diff --git a/README.md b/README.md index ace7f7c57..6ac520f98 100644 --- a/README.md +++ b/README.md @@ -173,7 +173,7 @@ Via the easy-to-use, efficient, flexible and scalable implementation, our vision - 🏆 **Streaming ASR and TTS System**: we provide production ready streaming asr and streaming tts system. - 💯 **Rule-based Chinese frontend**: our frontend contains Text Normalization and Grapheme-to-Phoneme (G2P, including Polyphone and Tone Sandhi). Moreover, we use self-defined linguistic rules to adapt Chinese context. - 📦 **Varieties of Functions that Vitalize both Industrial and Academia**: - - 🛎️ *Implementation of critical audio tasks*: this toolkit contains audio functions like Automatic Speech Recognition, Text-to-Speech Synthesis, Speaker Verfication, KeyWord Spotting, Audio Classification, and Speech Translation, etc. + - 🛎️ *Implementation of critical audio tasks*: this toolkit contains audio functions like Automatic Speech Recognition, Text-to-Speech Synthesis, Speaker Verification, KeyWord Spotting, Audio Classification, and Speech Translation, etc. - 🔬 *Integration of mainstream models and datasets*: the toolkit implements modules that participate in the whole pipeline of the speech tasks, and uses mainstream datasets like LibriSpeech, LJSpeech, AIShell, CSMSC, etc. See also [model list](#model-list) for more details. - 🧩 *Cascaded models application*: as an extension of the typical traditional audio tasks, we combine the workflows of the aforementioned tasks with other fields like Natural language processing (NLP) and Computer Vision (CV). @@ -1025,7 +1025,7 @@ You are warmly welcome to submit questions in [discussions](https://github.com/P - Many thanks to [vpegasus](https://github.com/vpegasus)/[xuesebot](https://github.com/vpegasus/xuesebot) for developing a rasa chatbot,which is able to speak and listen thanks to PaddleSpeech. - Many thanks to [chenkui164](https://github.com/chenkui164)/[FastASR](https://github.com/chenkui164/FastASR) for the C++ inference implementation of PaddleSpeech ASR. - Many thanks to [heyudage](https://github.com/heyudage)/[VoiceTyping](https://github.com/heyudage/VoiceTyping) for the real-time voice typing tool implementation of PaddleSpeech ASR streaming services. -- Many thanks to [EscaticZheng](https://github.com/EscaticZheng)/[ps3.9wheel-install](https://github.com/EscaticZheng/ps3.9wheel-install) for the python3.9 prebuilt wheel for PaddleSpeech installation in Windows without Viusal Studio. +- Many thanks to [EscaticZheng](https://github.com/EscaticZheng)/[ps3.9wheel-install](https://github.com/EscaticZheng/ps3.9wheel-install) for the python3.9 prebuilt wheel for PaddleSpeech installation in Windows without Visual Studio. Besides, PaddleSpeech depends on a lot of open source repositories. See [references](./docs/source/reference.md) for more information. - Many thanks to [chinobing](https://github.com/chinobing)/[FastAPI-PaddleSpeech-Audio-To-Text](https://github.com/chinobing/FastAPI-PaddleSpeech-Audio-To-Text) for converting audio to text based on FastAPI and PaddleSpeech. - Many thanks to [MistEO](https://github.com/MistEO)/[Pallas-Bot](https://github.com/MistEO/Pallas-Bot) for QQ bot based on PaddleSpeech TTS. diff --git a/audio/paddleaudio/compliance/kaldi.py b/audio/paddleaudio/compliance/kaldi.py index a94ec4053..d2184ebe3 100644 --- a/audio/paddleaudio/compliance/kaldi.py +++ b/audio/paddleaudio/compliance/kaldi.py @@ -233,7 +233,7 @@ def spectrogram(waveform: Tensor, round_to_power_of_two (bool, optional): If True, round window size to power of two by zero-padding input to FFT. Defaults to True. sr (int, optional): Sample rate of input waveform. Defaults to 16000. - snip_edges (bool, optional): Drop samples in the end of waveform that cann't fit a signal frame when it + snip_edges (bool, optional): Drop samples in the end of waveform that can't fit a signal frame when it is set True. Otherwise performs reflect padding to the end of waveform. Defaults to True. subtract_mean (bool, optional): Whether to subtract mean of feature files. Defaults to False. window_type (str, optional): Choose type of window for FFT computation. Defaults to "povey". @@ -443,7 +443,7 @@ def fbank(waveform: Tensor, round_to_power_of_two (bool, optional): If True, round window size to power of two by zero-padding input to FFT. Defaults to True. sr (int, optional): Sample rate of input waveform. Defaults to 16000. - snip_edges (bool, optional): Drop samples in the end of waveform that cann't fit a signal frame when it + snip_edges (bool, optional): Drop samples in the end of waveform that can't fit a signal frame when it is set True. Otherwise performs reflect padding to the end of waveform. Defaults to True. subtract_mean (bool, optional): Whether to subtract mean of feature files. Defaults to False. use_energy (bool, optional): Add an dimension with energy of spectrogram to the output. Defaults to False. @@ -566,7 +566,7 @@ def mfcc(waveform: Tensor, round_to_power_of_two (bool, optional): If True, round window size to power of two by zero-padding input to FFT. Defaults to True. sr (int, optional): Sample rate of input waveform. Defaults to 16000. - snip_edges (bool, optional): Drop samples in the end of waveform that cann't fit a signal frame when it + snip_edges (bool, optional): Drop samples in the end of waveform that can't fit a signal frame when it is set True. Otherwise performs reflect padding to the end of waveform. Defaults to True. subtract_mean (bool, optional): Whether to subtract mean of feature files. Defaults to False. use_energy (bool, optional): Add an dimension with energy of spectrogram to the output. Defaults to False. diff --git a/audio/paddleaudio/compliance/librosa.py b/audio/paddleaudio/compliance/librosa.py index c24d6d497..d0cee642a 100644 --- a/audio/paddleaudio/compliance/librosa.py +++ b/audio/paddleaudio/compliance/librosa.py @@ -527,7 +527,7 @@ def melspectrogram(x: np.ndarray, if fmax is None: fmax = sr // 2 if fmin < 0 or fmin >= fmax: - raise ParameterError('fmin and fmax must statisfy 0 Tuple[List[str], List[int]]: if not os.path.isdir(os.path.join(DATA_HOME, self.audio_path)) or \ not os.path.isfile(os.path.join(DATA_HOME, self.meta)): - download_and_decompress(self.archieves, DATA_HOME) + download_and_decompress(self.archives, DATA_HOME) meta_info = self._get_meta_info() diff --git a/audio/paddleaudio/datasets/gtzan.py b/audio/paddleaudio/datasets/gtzan.py index a76e9208e..299391968 100644 --- a/audio/paddleaudio/datasets/gtzan.py +++ b/audio/paddleaudio/datasets/gtzan.py @@ -35,7 +35,7 @@ class GTZAN(AudioClassificationDataset): https://ieeexplore.ieee.org/document/1021072/ """ - archieves = [ + archives = [ { 'url': 'http://opihi.cs.uvic.ca/sound/genres.tar.gz', 'md5': '5b3d6dddb579ab49814ab86dba69e7c7', @@ -57,7 +57,7 @@ class GTZAN(AudioClassificationDataset): feat_type='raw', **kwargs): """ - Ags: + Args: mode (:obj:`str`, `optional`, defaults to `train`): It identifies the dataset mode (train or dev). seed (:obj:`int`, `optional`, defaults to 0): @@ -85,7 +85,7 @@ class GTZAN(AudioClassificationDataset): split) -> Tuple[List[str], List[int]]: if not os.path.isdir(os.path.join(DATA_HOME, self.audio_path)) or \ not os.path.isfile(os.path.join(DATA_HOME, self.meta)): - download_and_decompress(self.archieves, DATA_HOME) + download_and_decompress(self.archives, DATA_HOME) meta_info = self._get_meta_info() random.seed(seed) # shuffle samples to split data diff --git a/audio/paddleaudio/datasets/rirs_noises.py b/audio/paddleaudio/datasets/rirs_noises.py index 74418daa2..e5d193537 100644 --- a/audio/paddleaudio/datasets/rirs_noises.py +++ b/audio/paddleaudio/datasets/rirs_noises.py @@ -30,7 +30,7 @@ __all__ = ['OpenRIRNoise'] class OpenRIRNoise(Dataset): - archieves = [ + archives = [ { 'url': 'http://www.openslr.org/resources/28/rirs_noises.zip', 'md5': 'e6f48e257286e05de56413b4779d8ffb', @@ -76,7 +76,7 @@ class OpenRIRNoise(Dataset): print(f"rirs noises base path: {self.base_path}") if not os.path.isdir(self.base_path): download_and_decompress( - self.archieves, self.base_path, decompress=True) + self.archives, self.base_path, decompress=True) else: print( f"{self.base_path} already exists, we will not download and decompress again" diff --git a/audio/paddleaudio/datasets/tess.py b/audio/paddleaudio/datasets/tess.py index e34eaea37..a770c5b0c 100644 --- a/audio/paddleaudio/datasets/tess.py +++ b/audio/paddleaudio/datasets/tess.py @@ -37,7 +37,7 @@ class TESS(AudioClassificationDataset): https://doi.org/10.5683/SP2/E8H2MF """ - archieves = [ + archives = [ { 'url': 'https://bj.bcebos.com/paddleaudio/datasets/TESS_Toronto_emotional_speech_set.zip', @@ -66,7 +66,7 @@ class TESS(AudioClassificationDataset): feat_type='raw', **kwargs): """ - Ags: + Args: mode (:obj:`str`, `optional`, defaults to `train`): It identifies the dataset mode (train or dev). seed (:obj:`int`, `optional`, defaults to 0): @@ -93,7 +93,7 @@ class TESS(AudioClassificationDataset): def _get_data(self, mode, seed, n_folds, split) -> Tuple[List[str], List[int]]: if not os.path.isdir(os.path.join(DATA_HOME, self.audio_path)): - download_and_decompress(self.archieves, DATA_HOME) + download_and_decompress(self.archives, DATA_HOME) wav_files = [] for root, _, files in os.walk(os.path.join(DATA_HOME, self.audio_path)): diff --git a/audio/paddleaudio/datasets/urban_sound.py b/audio/paddleaudio/datasets/urban_sound.py index 43d1b36c4..b9a5fc030 100644 --- a/audio/paddleaudio/datasets/urban_sound.py +++ b/audio/paddleaudio/datasets/urban_sound.py @@ -35,7 +35,7 @@ class UrbanSound8K(AudioClassificationDataset): https://dl.acm.org/doi/10.1145/2647868.2655045 """ - archieves = [ + archives = [ { 'url': 'https://zenodo.org/record/1203745/files/UrbanSound8K.tar.gz', @@ -62,7 +62,7 @@ class UrbanSound8K(AudioClassificationDataset): super(UrbanSound8K, self).__init__( files=files, labels=labels, feat_type=feat_type, **kwargs) """ - Ags: + Args: mode (:obj:`str`, `optional`, defaults to `train`): It identifies the dataset mode (train or dev). split (:obj:`int`, `optional`, defaults to 1): @@ -81,7 +81,7 @@ class UrbanSound8K(AudioClassificationDataset): def _get_data(self, mode: str, split: int) -> Tuple[List[str], List[int]]: if not os.path.isdir(os.path.join(DATA_HOME, self.audio_path)) or \ not os.path.isfile(os.path.join(DATA_HOME, self.meta)): - download_and_decompress(self.archieves, DATA_HOME) + download_and_decompress(self.archives, DATA_HOME) meta_info = self._get_meta_info() diff --git a/audio/paddleaudio/datasets/voxceleb.py b/audio/paddleaudio/datasets/voxceleb.py index 1fafb5176..225859700 100644 --- a/audio/paddleaudio/datasets/voxceleb.py +++ b/audio/paddleaudio/datasets/voxceleb.py @@ -34,7 +34,7 @@ __all__ = ['VoxCeleb'] class VoxCeleb(Dataset): source_url = 'https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/' - archieves_audio_dev = [ + archives_audio_dev = [ { 'url': source_url + 'vox1_dev_wav_partaa', 'md5': 'e395d020928bc15670b570a21695ed96', @@ -52,13 +52,13 @@ class VoxCeleb(Dataset): 'md5': '7bb1e9f70fddc7a678fa998ea8b3ba19', }, ] - archieves_audio_test = [ + archives_audio_test = [ { 'url': source_url + 'vox1_test_wav.zip', 'md5': '185fdc63c3c739954633d50379a3d102', }, ] - archieves_meta = [ + archives_meta = [ { 'url': 'https://www.robots.ox.ac.uk/~vgg/data/voxceleb/meta/veri_test2.txt', @@ -135,11 +135,11 @@ class VoxCeleb(Dataset): if not os.path.isdir(self.wav_path): print("start to download the voxceleb1 dataset") download_and_decompress( # multi-zip parts concatenate to vox1_dev_wav.zip - self.archieves_audio_dev, + self.archives_audio_dev, self.base_path, decompress=False) download_and_decompress( # download the vox1_test_wav.zip and unzip - self.archieves_audio_test, + self.archives_audio_test, self.base_path, decompress=True) @@ -157,7 +157,7 @@ class VoxCeleb(Dataset): if not os.path.isdir(self.meta_path): print("prepare the meta data") download_and_decompress( - self.archieves_meta, self.meta_path, decompress=False) + self.archives_meta, self.meta_path, decompress=False) # Data preparation. if not os.path.isdir(self.csv_path): diff --git a/audio/tests/backends/sox_io/save_test.py b/audio/tests/backends/sox_io/save_test.py index e73f9f63f..de500dc12 100644 --- a/audio/tests/backends/sox_io/save_test.py +++ b/audio/tests/backends/sox_io/save_test.py @@ -41,7 +41,7 @@ class TestSaveBase(TempDirMixin): test_mode: str="path", ): """`save` function produces file that is comparable with `sox` command - To compare that the file produced by `save` function agains the file produced by + To compare that the file produced by `save` function against the file produced by the equivalent `sox` command, we need to load both files. But there are many formats that cannot be opened with common Python modules (like SciPy). diff --git a/dataset/chime3_background/chime3_background.py b/dataset/chime3_background/chime3_background.py index 4f081e6c3..6ec8fdfed 100644 --- a/dataset/chime3_background/chime3_background.py +++ b/dataset/chime3_background/chime3_background.py @@ -109,7 +109,7 @@ def create_manifest(data_dir, manifest_path): def prepare_chime3(url, md5sum, target_dir, manifest_path): - """Download, unpack and create summmary manifest file.""" + """Download, unpack and create summary manifest file.""" if not os.path.exists(os.path.join(target_dir, "CHiME3")): # download filepath = download(url, md5sum, target_dir, diff --git a/dataset/timit/timit.py b/dataset/timit/timit.py index 2943ff548..492c6702d 100644 --- a/dataset/timit/timit.py +++ b/dataset/timit/timit.py @@ -210,7 +210,7 @@ def create_manifest(data_dir, manifest_path_prefix): def prepare_dataset(url, md5sum, target_dir, manifest_path): - """Download, unpack and create summmary manifest file. + """Download, unpack and create summary manifest file. """ filepath = os.path.join(target_dir, "TIMIT.zip") if not os.path.exists(filepath): diff --git a/demos/TTSAndroid/README.md b/demos/TTSAndroid/README.md index a26172cb6..6a6860400 100644 --- a/demos/TTSAndroid/README.md +++ b/demos/TTSAndroid/README.md @@ -8,7 +8,7 @@ ### 环境准备 -1. 在本地环境安装好 Android Studio 工具，详细安装方法请见 [Android Stuido 官网](https://developer.android.com/studio)。 +1. 在本地环境安装好 Android Studio 工具，详细安装方法请见 [Android Studio 官网](https://developer.android.com/studio)。 2. 准备一部 Android 手机，并开启 USB 调试模式。开启方法: `手机设置 -> 查找开发者选项 -> 打开开发者选项和 USB 调试模式`。 **注意**： @@ -20,10 +20,10 @@ 2. 手机连接电脑，打开 USB 调试和文件传输模式，并在 Android Studio 上连接自己的手机设备（手机需要开启允许从 USB 安装软件权限）。 **注意：** ->1. 如果您在导入项目、编译或者运行过程中遇到 NDK 配置错误的提示，请打开 `File > Project Structure > SDK Location`，修改 `Andriod NDK location` 为您本机配置的 NDK 所在路径。 ->2. 如果您是通过 Andriod Studio 的 SDK Tools 下载的 NDK (见本章节"环境准备")，可以直接点击下拉框选择默认路径。 +>1. 如果您在导入项目、编译或者运行过程中遇到 NDK 配置错误的提示，请打开 `File > Project Structure > SDK Location`，修改 `Android NDK location` 为您本机配置的 NDK 所在路径。 +>2. 如果您是通过 Android Studio 的 SDK Tools 下载的 NDK (见本章节"环境准备")，可以直接点击下拉框选择默认路径。 >3. 还有一种 NDK 配置方法，你可以在 `TTSAndroid/local.properties` 文件中手动添加 NDK 路径配置 `nkd.dir=/root/android-ndk-r20b` ->4. 如果以上步骤仍旧无法解决 NDK 配置错误，请尝试根据 Andriod Studio 官方文档中的[更新 Android Gradle 插件](https://developer.android.com/studio/releases/gradle-plugin?hl=zh-cn#updating-plugin)章节，尝试更新 Android Gradle plugin 版本。 +>4. 如果以上步骤仍旧无法解决 NDK 配置错误，请尝试根据 Android Studio 官方文档中的[更新 Android Gradle 插件](https://developer.android.com/studio/releases/gradle-plugin?hl=zh-cn#updating-plugin)章节，尝试更新 Android Gradle plugin 版本。 3. 点击 Run 按钮，自动编译 APP 并安装到手机。(该过程会自动下载 Paddle Lite 预测库和模型，需要联网) 成功后效果如下： diff --git a/demos/TTSCppFrontend/src/front/front_interface.cpp b/demos/TTSCppFrontend/src/front/front_interface.cpp index e7b08c798..dd6329ff7 100644 --- a/demos/TTSCppFrontend/src/front/front_interface.cpp +++ b/demos/TTSCppFrontend/src/front/front_interface.cpp @@ -115,27 +115,27 @@ int FrontEngineInterface::init() { // 生成词典（词到音素的映射） if (0 != GenDict(_word2phone_path, &word_phone_map)) { - LOG(ERROR) << "Genarate word2phone dict failed"; + LOG(ERROR) << "Generate word2phone dict failed"; return -1; } // 生成音素字典（音素到音素id的映射） if (0 != GenDict(_phone2id_path, &phone_id_map)) { - LOG(ERROR) << "Genarate phone2id dict failed"; + LOG(ERROR) << "Generate phone2id dict failed"; return -1; } // 生成音调字典（音调到音调id的映射） if (_separate_tone == "true") { if (0 != GenDict(_tone2id_path, &tone_id_map)) { - LOG(ERROR) << "Genarate tone2id dict failed"; + LOG(ERROR) << "Generate tone2id dict failed"; return -1; } } // 生成繁简字典（繁体到简体id的映射） if (0 != GenDict(_trand2simp_path, &trand_simp_map)) { - LOG(ERROR) << "Genarate trand2simp dict failed"; + LOG(ERROR) << "Generate trand2simp dict failed"; return -1; } @@ -263,7 +263,7 @@ int FrontEngineInterface::GetWordsIds( if (0 != GetInitialsFinals(word, &word_initials, &word_finals)) { LOG(ERROR) - << "Genarate the word_initials and word_finals of " + << "Generate the word_initials and word_finals of " << word << " failed"; return -1; } @@ -304,7 +304,7 @@ int FrontEngineInterface::GetWordsIds( // 音素到音素id if (0 != Phone2Phoneid(phone, phoneids, toneids)) { - LOG(ERROR) << "Genarate the phone id of " << word << " failed"; + LOG(ERROR) << "Generate the phone id of " << word << " failed"; return -1; } } @@ -916,11 +916,11 @@ int FrontEngineInterface::NeuralSandhi(const std::string &word, if (find(must_neural_tone_words.begin(), must_neural_tone_words.end(), word) != must_neural_tone_words.end() || - (word_num >= 2 && - find(must_neural_tone_words.begin(), - must_neural_tone_words.end(), - ppspeech::wstring2utf8string(word_wstr.substr( - word_num - 2))) != must_neural_tone_words.end())) { + (word_num >= 2 && find(must_neural_tone_words.begin(), + must_neural_tone_words.end(), + ppspeech::wstring2utf8string( + word_wstr.substr(word_num - 2))) != + must_neural_tone_words.end())) { (*finals).back() = (*finals).back().replace((*finals).back().length() - 1, 1, "5"); } diff --git a/demos/audio_searching/README.md b/demos/audio_searching/README.md index 5b3890382..d3852ace3 100644 --- a/demos/audio_searching/README.md +++ b/demos/audio_searching/README.md @@ -217,7 +217,7 @@ Then to start the system server, and it provides HTTP backend services. - memory：132G dataset： -- CN-Celeb, train size 650,000, test size 10,000, dimention 192, distance L2 +- CN-Celeb, train size 650,000, test size 10,000, dimension 192, distance L2 recall and elapsed time statistics are shown in the following figure： @@ -226,7 +226,7 @@ recall and elapsed time statistics are shown in the following figure： The retrieval framework based on Milvus takes about 2.9 milliseconds to retrieve on the premise of 90% recall rate, and it takes about 500 milliseconds for feature extraction (testing audio takes about 5 seconds), that is, a single audio test takes about 503 milliseconds in total, which can meet most application scenarios. -* compute embeding takes 500 ms +* compute embedding takes 500 ms * retrieval with cosine takes 2.9 ms * total takes 503 ms diff --git a/demos/audio_searching/requirements.txt b/demos/audio_searching/requirements.txt index 3c0f05afc..e6391694c 100644 --- a/demos/audio_searching/requirements.txt +++ b/demos/audio_searching/requirements.txt @@ -1,5 +1,4 @@ diskcache -dtaidistane fastapi librosa==0.8.0 numpy==1.22.0 diff --git a/demos/audio_searching/src/milvus_helpers.py b/demos/audio_searching/src/milvus_helpers.py index 1699e892e..801284ffd 100644 --- a/demos/audio_searching/src/milvus_helpers.py +++ b/demos/audio_searching/src/milvus_helpers.py @@ -77,13 +77,13 @@ class MilvusHelper: field1 = FieldSchema( name="id", dtype=DataType.INT64, - descrition="int64", + description="int64", is_primary=True, auto_id=True) field2 = FieldSchema( name="embedding", dtype=DataType.FLOAT_VECTOR, - descrition="speaker embeddings", + description="speaker embeddings", dim=VECTOR_DIMENSION, is_primary=False) schema = CollectionSchema( diff --git a/demos/speech_server/README.md b/demos/speech_server/README.md index 178374428..b44ec73fd 100644 --- a/demos/speech_server/README.md +++ b/demos/speech_server/README.md @@ -42,7 +42,7 @@ Currently the engine type supports two forms: python and inference (Paddle Infer paddlespeech_server start --help ``` Arguments: - - `config_file`: yaml file of the app, defalut: ./conf/application.yaml + - `config_file`: yaml file of the app, default: ./conf/application.yaml - `log_file`: log file. Default: ./log/paddlespeech.log Output: diff --git a/demos/speech_web/speech_server/main.py b/demos/speech_web/speech_server/main.py index f4678628f..1e4d5ed3d 100644 --- a/demos/speech_web/speech_server/main.py +++ b/demos/speech_web/speech_server/main.py @@ -225,7 +225,7 @@ async def websocket_endpoint_online(websocket: WebSocket): websocket (WebSocket): the websocket instance """ - #1. the interface wait to accept the websocket protocal header + #1. the interface wait to accept the websocket protocol header # and only we receive the header, it establish the connection with specific thread await websocket.accept() @@ -238,7 +238,7 @@ async def websocket_endpoint_online(websocket: WebSocket): connection_handler = None try: - #4. we do a loop to process the audio package by package according the protocal + #4. we do a loop to process the audio package by package according the protocol # and only if the client send finished signal, we will break the loop while True: # careful here, changed the source code from starlette.websockets diff --git a/demos/speech_web/web_client/package-lock.json b/demos/speech_web/web_client/package-lock.json index 95e082ecd..5b303286a 100644 --- a/demos/speech_web/web_client/package-lock.json +++ b/demos/speech_web/web_client/package-lock.json @@ -61,11 +61,12 @@ } }, "node_modules/@babel/runtime": { - 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resolved "https://registry.npmmirror.com/@element-plus/icons-vue/-/icons-vue-1.1.4.tgz" + resolved "https://registry.npmjs.org/@element-plus/icons-vue/-/icons-vue-1.1.4.tgz" integrity sha512-Iz/nHqdp1sFPmdzRwHkEQQA3lKvoObk8azgABZ81QUOpW9s/lUyQVUSh0tNtEPZXQlKwlSh7SPgoVxzrE0uuVQ== "@element-plus/icons-vue@^2.0.9": - version "2.0.9" - resolved "https://registry.npmmirror.com/@element-plus/icons-vue/-/icons-vue-2.0.9.tgz#b7777c57534522e387303d194451d50ff549d49a" - integrity sha512-okdrwiVeKBmW41Hkl0eMrXDjzJwhQMuKiBOu17rOszqM+LS/yBYpNQNV5Jvoh06Wc+89fMmb/uhzf8NZuDuUaQ== + version "2.3.1" + resolved "https://registry.npmjs.org/@element-plus/icons-vue/-/icons-vue-2.3.1.tgz" + integrity sha512-XxVUZv48RZAd87ucGS48jPf6pKu0yV5UCg9f4FFwtrYxXOwWuVJo6wOvSLKEoMQKjv8GsX/mhP6UsC1lRwbUWg== "@floating-ui/core@^0.6.1": version "0.6.1" @@ -86,11 +61,6 @@ dependencies: "@floating-ui/core" "^0.6.1" -"@jridgewell/sourcemap-codec@^1.5.0": - version "1.5.0" - resolved "https://registry.yarnpkg.com/@jridgewell/sourcemap-codec/-/sourcemap-codec-1.5.0.tgz#3188bcb273a414b0d215fd22a58540b989b9409a" - 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version "3.5.13" - resolved "https://registry.yarnpkg.com/@vue/compiler-sfc/-/compiler-sfc-3.5.13.tgz#461f8bd343b5c06fac4189c4fef8af32dea82b46" - integrity sha512-6VdaljMpD82w6c2749Zhf5T9u5uLBWKnVue6XWxprDobftnletJ8+oel7sexFfM3qIxNmVE7LSFGTpv6obNyaQ== - dependencies: - "@babel/parser" "^7.25.3" - "@vue/compiler-core" "3.5.13" - "@vue/compiler-dom" "3.5.13" - "@vue/compiler-ssr" "3.5.13" - "@vue/shared" "3.5.13" - estree-walker "^2.0.2" - magic-string "^0.30.11" - postcss "^8.4.48" - source-map-js "^1.2.0" - "@vue/compiler-ssr@3.2.32": version "3.2.32" resolved "https://registry.npmmirror.com/@vue/compiler-ssr/-/compiler-ssr-3.2.32.tgz" @@ -197,14 +133,6 @@ "@vue/compiler-dom" "3.2.32" "@vue/shared" "3.2.32" -"@vue/compiler-ssr@3.5.13": - version "3.5.13" - resolved "https://registry.yarnpkg.com/@vue/compiler-ssr/-/compiler-ssr-3.5.13.tgz#e771adcca6d3d000f91a4277c972a996d07f43ba" - integrity sha512-wMH6vrYHxQl/IybKJagqbquvxpWCuVYpoUJfCqFZwa/JY1GdATAQ+TgVtgrwwMZ0D07QhA99rs/EAAWfvG6KpA== - 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- `config_file`: yaml file of the app, defalut: `./conf/application.yaml` + - `config_file`: yaml file of the app, default: `./conf/application.yaml` - `log_file`: log file. Default: `./log/paddlespeech.log` Output: @@ -307,7 +307,7 @@ wget -c https://paddlespeech.cdn.bcebos.com/PaddleAudio/zh.wav - Command Line **Note:** The default deployment of the server is on the 'CPU' device, which can be deployed on the 'GPU' by modifying the 'device' parameter in the service configuration file. ```bash - In PaddleSpeech/demos/streaming_asr_server directory to lanuch punctuation service + In PaddleSpeech/demos/streaming_asr_server directory to launch punctuation service paddlespeech_server start --config_file conf/punc_application.yaml ``` @@ -414,7 +414,7 @@ wget -c https://paddlespeech.cdn.bcebos.com/PaddleAudio/zh.wav By default, each server is deployed on the 'CPU' device and speech recognition and punctuation prediction can be deployed on different 'GPU' by modifying the' device 'parameter in the service configuration file respectively. -We use `streaming_ asr_server.py` and `punc_server.py` two services to lanuch streaming speech recognition and punctuation prediction services respectively. And the `websocket_client.py` script can be used to call streaming speech recognition and punctuation prediction services at the same time. +We use `streaming_ asr_server.py` and `punc_server.py` two services to launch streaming speech recognition and punctuation prediction services respectively. And the `websocket_client.py` script can be used to call streaming speech recognition and punctuation prediction services at the same time. ### 1. Start two server @@ -584,7 +584,7 @@ bash server.sh By default, each server is deployed on the 'CPU' device and speech recognition and punctuation prediction can be deployed on different 'GPU' by modifying the' device 'parameter in the service configuration file respectively. -We use `streaming_ asr_server.py` and `punc_server.py` two services to lanuch streaming speech recognition and punctuation prediction services respectively. And the `websocket_client_srt.py` script can be used to call streaming speech recognition and punctuation prediction services at the same time, and will generate the corresponding subtitle (.srt format). +We use `streaming_ asr_server.py` and `punc_server.py` two services to launch streaming speech recognition and punctuation prediction services respectively. And the `websocket_client_srt.py` script can be used to call streaming speech recognition and punctuation prediction services at the same time, and will generate the corresponding subtitle (.srt format). **need to install ffmpeg before running this script** diff --git a/demos/streaming_tts_server/README.md b/demos/streaming_tts_server/README.md index ad87bebdc..01cd69620 100644 --- a/demos/streaming_tts_server/README.md +++ b/demos/streaming_tts_server/README.md @@ -52,7 +52,7 @@ The configuration file can be found in `conf/tts_online_application.yaml`. paddlespeech_server start --help ``` Arguments: - - `config_file`: yaml file of the app, defalut: ./conf/tts_online_application.yaml + - `config_file`: yaml file of the app, default: ./conf/tts_online_application.yaml - `log_file`: log file. Default: ./log/paddlespeech.log Output: @@ -180,7 +180,7 @@ The configuration file can be found in `conf/tts_online_application.yaml`. paddlespeech_server start --help ``` Arguments: - - `config_file`: yaml file of the app, defalut: ./conf/tts_online_application.yaml + - `config_file`: yaml file of the app, default: ./conf/tts_online_application.yaml - `log_file`: log file. Default: ./log/paddlespeech.log Output: diff --git a/demos/streaming_tts_serving_fastdeploy/streaming_tts_serving/1/model.py b/demos/streaming_tts_serving_fastdeploy/streaming_tts_serving/1/model.py index 46473fdb2..324cbf978 100644 --- a/demos/streaming_tts_serving_fastdeploy/streaming_tts_serving/1/model.py +++ b/demos/streaming_tts_serving_fastdeploy/streaming_tts_serving/1/model.py @@ -75,7 +75,7 @@ class TritonPythonModel: def initialize(self, args): """`initialize` is called only once when the model is being loaded. Implementing `initialize` function is optional. This function allows - the model to intialize any state associated with this model. + the model to initialize any state associated with this model. Parameters ---------- args : dict diff --git a/demos/text_to_speech/README.md b/demos/text_to_speech/README.md index b58777def..61c20c371 100644 --- a/demos/text_to_speech/README.md +++ b/demos/text_to_speech/README.md @@ -99,7 +99,7 @@ The input of this demo should be a text of the specific language that can be pas Arguments: - `input`(required): Input text to generate.. - `am`: Acoustic model type of tts task. Default: `fastspeech2_csmsc`. - - `am_config`: Config of acoustic model. Use deault config when it is None. Default: `None`. + - `am_config`: Config of acoustic model. Use default config when it is None. Default: `None`. - `am_ckpt`: Acoustic model checkpoint. Use pretrained model when it is None. Default: `None`. - `am_stat`: Mean and standard deviation used to normalize spectrogram when training acoustic model. Default: `None`. - `phones_dict`: Phone vocabulary file. Default: `None`. @@ -107,7 +107,7 @@ The input of this demo should be a text of the specific language that can be pas - `speaker_dict`: speaker id map file. Default: `None`. - `spk_id`: Speaker id for multi speaker acoustic model. Default: `0`. - `voc`: Vocoder type of tts task. Default: `pwgan_csmsc`. - - `voc_config`: Config of vocoder. Use deault config when it is None. Default: `None`. + - `voc_config`: Config of vocoder. Use default config when it is None. Default: `None`. - `voc_ckpt`: Vocoder checkpoint. Use pretrained model when it is None. Default: `None`. - `voc_stat`: Mean and standard deviation used to normalize spectrogram when training vocoder. Default: `None`. - `lang`: Language of tts task. Default: `zh`. diff --git a/demos/whisper/README.md b/demos/whisper/README.md index ccd695d5e..1d8e8c442 100644 --- a/demos/whisper/README.md +++ b/demos/whisper/README.md @@ -42,7 +42,7 @@ Whisper model trained by OpenAI whisper https://github.com/openai/whisper - `model`: Model type of asr task. Default: `whisper-large`. - `task`: Output type. Default: `transcribe`. - `lang`: Model language. Default: ``. Use `en` to choice English-only model. Now [medium,base,small,tiny] size can support English-only. - - `size`: Model size for decode. Defalut: `large`. Now can support [large,medium,base,small,tiny]. + - `size`: Model size for decode. Default: `large`. Now can support [large,medium,base,small,tiny]. - `language`: Set decode language. Default: `None`. Forcibly set the recognized language, which is determined by the model itself by default. - `sample_rate`: Sample rate of the model. Default: `16000`. Other sampling rates are not supported now. - `config`: Config of asr task. Use pretrained model when it is None. Default: `None`. diff --git a/docs/source/tts/advanced_usage.md b/docs/source/tts/advanced_usage.md index 4dd742b70..9f86689e7 100644 --- a/docs/source/tts/advanced_usage.md +++ b/docs/source/tts/advanced_usage.md @@ -303,7 +303,7 @@ The experimental codes in PaddleSpeech TTS are generally organized as follows: . ├── README.md (help information) ├── conf -│ └── default.yaml (defalut config) +│ └── default.yaml (default config) ├── local │ ├── preprocess.sh (script to call data preprocessing.py) │ ├── synthesize.sh (script to call synthesis.py) diff --git a/examples/aishell/asr0/local/train.sh b/examples/aishell/asr0/local/train.sh index c0da33257..8c12066c4 100755 --- a/examples/aishell/asr0/local/train.sh +++ b/examples/aishell/asr0/local/train.sh @@ -26,8 +26,8 @@ if [ ${seed} != 0 ]; then export FLAGS_cudnn_deterministic=True fi -# default memeory allocator strategy may case gpu training hang -# for no OOM raised when memory exhaused +# default memory allocator strategy may case gpu training hang +# for no OOM raised when memory exhausted export FLAGS_allocator_strategy=naive_best_fit if [ ${ngpu} == 0 ]; then diff --git a/examples/aishell/asr1/local/train.sh b/examples/aishell/asr1/local/train.sh index 3d4f052a3..ea64d42c4 100755 --- a/examples/aishell/asr1/local/train.sh +++ b/examples/aishell/asr1/local/train.sh @@ -35,8 +35,8 @@ echo ${ips_config} mkdir -p exp -# default memeory allocator strategy may case gpu training hang -# for no OOM raised when memory exhaused +# default memory allocator strategy may case gpu training hang +# for no OOM raised when memory exhausted export FLAGS_allocator_strategy=naive_best_fit if [ ${ngpu} == 0 ]; then diff --git a/examples/aishell/asr3/cmd.sh b/examples/aishell/asr3/cmd.sh index 7b70ef5e0..c87b0f233 100755 --- a/examples/aishell/asr3/cmd.sh +++ b/examples/aishell/asr3/cmd.sh @@ -54,8 +54,8 @@ elif [ "${cmd_backend}" = sge ]; then # "sbatch" (Slurm) elif [ "${cmd_backend}" = slurm ]; then # The default setting is written in conf/slurm.conf. - # You must change "-p cpu" and "-p gpu" for the "partion" for your environment. - # To know the "partion" names, type "sinfo". + # You must change "-p cpu" and "-p gpu" for the "partition" for your environment. + # To know the "partition" names, type "sinfo". # You can use "--gpu * " by default for slurm and it is interpreted as "--gres gpu:*" # The devices are allocated exclusively using "${CUDA_VISIBLE_DEVICES}". diff --git a/examples/aishell3/tts3/conf/conformer.yaml b/examples/aishell3/tts3/conf/conformer.yaml index 0834bfe3f..ae305ac81 100644 --- a/examples/aishell3/tts3/conf/conformer.yaml +++ b/examples/aishell3/tts3/conf/conformer.yaml @@ -42,7 +42,7 @@ model: 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_layers: 5 # number of layers of postnet postnet_filts: 5 # filter size of conv layers in postnet postnet_chans: 256 # number of channels of conv layers in postnet encoder_normalize_before: True # whether to perform layer normalization before the input @@ -66,14 +66,14 @@ model: 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_kernel_size: 5 # kernel size of conv layers 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_kernel_size: 3 # kernel size of conv layers 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 diff --git a/examples/aishell3/tts3/conf/default.yaml b/examples/aishell3/tts3/conf/default.yaml index e65b5d0ec..68a3c7fb9 100644 --- a/examples/aishell3/tts3/conf/default.yaml +++ b/examples/aishell3/tts3/conf/default.yaml @@ -42,7 +42,7 @@ model: 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_layers: 5 # number of layers of postnet 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 @@ -60,14 +60,14 @@ model: 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_kernel_size: 5 # kernel size of conv layers 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_kernel_size: 3 # kernel size of conv layers 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 diff --git a/examples/aishell3/vc1/conf/default.yaml b/examples/aishell3/vc1/conf/default.yaml index ac4956742..bde47b6db 100644 --- a/examples/aishell3/vc1/conf/default.yaml +++ b/examples/aishell3/vc1/conf/default.yaml @@ -42,7 +42,7 @@ model: 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_layers: 5 # number of layers of postnet 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 @@ -60,14 +60,14 @@ model: 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_kernel_size: 5 # kernel size of conv layers 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_kernel_size: 3 # kernel size of conv layers 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 diff --git a/examples/aishell3/vc2/conf/default.yaml b/examples/aishell3/vc2/conf/default.yaml index 5ef37f812..6374b4c87 100644 --- a/examples/aishell3/vc2/conf/default.yaml +++ b/examples/aishell3/vc2/conf/default.yaml @@ -42,7 +42,7 @@ model: 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_layers: 5 # number of layers of postnet 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 @@ -60,14 +60,14 @@ model: 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_kernel_size: 5 # kernel size of conv layers 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_kernel_size: 3 # kernel size of conv layers 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 diff --git a/examples/aishell3/voc5/conf/default.yaml b/examples/aishell3/voc5/conf/default.yaml index 728a90369..73953a1e7 100644 --- a/examples/aishell3/voc5/conf/default.yaml +++ b/examples/aishell3/voc5/conf/default.yaml @@ -39,7 +39,7 @@ generator_params: use_additional_convs: True # Whether to use additional conv layer in residual blocks. bias: True # Whether to use bias parameter in conv. nonlinear_activation: "leakyrelu" # Nonlinear activation type. - nonlinear_activation_params: # Nonlinear activation paramters. + nonlinear_activation_params: # Nonlinear activation parameters. negative_slope: 0.1 use_weight_norm: True # Whether to apply weight normalization. @@ -77,7 +77,7 @@ discriminator_params: max_downsample_channels: 1024 # Maximum number of channels in downsampling conv layers. bias: True # Whether to use bias parameter in conv layer." nonlinear_activation: "leakyrelu" # Nonlinear activation. - nonlinear_activation_params: # Nonlinear activation paramters. + nonlinear_activation_params: # Nonlinear activation parameters. negative_slope: 0.1 use_weight_norm: True # Whether to apply weight normalization. use_spectral_norm: False # Whether to apply spectral normalization. diff --git a/examples/canton/tts3/conf/default.yaml b/examples/canton/tts3/conf/default.yaml index a101e6eea..ce1536abb 100644 --- a/examples/canton/tts3/conf/default.yaml +++ b/examples/canton/tts3/conf/default.yaml @@ -45,7 +45,7 @@ model: 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_layers: 5 # number of layers of postnet 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 @@ -63,14 +63,14 @@ model: 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_kernel_size: 5 # kernel size of conv layers 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_kernel_size: 3 # kernel size of conv layers 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 diff --git a/examples/csmsc/jets/conf/default.yaml b/examples/csmsc/jets/conf/default.yaml index 1dafd20c1..0999b5bc0 100644 --- a/examples/csmsc/jets/conf/default.yaml +++ b/examples/csmsc/jets/conf/default.yaml @@ -60,14 +60,14 @@ model: 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_kernel_size: 5 # kernel size of conv layers 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_kernel_size: 3 # kernel size of conv layers 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 diff --git a/examples/csmsc/tts0/README.md b/examples/csmsc/tts0/README.md index 374270713..6269b419a 100644 --- a/examples/csmsc/tts0/README.md +++ b/examples/csmsc/tts0/README.md @@ -99,8 +99,10 @@ pwg_baker_ckpt_0.4 ``` `./local/synthesize.sh` calls `${BIN_DIR}/../synthesize.py`, which can synthesize waveform from `metadata.jsonl`. ```bash -CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh ${conf_path} ${train_output_path} ${ckpt_name} +CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name} ``` +`--stage` controls the vocoder model during synthesis, which can use stage `0-4` to select the vocoder to use {`pwgan`, `multi band melgan`, `style melgan`, ` hifigan`, `wavernn`} + ```text usage: synthesize.py [-h] [--am {speedyspeech_csmsc,fastspeech2_csmsc,fastspeech2_ljspeech,fastspeech2_aishell3,fastspeech2_vctk,tacotron2_csmsc,tacotron2_ljspeech,tacotron2_aishell3}] @@ -146,9 +148,12 @@ optional arguments: output dir. ``` `./local/synthesize_e2e.sh` calls `${BIN_DIR}/../synthesize_e2e.py`, which can synthesize waveform from text file. + ```bash -CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh ${conf_path} ${train_output_path} ${ckpt_name} +CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name} ``` +`--stage` controls the vocoder model during synthesis, which can use stage `0,1,3,4` to select the vocoder to use{`pwgan`, `multi band melgan`, `hifigan`, `wavernn`} + ```text usage: synthesize_e2e.py [-h] [--am {speedyspeech_csmsc,speedyspeech_aishell3,fastspeech2_csmsc,fastspeech2_ljspeech,fastspeech2_aishell3,fastspeech2_vctk,tacotron2_csmsc,tacotron2_ljspeech}] diff --git a/examples/csmsc/tts0/run.sh b/examples/csmsc/tts0/run.sh index 8f06e933c..83bb02a5f 100755 --- a/examples/csmsc/tts0/run.sh +++ b/examples/csmsc/tts0/run.sh @@ -27,13 +27,15 @@ if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then fi if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then - # synthesize, vocoder is pwgan - CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 + # synthesize, vocoder is pwgan by default stage 0 + # stage 1-4 to select the vocoder to use {multi band melgan, style melgan, hifigan, wavernn} + CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 fi if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then - # synthesize_e2e, vocoder is pwgan - CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 + # synthesize_e2e, vocoder is pwgan by default stage 0 + # stage 1,3,4 to select the vocoder to use {multi band melgan, hifigan, wavernn} + CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 fi if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then diff --git a/examples/csmsc/tts2/README.md b/examples/csmsc/tts2/README.md index 478ae4127..3c6e7d96c 100644 --- a/examples/csmsc/tts2/README.md +++ b/examples/csmsc/tts2/README.md @@ -116,8 +116,10 @@ pwg_baker_ckpt_0.4 ``` `./local/synthesize.sh` calls `${BIN_DIR}/../synthesize.py`, which can synthesize waveform from `metadata.jsonl`. ```bash -CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh ${conf_path} ${train_output_path} ${ckpt_name} +CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name} ``` +`--stage` controls the vocoder model during synthesis, which can use stage `0-4` to select the vocoder to use {`pwgan`, `multi band melgan`, `style melgan`, `hifigan`, `wavernn`} + ```text usage: synthesize.py [-h] [--am {speedyspeech_csmsc,fastspeech2_csmsc,fastspeech2_ljspeech,fastspeech2_aishell3,fastspeech2_vctk,tacotron2_csmsc,tacotron2_ljspeech,tacotron2_aishell3}] @@ -164,8 +166,10 @@ optional arguments: ``` `./local/synthesize_e2e.sh` calls `${BIN_DIR}/../synthesize_e2e.py`, which can synthesize waveform from text file. ```bash -CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh ${conf_path} ${train_output_path} ${ckpt_name} +CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name} ``` +`--stage` controls the vocoder model during synthesis, which can use stage `0,1,3,4` to select the vocoder to use {`pwgan`, `multi band melgan`, `hifigan`, `wavernn`} + ```text usage: synthesize_e2e.py [-h] [--am {speedyspeech_csmsc,speedyspeech_aishell3,fastspeech2_csmsc,fastspeech2_ljspeech,fastspeech2_aishell3,fastspeech2_vctk,tacotron2_csmsc,tacotron2_ljspeech}] diff --git a/examples/csmsc/tts2/run.sh b/examples/csmsc/tts2/run.sh index 5732ea3c7..6f62bc95b 100755 --- a/examples/csmsc/tts2/run.sh +++ b/examples/csmsc/tts2/run.sh @@ -27,13 +27,15 @@ if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then fi if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then - # synthesize, vocoder is pwgan by default - CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 + # synthesize, vocoder is pwgan by default stage 0 + # use stage 1-4 to select the vocoder to use {multi band melgan, style melgan, hifigan, wavernn} + CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 fi if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then - # synthesize_e2e, vocoder is pwgan by default - CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 + # synthesize_e2e, vocoder is pwgan by default stage 0 + # use stage 1,3,4 to select the vocoder to use {multi band melgan, hifigan, wavernn} + CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 fi if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then diff --git a/examples/csmsc/tts3/conf/cnndecoder.yaml b/examples/csmsc/tts3/conf/cnndecoder.yaml index 8b46fea44..d0bfe5079 100644 --- a/examples/csmsc/tts3/conf/cnndecoder.yaml +++ b/examples/csmsc/tts3/conf/cnndecoder.yaml @@ -43,7 +43,7 @@ model: 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_layers: 5 # number of layers of postnet 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 @@ -65,14 +65,14 @@ model: cnn_decoder_embedding_dim: 256 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_kernel_size: 5 # kernel size of conv layers 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_kernel_size: 3 # kernel size of conv layers 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 diff --git a/examples/csmsc/tts3/conf/conformer.yaml b/examples/csmsc/tts3/conf/conformer.yaml index fcad86150..f184450c2 100644 --- a/examples/csmsc/tts3/conf/conformer.yaml +++ b/examples/csmsc/tts3/conf/conformer.yaml @@ -42,7 +42,7 @@ model: 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_layers: 5 # number of layers of postnet postnet_filts: 5 # filter size of conv layers in postnet postnet_chans: 256 # number of channels of conv layers in postnet encoder_normalize_before: True # whether to perform layer normalization before the input @@ -66,14 +66,14 @@ model: 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_kernel_size: 5 # kernel size of conv layers 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_kernel_size: 3 # kernel size of conv layers 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 diff --git a/examples/csmsc/tts3/conf/default.yaml b/examples/csmsc/tts3/conf/default.yaml index 08b6f75ba..3a034cffc 100644 --- a/examples/csmsc/tts3/conf/default.yaml +++ b/examples/csmsc/tts3/conf/default.yaml @@ -42,7 +42,7 @@ model: 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_layers: 5 # number of layers of postnet 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 @@ -60,14 +60,14 @@ model: 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_kernel_size: 5 # kernel size of conv layers 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_kernel_size: 3 # kernel size of conv layers 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 diff --git a/examples/csmsc/tts3_rhy/run.sh b/examples/csmsc/tts3_rhy/run.sh index e49f43ee6..294ceded5 100755 --- a/examples/csmsc/tts3_rhy/run.sh +++ b/examples/csmsc/tts3_rhy/run.sh @@ -28,11 +28,13 @@ if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then fi if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then - # synthesize, vocoder is pwgan by default - CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 + # synthesize, vocoder is pwgan by default stage 0 + # use stage 1-4 to select the vocoder to use {multi band melgan, style melgan, hifigan, wavernn} + CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 fi if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then - # synthesize_e2e, vocoder is pwgan by default - CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 + # synthesize_e2e, vocoder is pwgan by default stage 0 + # use stage 1,3,4 to select the vocoder to use {multi band melgan, hifigan, wavernn} + CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 fi diff --git a/examples/csmsc/voc1/local/synthesize_e2e.sh b/examples/csmsc/voc1/local/synthesize_e2e.sh index 428c234ff..7e1a6e8b7 100644 --- a/examples/csmsc/voc1/local/synthesize_e2e.sh +++ b/examples/csmsc/voc1/local/synthesize_e2e.sh @@ -8,13 +8,13 @@ FLAGS_allocator_strategy=naive_best_fit \ FLAGS_fraction_of_gpu_memory_to_use=0.01 \ python3 ${BIN_DIR}/../../synthesize_e2e.py \ --am=fastspeech2_csmsc \ - --am_config=${config_path} \ - --am_ckpt=${train_output_path}/checkpoints/${ckpt_name} \ - --am_stat=dump/train/speech_stats.npy \ + --am_config=fastspeech2_nosil_baker_ckpt_0.4/default.yaml \ + --am_ckpt=fastspeech2_nosil_baker_ckpt_0.4/snapshot_iter_76000.pdz \ + --am_stat=fastspeech2_nosil_baker_ckpt_0.4/speech_stats.npy \ --voc=pwgan_csmsc \ - --voc_config=pwg_baker_ckpt_0.4/pwg_default.yaml \ - --voc_ckpt=pwg_baker_ckpt_0.4/pwg_snapshot_iter_400000.pdz \ - --voc_stat=pwg_baker_ckpt_0.4/pwg_stats.npy \ + --voc_config=${config_path} \ + --voc_ckpt=${train_output_path}/checkpoints/${ckpt_name} \ + --voc_stat=dump/train/feats_stats.npy \ --lang=zh \ --text=${BIN_DIR}/../../assets/sentences.txt \ --output_dir=${train_output_path}/test_e2e \ diff --git a/examples/csmsc/voc3/README.md b/examples/csmsc/voc3/README.md index a7807c727..667f5f0c9 100644 --- a/examples/csmsc/voc3/README.md +++ b/examples/csmsc/voc3/README.md @@ -86,7 +86,7 @@ Download pretrained MultiBand MelGAN model from [mb_melgan_csmsc_ckpt_0.1.1.zip] ```bash unzip mb_melgan_csmsc_ckpt_0.1.1.zip ``` -HiFiGAN checkpoint contains files listed below. +MultiBand MelGAN checkpoint contains files listed below. ```text mb_melgan_csmsc_ckpt_0.1.1 ├── default.yaml # default config used to train MultiBand MelGAN diff --git a/examples/csmsc/voc3/conf/default.yaml b/examples/csmsc/voc3/conf/default.yaml index a5ee17808..c424759d2 100644 --- a/examples/csmsc/voc3/conf/default.yaml +++ b/examples/csmsc/voc3/conf/default.yaml @@ -4,7 +4,7 @@ # This configuration requires ~ 8GB memory and will finish within 7 days on Titan V. # This configuration is based on full-band MelGAN but the hop size and sampling -# rate is different from the paper (16kHz vs 24kHz). The number of iteraions +# rate is different from the paper (16kHz vs 24kHz). The number of iterations # is not shown in the paper so currently we train 1M iterations (not sure enough # to converge). diff --git a/examples/csmsc/voc3/conf/finetune.yaml b/examples/csmsc/voc3/conf/finetune.yaml index 8c37ac302..2aeb3c3f3 100644 --- a/examples/csmsc/voc3/conf/finetune.yaml +++ b/examples/csmsc/voc3/conf/finetune.yaml @@ -4,7 +4,7 @@ # This configuration requires ~ 8GB memory and will finish within 7 days on Titan V. # This configuration is based on full-band MelGAN but the hop size and sampling -# rate is different from the paper (16kHz vs 24kHz). The number of iteraions +# rate is different from the paper (16kHz vs 24kHz). The number of iterations # is not shown in the paper so currently we train 1M iterations (not sure enough # to converge). diff --git a/examples/csmsc/voc5/conf/default.yaml b/examples/csmsc/voc5/conf/default.yaml index 38b94cf5c..4dc95ac32 100644 --- a/examples/csmsc/voc5/conf/default.yaml +++ b/examples/csmsc/voc5/conf/default.yaml @@ -38,7 +38,7 @@ generator_params: use_additional_convs: True # Whether to use additional conv layer in residual blocks. bias: True # Whether to use bias parameter in conv. nonlinear_activation: "leakyrelu" # Nonlinear activation type. - nonlinear_activation_params: # Nonlinear activation paramters. + nonlinear_activation_params: # Nonlinear activation parameters. negative_slope: 0.1 use_weight_norm: True # Whether to apply weight normalization. @@ -76,7 +76,7 @@ discriminator_params: max_downsample_channels: 1024 # Maximum number of channels in downsampling conv layers. bias: True # Whether to use bias parameter in conv layer." nonlinear_activation: "leakyrelu" # Nonlinear activation. - nonlinear_activation_params: # Nonlinear activation paramters. + nonlinear_activation_params: # Nonlinear activation parameters. negative_slope: 0.1 use_weight_norm: True # Whether to apply weight normalization. use_spectral_norm: False # Whether to apply spectral normalization. diff --git a/examples/csmsc/voc5/conf/finetune.yaml b/examples/csmsc/voc5/conf/finetune.yaml index 110ae052b..51be0706e 100644 --- a/examples/csmsc/voc5/conf/finetune.yaml +++ b/examples/csmsc/voc5/conf/finetune.yaml @@ -38,7 +38,7 @@ generator_params: use_additional_convs: True # Whether to use additional conv layer in residual blocks. bias: True # Whether to use bias parameter in conv. nonlinear_activation: "leakyrelu" # Nonlinear activation type. - nonlinear_activation_params: # Nonlinear activation paramters. + nonlinear_activation_params: # Nonlinear activation parameters. negative_slope: 0.1 use_weight_norm: True # Whether to apply weight normalization. @@ -76,7 +76,7 @@ discriminator_params: max_downsample_channels: 1024 # Maximum number of channels in downsampling conv layers. bias: True # Whether to use bias parameter in conv layer." nonlinear_activation: "leakyrelu" # Nonlinear activation. - nonlinear_activation_params: # Nonlinear activation paramters. + nonlinear_activation_params: # Nonlinear activation parameters. negative_slope: 0.1 use_weight_norm: True # Whether to apply weight normalization. use_spectral_norm: False # Whether to apply spectral normalization. diff --git a/examples/csmsc/voc5/conf/iSTFT.yaml b/examples/csmsc/voc5/conf/iSTFT.yaml index 06677d796..10b69f917 100644 --- a/examples/csmsc/voc5/conf/iSTFT.yaml +++ b/examples/csmsc/voc5/conf/iSTFT.yaml @@ -42,7 +42,7 @@ generator_params: use_additional_convs: True # Whether to use additional conv layer in residual blocks. bias: True # Whether to use bias parameter in conv. nonlinear_activation: "leakyrelu" # Nonlinear activation type. - nonlinear_activation_params: # Nonlinear activation paramters. + nonlinear_activation_params: # Nonlinear activation parameters. negative_slope: 0.1 use_weight_norm: True # Whether to apply weight normalization. @@ -83,7 +83,7 @@ discriminator_params: max_downsample_channels: 1024 # Maximum number of channels in downsampling conv layers. bias: True # Whether to use bias parameter in conv layer." nonlinear_activation: "leakyrelu" # Nonlinear activation. - nonlinear_activation_params: # Nonlinear activation paramters. + nonlinear_activation_params: # Nonlinear activation parameters. negative_slope: 0.1 use_weight_norm: True # Whether to apply weight normalization. use_spectral_norm: False # Whether to apply spectral normalization. diff --git a/examples/librispeech/asr0/local/train.sh b/examples/librispeech/asr0/local/train.sh index bb41fd554..e7d0b54c4 100755 --- a/examples/librispeech/asr0/local/train.sh +++ b/examples/librispeech/asr0/local/train.sh @@ -26,8 +26,8 @@ if [ ${seed} != 0 ]; then export FLAGS_cudnn_deterministic=True fi -# default memeory allocator strategy may case gpu training hang -# for no OOM raised when memory exhaused +# default memory allocator strategy may case gpu training hang +# for no OOM raised when memory exhausted export FLAGS_allocator_strategy=naive_best_fit if [ ${ngpu} == 0 ]; then diff --git a/examples/librispeech/asr1/cmd.sh b/examples/librispeech/asr1/cmd.sh index 7b70ef5e0..c87b0f233 100644 --- a/examples/librispeech/asr1/cmd.sh +++ b/examples/librispeech/asr1/cmd.sh @@ -54,8 +54,8 @@ elif [ "${cmd_backend}" = sge ]; then # "sbatch" (Slurm) elif [ "${cmd_backend}" = slurm ]; then # The default setting is written in conf/slurm.conf. - # You must change "-p cpu" and "-p gpu" for the "partion" for your environment. - # To know the "partion" names, type "sinfo". + # You must change "-p cpu" and "-p gpu" for the "partition" for your environment. + # To know the "partition" names, type "sinfo". # You can use "--gpu * " by default for slurm and it is interpreted as "--gres gpu:*" # The devices are allocated exclusively using "${CUDA_VISIBLE_DEVICES}". diff --git a/examples/librispeech/asr1/local/train.sh b/examples/librispeech/asr1/local/train.sh index e274b9133..55a88e116 100755 --- a/examples/librispeech/asr1/local/train.sh +++ b/examples/librispeech/asr1/local/train.sh @@ -29,8 +29,8 @@ fi # export FLAGS_cudnn_exhaustive_search=true # export FLAGS_conv_workspace_size_limit=4000 -# default memeory allocator strategy may case gpu training hang -# for no OOM raised when memory exhaused +# default memory allocator strategy may case gpu training hang +# for no OOM raised when memory exhausted export FLAGS_allocator_strategy=naive_best_fit if [ ${ngpu} == 0 ]; then diff --git a/examples/librispeech/asr2/cmd.sh b/examples/librispeech/asr2/cmd.sh index 7b70ef5e0..c87b0f233 100644 --- a/examples/librispeech/asr2/cmd.sh +++ b/examples/librispeech/asr2/cmd.sh @@ -54,8 +54,8 @@ elif [ "${cmd_backend}" = sge ]; then # "sbatch" (Slurm) elif [ "${cmd_backend}" = slurm ]; then # The default setting is written in conf/slurm.conf. - # You must change "-p cpu" and "-p gpu" for the "partion" for your environment. - # To know the "partion" names, type "sinfo". + # You must change "-p cpu" and "-p gpu" for the "partition" for your environment. + # To know the "partition" names, type "sinfo". # You can use "--gpu * " by default for slurm and it is interpreted as "--gres gpu:*" # The devices are allocated exclusively using "${CUDA_VISIBLE_DEVICES}". diff --git a/examples/librispeech/asr2/local/train.sh b/examples/librispeech/asr2/local/train.sh index c2f2d4b65..4c6723a7a 100755 --- a/examples/librispeech/asr2/local/train.sh +++ b/examples/librispeech/asr2/local/train.sh @@ -26,8 +26,8 @@ if [ ${seed} != 0 ]; then export FLAGS_cudnn_deterministic=True fi -# default memeory allocator strategy may case gpu training hang -# for no OOM raised when memory exhaused +# default memory allocator strategy may case gpu training hang +# for no OOM raised when memory exhausted export FLAGS_allocator_strategy=naive_best_fit if [ ${ngpu} == 0 ]; then diff --git a/examples/librispeech/asr3/cmd.sh b/examples/librispeech/asr3/cmd.sh index 7b70ef5e0..c87b0f233 100644 --- a/examples/librispeech/asr3/cmd.sh +++ b/examples/librispeech/asr3/cmd.sh @@ -54,8 +54,8 @@ elif [ "${cmd_backend}" = sge ]; then # "sbatch" (Slurm) elif [ "${cmd_backend}" = slurm ]; then # The default setting is written in conf/slurm.conf. - # You must change "-p cpu" and "-p gpu" for the "partion" for your environment. - # To know the "partion" names, type "sinfo". + # You must change "-p cpu" and "-p gpu" for the "partition" for your environment. + # To know the "partition" names, type "sinfo". # You can use "--gpu * " by default for slurm and it is interpreted as "--gres gpu:*" # The devices are allocated exclusively using "${CUDA_VISIBLE_DEVICES}". diff --git a/examples/librispeech/asr4/cmd.sh b/examples/librispeech/asr4/cmd.sh index 7b70ef5e0..c87b0f233 100644 --- a/examples/librispeech/asr4/cmd.sh +++ b/examples/librispeech/asr4/cmd.sh @@ -54,8 +54,8 @@ elif [ "${cmd_backend}" = sge ]; then # "sbatch" (Slurm) elif [ "${cmd_backend}" = slurm ]; then # The default setting is written in conf/slurm.conf. - # You must change "-p cpu" and "-p gpu" for the "partion" for your environment. - # To know the "partion" names, type "sinfo". + # You must change "-p cpu" and "-p gpu" for the "partition" for your environment. + # To know the "partition" names, type "sinfo". # You can use "--gpu * " by default for slurm and it is interpreted as "--gres gpu:*" # The devices are allocated exclusively using "${CUDA_VISIBLE_DEVICES}". diff --git a/examples/librispeech/asr5/cmd.sh b/examples/librispeech/asr5/cmd.sh index 7b70ef5e0..c87b0f233 100644 --- a/examples/librispeech/asr5/cmd.sh +++ b/examples/librispeech/asr5/cmd.sh @@ -54,8 +54,8 @@ elif [ "${cmd_backend}" = sge ]; then # "sbatch" (Slurm) elif [ "${cmd_backend}" = slurm ]; then # The default setting is written in conf/slurm.conf. - # You must change "-p cpu" and "-p gpu" for the "partion" for your environment. - # To know the "partion" names, type "sinfo". + # You must change "-p cpu" and "-p gpu" for the "partition" for your environment. + # To know the "partition" names, type "sinfo". # You can use "--gpu * " by default for slurm and it is interpreted as "--gres gpu:*" # The devices are allocated exclusively using "${CUDA_VISIBLE_DEVICES}". diff --git a/examples/ljspeech/tts1/conf/default.yaml b/examples/ljspeech/tts1/conf/default.yaml index 456b6a1e3..fecdd140e 100644 --- a/examples/ljspeech/tts1/conf/default.yaml +++ b/examples/ljspeech/tts1/conf/default.yaml @@ -34,7 +34,7 @@ model: # keyword arguments for the selected model 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_layers: 5 # number of layers of postnet 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 diff --git a/examples/ljspeech/tts3/README.md b/examples/ljspeech/tts3/README.md index cac214e74..12bd73777 100644 --- a/examples/ljspeech/tts3/README.md +++ b/examples/ljspeech/tts3/README.md @@ -105,8 +105,10 @@ pwg_ljspeech_ckpt_0.5 ``` `./local/synthesize.sh` calls `${BIN_DIR}/../synthesize.py`, which can synthesize waveform from `metadata.jsonl`. ```bash -CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh ${conf_path} ${train_output_path} ${ckpt_name} +CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name} ``` +`--stage` controls the vocoder model during synthesis, which can be `0` or `1`, use `pwgan` or `hifigan` model as vocoder. + ```text usage: synthesize.py [-h] [--am {speedyspeech_csmsc,fastspeech2_csmsc,fastspeech2_ljspeech,fastspeech2_aishell3,fastspeech2_vctk,tacotron2_csmsc,tacotron2_ljspeech,tacotron2_aishell3}] @@ -153,8 +155,10 @@ optional arguments: ``` `./local/synthesize_e2e.sh` calls `${BIN_DIR}/../synthesize_e2e.py`, which can synthesize waveform from text file. ```bash -CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh ${conf_path} ${train_output_path} ${ckpt_name} +CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name} ``` +`--stage` controls the vocoder model during synthesis, which can be `0` or `1`, use `pwgan` or `hifigan` model as vocoder. + ```text usage: synthesize_e2e.py [-h] [--am {speedyspeech_csmsc,speedyspeech_aishell3,fastspeech2_csmsc,fastspeech2_ljspeech,fastspeech2_aishell3,fastspeech2_vctk,tacotron2_csmsc,tacotron2_ljspeech}] diff --git a/examples/ljspeech/tts3/conf/default.yaml b/examples/ljspeech/tts3/conf/default.yaml index 5305c912f..eab4af03c 100644 --- a/examples/ljspeech/tts3/conf/default.yaml +++ b/examples/ljspeech/tts3/conf/default.yaml @@ -42,7 +42,7 @@ model: 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_layers: 5 # number of layers of postnet 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 @@ -60,14 +60,14 @@ model: 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_kernel_size: 5 # kernel size of conv layers 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_kernel_size: 3 # kernel size of conv layers 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 diff --git a/examples/ljspeech/tts3/run.sh b/examples/ljspeech/tts3/run.sh index 0d8da920c..b02126e6e 100755 --- a/examples/ljspeech/tts3/run.sh +++ b/examples/ljspeech/tts3/run.sh @@ -27,13 +27,13 @@ if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then fi if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then - # synthesize, vocoder is pwgan by default - CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 + # synthesize, vocoder is pwgan by default stage 0, stage 1 will use hifigan as vocoder + CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 fi if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then - # synthesize_e2e, vocoder is pwgan by default - CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 + # synthesize_e2e, vocoder is pwgan by default stage 0, stage 1 will use hifigan as vocoder + CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 fi if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then diff --git a/examples/ljspeech/voc5/conf/default.yaml b/examples/ljspeech/voc5/conf/default.yaml index 97c512204..e45d2d770 100644 --- a/examples/ljspeech/voc5/conf/default.yaml +++ b/examples/ljspeech/voc5/conf/default.yaml @@ -38,7 +38,7 @@ generator_params: use_additional_convs: True # Whether to use additional conv layer in residual blocks. bias: True # Whether to use bias parameter in conv. nonlinear_activation: "leakyrelu" # Nonlinear activation type. - nonlinear_activation_params: # Nonlinear activation paramters. + nonlinear_activation_params: # Nonlinear activation parameters. negative_slope: 0.1 use_weight_norm: True # Whether to apply weight normalization. @@ -76,7 +76,7 @@ discriminator_params: max_downsample_channels: 1024 # Maximum number of channels in downsampling conv layers. bias: True # Whether to use bias parameter in conv layer." nonlinear_activation: "leakyrelu" # Nonlinear activation. - nonlinear_activation_params: # Nonlinear activation paramters. + nonlinear_activation_params: # Nonlinear activation parameters. negative_slope: 0.1 use_weight_norm: True # Whether to apply weight normalization. use_spectral_norm: False # Whether to apply spectral normalization. diff --git a/examples/mustc/st1/cmd.sh b/examples/mustc/st1/cmd.sh index 7b70ef5e0..c87b0f233 100644 --- a/examples/mustc/st1/cmd.sh +++ b/examples/mustc/st1/cmd.sh @@ -54,8 +54,8 @@ elif [ "${cmd_backend}" = sge ]; then # "sbatch" (Slurm) elif [ "${cmd_backend}" = slurm ]; then # The default setting is written in conf/slurm.conf. - # You must change "-p cpu" and "-p gpu" for the "partion" for your environment. - # To know the "partion" names, type "sinfo". + # You must change "-p cpu" and "-p gpu" for the "partition" for your environment. + # To know the "partition" names, type "sinfo". # You can use "--gpu * " by default for slurm and it is interpreted as "--gres gpu:*" # The devices are allocated exclusively using "${CUDA_VISIBLE_DEVICES}". diff --git a/examples/opencpop/svs1/conf/default.yaml b/examples/opencpop/svs1/conf/default.yaml index 5d8060630..a1693923f 100644 --- a/examples/opencpop/svs1/conf/default.yaml +++ b/examples/opencpop/svs1/conf/default.yaml @@ -68,14 +68,14 @@ model: duration_predictor_dropout_rate: 0.5 # dropout rate in energy predictor 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_kernel_size: 5 # kernel size of conv layers 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_kernel_size: 3 # kernel size of conv layers 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 diff --git a/examples/opencpop/voc5/conf/default.yaml b/examples/opencpop/voc5/conf/default.yaml index 10449f860..18822f310 100644 --- a/examples/opencpop/voc5/conf/default.yaml +++ b/examples/opencpop/voc5/conf/default.yaml @@ -38,7 +38,7 @@ generator_params: use_additional_convs: True # Whether to use additional conv layer in residual blocks. bias: True # Whether to use bias parameter in conv. nonlinear_activation: "leakyrelu" # Nonlinear activation type. - nonlinear_activation_params: # Nonlinear activation paramters. + nonlinear_activation_params: # Nonlinear activation parameters. negative_slope: 0.1 use_weight_norm: True # Whether to apply weight normalization. @@ -76,7 +76,7 @@ discriminator_params: max_downsample_channels: 1024 # Maximum number of channels in downsampling conv layers. bias: True # Whether to use bias parameter in conv layer." nonlinear_activation: "leakyrelu" # Nonlinear activation. - nonlinear_activation_params: # Nonlinear activation paramters. + nonlinear_activation_params: # Nonlinear activation parameters. negative_slope: 0.1 use_weight_norm: True # Whether to apply weight normalization. use_spectral_norm: False # Whether to apply spectral normalization. diff --git a/examples/opencpop/voc5/conf/finetune.yaml b/examples/opencpop/voc5/conf/finetune.yaml index 0022a67aa..331f99755 100644 --- a/examples/opencpop/voc5/conf/finetune.yaml +++ b/examples/opencpop/voc5/conf/finetune.yaml @@ -38,7 +38,7 @@ generator_params: use_additional_convs: True # Whether to use additional conv layer in residual blocks. bias: True # Whether to use bias parameter in conv. nonlinear_activation: "leakyrelu" # Nonlinear activation type. - nonlinear_activation_params: # Nonlinear activation paramters. + nonlinear_activation_params: # Nonlinear activation parameters. negative_slope: 0.1 use_weight_norm: True # Whether to apply weight normalization. @@ -76,7 +76,7 @@ discriminator_params: max_downsample_channels: 1024 # Maximum number of channels in downsampling conv layers. bias: True # Whether to use bias parameter in conv layer." nonlinear_activation: "leakyrelu" # Nonlinear activation. - nonlinear_activation_params: # Nonlinear activation paramters. + nonlinear_activation_params: # Nonlinear activation parameters. negative_slope: 0.1 use_weight_norm: True # Whether to apply weight normalization. use_spectral_norm: False # Whether to apply spectral normalization. diff --git a/examples/other/ngram_lm/s0/local/kenlm_score_test.py b/examples/other/ngram_lm/s0/local/kenlm_score_test.py index 30bc1e4b1..4f388cd00 100644 --- a/examples/other/ngram_lm/s0/local/kenlm_score_test.py +++ b/examples/other/ngram_lm/s0/local/kenlm_score_test.py @@ -97,7 +97,7 @@ def test_full_scores_words(): if w not in model: print('"{0}" is an OOV'.format(w)) oov.append(w) - # zh_giga.no_cna_cmn.prune01244.klm is chinese charactor LM + # zh_giga.no_cna_cmn.prune01244.klm is chinese character LM assert oov == ["盘点", "不怕", "网站", "❗", "️", "海淘", "向来", "便宜", "保真", "！"], 'error oov' diff --git a/examples/tal_cs/asr1/local/data.sh b/examples/tal_cs/asr1/local/data.sh index 7ea12809f..c03650aca 100644 --- a/examples/tal_cs/asr1/local/data.sh +++ b/examples/tal_cs/asr1/local/data.sh @@ -24,7 +24,7 @@ mkdir -p ${TARGET_DIR} #prepare data if [ ${stage} -le -1 ] && [ ${stop_stage} -ge -1 ]; then if [ ! -d "${MAIN_ROOT}/dataset/tal_cs/TALCS_corpus" ]; then - echo "${MAIN_ROOT}/dataset/tal_cs/TALCS_corpus does not exist. Please donwload tal_cs data and unpack it from https://ai.100tal.com/dataset first." + echo "${MAIN_ROOT}/dataset/tal_cs/TALCS_corpus does not exist. Please download tal_cs data and unpack it from https://ai.100tal.com/dataset first." echo "data md5 reference: 4c879b3c9c05365fc9dee1fc68713afe" exit fi diff --git a/examples/tal_cs/asr1/local/train.sh b/examples/tal_cs/asr1/local/train.sh index bfa8dd97d..f70137b11 100755 --- a/examples/tal_cs/asr1/local/train.sh +++ b/examples/tal_cs/asr1/local/train.sh @@ -35,8 +35,8 @@ echo ${ips_config} mkdir -p exp -# default memeory allocator strategy may case gpu training hang -# for no OOM raised when memory exhaused +# default memory allocator strategy may case gpu training hang +# for no OOM raised when memory exhausted export FLAGS_allocator_strategy=naive_best_fit if [ ${ngpu} == 0 ]; then diff --git a/examples/ted_en_zh/st1/cmd.sh b/examples/ted_en_zh/st1/cmd.sh index 7b70ef5e0..c87b0f233 100644 --- a/examples/ted_en_zh/st1/cmd.sh +++ b/examples/ted_en_zh/st1/cmd.sh @@ -54,8 +54,8 @@ elif [ "${cmd_backend}" = sge ]; then # "sbatch" (Slurm) elif [ "${cmd_backend}" = slurm ]; then # The default setting is written in conf/slurm.conf. - # You must change "-p cpu" and "-p gpu" for the "partion" for your environment. - # To know the "partion" names, type "sinfo". + # You must change "-p cpu" and "-p gpu" for the "partition" for your environment. + # To know the "partition" names, type "sinfo". # You can use "--gpu * " by default for slurm and it is interpreted as "--gres gpu:*" # The devices are allocated exclusively using "${CUDA_VISIBLE_DEVICES}". diff --git a/examples/timit/asr1/local/train.sh b/examples/timit/asr1/local/train.sh index 1088c7ffa..2c961a571 100755 --- a/examples/timit/asr1/local/train.sh +++ b/examples/timit/asr1/local/train.sh @@ -19,8 +19,8 @@ if [ ${seed} != 0 ]; then export FLAGS_cudnn_deterministic=True fi -# default memeory allocator strategy may case gpu training hang -# for no OOM raised when memory exhaused +# default memory allocator strategy may case gpu training hang +# for no OOM raised when memory exhausted export FLAGS_allocator_strategy=naive_best_fit if [ ${ngpu} == 0 ]; then diff --git a/examples/tiny/asr0/local/train.sh b/examples/tiny/asr0/local/train.sh index e233a0c0a..aa89ed2bd 100755 --- a/examples/tiny/asr0/local/train.sh +++ b/examples/tiny/asr0/local/train.sh @@ -32,8 +32,8 @@ fi mkdir -p exp -# default memeory allocator strategy may case gpu training hang -# for no OOM raised when memory exhaused +# default memory allocator strategy may case gpu training hang +# for no OOM raised when memory exhausted export FLAGS_allocator_strategy=naive_best_fit if [ ${ngpu} == 0 ]; then diff --git a/examples/tiny/asr1/local/train.sh b/examples/tiny/asr1/local/train.sh index fbfb41f6f..dcc1ad5de 100755 --- a/examples/tiny/asr1/local/train.sh +++ b/examples/tiny/asr1/local/train.sh @@ -34,8 +34,8 @@ fi mkdir -p exp -# default memeory allocator strategy may case gpu training hang -# for no OOM raised when memory exhaused +# default memory allocator strategy may case gpu training hang +# for no OOM raised when memory exhausted export FLAGS_allocator_strategy=naive_best_fit if [ ${ngpu} == 0 ]; then diff --git a/examples/vctk/ernie_sat/README.md b/examples/vctk/ernie_sat/README.md index 3350a7451..3fe99172b 100644 --- a/examples/vctk/ernie_sat/README.md +++ b/examples/vctk/ernie_sat/README.md @@ -85,9 +85,12 @@ hifigan_vctk_ckpt_0.2.0 ``` `./local/synthesize.sh` calls `${BIN_DIR}/../synthesize.py`, which can synthesize waveform from `metadata.jsonl`. ```bash -CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh ${conf_path} ${train_output_path} ${ckpt_name} +CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name} ``` +`--stage` controls the vocoder model during synthesis, which can be `0` , use`hifigan` model as vocoder. + ## Speech Synthesis and Speech Editing + ### Prepare **prepare aligner** ```bash diff --git a/examples/vctk/ernie_sat/run.sh b/examples/vctk/ernie_sat/run.sh index cb80d1ad8..c9bdfde79 100755 --- a/examples/vctk/ernie_sat/run.sh +++ b/examples/vctk/ernie_sat/run.sh @@ -27,10 +27,11 @@ if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then fi if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then - # synthesize, vocoder is pwgan - CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 + # synthesize, vocoder is hifigan by default + CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 fi if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then - CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 + # synthesize, task_name is speech synthesize by default stage 0, stage 1 will use speech edit as taskname + CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 fi diff --git a/examples/vctk/tts3/README.md b/examples/vctk/tts3/README.md index aadbff6c3..a9d568ebf 100644 --- a/examples/vctk/tts3/README.md +++ b/examples/vctk/tts3/README.md @@ -108,8 +108,10 @@ pwg_vctk_ckpt_0.1.1 ``` `./local/synthesize.sh` calls `${BIN_DIR}/../synthesize.py`, which can synthesize waveform from `metadata.jsonl`. ```bash -CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh ${conf_path} ${train_output_path} ${ckpt_name} +CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name} ``` +`--stage` controls the vocoder model during synthesis, which can be `0` or `1`, use `pwgan` or `hifigan` model as vocoder. + ```text usage: synthesize.py [-h] [--am {speedyspeech_csmsc,fastspeech2_csmsc,fastspeech2_ljspeech,fastspeech2_aishell3,fastspeech2_vctk,tacotron2_csmsc,tacotron2_ljspeech,tacotron2_aishell3}] @@ -156,8 +158,10 @@ optional arguments: ``` `./local/synthesize_e2e.sh` calls `${BIN_DIR}/../synthesize_e2e.py`, which can synthesize waveform from text file. ```bash -CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh ${conf_path} ${train_output_path} ${ckpt_name} +CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name} ``` +`--stage` controls the vocoder model during synthesis, which can be `0` or `1`, use `pwgan` or `hifigan` model as vocoder. + ```text usage: synthesize_e2e.py [-h] [--am {speedyspeech_csmsc,speedyspeech_aishell3,fastspeech2_csmsc,fastspeech2_ljspeech,fastspeech2_aishell3,fastspeech2_vctk,tacotron2_csmsc,tacotron2_ljspeech}] diff --git a/examples/vctk/tts3/conf/default.yaml b/examples/vctk/tts3/conf/default.yaml index a75658d3d..d0d520e82 100644 --- a/examples/vctk/tts3/conf/default.yaml +++ b/examples/vctk/tts3/conf/default.yaml @@ -42,7 +42,7 @@ model: 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_layers: 5 # number of layers of postnet 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 @@ -60,14 +60,14 @@ model: 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_kernel_size: 5 # kernel size of conv layers 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_kernel_size: 3 # kernel size of conv layers 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 diff --git a/examples/vctk/tts3/run.sh b/examples/vctk/tts3/run.sh index 76307bd5f..8ce3b707d 100755 --- a/examples/vctk/tts3/run.sh +++ b/examples/vctk/tts3/run.sh @@ -27,13 +27,13 @@ if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then fi if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then - # synthesize, vocoder is pwgan by default - CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 + # synthesize, vocoder is pwgan by default stage 0, stage 1 will use hifigan as vocoder + CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 fi if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then - # synthesize_e2e, vocoder is pwgan by default - CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 + # synthesize_e2e, vocoder is pwgan by default 0, stage 1 will use hifigan as vocoder + CUDA_VISIBLE_DEVICES=${gpus} ./local/synthesize_e2e.sh --stage 0 ${conf_path} ${train_output_path} ${ckpt_name} || exit -1 fi if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then diff --git a/examples/vctk/voc5/conf/default.yaml b/examples/vctk/voc5/conf/default.yaml index 6361e01b2..ecf0c1775 100644 --- a/examples/vctk/voc5/conf/default.yaml +++ b/examples/vctk/voc5/conf/default.yaml @@ -39,7 +39,7 @@ generator_params: use_additional_convs: True # Whether to use additional conv layer in residual blocks. bias: True # Whether to use bias parameter in conv. nonlinear_activation: "leakyrelu" # Nonlinear activation type. - nonlinear_activation_params: # Nonlinear activation paramters. + nonlinear_activation_params: # Nonlinear activation parameters. negative_slope: 0.1 use_weight_norm: True # Whether to apply weight normalization. @@ -77,7 +77,7 @@ discriminator_params: max_downsample_channels: 1024 # Maximum number of channels in downsampling conv layers. bias: True # Whether to use bias parameter in conv layer." nonlinear_activation: "leakyrelu" # Nonlinear activation. - nonlinear_activation_params: # Nonlinear activation paramters. + nonlinear_activation_params: # Nonlinear activation parameters. negative_slope: 0.1 use_weight_norm: True # Whether to apply weight normalization. use_spectral_norm: False # Whether to apply spectral normalization. diff --git a/examples/voxceleb/sv0/local/data_prepare.py b/examples/voxceleb/sv0/local/data_prepare.py index e5a5dff7b..e7fc8a120 100644 --- a/examples/voxceleb/sv0/local/data_prepare.py +++ b/examples/voxceleb/sv0/local/data_prepare.py @@ -32,8 +32,8 @@ def main(args, config): seed_everything(config.seed) # stage 1: generate the voxceleb csv file - # Note: this may occurs c++ execption, but the program will execute fine - # so we ignore the execption + # Note: this may occurs c++ exception, but the program will execute fine + # so we ignore the exception # we explicitly pass the vox2 base path to data prepare and generate the audio info logger.info("start to generate the voxceleb dataset info") train_dataset = VoxCeleb( diff --git a/examples/wenetspeech/asr1/local/train.sh b/examples/wenetspeech/asr1/local/train.sh index 6813d270c..fe5773e39 100755 --- a/examples/wenetspeech/asr1/local/train.sh +++ b/examples/wenetspeech/asr1/local/train.sh @@ -35,8 +35,8 @@ echo ${ips_config} mkdir -p exp -# default memeory allocator strategy may case gpu training hang -# for no OOM raised when memory exhaused +# default memory allocator strategy may case gpu training hang +# for no OOM raised when memory exhausted export FLAGS_allocator_strategy=naive_best_fit if [ ${ngpu} == 0 ]; then diff --git a/examples/zh_en_tts/tts3/conf/default.yaml b/examples/zh_en_tts/tts3/conf/default.yaml index efa8b3ea2..be509432d 100644 --- a/examples/zh_en_tts/tts3/conf/default.yaml +++ b/examples/zh_en_tts/tts3/conf/default.yaml @@ -42,7 +42,7 @@ model: 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_layers: 5 # number of layers of postnet 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 @@ -60,14 +60,14 @@ model: 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_kernel_size: 5 # kernel size of conv layers 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_kernel_size: 3 # kernel size of conv layers 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 diff --git a/paddlespeech/audio/utils/tensor_utils.py b/paddlespeech/audio/utils/tensor_utils.py index b246a6459..b67b2dd81 100644 --- a/paddlespeech/audio/utils/tensor_utils.py +++ b/paddlespeech/audio/utils/tensor_utils.py @@ -79,7 +79,7 @@ def pad_sequence(sequences: List[paddle.Tensor], # assuming trailing dimensions and type of all the Tensors # in sequences are same and fetching those from sequences[0] max_size = paddle.shape(sequences[0]) - # (TODO Hui Zhang): slice not supprot `end==start` + # (TODO Hui Zhang): slice not support `end==start` # trailing_dims = max_size[1:] trailing_dims = tuple( max_size[1:].numpy().tolist()) if sequences[0].ndim >= 2 else () @@ -93,7 +93,7 @@ def pad_sequence(sequences: List[paddle.Tensor], length = tensor.shape[0] # use index notation to prevent duplicate references to the tensor if batch_first: - # TODO (Hui Zhang): set_value op not supprot `end==start` + # TODO (Hui Zhang): set_value op not support `end==start` # TODO (Hui Zhang): set_value op not support int16 # TODO (Hui Zhang): set_varbase 2 rank not support [0,0,...] # out_tensor[i, :length, ...] = tensor @@ -102,7 +102,7 @@ def pad_sequence(sequences: List[paddle.Tensor], else: out_tensor[i, length] = tensor else: - # TODO (Hui Zhang): set_value op not supprot `end==start` + # TODO (Hui Zhang): set_value op not support `end==start` # out_tensor[:length, i, ...] = tensor if length != 0: out_tensor[:length, i] = tensor diff --git a/paddlespeech/cli/asr/infer.py b/paddlespeech/cli/asr/infer.py index 231a00f4d..548beb7ba 100644 --- a/paddlespeech/cli/asr/infer.py +++ b/paddlespeech/cli/asr/infer.py @@ -79,7 +79,7 @@ class ASRExecutor(BaseExecutor): '--config', type=str, default=None, - help='Config of asr task. Use deault config when it is None.') + help='Config of asr task. Use default config when it is None.') self.parser.add_argument( '--decode_method', type=str, diff --git a/paddlespeech/cli/cls/infer.py b/paddlespeech/cli/cls/infer.py index fa49f7bdb..54780fdd2 100644 --- a/paddlespeech/cli/cls/infer.py +++ b/paddlespeech/cli/cls/infer.py @@ -51,7 +51,7 @@ class CLSExecutor(BaseExecutor): '--config', type=str, default=None, - help='Config of cls task. Use deault config when it is None.') + help='Config of cls task. Use default config when it is None.') self.parser.add_argument( '--ckpt_path', type=str, diff --git a/paddlespeech/cli/kws/infer.py b/paddlespeech/cli/kws/infer.py index 6dee4cc84..467b463f7 100644 --- a/paddlespeech/cli/kws/infer.py +++ b/paddlespeech/cli/kws/infer.py @@ -58,7 +58,7 @@ class KWSExecutor(BaseExecutor): '--config', type=str, default=None, - help='Config of kws task. Use deault config when it is None.') + help='Config of kws task. Use default config when it is None.') self.parser.add_argument( '--ckpt_path', type=str, diff --git a/paddlespeech/cli/ssl/infer.py b/paddlespeech/cli/ssl/infer.py index 33cdf7637..37ad0bd9d 100644 --- a/paddlespeech/cli/ssl/infer.py +++ b/paddlespeech/cli/ssl/infer.py @@ -76,7 +76,7 @@ class SSLExecutor(BaseExecutor): '--config', type=str, default=None, - help='Config of asr task. Use deault config when it is None.') + help='Config of asr task. Use default config when it is None.') self.parser.add_argument( '--decode_method', type=str, diff --git a/paddlespeech/cli/st/infer.py b/paddlespeech/cli/st/infer.py index 7e9957129..5dab6f53b 100644 --- a/paddlespeech/cli/st/infer.py +++ b/paddlespeech/cli/st/infer.py @@ -82,7 +82,7 @@ class STExecutor(BaseExecutor): "--config", type=str, default=None, - help="Config of st task. Use deault config when it is None.") + help="Config of st task. Use default config when it is None.") self.parser.add_argument( "--ckpt_path", type=str, diff --git a/paddlespeech/cli/text/infer.py b/paddlespeech/cli/text/infer.py index bd76a13d0..59286ea31 100644 --- a/paddlespeech/cli/text/infer.py +++ b/paddlespeech/cli/text/infer.py @@ -63,7 +63,7 @@ class TextExecutor(BaseExecutor): '--config', type=str, default=None, - help='Config of cls task. Use deault config when it is None.') + help='Config of cls task. Use default config when it is None.') self.parser.add_argument( '--ckpt_path', type=str, diff --git a/paddlespeech/cli/tts/infer.py b/paddlespeech/cli/tts/infer.py index beba7f602..1f128dfe9 100644 --- a/paddlespeech/cli/tts/infer.py +++ b/paddlespeech/cli/tts/infer.py @@ -90,7 +90,7 @@ class TTSExecutor(BaseExecutor): '--am_config', type=str, default=None, - help='Config of acoustic model. Use deault config when it is None.') + help='Config of acoustic model. Use default config when it is None.') self.parser.add_argument( '--am_ckpt', type=str, @@ -148,7 +148,7 @@ class TTSExecutor(BaseExecutor): '--voc_config', type=str, default=None, - help='Config of voc. Use deault config when it is None.') + help='Config of voc. Use default config when it is None.') self.parser.add_argument( '--voc_ckpt', type=str, diff --git a/paddlespeech/cli/vector/infer.py b/paddlespeech/cli/vector/infer.py index c4ae11c75..29c32e516 100644 --- a/paddlespeech/cli/vector/infer.py +++ b/paddlespeech/cli/vector/infer.py @@ -82,7 +82,7 @@ class VectorExecutor(BaseExecutor): '--config', type=str, default=None, - help='Config of asr task. Use deault config when it is None.') + help='Config of asr task. Use default config when it is None.') self.parser.add_argument( "--device", type=str, diff --git a/paddlespeech/cli/whisper/infer.py b/paddlespeech/cli/whisper/infer.py index 17e8c0b8c..5649b757f 100644 --- a/paddlespeech/cli/whisper/infer.py +++ b/paddlespeech/cli/whisper/infer.py @@ -96,7 +96,7 @@ class WhisperExecutor(BaseExecutor): '--config', type=str, default=None, - help='Config of asr task. Use deault config when it is None.') + help='Config of asr task. Use default config when it is None.') self.parser.add_argument( '--decode_method', type=str, diff --git a/paddlespeech/dataset/aidatatang_200zh/aidatatang_200zh.py b/paddlespeech/dataset/aidatatang_200zh/aidatatang_200zh.py index 5d914a438..7250a50b9 100644 --- a/paddlespeech/dataset/aidatatang_200zh/aidatatang_200zh.py +++ b/paddlespeech/dataset/aidatatang_200zh/aidatatang_200zh.py @@ -62,7 +62,7 @@ def create_manifest(data_dir, manifest_path_prefix): if line == '': continue audio_id, text = line.split(' ', 1) - # remove withespace, charactor text + # remove withespace, character text text = ''.join(text.split()) transcript_dict[audio_id] = text diff --git a/paddlespeech/dataset/aishell/aishell.py b/paddlespeech/dataset/aishell/aishell.py index 7ea4d6766..f227cfbd5 100644 --- a/paddlespeech/dataset/aishell/aishell.py +++ b/paddlespeech/dataset/aishell/aishell.py @@ -65,7 +65,7 @@ def create_manifest(data_dir, manifest_path_prefix): if line == '': continue audio_id, text = line.split(' ', 1) - # remove withespace, charactor text + # remove withespace, character text text = ''.join(text.split()) transcript_dict[audio_id] = text @@ -159,7 +159,7 @@ def check_dataset(data_dir): if line == '': continue audio_id, text = line.split(' ', 1) - # remove withespace, charactor text + # remove withespace, character text text = ''.join(text.split()) transcript_dict[audio_id] = text diff --git a/paddlespeech/resource/pretrained_models.py b/paddlespeech/resource/pretrained_models.py index 441512cdc..64ef44481 100644 --- a/paddlespeech/resource/pretrained_models.py +++ b/paddlespeech/resource/pretrained_models.py @@ -2106,7 +2106,7 @@ g2pw_onnx_models = { }, '1.1': { 'url': - 'https://paddlespeech.cdn.bcebos.com/Parakeet/released_models/g2p/G2PWModel_1.1.zip', + 'https://paddlespeech.cdn.bcebos.com/Parakeet/released_models/g2p/new/G2PWModel_1.1.zip', 'md5': 'f8b60501770bff92ed6ce90860a610e6', }, diff --git a/paddlespeech/s2t/exps/hubert/model.py b/paddlespeech/s2t/exps/hubert/model.py index bc05921dd..c2bd63583 100644 --- a/paddlespeech/s2t/exps/hubert/model.py +++ b/paddlespeech/s2t/exps/hubert/model.py @@ -362,7 +362,7 @@ class HubertASRTrainer(Trainer): scratch = None if self.args.resume: # just restore ckpt - # lr will resotre from optimizer ckpt + # lr will restore from optimizer ckpt resume_json_path = os.path.join(self.checkpoint_dir, self.args.resume + '.json') with open(resume_json_path, 'r', encoding='utf8') as f: @@ -370,20 +370,20 @@ class HubertASRTrainer(Trainer): self.iteration = 0 self.epoch = resume_json["epoch"] - # resotre model from *.pdparams + # restore model from *.pdparams params_path = os.path.join(self.checkpoint_dir, "{}".format(self.epoch)) + '.pdparams' model_dict = paddle.load(params_path) self.model.set_state_dict(model_dict) - # resotre optimizer from *.pdopt + # restore optimizer from *.pdopt optimizer_path = os.path.join(self.checkpoint_dir, "{}".format(self.epoch)) + '.pdopt' optimizer_dict = paddle.load(optimizer_path) self.model_optimizer.set_state_dict(optimizer_dict['model']) self.hubert_optimizer.set_state_dict(optimizer_dict['hubert']) - # resotre lr_scheduler from *.pdlrs + # restore lr_scheduler from *.pdlrs scheduler_path = os.path.join(self.checkpoint_dir, "{}".format(self.epoch)) + '.pdlrs' if os.path.isfile(os.path.join(scheduler_path)): diff --git a/paddlespeech/s2t/exps/wav2vec2/model.py b/paddlespeech/s2t/exps/wav2vec2/model.py index 6c90f99e1..7ba86c774 100644 --- a/paddlespeech/s2t/exps/wav2vec2/model.py +++ b/paddlespeech/s2t/exps/wav2vec2/model.py @@ -361,7 +361,7 @@ class Wav2Vec2ASRTrainer(Trainer): scratch = None if self.args.resume: # just restore ckpt - # lr will resotre from optimizer ckpt + # lr will restore from optimizer ckpt resume_json_path = os.path.join(self.checkpoint_dir, self.args.resume + '.json') with open(resume_json_path, 'r', encoding='utf8') as f: @@ -369,20 +369,20 @@ class Wav2Vec2ASRTrainer(Trainer): self.iteration = 0 self.epoch = resume_json["epoch"] - # resotre model from *.pdparams + # restore model from *.pdparams params_path = os.path.join(self.checkpoint_dir, "{}".format(self.epoch)) + '.pdparams' model_dict = paddle.load(params_path) self.model.set_state_dict(model_dict) - # resotre optimizer from *.pdopt + # restore optimizer from *.pdopt optimizer_path = os.path.join(self.checkpoint_dir, "{}".format(self.epoch)) + '.pdopt' optimizer_dict = paddle.load(optimizer_path) self.model_optimizer.set_state_dict(optimizer_dict['model']) self.wav2vec2_optimizer.set_state_dict(optimizer_dict['wav2vec2']) - # resotre lr_scheduler from *.pdlrs + # restore lr_scheduler from *.pdlrs scheduler_path = os.path.join(self.checkpoint_dir, "{}".format(self.epoch)) + '.pdlrs' if os.path.isfile(os.path.join(scheduler_path)): diff --git a/paddlespeech/s2t/exps/wavlm/model.py b/paddlespeech/s2t/exps/wavlm/model.py index 606867eae..5dfbf3b2e 100644 --- a/paddlespeech/s2t/exps/wavlm/model.py +++ b/paddlespeech/s2t/exps/wavlm/model.py @@ -361,7 +361,7 @@ class WavLMASRTrainer(Trainer): scratch = None if self.args.resume: # just restore ckpt - # lr will resotre from optimizer ckpt + # lr will restore from optimizer ckpt resume_json_path = os.path.join(self.checkpoint_dir, self.args.resume + '.json') with open(resume_json_path, 'r', encoding='utf8') as f: @@ -369,20 +369,20 @@ class WavLMASRTrainer(Trainer): self.iteration = 0 self.epoch = resume_json["epoch"] - # resotre model from *.pdparams + # restore model from *.pdparams params_path = os.path.join(self.checkpoint_dir, "{}".format(self.epoch)) + '.pdparams' model_dict = paddle.load(params_path) self.model.set_state_dict(model_dict) - # resotre optimizer from *.pdopt + # restore optimizer from *.pdopt optimizer_path = os.path.join(self.checkpoint_dir, "{}".format(self.epoch)) + '.pdopt' optimizer_dict = paddle.load(optimizer_path) self.model_optimizer.set_state_dict(optimizer_dict['model']) self.wavlm_optimizer.set_state_dict(optimizer_dict['wavlm']) - # resotre lr_scheduler from *.pdlrs + # restore lr_scheduler from *.pdlrs scheduler_path = os.path.join(self.checkpoint_dir, "{}".format(self.epoch)) + '.pdlrs' if os.path.isfile(os.path.join(scheduler_path)): diff --git a/paddlespeech/s2t/modules/align.py b/paddlespeech/s2t/modules/align.py index 46d8796ab..a206a350c 100644 --- a/paddlespeech/s2t/modules/align.py +++ b/paddlespeech/s2t/modules/align.py @@ -17,7 +17,7 @@ import paddle from paddle import nn """ To align the initializer between paddle and torch, - the API below are set defalut initializer with priority higger than global initializer. + the API below are set default initializer with priority higger than global initializer. """ global_init_type = None diff --git a/paddlespeech/s2t/training/cli.py b/paddlespeech/s2t/training/cli.py index ded2aff9f..fc0caf10a 100644 --- a/paddlespeech/s2t/training/cli.py +++ b/paddlespeech/s2t/training/cli.py @@ -47,7 +47,7 @@ def default_argument_parser(parser=None): other experiments with t2s. It requires a minimal set of command line arguments to start a training script. - The ``--config`` and ``--opts`` are used for overwrite the deault + The ``--config`` and ``--opts`` are used for overwrite the default configuration. The ``--data`` and ``--output`` specifies the data path and output path. diff --git a/paddlespeech/s2t/training/trainer.py b/paddlespeech/s2t/training/trainer.py index a8f36f91b..3facddc0e 100644 --- a/paddlespeech/s2t/training/trainer.py +++ b/paddlespeech/s2t/training/trainer.py @@ -215,7 +215,7 @@ class Trainer(): checkpoint_path=self.args.checkpoint_path) if infos: # just restore ckpt - # lr will resotre from optimizer ckpt + # lr will restore from optimizer ckpt self.iteration = infos["step"] self.epoch = infos["epoch"] diff --git a/paddlespeech/s2t/utils/error_rate.py b/paddlespeech/s2t/utils/error_rate.py index 548376aa2..9e3357b91 100644 --- a/paddlespeech/s2t/utils/error_rate.py +++ b/paddlespeech/s2t/utils/error_rate.py @@ -171,7 +171,7 @@ def wer(reference, hypothesis, ignore_case=False, delimiter=' '): def cer(reference, hypothesis, ignore_case=False, remove_space=False): - """Calculate charactor error rate (CER). CER compares reference text and + """Calculate character error rate (CER). CER compares reference text and hypothesis text in char-level. CER is defined as: .. math:: diff --git a/paddlespeech/s2t/utils/tensor_utils.py b/paddlespeech/s2t/utils/tensor_utils.py index 0d91b9cfb..15f4abdda 100644 --- a/paddlespeech/s2t/utils/tensor_utils.py +++ b/paddlespeech/s2t/utils/tensor_utils.py @@ -80,7 +80,7 @@ def pad_sequence(sequences: List[paddle.Tensor], # assuming trailing dimensions and type of all the Tensors # in sequences are same and fetching those from sequences[0] max_size = paddle.shape(sequences[0]) - # (TODO Hui Zhang): slice not supprot `end==start` + # (TODO Hui Zhang): slice not support `end==start` # trailing_dims = max_size[1:] trailing_dims = tuple( max_size[1:].numpy().tolist()) if sequences[0].ndim >= 2 else () @@ -98,7 +98,7 @@ def pad_sequence(sequences: List[paddle.Tensor], f"length {length}, out_tensor {out_tensor.shape}, tensor {tensor.shape}" ) if batch_first: - # TODO (Hui Zhang): set_value op not supprot `end==start` + # TODO (Hui Zhang): set_value op not support `end==start` # TODO (Hui Zhang): set_value op not support int16 # TODO (Hui Zhang): set_varbase 2 rank not support [0,0,...] # out_tensor[i, :length, ...] = tensor @@ -107,7 +107,7 @@ def pad_sequence(sequences: List[paddle.Tensor], else: out_tensor[i, length] = tensor else: - # TODO (Hui Zhang): set_value op not supprot `end==start` + # TODO (Hui Zhang): set_value op not support `end==start` # out_tensor[:length, i, ...] = tensor if length != 0: out_tensor[:length, i] = tensor diff --git a/paddlespeech/server/utils/audio_handler.py b/paddlespeech/server/utils/audio_handler.py index 4df651337..08f15fe70 100644 --- a/paddlespeech/server/utils/audio_handler.py +++ b/paddlespeech/server/utils/audio_handler.py @@ -79,7 +79,7 @@ class ASRWsAudioHandler: punc_server_ip=None, punc_server_port=None): """PaddleSpeech Online ASR Server Client audio handler - Online asr server use the websocket protocal + Online asr server use the websocket protocol Args: url (str, optional): the server ip. Defaults to None. port (int, optional): the server port. Defaults to None. @@ -144,10 +144,10 @@ class ASRWsAudioHandler: logger.error("No asr server, please input valid ip and port") return "" - # 1. send websocket handshake protocal + # 1. send websocket handshake protocol start_time = time.time() async with websockets.connect(self.url) as ws: - # 2. server has already received handshake protocal + # 2. server has already received handshake protocol # client start to send the command audio_info = json.dumps( { @@ -255,7 +255,7 @@ class ASRHttpHandler: class TTSWsHandler: def __init__(self, server="127.0.0.1", port=8092, play: bool=False): """PaddleSpeech Online TTS Server Client audio handler - Online tts server use the websocket protocal + Online tts server use the websocket protocol Args: server (str, optional): the server ip. Defaults to "127.0.0.1". port (int, optional): the server port. Defaults to 8092. @@ -405,7 +405,7 @@ class TTSWsHandler: class TTSHttpHandler: def __init__(self, server="127.0.0.1", port=8092, play: bool=False): """PaddleSpeech Online TTS Server Client audio handler - Online tts server use the websocket protocal + Online tts server use the websocket protocol Args: server (str, optional): the server ip. Defaults to "127.0.0.1". port (int, optional): the server port. Defaults to 8092. diff --git a/paddlespeech/server/ws/asr_api.py b/paddlespeech/server/ws/asr_api.py index b3ad0b7c5..3f90ac3b4 100644 --- a/paddlespeech/server/ws/asr_api.py +++ b/paddlespeech/server/ws/asr_api.py @@ -31,7 +31,7 @@ async def websocket_endpoint(websocket: WebSocket): websocket (WebSocket): the websocket instance """ - #1. the interface wait to accept the websocket protocal header + #1. the interface wait to accept the websocket protocol header # and only we receive the header, it establish the connection with specific thread await websocket.accept() @@ -45,7 +45,7 @@ async def websocket_endpoint(websocket: WebSocket): connection_handler = None try: - #4. we do a loop to process the audio package by package according the protocal + #4. we do a loop to process the audio package by package according the protocol # and only if the client send finished signal, we will break the loop while True: # careful here, changed the source code from starlette.websockets diff --git a/paddlespeech/server/ws/tts_api.py b/paddlespeech/server/ws/tts_api.py index 275711f58..11194958c 100644 --- a/paddlespeech/server/ws/tts_api.py +++ b/paddlespeech/server/ws/tts_api.py @@ -32,7 +32,7 @@ async def websocket_endpoint(websocket: WebSocket): websocket (WebSocket): the websocket instance """ - #1. the interface wait to accept the websocket protocal header + #1. the interface wait to accept the websocket protocol header # and only we receive the header, it establish the connection with specific thread await websocket.accept() diff --git a/paddlespeech/t2s/frontend/zh_frontend.py b/paddlespeech/t2s/frontend/zh_frontend.py index 95c75a7f0..3c87c6827 100644 --- a/paddlespeech/t2s/frontend/zh_frontend.py +++ b/paddlespeech/t2s/frontend/zh_frontend.py @@ -523,7 +523,7 @@ class Frontend(): initials = [] finals = [] - # to charactor list + # to character list words = self._split_word_to_char(words[0]) for pinyin, char in zip(pinyin_spec, words): diff --git a/paddlespeech/t2s/models/vits/residual_coupling.py b/paddlespeech/t2s/models/vits/residual_coupling.py index afa6d1fa7..09916484d 100644 --- a/paddlespeech/t2s/models/vits/residual_coupling.py +++ b/paddlespeech/t2s/models/vits/residual_coupling.py @@ -76,7 +76,7 @@ class ResidualAffineCouplingBlock(nn.Layer): use_weight_norm (bool): Whether to use weight normalization in WaveNet. bias (bool): - Whether to use bias paramters in WaveNet. + Whether to use bias parameters in WaveNet. use_only_mean (bool): Whether to estimate only mean. @@ -169,7 +169,7 @@ class ResidualAffineCouplingLayer(nn.Layer): use_weight_norm (bool): Whether to use weight normalization in WaveNet. bias (bool): - Whether to use bias paramters in WaveNet. + Whether to use bias parameters in WaveNet. use_only_mean (bool): Whether to estimate only mean. diff --git a/paddlespeech/t2s/modules/diffusion.py b/paddlespeech/t2s/modules/diffusion.py index adbd9ce7f..f00ddc595 100644 --- a/paddlespeech/t2s/modules/diffusion.py +++ b/paddlespeech/t2s/modules/diffusion.py @@ -40,7 +40,7 @@ class GaussianDiffusion(nn.Layer): num_max_timesteps (int, optional): The max timestep transition from real to noise, by default None. stretch (bool, optional): - Whether to stretch before diffusion, by defalut True. + Whether to stretch before diffusion, by default True. min_values: (paddle.Tensor): The minimum value of the feature to stretch. max_values: (paddle.Tensor): diff --git a/paddlespeech/t2s/training/cli.py b/paddlespeech/t2s/training/cli.py index 83dae1177..d503744d5 100644 --- a/paddlespeech/t2s/training/cli.py +++ b/paddlespeech/t2s/training/cli.py @@ -21,7 +21,7 @@ def default_argument_parser(): other experiments with t2s. It requires a minimal set of command line arguments to start a training script. - The ``--config`` and ``--opts`` are used for overwrite the deault + The ``--config`` and ``--opts`` are used for overwrite the default configuration. The ``--data`` and ``--output`` specifies the data path and output path. diff --git a/paddlespeech/t2s/utils/error_rate.py b/paddlespeech/t2s/utils/error_rate.py index 76a4f45be..1298680ed 100644 --- a/paddlespeech/t2s/utils/error_rate.py +++ b/paddlespeech/t2s/utils/error_rate.py @@ -159,7 +159,7 @@ def wer(reference, hypothesis, ignore_case=False, delimiter=' '): def cer(reference, hypothesis, ignore_case=False, remove_space=False): - """Calculate charactor error rate (CER). CER compares reference text and + """Calculate character error rate (CER). CER compares reference text and hypothesis text in char-level. CER is defined as: .. math:: CER = (Sc + Dc + Ic) / Nc diff --git a/paddlespeech/utils/initialize.py b/paddlespeech/utils/initialize.py index 8ebe6845e..efa6ee6d5 100644 --- a/paddlespeech/utils/initialize.py +++ b/paddlespeech/utils/initialize.py @@ -234,7 +234,7 @@ def kaiming_uniform_(tensor, Modified tensor inspace using kaiming_uniform method Args: tensor (paddle.Tensor): paddle Tensor - mode (str): ['fan_in', 'fan_out'], 'fin_in' defalut + mode (str): ['fan_in', 'fan_out'], 'fin_in' default nonlinearity (str): nonlinearity method name reverse (bool): reverse (bool: False): tensor data format order, False by default as [fout, fin, ...]. Return: @@ -256,7 +256,7 @@ def kaiming_normal_(tensor, Modified tensor inspace using kaiming_normal_ Args: tensor (paddle.Tensor): paddle Tensor - mode (str): ['fan_in', 'fan_out'], 'fin_in' defalut + mode (str): ['fan_in', 'fan_out'], 'fin_in' default nonlinearity (str): nonlinearity method name reverse (bool): reverse (bool: False): tensor data format order, False by default as [fout, fin, ...]. Return: diff --git a/runtime/engine/asr/decoder/ctc_prefix_beam_search_decoder.cc b/runtime/engine/asr/decoder/ctc_prefix_beam_search_decoder.cc index bf912af2e..1bda492c8 100644 --- a/runtime/engine/asr/decoder/ctc_prefix_beam_search_decoder.cc +++ b/runtime/engine/asr/decoder/ctc_prefix_beam_search_decoder.cc @@ -157,7 +157,7 @@ void CTCPrefixBeamSearch::AdvanceDecoding( next_score.v_b = prefix_score.ViterbiScore() + prob; next_score.times_b = prefix_score.Times(); - // Prefix not changed, copy the context from pefix + // Prefix not changed, copy the context from prefix if (context_graph_ && !next_score.has_context) { next_score.CopyContext(prefix_score); next_score.has_context = true; @@ -183,7 +183,7 @@ void CTCPrefixBeamSearch::AdvanceDecoding( } } - // Prefix not changed, copy the context from pefix + // Prefix not changed, copy the context from prefix if (context_graph_ && !next_score1.has_context) { next_score1.CopyContext(prefix_score); next_score1.has_context = true; diff --git a/runtime/engine/common/frontend/cmvn.cc b/runtime/engine/common/frontend/cmvn.cc index 0f1108208..bfb02a840 100644 --- a/runtime/engine/common/frontend/cmvn.cc +++ b/runtime/engine/common/frontend/cmvn.cc @@ -72,7 +72,7 @@ bool CMVN::Read(std::vector* feats) { return false; } - // appply cmvn + // apply cmvn kaldi::Timer timer; Compute(feats); VLOG(1) << "CMVN::Read cost: " << timer.Elapsed() << " sec."; diff --git a/runtime/engine/common/frontend/cmvn.h b/runtime/engine/common/frontend/cmvn.h index c515b6aeb..2d8917d95 100644 --- a/runtime/engine/common/frontend/cmvn.h +++ b/runtime/engine/common/frontend/cmvn.h @@ -29,7 +29,7 @@ class CMVN : public FrontendInterface { // the length of feats = feature_row * feature_dim, // the Matrix is squashed into Vector virtual bool Read(std::vector* feats); - // the dim_ is the feautre dim. + // the dim_ is the feature dim. virtual size_t Dim() const { return dim_; } virtual void SetFinished() { base_extractor_->SetFinished(); } virtual bool IsFinished() const { return base_extractor_->IsFinished(); } diff --git a/runtime/engine/common/frontend/db_norm.h b/runtime/engine/common/frontend/db_norm.h index 425971437..e9f8b6995 100644 --- a/runtime/engine/common/frontend/db_norm.h +++ b/runtime/engine/common/frontend/db_norm.h @@ -47,7 +47,7 @@ class DecibelNormalizer : public FrontendInterface { std::unique_ptr base_extractor); virtual void Accept(const kaldi::VectorBase& waves); virtual bool Read(kaldi::Vector* waves); - // noramlize audio, the dim is 1. + // normalize audio, the dim is 1. virtual size_t Dim() const { return dim_; } virtual void SetFinished() { base_extractor_->SetFinished(); } virtual bool IsFinished() const { return base_extractor_->IsFinished(); } diff --git a/runtime/engine/common/matrix/kaldi-matrix.cc b/runtime/engine/common/matrix/kaldi-matrix.cc index 6f65fb0a0..65e8e09a6 100644 --- a/runtime/engine/common/matrix/kaldi-matrix.cc +++ b/runtime/engine/common/matrix/kaldi-matrix.cc @@ -244,8 +244,8 @@ void MatrixBase::SymAddMat2(const Real alpha, /// function will produce NaN in the output. This is a bug in the /// ATLAS library. To overcome this, the AddMatMat function, which calls /// cblas_Xgemm(...) rather than cblas_Xsyrk(...), is used in this special - /// sitation. - /// Wei Shi: Note this bug is observerd for single precision matrix + /// situation. + /// Wei Shi: Note this bug is observed for single precision matrix /// on a 64-bit machine #ifdef HAVE_ATLAS if (transA == kTrans && num_rows_ >= 56) { @@ -683,7 +683,7 @@ empty. if (V_in == NULL) tmpV.Resize(1, this->num_cols_); // work-space if V_in empty. - /// Impementation notes: + /// Implementation notes: /// Lapack works in column-order, therefore the dimensions of *this are /// swapped as well as the U and V matrices. @@ -2378,7 +2378,7 @@ bool ReadHtk(std::istream &is, Matrix *M_ptr, HtkHeader *header_ptr) Matrix &M = *M_ptr; HtkHeader htk_hdr; - // TODO(arnab): this fails if the HTK file has CRC cheksum or is compressed. + // TODO(arnab): this fails if the HTK file has CRC checksum or is compressed. is.read((char*)&htk_hdr, sizeof(htk_hdr)); // we're being really POSIX here! if (is.fail()) { KALDI_WARN << "Could not read header from HTK feature file "; diff --git a/runtime/engine/common/matrix/kaldi-vector.cc b/runtime/engine/common/matrix/kaldi-vector.cc index 3ab9a7ffa..790ebe128 100644 --- a/runtime/engine/common/matrix/kaldi-vector.cc +++ b/runtime/engine/common/matrix/kaldi-vector.cc @@ -235,7 +235,7 @@ void VectorBase::CopyRowsFromMat(const MatrixBase &mat) { memcpy(inc_data, mat.Data(), cols * rows * sizeof(Real)); } else { for (MatrixIndexT i = 0; i < rows; i++) { - // copy the data to the propper position + // copy the data to the proper position memcpy(inc_data, mat.RowData(i), cols * sizeof(Real)); // set new copy position inc_data += cols; diff --git a/runtime/engine/common/utils/file_utils.cc b/runtime/engine/common/utils/file_utils.cc index 385f2b656..59bb64482 100644 --- a/runtime/engine/common/utils/file_utils.cc +++ b/runtime/engine/common/utils/file_utils.cc @@ -44,7 +44,7 @@ std::string ReadFile2String(const std::string& path) { } bool FileExists(const std::string& strFilename) { - // this funciton if from: + // this function if from: // https://github.com/kaldi-asr/kaldi/blob/master/src/fstext/deterministic-fst-test.cc struct stat stFileInfo; bool blnReturn; diff --git a/runtime/engine/kaldi/lat/kaldi-lattice.cc b/runtime/engine/kaldi/lat/kaldi-lattice.cc index 744cc5384..0bd291ee1 100644 --- a/runtime/engine/kaldi/lat/kaldi-lattice.cc +++ b/runtime/engine/kaldi/lat/kaldi-lattice.cc @@ -407,7 +407,7 @@ bool WriteLattice(std::ostream &os, bool binary, const Lattice &t) { if (os.fail()) KALDI_WARN << "Stream failure detected."; // Write another newline as a terminating character. The read routine will - // detect this [this is a Kaldi mechanism, not somethig in the original + // detect this [this is a Kaldi mechanism, not something in the original // OpenFst code]. os << '\n'; return os.good(); diff --git a/runtime/examples/README.md b/runtime/examples/README.md index de27bd94b..6d316d649 100644 --- a/runtime/examples/README.md +++ b/runtime/examples/README.md @@ -34,7 +34,7 @@ bash run.sh --stop_stage 4 ## Display Model with [Netron](https://github.com/lutzroeder/netron) -If you have a model, we can using this commnd to show model graph. +If you have a model, we can using this commend to show model graph. For example: ``` diff --git a/runtime/examples/audio_classification/README.md b/runtime/examples/audio_classification/README.md index 6d7a37423..7fb8d611a 100644 --- a/runtime/examples/audio_classification/README.md +++ b/runtime/examples/audio_classification/README.md @@ -74,7 +74,7 @@ includes/ #### set path push resource into android phone -1. change resource path in conf to gloabal path, such as: +1. change resource path in conf to global path, such as: [CONF] wav_normal=true @@ -92,9 +92,9 @@ push resource into android phone high_freq=14000 dither=0.0 2. adb push conf label_list scp test.wav /data/local/tmp/ -3. set reource path in android demo(android_demo/app/src/main/cpp/native-lib.cpp) to actual path, such as: +3. set resource path in android demo(android_demo/app/src/main/cpp/native-lib.cpp) to actual path, such as: std::string conf_path = "/data/local/tmp/conf"; std::string wav_path = "/data/local/tmp/test.wav"; -4. excecute android_demo in android studio +4. execute android_demo in android studio diff --git a/runtime/examples/custom_asr/README.md b/runtime/examples/custom_asr/README.md index 33cf4ff03..992e5aac5 100644 --- a/runtime/examples/custom_asr/README.md +++ b/runtime/examples/custom_asr/README.md @@ -13,7 +13,7 @@ eg: * after replace operation, G = fstreplace(G_with_slot, address_slot), we will get the customized graph. ![](https://ai-studio-static-online.cdn.bcebos.com/60a3095293044f10b73039ab10c7950d139a6717580a44a3ba878c6e74de402b) -These operations are in the scripts, please check out. we will lanuch more detail scripts. +These operations are in the scripts, please check out. we will launch more detail scripts. ## How to run diff --git a/runtime/examples/text_lm/local/mmseg.py b/runtime/examples/text_lm/local/mmseg.py index 74295cd3c..4d72afd39 100755 --- a/runtime/examples/text_lm/local/mmseg.py +++ b/runtime/examples/text_lm/local/mmseg.py @@ -156,8 +156,8 @@ class Analysis: return self.text[self.pos] #判断该字符是否是中文字符（不包括中文标点） - def isChineseChar(self, charater): - return 0x4e00 <= ord(charater) < 0x9fa6 + def isChineseChar(self, character): + return 0x4e00 <= ord(character) < 0x9fa6 #判断是否是ASCII码 def isASCIIChar(self, ch): @@ -253,7 +253,6 @@ class Analysis: # print(word3.length, word3.text) if word3.length == -1: chunk = Chunk(word1, word2) - # print("Ture") else: chunk = Chunk(word1, word2, word3) chunks.append(chunk) diff --git a/runtime/patch/openfst/src/include/fst/flags.h b/runtime/patch/openfst/src/include/fst/flags.h index b5ec8ff74..54dd30cc2 100644 --- a/runtime/patch/openfst/src/include/fst/flags.h +++ b/runtime/patch/openfst/src/include/fst/flags.h @@ -181,8 +181,8 @@ template class FlagRegisterer { public: FlagRegisterer(const string &name, const FlagDescription &desc) { - auto registr = FlagRegister::GetRegister(); - registr->SetDescription(name, desc); + auto r = FlagRegister::GetRegister(); + r->SetDescription(name, desc); } private: diff --git a/tests/test_tipc/conformer/scripts/aishell_tiny.py b/tests/test_tipc/conformer/scripts/aishell_tiny.py index c87463b50..27b713a55 100644 --- a/tests/test_tipc/conformer/scripts/aishell_tiny.py +++ b/tests/test_tipc/conformer/scripts/aishell_tiny.py @@ -62,7 +62,7 @@ def create_manifest(data_dir, manifest_path_prefix): if line == '': continue audio_id, text = line.split(' ', 1) - # remove withespace, charactor text + # remove withespace, character text text = ''.join(text.split()) transcript_dict[audio_id] = text diff --git a/tests/unit/cli/aishell_test_prepare.py b/tests/unit/cli/aishell_test_prepare.py index c364e4fd9..ef582426c 100644 --- a/tests/unit/cli/aishell_test_prepare.py +++ b/tests/unit/cli/aishell_test_prepare.py @@ -63,7 +63,7 @@ def create_manifest(data_dir, manifest_path_prefix): if line == '': continue audio_id, text = line.split(' ', 1) - # remove withespace, charactor text + # remove withespace, character text text = ''.join(text.split()) transcript_dict[audio_id] = text diff --git a/tests/unit/server/offline/test_server_client.sh b/tests/unit/server/offline/test_server_client.sh index 6418c82fd..26fb100a3 100644 --- a/tests/unit/server/offline/test_server_client.sh +++ b/tests/unit/server/offline/test_server_client.sh @@ -66,8 +66,8 @@ config_file=./conf/application.yaml server_ip=$(cat $config_file | grep "host" | awk -F " " '{print $2}') port=$(cat $config_file | grep "port" | awk '/port:/ {print $2}') -echo "Sevice ip: $server_ip" | tee ./log/test_result.log -echo "Sevice port: $port" | tee -a ./log/test_result.log +echo "Service ip: $server_ip" | tee ./log/test_result.log +echo "Service port: $port" | tee -a ./log/test_result.log # whether a process is listening on $port pid=`lsof -i :"$port"|grep -v "PID" | awk '{print $2}'` @@ -190,7 +190,7 @@ echo "************************************************************************** echo "All tests completed." | tee -a ./log/test_result.log -# sohw all the test results +# show all the test results echo "***************** Here are all the test results ********************" cat ./log/test_result.log diff --git a/tests/unit/server/online/tts/check_server/test.sh b/tests/unit/server/online/tts/check_server/test.sh index c62c54c76..998a07b3f 100644 --- a/tests/unit/server/online/tts/check_server/test.sh +++ b/tests/unit/server/online/tts/check_server/test.sh @@ -76,8 +76,8 @@ config_file=./conf/application.yaml server_ip=$(cat $config_file | grep "host" | awk -F " " '{print $2}') port=$(cat $config_file | grep "port" | awk '/port:/ {print $2}') -echo "Sevice ip: $server_ip" | tee $log/test_result.log -echo "Sevice port: $port" | tee -a $log/test_result.log +echo "Service ip: $server_ip" | tee $log/test_result.log +echo "Service port: $port" | tee -a $log/test_result.log # whether a process is listening on $port pid=`lsof -i :"$port"|grep -v "PID" | awk '{print $2}'` @@ -307,7 +307,7 @@ echo "************************************************************************** echo "All tests completed." | tee -a $log/test_result.log -# sohw all the test results +# show all the test results echo "***************** Here are all the test results ********************" cat $log/test_result.log diff --git a/tests/unit/tts/test_snapshot.py b/tests/unit/tts/test_snapshot.py index fb18c7d78..750e6b68d 100644 --- a/tests/unit/tts/test_snapshot.py +++ b/tests/unit/tts/test_snapshot.py @@ -30,7 +30,7 @@ def _test_snapshot(): # use a simplest iterable object as dataloader dataloader = count() - # hack the training proecss: training does nothing except increse iteration + # hack the training proecss: training does nothing except increase iteration updater = StandardUpdater(model, optimizer, dataloader=dataloader) updater.update_core = lambda x: None diff --git a/tools/extras/install_liblbfgs.sh b/tools/extras/install_liblbfgs.sh index 8d6ae4ab7..0148bd841 100755 --- a/tools/extras/install_liblbfgs.sh +++ b/tools/extras/install_liblbfgs.sh @@ -17,13 +17,13 @@ cd liblbfgs-$VER ./configure --prefix=`pwd` make # due to the liblbfgs project directory structure, we have to use -i -# but the erros are completely harmless +# but the errors are completely harmless make -i install cd .. ( [ ! -z "${LIBLBFGS}" ] && \ - echo >&2 "LIBLBFGS variable is aleady defined. Undefining..." && \ + echo >&2 "LIBLBFGS variable is already defined. Undefining..." && \ unset LIBLBFGS [ -f ./env.sh ] && . ./env.sh diff --git a/tools/extras/install_srilm.sh b/tools/extras/install_srilm.sh index f359e70ce..fdbcf5d97 100755 --- a/tools/extras/install_srilm.sh +++ b/tools/extras/install_srilm.sh @@ -68,7 +68,7 @@ make || exit cd .. ( [ ! -z "${SRILM}" ] && \ - echo >&2 "SRILM variable is aleady defined. Undefining..." && \ + echo >&2 "SRILM variable is already defined. Undefining..." && \ unset SRILM [ -f ./env.sh ] && . ./env.sh diff --git a/utils/format_triplet_data.py b/utils/format_triplet_data.py index e9a0cf54c..029ea2d9b 100755 --- a/utils/format_triplet_data.py +++ b/utils/format_triplet_data.py @@ -44,7 +44,7 @@ add_arg('manifest_paths', str, # bpe add_arg('spm_model_prefix', str, None, "spm model prefix, spm_model_%(bpe_mode)_%(count_threshold), only need when `unit_type` is spm") -add_arg('output_path', str, None, "filepath of formated manifest.", required=True) +add_arg('output_path', str, None, "filepath of formatted manifest.", required=True) # yapf: disable args = parser.parse_args() diff --git a/utils/fst/ctc_token_fst.py b/utils/fst/ctc_token_fst.py index f63e9cdac..85974f27f 100755 --- a/utils/fst/ctc_token_fst.py +++ b/utils/fst/ctc_token_fst.py @@ -32,7 +32,7 @@ def main(args): # leaving `token` print('{} {} {} {}'.format(node, 2, '', '')) node += 1 - # Fianl node + # Final node print('0') diff --git a/utils/fst/make_tlg.sh b/utils/fst/make_tlg.sh index c68387af9..944b8b1f3 100755 --- a/utils/fst/make_tlg.sh +++ b/utils/fst/make_tlg.sh @@ -21,7 +21,7 @@ cp -r $src_lang $tgt_lang # eps2disambig.pl: replace epsilons on the input side with the special disambiguation symbol #0. # s2eps.pl: replaces and with (on both input and output sides), for the G.fst acceptor. # G.fst, the disambiguation symbol #0 only appears on the input side -# do eps2disambig.pl and s2eps.pl maybe just for fallowing `fstrmepsilon`. +# do eps2disambig.pl and s2eps.pl maybe just for following `fstrmepsilon`. cat $arpa_lm | \ grep -v ' ' | \ grep -v ' ' | \ diff --git a/utils/generate_infer_yaml.py b/utils/generate_infer_yaml.py index ca8d6b60d..bd45a1bbd 100755 --- a/utils/generate_infer_yaml.py +++ b/utils/generate_infer_yaml.py @@ -3,7 +3,7 @@ ''' Merge training configs into a single inference config. The single inference config is for CLI, which only takes a single config to do inferencing. - The trainig configs includes: model config, preprocess config, decode config, vocab file and cmvn file. + The training configs includes: model config, preprocess config, decode config, vocab file and cmvn file. Process: # step 1: prepare dir @@ -11,7 +11,7 @@ cp -r exp conf data release_dir cd release_dir - # step 2: get "model.yaml" which conatains all configuration info. + # step 2: get "model.yaml" which contains all configuration info. # if does not contain preprocess.yaml file. e.g ds2: python generate_infer_yaml.py --cfg_pth conf/deepspeech2_online.yaml --dcd_pth conf/tuning/chunk_decode.yaml --vb_pth data/lang_char/vocab.txt --cmvn_pth data/mean_std.json --save_pth model.yaml --pre_pth null # if contains preprocess.yaml file. e.g u2: diff --git a/utils/tokenizer.perl b/utils/tokenizer.perl index 836fe19c6..babf81886 100644 --- a/utils/tokenizer.perl +++ b/utils/tokenizer.perl @@ -79,7 +79,7 @@ if ($HELP) print " -b ... disable Perl buffering.\n"; print " -time ... enable processing time calculation.\n"; print " -penn ... use Penn treebank-like tokenization.\n"; - print " -protected FILE ... specify file with patters to be protected in tokenisation.\n"; + print " -protected FILE ... specify file with patterns to be protected in tokenisation.\n"; print " -no-escape ... don't perform HTML escaping on apostrophy, quotes, etc.\n"; exit; } diff --git a/utils/train_arpa_with_kenlm.sh b/utils/train_arpa_with_kenlm.sh index 8af646ceb..b435239af 100755 --- a/utils/train_arpa_with_kenlm.sh +++ b/utils/train_arpa_with_kenlm.sh @@ -37,7 +37,7 @@ fi # the text should be properly pre-processed, e.g: # cleand, normalized and possibly word-segmented -# get rid off irrelavent symbols +# get rid off irrelevant symbols grep -v '' $symbol_table \ | grep -v '#0' \ | grep -v '' | grep -v '' \ @@ -51,7 +51,7 @@ grep -v '' $symbol_table \ # # TL;DR reason: # Unlike SRILM's -limit-vocab, kenlm's --limit_vocab_file option -# spcifies a *valid* set of vocabulary, whereas *valid but unseen* +# specifies a *valid* set of vocabulary, whereas *valid but unseen* # words are discarded in final arpa. # So the trick is, # we explicitly add kaldi's vocab(one word per line) to training text, diff --git a/utils/zh_tn.py b/utils/zh_tn.py index 6fee626bd..4bb684a1e 100755 --- a/utils/zh_tn.py +++ b/utils/zh_tn.py @@ -1288,7 +1288,7 @@ def normalize_corpus(corpus, def char_token(s: Text) -> List[Text]: - """chinese charactor + """chinese character Args: s (Text): "我爱中国“