernel_size, + padding=padding, + dilation=dilation, + bias_attr=bias) + nonlinear = getattr( + nn, nonlinear_activation)(**nonlinear_activation_params) + conv_layers.append(conv_layer) + conv_layers.append(nonlinear) + padding = (kernel_size - 1) // 2 + last_conv = nn.Conv1D( + conv_in_channels, + out_channels, + kernel_size, + padding=padding, + bias_attr=bias) + conv_layers.append(last_conv) + self.conv_layers = nn.Sequential(*conv_layers) + + if use_weight_norm: + self.apply_weight_norm() + + def forward(self, x): + """ + Parameters + ---------- + x : Tensor + Shape (N, in_channels, num_samples), the input audio. + + Returns + ------- + Tensor + Shape (N, out_channels, num_samples), the predicted logits. + """ + return self.conv_layers(x) + + def apply_weight_norm(self): + def _apply_weight_norm(layer): + if isinstance(layer, (nn.Conv1D, nn.Conv2D)): + nn.utils.weight_norm(layer) + + self.apply(_apply_weight_norm) + + def remove_weight_norm(self): + def _remove_weight_norm(layer): + try: + nn.utils.remove_weight_norm(layer) + except ValueError: + pass + + self.apply(_remove_weight_norm) + + +class ResidualPWGDiscriminator(nn.Layer): + """A wavenet-style discriminator for audio. + + Parameters + ---------- + in_channels : int, optional + Number of channels of the input audio, by default 1 + out_channels : int, optional + Output feature size, by default 1 + kernel_size : int, optional + Kernel size of residual blocks, by default 3 + layers : int, optional + Number of residual blocks, by default 30 + stacks : int, optional + Number of groups of residual blocks, within which the dilation + of each residual blocks grows exponentially, by default 3 + residual_channels : int, optional + Residual channels of residual blocks, by default 64 + gate_channels : int, optional + Gate channels of residual blocks, by default 128 + skip_channels : int, optional + Skip channels of residual blocks, by default 64 + dropout : float, optional + Dropout probability of residual blocks, by default 0. + bias : bool, optional + Whether to use bias in residual blocks, by default True + use_weight_norm : bool, optional + Whether to use weight normalization in all convolutional layers, + by default True + use_causal_conv : bool, optional + Whether to use causal convolution in residual blocks, by default False + nonlinear_activation : str, optional + Activation after convolutions other than those in residual blocks, + by default "LeakyReLU" + nonlinear_activation_params : Dict[str, Any], optional + Parameters to pass to the activation, by default {"negative_slope": 0.2} + """ + + def __init__(self, + in_channels: int=1, + out_channels: int=1, + kernel_size: int=3, + layers: int=30, + stacks: int=3, + residual_channels: int=64, + gate_channels: int=128, + skip_channels: int=64, + dropout: float=0., + bias: bool=True, + use_weight_norm: bool=True, + use_causal_conv: bool=False, + nonlinear_activation: str="LeakyReLU", + nonlinear_activation_params: Dict[ + str, Any]={"negative_slope": 0.2}): + super().__init__() + assert kernel_size % 2 == 1 + self.in_channels = in_channels + self.out_channels = out_channels + self.layers = layers + self.stacks = stacks + self.kernel_size = kernel_size + + assert layers % stacks == 0 + layers_per_stack = layers // stacks + + self.first_conv = nn.Sequential( + nn.Conv1D(in_channels, residual_channels, 1, bias_attr=True), + getattr(nn, nonlinear_activation)(**nonlinear_activation_params)) + + self.conv_layers = nn.LayerList() + for layer in range(layers): + dilation = 2**(layer % layers_per_stack) + conv = ResidualBlock( + kernel_size=kernel_size, + residual_channels=residual_channels, + gate_channels=gate_channels, + skip_channels=skip_channels, + aux_channels=None, # no auxiliary input + dropout=dropout, + dilation=dilation, + bias=bias, + use_causal_conv=use_causal_conv) + self.conv_layers.append(conv) + + self.last_conv_layers = nn.Sequential( + getattr(nn, nonlinear_activation)(**nonlinear_activation_params), + nn.Conv1D(skip_channels, skip_channels, 1, bias_attr=True), + getattr(nn, nonlinear_activation)(**nonlinear_activation_params), + nn.Conv1D(skip_channels, out_channels, 1, bias_attr=True)) + + if use_weight_norm: + self.apply_weight_norm() + + def forward(self, x): + """ + Parameters + ---------- + x : Tensor + Shape (N, in_channels, num_samples), the input audio. + + Returns + ------- + Tensor + Shape (N, out_channels, num_samples), the predicted logits. + """ + x = self.first_conv(x) + skip = 0 + for f in self.conv_layers: + x, h = f(x, None) + skip += h + skip *= math.sqrt(1 / len(self.conv_layers)) + + x = skip + x = self.last_conv_layers(x) + return x + + def apply_weight_norm(self): + def _apply_weight_norm(layer): + if isinstance(layer, (nn.Conv1D, nn.Conv2D)): + nn.utils.weight_norm(layer) + + self.apply(_apply_weight_norm) + + def remove_weight_norm(self): + def _remove_weight_norm(layer): + try: + nn.utils.remove_weight_norm(layer) + except ValueError: + pass + + self.apply(_remove_weight_norm) + + +class PWGInference(nn.Layer): + def __init__(self, normalizer, pwg_generator): + super().__init__() + self.normalizer = normalizer + self.pwg_generator = pwg_generator + + def forward(self, logmel): + normalized_mel = self.normalizer(logmel) + wav = self.pwg_generator.inference(normalized_mel) + return wav diff --git a/parakeet/models/parallel_wavegan/parallel_wavegan_updater.py b/parakeet/models/parallel_wavegan/parallel_wavegan_updater.py new file mode 100644 index 00000000..68328fb3 --- /dev/null +++ b/parakeet/models/parallel_wavegan/parallel_wavegan_updater.py @@ -0,0 +1,231 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import logging +from typing import Dict + +import paddle +from paddle import distributed as dist +from paddle.io import DataLoader +from paddle.nn import Layer +from paddle.optimizer import Optimizer +from paddle.optimizer.lr import LRScheduler +from parakeet.training.extensions.evaluator import StandardEvaluator +from parakeet.training.reporter import report +from parakeet.training.updaters.standard_updater import StandardUpdater +from parakeet.training.updaters.standard_updater import UpdaterState +from timer import timer +logging.basicConfig( + format='%(asctime)s [%(levelname)s] [%(filename)s:%(lineno)d] %(message)s', + datefmt='[%Y-%m-%d %H:%M:%S]') +logger = logging.getLogger(__name__) +logger.setLevel(logging.INFO) + + +class PWGUpdater(StandardUpdater): + def __init__(self, + models: Dict[str, Layer], + optimizers: Dict[str, Optimizer], + criterions: Dict[str, Layer], + schedulers: Dict[str, LRScheduler], + dataloader: DataLoader, + discriminator_train_start_steps: int, + lambda_adv: float, + output_dir=None): + self.models = models + self.generator: Layer = models['generator'] + self.discriminator: Layer = models['discriminator'] + + self.optimizers = optimizers + self.optimizer_g: Optimizer = optimizers['generator'] + self.optimizer_d: Optimizer = optimizers['discriminator'] + + self.criterions = criterions + self.criterion_stft = criterions['stft'] + self.criterion_mse = criterions['mse'] + + self.schedulers = schedulers + self.scheduler_g = schedulers['generator'] + self.scheduler_d = schedulers['discriminator'] + + self.dataloader = dataloader + + self.discriminator_train_start_steps = discriminator_train_start_steps + self.lambda_adv = lambda_adv + self.state = UpdaterState(iteration=0, epoch=0) + + self.train_iterator = iter(self.dataloader) + + log_file = output_dir / 'worker_{}.log'.format(dist.get_rank()) + self.filehandler = logging.FileHandler(str(log_file)) + logger.addHandler(self.filehandler) + self.logger = logger + self.msg = "" + + def update_core(self, batch): + self.msg = "Rank: {}, ".format(dist.get_rank()) + losses_dict = {} + + # parse batch + wav, mel = batch + + # Generator + noise = paddle.randn(wav.shape) + + with timer() as t: + wav_ = self.generator(noise, mel) + # logging.debug(f"Generator takes {t.elapse}s.") + + # initialize + gen_loss = 0.0 + + ## Multi-resolution stft loss + with timer() as t: + sc_loss, mag_loss = self.criterion_stft(wav_, wav) + # logging.debug(f"Multi-resolution STFT loss takes {t.elapse}s.") + + report("train/spectral_convergence_loss", float(sc_loss)) + report("train/log_stft_magnitude_loss", float(mag_loss)) + + losses_dict["spectral_convergence_loss"] = float(sc_loss) + losses_dict["log_stft_magnitude_loss"] = float(mag_loss) + + gen_loss += sc_loss + mag_loss + + ## Adversarial loss + if self.state.iteration > self.discriminator_train_start_steps: + with timer() as t: + p_ = self.discriminator(wav_) + adv_loss = self.criterion_mse(p_, paddle.ones_like(p_)) + # logging.debug( + # f"Discriminator and adversarial loss takes {t.elapse}s") + report("train/adversarial_loss", float(adv_loss)) + losses_dict["adversarial_loss"] = float(adv_loss) + gen_loss += self.lambda_adv * adv_loss + + report("train/generator_loss", float(gen_loss)) + losses_dict["generator_loss"] = float(gen_loss) + + with timer() as t: + self.optimizer_g.clear_grad() + gen_loss.backward() + # logging.debug(f"Backward takes {t.elapse}s.") + + with timer() as t: + self.optimizer_g.step() + self.scheduler_g.step() + # logging.debug(f"Update takes {t.elapse}s.") + + # Disctiminator + if self.state.iteration > self.discriminator_train_start_steps: + with paddle.no_grad(): + wav_ = self.generator(noise, mel) + p = self.discriminator(wav) + p_ = self.discriminator(wav_.detach()) + real_loss = self.criterion_mse(p, paddle.ones_like(p)) + fake_loss = self.criterion_mse(p_, paddle.zeros_like(p_)) + dis_loss = real_loss + fake_loss + report("train/real_loss", float(real_loss)) + report("train/fake_loss", float(fake_loss)) + report("train/discriminator_loss", float(dis_loss)) + losses_dict["real_loss"] = float(real_loss) + losses_dict["fake_loss"] = float(fake_loss) + losses_dict["discriminator_loss"] = float(dis_loss) + + self.optimizer_d.clear_grad() + dis_loss.backward() + + self.optimizer_d.step() + self.scheduler_d.step() + + self.msg += ', '.join('{}: {:>.6f}'.format(k, v) + for k, v in losses_dict.items()) + + +class PWGEvaluator(StandardEvaluator): + def __init__(self, + models, + criterions, + dataloader, + lambda_adv, + output_dir=None): + self.models = models + self.generator = models['generator'] + self.discriminator = models['discriminator'] + + self.criterions = criterions + self.criterion_stft = criterions['stft'] + self.criterion_mse = criterions['mse'] + + self.dataloader = dataloader + self.lambda_adv = lambda_adv + + log_file = output_dir / 'worker_{}.log'.format(dist.get_rank()) + self.filehandler = logging.FileHandler(str(log_file)) + logger.addHandler(self.filehandler) + self.logger = logger + self.msg = "" + + def evaluate_core(self, batch): + # logging.debug("Evaluate: ") + self.msg = "Evaluate: " + losses_dict = {} + + wav, mel = batch + noise = paddle.randn(wav.shape) + + with timer() as t: + wav_ = self.generator(noise, mel) + # logging.debug(f"Generator takes {t.elapse}s") + + ## Adversarial loss + with timer() as t: + p_ = self.discriminator(wav_) + adv_loss = self.criterion_mse(p_, paddle.ones_like(p_)) + # logging.debug( + # f"Discriminator and adversarial loss takes {t.elapse}s") + report("eval/adversarial_loss", float(adv_loss)) + losses_dict["adversarial_loss"] = float(adv_loss) + gen_loss = self.lambda_adv * adv_loss + + # stft loss + with timer() as t: + sc_loss, mag_loss = self.criterion_stft(wav_, wav) + # logging.debug(f"Multi-resolution STFT loss takes {t.elapse}s") + + report("eval/spectral_convergence_loss", float(sc_loss)) + report("eval/log_stft_magnitude_loss", float(mag_loss)) + losses_dict["spectral_convergence_loss"] = float(sc_loss) + losses_dict["log_stft_magnitude_loss"] = float(mag_loss) + gen_loss += sc_loss + mag_loss + + report("eval/generator_loss", float(gen_loss)) + losses_dict["generator_loss"] = float(gen_loss) + + # Disctiminator + p = self.discriminator(wav) + real_loss = self.criterion_mse(p, paddle.ones_like(p)) + fake_loss = self.criterion_mse(p_, paddle.zeros_like(p_)) + dis_loss = real_loss + fake_loss + report("eval/real_loss", float(real_loss)) + report("eval/fake_loss", float(fake_loss)) + report("eval/discriminator_loss", float(dis_loss)) + + losses_dict["real_loss"] = float(real_loss) + losses_dict["fake_loss"] = float(fake_loss) + losses_dict["discriminator_loss"] = float(dis_loss) + + self.msg += ', '.join('{}: {:>.6f}'.format(k, v) + for k, v in losses_dict.items()) + self.logger.info(self.msg) diff --git a/parakeet/models/speedyspeech/__init__.py b/parakeet/models/speedyspeech/__init__.py new file mode 100644 index 00000000..6d9b7088 --- /dev/null +++ b/parakeet/models/speedyspeech/__init__.py @@ -0,0 +1,16 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from .speedyspeech import * +from .speedyspeech_updater import * diff --git a/parakeet/models/speedyspeech/speedyspeech.py b/parakeet/models/speedyspeech/speedyspeech.py new file mode 100644 index 00000000..dea567b6 --- /dev/null +++ b/parakeet/models/speedyspeech/speedyspeech.py @@ -0,0 +1,232 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import paddle +from paddle import nn + +from parakeet.modules.expansion import expand +from parakeet.modules.positional_encoding import sinusoid_position_encoding + + +class ResidualBlock(nn.Layer): + def __init__(self, channels, kernel_size, dilation, n=2): + super().__init__() + blocks = [ + nn.Sequential( + nn.Conv1D( + channels, + channels, + kernel_size, + dilation=dilation, + padding="same", + data_format="NLC"), + nn.ReLU(), + nn.BatchNorm1D(channels, data_format="NLC"), ) for _ in range(n) + ] + self.blocks = nn.Sequential(*blocks) + + def forward(self, x): + return x + self.blocks(x) + + +class TextEmbedding(nn.Layer): + def __init__(self, + vocab_size: int, + embedding_size: int, + tone_vocab_size: int=None, + tone_embedding_size: int=None, + padding_idx: int=None, + tone_padding_idx: int=None, + concat: bool=False): + super().__init__() + self.text_embedding = nn.Embedding(vocab_size, embedding_size, + padding_idx) + if tone_vocab_size: + tone_embedding_size = tone_embedding_size or embedding_size + if tone_embedding_size != embedding_size and not concat: + raise ValueError( + "embedding size != tone_embedding size, only conat is avaiable." + ) + self.tone_embedding = nn.Embedding( + tone_vocab_size, tone_embedding_size, tone_padding_idx) + self.concat = concat + + def forward(self, text, tone=None): + text_embed = self.text_embedding(text) + if tone is None: + return text_embed + tone_embed = self.tone_embedding(tone) + if self.concat: + embed = paddle.concat([text_embed, tone_embed], -1) + else: + embed = text_embed + tone_embed + return embed + + +class SpeedySpeechEncoder(nn.Layer): + def __init__(self, vocab_size, tone_size, hidden_size, kernel_size, + dilations): + super().__init__() + self.embedding = TextEmbedding( + vocab_size, + hidden_size, + tone_size, + padding_idx=0, + tone_padding_idx=0) + self.prenet = nn.Sequential( + nn.Linear(hidden_size, hidden_size), + nn.ReLU(), ) + res_blocks = [ + ResidualBlock(hidden_size, kernel_size, d, n=2) for d in dilations + ] + self.res_blocks = nn.Sequential(*res_blocks) + + self.postnet1 = nn.Sequential(nn.Linear(hidden_size, hidden_size)) + self.postnet2 = nn.Sequential( + nn.ReLU(), + nn.BatchNorm1D(hidden_size, data_format="NLC"), + nn.Linear(hidden_size, hidden_size), ) + + def forward(self, text, tones): + embedding = self.embedding(text, tones) + embedding = self.prenet(embedding) + x = self.res_blocks(embedding) + x = embedding + self.postnet1(x) + x = self.postnet2(x) + return x + + +class DurationPredictor(nn.Layer): + def __init__(self, hidden_size): + super().__init__() + self.layers = nn.Sequential( + ResidualBlock(hidden_size, 4, 1, n=1), + ResidualBlock(hidden_size, 3, 1, n=1), + ResidualBlock(hidden_size, 1, 1, n=1), nn.Linear(hidden_size, 1)) + + def forward(self, x): + return paddle.squeeze(self.layers(x), -1) + + +class SpeedySpeechDecoder(nn.Layer): + def __init__(self, hidden_size, output_size, kernel_size, dilations): + super().__init__() + res_blocks = [ + ResidualBlock(hidden_size, kernel_size, d, n=2) for d in dilations + ] + self.res_blocks = nn.Sequential(*res_blocks) + + self.postnet1 = nn.Sequential(nn.Linear(hidden_size, hidden_size)) + self.postnet2 = nn.Sequential( + ResidualBlock(hidden_size, kernel_size, 1, n=2), + nn.Linear(hidden_size, output_size)) + + def forward(self, x): + xx = self.res_blocks(x) + x = x + self.postnet1(xx) + x = self.postnet2(x) + return x + + +class SpeedySpeech(nn.Layer): + def __init__( + self, + vocab_size, + encoder_hidden_size, + encoder_kernel_size, + encoder_dilations, + duration_predictor_hidden_size, + decoder_hidden_size, + decoder_output_size, + decoder_kernel_size, + decoder_dilations, + tone_size=None, ): + super().__init__() + encoder = SpeedySpeechEncoder(vocab_size, tone_size, + encoder_hidden_size, encoder_kernel_size, + encoder_dilations) + duration_predictor = DurationPredictor(duration_predictor_hidden_size) + decoder = SpeedySpeechDecoder(decoder_hidden_size, decoder_output_size, + decoder_kernel_size, decoder_dilations) + + self.encoder = encoder + self.duration_predictor = duration_predictor + self.decoder = decoder + + def forward(self, text, tones, durations): + # input of embedding must be int64 + text = paddle.cast(text, 'int64') + tones = paddle.cast(tones, 'int64') + durations = paddle.cast(durations, 'int64') + encodings = self.encoder(text, tones) + # (B, T) + pred_durations = self.duration_predictor(encodings.detach()) + + # expand encodings + durations_to_expand = durations + encodings = expand(encodings, durations_to_expand) + + # decode + # remove positional encoding here + _, t_dec, feature_size = encodings.shape + encodings += sinusoid_position_encoding(t_dec, feature_size) + decoded = self.decoder(encodings) + return decoded, pred_durations + + def inference(self, text, tones=None): + # text: [T] + # tones: [T] + # input of embedding must be int64 + text = paddle.cast(text, 'int64') + text = text.unsqueeze(0) + if tones is not None: + tones = paddle.cast(tones, 'int64') + tones = tones.unsqueeze(0) + + encodings = self.encoder(text, tones) + pred_durations = self.duration_predictor(encodings) # (1, T) + durations_to_expand = paddle.round(pred_durations.exp()) + durations_to_expand = (durations_to_expand).astype(paddle.int64) + + slens = paddle.sum(durations_to_expand, -1) # [1] + t_dec = slens[0] # [1] + t_enc = paddle.shape(pred_durations)[-1] + M = paddle.zeros([1, t_dec, t_enc]) + + k = paddle.full([1], 0, dtype=paddle.int64) + for j in range(t_enc): + d = durations_to_expand[0, j] + # If the d == 0, slice action is meaningless and not supported + if d >= 1: + M[0, k:k + d, j] = 1 + k += d + + encodings = paddle.matmul(M, encodings) + + shape = paddle.shape(encodings) + t_dec, feature_size = shape[1], shape[2] + encodings += sinusoid_position_encoding(t_dec, feature_size) + decoded = self.decoder(encodings) + return decoded[0] + + +class SpeedySpeechInference(nn.Layer): + def __init__(self, normalizer, speedyspeech_model): + super().__init__() + self.normalizer = normalizer + self.acoustic_model = speedyspeech_model + + def forward(self, phones, tones): + normalized_mel = self.acoustic_model.inference(phones, tones) + logmel = self.normalizer.inverse(normalized_mel) + return logmel diff --git a/parakeet/models/speedyspeech/speedyspeech_updater.py b/parakeet/models/speedyspeech/speedyspeech_updater.py new file mode 100644 index 00000000..3135d342 --- /dev/null +++ b/parakeet/models/speedyspeech/speedyspeech_updater.py @@ -0,0 +1,157 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import logging + +import paddle +from paddle import distributed as dist +from paddle.fluid.layers import huber_loss +from paddle.nn import functional as F +from parakeet.modules.losses import masked_l1_loss +from parakeet.modules.losses import weighted_mean +from parakeet.modules.ssim import ssim +from parakeet.training.extensions.evaluator import StandardEvaluator +from parakeet.training.reporter import report +from parakeet.training.updaters.standard_updater import StandardUpdater +logging.basicConfig( + format='%(asctime)s [%(levelname)s] [%(filename)s:%(lineno)d] %(message)s', + datefmt='[%Y-%m-%d %H:%M:%S]') +logger = logging.getLogger(__name__) +logger.setLevel(logging.INFO) + + +class SpeedySpeechUpdater(StandardUpdater): + def __init__(self, + model, + optimizer, + dataloader, + init_state=None, + output_dir=None): + super().__init__(model, optimizer, dataloader, init_state=None) + + log_file = output_dir / 'worker_{}.log'.format(dist.get_rank()) + self.filehandler = logging.FileHandler(str(log_file)) + logger.addHandler(self.filehandler) + self.logger = logger + self.msg = "" + + def update_core(self, batch): + self.msg = "Rank: {}, ".format(dist.get_rank()) + losses_dict = {} + + decoded, predicted_durations = self.model( + text=batch["phones"], + tones=batch["tones"], + durations=batch["durations"]) + + target_mel = batch["feats"] + spec_mask = F.sequence_mask( + batch["num_frames"], dtype=target_mel.dtype).unsqueeze(-1) + text_mask = F.sequence_mask( + batch["num_phones"], dtype=predicted_durations.dtype) + + # spec loss + l1_loss = masked_l1_loss(decoded, target_mel, spec_mask) + + # duration loss + target_durations = batch["durations"] + target_durations = paddle.maximum( + target_durations.astype(predicted_durations.dtype), + paddle.to_tensor([1.0])) + duration_loss = weighted_mean( + huber_loss( + predicted_durations, paddle.log(target_durations), delta=1.0), + text_mask, ) + + # ssim loss + ssim_loss = 1.0 - ssim((decoded * spec_mask).unsqueeze(1), + (target_mel * spec_mask).unsqueeze(1)) + + loss = l1_loss + ssim_loss + duration_loss + + optimizer = self.optimizer + optimizer.clear_grad() + loss.backward() + optimizer.step() + + report("train/loss", float(loss)) + report("train/l1_loss", float(l1_loss)) + report("train/duration_loss", float(duration_loss)) + report("train/ssim_loss", float(ssim_loss)) + + losses_dict["l1_loss"] = float(l1_loss) + losses_dict["duration_loss"] = float(duration_loss) + losses_dict["ssim_loss"] = float(ssim_loss) + losses_dict["loss"] = float(loss) + self.msg += ', '.join('{}: {:>.6f}'.format(k, v) + for k, v in losses_dict.items()) + + +class SpeedySpeechEvaluator(StandardEvaluator): + def __init__(self, model, dataloader, output_dir=None): + super().__init__(model, dataloader) + + log_file = output_dir / 'worker_{}.log'.format(dist.get_rank()) + self.filehandler = logging.FileHandler(str(log_file)) + logger.addHandler(self.filehandler) + self.logger = logger + self.msg = "" + + def evaluate_core(self, batch): + self.msg = "Evaluate: " + losses_dict = {} + + decoded, predicted_durations = self.model( + text=batch["phones"], + tones=batch["tones"], + durations=batch["durations"]) + + target_mel = batch["feats"] + spec_mask = F.sequence_mask( + batch["num_frames"], dtype=target_mel.dtype).unsqueeze(-1) + text_mask = F.sequence_mask( + batch["num_phones"], dtype=predicted_durations.dtype) + + # spec loss + l1_loss = masked_l1_loss(decoded, target_mel, spec_mask) + + # duration loss + target_durations = batch["durations"] + target_durations = paddle.maximum( + target_durations.astype(predicted_durations.dtype), + paddle.to_tensor([1.0])) + duration_loss = weighted_mean( + huber_loss( + predicted_durations, paddle.log(target_durations), delta=1.0), + text_mask, ) + + # ssim loss + ssim_loss = 1.0 - ssim((decoded * spec_mask).unsqueeze(1), + (target_mel * spec_mask).unsqueeze(1)) + + loss = l1_loss + ssim_loss + duration_loss + + # import pdb; pdb.set_trace() + + report("eval/loss", float(loss)) + report("eval/l1_loss", float(l1_loss)) + report("eval/duration_loss", float(duration_loss)) + report("eval/ssim_loss", float(ssim_loss)) + + losses_dict["l1_loss"] = float(l1_loss) + losses_dict["duration_loss"] = float(duration_loss) + losses_dict["ssim_loss"] = float(ssim_loss) + losses_dict["loss"] = float(loss) + self.msg += ', '.join('{}: {:>.6f}'.format(k, v) + for k, v in losses_dict.items()) + self.logger.info(self.msg) diff --git a/parakeet/models/tacotron2.py b/parakeet/models/tacotron2.py new file mode 100644 index 00000000..07af6b3f --- /dev/null +++ b/parakeet/models/tacotron2.py @@ -0,0 +1,982 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import math + +import paddle +from paddle import nn +from paddle.fluid.layers import sequence_mask +from paddle.nn import functional as F +from paddle.nn import initializer as I +from tqdm import trange + +from parakeet.modules.attention import LocationSensitiveAttention +from parakeet.modules.conv import Conv1dBatchNorm +from parakeet.modules.losses import guided_attention_loss +from parakeet.utils import checkpoint + +__all__ = ["Tacotron2", "Tacotron2Loss"] + + +class DecoderPreNet(nn.Layer): + """Decoder prenet module for Tacotron2. + + Parameters + ---------- + d_input: int + The input feature size. + + d_hidden: int + The hidden size. + + d_output: int + The output feature size. + + dropout_rate: float + The droput probability. + + """ + + def __init__(self, + d_input: int, + d_hidden: int, + d_output: int, + dropout_rate: float): + super().__init__() + + self.dropout_rate = dropout_rate + self.linear1 = nn.Linear(d_input, d_hidden, bias_attr=False) + self.linear2 = nn.Linear(d_hidden, d_output, bias_attr=False) + + def forward(self, x): + """Calculate forward propagation. + + Parameters + ---------- + x: Tensor [shape=(B, T_mel, C)] + Batch of the sequences of padded mel spectrogram. + + Returns + ------- + output: Tensor [shape=(B, T_mel, C)] + Batch of the sequences of padded hidden state. + + """ + + x = F.dropout(F.relu(self.linear1(x)), self.dropout_rate, training=True) + output = F.dropout( + F.relu(self.linear2(x)), self.dropout_rate, training=True) + return output + + +class DecoderPostNet(nn.Layer): + """Decoder postnet module for Tacotron2. + + Parameters + ---------- + d_mels: int + The number of mel bands. + + d_hidden: int + The hidden size of postnet. + + kernel_size: int + The kernel size of the conv layer in postnet. + + num_layers: int + The number of conv layers in postnet. + + dropout: float + The droput probability. + + """ + + def __init__(self, + d_mels: int, + d_hidden: int, + kernel_size: int, + num_layers: int, + dropout: float): + super().__init__() + self.dropout = dropout + self.num_layers = num_layers + + padding = int((kernel_size - 1) / 2) + + self.conv_batchnorms = nn.LayerList() + k = math.sqrt(1.0 / (d_mels * kernel_size)) + self.conv_batchnorms.append( + Conv1dBatchNorm( + d_mels, + d_hidden, + kernel_size=kernel_size, + padding=padding, + bias_attr=I.Uniform(-k, k), + data_format='NLC')) + + k = math.sqrt(1.0 / (d_hidden * kernel_size)) + self.conv_batchnorms.extend([ + Conv1dBatchNorm( + d_hidden, + d_hidden, + kernel_size=kernel_size, + padding=padding, + bias_attr=I.Uniform(-k, k), + data_format='NLC') for i in range(1, num_layers - 1) + ]) + + self.conv_batchnorms.append( + Conv1dBatchNorm( + d_hidden, + d_mels, + kernel_size=kernel_size, + padding=padding, + bias_attr=I.Uniform(-k, k), + data_format='NLC')) + + def forward(self, x): + """Calculate forward propagation. + + Parameters + ---------- + x: Tensor [shape=(B, T_mel, C)] + Output sequence of features from decoder. + + Returns + ------- + output: Tensor [shape=(B, T_mel, C)] + Output sequence of features after postnet. + + """ + + for i in range(len(self.conv_batchnorms) - 1): + x = F.dropout( + F.tanh(self.conv_batchnorms[i](x)), + self.dropout, + training=self.training) + output = F.dropout( + self.conv_batchnorms[self.num_layers - 1](x), + self.dropout, + training=self.training) + return output + + +class Tacotron2Encoder(nn.Layer): + """Tacotron2 encoder module for Tacotron2. + + Parameters + ---------- + d_hidden: int + The hidden size in encoder module. + + conv_layers: int + The number of conv layers. + + kernel_size: int + The kernel size of conv layers. + + p_dropout: float + The droput probability. + """ + + def __init__(self, + d_hidden: int, + conv_layers: int, + kernel_size: int, + p_dropout: float): + super().__init__() + + k = math.sqrt(1.0 / (d_hidden * kernel_size)) + self.conv_batchnorms = paddle.nn.LayerList([ + Conv1dBatchNorm( + d_hidden, + d_hidden, + kernel_size, + stride=1, + padding=int((kernel_size - 1) / 2), + bias_attr=I.Uniform(-k, k), + data_format='NLC') for i in range(conv_layers) + ]) + self.p_dropout = p_dropout + + self.hidden_size = int(d_hidden / 2) + self.lstm = nn.LSTM( + d_hidden, self.hidden_size, direction="bidirectional") + + def forward(self, x, input_lens=None): + """Calculate forward propagation of tacotron2 encoder. + + Parameters + ---------- + x: Tensor [shape=(B, T, C)] + Input embeddings. + + text_lens: Tensor [shape=(B,)], optional + Batch of lengths of each text input batch. Defaults to None. + + Returns + ------- + output : Tensor [shape=(B, T, C)] + Batch of the sequences of padded hidden states. + + """ + for conv_batchnorm in self.conv_batchnorms: + x = F.dropout( + F.relu(conv_batchnorm(x)), + self.p_dropout, + training=self.training) + + output, _ = self.lstm(inputs=x, sequence_length=input_lens) + return output + + +class Tacotron2Decoder(nn.Layer): + """Tacotron2 decoder module for Tacotron2. + + Parameters + ---------- + d_mels: int + The number of mel bands. + + reduction_factor: int + The reduction factor of tacotron. + + d_encoder: int + The hidden size of encoder. + + d_prenet: int + The hidden size in decoder prenet. + + d_attention_rnn: int + The attention rnn layer hidden size. + + d_decoder_rnn: int + The decoder rnn layer hidden size. + + d_attention: int + The hidden size of the linear layer in location sensitive attention. + + attention_filters: int + The filter size of the conv layer in location sensitive attention. + + attention_kernel_size: int + The kernel size of the conv layer in location sensitive attention. + + p_prenet_dropout: float + The droput probability in decoder prenet. + + p_attention_dropout: float + The droput probability in location sensitive attention. + + p_decoder_dropout: float + The droput probability in decoder. + + use_stop_token: bool + Whether to use a binary classifier for stop token prediction. + Defaults to False + """ + + def __init__(self, + d_mels: int, + reduction_factor: int, + d_encoder: int, + d_prenet: int, + d_attention_rnn: int, + d_decoder_rnn: int, + d_attention: int, + attention_filters: int, + attention_kernel_size: int, + p_prenet_dropout: float, + p_attention_dropout: float, + p_decoder_dropout: float, + use_stop_token: bool=False): + super().__init__() + self.d_mels = d_mels + self.reduction_factor = reduction_factor + self.d_encoder = d_encoder + self.d_attention_rnn = d_attention_rnn + self.d_decoder_rnn = d_decoder_rnn + self.p_attention_dropout = p_attention_dropout + self.p_decoder_dropout = p_decoder_dropout + + self.prenet = DecoderPreNet( + d_mels * reduction_factor, + d_prenet, + d_prenet, + dropout_rate=p_prenet_dropout) + + # attention_rnn takes attention's context vector has an + # auxiliary input + self.attention_rnn = nn.LSTMCell(d_prenet + d_encoder, d_attention_rnn) + + self.attention_layer = LocationSensitiveAttention( + d_attention_rnn, d_encoder, d_attention, attention_filters, + attention_kernel_size) + + # decoder_rnn takes prenet's output and attention_rnn's input + # as input + self.decoder_rnn = nn.LSTMCell(d_attention_rnn + d_encoder, + d_decoder_rnn) + self.linear_projection = nn.Linear(d_decoder_rnn + d_encoder, + d_mels * reduction_factor) + + self.use_stop_token = use_stop_token + if use_stop_token: + self.stop_layer = nn.Linear(d_decoder_rnn + d_encoder, 1) + + # states - temporary attributes + self.attention_hidden = None + self.attention_cell = None + + self.decoder_hidden = None + self.decoder_cell = None + + self.attention_weights = None + self.attention_weights_cum = None + self.attention_context = None + + self.key = None + self.mask = None + self.processed_key = None + + def _initialize_decoder_states(self, key): + """init states be used in decoder + """ + batch_size, encoder_steps, _ = key.shape + + self.attention_hidden = paddle.zeros( + shape=[batch_size, self.d_attention_rnn], dtype=key.dtype) + self.attention_cell = paddle.zeros( + shape=[batch_size, self.d_attention_rnn], dtype=key.dtype) + + self.decoder_hidden = paddle.zeros( + shape=[batch_size, self.d_decoder_rnn], dtype=key.dtype) + self.decoder_cell = paddle.zeros( + shape=[batch_size, self.d_decoder_rnn], dtype=key.dtype) + + self.attention_weights = paddle.zeros( + shape=[batch_size, encoder_steps], dtype=key.dtype) + self.attention_weights_cum = paddle.zeros( + shape=[batch_size, encoder_steps], dtype=key.dtype) + self.attention_context = paddle.zeros( + shape=[batch_size, self.d_encoder], dtype=key.dtype) + + self.key = key # [B, T, C] + # pre-compute projected keys to improve efficiency + self.processed_key = self.attention_layer.key_layer(key) # [B, T, C] + + def _decode(self, query): + """decode one time step + """ + cell_input = paddle.concat([query, self.attention_context], axis=-1) + + # The first lstm layer (or spec encoder lstm) + _, (self.attention_hidden, self.attention_cell) = self.attention_rnn( + cell_input, (self.attention_hidden, self.attention_cell)) + self.attention_hidden = F.dropout( + self.attention_hidden, + self.p_attention_dropout, + training=self.training) + + # Loaction sensitive attention + attention_weights_cat = paddle.stack( + [self.attention_weights, self.attention_weights_cum], axis=-1) + self.attention_context, self.attention_weights = self.attention_layer( + self.attention_hidden, self.processed_key, self.key, + attention_weights_cat, self.mask) + self.attention_weights_cum += self.attention_weights + + # The second lstm layer (or spec decoder lstm) + decoder_input = paddle.concat( + [self.attention_hidden, self.attention_context], axis=-1) + _, (self.decoder_hidden, self.decoder_cell) = self.decoder_rnn( + decoder_input, (self.decoder_hidden, self.decoder_cell)) + self.decoder_hidden = F.dropout( + self.decoder_hidden, + p=self.p_decoder_dropout, + training=self.training) + + # decode output one step + decoder_hidden_attention_context = paddle.concat( + [self.decoder_hidden, self.attention_context], axis=-1) + decoder_output = self.linear_projection( + decoder_hidden_attention_context) + if self.use_stop_token: + stop_logit = self.stop_layer(decoder_hidden_attention_context) + return decoder_output, self.attention_weights, stop_logit + return decoder_output, self.attention_weights + + def forward(self, keys, querys, mask): + """Calculate forward propagation of tacotron2 decoder. + + Parameters + ---------- + keys: Tensor[shape=(B, T_key, C)] + Batch of the sequences of padded output from encoder. + + querys: Tensor[shape(B, T_query, C)] + Batch of the sequences of padded mel spectrogram. + + mask: Tensor + Mask generated with text length. Shape should be (B, T_key, 1). + + Returns + ------- + mel_output: Tensor [shape=(B, T_query, C)] + Output sequence of features. + + alignments: Tensor [shape=(B, T_query, T_key)] + Attention weights. + """ + self._initialize_decoder_states(keys) + self.mask = mask + + querys = paddle.reshape( + querys, + [querys.shape[0], querys.shape[1] // self.reduction_factor, -1]) + start_step = paddle.zeros( + shape=[querys.shape[0], 1, querys.shape[-1]], dtype=querys.dtype) + querys = paddle.concat([start_step, querys], axis=1) + + querys = self.prenet(querys) + + mel_outputs, alignments = [], [] + stop_logits = [] + # Ignore the last time step + while len(mel_outputs) < querys.shape[1] - 1: + query = querys[:, len(mel_outputs), :] + if self.use_stop_token: + mel_output, attention_weights, stop_logit = self._decode(query) + else: + mel_output, attention_weights = self._decode(query) + mel_outputs.append(mel_output) + alignments.append(attention_weights) + if self.use_stop_token: + stop_logits.append(stop_logit) + + alignments = paddle.stack(alignments, axis=1) + mel_outputs = paddle.stack(mel_outputs, axis=1) + if self.use_stop_token: + stop_logits = paddle.concat(stop_logits, axis=1) + return mel_outputs, alignments, stop_logits + return mel_outputs, alignments + + def infer(self, key, max_decoder_steps=1000): + """Calculate forward propagation of tacotron2 decoder. + + Parameters + ---------- + keys: Tensor [shape=(B, T_key, C)] + Batch of the sequences of padded output from encoder. + + max_decoder_steps: int, optional + Number of max step when synthesize. Defaults to 1000. + + Returns + ------- + mel_output: Tensor [shape=(B, T_mel, C)] + Output sequence of features. + + alignments: Tensor [shape=(B, T_mel, T_key)] + Attention weights. + + """ + self._initialize_decoder_states(key) + self.mask = None # mask is not needed for single instance inference + encoder_steps = key.shape[1] + + # [B, C] + start_step = paddle.zeros( + shape=[key.shape[0], self.d_mels * self.reduction_factor], + dtype=key.dtype) + query = start_step # [B, C] + first_hit_end = None + + mel_outputs, alignments = [], [] + stop_logits = [] + for i in trange(max_decoder_steps): + query = self.prenet(query) + if self.use_stop_token: + mel_output, alignment, stop_logit = self._decode(query) + else: + mel_output, alignment = self._decode(query) + + mel_outputs.append(mel_output) + alignments.append(alignment) # (B=1, T) + if self.use_stop_token: + stop_logits.append(stop_logit) + + if self.use_stop_token: + if F.sigmoid(stop_logit) > 0.5: + print("hit stop condition!") + break + else: + if int(paddle.argmax(alignment[0])) == encoder_steps - 1: + if first_hit_end is None: + first_hit_end = i + elif i > (first_hit_end + 20): + print("content exhausted!") + break + if len(mel_outputs) == max_decoder_steps: + print("Warning! Reached max decoder steps!!!") + break + + query = mel_output + + alignments = paddle.stack(alignments, axis=1) + mel_outputs = paddle.stack(mel_outputs, axis=1) + if self.use_stop_token: + stop_logits = paddle.concat(stop_logits, axis=1) + return mel_outputs, alignments, stop_logits + return mel_outputs, alignments + + +class Tacotron2(nn.Layer): + """Tacotron2 model for end-to-end text-to-speech (E2E-TTS). + + This is a model of Spectrogram prediction network in Tacotron2 described + in `Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram + Predictions `_, + which converts the sequence of characters + into the sequence of mel spectrogram. + + Parameters + ---------- + vocab_size : int + Vocabulary size of phons of the model. + + n_tones: int + Vocabulary size of tones of the model. Defaults to None. If provided, + the model has an extra tone embedding. + + d_mels: int + Number of mel bands. + + d_encoder: int + Hidden size in encoder module. + + encoder_conv_layers: int + Number of conv layers in encoder. + + encoder_kernel_size: int + Kernel size of conv layers in encoder. + + d_prenet: int + Hidden size in decoder prenet. + + d_attention_rnn: int + Attention rnn layer hidden size in decoder. + + d_decoder_rnn: int + Decoder rnn layer hidden size in decoder. + + attention_filters: int + Filter size of the conv layer in location sensitive attention. + + attention_kernel_size: int + Kernel size of the conv layer in location sensitive attention. + + d_attention: int + Hidden size of the linear layer in location sensitive attention. + + d_postnet: int + Hidden size of postnet. + + postnet_kernel_size: int + Kernel size of the conv layer in postnet. + + postnet_conv_layers: int + Number of conv layers in postnet. + + reduction_factor: int + Reduction factor of tacotron2. + + p_encoder_dropout: float + Droput probability in encoder. + + p_prenet_dropout: float + Droput probability in decoder prenet. + + p_attention_dropout: float + Droput probability in location sensitive attention. + + p_decoder_dropout: float + Droput probability in decoder. + + p_postnet_dropout: float + Droput probability in postnet. + + d_global_condition: int + Feature size of global condition. Defaults to None. If provided, The + model assumes a global condition that is concatenated to the encoder + outputs. + + """ + + def __init__(self, + vocab_size, + n_tones=None, + d_mels: int=80, + d_encoder: int=512, + encoder_conv_layers: int=3, + encoder_kernel_size: int=5, + d_prenet: int=256, + d_attention_rnn: int=1024, + d_decoder_rnn: int=1024, + attention_filters: int=32, + attention_kernel_size: int=31, + d_attention: int=128, + d_postnet: int=512, + postnet_kernel_size: int=5, + postnet_conv_layers: int=5, + reduction_factor: int=1, + p_encoder_dropout: float=0.5, + p_prenet_dropout: float=0.5, + p_attention_dropout: float=0.1, + p_decoder_dropout: float=0.1, + p_postnet_dropout: float=0.5, + d_global_condition=None, + use_stop_token=False): + super().__init__() + + std = math.sqrt(2.0 / (vocab_size + d_encoder)) + val = math.sqrt(3.0) * std # uniform bounds for std + self.embedding = nn.Embedding( + vocab_size, d_encoder, weight_attr=I.Uniform(-val, val)) + if n_tones: + self.embedding_tones = nn.Embedding( + n_tones, + d_encoder, + padding_idx=0, + weight_attr=I.Uniform(-0.1 * val, 0.1 * val)) + self.toned = n_tones is not None + + self.encoder = Tacotron2Encoder(d_encoder, encoder_conv_layers, + encoder_kernel_size, p_encoder_dropout) + + # input augmentation scheme: concat global condition to the encoder output + if d_global_condition is not None: + d_encoder += d_global_condition + self.decoder = Tacotron2Decoder( + d_mels, + reduction_factor, + d_encoder, + d_prenet, + d_attention_rnn, + d_decoder_rnn, + d_attention, + attention_filters, + attention_kernel_size, + p_prenet_dropout, + p_attention_dropout, + p_decoder_dropout, + use_stop_token=use_stop_token) + self.postnet = DecoderPostNet( + d_mels=d_mels * reduction_factor, + d_hidden=d_postnet, + kernel_size=postnet_kernel_size, + num_layers=postnet_conv_layers, + dropout=p_postnet_dropout) + + def forward(self, + text_inputs, + text_lens, + mels, + output_lens=None, + tones=None, + global_condition=None): + """Calculate forward propagation of tacotron2. + + Parameters + ---------- + text_inputs: Tensor [shape=(B, T_text)] + Batch of the sequencees of padded character ids. + + text_lens: Tensor [shape=(B,)] + Batch of lengths of each text input batch. + + mels: Tensor [shape(B, T_mel, C)] + Batch of the sequences of padded mel spectrogram. + + output_lens: Tensor [shape=(B,)], optional + Batch of lengths of each mels batch. Defaults to None. + + tones: Tensor [shape=(B, T_text)] + Batch of sequences of padded tone ids. + + global_condition: Tensor [shape(B, C)] + Batch of global conditions. Defaults to None. If the + `d_global_condition` of the model is not None, this input should be + provided. + + use_stop_token: bool + Whether to include a binary classifier to predict the stop token. + Defaults to False. + + Returns + ------- + outputs : Dict[str, Tensor] + + mel_output: output sequence of features (B, T_mel, C); + + mel_outputs_postnet: output sequence of features after postnet (B, T_mel, C); + + alignments: attention weights (B, T_mel, T_text); + + stop_logits: output sequence of stop logits (B, T_mel) + """ + # input of embedding must be int64 + text_inputs = paddle.cast(text_inputs, 'int64') + embedded_inputs = self.embedding(text_inputs) + if self.toned: + embedded_inputs += self.embedding_tones(tones) + + encoder_outputs = self.encoder(embedded_inputs, text_lens) + + if global_condition is not None: + global_condition = global_condition.unsqueeze(1) + global_condition = paddle.expand(global_condition, + [-1, encoder_outputs.shape[1], -1]) + encoder_outputs = paddle.concat([encoder_outputs, global_condition], + -1) + + # [B, T_enc, 1] + mask = sequence_mask( + text_lens, dtype=encoder_outputs.dtype).unsqueeze(-1) + if self.decoder.use_stop_token: + mel_outputs, alignments, stop_logits = self.decoder( + encoder_outputs, mels, mask=mask) + else: + mel_outputs, alignments = self.decoder( + encoder_outputs, mels, mask=mask) + mel_outputs_postnet = self.postnet(mel_outputs) + mel_outputs_postnet = mel_outputs + mel_outputs_postnet + + if output_lens is not None: + # [B, T_dec, 1] + mask = sequence_mask(output_lens).unsqueeze(-1) + mel_outputs = mel_outputs * mask # [B, T, C] + mel_outputs_postnet = mel_outputs_postnet * mask # [B, T, C] + outputs = { + "mel_output": mel_outputs, + "mel_outputs_postnet": mel_outputs_postnet, + "alignments": alignments + } + if self.decoder.use_stop_token: + outputs["stop_logits"] = stop_logits + + return outputs + + @paddle.no_grad() + def infer(self, + text_inputs, + max_decoder_steps=1000, + tones=None, + global_condition=None): + """Generate the mel sepctrogram of features given the sequences of character ids. + + Parameters + ---------- + text_inputs: Tensor [shape=(B, T_text)] + Batch of the sequencees of padded character ids. + + max_decoder_steps: int, optional + Number of max step when synthesize. Defaults to 1000. + + Returns + ------- + outputs : Dict[str, Tensor] + + mel_output: output sequence of sepctrogram (B, T_mel, C); + + mel_outputs_postnet: output sequence of sepctrogram after postnet (B, T_mel, C); + + stop_logits: output sequence of stop logits (B, T_mel); + + alignments: attention weights (B, T_mel, T_text). This key is only + present when `use_stop_token` is True. + """ + # input of embedding must be int64 + text_inputs = paddle.cast(text_inputs, 'int64') + embedded_inputs = self.embedding(text_inputs) + if self.toned: + embedded_inputs += self.embedding_tones(tones) + encoder_outputs = self.encoder(embedded_inputs) + + if global_condition is not None: + global_condition = global_condition.unsqueeze(1) + global_condition = paddle.expand(global_condition, + [-1, encoder_outputs.shape[1], -1]) + encoder_outputs = paddle.concat([encoder_outputs, global_condition], + -1) + if self.decoder.use_stop_token: + mel_outputs, alignments, stop_logits = self.decoder.infer( + encoder_outputs, max_decoder_steps=max_decoder_steps) + else: + mel_outputs, alignments = self.decoder.infer( + encoder_outputs, max_decoder_steps=max_decoder_steps) + + mel_outputs_postnet = self.postnet(mel_outputs) + mel_outputs_postnet = mel_outputs + mel_outputs_postnet + + outputs = { + "mel_output": mel_outputs, + "mel_outputs_postnet": mel_outputs_postnet, + "alignments": alignments + } + if self.decoder.use_stop_token: + outputs["stop_logits"] = stop_logits + + return outputs + + @classmethod + def from_pretrained(cls, config, checkpoint_path): + """Build a Tacotron2 model from a pretrained model. + + Parameters + ---------- + config: yacs.config.CfgNode + model configs + + checkpoint_path: Path or str + the path of pretrained model checkpoint, without extension name + + Returns + ------- + ConditionalWaveFlow + The model built from pretrained result. + """ + model = cls(vocab_size=config.model.vocab_size, + n_tones=config.model.n_tones, + d_mels=config.data.n_mels, + d_encoder=config.model.d_encoder, + encoder_conv_layers=config.model.encoder_conv_layers, + encoder_kernel_size=config.model.encoder_kernel_size, + d_prenet=config.model.d_prenet, + d_attention_rnn=config.model.d_attention_rnn, + d_decoder_rnn=config.model.d_decoder_rnn, + attention_filters=config.model.attention_filters, + attention_kernel_size=config.model.attention_kernel_size, + d_attention=config.model.d_attention, + d_postnet=config.model.d_postnet, + postnet_kernel_size=config.model.postnet_kernel_size, + postnet_conv_layers=config.model.postnet_conv_layers, + reduction_factor=config.model.reduction_factor, + p_encoder_dropout=config.model.p_encoder_dropout, + p_prenet_dropout=config.model.p_prenet_dropout, + p_attention_dropout=config.model.p_attention_dropout, + p_decoder_dropout=config.model.p_decoder_dropout, + p_postnet_dropout=config.model.p_postnet_dropout, + d_global_condition=config.model.d_global_condition, + use_stop_token=config.model.use_stop_token) + checkpoint.load_parameters(model, checkpoint_path=checkpoint_path) + return model + + +class Tacotron2Loss(nn.Layer): + """ Tacotron2 Loss module + """ + + def __init__(self, + use_stop_token_loss=True, + use_guided_attention_loss=False, + sigma=0.2): + """Tacotron 2 Criterion. + + Args: + use_stop_token_loss (bool, optional): Whether to use a loss for stop token prediction. Defaults to True. + use_guided_attention_loss (bool, optional): Whether to use a loss for attention weights. Defaults to False. + sigma (float, optional): Hyper-parameter sigma for guided attention loss. Defaults to 0.2. + """ + super().__init__() + self.spec_criterion = nn.MSELoss() + self.use_stop_token_loss = use_stop_token_loss + self.use_guided_attention_loss = use_guided_attention_loss + self.attn_criterion = guided_attention_loss + self.stop_criterion = paddle.nn.BCEWithLogitsLoss() + self.sigma = sigma + + def forward(self, + mel_outputs, + mel_outputs_postnet, + mel_targets, + attention_weights=None, + slens=None, + plens=None, + stop_logits=None): + """Calculate tacotron2 loss. + + Parameters + ---------- + mel_outputs: Tensor [shape=(B, T_mel, C)] + Output mel spectrogram sequence. + + mel_outputs_postnet: Tensor [shape(B, T_mel, C)] + Output mel spectrogram sequence after postnet. + + mel_targets: Tensor [shape=(B, T_mel, C)] + Target mel spectrogram sequence. + + attention_weights: Tensor [shape=(B, T_mel, T_enc)] + Attention weights. This should be provided when + `use_guided_attention_loss` is True. + + slens: Tensor [shape=(B,)] + Number of frames of mel spectrograms. This should be provided when + `use_guided_attention_loss` is True. + + plens: Tensor [shape=(B, )] + Number of text or phone ids of each utterance. This should be + provided when `use_guided_attention_loss` is True. + + stop_logits: Tensor [shape=(B, T_mel)] + Stop logits of each mel spectrogram frame. This should be provided + when `use_stop_token_loss` is True. + + Returns + ------- + losses : Dict[str, Tensor] + + loss: the sum of the other three losses; + + mel_loss: MSE loss compute by mel_targets and mel_outputs; + + post_mel_loss: MSE loss compute by mel_targets and mel_outputs_postnet; + + guided_attn_loss: Guided attention loss for attention weights; + + stop_loss: Binary cross entropy loss for stop token prediction. + """ + mel_loss = self.spec_criterion(mel_outputs, mel_targets) + post_mel_loss = self.spec_criterion(mel_outputs_postnet, mel_targets) + total_loss = mel_loss + post_mel_loss + if self.use_guided_attention_loss: + gal_loss = self.attn_criterion(attention_weights, slens, plens, + self.sigma) + total_loss += gal_loss + if self.use_stop_token_loss: + T_dec = mel_targets.shape[1] + stop_labels = F.one_hot(slens - 1, num_classes=T_dec) + stop_token_loss = self.stop_criterion(stop_logits, stop_labels) + total_loss += stop_token_loss + + losses = { + "loss": total_loss, + "mel_loss": mel_loss, + "post_mel_loss": post_mel_loss + } + if self.use_guided_attention_loss: + losses["guided_attn_loss"] = gal_loss + if self.use_stop_token_loss: + losses["stop_loss"] = stop_token_loss + return losses diff --git a/parakeet/models/transformer_tts/__init__.py b/parakeet/models/transformer_tts/__init__.py new file mode 100644 index 00000000..0456c300 --- /dev/null +++ b/parakeet/models/transformer_tts/__init__.py @@ -0,0 +1,16 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from .transformer_tts import * +from .transformer_tts_updater import * diff --git a/parakeet/models/transformer_tts/transformer_tts.py b/parakeet/models/transformer_tts/transformer_tts.py new file mode 100644 index 00000000..42ab5f86 --- /dev/null +++ b/parakeet/models/transformer_tts/transformer_tts.py @@ -0,0 +1,1082 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Fastspeech2 related modules for paddle""" +from typing import Dict +from typing import Sequence +from typing import Tuple +import numpy +import paddle +from paddle import nn +import paddle.nn.functional as F +from typeguard import check_argument_types + +from parakeet.modules.fastspeech2_transformer.attention import MultiHeadedAttention +from parakeet.modules.fastspeech2_transformer.decoder import Decoder +from parakeet.modules.fastspeech2_transformer.embedding import PositionalEncoding +from parakeet.modules.fastspeech2_transformer.embedding import ScaledPositionalEncoding +from parakeet.modules.fastspeech2_transformer.encoder import Encoder +from parakeet.modules.fastspeech2_transformer.mask import subsequent_mask +from parakeet.modules.style_encoder import StyleEncoder +from parakeet.modules.tacotron2.decoder import Postnet +from parakeet.modules.tacotron2.decoder import Prenet as DecoderPrenet +from parakeet.modules.tacotron2.encoder import Encoder as EncoderPrenet +from parakeet.modules.nets_utils import initialize +from parakeet.modules.nets_utils import make_non_pad_mask +from parakeet.modules.nets_utils import make_pad_mask + + +class TransformerTTS(nn.Layer): + """TTS-Transformer module. + + This is a module of text-to-speech Transformer described in `Neural Speech Synthesis + with Transformer Network`_, which convert the sequence of tokens into the sequence + of Mel-filterbanks. + + .. _`Neural Speech Synthesis with Transformer Network`: + https://arxiv.org/pdf/1809.08895.pdf + + Parameters + ---------- + idim : int + Dimension of the inputs. + odim : int + Dimension of the outputs. + embed_dim : int, optional + Dimension of character embedding. + eprenet_conv_layers : int, optional + Number of encoder prenet convolution layers. + eprenet_conv_chans : int, optional + Number of encoder prenet convolution channels. + eprenet_conv_filts : int, optional + Filter size of encoder prenet convolution. + dprenet_layers : int, optional + Number of decoder prenet layers. + dprenet_units : int, optional + Number of decoder prenet hidden units. + elayers : int, optional + Number of encoder layers. + eunits : int, optional + Number of encoder hidden units. + adim : int, optional + Number of attention transformation dimensions. + aheads : int, optional + Number of heads for multi head attention. + dlayers : int, optional + Number of decoder layers. + dunits : int, optional + Number of decoder hidden units. + postnet_layers : int, optional + Number of postnet layers. + postnet_chans : int, optional + Number of postnet channels. + postnet_filts : int, optional + Filter size of postnet. + use_scaled_pos_enc : pool, optional + Whether to use trainable scaled positional encoding. + use_batch_norm : bool, optional + Whether to use batch normalization in encoder prenet. + encoder_normalize_before : bool, optional + Whether to perform layer normalization before encoder block. + decoder_normalize_before : bool, optional + Whether to perform layer normalization before decoder block. + encoder_concat_after : bool, optional + Whether to concatenate attention layer's input and output in encoder. + decoder_concat_after : bool, optional + Whether to concatenate attention layer's input and output in decoder. + positionwise_layer_type : str, optional + Position-wise operation type. + positionwise_conv_kernel_size : int, optional + Kernel size in position wise conv 1d. + reduction_factor : int, optional + Reduction factor. + spk_embed_dim : int, optional + Number of speaker embedding dimenstions. + spk_embed_integration_type : str, optional + How to integrate speaker embedding. + use_gst : str, optional + Whether to use global style token. + gst_tokens : int, optional + The number of GST embeddings. + gst_heads : int, optional + The number of heads in GST multihead attention. + gst_conv_layers : int, optional + The number of conv layers in GST. + gst_conv_chans_list : Sequence[int], optional + List of the number of channels of conv layers in GST. + gst_conv_kernel_size : int, optional + Kernal size of conv layers in GST. + gst_conv_stride : int, optional + Stride size of conv layers in GST. + gst_gru_layers : int, optional + The number of GRU layers in GST. + gst_gru_units : int, optional + The number of GRU units in GST. + transformer_lr : float, optional + Initial value of learning rate. + transformer_warmup_steps : int, optional + Optimizer warmup steps. + transformer_enc_dropout_rate : float, optional + Dropout rate in encoder except attention and positional encoding. + transformer_enc_positional_dropout_rate : float, optional + Dropout rate after encoder positional encoding. + transformer_enc_attn_dropout_rate : float, optional + Dropout rate in encoder self-attention module. + transformer_dec_dropout_rate : float, optional + Dropout rate in decoder except attention & positional encoding. + transformer_dec_positional_dropout_rate : float, optional + Dropout rate after decoder positional encoding. + transformer_dec_attn_dropout_rate : float, optional + Dropout rate in deocoder self-attention module. + transformer_enc_dec_attn_dropout_rate : float, optional + Dropout rate in encoder-deocoder attention module. + init_type : str, optional + How to initialize transformer parameters. + init_enc_alpha : float, optional + Initial value of alpha in scaled pos encoding of the encoder. + init_dec_alpha : float, optional + Initial value of alpha in scaled pos encoding of the decoder. + eprenet_dropout_rate : float, optional + Dropout rate in encoder prenet. + dprenet_dropout_rate : float, optional + Dropout rate in decoder prenet. + postnet_dropout_rate : float, optional + Dropout rate in postnet. + use_masking : bool, optional + Whether to apply masking for padded part in loss calculation. + use_weighted_masking : bool, optional + Whether to apply weighted masking in loss calculation. + bce_pos_weight : float, optional + Positive sample weight in bce calculation (only for use_masking=true). + loss_type : str, optional + How to calculate loss. + use_guided_attn_loss : bool, optional + Whether to use guided attention loss. + num_heads_applied_guided_attn : int, optional + Number of heads in each layer to apply guided attention loss. + num_layers_applied_guided_attn : int, optional + Number of layers to apply guided attention loss. + List of module names to apply guided attention loss. + """ + + def __init__( + self, + # network structure related + idim: int, + odim: int, + embed_dim: int=512, + eprenet_conv_layers: int=3, + eprenet_conv_chans: int=256, + eprenet_conv_filts: int=5, + dprenet_layers: int=2, + dprenet_units: int=256, + elayers: int=6, + eunits: int=1024, + adim: int=512, + aheads: int=4, + dlayers: int=6, + dunits: int=1024, + postnet_layers: int=5, + postnet_chans: int=256, + postnet_filts: int=5, + positionwise_layer_type: str="conv1d", + positionwise_conv_kernel_size: int=1, + use_scaled_pos_enc: bool=True, + use_batch_norm: bool=True, + encoder_normalize_before: bool=True, + decoder_normalize_before: bool=True, + encoder_concat_after: bool=False, + decoder_concat_after: bool=False, + reduction_factor: int=1, + spk_embed_dim: int=None, + spk_embed_integration_type: str="add", + use_gst: bool=False, + gst_tokens: int=10, + gst_heads: int=4, + gst_conv_layers: int=6, + gst_conv_chans_list: Sequence[int]=(32, 32, 64, 64, 128, 128), + gst_conv_kernel_size: int=3, + gst_conv_stride: int=2, + gst_gru_layers: int=1, + gst_gru_units: int=128, + # training related + transformer_enc_dropout_rate: float=0.1, + transformer_enc_positional_dropout_rate: float=0.1, + transformer_enc_attn_dropout_rate: float=0.1, + transformer_dec_dropout_rate: float=0.1, + transformer_dec_positional_dropout_rate: float=0.1, + transformer_dec_attn_dropout_rate: float=0.1, + transformer_enc_dec_attn_dropout_rate: float=0.1, + eprenet_dropout_rate: float=0.5, + dprenet_dropout_rate: float=0.5, + postnet_dropout_rate: float=0.5, + init_type: str="xavier_uniform", + init_enc_alpha: float=1.0, + init_dec_alpha: float=1.0, + use_guided_attn_loss: bool=True, + num_heads_applied_guided_attn: int=2, + num_layers_applied_guided_attn: int=2, ): + """Initialize Transformer module.""" + assert check_argument_types() + super().__init__() + + # store hyperparameters + self.idim = idim + self.odim = odim + self.eos = idim - 1 + self.spk_embed_dim = spk_embed_dim + self.reduction_factor = reduction_factor + self.use_gst = use_gst + self.use_scaled_pos_enc = use_scaled_pos_enc + self.use_guided_attn_loss = use_guided_attn_loss + if self.use_guided_attn_loss: + if num_layers_applied_guided_attn == -1: + self.num_layers_applied_guided_attn = elayers + else: + self.num_layers_applied_guided_attn = num_layers_applied_guided_attn + if num_heads_applied_guided_attn == -1: + self.num_heads_applied_guided_attn = aheads + else: + self.num_heads_applied_guided_attn = num_heads_applied_guided_attn + if self.spk_embed_dim is not None: + self.spk_embed_integration_type = spk_embed_integration_type + + # use idx 0 as padding idx + self.padding_idx = 0 + # set_global_initializer 会影响后面的全局，包括 create_parameter + initialize(self, init_type) + # get positional encoding class + pos_enc_class = (ScaledPositionalEncoding + if self.use_scaled_pos_enc else PositionalEncoding) + + # define transformer encoder + if eprenet_conv_layers != 0: + # encoder prenet + encoder_input_layer = nn.Sequential( + EncoderPrenet( + idim=idim, + embed_dim=embed_dim, + elayers=0, + econv_layers=eprenet_conv_layers, + econv_chans=eprenet_conv_chans, + econv_filts=eprenet_conv_filts, + use_batch_norm=use_batch_norm, + dropout_rate=eprenet_dropout_rate, + padding_idx=self.padding_idx, ), + nn.Linear(eprenet_conv_chans, adim), ) + else: + encoder_input_layer = nn.Embedding( + num_embeddings=idim, + embedding_dim=adim, + padding_idx=self.padding_idx) + self.encoder = Encoder( + idim=idim, + attention_dim=adim, + attention_heads=aheads, + linear_units=eunits, + num_blocks=elayers, + input_layer=encoder_input_layer, + dropout_rate=transformer_enc_dropout_rate, + positional_dropout_rate=transformer_enc_positional_dropout_rate, + attention_dropout_rate=transformer_enc_attn_dropout_rate, + pos_enc_class=pos_enc_class, + normalize_before=encoder_normalize_before, + concat_after=encoder_concat_after, + positionwise_layer_type=positionwise_layer_type, + positionwise_conv_kernel_size=positionwise_conv_kernel_size, ) + + # define GST + if self.use_gst: + self.gst = StyleEncoder( + idim=odim, # the input is mel-spectrogram + gst_tokens=gst_tokens, + gst_token_dim=adim, + gst_heads=gst_heads, + conv_layers=gst_conv_layers, + conv_chans_list=gst_conv_chans_list, + conv_kernel_size=gst_conv_kernel_size, + conv_stride=gst_conv_stride, + gru_layers=gst_gru_layers, + gru_units=gst_gru_units, ) + + # define projection layer + if self.spk_embed_dim is not None: + if self.spk_embed_integration_type == "add": + self.projection = nn.Linear(self.spk_embed_dim, adim) + else: + self.projection = nn.Linear(adim + self.spk_embed_dim, adim) + + # define transformer decoder + if dprenet_layers != 0: + # decoder prenet + decoder_input_layer = nn.Sequential( + DecoderPrenet( + idim=odim, + n_layers=dprenet_layers, + n_units=dprenet_units, + dropout_rate=dprenet_dropout_rate, ), + nn.Linear(dprenet_units, adim), ) + else: + decoder_input_layer = "linear" + self.decoder = Decoder( + odim=odim, # odim is needed when no prenet is used + attention_dim=adim, + attention_heads=aheads, + linear_units=dunits, + num_blocks=dlayers, + dropout_rate=transformer_dec_dropout_rate, + positional_dropout_rate=transformer_dec_positional_dropout_rate, + self_attention_dropout_rate=transformer_dec_attn_dropout_rate, + src_attention_dropout_rate=transformer_enc_dec_attn_dropout_rate, + input_layer=decoder_input_layer, + use_output_layer=False, + pos_enc_class=pos_enc_class, + normalize_before=decoder_normalize_before, + concat_after=decoder_concat_after, ) + + # define final projection + self.feat_out = nn.Linear(adim, odim * reduction_factor) + self.prob_out = nn.Linear(adim, reduction_factor) + + # define postnet + self.postnet = (None if postnet_layers == 0 else Postnet( + idim=idim, + odim=odim, + n_layers=postnet_layers, + n_chans=postnet_chans, + n_filts=postnet_filts, + use_batch_norm=use_batch_norm, + dropout_rate=postnet_dropout_rate, )) + + # 闭合的 initialize() 中的 set_global_initializer 的作用域，防止其影响到 self._reset_parameters() + nn.initializer.set_global_initializer(None) + + self._reset_parameters( + init_enc_alpha=init_enc_alpha, + init_dec_alpha=init_dec_alpha, ) + + def _reset_parameters(self, init_enc_alpha: float, init_dec_alpha: float): + + # initialize alpha in scaled positional encoding + if self.use_scaled_pos_enc: + init_enc_alpha = paddle.to_tensor(init_enc_alpha) + self.encoder.embed[-1].alpha = paddle.create_parameter( + shape=init_enc_alpha.shape, + dtype=str(init_enc_alpha.numpy().dtype), + default_initializer=paddle.nn.initializer.Assign( + init_enc_alpha)) + + init_dec_alpha = paddle.to_tensor(init_dec_alpha) + self.decoder.embed[-1].alpha = paddle.create_parameter( + shape=init_dec_alpha.shape, + dtype=str(init_dec_alpha.numpy().dtype), + default_initializer=paddle.nn.initializer.Assign( + init_dec_alpha)) + + def forward( + self, + text: paddle.Tensor, + text_lengths: paddle.Tensor, + speech: paddle.Tensor, + speech_lengths: paddle.Tensor, + spembs: paddle.Tensor=None, + ) -> Tuple[paddle.Tensor, Dict[str, paddle.Tensor], paddle.Tensor]: + """Calculate forward propagation. + + Parameters + ---------- + text : Tensor(int64) + Batch of padded character ids (B, Tmax). + text_lengths : Tensor(int64) + Batch of lengths of each input batch (B,). + speech : Tensor + Batch of padded target features (B, Lmax, odim). + speech_lengths : Tensor(int64) + Batch of the lengths of each target (B,). + spembs : Tensor, optional + Batch of speaker embeddings (B, spk_embed_dim). + + Returns + ---------- + Tensor + Loss scalar value. + Dict + Statistics to be monitored. + + """ + # input of embedding must be int64 + text_lengths = paddle.cast(text_lengths, 'int64') + + # Add eos at the last of sequence + text = numpy.pad(text.numpy(), ((0, 0), (0, 1)), 'constant') + xs = paddle.to_tensor(text, dtype='int64') + for i, l in enumerate(text_lengths): + xs[i, l] = self.eos + ilens = text_lengths + 1 + + ys = speech + olens = paddle.cast(speech_lengths, 'int64') + + # make labels for stop prediction + labels = make_pad_mask(olens - 1) + labels = numpy.pad( + labels.numpy(), ((0, 0), (0, 1)), 'constant', constant_values=1.0) + labels = paddle.to_tensor(labels) + labels = paddle.cast(labels, dtype="float32") + # labels = F.pad(labels, [0, 1], "constant", 1.0) + + # calculate transformer outputs + after_outs, before_outs, logits = self._forward(xs, ilens, ys, olens, + spembs) + + # modifiy mod part of groundtruth + + if self.reduction_factor > 1: + olens = paddle.to_tensor( + [olen - olen % self.reduction_factor for olen in olens.numpy()]) + max_olen = max(olens) + ys = ys[:, :max_olen] + labels = labels[:, :max_olen] + labels[:, -1] = 1.0 # make sure at least one frame has 1 + need_dict = {} + need_dict['encoder'] = self.encoder + need_dict['decoder'] = self.decoder + need_dict[ + 'num_heads_applied_guided_attn'] = self.num_heads_applied_guided_attn + need_dict[ + 'num_layers_applied_guided_attn'] = self.num_layers_applied_guided_attn + need_dict['use_scaled_pos_enc'] = self.use_scaled_pos_enc + + return after_outs, before_outs, logits, ys, labels, olens, ilens, need_dict + + def _forward( + self, + xs: paddle.Tensor, + ilens: paddle.Tensor, + ys: paddle.Tensor, + olens: paddle.Tensor, + spembs: paddle.Tensor, + ) -> Tuple[paddle.Tensor, paddle.Tensor, paddle.Tensor]: + # forward encoder + x_masks = self._source_mask(ilens) + hs, h_masks = self.encoder(xs, x_masks) + + # integrate with GST + if self.use_gst: + style_embs = self.gst(ys) + hs = hs + style_embs.unsqueeze(1) + + # integrate speaker embedding + if self.spk_embed_dim is not None: + hs = self._integrate_with_spk_embed(hs, spembs) + + # thin out frames for reduction factor (B, Lmax, odim) -> (B, Lmax//r, odim) + if self.reduction_factor > 1: + ys_in = ys[:, self.reduction_factor - 1::self.reduction_factor] + olens_in = olens.new( + [olen // self.reduction_factor for olen in olens]) + else: + ys_in, olens_in = ys, olens + + # add first zero frame and remove last frame for auto-regressive + ys_in = self._add_first_frame_and_remove_last_frame(ys_in) + + # forward decoder + y_masks = self._target_mask(olens_in) + zs, _ = self.decoder(ys_in, y_masks, hs, h_masks) + # (B, Lmax//r, odim * r) -> (B, Lmax//r * r, odim) + before_outs = self.feat_out(zs).reshape([zs.shape[0], -1, self.odim]) + # (B, Lmax//r, r) -> (B, Lmax//r * r) + logits = self.prob_out(zs).reshape([zs.shape[0], -1]) + + # postnet -> (B, Lmax//r * r, odim) + if self.postnet is None: + after_outs = before_outs + else: + after_outs = before_outs + self.postnet( + before_outs.transpose([0, 2, 1])).transpose([0, 2, 1]) + + return after_outs, before_outs, logits + + def inference( + self, + text: paddle.Tensor, + speech: paddle.Tensor=None, + spembs: paddle.Tensor=None, + threshold: float=0.5, + minlenratio: float=0.0, + maxlenratio: float=10.0, + use_teacher_forcing: bool=False, + ) -> Tuple[paddle.Tensor, paddle.Tensor, paddle.Tensor]: + """Generate the sequence of features given the sequences of characters. + + Parameters + ---------- + text : Tensor(int64) + Input sequence of characters (T,). + speech : Tensor, optional + Feature sequence to extract style (N, idim). + spembs : Tensor, optional + Speaker embedding vector (spk_embed_dim,). + threshold : float, optional + Threshold in inference. + minlenratio : float, optional + Minimum length ratio in inference. + maxlenratio : float, optional + Maximum length ratio in inference. + use_teacher_forcing : bool, optional + Whether to use teacher forcing. + + Returns + ---------- + Tensor + Output sequence of features (L, odim). + Tensor + Output sequence of stop probabilities (L,). + Tensor + Encoder-decoder (source) attention weights (#layers, #heads, L, T). + + """ + # input of embedding must be int64 + y = speech + spemb = spembs + + # add eos at the last of sequence + text = numpy.pad( + text.numpy(), (0, 1), 'constant', constant_values=self.eos) + x = paddle.to_tensor(text, dtype='int64') + + # inference with teacher forcing + if use_teacher_forcing: + assert speech is not None, "speech must be provided with teacher forcing." + + # get teacher forcing outputs + xs, ys = x.unsqueeze(0), y.unsqueeze(0) + spembs = None if spemb is None else spemb.unsqueeze(0) + ilens = paddle.to_tensor( + [xs.shape[1]], dtype=paddle.int64, place=xs.place) + olens = paddle.to_tensor( + [ys.shape[1]], dtype=paddle.int64, place=ys.place) + outs, *_ = self._forward(xs, ilens, ys, olens, spembs) + + # get attention weights + att_ws = [] + for i in range(len(self.decoder.decoders)): + att_ws += [self.decoder.decoders[i].src_attn.attn] + # (B, L, H, T_out, T_in) + att_ws = paddle.stack(att_ws, axis=1) + + return outs[0], None, att_ws[0] + + # forward encoder + xs = x.unsqueeze(0) + hs, _ = self.encoder(xs, None) + + # integrate GST + if self.use_gst: + style_embs = self.gst(y.unsqueeze(0)) + hs = hs + style_embs.unsqueeze(1) + + # integrate speaker embedding + if self.spk_embed_dim is not None: + spembs = spemb.unsqueeze(0) + hs = self._integrate_with_spk_embed(hs, spembs) + + # set limits of length + maxlen = int(hs.shape[1] * maxlenratio / self.reduction_factor) + minlen = int(hs.shape[1] * minlenratio / self.reduction_factor) + + # initialize + idx = 0 + ys = paddle.zeros([1, 1, self.odim]) + outs, probs = [], [] + + # forward decoder step-by-step + z_cache = None + while True: + # update index + idx += 1 + + # calculate output and stop prob at idx-th step + y_masks = subsequent_mask(idx).unsqueeze(0) + z, z_cache = self.decoder.forward_one_step( + ys, y_masks, hs, cache=z_cache) # (B, adim) + outs += [ + self.feat_out(z).reshape([self.reduction_factor, self.odim]) + ] # [(r, odim), ...] + probs += [F.sigmoid(self.prob_out(z))[0]] # [(r), ...] + + # update next inputs + ys = paddle.concat( + (ys, outs[-1][-1].reshape([1, 1, self.odim])), + axis=1) # (1, idx + 1, odim) + + # get attention weights + att_ws_ = [] + for name, m in self.named_sublayers(): + if isinstance(m, MultiHeadedAttention) and "src" in name: + # [(#heads, 1, T),...] + att_ws_ += [m.attn[0, :, -1].unsqueeze(1)] + if idx == 1: + att_ws = att_ws_ + else: + # [(#heads, l, T), ...] + att_ws = [ + paddle.concat([att_w, att_w_], axis=1) + for att_w, att_w_ in zip(att_ws, att_ws_) + ] + + # check whether to finish generation + if sum(paddle.cast(probs[-1] >= threshold, + 'int64')) > 0 or idx >= maxlen: + # check mininum length + if idx < minlen: + continue + # (L, odim) -> (1, L, odim) -> (1, odim, L) + outs = (paddle.concat(outs, axis=0).unsqueeze(0).transpose( + [0, 2, 1])) + if self.postnet is not None: + # (1, odim, L) + outs = outs + self.postnet(outs) + # (L, odim) + outs = outs.transpose([0, 2, 1]).squeeze(0) + probs = paddle.concat(probs, axis=0) + break + + # concatenate attention weights -> (#layers, #heads, L, T) + att_ws = paddle.stack(att_ws, axis=0) + + return outs, probs, att_ws + + def _add_first_frame_and_remove_last_frame( + self, ys: paddle.Tensor) -> paddle.Tensor: + ys_in = paddle.concat( + [paddle.zeros((ys.shape[0], 1, ys.shape[2])), ys[:, :-1]], axis=1) + return ys_in + + def _source_mask(self, ilens: paddle.Tensor) -> paddle.Tensor: + """Make masks for self-attention. + + Parameters + ---------- + ilens : Tensor + Batch of lengths (B,). + + Returns + ------- + Tensor + Mask tensor for self-attention. + dtype=paddle.bool + + Examples + ------- + >>> ilens = [5, 3] + >>> self._source_mask(ilens) + tensor([[[1, 1, 1, 1, 1], + [1, 1, 1, 0, 0]]]) bool + + """ + x_masks = make_non_pad_mask(ilens) + return x_masks.unsqueeze(-2) + + def _target_mask(self, olens: paddle.Tensor) -> paddle.Tensor: + """Make masks for masked self-attention. + + Parameters + ---------- + olens : LongTensor + Batch of lengths (B,). + + Returns + ---------- + Tensor + Mask tensor for masked self-attention. + + Examples + ---------- + >>> olens = [5, 3] + >>> self._target_mask(olens) + tensor([[[1, 0, 0, 0, 0], + [1, 1, 0, 0, 0], + [1, 1, 1, 0, 0], + [1, 1, 1, 1, 0], + [1, 1, 1, 1, 1]], + [[1, 0, 0, 0, 0], + [1, 1, 0, 0, 0], + [1, 1, 1, 0, 0], + [1, 1, 1, 0, 0], + [1, 1, 1, 0, 0]]], dtype=paddle.uint8) + + """ + y_masks = make_non_pad_mask(olens) + s_masks = subsequent_mask(y_masks.shape[-1]).unsqueeze(0) + return paddle.logical_and(y_masks.unsqueeze(-2), s_masks) + + def _integrate_with_spk_embed(self, + hs: paddle.Tensor, + spembs: paddle.Tensor) -> paddle.Tensor: + """Integrate speaker embedding with hidden states. + + Parameters + ---------- + hs : Tensor + Batch of hidden state sequences (B, Tmax, adim). + spembs : Tensor + Batch of speaker embeddings (B, spk_embed_dim). + + Returns + ---------- + Tensor + Batch of integrated hidden state sequences (B, Tmax, adim). + + """ + if self.spk_embed_integration_type == "add": + # apply projection and then add to hidden states + spembs = self.projection(F.normalize(spembs)) + hs = hs + spembs.unsqueeze(1) + elif self.spk_embed_integration_type == "concat": + # concat hidden states with spk embeds and then apply projection + spembs = F.normalize(spembs).unsqueeze(1).expand(-1, hs.shape[1], + -1) + hs = self.projection(paddle.concat([hs, spembs], axis=-1)) + else: + raise NotImplementedError("support only add or concat.") + + return hs + + +class TransformerTTSInference(nn.Layer): + def __init__(self, normalizer, model): + super().__init__() + self.normalizer = normalizer + self.acoustic_model = model + + def forward(self, text, spk_id=None): + normalized_mel = self.acoustic_model.inference(text)[0] + logmel = self.normalizer.inverse(normalized_mel) + return logmel + + +class TransformerTTSLoss(nn.Layer): + """Loss function module for Tacotron2.""" + + def __init__(self, + use_masking=True, + use_weighted_masking=False, + bce_pos_weight=5.0): + """Initialize Tactoron2 loss module. + + Parameters + ---------- + use_masking : bool + Whether to apply masking for padded part in loss calculation. + use_weighted_masking : bool + Whether to apply weighted masking in loss calculation. + bce_pos_weight : float + Weight of positive sample of stop token. + + """ + super().__init__() + assert (use_masking != use_weighted_masking) or not use_masking + self.use_masking = use_masking + self.use_weighted_masking = use_weighted_masking + + # define criterions + reduction = "none" if self.use_weighted_masking else "mean" + self.l1_criterion = nn.L1Loss(reduction=reduction) + self.mse_criterion = nn.MSELoss(reduction=reduction) + self.bce_criterion = nn.BCEWithLogitsLoss( + reduction=reduction, pos_weight=paddle.to_tensor(bce_pos_weight)) + + def forward(self, after_outs, before_outs, logits, ys, labels, olens): + """Calculate forward propagation. + + Parameters + ---------- + after_outs : Tensor + Batch of outputs after postnets (B, Lmax, odim). + before_outs : Tensor + Batch of outputs before postnets (B, Lmax, odim). + logits : Tensor + Batch of stop logits (B, Lmax). + ys : Tensor + Batch of padded target features (B, Lmax, odim). + labels : LongTensor + Batch of the sequences of stop token labels (B, Lmax). + olens : LongTensor + Batch of the lengths of each target (B,). + + Returns + ---------- + Tensor + L1 loss value. + Tensor + Mean square error loss value. + Tensor + Binary cross entropy loss value. + + """ + # make mask and apply it + if self.use_masking: + masks = make_non_pad_mask(olens).unsqueeze(-1) + ys = ys.masked_select(masks.broadcast_to(ys.shape)) + after_outs = after_outs.masked_select( + masks.broadcast_to(after_outs.shape)) + before_outs = before_outs.masked_select( + masks.broadcast_to(before_outs.shape)) + # Operator slice does not have kernel for data_type[bool] + tmp_masks = paddle.cast(masks, dtype='int64') + tmp_masks = tmp_masks[:, :, 0] + tmp_masks = paddle.cast(tmp_masks, dtype='bool') + labels = labels.masked_select(tmp_masks.broadcast_to(labels.shape)) + logits = logits.masked_select(tmp_masks.broadcast_to(logits.shape)) + + # calculate loss + l1_loss = self.l1_criterion(after_outs, ys) + self.l1_criterion( + before_outs, ys) + mse_loss = self.mse_criterion(after_outs, ys) + self.mse_criterion( + before_outs, ys) + bce_loss = self.bce_criterion(logits, labels) + + # make weighted mask and apply it + if self.use_weighted_masking: + masks = make_non_pad_mask(olens).unsqueeze(-1) + weights = masks.float() / masks.sum(dim=1, keepdim=True).float() + out_weights = weights.div(ys.shape[0] * ys.shape[2]) + logit_weights = weights.div(ys.shape[0]) + + # apply weight + l1_loss = l1_loss.multiply(out_weights) + l1_loss = l1_loss.masked_select( + masks.broadcast_to(l1_loss.shape)).sum() + + mse_loss = mse_loss.multiply(out_weights) + mse_loss = mse_loss.masked_select( + masks.broadcast_to(mse_loss.shape)).sum() + + bce_loss = bce_loss.multiply(logit_weights.squeeze(-1)) + bce_loss = bce_loss.masked_select( + masks.squeeze(-1).broadcast_to(bce_loss.shape)).sum() + + return l1_loss, mse_loss, bce_loss + + +class GuidedAttentionLoss(nn.Layer): + """Guided attention loss function module. + + This module calculates the guided attention loss described + in `Efficiently Trainable Text-to-Speech System Based + on Deep Convolutional Networks with Guided Attention`_, + which forces the attention to be diagonal. + + .. _`Efficiently Trainable Text-to-Speech System + Based on Deep Convolutional Networks with Guided Attention`: + https://arxiv.org/abs/1710.08969 + + """ + + def __init__(self, sigma=0.4, alpha=1.0, reset_always=True): + """Initialize guided attention loss module. + + Parameters + ---------- + sigma : float, optional + Standard deviation to control how close attention to a diagonal. + alpha : float, optional + Scaling coefficient (lambda). + reset_always : bool, optional + Whether to always reset masks. + + """ + super(GuidedAttentionLoss, self).__init__() + self.sigma = sigma + self.alpha = alpha + self.reset_always = reset_always + self.guided_attn_masks = None + self.masks = None + + def _reset_masks(self): + self.guided_attn_masks = None + self.masks = None + + def forward(self, att_ws, ilens, olens): + """Calculate forward propagation. + + Parameters + ---------- + att_ws : Tensor + Batch of attention weights (B, T_max_out, T_max_in). + ilens : LongTensor + Batch of input lenghts (B,). + olens : LongTensor + Batch of output lenghts (B,). + + Returns + ---------- + Tensor + Guided attention loss value. + + """ + if self.guided_attn_masks is None: + self.guided_attn_masks = self._make_guided_attention_masks(ilens, + olens) + if self.masks is None: + self.masks = self._make_masks(ilens, olens) + losses = self.guided_attn_masks * att_ws + loss = paddle.mean( + losses.masked_select(self.masks.broadcast_to(losses.shape))) + if self.reset_always: + self._reset_masks() + return self.alpha * loss + + def _make_guided_attention_masks(self, ilens, olens): + n_batches = len(ilens) + max_ilen = max(ilens) + max_olen = max(olens) + guided_attn_masks = paddle.zeros((n_batches, max_olen, max_ilen)) + + for idx, (ilen, olen) in enumerate(zip(ilens, olens)): + + ilen = int(ilen) + olen = int(olen) + guided_attn_masks[idx, :olen, : + ilen] = self._make_guided_attention_mask( + ilen, olen, self.sigma) + return guided_attn_masks + + @staticmethod + def _make_guided_attention_mask(ilen, olen, sigma): + """Make guided attention mask. + + Examples + ---------- + >>> guided_attn_mask =_make_guided_attention(5, 5, 0.4) + >>> guided_attn_mask.shape + [5, 5] + >>> guided_attn_mask + tensor([[0.0000, 0.1175, 0.3935, 0.6753, 0.8647], + [0.1175, 0.0000, 0.1175, 0.3935, 0.6753], + [0.3935, 0.1175, 0.0000, 0.1175, 0.3935], + [0.6753, 0.3935, 0.1175, 0.0000, 0.1175], + [0.8647, 0.6753, 0.3935, 0.1175, 0.0000]]) + >>> guided_attn_mask =_make_guided_attention(3, 6, 0.4) + >>> guided_attn_mask.shape + [6, 3] + >>> guided_attn_mask + tensor([[0.0000, 0.2934, 0.7506], + [0.0831, 0.0831, 0.5422], + [0.2934, 0.0000, 0.2934], + [0.5422, 0.0831, 0.0831], + [0.7506, 0.2934, 0.0000], + [0.8858, 0.5422, 0.0831]]) + + """ + grid_x, grid_y = paddle.meshgrid( + paddle.arange(olen), paddle.arange(ilen)) + grid_x = grid_x.cast(dtype=paddle.float32) + grid_y = grid_y.cast(dtype=paddle.float32) + return 1.0 - paddle.exp(-( + (grid_y / ilen - grid_x / olen)**2) / (2 * (sigma**2))) + + @staticmethod + def _make_masks(ilens, olens): + """Make masks indicating non-padded part. + + Parameters + ---------- + ilens (LongTensor or List): Batch of lengths (B,). + olens (LongTensor or List): Batch of lengths (B,). + + Returns + ---------- + Tensor + Mask tensor indicating non-padded part. + + Examples + ---------- + >>> ilens, olens = [5, 2], [8, 5] + >>> _make_mask(ilens, olens) + tensor([[[1, 1, 1, 1, 1], + [1, 1, 1, 1, 1], + [1, 1, 1, 1, 1], + [1, 1, 1, 1, 1], + [1, 1, 1, 1, 1], + [1, 1, 1, 1, 1], + [1, 1, 1, 1, 1], + [1, 1, 1, 1, 1]], + + [[1, 1, 0, 0, 0], + [1, 1, 0, 0, 0], + [1, 1, 0, 0, 0], + [1, 1, 0, 0, 0], + [1, 1, 0, 0, 0], + [0, 0, 0, 0, 0], + [0, 0, 0, 0, 0], + [0, 0, 0, 0, 0]]], dtype=paddle.uint8) + + """ + # (B, T_in) + in_masks = make_non_pad_mask(ilens) + # (B, T_out) + out_masks = make_non_pad_mask(olens) + # (B, T_out, T_in) + + return paddle.logical_and( + out_masks.unsqueeze(-1), in_masks.unsqueeze(-2)) + + +class GuidedMultiHeadAttentionLoss(GuidedAttentionLoss): + """Guided attention loss function module for multi head attention. + + Parameters + ---------- + sigma : float, optional + Standard deviation to controlGuidedAttentionLoss + how close attention to a diagonal. + alpha : float, optional + Scaling coefficient (lambda). + reset_always : bool, optional + Whether to always reset masks. + + """ + + def forward(self, att_ws, ilens, olens): + """Calculate forward propagation. + + Parameters + ---------- + att_ws : Tensor + Batch of multi head attention weights (B, H, T_max_out, T_max_in). + ilens : Tensor + Batch of input lenghts (B,). + olens : Tensor + Batch of output lenghts (B,). + + Returns + ---------- + Tensor + Guided attention loss value. + + """ + if self.guided_attn_masks is None: + self.guided_attn_masks = ( + self._make_guided_attention_masks(ilens, olens).unsqueeze(1)) + if self.masks is None: + self.masks = self._make_masks(ilens, olens).unsqueeze(1) + losses = self.guided_attn_masks * att_ws + loss = paddle.mean( + losses.masked_select(self.masks.broadcast_to(losses.shape))) + if self.reset_always: + self._reset_masks() + + return self.alpha * loss diff --git a/parakeet/models/transformer_tts/transformer_tts_updater.py b/parakeet/models/transformer_tts/transformer_tts_updater.py new file mode 100644 index 00000000..7e75a860 --- /dev/null +++ b/parakeet/models/transformer_tts/transformer_tts_updater.py @@ -0,0 +1,322 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import logging +from typing import Sequence + +import paddle +from paddle import distributed as dist +from parakeet.models.transformer_tts import GuidedMultiHeadAttentionLoss +from parakeet.models.transformer_tts import TransformerTTSLoss +from parakeet.training.extensions.evaluator import StandardEvaluator +from parakeet.training.reporter import report +from parakeet.training.updaters.standard_updater import StandardUpdater +logging.basicConfig( + format='%(asctime)s [%(levelname)s] [%(filename)s:%(lineno)d] %(message)s', + datefmt='[%Y-%m-%d %H:%M:%S]') +logger = logging.getLogger(__name__) +logger.setLevel(logging.INFO) + + +class TransformerTTSUpdater(StandardUpdater): + def __init__( + self, + model, + optimizer, + dataloader, + init_state=None, + use_masking=False, + use_weighted_masking=False, + output_dir=None, + bce_pos_weight=5.0, + loss_type: str="L1", + use_guided_attn_loss: bool=True, + modules_applied_guided_attn: Sequence[str]=("encoder-decoder"), + guided_attn_loss_sigma: float=0.4, + guided_attn_loss_lambda: float=1.0, ): + super().__init__(model, optimizer, dataloader, init_state=None) + self.use_masking = use_masking + self.use_weighted_masking = use_weighted_masking + self.bce_pos_weight = bce_pos_weight + self.loss_type = loss_type + self.use_guided_attn_loss = use_guided_attn_loss + self.guided_attn_loss_sigma = guided_attn_loss_sigma + self.guided_attn_loss_lambda = guided_attn_loss_lambda + self.modules_applied_guided_attn = modules_applied_guided_attn + + self.criterion = TransformerTTSLoss( + use_masking=self.use_masking, + use_weighted_masking=self.use_weighted_masking, + bce_pos_weight=self.bce_pos_weight) + + if self.use_guided_attn_loss: + self.attn_criterion = GuidedMultiHeadAttentionLoss( + sigma=self.guided_attn_loss_sigma, + alpha=self.guided_attn_loss_lambda, ) + + log_file = output_dir / 'worker_{}.log'.format(dist.get_rank()) + self.filehandler = logging.FileHandler(str(log_file)) + logger.addHandler(self.filehandler) + self.logger = logger + self.msg = "" + + def update_core(self, batch): + self.msg = "Rank: {}, ".format(dist.get_rank()) + losses_dict = {} + + after_outs, before_outs, logits, ys, labels, olens, ilens, need_dict = self.model( + text=batch["text"], + text_lengths=batch["text_lengths"], + speech=batch["speech"], + speech_lengths=batch["speech_lengths"], ) + + l1_loss, l2_loss, bce_loss = self.criterion( + after_outs=after_outs, + before_outs=before_outs, + logits=logits, + ys=ys, + labels=labels, + olens=olens) + + report("train/bce_loss", float(bce_loss)) + report("train/l1_loss", float(l1_loss)) + report("train/l2_loss", float(l2_loss)) + losses_dict["bce_loss"] = float(bce_loss) + losses_dict["l1_loss"] = float(l1_loss) + losses_dict["l2_loss"] = float(l2_loss) + # caluculate loss values + if self.loss_type == "L1": + loss = l1_loss + bce_loss + elif self.loss_type == "L2": + loss = l2_loss + bce_loss + elif self.loss_type == "L1+L2": + loss = l1_loss + l2_loss + bce_loss + else: + raise ValueError("unknown --loss-type " + self.loss_type) + + # calculate guided attention loss + if self.use_guided_attn_loss: + # calculate for encoder + if "encoder" in self.modules_applied_guided_attn: + att_ws = [] + for idx, layer_idx in enumerate( + reversed(range(len(need_dict['encoder'].encoders)))): + att_ws += [ + need_dict['encoder'].encoders[layer_idx].self_attn. + attn[:, :need_dict['num_heads_applied_guided_attn']] + ] + if idx + 1 == need_dict['num_layers_applied_guided_attn']: + break + # (B, H*L, T_in, T_in) + att_ws = paddle.concat(att_ws, axis=1) + enc_attn_loss = self.attn_criterion(att_ws, ilens, ilens) + loss = loss + enc_attn_loss + report("train/enc_attn_loss", float(enc_attn_loss)) + losses_dict["enc_attn_loss"] = float(enc_attn_loss) + # calculate for decoder + if "decoder" in self.modules_applied_guided_attn: + att_ws = [] + for idx, layer_idx in enumerate( + reversed(range(len(need_dict['decoder'].decoders)))): + att_ws += [ + need_dict['decoder'].decoders[layer_idx].self_attn. + attn[:, :need_dict['num_heads_applied_guided_attn']] + ] + if idx + 1 == need_dict['num_layers_applied_guided_attn']: + break + # (B, H*L, T_out, T_out) + att_ws = paddle.concat(att_ws, axis=1) + dec_attn_loss = self.attn_criterion(att_ws, olens, olens) + report("train/dec_attn_loss", float(dec_attn_loss)) + losses_dict["dec_attn_loss"] = float(dec_attn_loss) + loss = loss + dec_attn_loss + # calculate for encoder-decoder + if "encoder-decoder" in self.modules_applied_guided_attn: + att_ws = [] + for idx, layer_idx in enumerate( + reversed(range(len(need_dict['decoder'].decoders)))): + att_ws += [ + need_dict['decoder'].decoders[layer_idx].src_attn. + attn[:, :need_dict['num_heads_applied_guided_attn']] + ] + if idx + 1 == need_dict['num_layers_applied_guided_attn']: + break + # (B, H*L, T_out, T_in) + att_ws = paddle.concat(att_ws, axis=1) + enc_dec_attn_loss = self.attn_criterion(att_ws, ilens, olens) + report("train/enc_dec_attn_loss", float(enc_dec_attn_loss)) + losses_dict["enc_dec_attn_loss"] = float(enc_dec_attn_loss) + loss = loss + enc_dec_attn_loss + if need_dict['use_scaled_pos_enc']: + report("train/encoder_alpha", + float(need_dict['encoder'].embed[-1].alpha)) + report("train/decoder_alpha", + float(need_dict['decoder'].embed[-1].alpha)) + losses_dict["encoder_alpha"] = float( + need_dict['encoder'].embed[-1].alpha) + losses_dict["decoder_alpha"] = float( + need_dict['decoder'].embed[-1].alpha) + + optimizer = self.optimizer + optimizer.clear_grad() + loss.backward() + optimizer.step() + + report("train/loss", float(loss)) + losses_dict["loss"] = float(loss) + self.msg += ', '.join('{}: {:>.6f}'.format(k, v) + for k, v in losses_dict.items()) + + +class TransformerTTSEvaluator(StandardEvaluator): + def __init__( + self, + model, + dataloader, + init_state=None, + use_masking=False, + use_weighted_masking=False, + output_dir=None, + bce_pos_weight=5.0, + loss_type: str="L1", + use_guided_attn_loss: bool=True, + modules_applied_guided_attn: Sequence[str]=("encoder-decoder"), + guided_attn_loss_sigma: float=0.4, + guided_attn_loss_lambda: float=1.0, ): + super().__init__(model, dataloader) + self.use_masking = use_masking + self.use_weighted_masking = use_weighted_masking + self.bce_pos_weight = bce_pos_weight + self.loss_type = loss_type + self.use_guided_attn_loss = use_guided_attn_loss + self.guided_attn_loss_sigma = guided_attn_loss_sigma + self.guided_attn_loss_lambda = guided_attn_loss_lambda + self.modules_applied_guided_attn = modules_applied_guided_attn + + self.criterion = TransformerTTSLoss( + use_masking=self.use_masking, + use_weighted_masking=self.use_weighted_masking, + bce_pos_weight=self.bce_pos_weight) + + if self.use_guided_attn_loss: + self.attn_criterion = GuidedMultiHeadAttentionLoss( + sigma=self.guided_attn_loss_sigma, + alpha=self.guided_attn_loss_lambda, ) + + log_file = output_dir / 'worker_{}.log'.format(dist.get_rank()) + self.filehandler = logging.FileHandler(str(log_file)) + logger.addHandler(self.filehandler) + self.logger = logger + self.msg = "" + + def evaluate_core(self, batch): + self.msg = "Evaluate: " + losses_dict = {} + after_outs, before_outs, logits, ys, labels, olens, ilens, need_dict = self.model( + text=batch["text"], + text_lengths=batch["text_lengths"], + speech=batch["speech"], + speech_lengths=batch["speech_lengths"]) + + l1_loss, l2_loss, bce_loss = self.criterion( + after_outs=after_outs, + before_outs=before_outs, + logits=logits, + ys=ys, + labels=labels, + olens=olens) + + report("eval/bce_loss", float(bce_loss)) + report("eval/l1_loss", float(l1_loss)) + report("eval/l2_loss", float(l2_loss)) + losses_dict["bce_loss"] = float(bce_loss) + losses_dict["l1_loss"] = float(l1_loss) + losses_dict["l2_loss"] = float(l2_loss) + # caluculate loss values + if self.loss_type == "L1": + loss = l1_loss + bce_loss + elif self.loss_type == "L2": + loss = l2_loss + bce_loss + elif self.loss_type == "L1+L2": + loss = l1_loss + l2_loss + bce_loss + else: + raise ValueError("unknown --loss-type " + self.loss_type) + + # calculate guided attention loss + if self.use_guided_attn_loss: + # calculate for encoder + if "encoder" in self.modules_applied_guided_attn: + att_ws = [] + for idx, layer_idx in enumerate( + reversed(range(len(need_dict['encoder'].encoders)))): + att_ws += [ + need_dict['encoder'].encoders[layer_idx].self_attn. + attn[:, :need_dict['num_heads_applied_guided_attn']] + ] + if idx + 1 == need_dict['num_layers_applied_guided_attn']: + break + # (B, H*L, T_in, T_in) + att_ws = paddle.concat(att_ws, axis=1) + enc_attn_loss = self.attn_criterion(att_ws, ilens, ilens) + loss = loss + enc_attn_loss + report("train/enc_attn_loss", float(enc_attn_loss)) + losses_dict["enc_attn_loss"] = float(enc_attn_loss) + # calculate for decoder + if "decoder" in self.modules_applied_guided_attn: + att_ws = [] + for idx, layer_idx in enumerate( + reversed(range(len(need_dict['decoder'].decoders)))): + att_ws += [ + need_dict['decoder'].decoders[layer_idx].self_attn. + attn[:, :need_dict['num_heads_applied_guided_attn']] + ] + if idx + 1 == need_dict['num_layers_applied_guided_attn']: + break + # (B, H*L, T_out, T_out) + att_ws = paddle.concat(att_ws, axis=1) + dec_attn_loss = self.attn_criterion(att_ws, olens, olens) + report("eval/dec_attn_loss", float(dec_attn_loss)) + losses_dict["dec_attn_loss"] = float(dec_attn_loss) + loss = loss + dec_attn_loss + # calculate for encoder-decoder + if "encoder-decoder" in self.modules_applied_guided_attn: + + att_ws = [] + for idx, layer_idx in enumerate( + reversed(range(len(need_dict['decoder'].decoders)))): + att_ws += [ + need_dict['decoder'].decoders[layer_idx].src_attn. + attn[:, :need_dict['num_heads_applied_guided_attn']] + ] + if idx + 1 == need_dict['num_layers_applied_guided_attn']: + break + # (B, H*L, T_out, T_in) + att_ws = paddle.concat(att_ws, axis=1) + enc_dec_attn_loss = self.attn_criterion(att_ws, ilens, olens) + report("eval/enc_dec_attn_loss", float(enc_dec_attn_loss)) + losses_dict["enc_dec_attn_loss"] = float(enc_dec_attn_loss) + loss = loss + enc_dec_attn_loss + if need_dict['use_scaled_pos_enc']: + report("eval/encoder_alpha", + float(need_dict['encoder'].embed[-1].alpha)) + report("eval/decoder_alpha", + float(need_dict['decoder'].embed[-1].alpha)) + losses_dict["encoder_alpha"] = float( + need_dict['encoder'].embed[-1].alpha) + losses_dict["decoder_alpha"] = float( + need_dict['decoder'].embed[-1].alpha) + report("eval/loss", float(loss)) + losses_dict["loss"] = float(loss) + self.msg += ', '.join('{}: {:>.6f}'.format(k, v) + for k, v in losses_dict.items()) + self.logger.info(self.msg) diff --git a/parakeet/models/waveflow.py b/parakeet/models/waveflow.py new file mode 100644 index 00000000..b6317bf8 --- /dev/null +++ b/parakeet/models/waveflow.py @@ -0,0 +1,909 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import math +import time +from typing import List +from typing import Tuple +from typing import Union + +import numpy as np +import paddle +from paddle import nn +from paddle.nn import functional as F +from paddle.nn import initializer as I + +from parakeet.modules import geometry as geo +from parakeet.utils import checkpoint + +__all__ = ["WaveFlow", "ConditionalWaveFlow", "WaveFlowLoss"] + + +def fold(x, n_group): + r"""Fold audio or spectrogram's temporal dimension in to groups. + + Parameters + ---------- + x : Tensor [shape=(\*, time_steps) + The input tensor. + + n_group : int + The size of a group. + + Returns + --------- + Tensor : [shape=(\*, time_steps // n_group, group)] + Folded tensor. + """ + spatial_shape = list(x.shape[:-1]) + time_steps = paddle.shape(x)[-1] + new_shape = spatial_shape + [time_steps // n_group, n_group] + return paddle.reshape(x, new_shape) + + +class UpsampleNet(nn.LayerList): + """Layer to upsample mel spectrogram to the same temporal resolution with + the corresponding waveform. + + It consists of several conv2dtranspose layers which perform deconvolution + on mel and time dimension. + + Parameters + ---------- + upscale_factors : List[int], optional + Time upsampling factors for each Conv2DTranspose Layer. + + The ``UpsampleNet`` contains ``len(upscale_factor)`` Conv2DTranspose + Layers. Each upscale_factor is used as the ``stride`` for the + corresponding Conv2DTranspose. Defaults to [16, 16], this the default + upsampling factor is 256. + + Notes + ------ + ``np.prod(upscale_factors)`` should equals the ``hop_length`` of the stft + transformation used to extract spectrogram features from audio. + + For example, ``16 * 16 = 256``, then the spectrogram extracted with a stft + transformation whose ``hop_length`` equals 256 is suitable. + + See Also + --------- + ``librosa.core.stft`` + """ + + def __init__(self, upsample_factors): + super().__init__() + for factor in upsample_factors: + std = math.sqrt(1 / (3 * 2 * factor)) + init = I.Uniform(-std, std) + self.append( + nn.utils.weight_norm( + nn.Conv2DTranspose( + 1, + 1, (3, 2 * factor), + padding=(1, factor // 2), + stride=(1, factor), + weight_attr=init, + bias_attr=init))) + + # upsample factors + self.upsample_factor = np.prod(upsample_factors) + self.upsample_factors = upsample_factors + + def forward(self, x, trim_conv_artifact=False): + r"""Forward pass of the ``UpsampleNet``. + + Parameters + ----------- + x : Tensor [shape=(batch_size, input_channels, time_steps)] + The input spectrogram. + + trim_conv_artifact : bool, optional + Trim deconvolution artifact at each layer. Defaults to False. + + Returns + -------- + Tensor: [shape=(batch_size, input_channels, time_steps \* upsample_factor)] + The upsampled spectrogram. + + Notes + -------- + If trim_conv_artifact is ``True``, the output time steps is less + than ``time_steps \* upsample_factors``. + """ + x = paddle.unsqueeze(x, 1) # (B, C, T) -> (B, 1, C, T) + for layer in self: + x = layer(x) + if trim_conv_artifact: + time_cutoff = layer._kernel_size[1] - layer._stride[1] + x = x[:, :, :, :-time_cutoff] + x = F.leaky_relu(x, 0.4) + x = paddle.squeeze(x, 1) # back to (B, C, T) + return x + + +class ResidualBlock(nn.Layer): + """ResidualBlock, the basic unit of ResidualNet used in WaveFlow. + + It has a conv2d layer, which has causal padding in height dimension and + same paddign in width dimension. It also has projection for the condition + and output. + + Parameters + ---------- + channels : int + Feature size of the input. + + cond_channels : int + Featuer size of the condition. + + kernel_size : Tuple[int] + Kernel size of the Convolution2d applied to the input. + + dilations : int + Dilations of the Convolution2d applied to the input. + """ + + def __init__(self, channels, cond_channels, kernel_size, dilations): + super().__init__() + # input conv + std = math.sqrt(1 / channels * np.prod(kernel_size)) + init = I.Uniform(-std, std) + receptive_field = [ + 1 + (k - 1) * d for (k, d) in zip(kernel_size, dilations) + ] + rh, rw = receptive_field + paddings = [rh - 1, 0, rw // 2, (rw - 1) // 2] # causal & same + conv = nn.Conv2D( + channels, + 2 * channels, + kernel_size, + padding=paddings, + dilation=dilations, + weight_attr=init, + bias_attr=init) + self.conv = nn.utils.weight_norm(conv) + self.rh = rh + self.rw = rw + self.dilations = dilations + + # condition projection + std = math.sqrt(1 / cond_channels) + init = I.Uniform(-std, std) + condition_proj = nn.Conv2D( + cond_channels, + 2 * channels, (1, 1), + weight_attr=init, + bias_attr=init) + self.condition_proj = nn.utils.weight_norm(condition_proj) + + # parametric residual & skip connection + std = math.sqrt(1 / channels) + init = I.Uniform(-std, std) + out_proj = nn.Conv2D( + channels, 2 * channels, (1, 1), weight_attr=init, bias_attr=init) + self.out_proj = nn.utils.weight_norm(out_proj) + + def forward(self, x, condition): + """Compute output for a whole folded sequence. + + Parameters + ---------- + x : Tensor [shape=(batch_size, channel, height, width)] + The input. + + condition : Tensor [shape=(batch_size, condition_channel, height, width)] + The local condition. + + Returns + ------- + res : Tensor [shape=(batch_size, channel, height, width)] + The residual output. + + skip : Tensor [shape=(batch_size, channel, height, width)] + The skip output. + """ + x_in = x + x = self.conv(x) + x += self.condition_proj(condition) + + content, gate = paddle.chunk(x, 2, axis=1) + x = paddle.tanh(content) * F.sigmoid(gate) + + x = self.out_proj(x) + res, skip = paddle.chunk(x, 2, axis=1) + res = x_in + res + return res, skip + + def start_sequence(self): + """Prepare the layer for incremental computation of causal + convolution. Reset the buffer for causal convolution. + + Raises: + ValueError: If not in evaluation mode. + """ + if self.training: + raise ValueError("Only use start sequence at evaluation mode.") + self._conv_buffer = paddle.zeros([1]) + + # NOTE: call self.conv's weight norm hook expliccitly since + # its weight will be visited directly in `add_input` without + # calling its `__call__` method. If we do not trigger the weight + # norm hook, the weight may be outdated. e.g. after loading from + # a saved checkpoint + # see also: https://github.com/pytorch/pytorch/issues/47588 + for hook in self.conv._forward_pre_hooks.values(): + hook(self.conv, None) + + def add_input(self, x_row, condition_row): + """Compute the output for a row and update the buffer. + + Parameters + ---------- + x_row : Tensor [shape=(batch_size, channel, 1, width)] + A row of the input. + + condition_row : Tensor [shape=(batch_size, condition_channel, 1, width)] + A row of the condition. + + Returns + ------- + res : Tensor [shape=(batch_size, channel, 1, width)] + A row of the the residual output. + + skip : Tensor [shape=(batch_size, channel, 1, width)] + A row of the skip output. + """ + x_row_in = x_row + if len(paddle.shape(self._conv_buffer)) == 1: + self._init_buffer(x_row) + self._update_buffer(x_row) + rw = self.rw + x_row = F.conv2d( + self._conv_buffer, + self.conv.weight, + self.conv.bias, + padding=[0, 0, rw // 2, (rw - 1) // 2], + dilation=self.dilations) + x_row += self.condition_proj(condition_row) + content, gate = paddle.chunk(x_row, 2, axis=1) + x_row = paddle.tanh(content) * F.sigmoid(gate) + + x_row = self.out_proj(x_row) + res, skip = paddle.chunk(x_row, 2, axis=1) + res = x_row_in + res + return res, skip + + def _init_buffer(self, input): + batch_size, channels, _, width = input.shape + self._conv_buffer = paddle.zeros( + [batch_size, channels, self.rh, width], dtype=input.dtype) + + def _update_buffer(self, input): + self._conv_buffer = paddle.concat( + [self._conv_buffer[:, :, 1:, :], input], axis=2) + + +class ResidualNet(nn.LayerList): + """A stack of several ResidualBlocks. It merges condition at each layer. + + Parameters + ---------- + n_layer : int + Number of ResidualBlocks in the ResidualNet. + + residual_channels : int + Feature size of each ResidualBlocks. + + condition_channels : int + Feature size of the condition. + + kernel_size : Tuple[int] + Kernel size of each ResidualBlock. + + dilations_h : List[int] + Dilation in height dimension of every ResidualBlock. + + Raises + ------ + ValueError + If the length of dilations_h does not equals n_layers. + """ + + def __init__(self, + n_layer: int, + residual_channels: int, + condition_channels: int, + kernel_size: Tuple[int], + dilations_h: List[int]): + if len(dilations_h) != n_layer: + raise ValueError( + "number of dilations_h should equals num of layers") + super(ResidualNet, self).__init__() + for i in range(n_layer): + dilation = (dilations_h[i], 2**i) + layer = ResidualBlock(residual_channels, condition_channels, + kernel_size, dilation) + self.append(layer) + + def forward(self, x, condition): + """Comput the output of given the input and the condition. + + Parameters + ----------- + x : Tensor [shape=(batch_size, channel, height, width)] + The input. + + condition : Tensor [shape=(batch_size, condition_channel, height, width)] + The local condition. + + Returns + -------- + Tensor : [shape=(batch_size, channel, height, width)] + The output, which is an aggregation of all the skip outputs. + """ + skip_connections = [] + for layer in self: + x, skip = layer(x, condition) + skip_connections.append(skip) + out = paddle.sum(paddle.stack(skip_connections, 0), 0) + return out + + def start_sequence(self): + """Prepare the layer for incremental computation. + """ + for layer in self: + layer.start_sequence() + + def add_input(self, x_row, condition_row): + """Compute the output for a row and update the buffers. + + Parameters + ---------- + x_row : Tensor [shape=(batch_size, channel, 1, width)] + A row of the input. + + condition_row : Tensor [shape=(batch_size, condition_channel, 1, width)] + A row of the condition. + + Returns + ------- + res : Tensor [shape=(batch_size, channel, 1, width)] + A row of the the residual output. + + skip : Tensor [shape=(batch_size, channel, 1, width)] + A row of the skip output. + """ + skip_connections = [] + for layer in self: + x_row, skip = layer.add_input(x_row, condition_row) + skip_connections.append(skip) + out = paddle.sum(paddle.stack(skip_connections, 0), 0) + return out + + +class Flow(nn.Layer): + """A bijection (Reversable layer) that transform a density of latent + variables p(Z) into a complex data distribution p(X). + + It's an auto regressive flow. The ``forward`` method implements the + probability density estimation. The ``inverse`` method implements the + sampling. + + Parameters + ---------- + n_layers : int + Number of ResidualBlocks in the Flow. + + channels : int + Feature size of the ResidualBlocks. + + mel_bands : int + Feature size of the mel spectrogram (mel bands). + + kernel_size : Tuple[int] + Kernel size of each ResisualBlocks in the Flow. + + n_group : int + Number of timesteps to the folded into a group. + """ + dilations_dict = { + 8: [1, 1, 1, 1, 1, 1, 1, 1], + 16: [1, 1, 1, 1, 1, 1, 1, 1], + 32: [1, 2, 4, 1, 2, 4, 1, 2], + 64: [1, 2, 4, 8, 16, 1, 2, 4], + 128: [1, 2, 4, 8, 16, 32, 64, 1] + } + + def __init__(self, n_layers, channels, mel_bands, kernel_size, n_group): + super().__init__() + # input projection + self.input_proj = nn.utils.weight_norm( + nn.Conv2D( + 1, + channels, (1, 1), + weight_attr=I.Uniform(-1., 1.), + bias_attr=I.Uniform(-1., 1.))) + + # residual net + self.resnet = ResidualNet(n_layers, channels, mel_bands, kernel_size, + self.dilations_dict[n_group]) + + # output projection + self.output_proj = nn.Conv2D( + channels, + 2, (1, 1), + weight_attr=I.Constant(0.), + bias_attr=I.Constant(0.)) + + # specs + self.n_group = n_group + + def _predict_parameters(self, x, condition): + x = self.input_proj(x) + x = self.resnet(x, condition) + bijection_params = self.output_proj(x) + logs, b = paddle.chunk(bijection_params, 2, axis=1) + return logs, b + + def _transform(self, x, logs, b): + z_0 = x[:, :, :1, :] # the first row, just copy it + z_out = x[:, :, 1:, :] * paddle.exp(logs) + b + z_out = paddle.concat([z_0, z_out], axis=2) + return z_out + + def forward(self, x, condition): + """Probability density estimation. It is done by inversely transform + a sample from p(X) into a sample from p(Z). + + Parameters + ----------- + x : Tensor [shape=(batch, 1, height, width)] + A input sample of the distribution p(X). + + condition : Tensor [shape=(batch, condition_channel, height, width)] + The local condition. + + Returns + -------- + z (Tensor): shape(batch, 1, height, width), the transformed sample. + + Tuple[Tensor, Tensor] + The parameter of the transformation. + + logs (Tensor): shape(batch, 1, height - 1, width), the log scale + of the transformation from x to z. + + b (Tensor): shape(batch, 1, height - 1, width), the shift of the + transformation from x to z. + """ + # (B, C, H-1, W) + logs, b = self._predict_parameters(x[:, :, :-1, :], + condition[:, :, 1:, :]) + z = self._transform(x, logs, b) + return z, (logs, b) + + def _predict_row_parameters(self, x_row, condition_row): + x_row = self.input_proj(x_row) + x_row = self.resnet.add_input(x_row, condition_row) + bijection_params = self.output_proj(x_row) + logs, b = paddle.chunk(bijection_params, 2, axis=1) + return logs, b + + def _inverse_transform_row(self, z_row, logs, b): + x_row = (z_row - b) * paddle.exp(-logs) + return x_row + + def _inverse_row(self, z_row, x_row, condition_row): + logs, b = self._predict_row_parameters(x_row, condition_row) + x_next_row = self._inverse_transform_row(z_row, logs, b) + return x_next_row, (logs, b) + + def _start_sequence(self): + self.resnet.start_sequence() + + def inverse(self, z, condition): + """Sampling from the the distrition p(X). It is done by sample form + p(Z) and transform the sample. It is a auto regressive transformation. + + Parameters + ----------- + z : Tensor [shape=(batch, 1, height, width)] + A sample of the distribution p(Z). + + condition : Tensor [shape=(batch, condition_channel, height, width)] + The local condition. + + Returns + --------- + x : Tensor [shape=(batch, 1, height, width)] + The transformed sample. + + Tuple[Tensor, Tensor] + The parameter of the transformation. + + logs (Tensor): shape(batch, 1, height - 1, width), the log scale + of the transformation from x to z. + + b (Tensor): shape(batch, 1, height - 1, width), the shift of the + transformation from x to z. + """ + z_0 = z[:, :, :1, :] + x = paddle.zeros_like(z) + x[:, :, :1, :] = z_0 + + self._start_sequence() + + num_step = paddle.ones([1], dtype='int32') * (self.n_group) + for i in range(1, num_step): + x_row = x[:, :, i - 1:i, :] + z_row = z[:, :, i:i + 1, :] + condition_row = condition[:, :, i:i + 1, :] + x_next_row, (logs, b) = self._inverse_row(z_row, x_row, + condition_row) + x[:, :, i:i + 1, :] = x_next_row + + return x + + +class WaveFlow(nn.LayerList): + """An Deep Reversible layer that is composed of severel auto regressive + flows. + + Parameters + ----------- + n_flows : int + Number of flows in the WaveFlow model. + + n_layers : int + Number of ResidualBlocks in each Flow. + + n_group : int + Number of timesteps to fold as a group. + + channels : int + Feature size of each ResidualBlock. + + mel_bands : int + Feature size of mel spectrogram (mel bands). + + kernel_size : Union[int, List[int]] + Kernel size of the convolution layer in each ResidualBlock. + """ + + def __init__(self, n_flows, n_layers, n_group, channels, mel_bands, + kernel_size): + if n_group % 2 or n_flows % 2: + raise ValueError( + "number of flows and number of group must be even " + "since a permutation along group among flows is used.") + super().__init__() + for _ in range(n_flows): + self.append( + Flow(n_layers, channels, mel_bands, kernel_size, n_group)) + + # permutations in h + self.perms = self._create_perm(n_group, n_flows) + + # specs + self.n_group = n_group + self.n_flows = n_flows + + def _create_perm(self, n_group, n_flows): + indices = list(range(n_group)) + half = n_group // 2 + perms = [] + for i in range(n_flows): + if i < n_flows // 2: + perm = indices[::-1] + else: + perm = list(reversed(indices[:half])) + list( + reversed(indices[half:])) + perm = paddle.to_tensor(perm) + self.register_buffer(perm.name, perm) + perms.append(perm) + return perms + + def _trim(self, x, condition): + assert condition.shape[-1] >= x.shape[-1] + pruned_len = int(paddle.shape(x)[-1] // self.n_group * self.n_group) + + if x.shape[-1] > pruned_len: + x = x[:, :pruned_len] + if condition.shape[-1] > pruned_len: + condition = condition[:, :, :pruned_len] + return x, condition + + def forward(self, x, condition): + """Probability density estimation of random variable x given the + condition. + + Parameters + ----------- + x : Tensor [shape=(batch_size, time_steps)] + The audio. + + condition : Tensor [shape=(batch_size, condition channel, time_steps)] + The local condition (mel spectrogram here). + + Returns + -------- + z : Tensor [shape=(batch_size, time_steps)] + The transformed random variable. + + log_det_jacobian: Tensor [shape=(1,)] + The log determinant of the jacobian of the transformation from x + to z. + """ + # x: (B, T) + # condition: (B, C, T) upsampled condition + x, condition = self._trim(x, condition) + + # to (B, C, h, T//h) layout + x = paddle.unsqueeze( + paddle.transpose(fold(x, self.n_group), [0, 2, 1]), 1) + condition = paddle.transpose( + fold(condition, self.n_group), [0, 1, 3, 2]) + + # flows + logs_list = [] + for i, layer in enumerate(self): + x, (logs, b) = layer(x, condition) + logs_list.append(logs) + # permute paddle has no shuffle dim + x = geo.shuffle_dim(x, 2, perm=self.perms[i]) + condition = geo.shuffle_dim(condition, 2, perm=self.perms[i]) + + z = paddle.squeeze(x, 1) # (B, H, W) + batch_size = z.shape[0] + z = paddle.reshape(paddle.transpose(z, [0, 2, 1]), [batch_size, -1]) + + log_det_jacobian = paddle.sum(paddle.stack(logs_list)) + return z, log_det_jacobian + + def inverse(self, z, condition): + """Sampling from the the distrition p(X). + + It is done by sample a ``z`` form p(Z) and transform it into ``x``. + Each Flow transform .. math:: `z_{i-1}` to .. math:: `z_{i}` in an + autoregressive manner. + + Parameters + ---------- + z : Tensor [shape=(batch, 1, time_steps] + A sample of the distribution p(Z). + + condition : Tensor [shape=(batch, condition_channel, time_steps)] + The local condition. + + Returns + -------- + x : Tensor [shape=(batch_size, time_steps)] + The transformed sample (audio here). + """ + + z, condition = self._trim(z, condition) + # to (B, C, h, T//h) layout + z = paddle.unsqueeze( + paddle.transpose(fold(z, self.n_group), [0, 2, 1]), 1) + condition = paddle.transpose( + fold(condition, self.n_group), [0, 1, 3, 2]) + + # reverse it flow by flow + for i in reversed(range(self.n_flows)): + z = geo.shuffle_dim(z, 2, perm=self.perms[i]) + condition = geo.shuffle_dim(condition, 2, perm=self.perms[i]) + z = self[i].inverse(z, condition) + + x = paddle.squeeze(z, 1) # (B, H, W) + batch_size = x.shape[0] + x = paddle.reshape(paddle.transpose(x, [0, 2, 1]), [batch_size, -1]) + return x + + +class ConditionalWaveFlow(nn.LayerList): + """ConditionalWaveFlow, a UpsampleNet with a WaveFlow model. + + Parameters + ---------- + upsample_factors : List[int] + Upsample factors for the upsample net. + + n_flows : int + Number of flows in the WaveFlow model. + + n_layers : int + Number of ResidualBlocks in each Flow. + + n_group : int + Number of timesteps to fold as a group. + + channels : int + Feature size of each ResidualBlock. + + n_mels : int + Feature size of mel spectrogram (mel bands). + + kernel_size : Union[int, List[int]] + Kernel size of the convolution layer in each ResidualBlock. + """ + + def __init__(self, + upsample_factors: List[int], + n_flows: int, + n_layers: int, + n_group: int, + channels: int, + n_mels: int, + kernel_size: Union[int, List[int]]): + super().__init__() + self.encoder = UpsampleNet(upsample_factors) + self.decoder = WaveFlow( + n_flows=n_flows, + n_layers=n_layers, + n_group=n_group, + channels=channels, + mel_bands=n_mels, + kernel_size=kernel_size) + + def forward(self, audio, mel): + """Compute the transformed random variable z (x to z) and the log of + the determinant of the jacobian of the transformation from x to z. + + Parameters + ---------- + audio : Tensor [shape=(B, T)] + The audio. + + mel : Tensor [shape=(B, C_mel, T_mel)] + The mel spectrogram. + + Returns + ------- + z : Tensor [shape=(B, T)] + The inversely transformed random variable z (x to z) + + log_det_jacobian: Tensor [shape=(1,)] + the log of the determinant of the jacobian of the transformation + from x to z. + """ + condition = self.encoder(mel) + z, log_det_jacobian = self.decoder(audio, condition) + return z, log_det_jacobian + + @paddle.no_grad() + def infer(self, mel): + r"""Generate raw audio given mel spectrogram. + + Parameters + ---------- + mel : Tensor [shape=(B, C_mel, T_mel)] + Mel spectrogram (in log-magnitude). + + Returns + ------- + Tensor : [shape=(B, T)] + The synthesized audio, where``T <= T_mel \* upsample_factors``. + """ + start = time.time() + condition = self.encoder(mel, trim_conv_artifact=True) # (B, C, T) + batch_size, _, time_steps = condition.shape + z = paddle.randn([batch_size, time_steps], dtype=mel.dtype) + x = self.decoder.inverse(z, condition) + end = time.time() + print("time: {}s".format(end - start)) + return x + + @paddle.no_grad() + def predict(self, mel): + """Generate raw audio given mel spectrogram. + + Parameters + ---------- + mel : np.ndarray [shape=(C_mel, T_mel)] + Mel spectrogram of an utterance(in log-magnitude). + + Returns + ------- + np.ndarray [shape=(T,)] + The synthesized audio. + """ + mel = paddle.to_tensor(mel) + mel = paddle.unsqueeze(mel, 0) + audio = self.infer(mel) + audio = audio[0].numpy() + return audio + + @classmethod + def from_pretrained(cls, config, checkpoint_path): + """Build a ConditionalWaveFlow model from a pretrained model. + + Parameters + ---------- + config: yacs.config.CfgNode + model configs + + checkpoint_path: Path or str + the path of pretrained model checkpoint, without extension name + + Returns + ------- + ConditionalWaveFlow + The model built from pretrained result. + """ + model = cls(upsample_factors=config.model.upsample_factors, + n_flows=config.model.n_flows, + n_layers=config.model.n_layers, + n_group=config.model.n_group, + channels=config.model.channels, + n_mels=config.data.n_mels, + kernel_size=config.model.kernel_size) + checkpoint.load_parameters(model, checkpoint_path=checkpoint_path) + return model + + +class WaveFlowLoss(nn.Layer): + """Criterion of a WaveFlow model. + + Parameters + ---------- + sigma : float + The standard deviation of the gaussian noise used in WaveFlow, by + default 1.0. + """ + + def __init__(self, sigma=1.0): + super().__init__() + self.sigma = sigma + self.const = 0.5 * np.log(2 * np.pi) + np.log(self.sigma) + + def forward(self, z, log_det_jacobian): + """Compute the loss given the transformed random variable z and the + log_det_jacobian of transformation from x to z. + + Parameters + ---------- + z : Tensor [shape=(B, T)] + The transformed random variable (x to z). + + log_det_jacobian : Tensor [shape=(1,)] + The log of the determinant of the jacobian matrix of the + transformation from x to z. + + Returns + ------- + Tensor [shape=(1,)] + The loss. + """ + loss = paddle.sum(z * z) / (2 * self.sigma * self.sigma + ) - log_det_jacobian + loss = loss / np.prod(z.shape) + return loss + self.const + + +class ConditionalWaveFlow2Infer(ConditionalWaveFlow): + def forward(self, mel): + """Generate raw audio given mel spectrogram. + + Parameters + ---------- + mel : np.ndarray [shape=(C_mel, T_mel)] + Mel spectrogram of an utterance(in log-magnitude). + + Returns + ------- + np.ndarray [shape=(T,)] + The synthesized audio. + """ + audio = self.predict(mel) + return audio diff --git a/parakeet/modules/__init__.py b/parakeet/modules/__init__.py new file mode 100644 index 00000000..fd38c0c4 --- /dev/null +++ b/parakeet/modules/__init__.py @@ -0,0 +1,21 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from .attention import * +from .conv import * +from .geometry import * +from .losses import * +from .masking import * +from .positional_encoding import * +from .transformer import * diff --git a/parakeet/modules/attention.py b/parakeet/modules/attention.py new file mode 100644 index 00000000..154625cc --- /dev/null +++ b/parakeet/modules/attention.py @@ -0,0 +1,348 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import math + +import numpy as np +import paddle +from paddle import nn +from paddle.nn import functional as F + + +def scaled_dot_product_attention(q, k, v, mask=None, dropout=0.0, + training=True): + r"""Scaled dot product attention with masking. + + Assume that q, k, v all have the same leading dimensions (denoted as * in + descriptions below). Dropout is applied to attention weights before + weighted sum of values. + + Parameters + ----------- + q : Tensor [shape=(\*, T_q, d)] + the query tensor. + k : Tensor [shape=(\*, T_k, d)] + the key tensor. + v : Tensor [shape=(\*, T_k, d_v)] + the value tensor. + mask : Tensor, [shape=(\*, T_q, T_k) or broadcastable shape], optional + the mask tensor, zeros correspond to paddings. Defaults to None. + + Returns + ---------- + out : Tensor [shape=(\*, T_q, d_v)] + the context vector. + attn_weights : Tensor [shape=(\*, T_q, T_k)] + the attention weights. + """ + d = q.shape[-1] # we only support imperative execution + qk = paddle.matmul(q, k, transpose_y=True) + scaled_logit = paddle.scale(qk, 1.0 / math.sqrt(d)) + + if mask is not None: + scaled_logit += paddle.scale((1.0 - mask), -1e9) # hard coded here + + attn_weights = F.softmax(scaled_logit, axis=-1) + attn_weights = F.dropout(attn_weights, dropout, training=training) + out = paddle.matmul(attn_weights, v) + return out, attn_weights + + +def drop_head(x, drop_n_heads, training=True): + """Drop n context vectors from multiple ones. + + Parameters + ---------- + x : Tensor [shape=(batch_size, num_heads, time_steps, channels)] + The input, multiple context vectors. + drop_n_heads : int [0<= drop_n_heads <= num_heads] + Number of vectors to drop. + training : bool + A flag indicating whether it is in training. If `False`, no dropout is + applied. + + Returns + ------- + Tensor + The output. + """ + if not training or (drop_n_heads == 0): + return x + + batch_size, num_heads, _, _ = x.shape + # drop all heads + if num_heads == drop_n_heads: + return paddle.zeros_like(x) + + mask = np.ones([batch_size, num_heads]) + mask[:, :drop_n_heads] = 0 + for subarray in mask: + np.random.shuffle(subarray) + scale = float(num_heads) / (num_heads - drop_n_heads) + mask = scale * np.reshape(mask, [batch_size, num_heads, 1, 1]) + out = x * paddle.to_tensor(mask) + return out + + +def _split_heads(x, num_heads): + batch_size, time_steps, _ = x.shape + x = paddle.reshape(x, [batch_size, time_steps, num_heads, -1]) + x = paddle.transpose(x, [0, 2, 1, 3]) + return x + + +def _concat_heads(x): + batch_size, _, time_steps, _ = x.shape + x = paddle.transpose(x, [0, 2, 1, 3]) + x = paddle.reshape(x, [batch_size, time_steps, -1]) + return x + + +# Standard implementations of Monohead Attention & Multihead Attention +class MonoheadAttention(nn.Layer): + """Monohead Attention module. + + Parameters + ---------- + model_dim : int + Feature size of the query. + dropout : float, optional + Dropout probability of scaled dot product attention and final context + vector. Defaults to 0.0. + k_dim : int, optional + Feature size of the key of each scaled dot product attention. If not + provided, it is set to `model_dim / num_heads`. Defaults to None. + v_dim : int, optional + Feature size of the key of each scaled dot product attention. If not + provided, it is set to `model_dim / num_heads`. Defaults to None. + """ + + def __init__(self, + model_dim: int, + dropout: float=0.0, + k_dim: int=None, + v_dim: int=None): + super(MonoheadAttention, self).__init__() + k_dim = k_dim or model_dim + v_dim = v_dim or model_dim + self.affine_q = nn.Linear(model_dim, k_dim) + self.affine_k = nn.Linear(model_dim, k_dim) + self.affine_v = nn.Linear(model_dim, v_dim) + self.affine_o = nn.Linear(v_dim, model_dim) + + self.model_dim = model_dim + self.dropout = dropout + + def forward(self, q, k, v, mask): + """Compute context vector and attention weights. + + Parameters + ----------- + q : Tensor [shape=(batch_size, time_steps_q, model_dim)] + The queries. + k : Tensor [shape=(batch_size, time_steps_k, model_dim)] + The keys. + v : Tensor [shape=(batch_size, time_steps_k, model_dim)] + The values. + mask : Tensor [shape=(batch_size, times_steps_q, time_steps_k] or broadcastable shape + The mask. + + Returns + ---------- + out : Tensor [shape=(batch_size, time_steps_q, model_dim)] + The context vector. + attention_weights : Tensor [shape=(batch_size, times_steps_q, time_steps_k)] + The attention weights. + """ + q = self.affine_q(q) # (B, T, C) + k = self.affine_k(k) + v = self.affine_v(v) + + context_vectors, attention_weights = scaled_dot_product_attention( + q, k, v, mask, self.dropout, self.training) + + out = self.affine_o(context_vectors) + return out, attention_weights + + +class MultiheadAttention(nn.Layer): + """Multihead Attention module. + + Parameters + ----------- + model_dim: int + The feature size of query. + num_heads : int + The number of attention heads. + dropout : float, optional + Dropout probability of scaled dot product attention and final context + vector. Defaults to 0.0. + k_dim : int, optional + Feature size of the key of each scaled dot product attention. If not + provided, it is set to ``model_dim / num_heads``. Defaults to None. + v_dim : int, optional + Feature size of the key of each scaled dot product attention. If not + provided, it is set to ``model_dim / num_heads``. Defaults to None. + + Raises + --------- + ValueError + If ``model_dim`` is not divisible by ``num_heads``. + """ + + def __init__(self, + model_dim: int, + num_heads: int, + dropout: float=0.0, + k_dim: int=None, + v_dim: int=None): + super(MultiheadAttention, self).__init__() + if model_dim % num_heads != 0: + raise ValueError("model_dim must be divisible by num_heads") + depth = model_dim // num_heads + k_dim = k_dim or depth + v_dim = v_dim or depth + self.affine_q = nn.Linear(model_dim, num_heads * k_dim) + self.affine_k = nn.Linear(model_dim, num_heads * k_dim) + self.affine_v = nn.Linear(model_dim, num_heads * v_dim) + self.affine_o = nn.Linear(num_heads * v_dim, model_dim) + + self.num_heads = num_heads + self.model_dim = model_dim + self.dropout = dropout + + def forward(self, q, k, v, mask): + """Compute context vector and attention weights. + + Parameters + ----------- + q : Tensor [shape=(batch_size, time_steps_q, model_dim)] + The queries. + k : Tensor [shape=(batch_size, time_steps_k, model_dim)] + The keys. + v : Tensor [shape=(batch_size, time_steps_k, model_dim)] + The values. + mask : Tensor [shape=(batch_size, times_steps_q, time_steps_k] or broadcastable shape + The mask. + + Returns + ---------- + out : Tensor [shape=(batch_size, time_steps_q, model_dim)] + The context vector. + attention_weights : Tensor [shape=(batch_size, times_steps_q, time_steps_k)] + The attention weights. + """ + q = _split_heads(self.affine_q(q), self.num_heads) # (B, h, T, C) + k = _split_heads(self.affine_k(k), self.num_heads) + v = _split_heads(self.affine_v(v), self.num_heads) + mask = paddle.unsqueeze(mask, 1) # unsqueeze for the h dim + + context_vectors, attention_weights = scaled_dot_product_attention( + q, k, v, mask, self.dropout, self.training) + # NOTE: there is more sophisticated implementation: Scheduled DropHead + context_vectors = _concat_heads(context_vectors) # (B, T, h*C) + out = self.affine_o(context_vectors) + return out, attention_weights + + +class LocationSensitiveAttention(nn.Layer): + """Location Sensitive Attention module. + + Reference: `Attention-Based Models for Speech Recognition `_ + + Parameters + ----------- + d_query: int + The feature size of query. + d_key : int + The feature size of key. + d_attention : int + The feature size of dimension. + location_filters : int + Filter size of attention convolution. + location_kernel_size : int + Kernel size of attention convolution. + """ + + def __init__(self, + d_query: int, + d_key: int, + d_attention: int, + location_filters: int, + location_kernel_size: int): + super().__init__() + + self.query_layer = nn.Linear(d_query, d_attention, bias_attr=False) + self.key_layer = nn.Linear(d_key, d_attention, bias_attr=False) + self.value = nn.Linear(d_attention, 1, bias_attr=False) + + # Location Layer + self.location_conv = nn.Conv1D( + 2, + location_filters, + kernel_size=location_kernel_size, + padding=int((location_kernel_size - 1) / 2), + bias_attr=False, + data_format='NLC') + self.location_layer = nn.Linear( + location_filters, d_attention, bias_attr=False) + + def forward(self, + query, + processed_key, + value, + attention_weights_cat, + mask=None): + """Compute context vector and attention weights. + + Parameters + ----------- + query : Tensor [shape=(batch_size, d_query)] + The queries. + processed_key : Tensor [shape=(batch_size, time_steps_k, d_attention)] + The keys after linear layer. + value : Tensor [shape=(batch_size, time_steps_k, d_key)] + The values. + attention_weights_cat : Tensor [shape=(batch_size, time_step_k, 2)] + Attention weights concat. + mask : Tensor, optional + The mask. Shape should be (batch_size, times_steps_k, 1). + Defaults to None. + + Returns + ---------- + attention_context : Tensor [shape=(batch_size, d_attention)] + The context vector. + attention_weights : Tensor [shape=(batch_size, time_steps_k)] + The attention weights. + """ + + processed_query = self.query_layer(paddle.unsqueeze(query, axis=[1])) + processed_attention_weights = self.location_layer( + self.location_conv(attention_weights_cat)) + # (B, T_enc, 1) + alignment = self.value( + paddle.tanh(processed_attention_weights + processed_key + + processed_query)) + + if mask is not None: + alignment = alignment + (1.0 - mask) * -1e9 + + attention_weights = F.softmax(alignment, axis=1) + attention_context = paddle.matmul( + attention_weights, value, transpose_x=True) + + attention_weights = paddle.squeeze(attention_weights, axis=-1) + attention_context = paddle.squeeze(attention_context, axis=1) + + return attention_context, attention_weights diff --git a/parakeet/modules/audio.py b/parakeet/modules/audio.py new file mode 100644 index 00000000..926ce8f2 --- /dev/null +++ b/parakeet/modules/audio.py @@ -0,0 +1,229 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import librosa +import numpy as np +import paddle +from librosa.util import pad_center +from paddle import nn +from paddle.nn import functional as F +from scipy import signal + +__all__ = ["quantize", "dequantize", "STFT", "MelScale"] + + +def quantize(values, n_bands): + """Linearlly quantize a float Tensor in [-1, 1) to an interger Tensor in + [0, n_bands). + + Parameters + ----------- + values : Tensor [dtype: flaot32 or float64] + The floating point value. + + n_bands : int + The number of bands. The output integer Tensor's value is in the range + [0, n_bans). + + Returns + ---------- + Tensor [dtype: int 64] + The quantized tensor. + """ + quantized = paddle.cast((values + 1.0) / 2.0 * n_bands, "int64") + return quantized + + +def dequantize(quantized, n_bands, dtype=None): + """Linearlly dequantize an integer Tensor into a float Tensor in the range + [-1, 1). + + Parameters + ----------- + quantized : Tensor [dtype: int] + The quantized value in the range [0, n_bands). + + n_bands : int + Number of bands. The input integer Tensor's value is in the range + [0, n_bans). + + dtype : str, optional + Data type of the output. + + Returns + ----------- + Tensor + The dequantized tensor, dtype is specified by `dtype`. If `dtype` is + not specified, the default float data type is used. + """ + dtype = dtype or paddle.get_default_dtype() + value = (paddle.cast(quantized, dtype) + 0.5) * (2.0 / n_bands) - 1.0 + return value + + +class STFT(nn.Layer): + """A module for computing stft transformation in a differentiable way. + + Parameters + ------------ + n_fft : int + Number of samples in a frame. + hop_length : int + Number of samples shifted between adjacent frames. + win_length : int + Length of the window. + window : str, optional + Name of window function, see `scipy.signal.get_window` for more + details. Defaults to "hanning". + center : bool + If True, the signal y is padded so that frame D[:, t] is centered + at y[t * hop_length]. If False, then D[:, t] begins at y[t * hop_length]. + Defaults to True. + pad_mode : string or function + If center=True, this argument is passed to np.pad for padding the edges + of the signal y. By default (pad_mode="reflect"), y is padded on both + sides with its own reflection, mirrored around its first and last + sample respectively. If center=False, this argument is ignored. + + Notes + ----------- + It behaves like ``librosa.core.stft``. See ``librosa.core.stft`` for more + details. + + Given a audio which ``T`` samples, it the STFT transformation outputs a + spectrum with (C, frames) and complex dtype, where ``C = 1 + n_fft / 2`` + and ``frames = 1 + T // hop_lenghth``. + + Ony ``center`` and ``reflect`` padding is supported now. + + """ + + def __init__(self, + n_fft, + hop_length=None, + win_length=None, + window="hanning", + center=True, + pad_mode="reflect"): + super().__init__() + # By default, use the entire frame + if win_length is None: + win_length = n_fft + + # Set the default hop, if it's not already specified + if hop_length is None: + hop_length = int(win_length // 4) + + self.hop_length = hop_length + self.n_bin = 1 + n_fft // 2 + self.n_fft = n_fft + self.center = center + self.pad_mode = pad_mode + + # calculate window + window = signal.get_window(window, win_length, fftbins=True) + + # pad window to n_fft size + if n_fft != win_length: + window = pad_center(window, n_fft, mode="constant") + # lpad = (n_fft - win_length) // 2 + # rpad = n_fft - win_length - lpad + # window = np.pad(window, ((lpad, pad), ), 'constant') + + # calculate weights + # r = np.arange(0, n_fft) + # M = np.expand_dims(r, -1) * np.expand_dims(r, 0) + # w_real = np.reshape(window * + # np.cos(2 * np.pi * M / n_fft)[:self.n_bin], + # (self.n_bin, 1, self.n_fft)) + # w_imag = np.reshape(window * + # np.sin(-2 * np.pi * M / n_fft)[:self.n_bin], + # (self.n_bin, 1, self.n_fft)) + weight = np.fft.fft(np.eye(n_fft))[:self.n_bin] + w_real = weight.real + w_imag = weight.imag + w = np.concatenate([w_real, w_imag], axis=0) + w = w * window + w = np.expand_dims(w, 1) + weight = paddle.cast(paddle.to_tensor(w), paddle.get_default_dtype()) + self.register_buffer("weight", weight) + + def forward(self, x): + """Compute the stft transform. + Parameters + ------------ + x : Tensor [shape=(B, T)] + The input waveform. + Returns + ------------ + real : Tensor [shape=(B, C, frames)] + The real part of the spectrogram. + + imag : Tensor [shape=(B, C, frames)] + The image part of the spectrogram. + """ + x = paddle.unsqueeze(x, axis=1) + if self.center: + x = F.pad( + x, [self.n_fft // 2, self.n_fft // 2], + data_format='NCL', + mode=self.pad_mode) + + # to BCT, C=1 + out = F.conv1d(x, self.weight, stride=self.hop_length) + real, imag = paddle.chunk(out, 2, axis=1) # BCT + return real, imag + + def power(self, x): + """Compute the power spectrum. + Parameters + ------------ + x : Tensor [shape=(B, T)] + The input waveform. + Returns + ------------ + Tensor [shape=(B, C, T)] + The power spectrum. + """ + real, imag = self.forward(x) + power = real**2 + imag**2 + return power + + def magnitude(self, x): + """Compute the magnitude of the spectrum. + Parameters + ------------ + x : Tensor [shape=(B, T)] + The input waveform. + Returns + ------------ + Tensor [shape=(B, C, T)] + The magnitude of the spectrum. + """ + power = self.power(x) + magnitude = paddle.sqrt(power) # TODO(chenfeiyu): maybe clipping + return magnitude + + +class MelScale(nn.Layer): + def __init__(self, sr, n_fft, n_mels, fmin, fmax): + super().__init__() + mel_basis = librosa.filters.mel(sr, n_fft, n_mels, fmin, fmax) + # self.weight = paddle.to_tensor(mel_basis) + weight = paddle.to_tensor(mel_basis, dtype=paddle.get_default_dtype()) + self.register_buffer("weight", weight) + + def forward(self, spec): + # (n_mels, n_freq) * (batch_size, n_freq, n_frames) + mel = paddle.matmul(self.weight, spec) + return mel diff --git a/parakeet/modules/conv.py b/parakeet/modules/conv.py new file mode 100644 index 00000000..d9bd98df --- /dev/null +++ b/parakeet/modules/conv.py @@ -0,0 +1,260 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import paddle +from paddle import nn + +__all__ = [ + "Conv1dCell", + "Conv1dBatchNorm", +] + + +class Conv1dCell(nn.Conv1D): + """A subclass of Conv1D layer, which can be used in an autoregressive + decoder like an RNN cell. + + When used in autoregressive decoding, it performs causal temporal + convolution incrementally. At each time step, it takes a step input and + returns a step output. + + Notes + ------ + It is done by caching an internal buffer of length ``receptive_file - 1``. + when adding a step input, the buffer is shited by one step, the latest + input is added to be buffer and the oldest step is discarded. And it + returns a step output. For single step case, convolution is equivalent to a + linear transformation. + That it can be used as a cell depends on several restrictions: + 1. stride must be 1; + 2. padding must be a causal padding (recpetive_field - 1, 0). + Thus, these arguments are removed from the ``__init__`` method of this + class. + + Parameters + ---------- + in_channels: int + The feature size of the input. + out_channels: int + The feature size of the output. + kernel_size: int or Tuple[int] + The size of the kernel. + dilation: int or Tuple[int] + The dilation of the convolution, by default 1 + weight_attr: ParamAttr, Initializer, str or bool, optional + The parameter attribute of the convolution kernel, by default None. + bias_attr: ParamAttr, Initializer, str or bool, optional + The parameter attribute of the bias. If ``False``, this layer does not + have a bias, by default None. + + Examples + -------- + >>> cell = Conv1dCell(3, 4, kernel_size=5) + >>> inputs = [paddle.randn([4, 3]) for _ in range(16)] + >>> outputs = [] + >>> cell.eval() + >>> cell.start_sequence() + >>> for xt in inputs: + >>> outputs.append(cell.add_input(xt)) + >>> len(outputs)) + 16 + >>> outputs[0].shape + [4, 4] + """ + + def __init__(self, + in_channels, + out_channels, + kernel_size, + dilation=1, + weight_attr=None, + bias_attr=None): + _dilation = dilation[0] if isinstance(dilation, + (tuple, list)) else dilation + _kernel_size = kernel_size[0] if isinstance(kernel_size, ( + tuple, list)) else kernel_size + self._r = 1 + (_kernel_size - 1) * _dilation + super(Conv1dCell, self).__init__( + in_channels, + out_channels, + kernel_size, + padding=(self._r - 1, 0), + dilation=dilation, + weight_attr=weight_attr, + bias_attr=bias_attr, + data_format="NCL") + + @property + def receptive_field(self): + """The receptive field of the Conv1dCell. + """ + return self._r + + def start_sequence(self): + """Prepare the layer for a series of incremental forward. + + Warnings + --------- + This method should be called before a sequence of calls to + ``add_input``. + + Raises + ------ + Exception + If this method is called when the layer is in training mode. + """ + if self.training: + raise Exception("only use start_sequence in evaluation") + self._buffer = None + + # NOTE: call self's weight norm hook expliccitly since self.weight + # is visited directly in this method without calling self.__call__ + # method. If we do not trigger the weight norm hook, the weight + # may be outdated. e.g. after loading from a saved checkpoint + # see also: https://github.com/pytorch/pytorch/issues/47588 + for hook in self._forward_pre_hooks.values(): + hook(self, None) + self._reshaped_weight = paddle.reshape(self.weight, + (self._out_channels, -1)) + + def initialize_buffer(self, x_t): + """Initialize the buffer for the step input. + + Parameters + ---------- + x_t : Tensor [shape=(batch_size, in_channels)] + The step input. + """ + batch_size, _ = x_t.shape + self._buffer = paddle.zeros( + (batch_size, self._in_channels, self.receptive_field), + dtype=x_t.dtype) + + def update_buffer(self, x_t): + """Shift the buffer by one step. + + Parameters + ---------- + x_t : Tensor [shape=(batch_size, in_channels)] + The step input. + """ + self._buffer = paddle.concat( + [self._buffer[:, :, 1:], paddle.unsqueeze(x_t, -1)], -1) + + def add_input(self, x_t): + """Add step input and compute step output. + + Parameters + ----------- + x_t : Tensor [shape=(batch_size, in_channels)] + The step input. + + Returns + ------- + y_t :Tensor [shape=(batch_size, out_channels)] + The step output. + """ + batch_size = x_t.shape[0] + if self.receptive_field > 1: + if self._buffer is None: + self.initialize_buffer(x_t) + + # update buffer + self.update_buffer(x_t) + if self._dilation[0] > 1: + input = self._buffer[:, :, ::self._dilation[0]] + else: + input = self._buffer + input = paddle.reshape(input, (batch_size, -1)) + else: + input = x_t + y_t = paddle.matmul(input, self._reshaped_weight, transpose_y=True) + y_t = y_t + self.bias + return y_t + + +class Conv1dBatchNorm(nn.Layer): + """A Conv1D Layer followed by a BatchNorm1D. + + Parameters + ---------- + in_channels : int + The feature size of the input. + out_channels : int + The feature size of the output. + kernel_size : int + The size of the convolution kernel. + stride : int, optional + The stride of the convolution, by default 1. + padding : int, str or Tuple[int], optional + The padding of the convolution. + If int, a symmetrical padding is applied before convolution; + If str, it should be "same" or "valid"; + If Tuple[int], its length should be 2, meaning + ``(pad_before, pad_after)``, by default 0. + weight_attr : ParamAttr, Initializer, str or bool, optional + The parameter attribute of the convolution kernel, by default None. + bias_attr : ParamAttr, Initializer, str or bool, optional + The parameter attribute of the bias of the convolution, by default + None. + data_format : str ["NCL" or "NLC"], optional + The data layout of the input, by default "NCL" + momentum : float, optional + The momentum of the BatchNorm1D layer, by default 0.9 + epsilon : [type], optional + The epsilon of the BatchNorm1D layer, by default 1e-05 + """ + + def __init__(self, + in_channels, + out_channels, + kernel_size, + stride=1, + padding=0, + weight_attr=None, + bias_attr=None, + data_format="NCL", + momentum=0.9, + epsilon=1e-05): + super(Conv1dBatchNorm, self).__init__() + self.conv = nn.Conv1D( + in_channels, + out_channels, + kernel_size, + stride, + padding=padding, + weight_attr=weight_attr, + bias_attr=bias_attr, + data_format=data_format) + self.bn = nn.BatchNorm1D( + out_channels, + momentum=momentum, + epsilon=epsilon, + data_format=data_format) + + def forward(self, x): + """Forward pass of the Conv1dBatchNorm layer. + + Parameters + ---------- + x : Tensor [shape=(B, C_in, T_in) or (B, T_in, C_in)] + The input tensor. Its data layout depends on ``data_format``. + + Returns + ------- + Tensor [shape=(B, C_out, T_out) or (B, T_out, C_out)] + The output tensor. + """ + x = self.conv(x) + x = self.bn(x) + return x diff --git a/parakeet/modules/expansion.py b/parakeet/modules/expansion.py new file mode 100644 index 00000000..e9d4b6fe --- /dev/null +++ b/parakeet/modules/expansion.py @@ -0,0 +1,37 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import numpy as np +import paddle +from paddle import Tensor + + +def expand(encodings: Tensor, durations: Tensor) -> Tensor: + """ + encodings: (B, T, C) + durations: (B, T) + """ + batch_size, t_enc = durations.shape + durations = durations.numpy() + slens = np.sum(durations, -1) + t_dec = np.max(slens) + M = np.zeros([batch_size, t_dec, t_enc]) + for i in range(batch_size): + k = 0 + for j in range(t_enc): + d = durations[i, j] + M[i, k:k + d, j] = 1 + k += d + M = paddle.to_tensor(M, dtype=encodings.dtype) + encodings = paddle.matmul(M, encodings) + return encodings diff --git a/parakeet/modules/fastspeech2_predictor/__init__.py b/parakeet/modules/fastspeech2_predictor/__init__.py new file mode 100644 index 00000000..185a92b8 --- /dev/null +++ b/parakeet/modules/fastspeech2_predictor/__init__.py @@ -0,0 +1,13 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/parakeet/modules/fastspeech2_predictor/duration_predictor.py b/parakeet/modules/fastspeech2_predictor/duration_predictor.py new file mode 100644 index 00000000..d0f5262c --- /dev/null +++ b/parakeet/modules/fastspeech2_predictor/duration_predictor.py @@ -0,0 +1,184 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Duration predictor related modules.""" +import paddle +from paddle import nn + +from parakeet.modules.layer_norm import LayerNorm +from parakeet.modules.masked_fill import masked_fill + + +class DurationPredictor(nn.Layer): + """Duration predictor module. + + This is a module of duration predictor described + in `FastSpeech: Fast, Robust and Controllable Text to Speech`_. + The duration predictor predicts a duration of each frame in log domain + from the hidden embeddings of encoder. + + .. _`FastSpeech: Fast, Robust and Controllable Text to Speech`: + https://arxiv.org/pdf/1905.09263.pdf + + Note + ---------- + The calculation domain of outputs is different + between in `forward` and in `inference`. In `forward`, + the outputs are calculated in log domain but in `inference`, + those are calculated in linear domain. + + """ + + def __init__(self, + idim, + n_layers=2, + n_chans=384, + kernel_size=3, + dropout_rate=0.1, + offset=1.0): + """Initilize duration predictor module. + + Parameters + ---------- + idim : int + Input dimension. + n_layers : int, optional + Number of convolutional layers. + n_chans : int, optional + Number of channels of convolutional layers. + kernel_size : int, optional + Kernel size of convolutional layers. + dropout_rate : float, optional + Dropout rate. + offset : float, optional + Offset value to avoid nan in log domain. + + """ + super(DurationPredictor, self).__init__() + self.offset = offset + self.conv = nn.LayerList() + for idx in range(n_layers): + in_chans = idim if idx == 0 else n_chans + self.conv.append( + nn.Sequential( + nn.Conv1D( + in_chans, + n_chans, + kernel_size, + stride=1, + padding=(kernel_size - 1) // 2, ), + nn.ReLU(), + LayerNorm(n_chans, dim=1), + nn.Dropout(dropout_rate), )) + self.linear = nn.Linear(n_chans, 1, bias_attr=True) + + def _forward(self, xs, x_masks=None, is_inference=False): + # (B, idim, Tmax) + xs = xs.transpose([0, 2, 1]) + # (B, C, Tmax) + for f in self.conv: + xs = f(xs) + + # NOTE: calculate in log domain + # (B, Tmax) + xs = self.linear(xs.transpose([0, 2, 1])).squeeze(-1) + + if is_inference: + # NOTE: calculate in linear domain + xs = paddle.clip(paddle.round(xs.exp() - self.offset), min=0) + + if x_masks is not None: + xs = masked_fill(xs, x_masks, 0.0) + + return xs + + def forward(self, xs, x_masks=None): + """Calculate forward propagation. + + Parameters + ---------- + xs : Tensor + Batch of input sequences (B, Tmax, idim). + x_masks : ByteTensor, optional + Batch of masks indicating padded part (B, Tmax). + + Returns + ---------- + Tensor + Batch of predicted durations in log domain (B, Tmax). + """ + return self._forward(xs, x_masks, False) + + def inference(self, xs, x_masks=None): + """Inference duration. + + Parameters + ---------- + xs : Tensor + Batch of input sequences (B, Tmax, idim). + x_masks : Tensor(bool), optional + Batch of masks indicating padded part (B, Tmax). + + Returns + ---------- + Tensor + Batch of predicted durations in linear domain int64 (B, Tmax). + """ + return self._forward(xs, x_masks, True) + + +class DurationPredictorLoss(nn.Layer): + """Loss function module for duration predictor. + + The loss value is Calculated in log domain to make it Gaussian. + + """ + + def __init__(self, offset=1.0, reduction="mean"): + """Initilize duration predictor loss module. + + Parameters + ---------- + offset : float, optional + Offset value to avoid nan in log domain. + reduction : str + Reduction type in loss calculation. + """ + super(DurationPredictorLoss, self).__init__() + self.criterion = nn.MSELoss(reduction=reduction) + self.offset = offset + + def forward(self, outputs, targets): + """Calculate forward propagation. + + Parameters + ---------- + outputs : Tensor + Batch of prediction durations in log domain (B, T) + targets : Tensor + Batch of groundtruth durations in linear domain (B, T) + + Returns + ---------- + Tensor + Mean squared error loss value. + + Note + ---------- + `outputs` is in log domain but `targets` is in linear domain. + """ + # NOTE: outputs is in log domain while targets in linear + targets = paddle.log(targets.cast(dtype='float32') + self.offset) + loss = self.criterion(outputs, targets) + + return loss diff --git a/parakeet/modules/fastspeech2_predictor/length_regulator.py b/parakeet/modules/fastspeech2_predictor/length_regulator.py new file mode 100644 index 00000000..e5195e53 --- /dev/null +++ b/parakeet/modules/fastspeech2_predictor/length_regulator.py @@ -0,0 +1,89 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Length regulator related modules.""" +import numpy as np +import paddle +from paddle import nn + + +class LengthRegulator(nn.Layer): + """Length regulator module for feed-forward Transformer. + + This is a module of length regulator described in + `FastSpeech: Fast, Robust and Controllable Text to Speech`_. + The length regulator expands char or + phoneme-level embedding features to frame-level by repeating each + feature based on the corresponding predicted durations. + + .. _`FastSpeech: Fast, Robust and Controllable Text to Speech`: + https://arxiv.org/pdf/1905.09263.pdf + + """ + + def __init__(self, pad_value=0.0): + """Initilize length regulator module. + + Parameters + ---------- + pad_value : float, optional + Value used for padding. + + """ + super().__init__() + self.pad_value = pad_value + + def expand(self, encodings: paddle.Tensor, + durations: paddle.Tensor) -> paddle.Tensor: + """ + encodings: (B, T, C) + durations: (B, T) + """ + batch_size, t_enc = durations.shape + durations = durations.numpy() + slens = np.sum(durations, -1) + t_dec = np.max(slens) + M = np.zeros([batch_size, t_dec, t_enc]) + for i in range(batch_size): + k = 0 + for j in range(t_enc): + d = durations[i, j] + if d >= 1: + M[i, k:k + d, j] = 1 + k += d + M = paddle.to_tensor(M, dtype=encodings.dtype) + encodings = paddle.matmul(M, encodings) + return encodings + + def forward(self, xs, ds, alpha=1.0): + """Calculate forward propagation. + + Parameters + ---------- + xs : Tensor + Batch of sequences of char or phoneme embeddings (B, Tmax, D). + ds : LongTensor + Batch of durations of each frame (B, T). + alpha : float, optional + Alpha value to control speed of speech. + + Returns + ---------- + Tensor + replicated input tensor based on durations (B, T*, D). + """ + if alpha != 1.0: + assert alpha > 0 + ds = paddle.round(ds.cast(dtype=paddle.float32) * alpha) + ds = ds.cast(dtype=paddle.int64) + return self.expand(xs, ds) diff --git a/parakeet/modules/fastspeech2_predictor/variance_predictor.py b/parakeet/modules/fastspeech2_predictor/variance_predictor.py new file mode 100644 index 00000000..0a980dd5 --- /dev/null +++ b/parakeet/modules/fastspeech2_predictor/variance_predictor.py @@ -0,0 +1,104 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Variance predictor related modules.""" +import paddle +from paddle import nn +from typeguard import check_argument_types + +from parakeet.modules.layer_norm import LayerNorm +from parakeet.modules.masked_fill import masked_fill + + +class VariancePredictor(nn.Layer): + """Variance predictor module. + + This is a module of variacne predictor described in `FastSpeech 2: + Fast and High-Quality End-to-End Text to Speech`_. + + .. _`FastSpeech 2: Fast and High-Quality End-to-End Text to Speech`: + https://arxiv.org/abs/2006.04558 + + """ + + def __init__( + self, + idim: int, + n_layers: int=2, + n_chans: int=384, + kernel_size: int=3, + bias: bool=True, + dropout_rate: float=0.5, ): + """Initilize duration predictor module. + + Parameters + ---------- + idim : int + Input dimension. + n_layers : int, optional + Number of convolutional layers. + n_chans : int, optional + Number of channels of convolutional layers. + kernel_size : int, optional + Kernel size of convolutional layers. + dropout_rate : float, optional + Dropout rate. + """ + assert check_argument_types() + super().__init__() + self.conv = nn.LayerList() + for idx in range(n_layers): + in_chans = idim if idx == 0 else n_chans + self.conv.append( + nn.Sequential( + nn.Conv1D( + in_chans, + n_chans, + kernel_size, + stride=1, + padding=(kernel_size - 1) // 2, + bias_attr=True, ), + nn.ReLU(), + LayerNorm(n_chans, dim=1), + nn.Dropout(dropout_rate), )) + + self.linear = nn.Linear(n_chans, 1, bias_attr=True) + + def forward(self, xs: paddle.Tensor, + x_masks: paddle.Tensor=None) -> paddle.Tensor: + """Calculate forward propagation. + + Parameters + ---------- + xs : Tensor + Batch of input sequences (B, Tmax, idim). + x_masks : Tensor(bool), optional + Batch of masks indicating padded part (B, Tmax, 1). + + Returns + ---------- + Tensor + Batch of predicted sequences (B, Tmax, 1). + """ + # (B, idim, Tmax) + xs = xs.transpose([0, 2, 1]) + # (B, C, Tmax) + for f in self.conv: + # (B, C, Tmax) + xs = f(xs) + # (B, Tmax, 1) + xs = self.linear(xs.transpose([0, 2, 1])) + + if x_masks is not None: + xs = masked_fill(xs, x_masks, 0.0) + return xs diff --git a/parakeet/modules/fastspeech2_transformer/__init__.py b/parakeet/modules/fastspeech2_transformer/__init__.py new file mode 100644 index 00000000..abf198b9 --- /dev/null +++ b/parakeet/modules/fastspeech2_transformer/__init__.py @@ -0,0 +1,13 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/parakeet/modules/fastspeech2_transformer/attention.py b/parakeet/modules/fastspeech2_transformer/attention.py new file mode 100644 index 00000000..ae941a79 --- /dev/null +++ b/parakeet/modules/fastspeech2_transformer/attention.py @@ -0,0 +1,156 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Multi-Head Attention layer definition.""" +import math + +import numpy +import paddle +from paddle import nn + +from parakeet.modules.masked_fill import masked_fill + + +class MultiHeadedAttention(nn.Layer): + """Multi-Head Attention layer. + + Parameters + ---------- + n_head : int + The number of heads. + n_feat : int + The number of features. + dropout_rate : float + Dropout rate. + """ + + def __init__(self, n_head, n_feat, dropout_rate): + """Construct an MultiHeadedAttention object.""" + super(MultiHeadedAttention, self).__init__() + assert n_feat % n_head == 0 + # We assume d_v always equals d_k + self.d_k = n_feat // n_head + self.h = n_head + self.linear_q = nn.Linear(n_feat, n_feat, bias_attr=True) + self.linear_k = nn.Linear(n_feat, n_feat, bias_attr=True) + self.linear_v = nn.Linear(n_feat, n_feat, bias_attr=True) + self.linear_out = nn.Linear(n_feat, n_feat, bias_attr=True) + self.attn = None + self.dropout = nn.Dropout(p=dropout_rate) + + def forward_qkv(self, query, key, value): + """Transform query, key and value. + + Parameters + ---------- + query : paddle.Tensor + query tensor (#batch, time1, size). + key : paddle.Tensor + Key tensor (#batch, time2, size). + value : paddle.Tensor + Value tensor (#batch, time2, size). + + Returns + ---------- + paddle.Tensor + Transformed query tensor (#batch, n_head, time1, d_k). + paddle.Tensor + Transformed key tensor (#batch, n_head, time2, d_k). + paddle.Tensor + Transformed value tensor (#batch, n_head, time2, d_k). + """ + n_batch = query.shape[0] + + q = paddle.reshape( + self.linear_q(query), [n_batch, -1, self.h, self.d_k]) + k = paddle.reshape(self.linear_k(key), [n_batch, -1, self.h, self.d_k]) + v = paddle.reshape( + self.linear_v(value), [n_batch, -1, self.h, self.d_k]) + + # (batch, head, time1, d_k) + q = q.transpose((0, 2, 1, 3)) + # (batch, head, time2, d_k) + k = k.transpose((0, 2, 1, 3)) + # (batch, head, time2, d_k) + v = v.transpose((0, 2, 1, 3)) + return q, k, v + + def forward_attention(self, value, scores, mask=None): + """Compute attention context vector. + + Parameters + ---------- + value : paddle.Tensor + Transformed value (#batch, n_head, time2, d_k). + scores : paddle.Tensor + Attention score (#batch, n_head, time1, time2). + mask : paddle.Tensor + Mask (#batch, 1, time2) or (#batch, time1, time2). + + Returns + ---------- + paddle.Tensor: + Transformed value (#batch, time1, d_model) + weighted by the attention score (#batch, time1, time2). + """ + n_batch = value.shape[0] + softmax = paddle.nn.Softmax(axis=-1) + if mask is not None: + + mask = mask.unsqueeze(1) + mask = paddle.logical_not(mask) + min_value = float( + numpy.finfo( + paddle.to_tensor(0, dtype=scores.dtype).numpy().dtype).min) + + scores = masked_fill(scores, mask, min_value) + # (batch, head, time1, time2) + self.attn = softmax(scores) + self.attn = masked_fill(self.attn, mask, 0.0) + else: + # (batch, head, time1, time2) + self.attn = softmax(scores) + # (batch, head, time1, time2) + p_attn = self.dropout(self.attn) + # (batch, head, time1, time2) * (batch, head, time2, d_k) -> # (batch, head, time1, d_k) + x = paddle.matmul(p_attn, value) + # (batch, time1, d_model) + x = (paddle.reshape( + x.transpose((0, 2, 1, 3)), (n_batch, -1, self.h * self.d_k))) + + return self.linear_out(x) # (batch, time1, d_model) + + def forward(self, query, key, value, mask=None): + """Compute scaled dot product attention. + + Parameters + ---------- + query : paddle.Tensor + Query tensor (#batch, time1, size). + key : paddle.Tensor + Key tensor (#batch, time2, size). + value : paddle.Tensor + Value tensor (#batch, time2, size). + mask : paddle.Tensor + Mask tensor (#batch, 1, time2) or (#batch, time1, time2). + + Returns + ---------- + paddle.Tensor + Output tensor (#batch, time1, d_model). + """ + q, k, v = self.forward_qkv(query, key, value) + scores = paddle.matmul(q, k.transpose( + (0, 1, 3, 2))) / math.sqrt(self.d_k) + + return self.forward_attention(v, scores, mask) diff --git a/parakeet/modules/fastspeech2_transformer/decoder.py b/parakeet/modules/fastspeech2_transformer/decoder.py new file mode 100644 index 00000000..a41a87c8 --- /dev/null +++ b/parakeet/modules/fastspeech2_transformer/decoder.py @@ -0,0 +1,293 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# 暂时删除了 dyminic conv +"""Decoder definition.""" +import logging +from typing import Any +from typing import List +from typing import Tuple + +import paddle +import paddle.nn.functional as F +from paddle import nn + +from parakeet.modules.fastspeech2_transformer.attention import MultiHeadedAttention +from parakeet.modules.fastspeech2_transformer.decoder_layer import DecoderLayer +from parakeet.modules.fastspeech2_transformer.embedding import PositionalEncoding +from parakeet.modules.fastspeech2_transformer.lightconv import LightweightConvolution +from parakeet.modules.fastspeech2_transformer.mask import subsequent_mask +from parakeet.modules.fastspeech2_transformer.positionwise_feed_forward import PositionwiseFeedForward +from parakeet.modules.fastspeech2_transformer.repeat import repeat +from parakeet.modules.layer_norm import LayerNorm + + +class Decoder(nn.Layer): + """Transfomer decoder module. + + Parameters + ---------- + odim : int + Output diminsion. + self_attention_layer_type : str + Self-attention layer type. + attention_dim : int + Dimention of attention. + attention_heads : int + The number of heads of multi head attention. + conv_wshare : int + The number of kernel of convolution. Only used in + self_attention_layer_type == "lightconv*" or "dynamiconv*". + conv_kernel_length : Union[int, str]) + Kernel size str of convolution + (e.g. 71_71_71_71_71_71). Only used in self_attention_layer_type == "lightconv*" or "dynamiconv*". + conv_usebias : bool + Whether to use bias in convolution. Only used in + self_attention_layer_type == "lightconv*" or "dynamiconv*". + linear_units : int + The number of units of position-wise feed forward. + num_blocks : int + The number of decoder blocks. + dropout_rate : float + Dropout rate. + positional_dropout_rate : float + Dropout rate after adding positional encoding. + self_attention_dropout_rate : float + Dropout rate in self-attention. + src_attention_dropout_rate : float + Dropout rate in source-attention. + input_layer : (Union[str, paddle.nn.Layer]) + Input layer type. + use_output_layer : bool + Whether to use output layer. + pos_enc_class : paddle.nn.Layer + Positional encoding module class. + `PositionalEncoding `or `ScaledPositionalEncoding` + normalize_before : bool + Whether to use layer_norm before the first block. + concat_after : bool + Whether to concat attention layer's input and output. + if True, additional linear will be applied. + i.e. x -> x + linear(concat(x, att(x))) + if False, no additional linear will be applied. i.e. x -> x + att(x) + + """ + + def __init__( + self, + odim, + selfattention_layer_type="selfattn", + attention_dim=256, + attention_heads=4, + conv_wshare=4, + conv_kernel_length=11, + conv_usebias=False, + linear_units=2048, + num_blocks=6, + dropout_rate=0.1, + positional_dropout_rate=0.1, + self_attention_dropout_rate=0.0, + src_attention_dropout_rate=0.0, + input_layer="embed", + use_output_layer=True, + pos_enc_class=PositionalEncoding, + normalize_before=True, + concat_after=False, ): + """Construct an Decoder object.""" + nn.Layer.__init__(self) + if input_layer == "embed": + self.embed = nn.Sequential( + nn.Embedding(odim, attention_dim), + pos_enc_class(attention_dim, positional_dropout_rate), ) + elif input_layer == "linear": + self.embed = nn.Sequential( + nn.Linear(odim, attention_dim), + nn.LayerNorm(attention_dim), + nn.Dropout(dropout_rate), + nn.ReLU(), + pos_enc_class(attention_dim, positional_dropout_rate), ) + elif isinstance(input_layer, nn.Layer): + self.embed = nn.Sequential( + input_layer, + pos_enc_class(attention_dim, positional_dropout_rate)) + else: + raise NotImplementedError( + "only `embed` or paddle.nn.Layer is supported.") + self.normalize_before = normalize_before + + # self-attention module definition + if selfattention_layer_type == "selfattn": + logging.info("decoder self-attention layer type = self-attention") + decoder_selfattn_layer = MultiHeadedAttention + decoder_selfattn_layer_args = [ + (attention_heads, attention_dim, self_attention_dropout_rate, ) + ] * num_blocks + elif selfattention_layer_type == "lightconv": + logging.info( + "decoder self-attention layer type = lightweight convolution") + decoder_selfattn_layer = LightweightConvolution + decoder_selfattn_layer_args = [( + conv_wshare, attention_dim, self_attention_dropout_rate, + int(conv_kernel_length.split("_")[lnum]), True, conv_usebias, ) + for lnum in range(num_blocks)] + + self.decoders = repeat( + num_blocks, + lambda lnum: DecoderLayer( + attention_dim, + decoder_selfattn_layer(*decoder_selfattn_layer_args[lnum]), + MultiHeadedAttention(attention_heads, attention_dim, src_attention_dropout_rate), + PositionwiseFeedForward(attention_dim, linear_units, dropout_rate), + dropout_rate, + normalize_before, + concat_after, ), ) + self.selfattention_layer_type = selfattention_layer_type + if self.normalize_before: + self.after_norm = LayerNorm(attention_dim) + if use_output_layer: + self.output_layer = nn.Linear(attention_dim, odim) + else: + self.output_layer = None + + def forward(self, tgt, tgt_mask, memory, memory_mask): + """Forward decoder. + + Parameters + ---------- + tgt : paddle.Tensor + Input token ids, int64 (#batch, maxlen_out) if input_layer == "embed". + In the other case, input tensor (#batch, maxlen_out, odim). + tgt_mask : paddle.Tensor + Input token mask (#batch, maxlen_out). + memory : paddle.Tensor + Encoded memory, float32 (#batch, maxlen_in, feat). + memory_mask : paddle.Tensor + Encoded memory mask (#batch, maxlen_in). + + Returns + ---------- + paddle.Tensor + Decoded token score before softmax (#batch, maxlen_out, odim) + if use_output_layer is True. In the other case,final block outputs + (#batch, maxlen_out, attention_dim). + paddle.Tensor + Score mask before softmax (#batch, maxlen_out). + + """ + x = self.embed(tgt) + x, tgt_mask, memory, memory_mask = self.decoders(x, tgt_mask, memory, + memory_mask) + if self.normalize_before: + x = self.after_norm(x) + if self.output_layer is not None: + x = self.output_layer(x) + return x, tgt_mask + + def forward_one_step(self, tgt, tgt_mask, memory, cache=None): + """Forward one step. + + Parameters + ---------- + tgt : paddle.Tensor + Input token ids, int64 (#batch, maxlen_out). + tgt_mask : paddle.Tensor + Input token mask (#batch, maxlen_out). + memory : paddle.Tensor + Encoded memory, float32 (#batch, maxlen_in, feat). + cache : (List[paddle.Tensor]) + List of cached tensors. + Each tensor shape should be (#batch, maxlen_out - 1, size). + Returns + ---------- + paddle.Tensor + Output tensor (batch, maxlen_out, odim). + List[paddle.Tensor] + List of cache tensors of each decoder layer. + + """ + x = self.embed(tgt) + if cache is None: + cache = [None] * len(self.decoders) + new_cache = [] + for c, decoder in zip(cache, self.decoders): + x, tgt_mask, memory, memory_mask = decoder( + x, tgt_mask, memory, None, cache=c) + new_cache.append(x) + + if self.normalize_before: + y = self.after_norm(x[:, -1]) + else: + y = x[:, -1] + if self.output_layer is not None: + y = F.log_softmax(self.output_layer(y), axis=-1) + + return y, new_cache + + # beam search API (see ScorerInterface) + def score(self, ys, state, x): + """Score.""" + ys_mask = subsequent_mask(len(ys)).unsqueeze(0) + if self.selfattention_layer_type != "selfattn": + # TODO(karita): implement cache + logging.warning( + f"{self.selfattention_layer_type} does not support cached decoding." + ) + state = None + logp, state = self.forward_one_step( + ys.unsqueeze(0), ys_mask, x.unsqueeze(0), cache=state) + return logp.squeeze(0), state + + # batch beam search API (see BatchScorerInterface) + def batch_score(self, + ys: paddle.Tensor, + states: List[Any], + xs: paddle.Tensor) -> Tuple[paddle.Tensor, List[Any]]: + """Score new token batch (required). + + Parameters + ---------- + ys : paddle.Tensor + paddle.int64 prefix tokens (n_batch, ylen). + states : List[Any] + Scorer states for prefix tokens. + xs : paddle.Tensor + The encoder feature that generates ys (n_batch, xlen, n_feat). + + Returns + ---------- + tuple[paddle.Tensor, List[Any]] + Tuple ofbatchfied scores for next token with shape of `(n_batch, n_vocab)` + and next state list for ys. + + """ + # merge states + n_batch = len(ys) + n_layers = len(self.decoders) + if states[0] is None: + batch_state = None + else: + # transpose state of [batch, layer] into [layer, batch] + batch_state = [ + paddle.stack([states[b][i] for b in range(n_batch)]) + for i in range(n_layers) + ] + + # batch decoding + ys_mask = subsequent_mask(ys.shape[-1]).unsqueeze(0) + logp, states = self.forward_one_step(ys, ys_mask, xs, cache=batch_state) + + # transpose state of [layer, batch] into [batch, layer] + state_list = [[states[i][b] for i in range(n_layers)] + for b in range(n_batch)] + return logp, state_list diff --git a/parakeet/modules/fastspeech2_transformer/decoder_layer.py b/parakeet/modules/fastspeech2_transformer/decoder_layer.py new file mode 100644 index 00000000..53328866 --- /dev/null +++ b/parakeet/modules/fastspeech2_transformer/decoder_layer.py @@ -0,0 +1,158 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Decoder self-attention layer definition.""" + +import paddle +from paddle import nn +from parakeet.modules.layer_norm import LayerNorm + + +class DecoderLayer(nn.Layer): + """Single decoder layer module. + + Parameters + ---------- + size : int + Input dimension. + self_attn : paddle.nn.Layer + Self-attention module instance. + `MultiHeadedAttention` instance can be used as the argument. + src_attn : paddle.nn.Layer + Self-attention module instance. + `MultiHeadedAttention` instance can be used as the argument. + feed_forward : paddle.nn.Layer + Feed-forward module instance. + `PositionwiseFeedForward`, `MultiLayeredConv1d`, or `Conv1dLinear` instance can be used as the argument. + dropout_rate : float + Dropout rate. + normalize_before : bool + Whether to use layer_norm before the first block. + concat_after : bool + Whether to concat attention layer's input and output. + if True, additional linear will be applied. + i.e. x -> x + linear(concat(x, att(x))) + if False, no additional linear will be applied. i.e. x -> x + att(x) + + """ + + def __init__( + self, + size, + self_attn, + src_attn, + feed_forward, + dropout_rate, + normalize_before=True, + concat_after=False, ): + """Construct an DecoderLayer object.""" + super().__init__() + self.size = size + self.self_attn = self_attn + self.src_attn = src_attn + self.feed_forward = feed_forward + self.norm1 = LayerNorm(size) + self.norm2 = LayerNorm(size) + self.norm3 = LayerNorm(size) + self.dropout = nn.Dropout(dropout_rate) + self.normalize_before = normalize_before + self.concat_after = concat_after + if self.concat_after: + self.concat_linear1 = nn.Linear(size + size, size) + self.concat_linear2 = nn.Linear(size + size, size) + + def forward(self, tgt, tgt_mask, memory, memory_mask, cache=None): + """Compute decoded features. + + Parameters + ---------- + tgt : paddle.Tensor + Input tensor (#batch, maxlen_out, size). + tgt_mask : paddle.Tensor + Mask for input tensor (#batch, maxlen_out). + memory : paddle.Tensor + Encoded memory, float32 (#batch, maxlen_in, size). + memory_mask : paddle.Tensor + Encoded memory mask (#batch, maxlen_in). + cache : List[paddle.Tensor] + List of cached tensors. + Each tensor shape should be (#batch, maxlen_out - 1, size). + + Returns + ---------- + paddle.Tensor + Output tensor(#batch, maxlen_out, size). + paddle.Tensor + Mask for output tensor (#batch, maxlen_out). + paddle.Tensor + Encoded memory (#batch, maxlen_in, size). + paddle.Tensor + Encoded memory mask (#batch, maxlen_in). + + """ + residual = tgt + if self.normalize_before: + tgt = self.norm1(tgt) + + if cache is None: + tgt_q = tgt + tgt_q_mask = tgt_mask + else: + # compute only the last frame query keeping dim: max_time_out -> 1 + assert cache.shape == [ + tgt.shape[0], + tgt.shape[1] - 1, + self.size, + ], f"{cache.shape} == {(tgt.shape[0], tgt.shape[1] - 1, self.size)}" + tgt_q = tgt[:, -1:, :] + residual = residual[:, -1:, :] + tgt_q_mask = None + if tgt_mask is not None: + tgt_mask = paddle.cast(tgt_mask, dtype="int64") + tgt_q_mask = tgt_mask[:, -1:, :] + tgt_q_mask = paddle.cast(tgt_q_mask, dtype="bool") + + if self.concat_after: + tgt_concat = paddle.concat( + (tgt_q, self.self_attn(tgt_q, tgt, tgt, tgt_q_mask)), axis=-1) + x = residual + self.concat_linear1(tgt_concat) + else: + x = residual + self.dropout( + self.self_attn(tgt_q, tgt, tgt, tgt_q_mask)) + if not self.normalize_before: + x = self.norm1(x) + + residual = x + if self.normalize_before: + x = self.norm2(x) + if self.concat_after: + x_concat = paddle.concat( + (x, self.src_attn(x, memory, memory, memory_mask)), axis=-1) + x = residual + self.concat_linear2(x_concat) + else: + x = residual + self.dropout( + self.src_attn(x, memory, memory, memory_mask)) + if not self.normalize_before: + x = self.norm2(x) + + residual = x + if self.normalize_before: + x = self.norm3(x) + x = residual + self.dropout(self.feed_forward(x)) + if not self.normalize_before: + x = self.norm3(x) + + if cache is not None: + x = paddle.concat([cache, x], axis=1) + + return x, tgt_mask, memory, memory_mask diff --git a/parakeet/modules/fastspeech2_transformer/embedding.py b/parakeet/modules/fastspeech2_transformer/embedding.py new file mode 100644 index 00000000..6c1c7245 --- /dev/null +++ b/parakeet/modules/fastspeech2_transformer/embedding.py @@ -0,0 +1,126 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Positional Encoding Module.""" +import math + +import paddle +from paddle import nn + + +class PositionalEncoding(nn.Layer): + """Positional encoding. + + Parameters + ---------- + d_model : int + Embedding dimension. + dropout_rate : float + Dropout rate. + max_len : int + Maximum input length. + reverse : bool + Whether to reverse the input position. + """ + + def __init__(self, d_model, dropout_rate, max_len=5000, reverse=False): + """Construct an PositionalEncoding object.""" + super(PositionalEncoding, self).__init__() + self.d_model = d_model + self.reverse = reverse + self.xscale = math.sqrt(self.d_model) + self.dropout = nn.Dropout(p=dropout_rate) + self.pe = None + self.extend_pe(paddle.expand(paddle.to_tensor(0.0), (1, max_len))) + + def extend_pe(self, x): + """Reset the positional encodings.""" + + pe = paddle.zeros([x.shape[1], self.d_model]) + if self.reverse: + position = paddle.arange( + x.shape[1] - 1, -1, -1.0, dtype=paddle.float32).unsqueeze(1) + else: + position = paddle.arange( + 0, x.shape[1], dtype=paddle.float32).unsqueeze(1) + div_term = paddle.exp( + paddle.arange(0, self.d_model, 2, dtype=paddle.float32) * + -(math.log(10000.0) / self.d_model)) + pe[:, 0::2] = paddle.sin(position * div_term) + pe[:, 1::2] = paddle.cos(position * div_term) + pe = pe.unsqueeze(0) + self.pe = pe + + def forward(self, x: paddle.Tensor): + """Add positional encoding. + + Parameters + ---------- + x : paddle.Tensor + Input tensor (batch, time, `*`). + + Returns + ---------- + paddle.Tensor + Encoded tensor (batch, time, `*`). + """ + self.extend_pe(x) + x = x * self.xscale + self.pe[:, :x.shape[1]] + return self.dropout(x) + + +class ScaledPositionalEncoding(PositionalEncoding): + """Scaled positional encoding module. + + See Sec. 3.2 https://arxiv.org/abs/1809.08895 + + Parameters + ---------- + d_model : int + Embedding dimension. + dropout_rate : float + Dropout rate. + max_len : int + Maximum input length. + """ + + def __init__(self, d_model, dropout_rate, max_len=5000): + """Initialize class.""" + super().__init__( + d_model=d_model, dropout_rate=dropout_rate, max_len=max_len) + x = paddle.ones([1], dtype="float32") + self.alpha = paddle.create_parameter( + shape=x.shape, + dtype=str(x.numpy().dtype), + default_initializer=paddle.nn.initializer.Assign(x)) + + def reset_parameters(self): + """Reset parameters.""" + self.alpha = paddle.to_tensor(1.0) + + def forward(self, x): + """Add positional encoding. + + Parameters + ---------- + x : paddle.Tensor + Input tensor (batch, time, `*`). + + Returns + ---------- + paddle.Tensor + Encoded tensor (batch, time, `*`). + """ + self.extend_pe(x) + x = x + self.alpha * self.pe[:, :x.shape[1]] + return self.dropout(x) diff --git a/parakeet/modules/fastspeech2_transformer/encoder.py b/parakeet/modules/fastspeech2_transformer/encoder.py new file mode 100644 index 00000000..630b50ff --- /dev/null +++ b/parakeet/modules/fastspeech2_transformer/encoder.py @@ -0,0 +1,225 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import logging + +from paddle import nn + +from parakeet.modules.fastspeech2_transformer.attention import MultiHeadedAttention +from parakeet.modules.fastspeech2_transformer.embedding import PositionalEncoding +from parakeet.modules.fastspeech2_transformer.encoder_layer import EncoderLayer +from parakeet.modules.fastspeech2_transformer.multi_layer_conv import Conv1dLinear +from parakeet.modules.fastspeech2_transformer.multi_layer_conv import MultiLayeredConv1d +from parakeet.modules.fastspeech2_transformer.positionwise_feed_forward import PositionwiseFeedForward +from parakeet.modules.fastspeech2_transformer.repeat import repeat + + +class Encoder(nn.Layer): + """Transformer encoder module. + + Parameters + ---------- + idim : int + Input dimension. + attention_dim : int + Dimention of attention. + attention_heads : int + The number of heads of multi head attention. + linear_units : int + The number of units of position-wise feed forward. + num_blocks : int + The number of decoder blocks. + dropout_rate : float + Dropout rate. + positional_dropout_rate : float + Dropout rate after adding positional encoding. + attention_dropout_rate : float + Dropout rate in attention. + input_layer : Union[str, paddle.nn.Layer] + Input layer type. + pos_enc_class : paddle.nn.Layer + Positional encoding module class. + `PositionalEncoding `or `ScaledPositionalEncoding` + normalize_before : bool + Whether to use layer_norm before the first block. + concat_after : bool + Whether to concat attention layer's input and output. + if True, additional linear will be applied. + i.e. x -> x + linear(concat(x, att(x))) + if False, no additional linear will be applied. i.e. x -> x + att(x) + positionwise_layer_type : str + "linear", "conv1d", or "conv1d-linear". + positionwise_conv_kernel_size : int + Kernel size of positionwise conv1d layer. + selfattention_layer_type : str + Encoder attention layer type. + padding_idx : int + Padding idx for input_layer=embed. + """ + + def __init__( + self, + idim, + attention_dim=256, + attention_heads=4, + linear_units=2048, + num_blocks=6, + dropout_rate=0.1, + positional_dropout_rate=0.1, + attention_dropout_rate=0.0, + input_layer="conv2d", + pos_enc_class=PositionalEncoding, + normalize_before=True, + concat_after=False, + positionwise_layer_type="linear", + positionwise_conv_kernel_size=1, + selfattention_layer_type="selfattn", + padding_idx=-1, ): + """Construct an Encoder object.""" + super(Encoder, self).__init__() + self.conv_subsampling_factor = 1 + if input_layer == "linear": + self.embed = nn.Sequential( + nn.Linear(idim, attention_dim, bias_attr=True), + nn.LayerNorm(attention_dim), + nn.Dropout(dropout_rate), + nn.ReLU(), + pos_enc_class(attention_dim, positional_dropout_rate), ) + elif input_layer == "embed": + self.embed = nn.Sequential( + nn.Embedding(idim, attention_dim, padding_idx=padding_idx), + pos_enc_class(attention_dim, positional_dropout_rate), ) + elif isinstance(input_layer, nn.Layer): + self.embed = nn.Sequential( + input_layer, + pos_enc_class(attention_dim, positional_dropout_rate), ) + elif input_layer is None: + self.embed = nn.Sequential( + pos_enc_class(attention_dim, positional_dropout_rate)) + else: + raise ValueError("unknown input_layer: " + input_layer) + + self.normalize_before = normalize_before + positionwise_layer, positionwise_layer_args = self.get_positionwise_layer( + positionwise_layer_type, + attention_dim, + linear_units, + dropout_rate, + positionwise_conv_kernel_size, ) + if selfattention_layer_type in [ + "selfattn", + "rel_selfattn", + "legacy_rel_selfattn", + ]: + logging.info("encoder self-attention layer type = self-attention") + encoder_selfattn_layer = MultiHeadedAttention + encoder_selfattn_layer_args = [ + (attention_heads, attention_dim, attention_dropout_rate, ) + ] * num_blocks + + else: + raise NotImplementedError(selfattention_layer_type) + + self.encoders = repeat( + num_blocks, + lambda lnum: EncoderLayer( + attention_dim, + encoder_selfattn_layer(*encoder_selfattn_layer_args[lnum]), + positionwise_layer(*positionwise_layer_args), + dropout_rate, + normalize_before, + concat_after, ), ) + if self.normalize_before: + self.after_norm = nn.LayerNorm(attention_dim) + + def get_positionwise_layer( + self, + positionwise_layer_type="linear", + attention_dim=256, + linear_units=2048, + dropout_rate=0.1, + positionwise_conv_kernel_size=1, ): + """Define positionwise layer.""" + if positionwise_layer_type == "linear": + positionwise_layer = PositionwiseFeedForward + positionwise_layer_args = (attention_dim, linear_units, + dropout_rate) + elif positionwise_layer_type == "conv1d": + positionwise_layer = MultiLayeredConv1d + positionwise_layer_args = (attention_dim, linear_units, + positionwise_conv_kernel_size, + dropout_rate, ) + elif positionwise_layer_type == "conv1d-linear": + positionwise_layer = Conv1dLinear + positionwise_layer_args = (attention_dim, linear_units, + positionwise_conv_kernel_size, + dropout_rate, ) + else: + raise NotImplementedError("Support only linear or conv1d.") + return positionwise_layer, positionwise_layer_args + + def forward(self, xs, masks): + """Encode input sequence. + + Parameters + ---------- + xs : paddle.Tensor + Input tensor (#batch, time, idim). + masks : paddle.Tensor + Mask tensor (#batch, time). + + Returns + ---------- + paddle.Tensor + Output tensor (#batch, time, attention_dim). + paddle.Tensor + Mask tensor (#batch, time). + """ + xs = self.embed(xs) + xs, masks = self.encoders(xs, masks) + if self.normalize_before: + xs = self.after_norm(xs) + return xs, masks + + def forward_one_step(self, xs, masks, cache=None): + """Encode input frame. + + Parameters + ---------- + xs : paddle.Tensor + Input tensor. + masks : paddle.Tensor + Mask tensor. + cache : List[paddle.Tensor] + List of cache tensors. + + Returns + ---------- + paddle.Tensor + Output tensor. + paddle.Tensor + Mask tensor. + List[paddle.Tensor] + List of new cache tensors. + """ + + xs = self.embed(xs) + if cache is None: + cache = [None for _ in range(len(self.encoders))] + new_cache = [] + for c, e in zip(cache, self.encoders): + xs, masks = e(xs, masks, cache=c) + new_cache.append(xs) + if self.normalize_before: + xs = self.after_norm(xs) + return xs, masks, new_cache diff --git a/parakeet/modules/fastspeech2_transformer/encoder_layer.py b/parakeet/modules/fastspeech2_transformer/encoder_layer.py new file mode 100644 index 00000000..d8f89d67 --- /dev/null +++ b/parakeet/modules/fastspeech2_transformer/encoder_layer.py @@ -0,0 +1,115 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Encoder self-attention layer definition.""" +import paddle +from paddle import nn + + +class EncoderLayer(nn.Layer): + """Encoder layer module. + + Parameters + ---------- + size : int + Input dimension. + self_attn : paddle.nn.Layer + Self-attention module instance. + `MultiHeadedAttention` instance can be used as the argument. + feed_forward : paddle.nn.Layer + Feed-forward module instance. + `PositionwiseFeedForward`, `MultiLayeredConv1d`, or `Conv1dLinear` instance can be used as the argument. + dropout_rate : float + Dropout rate. + normalize_before : bool + Whether to use layer_norm before the first block. + concat_after : bool + Whether to concat attention layer's input and output. + if True, additional linear will be applied. + i.e. x -> x + linear(concat(x, att(x))) + if False, no additional linear will be applied. i.e. x -> x + att(x) + """ + + def __init__( + self, + size, + self_attn, + feed_forward, + dropout_rate, + normalize_before=True, + concat_after=False, ): + """Construct an EncoderLayer object.""" + super(EncoderLayer, self).__init__() + self.self_attn = self_attn + self.feed_forward = feed_forward + self.norm1 = nn.LayerNorm(size) + self.norm2 = nn.LayerNorm(size) + self.dropout = nn.Dropout(dropout_rate) + self.size = size + self.normalize_before = normalize_before + self.concat_after = concat_after + if self.concat_after: + self.concat_linear = nn.Linear(size + size, size, bias_attr=True) + + def forward(self, x, mask, cache=None): + """Compute encoded features. + + Parameters + ---------- + x_input : paddle.Tensor + Input tensor (#batch, time, size). + mask : paddle.Tensor + Mask tensor for the input (#batch, time). + cache : paddle.Tensor + Cache tensor of the input (#batch, time - 1, size). + + Returns + ---------- + paddle.Tensor + Output tensor (#batch, time, size). + paddle.Tensor + Mask tensor (#batch, time). + """ + residual = x + if self.normalize_before: + x = self.norm1(x) + + if cache is None: + x_q = x + else: + assert cache.shape == (x.shape[0], x.shape[1] - 1, self.size) + x_q = x[:, -1:, :] + residual = residual[:, -1:, :] + mask = None if mask is None else mask[:, -1:, :] + + if self.concat_after: + x_concat = paddle.concat( + (x, self.self_attn(x_q, x, x, mask)), axis=-1) + x = residual + self.concat_linear(x_concat) + else: + + x = residual + self.dropout(self.self_attn(x_q, x, x, mask)) + if not self.normalize_before: + x = self.norm1(x) + + residual = x + if self.normalize_before: + x = self.norm2(x) + x = residual + self.dropout(self.feed_forward(x)) + if not self.normalize_before: + x = self.norm2(x) + + if cache is not None: + x = paddle.concat([cache, x], axis=1) + + return x, mask diff --git a/parakeet/modules/fastspeech2_transformer/lightconv.py b/parakeet/modules/fastspeech2_transformer/lightconv.py new file mode 100644 index 00000000..e5f59df1 --- /dev/null +++ b/parakeet/modules/fastspeech2_transformer/lightconv.py @@ -0,0 +1,155 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Lightweight Convolution Module.""" + +import numpy +import paddle +from paddle import nn +import paddle.nn.functional as F + +from parakeet.modules.glu import GLU +from parakeet.modules.masked_fill import masked_fill + +MIN_VALUE = float(numpy.finfo(numpy.float32).min) + + +class LightweightConvolution(nn.Layer): + """Lightweight Convolution layer. + + This implementation is based on + https://github.com/pytorch/fairseq/tree/master/fairseq + + Parameters + ---------- + wshare : int + the number of kernel of convolution + n_feat : int + the number of features + dropout_rate : float + dropout_rate + kernel_size : int + kernel size (length) + use_kernel_mask : bool + Use causal mask or not for convolution kernel + use_bias : bool + Use bias term or not. + + """ + + def __init__( + self, + wshare, + n_feat, + dropout_rate, + kernel_size, + use_kernel_mask=False, + use_bias=False, ): + """Construct Lightweight Convolution layer.""" + super(LightweightConvolution, self).__init__() + + assert n_feat % wshare == 0 + self.wshare = wshare + self.use_kernel_mask = use_kernel_mask + self.dropout_rate = dropout_rate + self.kernel_size = kernel_size + self.padding_size = int(kernel_size / 2) + + # linear -> GLU -> lightconv -> linear + self.linear1 = nn.Linear(n_feat, n_feat * 2) + self.linear2 = nn.Linear(n_feat, n_feat) + self.act = GLU() + + # lightconv related + self.uniform_ = nn.initializer.Uniform() + self.weight = paddle.to_tensor( + numpy.random.uniform(0, 1, size=[self.wshare, 1, kernel_size]), + dtype="float32") + self.uniform_(self.weight) + self.weight = paddle.create_parameter( + shape=self.weight.shape, + dtype=str(self.weight.numpy().dtype), + default_initializer=paddle.nn.initializer.Assign(self.weight)) + self.use_bias = use_bias + if self.use_bias: + self.bias = paddle.Tensor(n_feat) + self.bias = paddle.create_parameter( + shape=self.bias.shape, + dtype=str(self.bias.numpy().dtype), + default_initializer=paddle.nn.initializer.Assign(self.bias)) + + # mask of kernel + kernel_mask0 = paddle.zeros([self.wshare, int(kernel_size / 2)]) + kernel_mask1 = paddle.ones([self.wshare, int(kernel_size / 2 + 1)]) + self.kernel_mask = paddle.concat( + (kernel_mask1, kernel_mask0), axis=-1).unsqueeze(1) + + def forward(self, query, key, value, mask): + """Forward of 'Lightweight Convolution'. + + This function takes query, key and value but uses only query. + This is just for compatibility with self-attention layer (attention.py) + + Parameters + ---------- + query : paddle.Tensor + (batch, time1, d_model) input tensor + key : paddle.Tensor + (batch, time2, d_model) NOT USED + value : paddle.Tensor + (batch, time2, d_model) NOT USED + mask : paddle.Tensor + (batch, time1, time2) mask + + Return + ---------- + x : paddle.Tensor + (batch, time1, d_model) ouput + + """ + # linear -> GLU -> lightconv -> linear + x = query + B, T, C = x.shape + H = self.wshare + + # first liner layer + x = self.linear1(x) + + # GLU activation + x = self.act(x) + + # lightconv + # B x C x T + x = x.transpose([0, 2, 1]).reshape([-1, H, T]) + weight = F.dropout( + self.weight, self.dropout_rate, training=self.training) + if self.use_kernel_mask: + weight = masked_fill(weight, self.kernel_mask == 0.0, float("-inf")) + # weight = weight.masked_fill(self.kernel_mask == 0.0, float("-inf")) + weight = F.softmax(weight, axis=-1) + x = F.conv1d( + x, weight, padding=self.padding_size, + groups=self.wshare).reshape([B, C, T]) + if self.use_bias: + x = x + self.bias.reshape([1, -1, 1]) + # B x T x C + x = x.transpose([0, 2, 1]) + + if mask is not None and not self.use_kernel_mask: + mask = mask.transpose([0, 2, 1]) + # x = x.masked_fill(mask == 0, 0.0) + x = masked_fill(x, mask == 0, 0.0) + + # second linear layer + x = self.linear2(x) + return x diff --git a/parakeet/modules/fastspeech2_transformer/mask.py b/parakeet/modules/fastspeech2_transformer/mask.py new file mode 100644 index 00000000..7dbd4d2f --- /dev/null +++ b/parakeet/modules/fastspeech2_transformer/mask.py @@ -0,0 +1,57 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Mask module.""" + +import paddle + + +def subsequent_mask(size, dtype=paddle.bool): + """Create mask for subsequent steps (size, size). + Parameters + ---------- + size : int + size of mask + dtype : paddle.dtype + result dtype + Return + ---------- + paddle.Tensor + >>> subsequent_mask(3) + [[1, 0, 0], + [1, 1, 0], + [1, 1, 1]] + """ + ret = paddle.ones([size, size], dtype=dtype) + return paddle.tril(ret) + + +def target_mask(ys_in_pad, ignore_id, dtype=paddle.bool): + """Create mask for decoder self-attention. + Parameters + ---------- + + ys_pad : paddle.Tensor + batch of padded target sequences (B, Lmax) + ignore_id : int + index of padding + dtype : torch.dtype + result dtype + Return + ---------- + paddle.Tensor + (B, Lmax, Lmax) + """ + ys_mask = ys_in_pad != ignore_id + m = subsequent_mask(ys_mask.shape[-1]).unsqueeze(0) + return ys_mask.unsqueeze(-2) & m diff --git a/parakeet/modules/fastspeech2_transformer/multi_layer_conv.py b/parakeet/modules/fastspeech2_transformer/multi_layer_conv.py new file mode 100644 index 00000000..8845b2a2 --- /dev/null +++ b/parakeet/modules/fastspeech2_transformer/multi_layer_conv.py @@ -0,0 +1,128 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Layer modules for FFT block in FastSpeech (Feed-forward Transformer).""" +import paddle + + +class MultiLayeredConv1d(paddle.nn.Layer): + """Multi-layered conv1d for Transformer block. + + This is a module of multi-leyered conv1d designed + to replace positionwise feed-forward network + in Transforner block, which is introduced in + `FastSpeech: Fast, Robust and Controllable Text to Speech`_. + + .. _`FastSpeech: Fast, Robust and Controllable Text to Speech`: + https://arxiv.org/pdf/1905.09263.pdf + + """ + + def __init__(self, in_chans, hidden_chans, kernel_size, dropout_rate): + """Initialize MultiLayeredConv1d module. + + Parameters + ---------- + in_chans : int + Number of input channels. + hidden_chans : int + Number of hidden channels. + kernel_size : int + Kernel size of conv1d. + dropout_rate : float + Dropout rate. + + """ + super(MultiLayeredConv1d, self).__init__() + self.w_1 = paddle.nn.Conv1D( + in_chans, + hidden_chans, + kernel_size, + stride=1, + padding=(kernel_size - 1) // 2, ) + self.w_2 = paddle.nn.Conv1D( + hidden_chans, + in_chans, + kernel_size, + stride=1, + padding=(kernel_size - 1) // 2, ) + self.dropout = paddle.nn.Dropout(dropout_rate) + self.relu = paddle.nn.ReLU() + + def forward(self, x): + """Calculate forward propagation. + + Parameters + ---------- + x : paddle.Tensor + Batch of input tensors (B, T, in_chans). + + Returns + ---------- + paddle.Tensor + Batch of output tensors (B, T, in_chans). + """ + x = self.relu(self.w_1(x.transpose([0, 2, 1]))).transpose([0, 2, 1]) + return self.w_2(self.dropout(x).transpose([0, 2, 1])).transpose( + [0, 2, 1]) + + +class Conv1dLinear(paddle.nn.Layer): + """Conv1D + Linear for Transformer block. + + A variant of MultiLayeredConv1d, which replaces second conv-layer to linear. + + """ + + def __init__(self, in_chans, hidden_chans, kernel_size, dropout_rate): + """Initialize Conv1dLinear module. + + Parameters + ---------- + in_chans : int + Number of input channels. + hidden_chans : int + Number of hidden channels. + kernel_size : int + Kernel size of conv1d. + dropout_rate : float + Dropout rate. + """ + super(Conv1dLinear, self).__init__() + self.w_1 = paddle.nn.Conv1D( + in_chans, + hidden_chans, + kernel_size, + stride=1, + padding=(kernel_size - 1) // 2, ) + self.w_2 = paddle.nn.Linear(hidden_chans, in_chans, bias_attr=True) + self.dropout = paddle.nn.Dropout(dropout_rate) + self.relu = paddle.nn.ReLU() + + def forward(self, x): + """Calculate forward propagation. + + Parameters + ---------- + x : paddle.Tensor + Batch of input tensors (B, T, in_chans). + + Returns + ---------- + paddle.Tensor + Batch of output tensors (B, T, in_chans). + + """ + x = self.relu(self.w_1(x.transpose([0, 2, 1]))).transpose([0, 2, 1]) + + return self.w_2(self.dropout(x)) diff --git a/parakeet/modules/fastspeech2_transformer/positionwise_feed_forward.py b/parakeet/modules/fastspeech2_transformer/positionwise_feed_forward.py new file mode 100644 index 00000000..39c06eba --- /dev/null +++ b/parakeet/modules/fastspeech2_transformer/positionwise_feed_forward.py @@ -0,0 +1,45 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Positionwise feed forward layer definition.""" +import paddle + + +class PositionwiseFeedForward(paddle.nn.Layer): + """Positionwise feed forward layer. + + Parameters + ---------- + idim : int + Input dimenstion. + hidden_units : int + The number of hidden units. + dropout_rate : float + Dropout rate. + """ + + def __init__(self, + idim, + hidden_units, + dropout_rate, + activation=paddle.nn.ReLU()): + """Construct an PositionwiseFeedForward object.""" + super(PositionwiseFeedForward, self).__init__() + self.w_1 = paddle.nn.Linear(idim, hidden_units, bias_attr=True) + self.w_2 = paddle.nn.Linear(hidden_units, idim, bias_attr=True) + self.dropout = paddle.nn.Dropout(dropout_rate) + self.activation = activation + + def forward(self, x): + """Forward funciton.""" + return self.w_2(self.dropout(self.activation(self.w_1(x)))) diff --git a/parakeet/modules/fastspeech2_transformer/repeat.py b/parakeet/modules/fastspeech2_transformer/repeat.py new file mode 100644 index 00000000..3c62298e --- /dev/null +++ b/parakeet/modules/fastspeech2_transformer/repeat.py @@ -0,0 +1,43 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Repeat the same layer definition.""" +import paddle + + +class MultiSequential(paddle.nn.Sequential): + """Multi-input multi-output paddle.nn.Sequential.""" + + def forward(self, *args): + """Repeat.""" + for m in self: + args = m(*args) + return args + + +def repeat(N, fn): + """Repeat module N times. + + Parameters + ---------- + N : int + Number of repeat time. + fn : Callable + Function to generate module. + + Returns + ---------- + MultiSequential + Repeated model instance. + """ + return MultiSequential(* [fn(n) for n in range(N)]) diff --git a/parakeet/modules/geometry.py b/parakeet/modules/geometry.py new file mode 100644 index 00000000..a3d56f7d --- /dev/null +++ b/parakeet/modules/geometry.py @@ -0,0 +1,50 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import numpy as np +import paddle + + +def shuffle_dim(x, axis, perm=None): + """Permute input tensor along aixs given the permutation or randomly. + + Parameters + ---------- + x : Tensor + The input tensor. + axis : int + The axis to shuffle. + perm : List[int], ndarray, optional + The order to reorder the tensor along the ``axis``-th dimension. + + It is a permutation of ``[0, d)``, where d is the size of the + ``axis``-th dimension of the input tensor. If not provided, + a random permutation is used. Defaults to None. + + Returns + --------- + Tensor + The shuffled tensor, which has the same shape as x does. + """ + size = x.shape[axis] + if perm is not None and len(perm) != size: + raise ValueError("length of permutation should equals the input " + "tensor's axis-th dimension's size") + if perm is not None: + perm = np.array(perm) + else: + perm = np.random.permutation(size) + + perm = paddle.to_tensor(perm) + out = paddle.gather(x, perm, axis) + return out diff --git a/parakeet/modules/glu.py b/parakeet/modules/glu.py new file mode 100644 index 00000000..1669fb36 --- /dev/null +++ b/parakeet/modules/glu.py @@ -0,0 +1,26 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from paddle import nn +from paddle.nn import functional as F + + +class GLU(nn.Layer): + """Gated Linear Units (GLU) Layer""" + + def __init__(self, dim: int=-1): + super().__init__() + self.dim = dim + + def forward(self, xs): + return F.glu(xs, axis=self.dim) diff --git a/parakeet/modules/layer_norm.py b/parakeet/modules/layer_norm.py new file mode 100644 index 00000000..3bab823f --- /dev/null +++ b/parakeet/modules/layer_norm.py @@ -0,0 +1,63 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Layer normalization module.""" +import paddle + + +class LayerNorm(paddle.nn.LayerNorm): + """Layer normalization module. + + Parameters + ---------- + nout : int + Output dim size. + dim : int + Dimension to be normalized. + """ + + def __init__(self, nout, dim=-1): + """Construct an LayerNorm object.""" + super(LayerNorm, self).__init__(nout) + self.dim = dim + + def forward(self, x): + """Apply layer normalization. + + Parameters + ---------- + x : paddle.Tensor + Input tensor. + + Returns + ---------- + paddle.Tensor + Normalized tensor. + """ + if self.dim == -1: + return super(LayerNorm, self).forward(x) + else: + len_dim = len(x.shape) + if self.dim < 0: + self.dim = len_dim + self.dim + assert self.dim >= 0 + + orig_perm = list(range(len_dim)) + new_perm = orig_perm[:] + new_perm[self.dim], new_perm[len_dim - + 1] = new_perm[len_dim - + 1], new_perm[self.dim] + + return paddle.transpose( + super(LayerNorm, self).forward(paddle.transpose(x, new_perm)), + new_perm) diff --git a/parakeet/modules/losses.py b/parakeet/modules/losses.py new file mode 100644 index 00000000..ece9e045 --- /dev/null +++ b/parakeet/modules/losses.py @@ -0,0 +1,125 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import paddle +from paddle.fluid.layers import sequence_mask +from paddle.nn import functional as F + +__all__ = [ + "guided_attention_loss", + "weighted_mean", + "masked_l1_loss", + "masked_softmax_with_cross_entropy", +] + + +def attention_guide(dec_lens, enc_lens, N, T, g, dtype=None): + """Build that W matrix. shape(B, T_dec, T_enc) + W[i, n, t] = 1 - exp(-(n/dec_lens[i] - t/enc_lens[i])**2 / (2g**2)) + + See also: + Tachibana, Hideyuki, Katsuya Uenoyama, and Shunsuke Aihara. 2017. “Efficiently Trainable Text-to-Speech System Based on Deep Convolutional Networks with Guided Attention.” ArXiv:1710.08969 [Cs, Eess], October. http://arxiv.org/abs/1710.08969. + """ + dtype = dtype or paddle.get_default_dtype() + dec_pos = paddle.arange(0, N).astype(dtype) / dec_lens.unsqueeze( + -1) # n/N # shape(B, T_dec) + enc_pos = paddle.arange(0, T).astype(dtype) / enc_lens.unsqueeze( + -1) # t/T # shape(B, T_enc) + W = 1 - paddle.exp(-(dec_pos.unsqueeze(-1) - enc_pos.unsqueeze(1))**2 / + (2 * g**2)) + + dec_mask = sequence_mask(dec_lens, maxlen=N) + enc_mask = sequence_mask(enc_lens, maxlen=T) + mask = dec_mask.unsqueeze(-1) * enc_mask.unsqueeze(1) + mask = paddle.cast(mask, W.dtype) + + W *= mask + return W + + +def guided_attention_loss(attention_weight, dec_lens, enc_lens, g): + """Guided attention loss, masked to excluded padding parts.""" + _, N, T = attention_weight.shape + W = attention_guide(dec_lens, enc_lens, N, T, g, attention_weight.dtype) + + total_tokens = (dec_lens * enc_lens).astype(W.dtype) + loss = paddle.mean(paddle.sum(W * attention_weight, [1, 2]) / total_tokens) + return loss + + +def weighted_mean(input, weight): + """Weighted mean. It can also be used as masked mean. + + Parameters + ----------- + input : Tensor + The input tensor. + weight : Tensor + The weight tensor with broadcastable shape with the input. + + Returns + ---------- + Tensor [shape=(1,)] + Weighted mean tensor with the same dtype as input. + """ + weight = paddle.cast(weight, input.dtype) + broadcast_ratio = input.size / weight.size + return paddle.sum(input * weight) / (paddle.sum(weight) * broadcast_ratio) + + +def masked_l1_loss(prediction, target, mask): + """Compute maksed L1 loss. + + Parameters + ---------- + prediction : Tensor + The prediction. + target : Tensor + The target. The shape should be broadcastable to ``prediction``. + mask : Tensor + The mask. The shape should be broadcatable to the broadcasted shape of + ``prediction`` and ``target``. + + Returns + ------- + Tensor [shape=(1,)] + The masked L1 loss. + """ + abs_error = F.l1_loss(prediction, target, reduction='none') + loss = weighted_mean(abs_error, mask) + return loss + + +def masked_softmax_with_cross_entropy(logits, label, mask, axis=-1): + """Compute masked softmax with cross entropy loss. + + Parameters + ---------- + logits : Tensor + The logits. The ``axis``-th axis is the class dimension. + label : Tensor [dtype: int] + The label. The size of the ``axis``-th axis should be 1. + mask : Tensor + The mask. The shape should be broadcastable to ``label``. + axis : int, optional + The index of the class dimension in the shape of ``logits``, by default + -1. + + Returns + ------- + Tensor [shape=(1,)] + The masked softmax with cross entropy loss. + """ + ce = F.softmax_with_cross_entropy(logits, label, axis=axis) + loss = weighted_mean(ce, mask) + return loss diff --git a/parakeet/modules/masked_fill.py b/parakeet/modules/masked_fill.py new file mode 100644 index 00000000..34230f1c --- /dev/null +++ b/parakeet/modules/masked_fill.py @@ -0,0 +1,37 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from typing import Union + +import paddle + + +def is_broadcastable(shp1, shp2): + for a, b in zip(shp1[::-1], shp2[::-1]): + if a == 1 or b == 1 or a == b: + pass + else: + return False + return True + + +def masked_fill(xs: paddle.Tensor, + mask: paddle.Tensor, + value: Union[float, int]): + assert is_broadcastable(xs.shape, mask.shape) is True + bshape = paddle.broadcast_shape(xs.shape, mask.shape) + mask = mask.broadcast_to(bshape) + trues = paddle.ones_like(xs) * value + mask = mask.cast(dtype=paddle.bool) + xs = paddle.where(mask, trues, xs) + return xs diff --git a/parakeet/modules/masking.py b/parakeet/modules/masking.py new file mode 100644 index 00000000..7cf37040 --- /dev/null +++ b/parakeet/modules/masking.py @@ -0,0 +1,120 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import paddle + +__all__ = [ + "id_mask", + "feature_mask", + "combine_mask", + "future_mask", +] + + +def id_mask(input, padding_index=0, dtype="bool"): + """Generate mask with input ids. + + Those positions where the value equals ``padding_index`` correspond to 0 or + ``False``, otherwise, 1 or ``True``. + + Parameters + ---------- + input : Tensor [dtype: int] + The input tensor. It represents the ids. + padding_index : int, optional + The id which represents padding, by default 0. + dtype : str, optional + Data type of the returned mask, by default "bool". + + Returns + ------- + Tensor + The generate mask. It has the same shape as ``input`` does. + """ + return paddle.cast(input != padding_index, dtype) + + +def feature_mask(input, axis, dtype="bool"): + """Compute mask from input features. + + For a input features, represented as batched feature vectors, those vectors + which all zeros are considerd padding vectors. + + Parameters + ---------- + input : Tensor [dtype: float] + The input tensor which represents featues. + axis : int + The index of the feature dimension in ``input``. Other dimensions are + considered ``spatial`` dimensions. + dtype : str, optional + Data type of the generated mask, by default "bool" + Returns + ------- + Tensor + The geenrated mask with ``spatial`` shape as mentioned above. + + It has one less dimension than ``input`` does. + """ + feature_sum = paddle.sum(paddle.abs(input), axis) + return paddle.cast(feature_sum != 0, dtype) + + +def combine_mask(mask1, mask2): + """Combine two mask with multiplication or logical and. + + Parameters + ----------- + mask1 : Tensor + The first mask. + mask2 : Tensor + The second mask with broadcastable shape with ``mask1``. + Returns + -------- + Tensor + Combined mask. + + Notes + ------ + It is mainly used to combine the padding mask and no future mask for + transformer decoder. + + Padding mask is used to mask padding positions of the decoder inputs and + no future mask is used to prevent the decoder to see future information. + """ + if mask1.dtype == paddle.fluid.core.VarDesc.VarType.BOOL: + return paddle.logical_and(mask1, mask2) + else: + return mask1 * mask2 + + +def future_mask(time_steps, dtype="bool"): + """Generate lower triangular mask. + + It is used at transformer decoder to prevent the decoder to see future + information. + + Parameters + ---------- + time_steps : int + Decoder time steps. + dtype : str, optional + The data type of the generate mask, by default "bool". + + Returns + ------- + Tensor + The generated mask. + """ + mask = paddle.tril(paddle.ones([time_steps, time_steps])) + return paddle.cast(mask, dtype) diff --git a/parakeet/modules/nets_utils.py b/parakeet/modules/nets_utils.py new file mode 100644 index 00000000..47eae65d --- /dev/null +++ b/parakeet/modules/nets_utils.py @@ -0,0 +1,157 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import paddle +from paddle import nn +from typeguard import check_argument_types + + +def pad_list(xs, pad_value): + """Perform padding for the list of tensors. + + Parameters + ---------- + xs : List[Tensor] + List of Tensors [(T_1, `*`), (T_2, `*`), ..., (T_B, `*`)]. + pad_value : float) + Value for padding. + + Returns + ---------- + Tensor + Padded tensor (B, Tmax, `*`). + + Examples + ---------- + >>> x = [paddle.ones([4]), paddle.ones([2]), paddle.ones([1])] + >>> x + [tensor([1., 1., 1., 1.]), tensor([1., 1.]), tensor([1.])] + >>> pad_list(x, 0) + tensor([[1., 1., 1., 1.], + [1., 1., 0., 0.], + [1., 0., 0., 0.]]) + """ + n_batch = len(xs) + max_len = max(x.shape[0] for x in xs) + pad = paddle.full([n_batch, max_len, *xs[0].shape[1:]], pad_value) + + for i in range(n_batch): + pad[i, :xs[i].shape[0]] = xs[i] + + return pad + + +def make_pad_mask(lengths, length_dim=-1): + """Make mask tensor containing indices of padded part. + + Parameters + ---------- + lengths : LongTensor or List + Batch of lengths (B,). + + Returns + ---------- + Tensor(bool) + Mask tensor containing indices of padded part bool. + + Examples + ---------- + With only lengths. + + >>> lengths = [5, 3, 2] + >>> make_non_pad_mask(lengths) + masks = [[0, 0, 0, 0 ,0], + [0, 0, 0, 1, 1], + [0, 0, 1, 1, 1]] + """ + if length_dim == 0: + raise ValueError("length_dim cannot be 0: {}".format(length_dim)) + + if not isinstance(lengths, list): + lengths = lengths.tolist() + bs = int(len(lengths)) + + maxlen = int(max(lengths)) + + seq_range = paddle.arange(0, maxlen, dtype=paddle.int64) + seq_range_expand = seq_range.unsqueeze(0).expand([bs, maxlen]) + + seq_length_expand = paddle.to_tensor( + lengths, dtype=seq_range_expand.dtype).unsqueeze(-1) + mask = seq_range_expand >= seq_length_expand + + return mask + + +def make_non_pad_mask(lengths, length_dim=-1): + """Make mask tensor containing indices of non-padded part. + + Parameters + ---------- + lengths : LongTensor or List + Batch of lengths (B,). + xs : Tensor, optional + The reference tensor. + If set, masks will be the same shape as this tensor. + length_dim : int, optional + Dimension indicator of the above tensor. + See the example. + + Returns + ---------- + Tensor(bool) + mask tensor containing indices of padded part bool. + + Examples + ---------- + With only lengths. + + >>> lengths = [5, 3, 2] + >>> make_non_pad_mask(lengths) + masks = [[1, 1, 1, 1 ,1], + [1, 1, 1, 0, 0], + [1, 1, 0, 0, 0]] + """ + return paddle.logical_not(make_pad_mask(lengths, length_dim)) + + +def initialize(model: nn.Layer, init: str): + """Initialize weights of a neural network module. + + Parameters are initialized using the given method or distribution. + + Custom initialization routines can be implemented into submodules + + Parameters + ---------- + model : paddle.nn.Layer + Target. + init : str + Method of initialization. + """ + assert check_argument_types() + + if init == "xavier_uniform": + nn.initializer.set_global_initializer(nn.initializer.XavierUniform(), + nn.initializer.Constant()) + elif init == "xavier_normal": + nn.initializer.set_global_initializer(nn.initializer.XavierNormal(), + nn.initializer.Constant()) + elif init == "kaiming_uniform": + nn.initializer.set_global_initializer(nn.initializer.KaimingUniform(), + nn.initializer.Constant()) + elif init == "kaiming_normal": + nn.initializer.set_global_initializer(nn.initializer.KaimingNormal(), + nn.initializer.Constant()) + else: + raise ValueError("Unknown initialization: " + init) diff --git a/parakeet/modules/normalizer.py b/parakeet/modules/normalizer.py new file mode 100644 index 00000000..a4fc598c --- /dev/null +++ b/parakeet/modules/normalizer.py @@ -0,0 +1,33 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import paddle +from paddle import nn + + +class ZScore(nn.Layer): + # feature last + def __init__(self, mu, sigma): + super().__init__() + self.register_buffer("mu", mu) + self.register_buffer("sigma", sigma) + + def forward(self, x): + # NOTE: to be compatible with paddle's to_static, we must explicitly + # call multiply, or add, etc, instead of +-*/, etc. + return paddle.divide(paddle.subtract(x, self.mu), self.sigma) + + def inverse(self, x): + # NOTE: to be compatible with paddle's to_static, we must explicitly + # call multiply, or add, etc, instead of +-*/, etc. + return paddle.add(paddle.multiply(x, self.sigma), self.mu) diff --git a/parakeet/modules/positional_encoding.py b/parakeet/modules/positional_encoding.py new file mode 100644 index 00000000..7c368c3a --- /dev/null +++ b/parakeet/modules/positional_encoding.py @@ -0,0 +1,66 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import paddle +from paddle import Tensor + +__all__ = ["sinusoid_position_encoding", "scaled_position_encoding"] + + +def sinusoid_position_encoding(num_positions: int, + feature_size: int, + omega: float=1.0, + start_pos: int=0, + dtype=None) -> paddle.Tensor: + # return tensor shape (num_positions, feature_size) + # NOTE: to be compatible with paddle's to_static, we cannnot raise + # an exception here, take care of it by yourself + # if (feature_size % 2 != 0): + # raise ValueError("size should be divisible by 2") + dtype = dtype or paddle.get_default_dtype() + + channel = paddle.arange(0, feature_size, 2, dtype=dtype) + index = paddle.arange(start_pos, start_pos + num_positions, 1, dtype=dtype) + p = (paddle.unsqueeze(index, -1) * + omega) / (10000.0**(channel / float(feature_size))) + encodings = paddle.zeros([num_positions, feature_size], dtype=dtype) + encodings[:, 0::2] = paddle.sin(p) + encodings[:, 1::2] = paddle.cos(p) + return encodings + + +def scaled_position_encoding(num_positions: int, + feature_size: int, + omega: Tensor, + start_pos: int=0, + dtype=None) -> Tensor: + # omega: Tensor (batch_size, ) + # return tensor shape (batch_size, num_positions, feature_size) + # consider renaming this as batched positioning encoding + if (feature_size % 2 != 0): + raise ValueError("size should be divisible by 2") + dtype = dtype or paddle.get_default_dtype() + + channel = paddle.arange(0, feature_size, 2, dtype=dtype) + index = paddle.arange( + start_pos, start_pos + num_positions, 1, dtype=omega.dtype) + batch_size = omega.shape[0] + omega = paddle.unsqueeze(omega, [1, 2]) + p = (paddle.unsqueeze(index, -1) * + omega) / (10000.0**(channel / float(feature_size))) + encodings = paddle.zeros( + [batch_size, num_positions, feature_size], dtype=dtype) + # it is nice to have fancy indexing and inplace operations + encodings[:, :, 0::2] = paddle.sin(p) + encodings[:, :, 1::2] = paddle.cos(p) + return encodings diff --git a/parakeet/modules/ssim.py b/parakeet/modules/ssim.py new file mode 100644 index 00000000..c9899cd6 --- /dev/null +++ b/parakeet/modules/ssim.py @@ -0,0 +1,80 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from math import exp + +import paddle +import paddle.nn.functional as F +from paddle import nn + + +def gaussian(window_size, sigma): + gauss = paddle.to_tensor([ + exp(-(x - window_size // 2)**2 / float(2 * sigma**2)) + for x in range(window_size) + ]) + return gauss / gauss.sum() + + +def create_window(window_size, channel): + _1D_window = gaussian(window_size, 1.5).unsqueeze(1) + _2D_window = paddle.matmul(_1D_window, paddle.transpose( + _1D_window, [1, 0])).unsqueeze([0, 1]) + window = paddle.expand(_2D_window, [channel, 1, window_size, window_size]) + return window + + +def _ssim(img1, img2, window, window_size, channel, size_average=True): + mu1 = F.conv2d(img1, window, padding=window_size // 2, groups=channel) + mu2 = F.conv2d(img2, window, padding=window_size // 2, groups=channel) + + mu1_sq = mu1.pow(2) + mu2_sq = mu2.pow(2) + mu1_mu2 = mu1 * mu2 + + sigma1_sq = F.conv2d( + img1 * img1, window, padding=window_size // 2, groups=channel) - mu1_sq + sigma2_sq = F.conv2d( + img2 * img2, window, padding=window_size // 2, groups=channel) - mu2_sq + sigma12 = F.conv2d( + img1 * img2, window, padding=window_size // 2, groups=channel) - mu1_mu2 + + C1 = 0.01**2 + C2 = 0.03**2 + + ssim_map = ((2 * mu1_mu2 + C1) * (2 * sigma12 + C2)) \ + / ((mu1_sq + mu2_sq + C1) * (sigma1_sq + sigma2_sq + C2)) + + if size_average: + return ssim_map.mean() + else: + return ssim_map.mean(1).mean(1).mean(1) + + +class SSIM(nn.Layer): + def __init__(self, window_size=11, size_average=True): + super().__init__() + self.window_size = window_size + self.size_average = size_average + self.channel = 1 + self.window = create_window(window_size, self.channel) + + def forward(self, img1, img2): + return _ssim(img1, img2, self.window, self.window_size, self.channel, + self.size_average) + + +def ssim(img1, img2, window_size=11, size_average=True): + (_, channel, _, _) = img1.shape + window = create_window(window_size, channel) + return _ssim(img1, img2, window, window_size, channel, size_average) diff --git a/parakeet/modules/stft_loss.py b/parakeet/modules/stft_loss.py new file mode 100644 index 00000000..1f400b46 --- /dev/null +++ b/parakeet/modules/stft_loss.py @@ -0,0 +1,219 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import paddle +from paddle import nn +from paddle.nn import functional as F +from scipy import signal + + +def stft(x, + fft_size, + hop_length=None, + win_length=None, + window='hann', + center=True, + pad_mode='reflect'): + """Perform STFT and convert to magnitude spectrogram. + Parameters + ---------- + x : Tensor + Input signal tensor (B, T). + fft_size : int + FFT size. + hop_size : int + Hop size. + win_length : int + window : str, optional + window : str + Name of window function, see `scipy.signal.get_window` for more + details. Defaults to "hann". + center : bool, optional + center (bool, optional): Whether to pad `x` to make that the + :math:`t \times hop\_length` at the center of :math:`t`-th frame. Default: `True`. + pad_mode : str, optional + Choose padding pattern when `center` is `True`. + Returns + ---------- + Tensor: + Magnitude spectrogram (B, #frames, fft_size // 2 + 1). + """ + # calculate window + window = signal.get_window(window, win_length, fftbins=True) + window = paddle.to_tensor(window) + x_stft = paddle.tensor.signal.stft( + x, + fft_size, + hop_length, + win_length, + window=window, + center=center, + pad_mode=pad_mode) + + real = x_stft.real() + imag = x_stft.imag() + + return paddle.sqrt(paddle.clip(real**2 + imag**2, min=1e-7)).transpose( + [0, 2, 1]) + + +class SpectralConvergenceLoss(nn.Layer): + """Spectral convergence loss module.""" + + def __init__(self): + """Initilize spectral convergence loss module.""" + super().__init__() + + def forward(self, x_mag, y_mag): + """Calculate forward propagation. + Parameters + ---------- + x_mag : Tensor + Magnitude spectrogram of predicted signal (B, #frames, #freq_bins). + y_mag : Tensor) + Magnitude spectrogram of groundtruth signal (B, #frames, #freq_bins). + Returns + ---------- + Tensor + Spectral convergence loss value. + """ + return paddle.norm( + y_mag - x_mag, p="fro") / paddle.clip( + paddle.norm(y_mag, p="fro"), min=1e-10) + + +class LogSTFTMagnitudeLoss(nn.Layer): + """Log STFT magnitude loss module.""" + + def __init__(self, epsilon=1e-7): + """Initilize los STFT magnitude loss module.""" + super().__init__() + self.epsilon = epsilon + + def forward(self, x_mag, y_mag): + """Calculate forward propagation. + Parameters + ---------- + x_mag : Tensor + Magnitude spectrogram of predicted signal (B, #frames, #freq_bins). + y_mag : Tensor + Magnitude spectrogram of groundtruth signal (B, #frames, #freq_bins). + Returns + ---------- + Tensor + Log STFT magnitude loss value. + """ + return F.l1_loss( + paddle.log(paddle.clip(y_mag, min=self.epsilon)), + paddle.log(paddle.clip(x_mag, min=self.epsilon))) + + +class STFTLoss(nn.Layer): + """STFT loss module.""" + + def __init__(self, + fft_size=1024, + shift_size=120, + win_length=600, + window="hann"): + """Initialize STFT loss module.""" + super().__init__() + self.fft_size = fft_size + self.shift_size = shift_size + self.win_length = win_length + self.window = window + self.spectral_convergence_loss = SpectralConvergenceLoss() + self.log_stft_magnitude_loss = LogSTFTMagnitudeLoss() + + def forward(self, x, y): + """Calculate forward propagation. + Parameters + ---------- + x : Tensor + Predicted signal (B, T). + y : Tensor + Groundtruth signal (B, T). + Returns + ---------- + Tensor + Spectral convergence loss value. + Tensor + Log STFT magnitude loss value. + """ + x_mag = stft(x, self.fft_size, self.shift_size, self.win_length, + self.window) + y_mag = stft(y, self.fft_size, self.shift_size, self.win_length, + self.window) + sc_loss = self.spectral_convergence_loss(x_mag, y_mag) + mag_loss = self.log_stft_magnitude_loss(x_mag, y_mag) + + return sc_loss, mag_loss + + +class MultiResolutionSTFTLoss(nn.Layer): + """Multi resolution STFT loss module.""" + + def __init__( + self, + fft_sizes=[1024, 2048, 512], + hop_sizes=[120, 240, 50], + win_lengths=[600, 1200, 240], + window="hann", ): + """Initialize Multi resolution STFT loss module. + Parameters + ---------- + fft_sizes : list + List of FFT sizes. + hop_sizes : list + List of hop sizes. + win_lengths : list + List of window lengths. + window : str + Window function type. + """ + super().__init__() + assert len(fft_sizes) == len(hop_sizes) == len(win_lengths) + self.stft_losses = nn.LayerList() + for fs, ss, wl in zip(fft_sizes, hop_sizes, win_lengths): + self.stft_losses.append(STFTLoss(fs, ss, wl, window)) + + def forward(self, x, y): + """Calculate forward propagation. + Parameters + ---------- + x : Tensor + Predicted signal (B, T) or (B, #subband, T). + y : Tensor + Groundtruth signal (B, T) or (B, #subband, T). + Returns + ---------- + Tensor + Multi resolution spectral convergence loss value. + Tensor + Multi resolution log STFT magnitude loss value. + """ + if len(x.shape) == 3: + # (B, C, T) -> (B x C, T) + x = x.reshape([-1, x.shape[2]]) + # (B, C, T) -> (B x C, T) + y = y.reshape([-1, y.shape[2]]) + sc_loss = 0.0 + mag_loss = 0.0 + for f in self.stft_losses: + sc_l, mag_l = f(x, y) + sc_loss += sc_l + mag_loss += mag_l + sc_loss /= len(self.stft_losses) + mag_loss /= len(self.stft_losses) + + return sc_loss, mag_loss diff --git a/parakeet/modules/style_encoder.py b/parakeet/modules/style_encoder.py new file mode 100644 index 00000000..aa94d4ba --- /dev/null +++ b/parakeet/modules/style_encoder.py @@ -0,0 +1,308 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Style encoder of GST-Tacotron.""" + +from typeguard import check_argument_types +from typing import Sequence + +import paddle +from paddle import nn +from parakeet.modules.fastspeech2_transformer.attention import MultiHeadedAttention as BaseMultiHeadedAttention + + +class StyleEncoder(nn.Layer): + """Style encoder. + + This module is style encoder introduced in `Style Tokens: Unsupervised Style + Modeling, Control and Transfer in End-to-End Speech Synthesis`. + + .. _`Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End + Speech Synthesis`: https://arxiv.org/abs/1803.09017 + + Parameters + ---------- + idim : int, optional + Dimension of the input mel-spectrogram. + gst_tokens : int, optional + The number of GST embeddings. + gst_token_dim : int, optional + Dimension of each GST embedding. + gst_heads : int, optional + The number of heads in GST multihead attention. + conv_layers : int, optional + The number of conv layers in the reference encoder. + conv_chans_list : Sequence[int], optional + List of the number of channels of conv layers in the referece encoder. + conv_kernel_size : int, optional + Kernal size of conv layers in the reference encoder. + conv_stride : int, optional + Stride size of conv layers in the reference encoder. + gru_layers : int, optional + The number of GRU layers in the reference encoder. + gru_units : int, optional + The number of GRU units in the reference encoder. + + Todo + ---------- + * Support manual weight specification in inference. + + """ + + def __init__( + self, + idim: int=80, + gst_tokens: int=10, + gst_token_dim: int=256, + gst_heads: int=4, + conv_layers: int=6, + conv_chans_list: Sequence[int]=(32, 32, 64, 64, 128, 128), + conv_kernel_size: int=3, + conv_stride: int=2, + gru_layers: int=1, + gru_units: int=128, ): + """Initilize global style encoder module.""" + assert check_argument_types() + super(StyleEncoder, self).__init__() + + self.ref_enc = ReferenceEncoder( + idim=idim, + conv_layers=conv_layers, + conv_chans_list=conv_chans_list, + conv_kernel_size=conv_kernel_size, + conv_stride=conv_stride, + gru_layers=gru_layers, + gru_units=gru_units, ) + self.stl = StyleTokenLayer( + ref_embed_dim=gru_units, + gst_tokens=gst_tokens, + gst_token_dim=gst_token_dim, + gst_heads=gst_heads, ) + + def forward(self, speech: paddle.Tensor) -> paddle.Tensor: + """Calculate forward propagation. + + Args: + speech (Tensor): Batch of padded target features (B, Lmax, odim). + + Returns: + Tensor: Style token embeddings (B, token_dim). + + """ + ref_embs = self.ref_enc(speech) + style_embs = self.stl(ref_embs) + + return style_embs + + +class ReferenceEncoder(nn.Layer): + """Reference encoder module. + + This module is refernece encoder introduced in `Style Tokens: Unsupervised Style + Modeling, Control and Transfer in End-to-End Speech Synthesis`. + + .. _`Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End + Speech Synthesis`: https://arxiv.org/abs/1803.09017 + + Parameters + ---------- + idim : int, optional + Dimension of the input mel-spectrogram. + conv_layers : int, optional + The number of conv layers in the reference encoder. + conv_chans_list: : Sequence[int], optional + List of the number of channels of conv layers in the referece encoder. + conv_kernel_size : int, optional + Kernal size of conv layers in the reference encoder. + conv_stride : int, optional + Stride size of conv layers in the reference encoder. + gru_layers : int, optional + The number of GRU layers in the reference encoder. + gru_units : int, optional + The number of GRU units in the reference encoder. + + """ + + def __init__( + self, + idim=80, + conv_layers: int=6, + conv_chans_list: Sequence[int]=(32, 32, 64, 64, 128, 128), + conv_kernel_size: int=3, + conv_stride: int=2, + gru_layers: int=1, + gru_units: int=128, ): + """Initilize reference encoder module.""" + assert check_argument_types() + super(ReferenceEncoder, self).__init__() + + # check hyperparameters are valid + assert conv_kernel_size % 2 == 1, "kernel size must be odd." + assert ( + len(conv_chans_list) == conv_layers + ), "the number of conv layers and length of channels list must be the same." + + convs = [] + padding = (conv_kernel_size - 1) // 2 + for i in range(conv_layers): + conv_in_chans = 1 if i == 0 else conv_chans_list[i - 1] + conv_out_chans = conv_chans_list[i] + convs += [ + nn.Conv2D( + conv_in_chans, + conv_out_chans, + kernel_size=conv_kernel_size, + stride=conv_stride, + padding=padding, + # Do not use bias due to the following batch norm + bias_attr=False, ), + nn.BatchNorm2D(conv_out_chans), + nn.ReLU(), + ] + self.convs = nn.Sequential(*convs) + + self.conv_layers = conv_layers + self.kernel_size = conv_kernel_size + self.stride = conv_stride + self.padding = padding + + # get the number of GRU input units + gru_in_units = idim + for i in range(conv_layers): + gru_in_units = (gru_in_units - conv_kernel_size + 2 * padding + ) // conv_stride + 1 + gru_in_units *= conv_out_chans + self.gru = nn.GRU(gru_in_units, gru_units, gru_layers, time_major=False) + + def forward(self, speech: paddle.Tensor) -> paddle.Tensor: + """Calculate forward propagation. + + Parameters + ---------- + speech : Tensor + Batch of padded target features (B, Lmax, idim). + + Return + ---------- + Tensor + Reference embedding (B, gru_units) + + """ + batch_size = speech.shape[0] + # (B, 1, Lmax, idim) + xs = speech.unsqueeze(1) + # (B, Lmax', conv_out_chans, idim') + hs = self.convs(xs).transpose([0, 2, 1, 3]) + time_length = hs.shape[1] + # (B, Lmax', gru_units) + hs = hs.reshape(shape=[batch_size, time_length, -1]) + self.gru.flatten_parameters() + # (gru_layers, batch_size, gru_units) + _, ref_embs = self.gru(hs) + # (batch_size, gru_units) + ref_embs = ref_embs[-1] + + return ref_embs + + +class StyleTokenLayer(nn.Layer): + """Style token layer module. + + This module is style token layer introduced in `Style Tokens: Unsupervised Style + Modeling, Control and Transfer in End-to-End Speech Synthesis`. + + .. _`Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End + Speech Synthesis`: https://arxiv.org/abs/1803.09017 + + Parameters + ---------- + ref_embed_dim : int, optional + Dimension of the input reference embedding. + gst_tokens : int, optional + The number of GST embeddings. + gst_token_dim : int, optional + Dimension of each GST embedding. + gst_heads : int, optional + The number of heads in GST multihead attention. + dropout_rate : float, optional + Dropout rate in multi-head attention. + + """ + + def __init__( + self, + ref_embed_dim: int=128, + gst_tokens: int=10, + gst_token_dim: int=256, + gst_heads: int=4, + dropout_rate: float=0.0, ): + """Initilize style token layer module.""" + assert check_argument_types() + super(StyleTokenLayer, self).__init__() + + gst_embs = paddle.randn(shape=[gst_tokens, gst_token_dim // gst_heads]) + self.gst_embs = paddle.create_parameter( + shape=gst_embs.shape, + dtype=str(gst_embs.numpy().dtype), + default_initializer=paddle.nn.initializer.Assign(gst_embs)) + self.mha = MultiHeadedAttention( + q_dim=ref_embed_dim, + k_dim=gst_token_dim // gst_heads, + v_dim=gst_token_dim // gst_heads, + n_head=gst_heads, + n_feat=gst_token_dim, + dropout_rate=dropout_rate, ) + + def forward(self, ref_embs: paddle.Tensor) -> paddle.Tensor: + """Calculate forward propagation. + + Parameters + ---------- + ref_embs : Tensor + Reference embeddings (B, ref_embed_dim). + + Returns + ---------- + Tensor + Style token embeddings (B, gst_token_dim). + + """ + batch_size = ref_embs.shape[0] + # (num_tokens, token_dim) -> (batch_size, num_tokens, token_dim) + gst_embs = paddle.tanh(self.gst_embs).unsqueeze(0).expand( + [batch_size, -1, -1]) + # (batch_size, 1 ,ref_embed_dim) + ref_embs = ref_embs.unsqueeze(1) + style_embs = self.mha(ref_embs, gst_embs, gst_embs, None) + + return style_embs.squeeze(1) + + +class MultiHeadedAttention(BaseMultiHeadedAttention): + """Multi head attention module with different input dimension.""" + + def __init__(self, q_dim, k_dim, v_dim, n_head, n_feat, dropout_rate=0.0): + """Initialize multi head attention module.""" + # NOTE(kan-bayashi): Do not use super().__init__() here since we want to + # overwrite BaseMultiHeadedAttention.__init__() method. + nn.Layer.__init__(self) + assert n_feat % n_head == 0 + # We assume d_v always equals d_k + self.d_k = n_feat // n_head + self.h = n_head + self.linear_q = nn.Linear(q_dim, n_feat) + self.linear_k = nn.Linear(k_dim, n_feat) + self.linear_v = nn.Linear(v_dim, n_feat) + self.linear_out = nn.Linear(n_feat, n_feat) + self.attn = None + self.dropout = nn.Dropout(p=dropout_rate) diff --git a/parakeet/modules/tacotron2/__init__.py b/parakeet/modules/tacotron2/__init__.py new file mode 100644 index 00000000..abf198b9 --- /dev/null +++ b/parakeet/modules/tacotron2/__init__.py @@ -0,0 +1,13 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/parakeet/modules/tacotron2/decoder.py b/parakeet/modules/tacotron2/decoder.py new file mode 100644 index 00000000..bf9d7e36 --- /dev/null +++ b/parakeet/modules/tacotron2/decoder.py @@ -0,0 +1,198 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Tacotron2 decoder related modules.""" + +import six +import paddle.nn.functional as F +from paddle import nn + + +class Prenet(nn.Layer): + """Prenet module for decoder of Spectrogram prediction network. + + This is a module of Prenet in the decoder of Spectrogram prediction network, + which described in `Natural TTS + Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions`_. + The Prenet preforms nonlinear conversion + of inputs before input to auto-regressive lstm, + which helps to learn diagonal attentions. + + Notes + ---------- + This module alway applies dropout even in evaluation. + See the detail in `Natural TTS Synthesis by + Conditioning WaveNet on Mel Spectrogram Predictions`_. + + .. _`Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions`: + https://arxiv.org/abs/1712.05884 + + """ + + def __init__(self, idim, n_layers=2, n_units=256, dropout_rate=0.5): + """Initialize prenet module. + + Parameters + ---------- + idim : int + Dimension of the inputs. + odim : int + Dimension of the outputs. + n_layers : int, optional + The number of prenet layers. + n_units : int, optional + The number of prenet units. + """ + super().__init__() + self.dropout_rate = dropout_rate + self.prenet = nn.LayerList() + for layer in six.moves.range(n_layers): + n_inputs = idim if layer == 0 else n_units + self.prenet.append( + nn.Sequential(nn.Linear(n_inputs, n_units), nn.ReLU())) + + def forward(self, x): + """Calculate forward propagation. + + Parameters + ---------- + x : Tensor + Batch of input tensors (B, ..., idim). + + Returns + ---------- + Tensor + Batch of output tensors (B, ..., odim). + + """ + for i in six.moves.range(len(self.prenet)): + # F.dropout 引入了随机, tacotron2 的 dropout 是不能去掉的 + x = F.dropout(self.prenet[i](x)) + return x + + +class Postnet(nn.Layer): + """Postnet module for Spectrogram prediction network. + + This is a module of Postnet in Spectrogram prediction network, + which described in `Natural TTS Synthesis by + Conditioning WaveNet on Mel Spectrogram Predictions`_. + The Postnet predicts refines the predicted + Mel-filterbank of the decoder, + which helps to compensate the detail sturcture of spectrogram. + + .. _`Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions`: + https://arxiv.org/abs/1712.05884 + + """ + + def __init__( + self, + idim, + odim, + n_layers=5, + n_chans=512, + n_filts=5, + dropout_rate=0.5, + use_batch_norm=True, ): + """Initialize postnet module. + + Parameters + ---------- + idim : int + Dimension of the inputs. + odim : int + Dimension of the outputs. + n_layers : int, optional + The number of layers. + n_filts : int, optional + The number of filter size. + n_units : int, optional + The number of filter channels. + use_batch_norm : bool, optional + Whether to use batch normalization.. + dropout_rate : float, optional + Dropout rate.. + """ + super().__init__() + self.postnet = nn.LayerList() + for layer in six.moves.range(n_layers - 1): + ichans = odim if layer == 0 else n_chans + ochans = odim if layer == n_layers - 1 else n_chans + if use_batch_norm: + self.postnet.append( + nn.Sequential( + nn.Conv1D( + ichans, + ochans, + n_filts, + stride=1, + padding=(n_filts - 1) // 2, + bias_attr=False, ), + nn.BatchNorm1D(ochans), + nn.Tanh(), + nn.Dropout(dropout_rate), )) + else: + self.postnet.append( + nn.Sequential( + nn.Conv1D( + ichans, + ochans, + n_filts, + stride=1, + padding=(n_filts - 1) // 2, + bias_attr=False, ), + nn.Tanh(), + nn.Dropout(dropout_rate), )) + ichans = n_chans if n_layers != 1 else odim + if use_batch_norm: + self.postnet.append( + nn.Sequential( + nn.Conv1D( + ichans, + odim, + n_filts, + stride=1, + padding=(n_filts - 1) // 2, + bias_attr=False, ), + nn.BatchNorm1D(odim), + nn.Dropout(dropout_rate), )) + else: + self.postnet.append( + nn.Sequential( + nn.Conv1D( + ichans, + odim, + n_filts, + stride=1, + padding=(n_filts - 1) // 2, + bias_attr=False, ), + nn.Dropout(dropout_rate), )) + + def forward(self, xs): + """Calculate forward propagation. + + Parameters + ---------- + xs : Tensor + Batch of the sequences of padded input tensors (B, idim, Tmax). + + Returns + ---------- + Tensor + Batch of padded output tensor. (B, odim, Tmax). + + """ + for i in six.moves.range(len(self.postnet)): + xs = self.postnet[i](xs) + return xs diff --git a/parakeet/modules/tacotron2/encoder.py b/parakeet/modules/tacotron2/encoder.py new file mode 100644 index 00000000..1e22b769 --- /dev/null +++ b/parakeet/modules/tacotron2/encoder.py @@ -0,0 +1,198 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Tacotron2 encoder related modules.""" + +import six + +import paddle +from paddle import nn + + +class Encoder(nn.Layer): + """Encoder module of Spectrogram prediction network. + + This is a module of encoder of Spectrogram prediction network in Tacotron2, + which described in `Natural TTS Synthesis by Conditioning WaveNet on Mel + Spectrogram Predictions`_. This is the encoder which converts either a sequence + of characters or acoustic features into the sequence of hidden states. + + .. _`Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions`: + https://arxiv.org/abs/1712.05884 + + """ + + def __init__( + self, + idim, + input_layer="embed", + embed_dim=512, + elayers=1, + eunits=512, + econv_layers=3, + econv_chans=512, + econv_filts=5, + use_batch_norm=True, + use_residual=False, + dropout_rate=0.5, + padding_idx=0, ): + """Initialize Tacotron2 encoder module. + + Parameters + ---------- + idim : int + Dimension of the inputs. + input_layer : str + Input layer type. + embed_dim : int, optional + Dimension of character embedding. + elayers : int, optional + The number of encoder blstm layers. + eunits : int, optional + The number of encoder blstm units. + econv_layers : int, optional + The number of encoder conv layers. + econv_filts : int, optional + The number of encoder conv filter size. + econv_chans : int, optional + The number of encoder conv filter channels. + use_batch_norm : bool, optional + Whether to use batch normalization. + use_residual : bool, optional + Whether to use residual connection. + dropout_rate : float, optional + Dropout rate. + + """ + super(Encoder, self).__init__() + # store the hyperparameters + self.idim = idim + self.use_residual = use_residual + + # define network layer modules + if input_layer == "linear": + self.embed = nn.Linear(idim, econv_chans) + elif input_layer == "embed": + self.embed = nn.Embedding(idim, embed_dim, padding_idx=padding_idx) + else: + raise ValueError("unknown input_layer: " + input_layer) + + if econv_layers > 0: + self.convs = nn.LayerList() + for layer in six.moves.range(econv_layers): + ichans = (embed_dim if layer == 0 and input_layer == "embed" + else econv_chans) + if use_batch_norm: + self.convs.append( + nn.Sequential( + nn.Conv1D( + ichans, + econv_chans, + econv_filts, + stride=1, + padding=(econv_filts - 1) // 2, + bias_attr=False, ), + nn.BatchNorm1D(econv_chans), + nn.ReLU(), + nn.Dropout(dropout_rate), )) + else: + self.convs += [ + nn.Sequential( + nn.Conv1D( + ichans, + econv_chans, + econv_filts, + stride=1, + padding=(econv_filts - 1) // 2, + bias_attr=False, ), + nn.ReLU(), + nn.Dropout(dropout_rate), ) + ] + else: + self.convs = None + if elayers > 0: + iunits = econv_chans if econv_layers != 0 else embed_dim + # batch_first=True, bidirectional=True + self.blstm = nn.LSTM( + iunits, + eunits // 2, + elayers, + time_major=False, + direction='bidirectional', + bias_ih_attr=True, + bias_hh_attr=True) + else: + self.blstm = None + + # # initialize + # self.apply(encoder_init) + + def forward(self, xs, ilens=None): + """Calculate forward propagation. + + Parameters + ---------- + xs : Tensor + Batch of the padded sequence. Either character ids (B, Tmax) + or acoustic feature (B, Tmax, idim * encoder_reduction_factor). + Padded value should be 0. + ilens : LongTensor + Batch of lengths of each input batch (B,). + + Returns + ---------- + Tensor + Batch of the sequences of encoder states(B, Tmax, eunits). + LongTensor + Batch of lengths of each sequence (B,) + + """ + xs = self.embed(xs).transpose([0, 2, 1]) + if self.convs is not None: + for i in six.moves.range(len(self.convs)): + if self.use_residual: + xs += self.convs[i](xs) + else: + xs = self.convs[i](xs) + if self.blstm is None: + return xs.transpose([0, 2, 1]) + if not isinstance(ilens, paddle.Tensor): + ilens = paddle.to_tensor(ilens) + xs = xs.transpose([0, 2, 1]) + self.blstm.flatten_parameters() + # (B, Tmax, C) + xs, _ = self.blstm(xs) + # hlens 是什么 + hlens = ilens + + return xs, hlens + + def inference(self, x): + """Inference. + + Parameters + ---------- + x : Tensor + The sequeunce of character ids (T,) + or acoustic feature (T, idim * encoder_reduction_factor). + + Returns + ---------- + Tensor + The sequences of encoder states(T, eunits). + + """ + xs = x.unsqueeze(0) + ilens = paddle.to_tensor([x.shape[0]]) + + return self.forward(xs, ilens)[0][0] diff --git a/parakeet/modules/transformer.py b/parakeet/modules/transformer.py new file mode 100644 index 00000000..696b12b6 --- /dev/null +++ b/parakeet/modules/transformer.py @@ -0,0 +1,207 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from paddle import nn +from parakeet.modules import attention as attn +from paddle.nn import functional as F + +__all__ = [ + "PositionwiseFFN", + "TransformerEncoderLayer", + "TransformerDecoderLayer", +] + + +class PositionwiseFFN(nn.Layer): + """A faithful implementation of Position-wise Feed-Forward Network + in `Attention is All You Need `_. + It is basically a 2-layer MLP, with relu actication and dropout in between. + + Parameters + ---------- + input_size: int + The feature size of the intput. It is also the feature size of the + output. + hidden_size: int + The hidden size. + dropout: float + The probability of the Dropout applied to the output of the first + layer, by default 0. + """ + + def __init__(self, input_size: int, hidden_size: int, dropout=0.0): + super(PositionwiseFFN, self).__init__() + self.linear1 = nn.Linear(input_size, hidden_size) + self.linear2 = nn.Linear(hidden_size, input_size) + self.dropout = nn.Dropout(dropout) + + self.input_size = input_size + self.hidden_szie = hidden_size + + def forward(self, x): + r"""Forward pass of positionwise feed forward network. + + Parameters + ---------- + x : Tensor [shape=(\*, input_size)] + The input tensor, where ``\*`` means arbitary shape. + + Returns + ------- + Tensor [shape=(\*, input_size)] + The output tensor. + """ + l1 = self.dropout(F.relu(self.linear1(x))) + l2 = self.linear2(l1) + return l2 + + +class TransformerEncoderLayer(nn.Layer): + """A faithful implementation of Transformer encoder layer in + `Attention is All You Need `_. + + Parameters + ---------- + d_model :int + The feature size of the input. It is also the feature size of the + output. + n_heads : int + The number of heads of self attention (a ``MultiheadAttention`` + layer). + d_ffn : int + The hidden size of the positional feed forward network (a + ``PositionwiseFFN`` layer). + dropout : float, optional + The probability of the dropout in MultiHeadAttention and + PositionwiseFFN, by default 0. + + Notes + ------ + It uses the PostLN (post layer norm) scheme. + """ + + def __init__(self, d_model, n_heads, d_ffn, dropout=0.): + super(TransformerEncoderLayer, self).__init__() + self.self_mha = attn.MultiheadAttention(d_model, n_heads, dropout) + self.layer_norm1 = nn.LayerNorm([d_model], epsilon=1e-6) + + self.ffn = PositionwiseFFN(d_model, d_ffn, dropout) + self.layer_norm2 = nn.LayerNorm([d_model], epsilon=1e-6) + + self.dropout = dropout + + def forward(self, x, mask): + """Forward pass of TransformerEncoderLayer. + + Parameters + ---------- + x : Tensor [shape=(batch_size, time_steps, d_model)] + The input. + mask : Tensor + The padding mask. The shape is (batch_size, time_steps, + time_steps) or broadcastable shape. + + Returns + ------- + x :Tensor [shape=(batch_size, time_steps, d_model)] + The encoded output. + + attn_weights : Tensor [shape=(batch_size, n_heads, time_steps, time_steps)] + The attention weights of the self attention. + """ + context_vector, attn_weights = self.self_mha(x, x, x, mask) + x = self.layer_norm1( + F.dropout(x + context_vector, self.dropout, training=self.training)) + + x = self.layer_norm2( + F.dropout(x + self.ffn(x), self.dropout, training=self.training)) + return x, attn_weights + + +class TransformerDecoderLayer(nn.Layer): + """A faithful implementation of Transformer decoder layer in + `Attention is All You Need `_. + + Parameters + ---------- + d_model :int + The feature size of the input. It is also the feature size of the + output. + n_heads : int + The number of heads of attentions (``MultiheadAttention`` + layers). + d_ffn : int + The hidden size of the positional feed forward network (a + ``PositionwiseFFN`` layer). + dropout : float, optional + The probability of the dropout in MultiHeadAttention and + PositionwiseFFN, by default 0. + + Notes + ------ + It uses the PostLN (post layer norm) scheme. + """ + + def __init__(self, d_model, n_heads, d_ffn, dropout=0.): + super(TransformerDecoderLayer, self).__init__() + self.self_mha = attn.MultiheadAttention(d_model, n_heads, dropout) + self.layer_norm1 = nn.LayerNorm([d_model], epsilon=1e-6) + + self.cross_mha = attn.MultiheadAttention(d_model, n_heads, dropout) + self.layer_norm2 = nn.LayerNorm([d_model], epsilon=1e-6) + + self.ffn = PositionwiseFFN(d_model, d_ffn, dropout) + self.layer_norm3 = nn.LayerNorm([d_model], epsilon=1e-6) + + self.dropout = dropout + + def forward(self, q, k, v, encoder_mask, decoder_mask): + """Forward pass of TransformerEncoderLayer. + + Parameters + ---------- + q : Tensor [shape=(batch_size, time_steps_q, d_model)] + The decoder input. + k : Tensor [shape=(batch_size, time_steps_k, d_model)] + The keys. + v : Tensor [shape=(batch_size, time_steps_k, d_model)] + The values + encoder_mask : Tensor + Encoder padding mask, shape is ``(batch_size, time_steps_k, + time_steps_k)`` or broadcastable shape. + decoder_mask : Tensor + Decoder mask, shape is ``(batch_size, time_steps_q, time_steps_k)`` + or broadcastable shape. + + Returns + -------- + q : Tensor [shape=(batch_size, time_steps_q, d_model)] + The decoder output. + self_attn_weights : Tensor [shape=(batch_size, n_heads, time_steps_q, time_steps_q)] + Decoder self attention. + + cross_attn_weights : Tensor [shape=(batch_size, n_heads, time_steps_q, time_steps_k)] + Decoder-encoder cross attention. + """ + context_vector, self_attn_weights = self.self_mha(q, q, q, decoder_mask) + q = self.layer_norm1( + F.dropout(q + context_vector, self.dropout, training=self.training)) + + context_vector, cross_attn_weights = self.cross_mha(q, k, v, + encoder_mask) + q = self.layer_norm2( + F.dropout(q + context_vector, self.dropout, training=self.training)) + + q = self.layer_norm3( + F.dropout(q + self.ffn(q), self.dropout, training=self.training)) + return q, self_attn_weights, cross_attn_weights diff --git a/parakeet/training/__init__.py b/parakeet/training/__init__.py new file mode 100644 index 00000000..277171de --- /dev/null +++ b/parakeet/training/__init__.py @@ -0,0 +1,16 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from .cli import * +from .experiment import * diff --git a/parakeet/training/cli.py b/parakeet/training/cli.py new file mode 100644 index 00000000..a6309941 --- /dev/null +++ b/parakeet/training/cli.py @@ -0,0 +1,63 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import argparse + + +def default_argument_parser(): + r"""A simple yet genral argument parser for experiments with parakeet. + + This is used in examples with parakeet. And it is intended to be used by + other experiments with parakeet. It requires a minimal set of command line + arguments to start a training script. + + The ``--config`` and ``--opts`` are used for overwrite the deault + configuration. + + The ``--data`` and ``--output`` specifies the data path and output path. + Resuming training from existing progress at the output directory is the + intended default behavior. + + The ``--checkpoint_path`` specifies the checkpoint to load from. + + The ``--device`` and ``--nprocs`` specifies how to run the training. + + See Also + -------- + parakeet.training.experiment + + Returns + ------- + argparse.ArgumentParser + the parser + """ + parser = argparse.ArgumentParser() + + # yapf: disable + # data and outpu + parser.add_argument("--config", metavar="FILE", help="path of the config file to overwrite to default config with.") + parser.add_argument("--data", metavar="DATA_DIR", help="path to the datatset.") + parser.add_argument("--output", metavar="OUTPUT_DIR", help="path to save checkpoint and logs.") + + # load from saved checkpoint + parser.add_argument("--checkpoint_path", type=str, help="path of the checkpoint to load") + + # running + parser.add_argument("--device", type=str, choices=["cpu", "gpu"], help="device type to use, cpu and gpu are supported.") + parser.add_argument("--nprocs", type=int, default=1, help="number of parallel processes to use.") + + # overwrite extra config and default config + parser.add_argument("--opts", nargs=argparse.REMAINDER, help="options to overwrite --config file and the default config, passing in KEY VALUE pairs") + # yapd: enable + + return parser diff --git a/parakeet/training/default_config.py b/parakeet/training/default_config.py new file mode 100644 index 00000000..7deb795a --- /dev/null +++ b/parakeet/training/default_config.py @@ -0,0 +1,25 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from yacs.config import CfgNode + +_C = CfgNode( + dict( + valid_interval=1000, # validation + save_interval=10000, # checkpoint + max_iteration=900000, # max iteration to train + )) + + +def get_default_training_config(): + return _C.clone() diff --git a/parakeet/training/experiment.py b/parakeet/training/experiment.py new file mode 100644 index 00000000..739fd75d --- /dev/null +++ b/parakeet/training/experiment.py @@ -0,0 +1,303 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import logging +import sys +from pathlib import Path + +import paddle +from paddle import distributed as dist +from paddle.io import DistributedBatchSampler +from visualdl import LogWriter + +from parakeet.utils import checkpoint +from parakeet.utils import mp_tools + +__all__ = ["ExperimentBase"] + + +class ExperimentBase(object): + """ + An experiment template in order to structure the training code and take + care of saving, loading, logging, visualization stuffs. It's intended to + be flexible and simple. + + So it only handles output directory (create directory for the output, + create a checkpoint directory, dump the config in use and create + visualizer and logger) in a standard way without enforcing any + input-output protocols to the model and dataloader. It leaves the main + part for the user to implement their own (setup the model, criterion, + optimizer, define a training step, define a validation function and + customize all the text and visual logs). + + It does not save too much boilerplate code. The users still have to write + the forward/backward/update mannually, but they are free to add + non-standard behaviors if needed. + + We have some conventions to follow. + 1. Experiment should have ``model``, ``optimizer``, ``train_loader`` and + ``valid_loader``, ``config`` and ``args`` attributes. + 2. The config should have a ``training`` field, which has + ``valid_interval``, ``save_interval`` and ``max_iteration`` keys. It is + used as the trigger to invoke validation, checkpointing and stop of the + experiment. + 3. There are four methods, namely ``train_batch``, ``valid``, + ``setup_model`` and ``setup_dataloader`` that should be implemented. + + Feel free to add/overwrite other methods and standalone functions if you + need. + + Parameters + ---------- + config: yacs.config.CfgNode + The configuration used for the experiment. + + args: argparse.Namespace + The parsed command line arguments. + + Examples + -------- + >>> def main_sp(config, args): + >>> exp = Experiment(config, args) + >>> exp.setup() + >>> exe.resume_or_load() + >>> exp.run() + >>> + >>> config = get_cfg_defaults() + >>> parser = default_argument_parser() + >>> args = parser.parse_args() + >>> if args.config: + >>> config.merge_from_file(args.config) + >>> if args.opts: + >>> config.merge_from_list(args.opts) + >>> config.freeze() + >>> + >>> if args.nprocs > 1 and args.device == "gpu": + >>> dist.spawn(main_sp, args=(config, args), nprocs=args.nprocs) + >>> else: + >>> main_sp(config, args) + """ + + def __init__(self, config, args): + self.config = config + self.args = args + + self.model = None + self.optimizer = None + self.iteration = 0 + self.epoch = 0 + self.train_loader = None + self.valid_loader = None + self.iterator = None + self.logger = None + self.visualizer = None + self.output_dir = None + self.checkpoint_dir = None + + def setup(self): + """Setup the experiment. + """ + paddle.set_device(self.args.device) + if self.parallel: + self.init_parallel() + + self.setup_output_dir() + self.dump_config() + self.setup_visualizer() + self.setup_logger() + self.setup_checkpointer() + + self.setup_dataloader() + self.setup_model() + + self.iteration = 0 + self.epoch = 0 + + @property + def parallel(self): + """A flag indicating whether the experiment should run with + multiprocessing. + """ + return self.args.device == "gpu" and self.args.nprocs > 1 + + def init_parallel(self): + """Init environment for multiprocess training. + """ + dist.init_parallel_env() + + @mp_tools.rank_zero_only + def save(self): + """Save checkpoint (model parameters and optimizer states). + """ + checkpoint.save_parameters(self.checkpoint_dir, self.iteration, + self.model, self.optimizer) + + def resume_or_load(self): + """Resume from latest checkpoint at checkpoints in the output + directory or load a specified checkpoint. + + If ``args.checkpoint_path`` is not None, load the checkpoint, else + resume training. + """ + iteration = checkpoint.load_parameters( + self.model, + self.optimizer, + checkpoint_dir=self.checkpoint_dir, + checkpoint_path=self.args.checkpoint_path) + self.iteration = iteration + + def read_batch(self): + """Read a batch from the train_loader. + + Returns + ------- + List[Tensor] + A batch. + """ + try: + batch = next(self.iterator) + except StopIteration: + self.new_epoch() + batch = next(self.iterator) + return batch + + def new_epoch(self): + """Reset the train loader and increment ``epoch``. + """ + self.epoch += 1 + if self.parallel and isinstance(self.train_loader.batch_sampler, + DistributedBatchSampler): + self.train_loader.batch_sampler.set_epoch(self.epoch) + self.iterator = iter(self.train_loader) + + def train(self): + """The training process. + + It includes forward/backward/update and periodical validation and + saving. + """ + self.new_epoch() + while self.iteration < self.config.training.max_iteration: + self.iteration += 1 + self.train_batch() + + if self.iteration % self.config.training.valid_interval == 0: + self.valid() + + if self.iteration % self.config.training.save_interval == 0: + self.save() + + def run(self): + """The routine of the experiment after setup. This method is intended + to be used by the user. + """ + try: + self.train() + except KeyboardInterrupt as exception: + # delete this, because it can not save a complete model + # self.save() + self.close() + sys.exit(exception) + finally: + self.close() + + def setup_output_dir(self): + """Create a directory used for output. + """ + # output dir + output_dir = Path(self.args.output).expanduser() + output_dir.mkdir(parents=True, exist_ok=True) + + self.output_dir = output_dir + + def setup_checkpointer(self): + """Create a directory used to save checkpoints into. + + It is "checkpoints" inside the output directory. + """ + # checkpoint dir + checkpoint_dir = self.output_dir / "checkpoints" + checkpoint_dir.mkdir(exist_ok=True) + + self.checkpoint_dir = checkpoint_dir + + @mp_tools.rank_zero_only + def close(self): + """Close visualizer to avoid hanging after training""" + # https://github.com/pytorch/fairseq/issues/2357 + self.visualizer.close() + + @mp_tools.rank_zero_only + def setup_visualizer(self): + """Initialize a visualizer to log the experiment. + + The visual log is saved in the output directory. + + Notes + ------ + Only the main process has a visualizer with it. Use multiple + visualizers in multiprocess to write to a same log file may cause + unexpected behaviors. + """ + # visualizer + visualizer = LogWriter(logdir=str(self.output_dir)) + + self.visualizer = visualizer + + def setup_logger(self): + """Initialize a text logger to log the experiment. + + Each process has its own text logger. The logging message is write to + the standard output and a text file named ``worker_n.log`` in the + output directory, where ``n`` means the rank of the process. + """ + logger = logging.getLogger(__name__) + logger.setLevel("INFO") + log_file = self.output_dir / 'worker_{}.log'.format(dist.get_rank()) + logger.addHandler(logging.FileHandler(str(log_file))) + + self.logger = logger + + @mp_tools.rank_zero_only + def dump_config(self): + """Save the configuration used for this experiment. + + It is saved in to ``config.yaml`` in the output directory at the + beginning of the experiment. + """ + with open(self.output_dir / "config.yaml", 'wt') as f: + print(self.config, file=f) + + def train_batch(self): + """The training loop. A subclass should implement this method. + """ + raise NotImplementedError("train_batch should be implemented.") + + @mp_tools.rank_zero_only + @paddle.no_grad() + def valid(self): + """The validation. A subclass should implement this method. + """ + raise NotImplementedError("valid should be implemented.") + + def setup_model(self): + """Setup model, criterion and optimizer, etc. A subclass should + implement this method. + """ + raise NotImplementedError("setup_model should be implemented.") + + def setup_dataloader(self): + """Setup training dataloader and validation dataloader. A subclass + should implement this method. + """ + raise NotImplementedError("setup_dataloader should be implemented.") diff --git a/parakeet/training/extension.py b/parakeet/training/extension.py new file mode 100644 index 00000000..07e92696 --- /dev/null +++ b/parakeet/training/extension.py @@ -0,0 +1,79 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from typing import Callable + +PRIORITY_WRITER = 300 +PRIORITY_EDITOR = 200 +PRIORITY_READER = 100 + + +class Extension(object): + """Extension to customize the behavior of Trainer.""" + trigger = (1, 'iteration') + priority = PRIORITY_READER + name = None + + @property + def default_name(self): + """Default name of the extension, class name by default.""" + return type(self).__name__ + + def __call__(self, trainer): + """Main action of the extention. After each update, it is executed + when the trigger fires.""" + raise NotImplementedError( + 'Extension implementation must override __call__.') + + def initialize(self, trainer): + """Action that is executed once to get the corect trainer state. + It is called before training normally, but if the trainer restores + states with an Snapshot extension, this method should also be called.g + """ + pass + + def on_error(self, trainer, exc, tb): + """Handles the error raised during training before finalization. + """ + pass + + def finalize(self, trainer): + """Action that is executed when training is done. + For example, visualizers would need to be closed. + """ + pass + + +def make_extension(trigger: Callable=None, + default_name: str=None, + priority: int=None, + finalizer: Callable=None, + initializer: Callable=None, + on_error: Callable=None): + """Make an Extension-like object by injecting required attributes to it. + """ + if trigger is None: + trigger = Extension.trigger + if priority is None: + priority = Extension.priority + + def decorator(ext): + ext.trigger = trigger + ext.default_name = default_name or ext.__name__ + ext.priority = priority + ext.finalize = finalizer + ext.on_error = on_error + ext.initialize = initializer + return ext + + return decorator diff --git a/parakeet/training/extensions/__init__.py b/parakeet/training/extensions/__init__.py new file mode 100644 index 00000000..abf198b9 --- /dev/null +++ b/parakeet/training/extensions/__init__.py @@ -0,0 +1,13 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/parakeet/training/extensions/evaluator.py b/parakeet/training/extensions/evaluator.py new file mode 100644 index 00000000..47b35272 --- /dev/null +++ b/parakeet/training/extensions/evaluator.py @@ -0,0 +1,71 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from typing import Dict + +import paddle +from paddle.io import DataLoader +from paddle.nn import Layer + +from parakeet.training import extension +from parakeet.training.reporter import DictSummary +from parakeet.training.reporter import report +from parakeet.training.reporter import scope + + +class StandardEvaluator(extension.Extension): + + trigger = (1, 'epoch') + default_name = 'validation' + priority = extension.PRIORITY_WRITER + + name = None + + def __init__(self, model: Layer, dataloader: DataLoader): + # it is designed to hold multiple models + models = {"main": model} + self.models: Dict[str, Layer] = models + self.model = model + + # dataloaders + self.dataloader = dataloader + + def evaluate_core(self, batch): + # compute + self.model(batch) # you may report here + + def evaluate(self): + # switch to eval mode + for layer in self.models.values(): + layer.eval() + + # to average evaluation metrics + summary = DictSummary() + for batch in self.dataloader: + observation = {} + with scope(observation): + # main evaluation computation here. + with paddle.no_grad(): + self.evaluate_core(batch) + summary.add(observation) + summary = summary.compute_mean() + return summary + + def __call__(self, trainer=None): + # evaluate and report the averaged metric to current observation + # if it is used to extend a trainer, the metrics is reported to + # to observation of the trainer + # or otherwise, you can use your own observation + summary = self.evaluate() + for k, v in summary.items(): + report(k, v) diff --git a/parakeet/training/extensions/snapshot.py b/parakeet/training/extensions/snapshot.py new file mode 100644 index 00000000..7806dd6e --- /dev/null +++ b/parakeet/training/extensions/snapshot.py @@ -0,0 +1,111 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import logging +import os +from datetime import datetime +from pathlib import Path +from typing import Any +from typing import Dict +from typing import List + +import jsonlines + +from parakeet.training import extension +from parakeet.training.trainer import Trainer +from parakeet.utils.mp_tools import rank_zero_only + + +def load_records(records_fp): + """Load record files (json lines.)""" + with jsonlines.open(records_fp, 'r') as reader: + records = list(reader) + return records + + +class Snapshot(extension.Extension): + """An extension to make snapshot of the updater object inside + the trainer. It is done by calling the updater's `save` method. + + An Updater save its state_dict by default, which contains the + updater state, (i.e. epoch and iteration) and all the model + parameters and optimizer states. If the updater inside the trainer + subclasses StandardUpdater, everything is good to go. + + Parameters + ---------- + checkpoint_dir : Union[str, Path] + The directory to save checkpoints into. + """ + + trigger = (1, 'epoch') + priority = -100 + default_name = "snapshot" + + def __init__(self, max_size: int=5, snapshot_on_error: bool=False): + self.records: List[Dict[str, Any]] = [] + self.max_size = max_size + self._snapshot_on_error = snapshot_on_error + self._save_all = (max_size == -1) + self.checkpoint_dir = None + + def initialize(self, trainer: Trainer): + """Setting up this extention.""" + self.checkpoint_dir = trainer.out / "checkpoints" + + # load existing records + record_path: Path = self.checkpoint_dir / "records.jsonl" + if record_path.exists(): + logging.debug("Loading from an existing checkpoint dir") + self.records = load_records(record_path) + trainer.updater.load(self.records[-1]['path']) + + def on_error(self, trainer, exc, tb): + if self._snapshot_on_error: + self.save_checkpoint_and_update(trainer) + + def __call__(self, trainer: Trainer): + self.save_checkpoint_and_update(trainer) + + def full(self): + """Whether the number of snapshots it keeps track of is greater + than the max_size.""" + return (not self._save_all) and len(self.records) > self.max_size + + @rank_zero_only + def save_checkpoint_and_update(self, trainer: Trainer): + """Saving new snapshot and remove the oldest snapshot if needed.""" + iteration = trainer.updater.state.iteration + path = self.checkpoint_dir / f"snapshot_iter_{iteration}.pdz" + + # add the new one + trainer.updater.save(path) + record = { + "time": str(datetime.now()), + 'path': str(path.resolve()), # use absolute path + 'iteration': iteration + } + self.records.append(record) + + # remove the earist + if self.full(): + eariest_record = self.records[0] + os.remove(eariest_record["path"]) + self.records.pop(0) + + # update the record file + record_path = self.checkpoint_dir / "records.jsonl" + with jsonlines.open(record_path, 'w') as writer: + for record in self.records: + # jsonlines.open may return a Writer or a Reader + writer.write(record) # pylint: disable=no-member diff --git a/parakeet/training/extensions/visualizer.py b/parakeet/training/extensions/visualizer.py new file mode 100644 index 00000000..1c66ad8d --- /dev/null +++ b/parakeet/training/extensions/visualizer.py @@ -0,0 +1,37 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from parakeet.training import extension +from parakeet.training.trainer import Trainer + + +class VisualDL(extension.Extension): + """A wrapper of visualdl log writer. It assumes that the metrics to be visualized + are all scalars which are recorded into the `.observation` dictionary of the + trainer object. The dictionary is created for each step, thus the visualdl log + writer uses the iteration from the updater's `iteration` as the global step to + add records. + """ + trigger = (1, 'iteration') + default_name = 'visualdl' + priority = extension.PRIORITY_READER + + def __init__(self, writer): + self.writer = writer + + def __call__(self, trainer: Trainer): + for k, v in trainer.observation.items(): + self.writer.add_scalar(k, v, step=trainer.updater.state.iteration) + + def finalize(self, trainer): + self.writer.close() diff --git a/parakeet/training/optimizer.py b/parakeet/training/optimizer.py new file mode 100644 index 00000000..1f5496c0 --- /dev/null +++ b/parakeet/training/optimizer.py @@ -0,0 +1,46 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import paddle + +optim_classes = dict( + adadelta=paddle.optimizer.Adadelta, + adagrad=paddle.optimizer.Adagrad, + adam=paddle.optimizer.Adam, + adamax=paddle.optimizer.Adamax, + adamw=paddle.optimizer.AdamW, + lamb=paddle.optimizer.Lamb, + momentum=paddle.optimizer.Momentum, + rmsprop=paddle.optimizer.RMSProp, + sgd=paddle.optimizer.SGD, ) + + +def build_optimizers(model: paddle.nn.Layer, + optim='adadelta', + max_grad_norm=None, + learning_rate=0.01) -> paddle.optimizer: + optim_class = optim_classes.get(optim) + if optim_class is None: + raise ValueError(f"must be one of {list(optim_classes)}: {optim}") + else: + grad_clip = None + if max_grad_norm: + grad_clip = paddle.nn.ClipGradByGlobalNorm(max_grad_norm) + optim = optim_class( + parameters=model.parameters(), + learning_rate=learning_rate, + grad_clip=grad_clip) + + optimizers = optim + return optimizers diff --git a/parakeet/training/reporter.py b/parakeet/training/reporter.py new file mode 100644 index 00000000..013c754e --- /dev/null +++ b/parakeet/training/reporter.py @@ -0,0 +1,158 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import contextlib +import math +from collections import defaultdict + +OBSERVATIONS = None + + +@contextlib.contextmanager +def scope(observations): + # make `observation` the target to report to. + # it is basically a dictionary that stores temporary observations + global OBSERVATIONS + old = OBSERVATIONS + OBSERVATIONS = observations + + try: + yield + finally: + OBSERVATIONS = old + + +def get_observations(): + global OBSERVATIONS + return OBSERVATIONS + + +def report(name, value): + # a simple function to report named value + # you can use it everywhere, it will get the default target and writ to it + # you can think of it as std.out + observations = get_observations() + if observations is None: + return + else: + observations[name] = value + + +class Summary(object): + """Online summarization of a sequence of scalars. + Summary computes the statistics of given scalars online. + """ + + def __init__(self): + self._x = 0.0 + self._x2 = 0.0 + self._n = 0 + + def add(self, value, weight=1): + """Adds a scalar value. + + Args: + value: Scalar value to accumulate. It is either a NumPy scalar or + a zero-dimensional array (on CPU or GPU). + weight: An optional weight for the value. It is a NumPy scalar or + a zero-dimensional array (on CPU or GPU). + Default is 1 (integer). + + """ + self._x += weight * value + self._x2 += weight * value * value + self._n += weight + + def compute_mean(self): + """Computes the mean.""" + x, n = self._x, self._n + return x / n + + def make_statistics(self): + """Computes and returns the mean and standard deviation values. + + Returns: + tuple: Mean and standard deviation values. + + """ + x, n = self._x, self._n + mean = x / n + var = self._x2 / n - mean * mean + std = math.sqrt(var) + return mean, std + + +class DictSummary(object): + """Online summarization of a sequence of dictionaries. + + ``DictSummary`` computes the statistics of a given set of scalars online. + It only computes the statistics for scalar values and variables of scalar + values in the dictionaries. + + """ + + def __init__(self): + self._summaries = defaultdict(Summary) + + def add(self, d): + """Adds a dictionary of scalars. + + Args: + d (dict): Dictionary of scalars to accumulate. Only elements of + scalars, zero-dimensional arrays, and variables of + zero-dimensional arrays are accumulated. When the value + is a tuple, the second element is interpreted as a weight. + + """ + summaries = self._summaries + for k, v in d.items(): + w = 1 + if isinstance(v, tuple): + w = v[1] + v = v[0] + summaries[k].add(v, weight=w) + + def compute_mean(self): + """Creates a dictionary of mean values. + + It returns a single dictionary that holds a mean value for each entry + added to the summary. + + Returns: + dict: Dictionary of mean values. + + """ + return { + name: summary.compute_mean() + for name, summary in self._summaries.items() + } + + def make_statistics(self): + """Creates a dictionary of statistics. + + It returns a single dictionary that holds mean and standard deviation + values for every entry added to the summary. For an entry of name + ``'key'``, these values are added to the dictionary by names ``'key'`` + and ``'key.std'``, respectively. + + Returns: + dict: Dictionary of statistics of all entries. + + """ + stats = {} + for name, summary in self._summaries.items(): + mean, std = summary.make_statistics() + stats[name] = mean + stats[name + '.std'] = std + + return stats diff --git a/parakeet/training/seeding.py b/parakeet/training/seeding.py new file mode 100644 index 00000000..8ca30fd3 --- /dev/null +++ b/parakeet/training/seeding.py @@ -0,0 +1,26 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import logging +import random + +import numpy as np +import paddle + + +def seed_everything(seed: int): + """Seed paddle, random and np.random to help reproductivity.""" + paddle.seed(seed) + random.seed(seed) + np.random.seed(seed) + logging.debug(f"Set the seed of paddle, random, np.random to {seed}.") diff --git a/parakeet/training/trainer.py b/parakeet/training/trainer.py new file mode 100644 index 00000000..dd4862f5 --- /dev/null +++ b/parakeet/training/trainer.py @@ -0,0 +1,202 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import sys +import traceback +from collections import OrderedDict +from pathlib import Path +from typing import Callable +from typing import List +from typing import Union + +import six + +from parakeet.training.extension import Extension +from parakeet.training.extension import PRIORITY_READER +from parakeet.training.reporter import scope +from parakeet.training.trigger import get_trigger +from parakeet.training.triggers.limit_trigger import LimitTrigger +from parakeet.training.updater import UpdaterBase +from parakeet.utils import profiler + + +class _ExtensionEntry(object): + def __init__(self, extension, trigger, priority): + self.extension = extension + self.trigger = trigger + self.priority = priority + + +class Trainer(object): + def __init__(self, + updater: UpdaterBase, + stop_trigger: Callable=None, + out: Union[str, Path]='result', + extensions: List[Extension]=None, + profiler_options: str=None): + self.updater = updater + self.extensions = OrderedDict() + self.stop_trigger = LimitTrigger(*stop_trigger) + self.out = Path(out) + self.observation = None + self.profiler_options = profiler_options + self._done = False + if extensions: + for ext in extensions: + self.extend(ext) + + @property + def is_before_training(self): + return self.updater.state.iteration == 0 + + def extend(self, extension, name=None, trigger=None, priority=None): + # get name for the extension + # argument \ + # -> extention's name \ + # -> default_name (class name, when it is an object) \ + # -> function name when it is a function \ + # -> error + + if name is None: + name = getattr(extension, 'name', None) + if name is None: + name = getattr(extension, 'default_name', None) + if name is None: + name = getattr(extension, '__name__', None) + if name is None: + raise ValueError("Name is not given for the extension.") + if name == 'training': + raise ValueError("training is a reserved name.") + + if trigger is None: + trigger = getattr(extension, 'trigger', (1, 'iteration')) + trigger = get_trigger(trigger) + + if priority is None: + priority = getattr(extension, 'priority', PRIORITY_READER) + + # add suffix to avoid nameing conflict + ordinal = 0 + modified_name = name + while modified_name in self.extensions: + ordinal += 1 + modified_name = f"{name}_{ordinal}" + extension.name = modified_name + + self.extensions[modified_name] = _ExtensionEntry(extension, trigger, + priority) + + def get_extension(self, name): + """get extension by name.""" + extensions = self.extensions + if name in extensions: + return extensions[name].extension + else: + raise ValueError(f'extension {name} not found') + + def run(self): + if self._done: + raise RuntimeError("Training is already done!.") + + self.out.mkdir(parents=True, exist_ok=True) + + # sort extensions by priorities once + extension_order = sorted( + self.extensions.keys(), + key=lambda name: self.extensions[name].priority, + reverse=True) + extensions = [(name, self.extensions[name]) for name in extension_order] + + # initializing all extensions + for name, entry in extensions: + if hasattr(entry.extension, "initialize"): + entry.extension.initialize(self) + + update = self.updater.update # training step + + stop_trigger = self.stop_trigger + + # display only one progress bar + max_iteration = None + if isinstance(stop_trigger, LimitTrigger): + if stop_trigger.unit == 'epoch': + max_epoch = self.stop_trigger.limit + updates_per_epoch = getattr(self.updater, "updates_per_epoch", + None) + max_iteration = max_epoch * updates_per_epoch if updates_per_epoch else None + else: + max_iteration = self.stop_trigger.limit + + try: + while not stop_trigger(self): + self.observation = {} + # set observation as the report target + # you can use report freely in Updater.update() + + # updating parameters and state + with scope(self.observation): + + update() + if self.profiler_options: + profiler.add_profiler_step(self.profiler_options) + batch_read_time = self.updater.batch_read_time + batch_time = self.updater.batch_time + avg_batch_cost = batch_read_time + batch_time + logger = self.updater.logger + logger.removeHandler(self.updater.filehandler) + msg = self.updater.msg + msg = " iter: {}/{}, ".format(self.updater.state.iteration, + max_iteration) + msg + msg += ", avg_reader_cost: {:.5f} sec, ".format( + batch_read_time + ) + "avg_batch_cost: {:.5f} sec, ".format(avg_batch_cost) + msg += "avg_samples: {}, ".format( + self.updater. + batch_size) + "avg_ips: {:.5f} sequences/sec".format( + self.updater.batch_size / avg_batch_cost) + logger.info(msg) + + # execute extension when necessary + for name, entry in extensions: + if entry.trigger(self): + entry.extension(self) + + # print("###", self.observation) + except Exception as e: + f = sys.stderr + f.write(f"Exception in main training loop: {e}\n") + f.write("Traceback (most recent call last):\n") + traceback.print_tb(sys.exc_info()[2]) + f.write( + "Trainer extensions will try to handle the extension. Then all extensions will finalize." + ) + + # capture the exception in the mian training loop + exc_info = sys.exc_info() + + # try to handle it + for name, entry in extensions: + if hasattr(entry.extension, "on_error"): + try: + entry.extension.on_error(self, e, sys.exc_info()[2]) + except Exception as ee: + f.write(f"Exception in error handler: {ee}\n") + f.write('Traceback (most recent call last):\n') + traceback.print_tb(sys.exc_info()[2]) + + # raise exception in main training loop + six.reraise(*exc_info) + finally: + for name, entry in extensions: + if hasattr(entry.extension, "finalize"): + entry.extension.finalize(self) diff --git a/parakeet/training/trigger.py b/parakeet/training/trigger.py new file mode 100644 index 00000000..aae1d544 --- /dev/null +++ b/parakeet/training/trigger.py @@ -0,0 +1,28 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from parakeet.training.triggers.interval_trigger import IntervalTrigger + + +def never_fail_trigger(trainer): + return False + + +def get_trigger(trigger): + if trigger is None: + return never_fail_trigger + if callable(trigger): + return trigger + else: + trigger = IntervalTrigger(*trigger) + return trigger diff --git a/parakeet/training/triggers/__init__.py b/parakeet/training/triggers/__init__.py new file mode 100644 index 00000000..abf198b9 --- /dev/null +++ b/parakeet/training/triggers/__init__.py @@ -0,0 +1,13 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/parakeet/training/triggers/interval_trigger.py b/parakeet/training/triggers/interval_trigger.py new file mode 100644 index 00000000..98c03684 --- /dev/null +++ b/parakeet/training/triggers/interval_trigger.py @@ -0,0 +1,38 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + + +class IntervalTrigger(object): + """A Predicate to do something every N cycle.""" + + def __init__(self, period: int, unit: str): + if unit not in ("iteration", "epoch"): + raise ValueError("unit should be 'iteration' or 'epoch'") + if period <= 0: + raise ValueError("period should be a positive integer.") + self.period = period + self.unit = unit + self.last_index = None + + def __call__(self, trainer): + if self.last_index is None: + last_index = getattr(trainer.updater.state, self.unit) + self.last_index = last_index + + last_index = self.last_index + index = getattr(trainer.updater.state, self.unit) + fire = index // self.period != last_index // self.period + + self.last_index = index + return fire diff --git a/parakeet/training/triggers/limit_trigger.py b/parakeet/training/triggers/limit_trigger.py new file mode 100644 index 00000000..dd7a135e --- /dev/null +++ b/parakeet/training/triggers/limit_trigger.py @@ -0,0 +1,31 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + + +class LimitTrigger(object): + """A Predicate to decide whether to stop.""" + + def __init__(self, limit: int, unit: str): + if unit not in ("iteration", "epoch"): + raise ValueError("unit should be 'iteration' or 'epoch'") + if limit <= 0: + raise ValueError("limit should be a positive integer.") + self.limit = limit + self.unit = unit + + def __call__(self, trainer): + state = trainer.updater.state + index = getattr(state, self.unit) + fire = index >= self.limit + return fire diff --git a/parakeet/training/triggers/time_trigger.py b/parakeet/training/triggers/time_trigger.py new file mode 100644 index 00000000..aff93825 --- /dev/null +++ b/parakeet/training/triggers/time_trigger.py @@ -0,0 +1,35 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + + +class TimeTrigger(object): + """Trigger based on a fixed time interval. + + This trigger accepts iterations with a given interval time. + + Args: + period (float): Interval time. It is given in seconds. + + """ + + def __init__(self, period): + self._period = period + self._next_time = self._period + + def __call__(self, trainer): + if self._next_time < trainer.elapsed_time: + self._next_time += self._period + return True + else: + return False diff --git a/parakeet/training/updater.py b/parakeet/training/updater.py new file mode 100644 index 00000000..1db3d5f9 --- /dev/null +++ b/parakeet/training/updater.py @@ -0,0 +1,85 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import logging +from dataclasses import dataclass + +import paddle + + +@dataclass +class UpdaterState: + iteration: int = 0 + epoch: int = 0 + + +class UpdaterBase(object): + """An updater is the abstraction of how a model is trained given the + dataloader and the optimizer. + + The `update_core` method is a step in the training loop with only necessary + operations (get a batch, forward and backward, update the parameters). + + Other stuffs are made extensions. Visualization, saving, loading and + periodical validation and evaluation are not considered here. + + But even in such simplist case, things are not that simple. There is an + attempt to standardize this process and requires only the model and + dataset and do all the stuffs automatically. But this may hurt flexibility. + + If we assume a batch yield from the dataloader is just the input to the + model, we will find that some model requires more arguments, or just some + keyword arguments. But this prevents us from over-simplifying it. + + From another perspective, the batch may includes not just the input, but + also the target. But the model's forward method may just need the input. + We can pass a dict or a super-long tuple to the model and let it pick what + it really needs. But this is an abuse of lazy interface. + + After all, we care about how a model is trained. But just how the model is + used for inference. We want to control how a model is trained. We just + don't want to be messed up with other auxiliary code. + + So the best practice is to define a model and define a updater for it. + """ + + def __init__(self, init_state=None): + if init_state is None: + self.state = UpdaterState() + else: + self.state = init_state + + def update(self, batch): + raise NotImplementedError( + "Implement your own `update` method for training a step.") + + def state_dict(self): + state_dict = { + "epoch": self.state.epoch, + "iteration": self.state.iteration, + } + return state_dict + + def set_state_dict(self, state_dict): + self.state.epoch = state_dict["epoch"] + self.state.iteration = state_dict["iteration"] + + def save(self, path): + logging.debug(f"Saving to {path}.") + archive = self.state_dict() + paddle.save(archive, str(path)) + + def load(self, path): + logging.debug(f"Loading from {path}.") + archive = paddle.load(str(path)) + self.set_state_dict(archive) diff --git a/parakeet/training/updaters/__init__.py b/parakeet/training/updaters/__init__.py new file mode 100644 index 00000000..abf198b9 --- /dev/null +++ b/parakeet/training/updaters/__init__.py @@ -0,0 +1,13 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/parakeet/training/updaters/standard_updater.py b/parakeet/training/updaters/standard_updater.py new file mode 100644 index 00000000..ea3ec3fa --- /dev/null +++ b/parakeet/training/updaters/standard_updater.py @@ -0,0 +1,199 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import logging +import time +from typing import Dict +from typing import Optional + +from paddle import Tensor +from paddle.io import DataLoader +from paddle.io import DistributedBatchSampler +from paddle.nn import Layer +from paddle.optimizer import Optimizer +from timer import timer + +from parakeet.training.reporter import report +from parakeet.training.updater import UpdaterBase +from parakeet.training.updater import UpdaterState + + +class StandardUpdater(UpdaterBase): + """An example of over-simplification. Things may not be that simple, but + you can subclass it to fit your need. + """ + + def __init__(self, + model: Layer, + optimizer: Optimizer, + dataloader: DataLoader, + init_state: Optional[UpdaterState]=None): + # it is designed to hold multiple models + models = {"main": model} + self.models: Dict[str, Layer] = models + self.model = model + + # it is designed to hold multiple optimizers + optimizers = {"main": optimizer} + self.optimizer = optimizer + self.optimizers: Dict[str, Optimizer] = optimizers + + # dataloaders + self.dataloader = dataloader + + # init state + if init_state is None: + self.state = UpdaterState() + else: + self.state = init_state + + self.train_iterator = iter(dataloader) + self.batch_read_time = 0 + self.batch_time = 0 + + def update(self): + # We increase the iteration index after updating and before extension. + # Here are the reasons. + + # 0. Snapshotting(as well as other extensions, like visualizer) is + # executed after a step of updating; + # 1. We decide to increase the iteration index after updating and + # before any all extension is executed. + # 3. We do not increase the iteration after extension because we + # prefer a consistent resume behavior, when load from a + # `snapshot_iter_100.pdz` then the next step to train is `101`, + # naturally. But if iteration is increased increased after + # extension(including snapshot), then, a `snapshot_iter_99` is + # loaded. You would need a extra increasing of the iteration idex + # before training to avoid another iteration `99`, which has been + # done before snapshotting. + # 4. Thus iteration index represrnts "currently how mant epochs has + # been done." + # NOTE: use report to capture the correctly value. If you want to + # report the learning rate used for a step, you must report it before + # the learning rate scheduler's step() has been called. In paddle's + # convention, we do not use an extension to change the learning rate. + # so if you want to report it, do it in the updater. + + # Then here comes the next question. When is the proper time to + # increase the epoch index? Since all extensions are executed after + # updating, it is the time that after updating is the proper time to + # increase epoch index. + # 1. If we increase the epoch index before updating, then an extension + # based ot epoch would miss the correct timing. It could only be + # triggerd after an extra updating. + # 2. Theoretically, when an epoch is done, the epoch index should be + # increased. So it would be increase after updating. + # 3. Thus, eppoch index represents "currently how many epochs has been + # done." So it starts from 0. + + # switch to training mode + for layer in self.models.values(): + layer.train() + + # training for a step is implemented here + time_before_read = time.time() + batch = self.read_batch() + time_before_core = time.time() + self.update_core(batch) + self.batch_time = time.time() - time_before_core + self.batch_read_time = time_before_core - time_before_read + if isinstance(batch, dict): + self.batch_size = len(list(batch.items())[0][-1]) + # for pwg + elif isinstance(batch, list): + self.batch_size = batch[0].shape[0] + + self.state.iteration += 1 + if self.updates_per_epoch is not None: + if self.state.iteration % self.updates_per_epoch == 0: + self.state.epoch += 1 + + def update_core(self, batch): + """A simple case for a training step. Basic assumptions are: + Single model; + Single optimizer; + A batch from the dataloader is just the input of the model; + The model return a single loss, or a dict containing serval losses. + Parameters updates at every batch, no gradient accumulation. + """ + loss = self.model(*batch) + + if isinstance(loss, Tensor): + loss_dict = {"main": loss} + else: + # Dict[str, Tensor] + loss_dict = loss + if "main" not in loss_dict: + main_loss = 0 + for loss_item in loss.values(): + main_loss += loss_item + loss_dict["main"] = main_loss + + for name, loss_item in loss_dict.items(): + report(name, float(loss_item)) + + self.optimizer.clear_gradient() + loss_dict["main"].backward() + self.optimizer.update() + + @property + def updates_per_epoch(self): + """Number of updater per epoch, determined by the length of the + dataloader.""" + length_of_dataloader = None + try: + length_of_dataloader = len(self.dataloader) + except TypeError: + logging.debug("This dataloader has no __len__.") + finally: + return length_of_dataloader + + def new_epoch(self): + """Start a new epoch.""" + # NOTE: all batch sampler for distributed training should + # subclass DistributedBatchSampler and implement `set_epoch` method + batch_sampler = self.dataloader.batch_sampler + if isinstance(batch_sampler, DistributedBatchSampler): + batch_sampler.set_epoch(self.state.epoch) + self.train_iterator = iter(self.dataloader) + + def read_batch(self): + """Read a batch from the data loader, auto renew when data is exhausted.""" + with timer() as t: + try: + batch = next(self.train_iterator) + except StopIteration: + self.new_epoch() + batch = next(self.train_iterator) + logging.debug( + f"Read a batch takes {t.elapse}s.") # replace it with logging + return batch + + def state_dict(self): + """State dict of a Updater, model, optimizer and updater state are included.""" + state_dict = super().state_dict() + for name, layer in self.models.items(): + state_dict[f"{name}_params"] = layer.state_dict() + for name, optim in self.optimizers.items(): + state_dict[f"{name}_optimizer"] = optim.state_dict() + return state_dict + + def set_state_dict(self, state_dict): + """Set state dict for a Updater. Parameters of models, states for + optimizers and UpdaterState are restored.""" + for name, layer in self.models.items(): + layer.set_state_dict(state_dict[f"{name}_params"]) + for name, optim in self.optimizers.items(): + optim.set_state_dict(state_dict[f"{name}_optimizer"]) + super().set_state_dict(state_dict) diff --git a/parakeet/utils/__init__.py b/parakeet/utils/__init__.py new file mode 100644 index 00000000..9811f201 --- /dev/null +++ b/parakeet/utils/__init__.py @@ -0,0 +1,19 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from . import checkpoint +from . import display +from . import layer_tools +from . import mp_tools +from . import scheduler diff --git a/parakeet/utils/checkpoint.py b/parakeet/utils/checkpoint.py new file mode 100644 index 00000000..8df791bb --- /dev/null +++ b/parakeet/utils/checkpoint.py @@ -0,0 +1,138 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import os + +import paddle +from paddle import distributed as dist + +from parakeet.utils import mp_tools + +__all__ = ["load_parameters", "save_parameters"] + + +def _load_latest_checkpoint(checkpoint_dir: str) -> int: + """Get the iteration number corresponding to the latest saved checkpoint. + + Args: + checkpoint_dir (str): the directory where checkpoint is saved. + + Returns: + int: the latest iteration number. + """ + checkpoint_record = os.path.join(checkpoint_dir, "checkpoint") + if (not os.path.isfile(checkpoint_record)): + return 0 + + # Fetch the latest checkpoint index. + with open(checkpoint_record, "rt") as handle: + latest_checkpoint = handle.readline().split()[-1] + iteration = int(latest_checkpoint.split("-")[-1]) + + return iteration + + +def _save_checkpoint(checkpoint_dir: str, iteration: int): + """Save the iteration number of the latest model to be checkpointed. + + Args: + checkpoint_dir (str): the directory where checkpoint is saved. + iteration (int): the latest iteration number. + + Returns: + None + """ + checkpoint_record = os.path.join(checkpoint_dir, "checkpoint") + # Update the latest checkpoint index. + with open(checkpoint_record, "wt") as handle: + handle.write("model_checkpoint_path: step-{}".format(iteration)) + + +def load_parameters(model, + optimizer=None, + checkpoint_dir=None, + checkpoint_path=None): + """Load a specific model checkpoint from disk. + + Args: + model (Layer): model to load parameters. + optimizer (Optimizer, optional): optimizer to load states if needed. + Defaults to None. + checkpoint_dir (str, optional): the directory where checkpoint is saved. + checkpoint_path (str, optional): if specified, load the checkpoint + stored in the checkpoint_path and the argument 'checkpoint_dir' will + be ignored. Defaults to None. + + Returns: + iteration (int): number of iterations that the loaded checkpoint has + been trained. + """ + if checkpoint_path is not None: + iteration = int(os.path.basename(checkpoint_path).split("-")[-1]) + elif checkpoint_dir is not None: + iteration = _load_latest_checkpoint(checkpoint_dir) + if iteration == 0: + return iteration + checkpoint_path = os.path.join(checkpoint_dir, + "step-{}".format(iteration)) + else: + raise ValueError( + "At least one of 'checkpoint_dir' and 'checkpoint_path' should be specified!" + ) + + local_rank = dist.get_rank() + + params_path = checkpoint_path + ".pdparams" + model_dict = paddle.load(params_path) + model.set_state_dict(model_dict) + print("[checkpoint] Rank {}: loaded model from {}".format(local_rank, + params_path)) + + optimizer_path = checkpoint_path + ".pdopt" + if optimizer and os.path.isfile(optimizer_path): + optimizer_dict = paddle.load(optimizer_path) + optimizer.set_state_dict(optimizer_dict) + print("[checkpoint] Rank {}: loaded optimizer state from {}".format( + local_rank, optimizer_path)) + + return iteration + + +@mp_tools.rank_zero_only +def save_parameters(checkpoint_dir, iteration, model, optimizer=None): + """Checkpoint the latest trained model parameters. + + Args: + checkpoint_dir (str): the directory where checkpoint is saved. + iteration (int): the latest iteration number. + model (Layer): model to be checkpointed. + optimizer (Optimizer, optional): optimizer to be checkpointed. + Defaults to None. + + Returns: + None + """ + checkpoint_path = os.path.join(checkpoint_dir, "step-{}".format(iteration)) + + model_dict = model.state_dict() + params_path = checkpoint_path + ".pdparams" + paddle.save(model_dict, params_path) + print("[checkpoint] Saved model to {}".format(params_path)) + + if optimizer: + opt_dict = optimizer.state_dict() + optimizer_path = checkpoint_path + ".pdopt" + paddle.save(opt_dict, optimizer_path) + print("[checkpoint] Saved optimzier state to {}".format(optimizer_path)) + + _save_checkpoint(checkpoint_dir, iteration) diff --git a/parakeet/utils/display.py b/parakeet/utils/display.py new file mode 100644 index 00000000..af7d44ea --- /dev/null +++ b/parakeet/utils/display.py @@ -0,0 +1,110 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import librosa.display +import matplotlib.pylab as plt + +__all__ = [ + "plot_alignment", + "plot_spectrogram", + "plot_waveform", + "plot_multihead_alignments", + "plot_multilayer_multihead_alignments", +] + + +def plot_alignment(alignment, title=None): + # alignment: [encoder_steps, decoder_steps) + fig, ax = plt.subplots(figsize=(6, 4)) + im = ax.imshow( + alignment, aspect='auto', origin='lower', interpolation='none') + fig.colorbar(im, ax=ax) + xlabel = 'Decoder timestep' + if title is not None: + xlabel += '\n\n' + title + plt.xlabel(xlabel) + plt.ylabel('Encoder timestep') + plt.tight_layout() + return fig + + +def plot_multihead_alignments(alignments, title=None): + # alignments: [N, encoder_steps, decoder_steps) + num_subplots = alignments.shape[0] + + fig, axes = plt.subplots( + figsize=(6 * num_subplots, 4), + ncols=num_subplots, + sharey=True, + squeeze=True) + for i, ax in enumerate(axes): + im = ax.imshow( + alignments[i], aspect='auto', origin='lower', interpolation='none') + fig.colorbar(im, ax=ax) + xlabel = 'Decoder timestep' + if title is not None: + xlabel += '\n\n' + title + ax.set_xlabel(xlabel) + if i == 0: + ax.set_ylabel('Encoder timestep') + plt.tight_layout() + return fig + + +def plot_multilayer_multihead_alignments(alignments, title=None): + # alignments: [num_layers, num_heads, encoder_steps, decoder_steps) + num_layers, num_heads, *_ = alignments.shape + + fig, axes = plt.subplots( + figsize=(6 * num_heads, 4 * num_layers), + nrows=num_layers, + ncols=num_heads, + sharex=True, + sharey=True, + squeeze=True) + for i, row in enumerate(axes): + for j, ax in enumerate(row): + im = ax.imshow( + alignments[i, j], + aspect='auto', + origin='lower', + interpolation='none') + fig.colorbar(im, ax=ax) + xlabel = 'Decoder timestep' + if title is not None: + xlabel += '\n\n' + title + if i == num_layers - 1: + ax.set_xlabel(xlabel) + if j == 0: + ax.set_ylabel('Encoder timestep') + plt.tight_layout() + return fig + + +def plot_spectrogram(spec): + # spec: [C, T] librosa convention + fig, ax = plt.subplots(figsize=(12, 3)) + im = ax.imshow(spec, aspect="auto", origin="lower", interpolation='none') + plt.colorbar(im, ax=ax) + plt.xlabel("Frames") + plt.ylabel("Channels") + plt.tight_layout() + return fig + + +def plot_waveform(wav, sr=22050): + fig, ax = plt.subplots(figsize=(12, 3)) + im = librosa.display.waveplot(wav, sr=22050) + plt.colorbar(im, ax=ax) + plt.tight_layout() + return fig diff --git a/parakeet/utils/error_rate.py b/parakeet/utils/error_rate.py new file mode 100644 index 00000000..7a9fe5ad --- /dev/null +++ b/parakeet/utils/error_rate.py @@ -0,0 +1,239 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""This module provides functions to calculate error rate in different level. +e.g. wer for word-level, cer for char-level. +""" +import numpy as np + +__all__ = ['word_errors', 'char_errors', 'wer', 'cer'] + + +def _levenshtein_distance(ref, hyp): + """Levenshtein distance is a string metric for measuring the difference + between two sequences. Informally, the levenshtein disctance is defined as + the minimum number of single-character edits (substitutions, insertions or + deletions) required to change one word into the other. We can naturally + extend the edits to word level when calculate levenshtein disctance for + two sentences. + """ + m = len(ref) + n = len(hyp) + + # special case + if ref == hyp: + return 0 + if m == 0: + return n + if n == 0: + return m + + if m < n: + ref, hyp = hyp, ref + m, n = n, m + + # use O(min(m, n)) space + distance = np.zeros((2, n + 1), dtype=np.int32) + + # initialize distance matrix + for j in range(n + 1): + distance[0][j] = j + + # calculate levenshtein distance + for i in range(1, m + 1): + prev_row_idx = (i - 1) % 2 + cur_row_idx = i % 2 + distance[cur_row_idx][0] = i + for j in range(1, n + 1): + if ref[i - 1] == hyp[j - 1]: + distance[cur_row_idx][j] = distance[prev_row_idx][j - 1] + else: + s_num = distance[prev_row_idx][j - 1] + 1 + i_num = distance[cur_row_idx][j - 1] + 1 + d_num = distance[prev_row_idx][j] + 1 + distance[cur_row_idx][j] = min(s_num, i_num, d_num) + + return distance[m % 2][n] + + +def word_errors(reference, hypothesis, ignore_case=False, delimiter=' '): + """Compute the levenshtein distance between reference sequence and + hypothesis sequence in word-level. + + Parameters + ---------- + reference : str + The reference sentence. + hypothesis : str + The hypothesis sentence. + ignore_case : bool + Whether case-sensitive or not. + delimiter : char(str) + Delimiter of input sentences. + + Returns + ---------- + list + Levenshtein distance and word number of reference sentence. + """ + if ignore_case: + reference = reference.lower() + hypothesis = hypothesis.lower() + + ref_words = list(filter(None, reference.split(delimiter))) + hyp_words = list(filter(None, hypothesis.split(delimiter))) + + edit_distance = _levenshtein_distance(ref_words, hyp_words) + return float(edit_distance), len(ref_words) + + +def char_errors(reference, hypothesis, ignore_case=False, remove_space=False): + """Compute the levenshtein distance between reference sequence and + hypothesis sequence in char-level. + + Parameters + ---------- + reference: str + The reference sentence. + hypothesis: str + The hypothesis sentence. + ignore_case: bool + Whether case-sensitive or not. + remove_space: bool + Whether remove internal space characters + + Returns + ---------- + list + Levenshtein distance and length of reference sentence. + """ + if ignore_case: + reference = reference.lower() + hypothesis = hypothesis.lower() + + join_char = ' ' + if remove_space: + join_char = '' + + reference = join_char.join(list(filter(None, reference.split(' ')))) + hypothesis = join_char.join(list(filter(None, hypothesis.split(' ')))) + + edit_distance = _levenshtein_distance(reference, hypothesis) + return float(edit_distance), len(reference) + + +def wer(reference, hypothesis, ignore_case=False, delimiter=' '): + """Calculate word error rate (WER). WER compares reference text and + hypothesis text in word-level. WER is defined as: + .. math:: + WER = (Sw + Dw + Iw) / Nw + where + .. code-block:: text + Sw is the number of words subsituted, + Dw is the number of words deleted, + Iw is the number of words inserted, + Nw is the number of words in the reference + We can use levenshtein distance to calculate WER. Please draw an attention + that empty items will be removed when splitting sentences by delimiter. + + Parameters + ---------- + reference: str + The reference sentence. + + hypothesis: str + The hypothesis sentence. + ignore_case: bool + Whether case-sensitive or not. + delimiter: char + Delimiter of input sentences. + + Returns + ---------- + float + Word error rate. + + Raises + ---------- + ValueError + If word number of reference is zero. + """ + edit_distance, ref_len = word_errors(reference, hypothesis, ignore_case, + delimiter) + + if ref_len == 0: + raise ValueError("Reference's word number should be greater than 0.") + + wer = float(edit_distance) / ref_len + return wer + + +def cer(reference, hypothesis, ignore_case=False, remove_space=False): + """Calculate charactor error rate (CER). CER compares reference text and + hypothesis text in char-level. CER is defined as: + .. math:: + CER = (Sc + Dc + Ic) / Nc + where + .. code-block:: text + Sc is the number of characters substituted, + Dc is the number of characters deleted, + Ic is the number of characters inserted + Nc is the number of characters in the reference + We can use levenshtein distance to calculate CER. Chinese input should be + encoded to unicode. Please draw an attention that the leading and tailing + space characters will be truncated and multiple consecutive space + characters in a sentence will be replaced by one space character. + + Parameters + ---------- + reference: str + The reference sentence. + hypothesis: str + The hypothesis sentence. + ignore_case: bool + Whether case-sensitive or not. + remove_space: bool + Whether remove internal space characters + + Returns + ---------- + float + Character error rate. + + Raises + ---------- + ValueError + If the reference length is zero. + """ + edit_distance, ref_len = char_errors(reference, hypothesis, ignore_case, + remove_space) + + if ref_len == 0: + raise ValueError("Length of reference should be greater than 0.") + + cer = float(edit_distance) / ref_len + return cer + + +if __name__ == "__main__": + reference = [ + 'j', 'iou4', 'zh', 'e4', 'iang5', 'x', 'v2', 'b', 'o1', 'k', 'ai1', + 'sh', 'iii3', 'l', 'e5', 'b', 'ei3', 'p', 'iao1', 'sh', 'eng1', 'ia2' + ] + hypothesis = [ + 'j', 'iou4', 'zh', 'e4', 'iang4', 'x', 'v2', 'b', 'o1', 'k', 'ai1', + 'sh', 'iii3', 'l', 'e5', 'b', 'ei3', 'p', 'iao1', 'sh', 'eng1', 'ia2' + ] + reference = " ".join(reference) + hypothesis = " ".join(hypothesis) + print(wer(reference, hypothesis)) diff --git a/parakeet/utils/h5_utils.py b/parakeet/utils/h5_utils.py new file mode 100644 index 00000000..d0e277db --- /dev/null +++ b/parakeet/utils/h5_utils.py @@ -0,0 +1,105 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import logging +import sys +from pathlib import Path +from typing import Any +from typing import Union + +import h5py +import numpy as np + + +def read_hdf5(filename: Union[Path, str], dataset_name: str) -> Any: + """Read a dataset from a HDF5 file. + + Parameters + ---------- + filename : Union[Path, str] + Path of the HDF5 file. + dataset_name : str + Name of the dataset to read. + + Returns + ------- + Any + The retrieved dataset. + """ + filename = Path(filename) + + if not filename.exists(): + logging.error(f"There is no such a hdf5 file ({filename}).") + sys.exit(1) + + hdf5_file = h5py.File(filename, "r") + + if dataset_name not in hdf5_file: + logging.error(f"There is no such a data in hdf5 file. ({dataset_name})") + sys.exit(1) + + # [()]: a special syntax of h5py to get the dataset as-is + hdf5_data = hdf5_file[dataset_name][()] + hdf5_file.close() + + return hdf5_data + + +def write_hdf5(filename: Union[Path, str], + dataset_name: str, + write_data: np.ndarray, + is_overwrite: bool=True) -> None: + """Write dataset to HDF5 file. + + Parameters + ---------- + filename : Union[Path, str] + Path of the HDF5 file. + dataset_name : str + Name of the dataset to write to. + write_data : np.ndarrays + The data to write. + is_overwrite : bool, optional + Whether to overwrite, by default True + """ + # convert to numpy array + filename = Path(filename) + write_data = np.array(write_data) + + # check folder existence + filename.parent.mkdir(parents=True, exist_ok=True) + + # check hdf5 existence + if filename.exists(): + # if already exists, open with r+ mode + hdf5_file = h5py.File(filename, "r+") + # check dataset existence + if dataset_name in hdf5_file: + if is_overwrite: + logging.warning("Dataset in hdf5 file already exists. " + "recreate dataset in hdf5.") + hdf5_file.__delitem__(dataset_name) + else: + logging.error( + "Dataset in hdf5 file already exists. " + "if you want to overwrite, please set is_overwrite = True.") + hdf5_file.close() + sys.exit(1) + else: + # if not exists, open with w mode + hdf5_file = h5py.File(filename, "w") + + # write data to hdf5 + hdf5_file.create_dataset(dataset_name, data=write_data) + hdf5_file.flush() + hdf5_file.close() diff --git a/parakeet/utils/internals.py b/parakeet/utils/internals.py new file mode 100644 index 00000000..6c10bd2d --- /dev/null +++ b/parakeet/utils/internals.py @@ -0,0 +1,52 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import numpy as np +from paddle.framework import core + +__all__ = ["convert_dtype_to_np_dtype_"] + + +def convert_dtype_to_np_dtype_(dtype): + """ + Convert paddle's data type to corrsponding numpy data type. + + Args: + dtype(np.dtype): the data type in paddle. + + Returns: + type: the data type in numpy. + + """ + if dtype is core.VarDesc.VarType.FP32: + return np.float32 + elif dtype is core.VarDesc.VarType.FP64: + return np.float64 + elif dtype is core.VarDesc.VarType.FP16: + return np.float16 + elif dtype is core.VarDesc.VarType.BOOL: + return np.bool + elif dtype is core.VarDesc.VarType.INT32: + return np.int32 + elif dtype is core.VarDesc.VarType.INT64: + return np.int64 + elif dtype is core.VarDesc.VarType.INT16: + return np.int16 + elif dtype is core.VarDesc.VarType.INT8: + return np.int8 + elif dtype is core.VarDesc.VarType.UINT8: + return np.uint8 + elif dtype is core.VarDesc.VarType.BF16: + return np.uint16 + else: + raise ValueError("Not supported dtype %s" % dtype) diff --git a/parakeet/utils/layer_tools.py b/parakeet/utils/layer_tools.py new file mode 100644 index 00000000..6e971f98 --- /dev/null +++ b/parakeet/utils/layer_tools.py @@ -0,0 +1,56 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import numpy as np +from paddle import nn + +__all__ = ["summary", "gradient_norm", "freeze", "unfreeze"] + + +def summary(layer: nn.Layer): + num_params = num_elements = 0 + print("layer summary:") + for name, param in layer.state_dict().items(): + print("{}|{}|{}".format(name, param.shape, np.prod(param.shape))) + num_elements += np.prod(param.shape) + num_params += 1 + print("layer has {} parameters, {} elements.".format(num_params, + num_elements)) + + +def gradient_norm(layer: nn.Layer): + grad_norm_dict = {} + for name, param in layer.state_dict().items(): + if param.trainable: + grad = param.gradient() + grad_norm_dict[name] = np.linalg.norm(grad) / grad.size + return grad_norm_dict + + +def recursively_remove_weight_norm(layer: nn.Layer): + for layer in layer.sublayers(): + try: + nn.utils.remove_weight_norm(layer) + except Exception as e: + # ther is not weight norm hoom in this layer + pass + + +def freeze(layer: nn.Layer): + for param in layer.parameters(): + param.trainable = False + + +def unfreeze(layer: nn.Layer): + for param in layer.parameters(): + param.trainable = True diff --git a/parakeet/utils/mp_tools.py b/parakeet/utils/mp_tools.py new file mode 100644 index 00000000..ed8c83ee --- /dev/null +++ b/parakeet/utils/mp_tools.py @@ -0,0 +1,29 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from functools import wraps + +from paddle import distributed as dist + +__all__ = ["rank_zero_only"] + + +def rank_zero_only(func): + @wraps(func) + def wrapper(*args, **kwargs): + if dist.get_rank() != 0: + return + result = func(*args, **kwargs) + return result + + return wrapper diff --git a/parakeet/utils/profile.py b/parakeet/utils/profile.py new file mode 100644 index 00000000..5f9b4952 --- /dev/null +++ b/parakeet/utils/profile.py @@ -0,0 +1,34 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from contextlib import contextmanager + +import paddle +from paddle.framework import core +from paddle.framework import CUDAPlace + + +def synchronize(): + """Trigger cuda synchronization for better timing.""" + place = paddle.fluid.framework._current_expected_place() + if isinstance(place, CUDAPlace): + paddle.fluid.core._cuda_synchronize(place) + + +@contextmanager +def nvtx_span(name): + try: + core.nvprof_nvtx_push(name) + yield + finally: + core.nvprof_nvtx_pop() diff --git a/parakeet/utils/profiler.py b/parakeet/utils/profiler.py new file mode 100644 index 00000000..e64afd6a --- /dev/null +++ b/parakeet/utils/profiler.py @@ -0,0 +1,110 @@ +# copyright (c) 2021 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import sys +import paddle + +# A global variable to record the number of calling times for profiler +# functions. It is used to specify the tracing range of training steps. +_profiler_step_id = 0 + +# A global variable to avoid parsing from string every time. +_profiler_options = None + + +class ProfilerOptions(object): + ''' + Use a string to initialize a ProfilerOptions. + The string should be in the format: "key1=value1;key2=value;key3=value3". + For example: + "profile_path=model.profile" + "batch_range=[50, 60]; profile_path=model.profile" + "batch_range=[50, 60]; tracer_option=OpDetail; profile_path=model.profile" + ProfilerOptions supports following key-value pair: + batch_range - a integer list, e.g. [100, 110]. + state - a string, the optional values are 'CPU', 'GPU' or 'All'. + sorted_key - a string, the optional values are 'calls', 'total', + 'max', 'min' or 'ave. + tracer_option - a string, the optional values are 'Default', 'OpDetail', + 'AllOpDetail'. + profile_path - a string, the path to save the serialized profile data, + which can be used to generate a timeline. + exit_on_finished - a boolean. + ''' + + def __init__(self, options_str): + assert isinstance(options_str, str) + + self._options = { + 'batch_range': [10, 20], + 'state': 'All', + 'sorted_key': 'total', + 'tracer_option': 'Default', + 'profile_path': '/tmp/profile', + 'exit_on_finished': True + } + self._parse_from_string(options_str) + + def _parse_from_string(self, options_str): + for kv in options_str.replace(' ', '').split(';'): + key, value = kv.split('=') + if key == 'batch_range': + value_list = value.replace('[', '').replace(']', '').split(',') + value_list = list(map(int, value_list)) + if len(value_list) >= 2 and value_list[0] >= 0 and value_list[ + 1] > value_list[0]: + self._options[key] = value_list + elif key == 'exit_on_finished': + self._options[key] = value.lower() in ("yes", "true", "t", "1") + elif key in [ + 'state', 'sorted_key', 'tracer_option', 'profile_path' + ]: + self._options[key] = value + + def __getitem__(self, name): + if self._options.get(name, None) is None: + raise ValueError( + "ProfilerOptions does not have an option named %s." % name) + return self._options[name] + + +def add_profiler_step(options_str=None): + ''' + Enable the operator-level timing using PaddlePaddle's profiler. + The profiler uses a independent variable to count the profiler steps. + One call of this function is treated as a profiler step. + + Args: + profiler_options - a string to initialize the ProfilerOptions. + Default is None, and the profiler is disabled. + ''' + if options_str is None: + return + + global _profiler_step_id + global _profiler_options + + if _profiler_options is None: + _profiler_options = ProfilerOptions(options_str) + + if _profiler_step_id == _profiler_options['batch_range'][0]: + paddle.utils.profiler.start_profiler(_profiler_options['state'], + _profiler_options['tracer_option']) + elif _profiler_step_id == _profiler_options['batch_range'][1]: + paddle.utils.profiler.stop_profiler(_profiler_options['sorted_key'], + _profiler_options['profile_path']) + if _profiler_options['exit_on_finished']: + sys.exit(0) + + _profiler_step_id += 1 diff --git a/parakeet/utils/scheduler.py b/parakeet/utils/scheduler.py new file mode 100644 index 00000000..9338995a --- /dev/null +++ b/parakeet/utils/scheduler.py @@ -0,0 +1,73 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +__all__ = ["SchedulerBase", "Constant", "PieceWise", "StepWise"] + + +class SchedulerBase(object): + def __call__(self, step): + raise NotImplementedError("You should implement the __call__ method.") + + +class Constant(SchedulerBase): + def __init__(self, value): + self.value = value + + def __call__(self, step): + return self.value + + +class PieceWise(SchedulerBase): + def __init__(self, anchors): + anchors = list(anchors) + anchors = sorted(anchors, key=lambda x: x[0]) + assert anchors[0][0] == 0, "it must start from zero" + self.xs = [item[0] for item in anchors] + self.ys = [item[1] for item in anchors] + self.num_anchors = len(self.xs) + + def __call__(self, step): + i = 0 + for x in self.xs: + if step >= x: + i += 1 + if i == 0: + return self.ys[0] + if i == self.num_anchors: + return self.ys[-1] + k = (self.ys[i] - self.ys[i - 1]) / (self.xs[i] - self.xs[i - 1]) + out = self.ys[i - 1] + (step - self.xs[i - 1]) * k + return out + + +class StepWise(SchedulerBase): + def __init__(self, anchors): + anchors = list(anchors) + anchors = sorted(anchors, key=lambda x: x[0]) + assert anchors[0][0] == 0, "it must start from zero" + self.xs = [item[0] for item in anchors] + self.ys = [item[1] for item in anchors] + self.num_anchors = len(self.xs) + + def __call__(self, step): + i = 0 + for x in self.xs: + if step >= x: + i += 1 + + if i == self.num_anchors: + return self.ys[-1] + if i == 0: + return self.ys[0] + return self.ys[i - 1] diff --git a/parakeet/utils/timeline.py b/parakeet/utils/timeline.py new file mode 100644 index 00000000..0a5509db --- /dev/null +++ b/parakeet/utils/timeline.py @@ -0,0 +1,315 @@ +# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import argparse +import json + +import paddle.fluid.proto.profiler.profiler_pb2 as profiler_pb2 +import six + +parser = argparse.ArgumentParser(description=__doc__) +parser.add_argument( + '--profile_path', + type=str, + default='', + help='Input profile file name. If there are multiple file, the format ' + 'should be trainer1=file1,trainer2=file2,ps=file3') +parser.add_argument( + '--timeline_path', type=str, default='', help='Output timeline file name.') +args = parser.parse_args() + + +class _ChromeTraceFormatter(object): + def __init__(self): + self._events = [] + self._metadata = [] + + def _create_event(self, ph, category, name, pid, tid, timestamp): + """Creates a new Chrome Trace event. + + For details of the file format, see: + https://github.com/catapult-project/catapult/blob/master/tracing/README.md + + Args: + ph: The type of event - usually a single character. + category: The event category as a string. + name: The event name as a string. + pid: Identifier of the process generating this event as an integer. + tid: Identifier of the thread generating this event as an integer. + timestamp: The timestamp of this event as a long integer. + + Returns: + A JSON compatible event object. + """ + event = {} + event['ph'] = ph + event['cat'] = category + event['name'] = name.replace("ParallelExecutor::Run/", "") + event['pid'] = pid + event['tid'] = tid + event['ts'] = timestamp + return event + + def emit_pid(self, name, pid): + """Adds a process metadata event to the trace. + + Args: + name: The process name as a string. + pid: Identifier of the process as an integer. + """ + event = {} + event['name'] = 'process_name' + event['ph'] = 'M' + event['pid'] = pid + event['args'] = {'name': name} + self._metadata.append(event) + + def emit_region(self, timestamp, duration, pid, tid, category, name, args): + """Adds a region event to the trace. + + Args: + timestamp: The start timestamp of this region as a long integer. + duration: The duration of this region as a long integer. + pid: Identifier of the process generating this event as an integer. + tid: Identifier of the thread generating this event as an integer. + category: The event category as a string. + name: The event name as a string. + args: A JSON-compatible dictionary of event arguments. + """ + event = self._create_event('X', category, name, pid, tid, timestamp) + event['dur'] = duration + event['args'] = args + self._events.append(event) + + def emit_counter(self, category, name, pid, timestamp, counter, value): + """Emits a record for a single counter. + + Args: + category: The event category as string + name: The event name as string + pid: Identifier of the process generating this event as integer + timestamp: The timestamps of this event as long integer + counter: Name of the counter as string + value: Value of the counter as integer + tid: Thread id of the allocation as integer + """ + event = self._create_event('C', category, name, pid, 0, timestamp) + event['args'] = {counter: value} + self._events.append(event) + + def format_to_string(self, pretty=False): + """Formats the chrome trace to a string. + + Args: + pretty: (Optional.) If True, produce human-readable JSON output. + + Returns: + A JSON-formatted string in Chrome Trace format. + """ + trace = {} + trace['traceEvents'] = self._metadata + self._events + if pretty: + return json.dumps(trace, indent=4, separators=(',', ': ')) + else: + return json.dumps(trace, separators=(',', ':')) + + +class Timeline(object): + def __init__(self, profile_dict): + self._profile_dict = profile_dict + self._pid = 0 + self._devices = dict() + self._mem_devices = dict() + self._chrome_trace = _ChromeTraceFormatter() + + def _allocate_pid(self): + cur_pid = self._pid + self._pid += 1 + return cur_pid + + def _allocate_pids(self): + for k, profile_pb in six.iteritems(self._profile_dict): + for event in profile_pb.events: + if event.type == profiler_pb2.Event.CPU: + if (k, event.device_id, "CPU") not in self._devices: + pid = self._allocate_pid() + self._devices[(k, event.device_id, "CPU")] = pid + # -1 device id represents CUDA API(RunTime) call.(e.g. cudaLaunch, cudaMemcpy) + if event.device_id == -1: + self._chrome_trace.emit_pid("%s:cuda_api" % k, pid) + else: + self._chrome_trace.emit_pid( + "%s:cpu:block:%d" % (k, event.device_id), pid) + elif event.type == profiler_pb2.Event.GPUKernel: + if (k, event.device_id, "GPUKernel") not in self._devices: + pid = self._allocate_pid() + self._devices[(k, event.device_id, "GPUKernel")] = pid + self._chrome_trace.emit_pid("%s:gpu:%d" % + (k, event.device_id), pid) + if not hasattr(profile_pb, "mem_events"): + continue + for mevent in profile_pb.mem_events: + if mevent.place == profiler_pb2.MemEvent.CUDAPlace: + if (k, mevent.device_id, "GPU") not in self._mem_devices: + pid = self._allocate_pid() + self._mem_devices[(k, mevent.device_id, "GPU")] = pid + self._chrome_trace.emit_pid( + "memory usage on %s:gpu:%d" % (k, mevent.device_id), + pid) + elif mevent.place == profiler_pb2.MemEvent.CPUPlace: + if (k, mevent.device_id, "CPU") not in self._mem_devices: + pid = self._allocate_pid() + self._mem_devices[(k, mevent.device_id, "CPU")] = pid + self._chrome_trace.emit_pid( + "memory usage on %s:cpu:%d" % (k, mevent.device_id), + pid) + elif mevent.place == profiler_pb2.MemEvent.CUDAPinnedPlace: + if (k, mevent.device_id, + "CUDAPinnedPlace") not in self._mem_devices: + pid = self._allocate_pid() + self._mem_devices[(k, mevent.device_id, + "CUDAPinnedPlace")] = pid + self._chrome_trace.emit_pid( + "memory usage on %s:cudapinnedplace:%d" % + (k, mevent.device_id), pid) + elif mevent.place == profiler_pb2.MemEvent.NPUPlace: + if (k, mevent.device_id, "NPU") not in self._mem_devices: + pid = self._allocate_pid() + self._mem_devices[(k, mevent.device_id, "NPU")] = pid + self._chrome_trace.emit_pid( + "memory usage on %s:npu:%d" % (k, mevent.device_id), + pid) + if (k, 0, "CPU") not in self._mem_devices: + pid = self._allocate_pid() + self._mem_devices[(k, 0, "CPU")] = pid + self._chrome_trace.emit_pid("memory usage on %s:cpu:%d" % + (k, 0), pid) + if (k, 0, "GPU") not in self._mem_devices: + pid = self._allocate_pid() + self._mem_devices[(k, 0, "GPU")] = pid + self._chrome_trace.emit_pid("memory usage on %s:gpu:%d" % + (k, 0), pid) + if (k, 0, "CUDAPinnedPlace") not in self._mem_devices: + pid = self._allocate_pid() + self._mem_devices[(k, 0, "CUDAPinnedPlace")] = pid + self._chrome_trace.emit_pid( + "memory usage on %s:cudapinnedplace:%d" % (k, 0), pid) + if (k, 0, "NPU") not in self._mem_devices: + pid = self._allocate_pid() + self._mem_devices[(k, 0, "NPU")] = pid + self._chrome_trace.emit_pid("memory usage on %s:npu:%d" % + (k, 0), pid) + + def _allocate_events(self): + for k, profile_pb in six.iteritems(self._profile_dict): + for event in profile_pb.events: + if event.type == profiler_pb2.Event.CPU: + type = "CPU" + elif event.type == profiler_pb2.Event.GPUKernel: + type = "GPUKernel" + pid = self._devices[(k, event.device_id, type)] + args = {'name': event.name} + if event.memcopy.bytes > 0: + args['mem_bytes'] = event.memcopy.bytes + if hasattr(event, "detail_info") and event.detail_info: + args['detail_info'] = event.detail_info + # TODO(panyx0718): Chrome tracing only handles ms. However, some + # ops takes micro-seconds. Hence, we keep the ns here. + self._chrome_trace.emit_region( + event.start_ns, (event.end_ns - event.start_ns) / 1.0, pid, + event.sub_device_id, 'Op', event.name, args) + + def _allocate_memory_event(self): + if not hasattr(profiler_pb2, "MemEvent"): + return + place_to_str = { + profiler_pb2.MemEvent.CPUPlace: "CPU", + profiler_pb2.MemEvent.CUDAPlace: "GPU", + profiler_pb2.MemEvent.CUDAPinnedPlace: "CUDAPinnedPlace", + profiler_pb2.MemEvent.NPUPlace: "NPU" + } + for k, profile_pb in six.iteritems(self._profile_dict): + mem_list = [] + end_profiler = 0 + for mevent in profile_pb.mem_events: + crt_info = dict() + crt_info['time'] = mevent.start_ns + crt_info['size'] = mevent.bytes + if mevent.place in place_to_str: + place = place_to_str[mevent.place] + else: + place = "UnDefine" + crt_info['place'] = place + pid = self._mem_devices[(k, mevent.device_id, place)] + crt_info['pid'] = pid + crt_info['thread_id'] = mevent.thread_id + crt_info['device_id'] = mevent.device_id + mem_list.append(crt_info) + crt_info = dict() + crt_info['place'] = place + crt_info['pid'] = pid + crt_info['thread_id'] = mevent.thread_id + crt_info['device_id'] = mevent.device_id + crt_info['time'] = mevent.end_ns + crt_info['size'] = -mevent.bytes + mem_list.append(crt_info) + end_profiler = max(end_profiler, crt_info['time']) + mem_list.sort(key=lambda tmp: (tmp.get('time', 0))) + i = 0 + total_size = 0 + while i < len(mem_list): + total_size += mem_list[i]['size'] + while i < len(mem_list) - 1 and mem_list[i]['time'] == mem_list[ + i + 1]['time']: + total_size += mem_list[i + 1]['size'] + i += 1 + + self._chrome_trace.emit_counter( + "Memory", "Memory", mem_list[i]['pid'], mem_list[i]['time'], + 0, total_size) + i += 1 + + def generate_chrome_trace(self): + self._allocate_pids() + self._allocate_events() + self._allocate_memory_event() + return self._chrome_trace.format_to_string() + + +profile_path = '/tmp/profile' +if args.profile_path: + profile_path = args.profile_path +timeline_path = '/tmp/timeline' +if args.timeline_path: + timeline_path = args.timeline_path + +profile_paths = profile_path.split(',') +profile_dict = dict() +if len(profile_paths) == 1: + with open(profile_path, 'rb') as f: + profile_s = f.read() + profile_pb = profiler_pb2.Profile() + profile_pb.ParseFromString(profile_s) + profile_dict['trainer'] = profile_pb +else: + for profile_path in profile_paths: + k, v = profile_path.split('=') + with open(v, 'rb') as f: + profile_s = f.read() + profile_pb = profiler_pb2.Profile() + profile_pb.ParseFromString(profile_s) + profile_dict[k] = profile_pb + +tl = Timeline(profile_dict) +with open(timeline_path, 'w') as f: + f.write(tl.generate_chrome_trace()) diff --git a/setup.py b/setup.py new file mode 100644 index 00000000..34dcd919 --- /dev/null +++ b/setup.py @@ -0,0 +1,99 @@ +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import io +import os +import re + +from setuptools import find_packages +from setuptools import setup + + +def read(*names, **kwargs): + with io.open( + os.path.join(os.path.dirname(__file__), *names), + encoding=kwargs.get("encoding", "utf8")) as fp: + return fp.read() + + +def find_version(*file_paths): + version_file = read(*file_paths) + version_match = re.search(r"^__version__ = ['\"]([^'\"]*)['\"]", + version_file, re.M) + if version_match: + return version_match.group(1) + raise RuntimeError("Unable to find version string.") + + +VERSION = find_version('parakeet', '__init__.py') +long_description = read("README.md") + +setup_info = dict( + # Metadata + name='paddle-parakeet', + version=VERSION, + author='PaddleSL Team', + author_email='', + url='https://github.com/PaddlePaddle', + description='Speech synthesis tools and models based on Paddlepaddle', + long_description=long_description, + long_description_content_type="text/markdown", + license='Apache 2', + python_requires='>=3.6', + install_requires=[ + 'numpy', + 'nltk', + 'inflect', + 'librosa', + 'unidecode', + 'numba', + 'tqdm', + 'llvmlite', + 'matplotlib', + 'visualdl==2.2.0', + 'scipy', + 'pandas', + 'sox', + 'soundfile~=0.10', + 'g2p_en', + 'yacs', + 'pypinyin', + 'webrtcvad', + 'g2pM', + 'praatio~=4.1', + "h5py", + "timer", + 'jsonlines', + 'pyworld', + 'typeguard', + 'jieba', + "phkit", + ], + extras_require={ + 'doc': ["sphinx", "sphinx-rtd-theme", "numpydoc"], + }, + + # Package info + packages=find_packages(exclude=('tests', 'tests.*')), + zip_safe=True, + classifiers=[ + 'Development Status :: 4 - Beta', + 'Intended Audience :: Developers', + 'Intended Audience :: Science/Research', + 'Topic :: Scientific/Engineering :: Artificial Intelligence', + 'License :: OSI Approved :: Apache Software License', + 'Programming Language :: Python :: 3.6', + 'Programming Language :: Python :: 3.7', + ], ) + +setup(**setup_info) diff --git a/tests/benchmark/README.md b/tests/benchmark/conformer/README.md similarity index 100% rename from tests/benchmark/README.md rename to tests/benchmark/conformer/README.md diff --git a/tests/benchmark/analysis.py b/tests/benchmark/conformer/analysis.py similarity index 100% rename from tests/benchmark/analysis.py rename to tests/benchmark/conformer/analysis.py diff --git a/tests/benchmark/prepare.sh b/tests/benchmark/conformer/prepare.sh similarity index 100% rename from tests/benchmark/prepare.sh rename to tests/benchmark/conformer/prepare.sh diff --git a/tests/benchmark/run.sh b/tests/benchmark/conformer/run.sh similarity index 100% rename from tests/benchmark/run.sh rename to tests/benchmark/conformer/run.sh diff --git a/tests/benchmark/run_analysis_mp.sh b/tests/benchmark/conformer/run_analysis_mp.sh similarity index 100% rename from tests/benchmark/run_analysis_mp.sh rename to tests/benchmark/conformer/run_analysis_mp.sh diff --git a/tests/benchmark/run_analysis_sp.sh b/tests/benchmark/conformer/run_analysis_sp.sh similarity index 100% rename from tests/benchmark/run_analysis_sp.sh rename to tests/benchmark/conformer/run_analysis_sp.sh diff --git a/tests/benchmark/run_benchmark.sh b/tests/benchmark/conformer/run_benchmark.sh similarity index 100% rename from tests/benchmark/run_benchmark.sh rename to tests/benchmark/conformer/run_benchmark.sh diff --git a/tests/benchmark/pwgan/README.md b/tests/benchmark/pwgan/README.md new file mode 100644 index 00000000..3d2267ae --- /dev/null +++ b/tests/benchmark/pwgan/README.md @@ -0,0 +1,11 @@ +执行 +```bash +./run_all.sh +``` +即可运行. +执行逻辑： +1. cd 到 ../../../ (也就是 Parakeet 目录) +2. 安装 parakeet 所需依赖 +3. 从 bos 下载数据集并解压缩 +4. 预处理数据集为训练 pwg 所需格式，保存到 Parakeet/dump 文件夹底下 +5. 按照不同的参数执行 run_benchmark.sh 脚本 diff --git a/tests/benchmark/pwgan/run_all.sh b/tests/benchmark/pwgan/run_all.sh new file mode 100755 index 00000000..e26db317 --- /dev/null +++ b/tests/benchmark/pwgan/run_all.sh @@ -0,0 +1,52 @@ +#!/usr/bin/env bash + +stage=0 +stop_stage=100 + +# 提供可稳定复现性能的脚本，默认在标准docker环境内py37执行： paddlepaddle/paddle:latest-gpu-cuda10.1-cudnn7 paddle=2.1.2 py=37 +# 执行目录：需说明 +cd ../../../ +# 1 安装该模型需要的依赖 (如需开启优化策略请注明) +if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then + sudo apt-get install libsndfile1 + pip install -e . +fi +# 2 拷贝该模型需要数据、预训练模型 +# 下载 baker 数据集到 home 目录下并解压缩到 home 目录下 +if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then + wget https://weixinxcxdb.oss-cn-beijing.aliyuncs.com/gwYinPinKu/BZNSYP.rar + mkdir BZNSYP + unrar x BZNSYP.rar BZNSYP + wget https://paddlespeech.bj.bcebos.com/Parakeet/benchmark/durations.txt +fi +# 数据预处理 +if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then + + python examples/GANVocoder/preprocess.py --rootdir=BZNSYP/ --dumpdir=dump --num-cpu=20 --cut-sil=True --dur-file=durations.txt --config=examples/GANVocoder/parallelwave_gan/baker/conf/default.yaml + python utils/compute_statistics.py --metadata=dump/train/raw/metadata.jsonl --field-name="feats" + python examples/GANVocoder/normalize.py --metadata=dump/train/raw/metadata.jsonl --dumpdir=dump/train/norm --stats=dump/train/feats_stats.npy + python examples/GANVocoder/normalize.py --metadata=dump/dev/raw/metadata.jsonl --dumpdir=dump/dev/norm --stats=dump/train/feats_stats.npy + python examples/GANVocoder/normalize.py --metadata=dump/test/raw/metadata.jsonl --dumpdir=dump/test/norm --stats=dump/train/feats_stats.npy +fi +# 3 批量运行（如不方便批量，1，2需放到单个模型中） +if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then + + model_mode_list=(pwg) + fp_item_list=(fp32) + # 满 bs 是 26 + bs_item_list=(6 26) + for model_mode in ${model_mode_list[@]}; do + for fp_item in ${fp_item_list[@]}; do + for bs_item in ${bs_item_list[@]}; do + echo "index is speed, 1gpus, begin, ${model_name}" + run_mode=sp + CUDA_VISIBLE_DEVICES=0 bash tests/benchmark/PWGAN/run_benchmark.sh ${run_mode} ${bs_item} ${fp_item} 100 ${model_mode} # (5min) + sleep 60 + echo "index is speed, 8gpus, run_mode is multi_process, begin, ${model_name}" + run_mode=mp + CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 bash benchmark/run_benchmark.sh ${run_mode} ${bs_item} ${fp_item} 100 ${model_mode} + sleep 60 + done + done + done +fi \ No newline at end of file diff --git a/tests/benchmark/pwgan/run_benchmark.sh b/tests/benchmark/pwgan/run_benchmark.sh new file mode 100755 index 00000000..bcdccccf --- /dev/null +++ b/tests/benchmark/pwgan/run_benchmark.sh @@ -0,0 +1,56 @@ +#!/usr/bin/env bash +set -xe +# 运行示例：CUDA_VISIBLE_DEVICES=0 bash run_benchmark.sh ${run_mode} ${bs_item} ${fp_item} 500 ${model_mode} +# 参数说明 +function _set_params(){ + run_mode=${1:-"sp"} # 单卡sp|多卡mp + batch_size=${2:-"8"} + fp_item=${3:-"fp32"} # fp32|fp16 + max_iter=${4:-"500"} # 可选，如果需要修改代码提前中断 + model_name=${5:-"model_name"} + run_log_path=${TRAIN_LOG_DIR:-$(pwd)} # TRAIN_LOG_DIR 后续QA设置该参数 + +# 以下不用修改 + device=${CUDA_VISIBLE_DEVICES//,/ } + arr=(${device}) + num_gpu_devices=${#arr[*]} + log_file=${run_log_path}/${model_name}_${run_mode}_bs${batch_size}_${fp_item}_${num_gpu_devices} +} +function _train(){ + echo "Train on ${num_gpu_devices} GPUs" + echo "current CUDA_VISIBLE_DEVICES=$CUDA_VISIBLE_DEVICES, gpus=$num_gpu_devices, batch_size=$batch_size" + + train_cmd="--batch-size=${batch_size}\ + --max-iter=${max_iter} + --train-metadata=dump/train/norm/metadata.jsonl \ + --dev-metadata=dump/dev/norm/metadata.jsonl \ + --config=examples/GANVocoder/parallelwave_gan/baker/conf/default.yaml \ + --output-dir=exp/default \ + --run-benchmark=true" + + case ${run_mode} in + sp) train_cmd="python3 examples/GANVocoder/parallelwave_gan/train.py --nprocs=1 ${train_cmd}" ;; + mp) train_cmd="python3 examples/GANVocoder/parallelwave_gan/train.py --nprocs=8 ${train_cmd}" + log_parse_file="mylog/workerlog.0" ;; + *) echo "choose run_mode(sp or mp)"; exit 1; + esac +# 以下不用修改 + timeout 15m ${train_cmd} > ${log_file} 2>&1 + if [ $? -ne 0 ];then + echo -e "${model_name}, FAIL" + export job_fail_flag=1 + else + echo -e "${model_name}, SUCCESS" + export job_fail_flag=0 + fi + + trap 'for pid in $(jobs -pr); do kill -KILL $pid; done' INT QUIT TERM + + if [ $run_mode = "mp" -a -d mylog ]; then + rm ${log_file} + cp mylog/workerlog.0 ${log_file} + fi +} + +_set_params $@ +_train \ No newline at end of file diff --git a/tests/chains/README.md b/tests/chains/ds2/README.md similarity index 100% rename from tests/chains/README.md rename to tests/chains/ds2/README.md diff --git a/tests/chains/ds2_params_lite_train_infer.txt b/tests/chains/ds2/ds2_params_lite_train_infer.txt similarity index 100% rename from tests/chains/ds2_params_lite_train_infer.txt rename to tests/chains/ds2/ds2_params_lite_train_infer.txt diff --git a/tests/chains/ds2_params_whole_train_infer.txt b/tests/chains/ds2/ds2_params_whole_train_infer.txt similarity index 100% rename from tests/chains/ds2_params_whole_train_infer.txt rename to tests/chains/ds2/ds2_params_whole_train_infer.txt diff --git a/tests/chains/lite_train_infer.sh b/tests/chains/ds2/lite_train_infer.sh similarity index 100% rename from tests/chains/lite_train_infer.sh rename to tests/chains/ds2/lite_train_infer.sh diff --git a/tests/chains/prepare.sh b/tests/chains/ds2/prepare.sh similarity index 100% rename from tests/chains/prepare.sh rename to tests/chains/ds2/prepare.sh diff --git a/tests/chains/speedyspeech_params_lite.txt b/tests/chains/ds2/speedyspeech_params_lite.txt similarity index 100% rename from tests/chains/speedyspeech_params_lite.txt rename to tests/chains/ds2/speedyspeech_params_lite.txt diff --git a/tests/chains/test.sh b/tests/chains/ds2/test.sh similarity index 100% rename from tests/chains/test.sh rename to tests/chains/ds2/test.sh diff --git a/tests/chains/whole_train_infer.sh b/tests/chains/ds2/whole_train_infer.sh similarity index 100% rename from tests/chains/whole_train_infer.sh rename to tests/chains/ds2/whole_train_infer.sh diff --git a/tests/chains/speedyspeech/README.md b/tests/chains/speedyspeech/README.md new file mode 100644 index 00000000..60969212 --- /dev/null +++ b/tests/chains/speedyspeech/README.md @@ -0,0 +1,16 @@ +Please use lite_train_infer.sh, whole_train_infer.sh, infer.sh. + +For lite_train_infer +``` +bash lite_train_infer.sh +``` + +For whole_train_infer +``` +bash whole_train_infer.sh +``` + +For infer +``` +bash infer.sh +``` diff --git a/tests/chains/speedyspeech/infer.sh b/tests/chains/speedyspeech/infer.sh new file mode 100755 index 00000000..c1d19de0 --- /dev/null +++ b/tests/chains/speedyspeech/infer.sh @@ -0,0 +1,2 @@ +bash prepare.sh infer +bash test.sh speedyspeech_params_lite_single_gpu.txt infer diff --git a/tests/chains/speedyspeech/lite_train_infer.sh b/tests/chains/speedyspeech/lite_train_infer.sh new file mode 100644 index 00000000..de67efa0 --- /dev/null +++ b/tests/chains/speedyspeech/lite_train_infer.sh @@ -0,0 +1,7 @@ +rm exp -rf +rm e2e -rf +bash prepare.sh lite_train_infer +bash test.sh speedyspeech_params_lite_single_gpu.txt lite_train_infer +rm exp -rf +rm e2e -rf +bash test.sh speedyspeech_params_lite_multi_gpu.txt lite_train_infer diff --git a/tests/chains/speedyspeech/prepare.sh b/tests/chains/speedyspeech/prepare.sh new file mode 100644 index 00000000..fb6ef285 --- /dev/null +++ b/tests/chains/speedyspeech/prepare.sh @@ -0,0 +1,54 @@ +#!/bin/bash +# usage bash prepare.sh MODE +# FILENAME=$1 +# MODE be one of ['lite_train_infer' 'whole_infer' 'whole_train_infer', 'infer'] +MODE=$1 + +# dataline=$(cat ${FILENAME}) + +# parser params +IFS=$'\n' +lines=(${dataline}) +function func_parser_key(){ + strs=$1 + IFS=":" + array=(${strs}) + tmp=${array[0]} + echo ${tmp} +} +function func_parser_value(){ + strs=$1 + IFS=":" + array=(${strs}) + tmp=${array[1]} + echo ${tmp} +} +IFS=$'\n' +# The training params +model_name=$(func_parser_value "${lines[1]}") + +trainer_list=$(func_parser_value "${lines[14]}") + +# MODE be one of ['lite_train_infer' 'whole_infer' 'whole_train_infer'] +if [ ${MODE} = "lite_train_infer" ];then + # pretrain lite train data + wget -nc -P ./pretrain_models/ https://paddlespeech.bj.bcebos.com/Parakeet/pwg_baker_ckpt_0.4.zip + (cd ./pretrain_models && unzip pwg_baker_ckpt_0.4.zip) + # download data + rm -rf ./train_data/mini_BZNSYP + wget -nc -P ./train_data/ https://paddlespeech.bj.bcebos.com/datasets/CE/speedyspeech_v0.5/mini_BZNSYP.tar.gz + cd ./train_data/ && tar xzf mini_BZNSYP.tar.gz + cd ../ +elif [ ${MODE} = "whole_train_infer" ];then + wget -nc -P ./pretrain_models/ https://paddlespeech.bj.bcebos.com/Parakeet/speedyspeech_nosil_baker_ckpt_0.5.zip + wget -nc -P ./pretrain_models/ https://paddlespeech.bj.bcebos.com/Parakeet/pwg_baker_ckpt_0.4.zip + (cd ./pretrain_models && unzip speedyspeech_nosil_baker_ckpt_0.5.zip && unzip pwg_baker_ckpt_0.4.zip) + rm -rf ./train_data/processed_BZNSYP + wget -nc -P ./train_data/ https://paddlespeech.bj.bcebos.com/datasets/CE/speedyspeech_v0.5/processed_BZNSYP.tar.gz + cd ./train_data/ && tar xzf processed_BZNSYP.tar.gz + cd ../ +else + # whole infer using paddle inference library + wget -nc -P ./pretrain_models/ https://paddlespeech.bj.bcebos.com/Parakeet/speedyspeech_pwg_inference_0.5.zip + (cd ./pretrain_models && unzip speedyspeech_pwg_inference_0.5.zip) +fi diff --git a/tests/chains/speedyspeech/speedyspeech_params_lite_multi_gpu.txt b/tests/chains/speedyspeech/speedyspeech_params_lite_multi_gpu.txt new file mode 100644 index 00000000..98026241 --- /dev/null +++ b/tests/chains/speedyspeech/speedyspeech_params_lite_multi_gpu.txt @@ -0,0 +1,50 @@ +===========================train_params=========================== +model_name:speedyspeech +python:python3.7 +gpu_list:0,1 +null:null +null:null +null:null +null:null +null:null +null:null +null:null +null:null +null:null +## +trainer:norm_train +norm_train:../../examples/speedyspeech/train.py --train-metadata=train_data/mini_BZNSYP/train/norm/metadata.jsonl --dev-metadata=train_data/mini_BZNSYP/dev/norm/metadata.jsonl --config=../../examples/speedyspeech/baker/conf/default.yaml --batch_size=32 --max_epoch=20 --num_snapshots=10 --output-dir=exp/default --phones-dict=train_data/mini_BZNSYP/phone_id_map.txt --tones-dict=train_data/mini_BZNSYP/tone_id_map.txt --use-relative-path=True +null:null +null:null +null:null +null:null +null:null +## +===========================eval_params=========================== +eval:../../examples/speedyspeech/baker/synthesize_e2e.py --speedyspeech-config=../../examples/speedyspeech/baker/conf/default.yaml --speedyspeech-checkpoint=exp/default/checkpoints/snapshot_iter_20.pdz --speedyspeech-stat=train_data/mini_BZNSYP/train/feats_stats.npy --pwg-config=pretrain_models/pwg_baker_ckpt_0.4/pwg_default.yaml --pwg-checkpoint=pretrain_models/pwg_baker_ckpt_0.4/pwg_snapshot_iter_400000.pdz --pwg-stat=pretrain_models/pwg_baker_ckpt_0.4/pwg_stats.npy --text=../../examples/speedyspeech/sentences.txt --output-dir=e2e --inference-dir=inference --device="gpu" --phones-dict=train_data/mini_BZNSYP/phone_id_map.txt --tones-dict=train_data/mini_BZNSYP/tone_id_map.txt +null:null +## +===========================infer_params=========================== +null:null +null:null +null:null +null:null +null:null +null:null +null:null +null:null +## +null:null +null:null +null:null +inference:../../examples/speedyspeech/baker/inference.py --inference-dir=pretrain_models/speedyspeech_pwg_inference_0.5 --text=../../examples/speedyspeech/sentences.txt --output-dir=inference_out --enable-auto-log --phones-dict=pretrain_models/speedyspeech_pwg_inference_0.5/phone_id_map.txt --tones-dict=pretrain_models/speedyspeech_pwg_inference_0.5/tone_id_map.txt +null:null +null:null +null:null +null:null +null:null +null:null +null:null +null:null +null:null +null:null diff --git a/tests/chains/speedyspeech/speedyspeech_params_lite_single_gpu.txt b/tests/chains/speedyspeech/speedyspeech_params_lite_single_gpu.txt new file mode 100644 index 00000000..e821183a --- /dev/null +++ b/tests/chains/speedyspeech/speedyspeech_params_lite_single_gpu.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:speedyspeech +python:python3.7 +gpu_list:0 +null:null +null:null +null:null +null:null +null:null +null:null +null:null +null:null +null:null +## +trainer:norm_train +norm_train:../../examples/speedyspeech/train.py --train-metadata=train_data/mini_BZNSYP/train/norm/metadata.jsonl --dev-metadata=train_data/mini_BZNSYP/dev/norm/metadata.jsonl --config=../../examples/speedyspeech/baker/conf/default.yaml --batch_size=32 --max_epoch=10 --num_snapshots=10 --output-dir=exp/default --phones-dict=train_data/mini_BZNSYP/phone_id_map.txt --tones-dict=train_data/mini_BZNSYP/tone_id_map.txt --use-relative-path=True +null:null +null:null +null:null +null:null +null:null +## +===========================eval_params=========================== +eval:../../examples/speedyspeech/baker/synthesize_e2e.py --speedyspeech-config=../../examples/speedyspeech/baker/conf/default.yaml --speedyspeech-checkpoint=exp/default/checkpoints/snapshot_iter_30.pdz --speedyspeech-stat=train_data/mini_BZNSYP/train/feats_stats.npy --pwg-config=pretrain_models/pwg_baker_ckpt_0.4/pwg_default.yaml --pwg-checkpoint=pretrain_models/pwg_baker_ckpt_0.4/pwg_snapshot_iter_400000.pdz --pwg-stat=pretrain_models/pwg_baker_ckpt_0.4/pwg_stats.npy --text=../../examples/speedyspeech/sentences.txt --output-dir=e2e --inference-dir=inference --device="gpu" --phones-dict=train_data/mini_BZNSYP/phone_id_map.txt --tones-dict=train_data/mini_BZNSYP/tone_id_map.txt +null:null +## +===========================infer_params=========================== +null:null +null:null +null:null +null:null +null:null +null:null +null:null +null:null +## +null:null +null:null +null:null +inference:../../examples/speedyspeech/baker/inference.py --inference-dir=pretrain_models/speedyspeech_pwg_inference_0.5 --text=../../examples/speedyspeech/sentences.txt --output-dir=inference_out --enable-auto-log --phones-dict=pretrain_models/speedyspeech_pwg_inference_0.5/phone_id_map.txt --tones-dict=pretrain_models/speedyspeech_pwg_inference_0.5/tone_id_map.txt +--use_gpu:True +null:null +null:null +null:null +null:null +null:null +null:null +null:null +null:null +null:null +null:null diff --git a/tests/chains/speedyspeech/speedyspeech_params_whole_multi_gpu.txt b/tests/chains/speedyspeech/speedyspeech_params_whole_multi_gpu.txt new file mode 100644 index 00000000..7c517119 --- /dev/null +++ b/tests/chains/speedyspeech/speedyspeech_params_whole_multi_gpu.txt @@ -0,0 +1,50 @@ +===========================train_params=========================== +model_name:speedyspeech +python:python3.7 +gpu_list:0,1 +null:null +null:null +null:null +null:null +null:null +null:null +null:null +null:null +null:null +## +trainer:norm_train +norm_train:../../examples/speedyspeech/train.py --train-metadata=train_data/processed_BZNSYP/train/norm/metadata.jsonl --dev-metadata=train_data/processed_BZNSYP/dev/norm/metadata.jsonl --config=../../examples/speedyspeech/baker/conf/default.yaml --output-dir=exp/whole --phones-dict=train_data/processed_BZNSYP/phone_id_map.txt --tones-dict=train_data/processed_BZNSYP/tone_id_map.txt --use-relative-path=True +null:null +null:null +null:null +null:null +null:null +## +===========================eval_params=========================== +eval:../../examples/speedyspeech/baker/synthesize_e2e.py --speedyspeech-config=pretrain_models/speedyspeech_nosil_baker_ckpt_0.5/default.yaml --speedyspeech-checkpoint=pretrain_models/speedyspeech_nosil_baker_ckpt_0.5/snapshot_iter_11400.pdz --speedyspeech-stat=pretrain_models/speedyspeech_nosil_baker_ckpt_0.5/feats_stats.npy --pwg-config=pretrain_models/pwg_baker_ckpt_0.4/pwg_default.yaml --pwg-checkpoint=pretrain_models/pwg_baker_ckpt_0.4/pwg_snapshot_iter_400000.pdz --pwg-stat=pretrain_models/pwg_baker_ckpt_0.4/pwg_stats.npy --text=../../examples/speedyspeech/sentences.txt --output-dir=e2e --inference-dir=inference --device="gpu" --phones-dict=pretrain_models/speedyspeech_nosil_baker_ckpt_0.5/phone_id_map.txt --tones-dict=pretrain_models/speedyspeech_nosil_baker_ckpt_0.5/tone_id_map.txt +null:null +## +===========================infer_params=========================== +null:null +null:null +null:null +null:null +null:null +null:null +null:null +null:null +## +null:null +null:null +null:null +inference:../../examples/speedyspeech/baker/inference.py --inference-dir=pretrain_models/speedyspeech_pwg_inference_0.5 --text=../../examples/speedyspeech/sentences.txt --output-dir=inference_out --enable-auto-log --phones-dict=pretrain_models/speedyspeech_pwg_inference_0.5/phone_id_map.txt --tones-dict=pretrain_models/speedyspeech_pwg_inference_0.5/tone_id_map.txt +null:null +null:null +null:null +null:null +null:null +null:null +null:null +null:null +null:null +null:null diff --git a/tests/chains/speedyspeech/speedyspeech_params_whole_single_gpu.txt b/tests/chains/speedyspeech/speedyspeech_params_whole_single_gpu.txt new file mode 100644 index 00000000..9a6c611e --- /dev/null +++ b/tests/chains/speedyspeech/speedyspeech_params_whole_single_gpu.txt @@ -0,0 +1,50 @@ +===========================train_params=========================== +model_name:speedyspeech +python:python3.7 +gpu_list:0 +null:null +null:null +null:null +null:null +null:null +null:null +null:null +null:null +null:null +## +trainer:norm_train +norm_train:../../examples/speedyspeech/train.py --train-metadata=train_data/processed_BZNSYP/train/norm/metadata.jsonl --dev-metadata=train_data/processed_BZNSYP/dev/norm/metadata.jsonl --config=../../examples/speedyspeech/baker/conf/default.yaml --output-dir=exp/whole --phones-dict=train_data/processed_BZNSYP/phone_id_map.txt --tones-dict=train_data/processed_BZNSYP/tone_id_map.txt --use-relative-path=True +null:null +null:null +null:null +null:null +null:null +## +===========================eval_params=========================== +eval:../../examples/speedyspeech/baker/synthesize_e2e.py --speedyspeech-config=pretrain_models/speedyspeech_nosil_baker_ckpt_0.5/default.yaml --speedyspeech-checkpoint=pretrain_models/speedyspeech_nosil_baker_ckpt_0.5/snapshot_iter_11400.pdz --speedyspeech-stat=pretrain_models/speedyspeech_nosil_baker_ckpt_0.5/feats_stats.npy --pwg-config=pretrain_models/pwg_baker_ckpt_0.4/pwg_default.yaml --pwg-checkpoint=pretrain_models/pwg_baker_ckpt_0.4/pwg_snapshot_iter_400000.pdz --pwg-stat=pretrain_models/pwg_baker_ckpt_0.4/pwg_stats.npy --text=../../examples/speedyspeech/sentences.txt --output-dir=e2e --inference-dir=inference --device="gpu" --phones-dict=pretrain_models/speedyspeech_nosil_baker_ckpt_0.5/phone_id_map.txt --tones-dict=pretrain_models/speedyspeech_nosil_baker_ckpt_0.5/tone_id_map.txt +null:null +## +===========================infer_params=========================== +null:null +null:null +null:null +null:null +null:null +null:null +null:null +null:null +## +null:null +null:null +null:null +inference:../../examples/speedyspeech/baker/inference.py --inference-dir=pretrain_models/speedyspeech_pwg_inference_0.5 --text=../../examples/speedyspeech/sentences.txt --output-dir=inference_out --enable-auto-log --phones-dict=pretrain_models/speedyspeech_pwg_inference_0.5/phone_id_map.txt --tones-dict=pretrain_models/speedyspeech_pwg_inference_0.5/tone_id_map.txt +null:null +null:null +null:null +null:null +null:null +null:null +null:null +null:null +null:null +null:null diff --git a/tests/chains/speedyspeech/test.sh b/tests/chains/speedyspeech/test.sh new file mode 100644 index 00000000..f4441335 --- /dev/null +++ b/tests/chains/speedyspeech/test.sh @@ -0,0 +1,367 @@ +#!/bin/bash +# usage: bash test.sh ***.txt MODE + +FILENAME=$1 +# MODE be one of ['lite_train_infer' 'whole_infer' 'whole_train_infer', 'infer'] +MODE=$2 + +dataline=$(cat ${FILENAME}) + +# parser params +IFS=$'\n' +lines=(${dataline}) + +function func_parser_key(){ + strs=$1 + IFS=":" + array=(${strs}) + tmp=${array[0]} + echo ${tmp} +} +function func_parser_value(){ + strs=$1 + IFS=":" + array=(${strs}) + tmp=${array[1]} + echo ${tmp} +} +function func_set_params(){ + key=$1 + value=$2 + if [ ${key} = "null" ];then + echo " " + elif [[ ${value} = "null" ]] || [[ ${value} = " " ]] || [ ${#value} -le 0 ];then + echo " " + else + echo "${key}=${value}" + fi +} +function func_parser_params(){ + strs=$1 + IFS=":" + array=(${strs}) + key=${array[0]} + tmp=${array[1]} + IFS="|" + res="" + for _params in ${tmp[*]}; do + IFS="=" + array=(${_params}) + mode=${array[0]} + value=${array[1]} + if [[ ${mode} = ${MODE} ]]; then + IFS="|" + #echo $(func_set_params "${mode}" "${value}") + echo $value + break + fi + IFS="|" + done + echo ${res} +} +function status_check(){ + last_status=$1 # the exit code + run_command=$2 + run_log=$3 + if [ $last_status -eq 0 ]; then + echo -e "\033[33m Run successfully with command - ${run_command}! \033[0m" | tee -a ${run_log} + else + echo -e "\033[33m Run failed with command - ${run_command}! \033[0m" | tee -a ${run_log} + fi +} + +IFS=$'\n' +# The training params +model_name=$(func_parser_value "${lines[1]}") +python=$(func_parser_value "${lines[2]}") +gpu_list=$(func_parser_value "${lines[3]}") +train_use_gpu_key=$(func_parser_key "${lines[4]}") +train_use_gpu_value=$(func_parser_value "${lines[4]}") +autocast_list=$(func_parser_value "${lines[5]}") +autocast_key=$(func_parser_key "${lines[5]}") +epoch_key=$(func_parser_key "${lines[6]}") +epoch_num=$(func_parser_params "${lines[6]}") +save_model_key=$(func_parser_key "${lines[7]}") +train_batch_key=$(func_parser_key "${lines[8]}") +train_batch_value=$(func_parser_params "${lines[8]}") +pretrain_model_key=$(func_parser_key "${lines[9]}") +pretrain_model_value=$(func_parser_value "${lines[9]}") +train_model_name=$(func_parser_value "${lines[10]}") +train_infer_img_dir=$(func_parser_value "${lines[11]}") +train_param_key1=$(func_parser_key "${lines[12]}") +train_param_value1=$(func_parser_value "${lines[12]}") + +trainer_list=$(func_parser_value "${lines[14]}") +trainer_norm=$(func_parser_key "${lines[15]}") +norm_trainer=$(func_parser_value "${lines[15]}") +pact_key=$(func_parser_key "${lines[16]}") +pact_trainer=$(func_parser_value "${lines[16]}") +fpgm_key=$(func_parser_key "${lines[17]}") +fpgm_trainer=$(func_parser_value "${lines[17]}") +distill_key=$(func_parser_key "${lines[18]}") +distill_trainer=$(func_parser_value "${lines[18]}") +trainer_key1=$(func_parser_key "${lines[19]}") +trainer_value1=$(func_parser_value "${lines[19]}") +trainer_key2=$(func_parser_key "${lines[20]}") +trainer_value2=$(func_parser_value "${lines[20]}") + +eval_py=$(func_parser_value "${lines[23]}") +eval_key1=$(func_parser_key "${lines[24]}") +eval_value1=$(func_parser_value "${lines[24]}") + +save_infer_key=$(func_parser_key "${lines[27]}") +export_weight=$(func_parser_key "${lines[28]}") +norm_export=$(func_parser_value "${lines[29]}") +pact_export=$(func_parser_value "${lines[30]}") +fpgm_export=$(func_parser_value "${lines[31]}") +distill_export=$(func_parser_value "${lines[32]}") +export_key1=$(func_parser_key "${lines[33]}") +export_value1=$(func_parser_value "${lines[33]}") +export_key2=$(func_parser_key "${lines[34]}") +export_value2=$(func_parser_value "${lines[34]}") + +# parser inference model +infer_model_dir_list=$(func_parser_value "${lines[36]}") +infer_export_list=$(func_parser_value "${lines[37]}") +infer_is_quant=$(func_parser_value "${lines[38]}") +# parser inference +inference_py=$(func_parser_value "${lines[39]}") +use_gpu_key=$(func_parser_key "${lines[40]}") +use_gpu_list=$(func_parser_value "${lines[40]}") +use_mkldnn_key=$(func_parser_key "${lines[41]}") +use_mkldnn_list=$(func_parser_value "${lines[41]}") +cpu_threads_key=$(func_parser_key "${lines[42]}") +cpu_threads_list=$(func_parser_value "${lines[42]}") +batch_size_key=$(func_parser_key "${lines[43]}") +batch_size_list=$(func_parser_value "${lines[43]}") +use_trt_key=$(func_parser_key "${lines[44]}") +use_trt_list=$(func_parser_value "${lines[44]}") +precision_key=$(func_parser_key "${lines[45]}") +precision_list=$(func_parser_value "${lines[45]}") +infer_model_key=$(func_parser_key "${lines[46]}") +image_dir_key=$(func_parser_key "${lines[47]}") +infer_img_dir=$(func_parser_value "${lines[47]}") +save_log_key=$(func_parser_key "${lines[48]}") +benchmark_key=$(func_parser_key "${lines[49]}") +benchmark_value=$(func_parser_value "${lines[49]}") +infer_key1=$(func_parser_key "${lines[50]}") +infer_value1=$(func_parser_value "${lines[50]}") + +LOG_PATH="./tests/output" +mkdir -p ${LOG_PATH} +status_log="${LOG_PATH}/results.log" + + +function func_inference(){ + IFS='|' + _python=$1 + _script=$2 + _model_dir=$3 + _log_path=$4 + _img_dir=$5 + _flag_quant=$6 + # inference + for use_gpu in ${use_gpu_list[*]}; do + if [ ${use_gpu} = "False" ] || [ ${use_gpu} = "cpu" ]; then + for use_mkldnn in ${use_mkldnn_list[*]}; do + if [ ${use_mkldnn} = "False" ] && [ ${_flag_quant} = "True" ]; then + continue + fi + for threads in ${cpu_threads_list[*]}; do + for batch_size in ${batch_size_list[*]}; do + _save_log_path="${_log_path}/infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_batchsize_${batch_size}.log" + set_infer_data=$(func_set_params "${image_dir_key}" "${_img_dir}") + set_benchmark=$(func_set_params "${benchmark_key}" "${benchmark_value}") + set_batchsize=$(func_set_params "${batch_size_key}" "${batch_size}") + set_cpu_threads=$(func_set_params "${cpu_threads_key}" "${threads}") + set_model_dir=$(func_set_params "${infer_model_key}" "${_model_dir}") + set_infer_params1=$(func_set_params "${infer_key1}" "${infer_value1}") + command="${_python} ${_script} > ${_save_log_path} 2>&1 " + eval $command + last_status=${PIPESTATUS[0]} + eval "cat ${_save_log_path}" + status_check $last_status "${command}" "${status_log}" + done + done + done + elif [ ${use_gpu} = "True" ] || [ ${use_gpu} = "gpu" ]; then + for use_trt in ${use_trt_list[*]}; do + for precision in ${precision_list[*]}; do + if [[ ${_flag_quant} = "False" ]] && [[ ${precision} =~ "int8" ]]; then + continue + fi + if [[ ${precision} =~ "fp16" || ${precision} =~ "int8" ]] && [ ${use_trt} = "False" ]; then + continue + fi + if [[ ${use_trt} = "False" || ${precision} =~ "int8" ]] && [ ${_flag_quant} = "True" ]; then + continue + fi + for batch_size in ${batch_size_list[*]}; do + _save_log_path="${_log_path}/infer_gpu_usetrt_${use_trt}_precision_${precision}_batchsize_${batch_size}.log" + set_infer_data=$(func_set_params "${image_dir_key}" "${_img_dir}") + set_benchmark=$(func_set_params "${benchmark_key}" "${benchmark_value}") + set_batchsize=$(func_set_params "${batch_size_key}" "${batch_size}") + set_tensorrt=$(func_set_params "${use_trt_key}" "${use_trt}") + set_precision=$(func_set_params "${precision_key}" "${precision}") + set_model_dir=$(func_set_params "${infer_model_key}" "${_model_dir}") + set_infer_params1=$(func_set_params "${infer_key1}" "${infer_value1}") + command="${_python} ${_script} > ${_save_log_path} 2>&1 " + eval $command + last_status=${PIPESTATUS[0]} + eval "cat ${_save_log_path}" + status_check $last_status "${command}" "${status_log}" + + done + done + done + else + echo "Does not support hardware other than CPU and GPU Currently!" + fi + done +} + +if [ ${MODE} = "infer" ]; then + GPUID=$3 + if [ ${#GPUID} -le 0 ];then + env=" " + else + env="export CUDA_VISIBLE_DEVICES=${GPUID}" + fi + # set CUDA_VISIBLE_DEVICES + eval $env + export Count=0 + IFS="|" + infer_run_exports=(${infer_export_list}) + infer_quant_flag=(${infer_is_quant}) + for infer_model in ${infer_model_dir_list[*]}; do + # run export + if [ ${infer_run_exports[Count]} != "null" ];then + set_export_weight=$(func_set_params "${export_weight}" "${infer_model}") + set_save_infer_key=$(func_set_params "${save_infer_key}" "${infer_model}") + export_cmd="${python} ${norm_export} ${set_export_weight} ${set_save_infer_key}" + eval $export_cmd + status_export=$? + if [ ${status_export} = 0 ];then + status_check $status_export "${export_cmd}" "${status_log}" + fi + fi + #run inference + is_quant=${infer_quant_flag[Count]} + func_inference "${python}" "${inference_py}" "${infer_model}" "${LOG_PATH}" "${infer_img_dir}" ${is_quant} + Count=$(($Count + 1)) + done + +else + IFS="|" + export Count=0 + USE_GPU_KEY=(${train_use_gpu_value}) + for gpu in ${gpu_list[*]}; do + use_gpu=${USE_GPU_KEY[Count]} + Count=$(($Count + 1)) + if [ ${gpu} = "-1" ];then + env="" + elif [ ${#gpu} -le 1 ];then + env="export CUDA_VISIBLE_DEVICES=${gpu}" + eval ${env} + elif [ ${#gpu} -le 15 ];then + IFS="," + array=(${gpu}) + env="export CUDA_VISIBLE_DEVICES=${array[0]}" + IFS="|" + else + IFS=";" + array=(${gpu}) + ips=${array[0]} + gpu=${array[1]} + IFS="|" + env=" " + fi + for autocast in ${autocast_list[*]}; do + for trainer in ${trainer_list[*]}; do + flag_quant=False + if [ ${trainer} = ${pact_key} ]; then + run_train=${pact_trainer} + run_export=${pact_export} + flag_quant=True + elif [ ${trainer} = "${fpgm_key}" ]; then + run_train=${fpgm_trainer} + run_export=${fpgm_export} + elif [ ${trainer} = "${distill_key}" ]; then + run_train=${distill_trainer} + run_export=${distill_export} + elif [ ${trainer} = ${trainer_key1} ]; then + run_train=${trainer_value1} + run_export=${export_value1} + elif [[ ${trainer} = ${trainer_key2} ]]; then + run_train=${trainer_value2} + run_export=${export_value2} + else + run_train=${norm_trainer} + run_export=${norm_export} + fi + + if [ ${run_train} = "null" ]; then + continue + fi + + set_autocast=$(func_set_params "${autocast_key}" "${autocast}") + set_epoch=$(func_set_params "${epoch_key}" "${epoch_num}") + set_pretrain=$(func_set_params "${pretrain_model_key}" "${pretrain_model_value}") + set_batchsize=$(func_set_params "${train_batch_key}" "${train_batch_value}") + set_train_params1=$(func_set_params "${train_param_key1}" "${train_param_value1}") + set_use_gpu=$(func_set_params "${train_use_gpu_key}" "${use_gpu}") + save_log="${LOG_PATH}/${trainer}_gpus_${gpu}_autocast_${autocast}" + + # load pretrain from norm training if current trainer is pact or fpgm trainer + if [ ${trainer} = ${pact_key} ] || [ ${trainer} = ${fpgm_key} ]; then + set_pretrain="${load_norm_train_model}" + fi + + set_save_model=$(func_set_params "${save_model_key}" "${save_log}") + if [ ${#gpu} -le 2 ];then # train with cpu or single gpu + cmd="${python} ${run_train} " + elif [ ${#gpu} -le 15 ];then # train with multi-gpu + gsu=${gpu//,/ } + nump=`echo $gsu | wc -w` + CUDA_VISIBLE_DEVICES=${gpu} + cmd="${python} ${run_train} --nprocs=$nump" + else # train with multi-machine + cmd="${python} -m paddle.distributed.launch --ips=${ips} --gpus=${gpu} ${run_train} ${set_save_model} ${set_pretrain} ${set_epoch} ${set_autocast} ${set_batchsize} ${set_train_params1}" + fi + # run train + # eval "unset CUDA_VISIBLE_DEVICES" + eval $cmd + status_check $? "${cmd}" "${status_log}" + + set_eval_pretrain=$(func_set_params "${pretrain_model_key}" "${save_log}/${train_model_name}") + # save norm trained models to set pretrain for pact training and fpgm training + if [ ${trainer} = ${trainer_norm} ]; then + load_norm_train_model=${set_eval_pretrain} + fi + # run eval + if [ ${eval_py} != "null" ]; then + set_eval_params1=$(func_set_params "${eval_key1}" "${eval_value1}") + eval_cmd="${python} ${eval_py} ${set_eval_pretrain} ${set_use_gpu} ${set_eval_params1}" + eval $eval_cmd + status_check $? "${eval_cmd}" "${status_log}" + fi + # run export model + if [ ${run_export} != "null" ]; then + # run export model + save_infer_path="${save_log}" + set_export_weight=$(func_set_params "${export_weight}" "${save_log}/${train_model_name}") + set_save_infer_key=$(func_set_params "${save_infer_key}" "${save_infer_path}") + export_cmd="${python} ${run_export} ${set_export_weight} ${set_save_infer_key}" + eval $export_cmd + status_check $? "${export_cmd}" "${status_log}" + + #run inference + eval $env + save_infer_path="${save_log}" + func_inference "${python}" "${inference_py}" "${save_infer_path}" "${LOG_PATH}" "${train_infer_img_dir}" "${flag_quant}" + eval "unset CUDA_VISIBLE_DEVICES" + fi + done # done with: for trainer in ${trainer_list[*]}; do + done # done with: for autocast in ${autocast_list[*]}; do + done # done with: for gpu in ${gpu_list[*]}; do +fi # end if [ ${MODE} = "infer" ]; then diff --git a/tests/chains/speedyspeech/whole_train_infer.sh b/tests/chains/speedyspeech/whole_train_infer.sh new file mode 100644 index 00000000..fa2b89df --- /dev/null +++ b/tests/chains/speedyspeech/whole_train_infer.sh @@ -0,0 +1,7 @@ +rm exp -rf +rm e2e -rf +bash prepare.sh whole_train_infer +bash test.sh speedyspeech_params_whole_single_gpu.txt whole_train_infer +rm exp -rf +rm e2e -rf +bash test.sh speedyspeech_params_whole_multi_gpu.txt whole_train_infer diff --git a/tests/deepspeech2_model_test.py b/tests/unit/asr/deepspeech2_model_test.py similarity index 100% rename from tests/deepspeech2_model_test.py rename to tests/unit/asr/deepspeech2_model_test.py diff --git a/tests/deepspeech2_online_model_test.py b/tests/unit/asr/deepspeech2_online_model_test.py similarity index 100% rename from tests/deepspeech2_online_model_test.py rename to tests/unit/asr/deepspeech2_online_model_test.py diff --git a/tests/error_rate_test.py b/tests/unit/asr/error_rate_test.py similarity index 100% rename from tests/error_rate_test.py rename to tests/unit/asr/error_rate_test.py diff --git a/tests/mask_test.py b/tests/unit/asr/mask_test.py similarity index 100% rename from tests/mask_test.py rename to tests/unit/asr/mask_test.py diff --git a/tests/u2_model_test.py b/tests/unit/asr/u2_model_test.py similarity index 100% rename from tests/u2_model_test.py rename to tests/unit/asr/u2_model_test.py diff --git a/tests/unit/tts/test_data_table.py b/tests/unit/tts/test_data_table.py new file mode 100644 index 00000000..3664ea31 --- /dev/null +++ b/tests/unit/tts/test_data_table.py @@ -0,0 +1,21 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from parakeet.datasets.data_tabel import DataTable + + +def test_audio_dataset(): + metadata = [{'name': 'Sonic', 'v': 1000}, {'name': 'Prestol', 'v': 2000}] + converters = {'v': lambda x: x / 1000} + dataset = DataTable(metadata, fields=['v'], converters=converters) + assert dataset[0] == {'v': 1.0} diff --git a/tests/unit/tts/test_expansion.py b/tests/unit/tts/test_expansion.py new file mode 100644 index 00000000..418e9ba1 --- /dev/null +++ b/tests/unit/tts/test_expansion.py @@ -0,0 +1,29 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import paddle + +from parakeet.modules import expansion + + +def test_expand(): + x = paddle.randn([2, 4, 3]) # (B, T, C) + lengths = paddle.to_tensor([[1, 2, 2, 1], [3, 1, 4, 0]]) + y = expansion.expand(x, lengths) + + assert y.shape == [2, 8, 3] + print("the first sequence") + print(y[0]) + + print("the second sequence") + print(y[1]) diff --git a/tests/unit/tts/test_optimizer.py b/tests/unit/tts/test_optimizer.py new file mode 100644 index 00000000..74f50361 --- /dev/null +++ b/tests/unit/tts/test_optimizer.py @@ -0,0 +1,38 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import shutil +from pathlib import Path + +import paddle +from paddle import nn +from paddle.optimizer import Adam +from paddle.optimizer.lr import StepDecay + + +def test_optimizer(): + model1 = nn.Linear(3, 4) + optim1 = Adam( + parameters=model1.parameters(), learning_rate=StepDecay(0.1, 100)) + + output_dir = Path("temp_test_optimizer") + shutil.rmtree(output_dir, ignore_errors=True) + output_dir.mkdir(exist_ok=True, parents=True) + + # model1.set_state_dict(model1.state_dict()) + optim1.set_state_dict(optim1.state_dict()) + + x = paddle.randn([6, 3]) + y = model1(x).sum() + y.backward() + optim1.step() diff --git a/tests/unit/tts/test_pwg.py b/tests/unit/tts/test_pwg.py new file mode 100644 index 00000000..2f07a4ab --- /dev/null +++ b/tests/unit/tts/test_pwg.py @@ -0,0 +1,243 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import paddle +import torch +from parallel_wavegan.layers import residual_block +from parallel_wavegan.layers import upsample +from parallel_wavegan.models import parallel_wavegan as pwgan +from timer import timer + +from parakeet.models.parallel_wavegan import ConvInUpsampleNet +from parakeet.models.parallel_wavegan import PWGDiscriminator +from parakeet.models.parallel_wavegan import PWGGenerator +from parakeet.models.parallel_wavegan import ResidualBlock +from parakeet.models.parallel_wavegan import ResidualPWGDiscriminator +from parakeet.utils.layer_tools import summary +from parakeet.utils.profile import synchronize + +paddle.set_device("gpu:0") +device = torch.device("cuda:0") + + +def test_convin_upsample_net(): + net = ConvInUpsampleNet( + [4, 4, 4, 4], + "LeakyReLU", {"negative_slope": 0.2}, + freq_axis_kernel_size=3, + aux_context_window=0) + net2 = upsample.ConvInUpsampleNetwork( + [4, 4, 4, 4], + nonlinear_activation="LeakyReLU", + nonlinear_activation_params={"negative_slope": 0.2}, + freq_axis_kernel_size=3, + aux_context_window=0).to(device) + summary(net) + for k, v in net2.named_parameters(): + print(k, v.shape) + net.state_dict()[k].set_value(v.data.cpu().numpy()) + + c = paddle.randn([4, 80, 180]) + synchronize() + with timer(unit='s') as t: + out = net(c) + synchronize() + print(f"paddle conv_in_upsample_net forward takes {t.elapse}s.") + + with timer(unit='s') as t: + out.sum().backward() + synchronize() + print(f"paddle conv_in_upsample_net backward takes {t.elapse}s.") + + c_torch = torch.as_tensor(c.numpy()).to(device) + torch.cuda.synchronize() + with timer(unit='s') as t: + out2 = net2(c_torch) + print(f"torch conv_in_upsample_net forward takes {t.elapse}s.") + + with timer(unit='s') as t: + out2.sum().backward() + print(f"torch conv_in_upsample_net backward takes {t.elapse}s.") + + print("forward check") + print(out.numpy()[0]) + print(out2.data.cpu().numpy()[0]) + + print("backward check") + print(net.conv_in.weight.grad.numpy()[0]) + print(net2.conv_in.weight.grad.data.cpu().numpy()[0]) + + +def test_residual_block(): + net = ResidualBlock(dilation=9) + net2 = residual_block.ResidualBlock(dilation=9) + summary(net) + summary(net2) + for k, v in net2.named_parameters(): + net.state_dict()[k].set_value(v.data.cpu().numpy()) + + x = paddle.randn([4, 64, 180]) + c = paddle.randn([4, 80, 180]) + res, skip = net(x, c) + res2, skip2 = net2(torch.as_tensor(x.numpy()), torch.as_tensor(c.numpy())) + + print("forward:") + print(res.numpy()[0]) + print(res2.data.cpu().numpy()[0]) + print(skip.numpy()[0]) + print(skip2.data.cpu().numpy()[0]) + + (res.sum() + skip.sum()).backward() + (res2.sum() + skip2.sum()).backward() + + print("backward:") + print(net.conv.weight.grad.numpy().squeeze()[0]) + print(net2.conv.weight.grad.data.cpu().numpy().squeeze()[0]) + + +def test_pwg_generator(): + net = PWGGenerator( + layers=9, + stacks=3, + upsample_scales=[4, 4, 4, 4], + nonlinear_activation="LeakyReLU", + nonlinear_activation_params={"negative_slope": 0.5}, + use_weight_norm=True) + net2 = pwgan.ParallelWaveGANGenerator( + layers=9, + stacks=3, + upsample_params={ + "upsample_scales": [4, 4, 4, 4], + "nonlinear_activation": "LeakyReLU", + "nonlinear_activation_params": { + "negative_slope": 0.5 + } + }, + use_weight_norm=True).to(device) + summary(net) + summary(net2) + for k, v in net2.named_parameters(): + p = net.state_dict()[k] + if k.endswith("_g"): + p.set_value(v.data.cpu().numpy().reshape([-1])) + else: + p.set_value(v.data.cpu().numpy()) + x = paddle.randn([4, 1, 80 * 256]) + c = paddle.randn([4, 80, 80 + 4]) + + synchronize() + with timer(unit='s') as t: + out = net(x, c) + synchronize() + print(f"paddle generator forward takes {t.elapse}s.") + + synchronize() + with timer(unit='s') as t: + out.sum().backward() + synchronize() + print(f"paddle generator backward takes {t.elapse}s.") + + x_torch = torch.as_tensor(x.numpy()).to(device) + c_torch = torch.as_tensor(c.numpy()).to(device) + + torch.cuda.synchronize() + with timer(unit='s') as t: + out2 = net2(x_torch, c_torch) + torch.cuda.synchronize() + print(f"torch generator forward takes {t.elapse}s.") + + torch.cuda.synchronize() + with timer(unit='s') as t: + out2.sum().backward() + torch.cuda.synchronize() + print(f"torch generator backward takes {t.elapse}s.") + + print("test forward:") + print(out.numpy()[0]) + print(out2.data.cpu().numpy()[0]) + + print("test backward:") + print("wv") + print(net.first_conv.weight_v.grad.numpy().squeeze()) + print(net2.first_conv.weight_v.grad.data.cpu().numpy().squeeze()) + + print("wg") + print(net.first_conv.weight_g.grad.numpy().squeeze()) + print(net2.first_conv.weight_g.grad.data.cpu().numpy().squeeze()) + # print(out.shape) + + +def test_pwg_discriminator(): + net = PWGDiscriminator() + net2 = pwgan.ParallelWaveGANDiscriminator().to(device) + summary(net) + summary(net2) + for k, v in net2.named_parameters(): + p = net.state_dict()[k] + if k.endswith("_g"): + p.set_value(v.data.cpu().numpy().reshape([-1])) + else: + p.set_value(v.data.cpu().numpy()) + x = paddle.randn([4, 1, 180 * 256]) + + synchronize() + with timer() as t: + y = net(x) + synchronize() + print(f"forward takes {t.elapse}s.") + + synchronize() + with timer() as t: + y.sum().backward() + synchronize() + print(f"backward takes {t.elapse}s.") + + x_torch = torch.as_tensor(x.numpy()).to(device) + torch.cuda.synchronize() + with timer() as t: + y2 = net2(x_torch) + torch.cuda.synchronize() + print(f"forward takes {t.elapse}s.") + + torch.cuda.synchronize() + with timer() as t: + y2.sum().backward() + torch.cuda.synchronize() + print(f"backward takes {t.elapse}s.") + + print("test forward:") + print(y.numpy()[0]) + print(y2.data.cpu().numpy()[0]) + + print("test backward:") + print(net.conv_layers[0].weight_v.grad.numpy().squeeze()) + print(net2.conv_layers[0].weight_v.grad.data.cpu().numpy().squeeze()) + + +def test_residual_pwg_discriminator(): + net = ResidualPWGDiscriminator() + net2 = pwgan.ResidualParallelWaveGANDiscriminator() + summary(net) + summary(net2) + for k, v in net2.named_parameters(): + p = net.state_dict()[k] + if k.endswith("_g"): + p.set_value(v.data.cpu().numpy().reshape([-1])) + else: + p.set_value(v.data.cpu().numpy()) + x = paddle.randn([4, 1, 180 * 256]) + y = net(x) + y2 = net2(torch.as_tensor(x.numpy())) + print(y.numpy()[0]) + print(y2.data.cpu().numpy()[0]) + print(y.shape) diff --git a/tests/unit/tts/test_raise.py b/tests/unit/tts/test_raise.py new file mode 100644 index 00000000..7abdadfe --- /dev/null +++ b/tests/unit/tts/test_raise.py @@ -0,0 +1,50 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import paddle +from paddle.static import InputSpec + + +def sinusoid_position_encoding(num_positions: int, + feature_size: int, + omega: float=1.0, + start_pos: int=0, + dtype=None) -> paddle.Tensor: + # return tensor shape (num_positions, feature_size) + + if (feature_size % 2 != 0): + raise ValueError("size should be divisible by 2") + dtype = dtype or paddle.get_default_dtype() + + channel = paddle.arange(0, feature_size, 2, dtype=dtype) + index = paddle.arange(start_pos, start_pos + num_positions, 1, dtype=dtype) + p = (paddle.unsqueeze(index, -1) * + omega) / (10000.0**(channel / float(feature_size))) + encodings = paddle.zeros([num_positions, feature_size], dtype=dtype) + encodings[:, 0::2] = paddle.sin(p) + encodings[:, 1::2] = paddle.cos(p) + return encodings + + +def call_it(x): + shape = paddle.shape(x) + a = shape[0] + b = shape[1] + c = sinusoid_position_encoding(a, b) + return c + + +call_it(paddle.randn([8, 32])) +m = paddle.jit.to_static( + call_it, input_spec=[InputSpec([-1, -1], dtype=paddle.int32)]) +m(paddle.randn([8, 32]).astype(paddle.int32)) diff --git a/tests/unit/tts/test_reporter.py b/tests/unit/tts/test_reporter.py new file mode 100644 index 00000000..bba81d62 --- /dev/null +++ b/tests/unit/tts/test_reporter.py @@ -0,0 +1,52 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import numpy as np + +from parakeet.training.reporter import report +from parakeet.training.reporter import scope +from parakeet.training.reporter import Summary + + +def test_reporter_scope(): + first = {} + second = {} + third = {} + + with scope(first): + report("first_begin", 1) + with scope(second): + report("second_begin", 2) + with scope(third): + report("third_begin", 3) + report("third_end", 4) + report("seconf_end", 5) + report("first_end", 6) + + assert first == {'first_begin': 1, 'first_end': 6} + assert second == {'second_begin': 2, 'seconf_end': 5} + assert third == {'third_begin': 3, 'third_end': 4} + print(first) + print(second) + print(third) + + +def test_summary(): + summary = Summary() + summary.add(1) + summary.add(2) + summary.add(3) + state = summary.make_statistics() + print(state) + np.testing.assert_allclose( + np.array(list(state)), np.array([2.0, np.std([1, 2, 3])])) diff --git a/tests/unit/tts/test_snapshot.py b/tests/unit/tts/test_snapshot.py new file mode 100644 index 00000000..e940a81f --- /dev/null +++ b/tests/unit/tts/test_snapshot.py @@ -0,0 +1,51 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import shutil +from itertools import count + +from paddle import nn +from paddle.optimizer import Adam + +from parakeet.training.extensions.snapshot import Snapshot +from parakeet.training.trainer import Trainer +from parakeet.training.updater import StandardUpdater + + +def test_snapshot(): + model = nn.Linear(3, 4) + optimizer = Adam(parameters=model.parameters()) + + # use a simplest iterable object as dataloader + dataloader = count() + + # hack the training proecss: training does nothing except increse iteration + updater = StandardUpdater(model, optimizer, dataloader=dataloader) + updater.update_core = lambda x: None + + trainer = Trainer( + updater, stop_trigger=(1000, 'iteration'), out='temp_test_snapshot') + shutil.rmtree(trainer.out, ignore_errors=True) + + snap = Snapshot(max_size=5) + trigger = (10, 'iteration') + trainer.extend(snap, name='snapshot', trigger=trigger, priority=0) + + trainer.run() + + checkpoint_dir = trainer.out / "checkpoints" + snapshots = sorted(list(checkpoint_dir.glob("snapshot_iter_*.pdz"))) + for snap in snapshots: + print(snap) + assert len(snapshots) == 5 + shutil.rmtree(trainer.out) diff --git a/tests/unit/tts/test_stft.py b/tests/unit/tts/test_stft.py new file mode 100644 index 00000000..8e6ce470 --- /dev/null +++ b/tests/unit/tts/test_stft.py @@ -0,0 +1,73 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import librosa +import numpy as np +import paddle +import torch +from parallel_wavegan.losses import stft_loss as sl +from scipy import signal + +from parakeet.modules.stft_loss import MultiResolutionSTFTLoss +from parakeet.modules.stft_loss import STFT + + +def test_stft(): + stft = STFT(n_fft=1024, hop_length=256, win_length=1024) + x = paddle.uniform([4, 46080]) + S = stft.magnitude(x) + window = signal.get_window('hann', 1024, fftbins=True) + D2 = torch.stft( + torch.as_tensor(x.numpy()), + n_fft=1024, + hop_length=256, + win_length=1024, + window=torch.as_tensor(window)) + S2 = (D2**2).sum(-1).sqrt() + S3 = np.abs( + librosa.stft(x.numpy()[0], n_fft=1024, hop_length=256, win_length=1024)) + print(S2.shape) + print(S.numpy()[0]) + print(S2.data.cpu().numpy()[0]) + print(S3) + + +def test_torch_stft(): + # NOTE: torch.stft use no window by default + x = np.random.uniform(-1.0, 1.0, size=(46080, )) + window = signal.get_window('hann', 1024, fftbins=True) + D2 = torch.stft( + torch.as_tensor(x), + n_fft=1024, + hop_length=256, + win_length=1024, + window=torch.as_tensor(window)) + D3 = librosa.stft( + x, n_fft=1024, hop_length=256, win_length=1024, window='hann') + print(D2[:, :, 0].data.cpu().numpy()[:, 30:60]) + print(D3.real[:, 30:60]) + # print(D3.imag[:, 30:60]) + + +def test_multi_resolution_stft_loss(): + net = MultiResolutionSTFTLoss() + net2 = sl.MultiResolutionSTFTLoss() + + x = paddle.uniform([4, 46080]) + y = paddle.uniform([4, 46080]) + sc, m = net(x, y) + sc2, m2 = net2(torch.as_tensor(x.numpy()), torch.as_tensor(y.numpy())) + print(sc.numpy()) + print(sc2.data.cpu().numpy()) + print(m.numpy()) + print(m2.data.cpu().numpy()) diff --git a/tests/unit/tts/test_to_static.py b/tests/unit/tts/test_to_static.py new file mode 100644 index 00000000..b8ff3002 --- /dev/null +++ b/tests/unit/tts/test_to_static.py @@ -0,0 +1,64 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import math + +import paddle +from paddle import nn +from paddle.jit import to_static +from paddle.static import InputSpec + + +def test_applicative_evaluation(): + def m_sqrt2(x): + return paddle.scale(x, math.sqrt(2)) + + subgraph = to_static(m_sqrt2, input_spec=[InputSpec([-1])]) + paddle.jit.save(subgraph, './temp_test_to_static') + + fn = paddle.jit.load('./temp_test_to_static') + x = paddle.arange(10, dtype=paddle.float32) + y = fn(x) + + print(x) + print(y) + + +def test_nested_sequential(): + class Net(nn.Layer): + def __init__(self): + super().__init__() + group1 = nn.Sequential( + nn.Linear(2, 3), + nn.Sigmoid(), ) + group2 = nn.Sequential( + nn.Sequential(nn.Linear(3, 3)), + nn.Linear(3, 4), + nn.ReLU(), ) + self.layers = nn.Sequential(group1, group2) + + def forward(self, x): + return self.layers(x) + + net = Net() + x = paddle.randn([4, 2]) + y = net(x) + print(y) + + subgraph = to_static(net, input_spec=[InputSpec([-1, 2])]) + paddle.jit.save(subgraph, './temp_test_to_static') + + fn = paddle.jit.load('./temp_test_to_static') + y = fn(x) + + print(y) diff --git a/utils/compute_statistics.py b/utils/compute_statistics.py new file mode 100644 index 00000000..84e50ded --- /dev/null +++ b/utils/compute_statistics.py @@ -0,0 +1,111 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +"""Calculate statistics of feature files.""" +import argparse +import logging +from pathlib import Path + +import jsonlines +import numpy as np +from sklearn.preprocessing import StandardScaler +from tqdm import tqdm + +from parakeet.datasets.data_table import DataTable + + +def main(): + """Run preprocessing process.""" + parser = argparse.ArgumentParser( + description="Compute mean and variance of dumped raw features.") + parser.add_argument( + "--metadata", type=str, help="json file with id and file paths ") + parser.add_argument( + "--field-name", + type=str, + help="name of the field to compute statistics for.") + + parser.add_argument( + "--output", + type=str, + help="path to save statistics. if not provided, " + "stats will be saved in the above root directory with name stats.npy") + + def str2bool(str): + return True if str.lower() == 'true' else False + + parser.add_argument( + "--use-relative-path", + type=str2bool, + default=False, + help="whether use relative path in metadata") + + parser.add_argument( + "--verbose", + type=int, + default=1, + help="logging level. higher is more logging. (default=1)") + args = parser.parse_args() + + # set logger + if args.verbose > 1: + logging.basicConfig( + level=logging.DEBUG, + format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s" + ) + elif args.verbose > 0: + logging.basicConfig( + level=logging.INFO, + format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s" + ) + else: + logging.basicConfig( + level=logging.WARN, + format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s" + ) + logging.warning('Skip DEBUG/INFO messages') + + # check directory existence + if args.output is None: + args.output = Path( + args.metadata).parent.with_name(args.field_name + "_stats.npy") + else: + args.output = Path(args.output) + args.output.parent.mkdir(parents=True, exist_ok=True) + + with jsonlines.open(args.metadata, 'r') as reader: + metadata = list(reader) + + if args.use_relative_path: + # if use_relative_path in preprocess, covert it to absolute path here + metadata_dir = Path(args.metadata).parent + for item in metadata: + item["feats"] = str(metadata_dir / item["feats"]) + dataset = DataTable( + metadata, + fields=[args.field_name], + converters={args.field_name: np.load}, ) + logging.info(f"The number of files = {len(dataset)}.") + + # calculate statistics + scaler = StandardScaler() + for datum in tqdm(dataset): + # StandardScalar supports (*, num_features) by default + scaler.partial_fit(datum[args.field_name]) + + stats = np.stack([scaler.mean_, scaler.scale_], axis=0) + np.save(str(args.output), stats.astype(np.float32), allow_pickle=False) + + +if __name__ == "__main__": + main() diff --git a/utils/gen_duration_from_textgrid.py b/utils/gen_duration_from_textgrid.py new file mode 100644 index 00000000..b2a5fa3d --- /dev/null +++ b/utils/gen_duration_from_textgrid.py @@ -0,0 +1,113 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import argparse +import os +from pathlib import Path + +import librosa +import numpy as np +import yaml +from praatio import tgio +from yacs.config import CfgNode + + +def readtg(tg_path, sample_rate=24000, n_shift=300): + alignment = tgio.openTextgrid(tg_path, readRaw=True) + phones = [] + ends = [] + for interval in alignment.tierDict["phones"].entryList: + phone = interval.label + phones.append(phone) + ends.append(interval.end) + frame_pos = librosa.time_to_frames(ends, sr=sample_rate, hop_length=n_shift) + durations = np.diff(frame_pos, prepend=0) + assert len(durations) == len(phones) + # merge "" and sp in the end + if phones[-1] == "" and len(phones) > 1 and phones[-2] == "sp": + phones = phones[:-1] + durations[-2] += durations[-1] + durations = durations[:-1] + # replace the last "sp" with "sil" in MFA1.x + phones[-1] = "sil" if phones[-1] == "sp" else phones[-1] + # replace the edge "" with "sil", replace the inner "" with "sp" + new_phones = [] + for i, phn in enumerate(phones): + if phn == "": + if i in {0, len(phones) - 1}: + new_phones.append("sil") + else: + new_phones.append("sp") + else: + new_phones.append(phn) + phones = new_phones + results = "" + for (p, d) in zip(phones, durations): + results += p + " " + str(d) + " " + return results.strip() + + +# assume that the directory structure of inputdir is inputdir/speaker/*.TextGrid +# in MFA1.x, there are blank labels("") in the end, and maybe "sp" before it +# in MFA2.x, there are blank labels("") in the begin and the end, while no "sp" and "sil" anymore +# we replace it with "sil" +def gen_duration_from_textgrid(inputdir, output, sample_rate=24000, + n_shift=300): + # key: utt_id, value: (speaker, phn_durs) + durations_dict = {} + list_dir = os.listdir(inputdir) + speakers = [dir for dir in list_dir if os.path.isdir(inputdir / dir)] + for speaker in speakers: + subdir = inputdir / speaker + for file in os.listdir(subdir): + if file.endswith(".TextGrid"): + tg_path = subdir / file + name = file.split(".")[0] + durations_dict[name] = (speaker, readtg( + tg_path, sample_rate=sample_rate, n_shift=n_shift)) + with open(output, "w") as wf: + for name in sorted(durations_dict.keys()): + wf.write(name + "|" + durations_dict[name][0] + "|" + + durations_dict[name][1] + "\n") + + +def main(): + # parse config and args + parser = argparse.ArgumentParser( + description="Preprocess audio and then extract features.") + parser.add_argument( + "--inputdir", + default=None, + type=str, + help="directory to alignment files.") + parser.add_argument( + "--output", type=str, required=True, help="output duration file.") + parser.add_argument("--sample-rate", type=int, help="the sample of wavs.") + parser.add_argument( + "--n-shift", + type=int, + help="the n_shift of time_to_freames, also called hop_length.") + parser.add_argument( + "--config", type=str, help="config file with fs and n_shift.") + + args = parser.parse_args() + with open(args.config) as f: + config = CfgNode(yaml.safe_load(f)) + + inputdir = Path(args.inputdir).expanduser() + output = Path(args.output).expanduser() + gen_duration_from_textgrid(inputdir, output, config.fs, config.n_shift) + + +if __name__ == "__main__": + main()

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