@ -67,7 +67,7 @@ There are two common ways to define a model which consists of several modules.
```
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 PaddleSpeech TTS, 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.
In the directory structure of PaddleSpeech TTS, modules with high reusability are placed in `paddlespeech.t2s.modules`, but models for specific tasks are placed in `paddlespeech.t2s.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.
## PaddleSpeech TTS's Data Components
Another critical componnet for a deep learning project is data.
@ -93,7 +93,7 @@ Then we need to select a format for saving metadata to the hard disk. There are
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`.
The implementation of `DataTable` can be found in `paddlespeech/t2s/datasets/data_table.py`.
```python
class DataTable(Dataset):
"""Dataset to load and convert data for general purpose.
@ -179,9 +179,9 @@ We think this method is a little ugly. We prefer to return the necessary informa
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.
There is a module level variable in `paddlespeech/t2s/training/reporter.py` `OBSERVATIONS`，which is a `Dict` to store key-value.
@ -39,7 +39,7 @@ There are silence in the edge of AISHELL-3's wavs, and the audio amplitude is ve
We use Montreal Force Aligner 1.0. The label in aishell3 include pinyin，so the lexicon we provided to MFA is pinyin rather than Chinese characters. And the prosody marks(`$` and `%`) need to be removed. You shoud preprocess the dataset into the format which MFA needs, the texts have the same name with wavs and have the suffix `.lab`.
We use [lexicon.txt](https://github.com/PaddlePaddle/DeepSpeech/blob/develop/parakeet/exps/voice_cloning/tacotron2_ge2e/lexicon.txt) as the lexicon.
We use [lexicon.txt](https://github.com/PaddlePaddle/DeepSpeech/blob/develop/paddlespeech/t2s/exps/voice_cloning/tacotron2_ge2e/lexicon.txt) as the lexicon.
You can download the alignment results from here [alignment_aishell3.tar.gz](https://paddlespeech.bj.bcebos.com/Parakeet/alignment_aishell3.tar.gz), or train your own MFA model reference to [use_mfa example](https://github.com/PaddlePaddle/DeepSpeech/tree/develop/examples/other/use_mfa) (use MFA1.x now) of our repo.
Hui Zhang
4 years ago