README_cn.md

 (简体中文|[English](./README.md))
<p align="center">
  <img src="./docs/images/PaddleSpeech_logo.png" />
</p>
<div align="center">  

  <h3>
  <a href="#quick-start"> 快速开始 </a>
  | <a href="#documents"> 教程 </a>
  | <a href="#model-list"> 模型列表 </a>
</div>

------------------------------------------------------------------------------------
<p align="center">
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**PaddleSpeech** 是基于飞桨 [PaddlePaddle](https://github.com/PaddlePaddle/Paddle) 深度学习开源框架平台上的一个开源模型库，用于语音和音频中的各种关键任务的开发，包含大量前沿和有影响力的模型，一些典型的应用示例如下：
##### 语音识别

<div align = "center">
<table style="width:100%">
  <thead>
    <tr>
      <th> 输入音频  </th>
      <th width="550"> 识别结果  </th>
    </tr>
  </thead>
  <tbody>
   <tr>
      <td align = "center">
      <a href="https://paddlespeech.bj.bcebos.com/PaddleAudio/en.wav" rel="nofollow">
            <img align="center" src="./docs/images/audio_icon.png" width="200 style="max-width: 100%;"></a><br>
      </td>
      <td >I knocked at the door on the ancient side of the building.</td>
    </tr>
    <tr>
      <td align = "center">
      <a href="https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav" rel="nofollow">
            <img align="center" src="./docs/images/audio_icon.png" width="200" style="max-width: 100%;"></a><br>
      </td>
      <td>我认为跑步最重要的就是给我带来了身体健康。</td>
    </tr>
    
  </tbody>
</table>

</div>

##### 语音翻译 (英译中)

<div align = "center">
<table style="width:100%">
  <thead>
    <tr>
      <th> 输入音频  </th>
      <th width="550"> 翻译结果  </th>
    </tr>
  </thead>
  <tbody>
   <tr>
      <td align = "center">
      <a href="https://paddlespeech.bj.bcebos.com/PaddleAudio/en.wav" rel="nofollow">
            <img align="center" src="./docs/images/audio_icon.png" width="200 style="max-width: 100%;"></a><br>
      </td>
      <td >我 在 这栋 建筑 的 古老 门上 敲门。</td>
    </tr>
  </tbody>
</table>

</div>

##### 文本转语音
<div align = "center">
<table style="width:100%">
  <thead>
    <tr>
      <th><img width="200" height="1"> 输入文本 <img width="200" height="1"> </th>
      <th>合成音频</th>
    </tr>
  </thead>
  <tbody>
   <tr>
      <td >Life was like a box of chocolates, you never know what you're gonna get.</td>
      <td align = "center">
      <a href="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/transformer_tts_ljspeech_ckpt_0.4_waveflow_ljspeech_ckpt_0.3/001.wav" rel="nofollow">
            <img align="center" src="./docs/images/audio_icon.png" width="200" style="max-width: 100%;"></a><br>
      </td>
    </tr>
    <tr>
      <td >早上好，今天是2020/10/29，最低温度是-3°C。</td>
      <td align = "center">
      <a href="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/001.wav" rel="nofollow">
            <img align="center" src="./docs/images/audio_icon.png" width="200" style="max-width: 100%;"></a><br>
      </td>
    </tr>
  </tbody>
</table>

</div>

更多合成音频，可以参考 [PaddleSpeech 语音合成音频示例](https://paddlespeech.readthedocs.io/en/latest/tts/demo.html)。

### 特性:

本项目采用了易用、高效、灵活以及可扩展的实现，旨在为工业应用、学术研究提供更好的支持，实现的功能包含训练、推断以及测试模块，以及部署过程，主要包括
- 📦 **易用性**: 安装门槛低，可使用[CLI](#quick-start)快速开始。
- 🏆 **对标SoTA**: 提供了高速、轻量级模型，且借鉴了最前沿的技术。
- 💯 **基于规则的中文前端**: 我们的前端包含文本正则化和字音转换（G2P）。此外，我们使用自定义语言规则来适应中文语境。
- **多种工业界以及学术界主流功能支持**:
  - 🛎️ 典型音频任务: 本工具包提供了音频任务如音频分类、语音翻译、自动语音识别、文本转语音、语音合成等任务的实现。
  - 🔬 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，我们结合了自然与语言处理、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:

<!---
2021.12.14: We would like to have an online courses to introduce basics and research of speech, as well as code practice with `paddlespeech`. Please pay attention to our [Calendar](https://www.paddlepaddle.org.cn/live).
--->
- 🤗 2021.12.14: 我们在 Hugging Face Spaces 上的 [ASR](https://huggingface.co/spaces/KPatrick/PaddleSpeechASR) 以及 [TTS](https://huggingface.co/spaces/akhaliq/paddlespeech) Demos 上线啦!
- 👏🏻 2021.12.10: PaddleSpeech CLI 上线！覆盖了声音分类、语音识别、语音翻译（英译中）以及语音合成。

### 交流
欢迎加入以下微信群，直接和我们 PaddleSpeech 团队进行交流！

<div align="center">
<img src="./docs/images/wechat_group.png"  width = "200"  />

</div>

## 安装

我们强烈建议用户在 **Linux** 环境下，*3.7* 以上版本的 *python* 上安装 PaddleSpeech。这种情况下安装 `paddlespeech` 只需要一条 `pip` 命令:
```python
pip install paddlepaddle paddlespeech
```
目前为止，对于 **Mac OSX、 LiNUX** 支持声音分类、语音识别、语音合成和语音翻译四种功能，**Windows** 下暂不支持语音翻译功能。 想了解更多安装细节，可以参考[安装文档](./docs/source/install_cn.md)。

## 快速开始

安装完成后，开发者可以通过命令行快速开始，改变`--input `可以尝试用自己的音频或文本测试。

**声音分类**     
```shell
paddlespeech cls --input input.wav
```
**语音识别**
```shell
paddlespeech asr --lang zh --input input_16k.wav
```
**语音翻译** (English to Chinese)
```shell
paddlespeech st --input input_16k.wav
```
**语音合成** 
```shell
paddlespeech tts --input "你好，欢迎使用百度飞桨深度学习框架！" --output output.wav
```
> Note: 如果需要训练或者微调，请查看[语音识别](./docs/source/asr/quick_start.md)， [语音合成](./docs/source/tts/quick_start.md)。

## 模型列表

PaddleSpeech 支持很多主流的模型，并提供了预训练模型，详情请见[模型列表](./docs/source/released_model.md)。

**语音转文本** 包含声学模型和语言模型, 详情如下：

<!---
The current hyperlinks redirect to [Previous Parakeet](https://github.com/PaddlePaddle/Parakeet/tree/develop/examples).
-->

<table style="width:100%">
  <thead>
    <tr>
      <th>语音转文本模块种类</th>
      <th>数据集</th>
      <th>模型种类</th>
      <th>链接</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td rowspan="3">语音识别</td>
      <td rowspan="2" >Aishell</td>
      <td >DeepSpeech2 RNN + Conv based Models</td>
      <td>
      <a href = "./examples/aishell/asr0">deepspeech2-aishell</a>
      </td>
    </tr>
    <tr>
      <td>基于Transformer的Attention模型 </td>
      <td>
      <a href = "./examples/aishell/asr1">u2.transformer.conformer-aishell</a>
      </td>
    </tr>
      <tr>
      <td> Librispeech</td>
      <td>基于Transformer的Attention模型 </td>
      <td>
      <a href = "./examples/librispeech/asr0">deepspeech2-librispeech</a> / <a href = "./examples/librispeech/asr1">transformer.conformer.u2-librispeech</a>  / <a href = "./examples/librispeech/asr2">transformer.conformer.u2-kaldi-librispeech</a>
      </td>
      </td>
    </tr>
  <tr>
  <td>对齐</td>
  <td>THCHS30</td>
  <td>MFA</td>
  <td>
  <a href = ".examples/thchs30/align0">mfa-thchs30</a>
  </td>
  </tr>
   <tr>
      <td rowspan="2">语言模型</td>
      <td colspan = "2">Ngram 语言模型</td>
      <td>
      <a href = "./examples/other/ngram_lm">kenlm</a>
      </td>
    </tr>
    <tr>
      <td>TIMIT</td>
      <td>Unified Streaming & Non-streaming Two-pass</td>
      <td>
    <a href = "./examples/timit/asr1"> u2-timit</a>
      </td>
    </tr>
    <tr>
      <td rowspan="2">语音翻译（英译中）</td> 
      <td rowspan="2">TED En-Zh</td>
      <td>Transformer + ASR MTL</td>
      <td>
      <a href = "./examples/ted_en_zh/st0">transformer-ted</a>
      </td>
  </tr>
  <tr>
      <td>FAT + Transformer + ASR MTL</td>
      <td>
      <a href = "./examples/ted_en_zh/st1">fat-st-ted</a>
      </td>
  </tr>
  </tbody>
</table>

PaddleSpeech 中的 **文本转语音** 主要包含三个模块：*文本前端*、*声学模型* 和 *声码器*。声学模型和声码器模型如下：

<table>
  <thead>
    <tr>
      <th> 文字转语音模块类型 <img width="110" height="1"> </th>
      <th>  模型种类  </th>
      <th> <img width="50" height="1"> 数据集  <img width="50" height="1"> </th>
      <th> <img width="101" height="1"> 链接 <img width="105" height="1"> </th>
    </tr>
  </thead>
  <tbody>
    <tr>
    <td> 文本前端</td>
    <td colspan="2"> &emsp; </td>
    <td>
    <a href = "./examples/other/tn">tn</a> / <a href = "./examples/other/g2p">g2p</a>
    </td>
    </tr>
    <tr>
      <td rowspan="4">声学模型</td>
      <td >Tacotron2</td>
      <td rowspan="2" >LJSpeech</td>
      <td>
      <a href = "./examples/ljspeech/tts0">tacotron2-ljspeech</a>
      </td>
    </tr>
    <tr>
      <td>Transformer TTS</td>
      <td>
      <a href = "./examples/ljspeech/tts1">transformer-ljspeech</a>
      </td>
    </tr>
    <tr>
      <td>SpeedySpeech</td>
      <td>CSMSC</td>
      <td >
      <a href = "./examples/csmsc/tts2">speedyspeech-csmsc</a>
      </td>
    </tr>
    <tr>
      <td>FastSpeech2</td>
      <td>AISHELL-3 / VCTK / LJSpeech / CSMSC</td>
      <td>
      <a href = "./examples/aishell3/tts3">fastspeech2-aishell3</a> / <a href = "./examples/vctk/tts3">fastspeech2-vctk</a> / <a href = "./examples/ljspeech/tts3">fastspeech2-ljspeech</a> / <a href = "./examples/csmsc/tts3">fastspeech2-csmsc</a>
      </td>
    </tr>
   <tr>
      <td rowspan="3">Vocoder</td>
      <td >WaveFlow</td>
      <td >LJSpeech</td>
      <td>
      <a href = "./examples/ljspeech/voc0">waveflow-ljspeech</a>
      </td>
    </tr>
    <tr>
      <td >Parallel WaveGAN</td>
      <td >LJSpeech / VCTK / CSMSC</td>
      <td>
      <a href = "./examples/ljspeech/voc1">PWGAN-ljspeech</a> / <a href = "./examples/vctk/voc1">PWGAN-vctk</a> / <a href = "./examples/csmsc/voc1">PWGAN-csmsc</a>
      </td>
    </tr>
    <tr>
      <td >Multi Band MelGAN</td>
      <td >CSMSC</td>
      <td>
      <a href = "./examples/csmsc/voc3">Multi Band MelGAN-csmsc</a> 
      </td>
    </tr>                                                                                                                                           
    <tr>
      <td rowspan="3">Voice Cloning</td>
      <td>GE2E</td>
      <td >Librispeech, etc.</td>
      <td>
      <a href = "./examples/other/ge2e">ge2e</a>
      </td>
    </tr>
    <tr>
      <td>GE2E + Tactron2</td>
      <td>AISHELL-3</td>
      <td>
      <a href = "./examples/aishell3/vc0">ge2e-tactron2-aishell3</a>
      </td>
    </tr>
    <tr>
      <td>GE2E + FastSpeech2</td>
      <td>AISHELL-3</td>
      <td>
      <a href = "./examples/aishell3/vc1">ge2e-fastspeech2-aishell3</a>
      </td>
    </tr>
  </tbody>
</table>

**声音分类**

<table style="width:100%">
  <thead>
    <tr>
      <th> <img width="150" height="1">任务 <img width="150" height="1"></th>
      <th> <img width="110" height="1">数据集 <img width="110" height="1"></th>
      <th> 模型种类 </th>
      <th> 链接</th>
    </tr>
  </thead>
  <tbody>
  

  <tr>
      <td>Audio Classification</td>
      <td>ESC-50</td>
      <td>PANN</td>
      <td>
      <a href = "./examples/esc50/cls0">pann-esc50</a>
      </td>
    </tr>
  </tbody>
</table>

## 文档

[语音 SoTA](https://paperswithcode.com/area/speech)、[声音 SoTA](https://paperswithcode.com/area/audio)、[音乐 SoTA](https://paperswithcode.com/area/music) 概述了相关领域的热门学术话题。对于 PaddleSpeech 的所关注的任务，以下指南有助于掌握核心思想。

- [安装](./docs/source/install.md)
- 教程
  - [语音识别](./docs/source/asr/quick_start.md)
    - [简介](./docs/source/asr/models_introduction.md)
    - [数据准备](./docs/source/asr/data_preparation.md)
    - [数据增强](./docs/source/asr/augmentation.md)
    - [Ngram 语言模型](./docs/source/asr/ngram_lm.md)
  - [语音合成](./docs/source/tts/quick_start.md)
    - [简介](./docs/source/tts/models_introduction.md)
    - [进阶用法](./docs/source/tts/advanced_usage.md)
    - [中文文本前端](./docs/source/tts/zh_text_frontend.md)
    - [音频示例](https://paddlespeech.readthedocs.io/en/latest/tts/demo.html)
  - 声音分类
  - 语音翻译
- [模型](./docs/source/released_model.md)


语音合成模块最初被称为 [Parakeet](https://github.com/PaddlePaddle/Parakeet)，现在与此仓库合并。如果您对该任务的学术研究感兴趣，请参阅 [TTS 研究概述](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/docs/source/tts#overview)。此外，[模型介绍](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/docs/source/tts/models_introduction.md) 是了解语音合成流程的一个很好的指南。

## 引用

要引用 PaddleSpeech 进行研究，请使用以下格式进行引用。
```tex
@misc{ppspeech2021,
title={PaddleSpeech, a toolkit for audio processing based on PaddlePaddle.},
author={PaddlePaddle Authors},
howpublished = {\url{https://github.com/PaddlePaddle/PaddleSpeech}},
year={2021}
}
```

## 参与PaddleSpeech的开发


热烈欢迎您在[讨论](https://github.com/PaddlePaddle/PaddleSpeech/discussions) 中提交问题，并在[问题](https://github.com/PaddlePaddle/PaddleSpeech/issues) 中指出发现的bug。此外，我们非常希望您愿意参与到PaddleSpeech的开发中！

### 贡献者
<p align="center">
<a href="https://github.com/zh794390558"><img src="https://avatars.githubusercontent.com/u/3038472?v=4" width=75 height=75></a>
<a href="https://github.com/Jackwaterveg"><img src="https://avatars.githubusercontent.com/u/87408988?v=4" width=75 height=75></a>
<a href="https://github.com/yt605155624"><img src="https://avatars.githubusercontent.com/u/24568452?v=4" width=75 height=75></a>
<a href="https://github.com/kuke"><img src="https://avatars.githubusercontent.com/u/3064195?v=4" width=75 height=75></a>
<a href="https://github.com/xinghai-sun"><img src="https://avatars.githubusercontent.com/u/7038341?v=4" width=75 height=75></a>
<a href="https://github.com/pkuyym"><img src="https://avatars.githubusercontent.com/u/5782283?v=4" width=75 height=75></a>
<a href="https://github.com/KPatr1ck"><img src="https://avatars.githubusercontent.com/u/22954146?v=4" width=75 height=75></a>
<a href="https://github.com/LittleChenCc"><img src="https://avatars.githubusercontent.com/u/10339970?v=4" width=75 height=75></a>
<a href="https://github.com/745165806"><img src="https://avatars.githubusercontent.com/u/20623194?v=4" width=75 height=75></a>
<a href="https://github.com/Mingxue-Xu"><img src="https://avatars.githubusercontent.com/u/92848346?v=4" width=75 height=75></a>
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<a href="https://github.com/lfchener"><img src="https://avatars.githubusercontent.com/u/6771821?v=4" width=75 height=75></a>
<a href="https://github.com/luotao1"><img src="https://avatars.githubusercontent.com/u/6836917?v=4" width=75 height=75></a>
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<a href="https://github.com/iclementine"><img src="https://avatars.githubusercontent.com/u/16222986?v=4" width=75 height=75></a>
<a href="https://github.com/ZeyuChen"><img src="https://avatars.githubusercontent.com/u/1371212?v=4" width=75 height=75></a>
<a href="https://github.com/AK391"><img src="https://avatars.githubusercontent.com/u/81195143?v=4" width=75 height=75></a>
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<a href="https://github.com/jiqiren11"><img src="https://avatars.githubusercontent.com/u/82639260?v=4" width=75 height=75></a>
<a href="https://github.com/AshishKarel"><img src="https://avatars.githubusercontent.com/u/58069375?v=4" width=75 height=75></a>
<a href="https://github.com/chesterkuo"><img src="https://avatars.githubusercontent.com/u/6285069?v=4" width=75 height=75></a>
<a href="https://github.com/tensor-tang"><img src="https://avatars.githubusercontent.com/u/21351065?v=4" width=75 height=75></a>
<a href="https://github.com/hysunflower"><img src="https://avatars.githubusercontent.com/u/52739577?v=4" width=75 height=75></a>  
<a href="https://github.com/wwhu"><img src="https://avatars.githubusercontent.com/u/6081200?v=4" width=75 height=75></a>
<a href="https://github.com/lispc"><img src="https://avatars.githubusercontent.com/u/2833376?v=4" width=75 height=75></a>
<a href="https://github.com/jerryuhoo"><img src="https://avatars.githubusercontent.com/u/24245709?v=4" width=75 height=75></a>
<a href="https://github.com/harisankarh"><img src="https://avatars.githubusercontent.com/u/1307053?v=4" width=75 height=75></a>
<a href="https://github.com/Jackiexiao"><img src="https://avatars.githubusercontent.com/u/18050469?v=4" width=75 height=75></a>
<a href="https://github.com/limpidezza"><img src="https://avatars.githubusercontent.com/u/71760778?v=4" width=75 height=75></a>
</p>

## 致谢

- 非常感谢 [yeyupiaoling](https://github.com/yeyupiaoling) 多年来的关注和建议，以及在诸多问题上的帮助。
- 非常感谢 [AK391](https://github.com/AK391) 在 Huggingface Spaces 上使用 Gradio 对我们的语音合成功能进行网页版演示。

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)。

## License

PaddleSpeech 在 [Apache-2.0 许可](./LICENSE) 下提供。