diff --git a/.github/stale.yml b/.github/stale.yml index da19b6606..6b0da9b98 100644 --- a/.github/stale.yml +++ b/.github/stale.yml @@ -6,7 +6,8 @@ daysUntilClose: 30 exemptLabels: - Roadmap - Bug - - New Feature + - feature request + - Tips # Label to use when marking an issue as stale staleLabel: Stale # Comment to post when marking an issue as stale. Set to `false` to disable @@ -17,4 +18,4 @@ markComment: > unmarkComment: false # Comment to post when closing a stale issue. Set to `false` to disable closeComment: > - This issue is closed. Please re-open if needed. \ No newline at end of file + This issue is closed. Please re-open if needed. diff --git a/README.md b/README.md index 2fb773634..d3b09576d 100644 --- a/README.md +++ b/README.md @@ -97,26 +97,40 @@ - Life was like a box of chocolates, you never know what you're gonna get. + Life was like a box of chocolates, you never know what you're gonna get.
- 早上好，今天是2020/10/29，最低温度是-3°C。 + 早上好，今天是2020/10/29，最低温度是-3°C。
- 季姬寂，集鸡，鸡即棘鸡。棘鸡饥叽，季姬及箕稷济鸡。鸡既济，跻姬笈，季姬忌，急咭鸡，鸡急，继圾几，季姬急，即籍箕击鸡，箕疾击几伎，伎即齑，鸡叽集几基，季姬急极屐击鸡，鸡既殛，季姬激，即记《季姬击鸡记》。 + 季姬寂，集鸡，鸡即棘鸡。棘鸡饥叽，季姬及箕稷济鸡。鸡既济，跻姬笈，季姬忌，急咭鸡，鸡急，继圾几，季姬急，即籍箕击鸡，箕疾击几伎，伎即齑，鸡叽集几基，季姬急极屐击鸡，鸡既殛，季姬激，即记《季姬击鸡记》。
+ + 大家好，我是 parrot 虚拟老师，我们来读一首诗，我与春风皆过客，I and the spring breeze are passing by，你携秋水揽星河，you take the autumn water to take the galaxy。 + + +
+ + + + 宜家唔系事必要你讲，但系你所讲嘅说话将会变成呈堂证供。 + + +
+ + @@ -157,18 +171,19 @@ Via the easy-to-use, efficient, flexible and scalable implementation, our vision - 🧩 *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). ### Recent Update -- 🔥 2022.01.10: Add [code-switch asr CLI and Demos](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/demos/speech_recognition). -- 👑 2022.01.06: Add [code-switch asr tal_cs recipe](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/tal_cs/asr1/). -- 🎉 2022.12.02: Add [end-to-end Prosody Prediction pipeline](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/csmsc/tts3_rhy) (including using prosody labels in Acoustic Model). -- 🎉 2022.11.30: Add [TTS Android Demo](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/demos/TTSAndroid). +- 🎉 2023.02.16: Add [Cantonese TTS](./examples/canton/tts3). +- 🔥 2023.01.10: Add [code-switch asr CLI and Demos](./demos/speech_recognition). +- 👑 2023.01.06: Add [code-switch asr tal_cs recipe](./examples/tal_cs/asr1/). +- 🎉 2022.12.02: Add [end-to-end Prosody Prediction pipeline](./examples/csmsc/tts3_rhy) (including using prosody labels in Acoustic Model). +- 🎉 2022.11.30: Add [TTS Android Demo](./demos/TTSAndroid). - 🤗 2022.11.28: PP-TTS and PP-ASR demos are available in [AIStudio](https://aistudio.baidu.com/aistudio/modelsoverview) and [official website of paddlepaddle](https://www.paddlepaddle.org.cn/models). - 👑 2022.11.18: Add [Whisper CLI and Demos](https://github.com/PaddlePaddle/PaddleSpeech/pull/2640), support multi language recognition and translation. -- 🔥 2022.11.18: Add [Wav2vec2 CLI and Demos](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/demos/speech_ssl), Support ASR and Feature Extraction. +- 🔥 2022.11.18: Add [Wav2vec2 CLI and Demos](./demos/speech_ssl), Support ASR and Feature Extraction. - 🎉 2022.11.17: Add [male voice for TTS](https://github.com/PaddlePaddle/PaddleSpeech/pull/2660). -- 🔥 2022.11.07: Add [U2/U2++ C++ High Performance Streaming ASR Deployment](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/speechx/examples/u2pp_ol/wenetspeech). +- 🔥 2022.11.07: Add [U2/U2++ C++ High Performance Streaming ASR Deployment](./speechx/examples/u2pp_ol/wenetspeech). - 👑 2022.11.01: Add [Adversarial Loss](https://arxiv.org/pdf/1907.04448.pdf) for [Chinese English mixed TTS](./examples/zh_en_tts/tts3). -- 🔥 2022.10.26: Add [Prosody Prediction](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/other/rhy) for TTS. +- 🔥 2022.10.26: Add [Prosody Prediction](./examples/other/rhy) for TTS. - 🎉 2022.10.21: Add [SSML](https://github.com/PaddlePaddle/PaddleSpeech/discussions/2538) for TTS Chinese Text Frontend. - 👑 2022.10.11: Add [Wav2vec2ASR-en](./examples/librispeech/asr3), wav2vec2.0 fine-tuning for ASR on LibriSpeech. - 🔥 2022.09.26: Add Voice Cloning, TTS finetune, and [ERNIE-SAT](https://arxiv.org/abs/2211.03545) in [PaddleSpeech Web Demo](./demos/speech_web). @@ -191,7 +206,7 @@ Via the easy-to-use, efficient, flexible and scalable implementation, our vision - Scan the QR code below with your Wechat, you can access to official technical exchange group and get the bonus ( more than 20GB learning materials, such as papers, codes and videos ) and the live link of the lessons. Look forward to your participation.
- +
## Installation @@ -987,8 +1002,9 @@ 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. 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. ## License diff --git a/README_cn.md b/README_cn.md index 53f6a66e4..be1c5d44f 100644 --- a/README_cn.md +++ b/README_cn.md @@ -122,6 +122,20 @@
+ + 大家好，我是 parrot 虚拟老师，我们来读一首诗，我与春风皆过客，I and the spring breeze are passing by，你携秋水揽星河，you take the autumn water to take the galaxy。 + + +
+ + + + 宜家唔系事必要你讲，但系你所讲嘅说话将会变成呈堂证供。 + + +
+ + @@ -161,20 +175,19 @@ - 🔬 主流模型及数据集: 本工具包实现了参与整条语音任务流水线的各个模块，并且采用了主流数据集如 LibriSpeech、LJSpeech、AIShell、CSMSC，详情请见 [模型列表](#model-list)。 - 🧩 级联模型应用: 作为传统语音任务的扩展，我们结合了自然语言处理、计算机视觉等任务，实现更接近实际需求的产业级应用。 - - ### 近期更新 -- 🔥 2022.01.10: 新增 [中英混合 ASR CLI 和 Demos](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/demos/speech_recognition). -- 👑 2022.01.06: 新增 [ASR中英混合 tal_cs 训练推理流程](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/tal_cs/asr1/). -- 🎉 2022.12.02: 新增 [端到端韵律预测全流程](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/csmsc/tts3_rhy) (包含在声学模型中使用韵律标签)。 -- 🎉 2022.11.30: 新增 [TTS Android 部署示例](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/demos/TTSAndroid)。 +- 🎉 2023.02.16: 新增[粤语语音合成](./examples/canton/tts3)。 +- 🔥 2023.01.10: 新增[中英混合 ASR CLI 和 Demos](./demos/speech_recognition)。 +- 👑 2023.01.06: 新增 [ASR 中英混合 tal_cs 训练推理流程](./examples/tal_cs/asr1/)。 +- 🎉 2022.12.02: 新增[端到端韵律预测全流程](./examples/csmsc/tts3_rhy) (包含在声学模型中使用韵律标签)。 +- 🎉 2022.11.30: 新增 [TTS Android 部署示例](./demos/TTSAndroid)。 - 🤗 2022.11.28: PP-TTS and PP-ASR 示例可在 [AIStudio](https://aistudio.baidu.com/aistudio/modelsoverview) 和[飞桨官网](https://www.paddlepaddle.org.cn/models)体验！ - 👑 2022.11.18: 新增 [Whisper CLI 和 Demos](https://github.com/PaddlePaddle/PaddleSpeech/pull/2640), 支持多种语言的识别与翻译。 -- 🔥 2022.11.18: 新增 [Wav2vec2 CLI 和 Demos](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/demos/speech_ssl), 支持 ASR 和 特征提取. +- 🔥 2022.11.18: 新增 [Wav2vec2 CLI 和 Demos](./demos/speech_ssl), 支持 ASR 和特征提取。 - 🎉 2022.11.17: TTS 新增[高质量男性音色](https://github.com/PaddlePaddle/PaddleSpeech/pull/2660)。 -- 🔥 2022.11.07: 新增 [U2/U2++ 高性能流式 ASR C++ 部署](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/speechx/examples/u2pp_ol/wenetspeech)。 +- 🔥 2022.11.07: 新增 [U2/U2++ 高性能流式 ASR C++ 部署](./speechx/examples/u2pp_ol/wenetspeech)。 - 👑 2022.11.01: [中英文混合 TTS](./examples/zh_en_tts/tts3) 新增 [Adversarial Loss](https://arxiv.org/pdf/1907.04448.pdf) 模块。 -- 🔥 2022.10.26: TTS 新增[韵律预测](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/other/rhy)功能。 +- 🔥 2022.10.26: TTS 新增[韵律预测](./develop/examples/other/rhy)功能。 - 🎉 2022.10.21: TTS 中文文本前端新增 [SSML](https://github.com/PaddlePaddle/PaddleSpeech/discussions/2538) 功能。 - 👑 2022.10.11: 新增 [Wav2vec2ASR-en](./examples/librispeech/asr3), 在 LibriSpeech 上针对 ASR 任务对 wav2vec2.0 的 finetuning。 - 🔥 2022.09.26: 新增 Voice Cloning, TTS finetune 和 [ERNIE-SAT](https://arxiv.org/abs/2211.03545) 到 [PaddleSpeech 网页应用](./demos/speech_web)。 @@ -202,7 +215,7 @@ 微信扫描二维码关注公众号，点击“马上报名”填写问卷加入官方交流群，获得更高效的问题答疑，与各行各业开发者充分交流，期待您的加入。
- +
@@ -988,10 +1001,11 @@ PaddleSpeech 的 **语音合成** 主要包含三个模块：文本前端、声 - 非常感谢 [awmmmm](https://github.com/awmmmm) 提供 fastspeech2 aishell3 conformer 预训练模型。 - 非常感谢 [phecda-xu](https://github.com/phecda-xu)/[PaddleDubbing](https://github.com/phecda-xu/PaddleDubbing) 基于 PaddleSpeech 的 TTS 模型搭建带 GUI 操作界面的配音工具。 - 非常感谢 [jerryuhoo](https://github.com/jerryuhoo)/[VTuberTalk](https://github.com/jerryuhoo/VTuberTalk) 基于 PaddleSpeech 的 TTS GUI 界面和基于 ASR 制作数据集的相关代码。 - - 非常感谢 [vpegasus](https://github.com/vpegasus)/[xuesebot](https://github.com/vpegasus/xuesebot) 基于 PaddleSpeech 的 ASR 与 TTS 设计的可听、说对话机器人。 - 非常感谢 [chenkui164](https://github.com/chenkui164)/[FastASR](https://github.com/chenkui164/FastASR) 对 PaddleSpeech 的 ASR 进行 C++ 推理实现。 - 非常感谢 [heyudage](https://github.com/heyudage)/[VoiceTyping](https://github.com/heyudage/VoiceTyping) 基于 PaddleSpeech 的 ASR 流式服务实现的实时语音输入法工具。 +- 非常感谢 [EscaticZheng](https://github.com/EscaticZheng)/[ps3.9wheel-install](https://github.com/EscaticZheng/ps3.9wheel-install) 对PaddleSpeech在Windows下的安装提供了无需Visua Studio，基于python3.9的预编译依赖安装包。 +- 非常感谢 [chinobing](https://github.com/chinobing)/[FastAPI-PaddleSpeech-Audio-To-Text](https://github.com/chinobing/FastAPI-PaddleSpeech-Audio-To-Text) 利用 FastAPI 实现 PaddleSpeech 语音转文字，文件上传、分割、转换进度显示、后台更新任务并以 csv 格式输出。 此外，PaddleSpeech 依赖于许多开源存储库。有关更多信息，请参阅 [references](./docs/source/reference.md)。 diff --git a/audio/setup.py b/audio/setup.py index 82e9a55a5..823e5dfad 100644 --- a/audio/setup.py +++ b/audio/setup.py @@ -40,14 +40,9 @@ COMMITID = 'none' base = [ "kaldiio", "librosa==0.8.1", - "scipy>=1.0.0", - "soundfile~=0.10", - "colorlog", - "pathos == 0.2.8", + "pathos", "pybind11", "parameterized", - "tqdm", - "scikit-learn" ] requirements = { @@ -273,7 +268,7 @@ def main(): }, # Package info - packages=find_packages(include=('paddleaudio*')), + packages=find_packages(include=['paddleaudio*']), package_data=lib_package_data, ext_modules=setup_helpers.get_ext_modules(), zip_safe=True, diff --git a/demos/speech_web/speech_server/requirements.txt b/demos/speech_web/speech_server/requirements.txt index cdc654656..8425a1fee 100644 --- a/demos/speech_web/speech_server/requirements.txt +++ b/demos/speech_web/speech_server/requirements.txt @@ -1,8 +1,6 @@ aiofiles faiss-cpu -praatio==5.0.0 +praatio>=5.0.0 pydantic python-multipart -scikit_learn starlette -uvicorn diff --git a/docs/requirements.txt b/docs/requirements.txt index c6228d917..65f451cd2 100644 --- a/docs/requirements.txt +++ b/docs/requirements.txt @@ -1,12 +1,9 @@ braceexpand -colorlog editdistance -fastapi g2p_en g2pM h5py inflect -jieba jsonlines kaldiio keyboard @@ -16,7 +13,7 @@ matplotlib myst-parser nara_wpe numpydoc -onnxruntime==1.10.0 +onnxruntime>=1.11.0 opencc paddlenlp # use paddlepaddle == 2.3.* according to: https://github.com/PaddlePaddle/Paddle/issues/48243 @@ -24,32 +21,25 @@ paddlepaddle>=2.2.2,<2.4.0 paddlespeech_ctcdecoders paddlespeech_feat pandas -pathos==0.2.8 pattern_singleton -Pillow>=9.0.0 ppdiffusers>=0.9.0 -praatio==5.0.0 +praatio>=5.0.0 prettytable pypinyin-dict pypinyin<=0.44.0 python-dateutil -pyworld==0.2.12 +pyworld>=0.2.12 recommonmark>=0.5.0 -resampy==0.2.2 +resampy sacrebleu -scipy -sentencepiece~=0.1.96 -soundfile~=0.10 sphinx sphinx-autobuild sphinx-markdown-tables sphinx_rtd_theme textgrid timer -tqdm +ToJyutping typeguard -uvicorn -visualdl webrtcvad websockets yacs~=0.1.8 diff --git a/examples/aishell/asr3/README.md b/examples/aishell/asr3/README.md new file mode 100644 index 000000000..e5806d621 --- /dev/null +++ b/examples/aishell/asr3/README.md @@ -0,0 +1,198 @@ +# Wav2vec2ASR with Aishell +This example contains code used to finetune [wav2vec2.0](https://https://arxiv.org/pdf/2006.11477.pdf) model with [Aishell dataset](http://www.openslr.org/resources/33) +## Overview +All the scripts you need are in `run.sh`. There are several stages in `run.sh`, and each stage has its function. +| Stage | Function | +|:---- |:----------------------------------------------------------- | +| 0 | Process data. It includes:
(1) Download the dataset
(2) Calculate the CMVN of the train dataset
(3) Get the vocabulary file
(4) Get the manifest files of the train, development and test dataset
(5) Download the pretrained wav2vec2 model | +| 1 | Train the model | +| 2 | Get the final model by averaging the top-k models, set k = 1 means to choose the best model | +| 3 | Test the final model performance | +| 4 | Infer the single audio file | + + +You can choose to run a range of stages by setting `stage` and `stop_stage `. + +For example, if you want to execute the code in stage 2 and stage 3, you can run this script: +```bash +bash run.sh --stage 2 --stop_stage 3 +``` +Or you can set `stage` equal to `stop-stage` to only run one stage. +For example, if you only want to run `stage 0`, you can use the script below: +```bash +bash run.sh --stage 0 --stop_stage 0 +``` +The document below will describe the scripts in `run.sh` in detail. +## The Environment Variables +The path.sh contains the environment variables. +```bash +. ./path.sh +. ./cmd.sh +``` +This script needs to be run first. And another script is also needed: +```bash +source ${MAIN_ROOT}/utils/parse_options.sh +``` +It will support the way of using `--variable value` in the shell scripts. +## The Local Variables +Some local variables are set in `run.sh`. +`gpus` denotes the GPU number you want to use. If you set `gpus=`, it means you only use CPU. +`stage` denotes the number of stages you want to start from in the experiments. +`stop stage` denotes the number of the stage you want to end at in the experiments. +`conf_path` denotes the config path of the model. +`avg_num` denotes the number K of top-K models you want to average to get the final model. +`audio file` denotes the file path of the single file you want to infer in stage 5 +`ckpt` denotes the checkpoint prefix of the model, e.g. "wav2vec2ASR" + +You can set the local variables (except `ckpt`) when you use `run.sh` + +For example, you can set the `gpus` and `avg_num` when you use the command line: +```bash +bash run.sh --gpus 0,1 --avg_num 20 +``` +## Stage 0: Data Processing +To use this example, you need to process data firstly and you can use stage 0 in `run.sh` to do this. The code is shown below: +```bash + if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then + # prepare data + bash ./local/data.sh || exit -1 + fi +``` +Stage 0 is for processing the data. + +If you only want to process the data. You can run +```bash +bash run.sh --stage 0 --stop_stage 0 +``` +You can also just run these scripts in your command line. +```bash +. ./path.sh +. ./cmd.sh +bash ./local/data.sh +``` +After processing the data, the `data` directory will look like this: +```bash +data/ +|-- dev.meta +|-- lang_char +| `-- vocab.txt +|-- manifest.dev +|-- manifest.dev.raw +|-- manifest.test +|-- manifest.test.raw +|-- manifest.train +|-- manifest.train.raw +|-- mean_std.json +|-- test.meta +|-- train.meta +|-- train.csv +|-- dev.csv +|-- test.csv +``` + +Stage 0 also downloads the Chinese pre-trained [wav2vec2](https://paddlespeech.bj.bcebos.com/wav2vec/chinese-wav2vec2-large.pdparams) model. +```bash +mkdir -p exp/wav2vec2 +wget -P exp/wav2vec2 https://paddlespeech.bj.bcebos.com/wav2vec/chinese-wav2vec2-large.pdparams +``` +## Stage 1: Model Training +If you want to train the model. you can use stage 1 in `run.sh`. The code is shown below. +```bash +if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then + # train model, all `ckpt` under `exp` dir + CUDA_VISIBLE_DEVICES=${gpus} ./local/train.sh ${conf_path} ${ckpt} + fi +``` +If you want to train the model, you can use the script below to execute stage 0 and stage 1: +```bash +bash run.sh --stage 0 --stop_stage 1 +``` +or you can run these scripts in the command line (only use CPU). +```bash +. ./path.sh +. ./cmd.sh +bash ./local/data.sh +CUDA_VISIBLE_DEVICES= ./local/train.sh conf/wav2vec2ASR.yaml wav2vec2ASR +``` +## Stage 2: Top-k Models Averaging +After training the model, we need to get the final model for testing and inference. In every epoch, the model checkpoint is saved, so we can choose the best model from them based on the validation loss or we can sort them and average the parameters of the top-k models to get the final model. We can use stage 2 to do this, and the code is shown below. Note: We only train one epoch for wav2vec2ASR, thus the `avg_num` is set to 1. +```bash + if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then + # avg n best model + avg.sh best exp/${ckpt}/checkpoints ${avg_num} + fi +``` +The `avg.sh` is in the `../../../utils/` which is define in the `path.sh`. +If you want to get the final model, you can use the script below to execute stage 0, stage 1, and stage 2: +```bash +bash run.sh --stage 0 --stop_stage 2 +``` +or you can run these scripts in the command line (only use CPU). + +```bash +. ./path.sh +. ./cmd.sh +bash ./local/data.sh +CUDA_VISIBLE_DEVICES= ./local/train.sh conf/wav2vec2ASR.yaml wav2vec2ASR +avg.sh best exp/wav2vec2ASR/checkpoints 1 +``` +## Stage 3: Model Testing +The test stage is to evaluate the model performance. The code of test stage is shown below: +```bash + if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then + # test ckpt avg_n + CUDA_VISIBLE_DEVICES=0 ./local/test.sh ${conf_path} ${decode_conf_path} exp/${ckpt}/checkpoints/${avg_ckpt} || exit -1 + fi +``` +If you want to train a model and test it, you can use the script below to execute stage 0, stage 1, stage 2, and stage 3 : +```bash +bash run.sh --stage 0 --stop_stage 3 +``` +or you can run these scripts in the command line (only use CPU). +```bash +. ./path.sh +. ./cmd.sh +bash ./local/data.sh +CUDA_VISIBLE_DEVICES= ./local/train.sh conf/wav2vec2ASR.yaml wav2vec2ASR +avg.sh best exp/wav2vec2ASR/checkpoints 1 +CUDA_VISIBLE_DEVICES= ./local/test.sh conf/wav2vec2ASR.yaml conf/tuning/decode.yaml exp/wav2vec2ASR/checkpoints/avg_1 +``` +## Pretrained Model +You can get the pretrained wav2vec2ASR from [this](../../../docs/source/released_model.md). + +using the `tar` scripts to unpack the model and then you can use the script to test the model. + +For example: +```bash +wget https://paddlespeech.bj.bcebos.com/s2t/aishell/asr3/wav2vec2ASR-large-aishell1_ckpt_1.3.0.model.tar.gz +tar xzvf wav2vec2ASR-large-aishell1_ckpt_1.3.0.model.tar.gz +source path.sh +# If you have process the data and get the manifest file， you can skip the following 2 steps +bash local/data.sh --stage -1 --stop_stage -1 +bash local/data.sh --stage 2 --stop_stage 2 +CUDA_VISIBLE_DEVICES= ./local/test.sh conf/wav2vec2ASR.yaml conf/tuning/decode.yaml exp/wav2vec2ASR/checkpoints/avg_1 +``` +The performance of the released models are shown in [here](./RESULTS.md). + + +## Stage 4: Single Audio File Inference +In some situations, you want to use the trained model to do the inference for the single audio file. You can use stage 5. The code is shown below +```bash + if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then + # test a single .wav file + CUDA_VISIBLE_DEVICES=0 ./local/test_wav.sh ${conf_path} ${decode_conf_path} exp/${ckpt}/checkpoints/${avg_ckpt} ${audio_file} || exit -1 + fi +``` +you can train the model by yourself using ```bash run.sh --stage 0 --stop_stage 3```, or you can download the pretrained model through the script below: +```bash +wget https://paddlespeech.bj.bcebos.com/s2t/aishell/asr3/wav2vec2ASR-large-aishell1_ckpt_1.3.0.model.tar.gz +tar xzvf wav2vec2ASR-large-aishell1_ckpt_1.3.0.model.tar.gz +``` +You can download the audio demo: +```bash +wget -nc https://paddlespeech.bj.bcebos.com/datasets/single_wav/en/demo_002_en.wav -P data/ +``` +You need to prepare an audio file or use the audio demo above, please confirm the sample rate of the audio is 16K. You can get the result of the audio demo by running the script below. +```bash +CUDA_VISIBLE_DEVICES= ./local/test_wav.sh conf/wav2vec2ASR.yaml conf/tuning/decode.yaml exp/wav2vec2ASR/checkpoints/avg_1 data/demo_002_en.wav +``` diff --git a/examples/aishell/asr3/cmd.sh b/examples/aishell/asr3/cmd.sh new file mode 100755 index 000000000..7b70ef5e0 --- /dev/null +++ b/examples/aishell/asr3/cmd.sh @@ -0,0 +1,89 @@ +# ====== About run.pl, queue.pl, slurm.pl, and ssh.pl ====== +# Usage: .pl [options] JOB=1: +# e.g. +# run.pl --mem 4G JOB=1:10 echo.JOB.log echo JOB +# +# Options: +# --time