(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="#quick-start-server"> 快速使用服务 </a>
  | <a href="#documents"> 教程文档 </a>
  | <a href="#model-list"> 模型列表 </a>
</div>

------------------------------------------------------------------------------------
<p align="center">
    <a href="./LICENSE"><img src="https://img.shields.io/badge/license-Apache%202-red.svg"></a>
    <a href="support os"><img src="https://img.shields.io/badge/os-linux-yellow.svg"></a>
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    <a href="https://huggingface.co/spaces"><img src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue"></a>
</p>

<!---
from https://github.com/18F/open-source-guide/blob/18f-pages/pages/making-readmes-readable.md
1.What is this repo or project? (You can reuse the repo description you used earlier because this section doesn’t have to be long.)
2.How does it work?
3.Who will use this repo or project?
4.What is the goal of this project?
-->

**PaddleSpeech** 是基于飞桨 [PaddlePaddle](https://github.com/PaddlePaddle/Paddle) 的语音方向的开源模型库，用于语音和音频中的各种关键任务的开发，包含大量基于深度学习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>

##### 语音合成
<div align = "center">
<table style="width:100%">
  <thead>
    <tr>
      <th width="550">输入文本</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/tacotron2_ljspeech_waveflow_samples_0.2/sentence_1.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>
    <tr>
      <td >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》。</td>
      <td align = "center">
      <a href="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/jijiji.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)。

##### 标点恢复
<div align = "center">
<table style="width:100%">
  <thead>
    <tr>
      <th width="390"> 输入文本 </th>
      <th width="390"> 输出文本 </th>
    </tr>
  </thead>
  <tbody>
   <tr>
      <td>今天的天气真不错啊你下午有空吗我想约你一起去吃饭</td>
      <td>今天的天气真不错啊！你下午有空吗？我想约你一起去吃饭。</td>
    </tr>
  </tbody>
</table>

</div>

### ⭐ 应用案例
- **[PaddleBoBo](https://github.com/JiehangXie/PaddleBoBo): 使用 PaddleSpeech 的语音合成模块生成虚拟人的声音。**
  
<div align="center"><a href="https://www.bilibili.com/video/BV1cL411V71o?share_source=copy_web"><img src="https://ai-studio-static-online.cdn.bcebos.com/06fd746ab32042f398fb6f33f873e6869e846fe63c214596ae37860fe8103720" / width="500px"></a></div>

- [PaddleSpeech 示例视频](https://paddlespeech.readthedocs.io/en/latest/demo_video.html)


- **[VTuberTalk](https://github.com/jerryuhoo/VTuberTalk): 使用 PaddleSpeech 的语音合成和语音识别从视频中克隆人声。**

<div align="center">
<img src="https://raw.githubusercontent.com/jerryuhoo/VTuberTalk/main/gui/gui.png"  width = "500px"  />
</div>

### 🔥 热门活动

- 2021.12.21~12.24

  4 日直播课: 深度解读 PaddleSpeech 语音技术!

  **直播回放与课件资料: https://aistudio.baidu.com/aistudio/education/group/info/25130**
### 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).
--->
- 👏🏻 2022.03.28: PaddleSpeech Server 上线! 覆盖了声音分类、语音识别、以及语音合成。
- 👏🏻 2022.03.28: PaddleSpeech CLI 上线声纹验证。
- 🤗  2021.12.14: Our PaddleSpeech [ASR](https://huggingface.co/spaces/KPatrick/PaddleSpeechASR) and [TTS](https://huggingface.co/spaces/KPatrick/PaddleSpeechTTS) Demos on Hugging Face Spaces are available!
- 👏🏻 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。

### 技术交流群
微信扫描二维码（好友申请通过后回复【语音】）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。

<div align="center">
<img src="https://raw.githubusercontent.com/yt605155624/lanceTest/main/images/wechat_4.jpg"  width = "300"  />
</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。
目前为止，**Linux** 支持声音分类、语音识别、语音合成和语音翻译四种功能，**Mac OSX、 Windows** 下暂不支持语音翻译功能。 想了解具体安装细节，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
```
**声纹识别**
```shell
paddlespeech vector --task spk --input input_16k.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
```
- 语音合成的 web demo 已经集成进了 [Huggingface Spaces](https://huggingface.co/spaces). 请参考: [TTS Demo](https://huggingface.co/spaces/akhaliq/paddlespeech)

**文本后处理** 
 - 标点恢复
   ```bash
   paddlespeech text --task punc --input 今天的天气真不错啊你下午有空吗我想约你一起去吃饭
   ```

**批处理**
```
echo -e "1 欢迎光临。\n2 谢谢惠顾。" | paddlespeech tts
```  

**Shell管道**
ASR + Punc:
```
paddlespeech asr --input ./zh.wav | paddlespeech text --task punc
```

更多命令行命令请参考 [demos](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/demos)
> 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)。


## 快速使用服务
安装完成后，开发者可以通过命令行快速使用服务。

**启动服务**     
```shell
paddlespeech_server start --config_file ./paddlespeech/server/conf/application.yaml
```

**访问语音识别服务**     
```shell
paddlespeech_client asr --server_ip 127.0.0.1 --port 8090 --input input_16k.wav
```

**访问语音合成服务**     
```shell
paddlespeech_client tts --server_ip 127.0.0.1 --port 8090 --input "您好，欢迎使用百度飞桨语音合成服务。" --output output.wav
```

**访问音频分类服务**     
```shell
paddlespeech_client cls --server_ip 127.0.0.1 --port 8090 --input input.wav
```

更多服务相关的命令行使用信息，请参考 [demos](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/demos/speech_server)


## 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)。

PaddleSpeech 的 **语音转文本** 包含语音识别声学模型、语音识别语言模型和语音翻译, 详情如下：

<table style="width:100%">
  <thead>
    <tr>
      <th>语音转文本模块类型</th>
      <th>数据集</th>
      <th>模型种类</th>
      <th>链接</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td rowspan="4">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>Transformer based Attention Models </td>
      <td>
      <a href = "./examples/aishell/asr1">u2.transformer.conformer-aishell</a>
      </td>
    </tr>
      <tr>
      <td> Librispeech</td>
      <td>Transformer based Attention Models </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>TIMIT</td>
      <td>Unified Streaming & Non-streaming Two-pass</td>
      <td>
    <a href = "./examples/timit/asr1"> u2-timit</a>
      </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="1">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 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>

<a name="语音合成模型"></a>
PaddleSpeech 的 **语音合成** 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> 语音合成模块类型 </th>
      <th> 模型种类 </th>
      <th> 数据集  </th>
      <th> 链接  </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>LJSpeech / CSMSC</td>
      <td>
      <a href = "./examples/ljspeech/tts0">tacotron2-ljspeech</a> / <a href = "./examples/csmsc/tts0">tacotron2-csmsc</a>
      </td>
    </tr>
    <tr>
      <td>Transformer TTS</td>
      <td>LJSpeech</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>LJSpeech / VCTK / CSMSC / AISHELL-3</td>
      <td>
      <a href = "./examples/ljspeech/tts3">fastspeech2-ljspeech</a> / <a href = "./examples/vctk/tts3">fastspeech2-vctk</a> / <a href = "./examples/csmsc/tts3">fastspeech2-csmsc</a> / <a href = "./examples/aishell3/tts3">fastspeech2-aishell3</a>
      </td>
    </tr>
   <tr>
      <td rowspan="6">声码器</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 / AISHELL-3</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> /  <a href = "./examples/aishell3/voc1">PWGAN-aishell3</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 >Style MelGAN</td>
      <td >CSMSC</td>
      <td>
      <a href = "./examples/csmsc/voc4">Style MelGAN-csmsc</a> 
      </td>
    </tr>
    <tr>
      <td >HiFiGAN</td>
      <td >LJSpeech / VCTK / CSMSC / AISHELL-3</td>
      <td>
      <a href = "./examples/ljspeech/voc5">HiFiGAN-ljspeech</a> / <a href = "./examples/vctk/voc5">HiFiGAN-vctk</a> / <a href = "./examples/csmsc/voc5">HiFiGAN-csmsc</a> / <a href = "./examples/aishell3/voc5">HiFiGAN-aishell3</a>
      </td>
    </tr>
    <tr>
      <td >WaveRNN</td>
      <td >CSMSC</td>
      <td>
      <a href = "./examples/csmsc/voc6">WaveRNN-csmsc</a>
      </td>
    </tr>
    <tr>
      <td rowspan="3">声音克隆</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>

<a name="声音分类模型"></a>
**声音分类**

<table style="width:100%">
  <thead>
    <tr>
      <th> 任务 </th>
      <th> 数据集 </th>
      <th> 模型种类 </th>
      <th> 链接</th>
    </tr>
  </thead>
  <tbody>
  <tr>
      <td>声音分类</td>
      <td>ESC-50</td>
      <td>PANN</td>
      <td>
      <a href = "./examples/esc50/cls0">pann-esc50</a>
      </td>
    </tr>
  </tbody>
</table>


**声纹识别**

<table style="width:100%">
  <thead>
    <tr>
      <th> Task </th>
      <th> Dataset </th>
      <th> Model Type </th>
      <th> Link </th>
    </tr>
  </thead>
  <tbody>
  <tr>
      <td>Speaker Verification</td>
      <td>VoxCeleb12</td>
      <td>ECAPA-TDNN</td>
      <td>
      <a href = "./examples/voxceleb/sv0">ecapa-tdnn-voxceleb12</a>
      </td>
    </tr>
  </tbody>
</table>

**标点恢复**

<table style="width:100%">
  <thead>
    <tr>
      <th> 任务 </th>
      <th> 数据集 </th>
      <th> 模型种类 </th>
      <th> 链接 </th>
    </tr>
  </thead>
  <tbody>
  <tr>
      <td>标点恢复</td>
      <td>IWLST2012_zh</td>
      <td>Ernie Linear</td>
      <td>
      <a href = "./examples/iwslt2012/punc0">iwslt2012-punc0</a>
      </td>
    </tr>
  </tbody>
</table>

## 教程文档

对于 PaddleSpeech 的所关注的任务，以下指南有助于帮助开发者快速入门，了解语音相关核心思想。

- [下载安装](./docs/source/install_cn.md)
- [快速开始](#快速开始)
- Notebook基础教程
  - [声音分类](./docs/tutorial/cls/cls_tutorial.ipynb)
  - [语音识别](./docs/tutorial/asr/tutorial_transformer.ipynb)
  - [语音翻译](./docs/tutorial/st/st_tutorial.ipynb)
  - [声音合成](./docs/tutorial/tts/tts_tutorial.ipynb)
  - [示例Demo](./demos/README.md)
- 进阶文档  
  - [语音识别自定义训练](./docs/source/asr/quick_start.md)
    - [简介](./docs/source/asr/models_introduction.md)
    - [数据准备](./docs/source/asr/data_preparation.md)
    - [Ngram 语言模型](./docs/source/asr/ngram_lm.md)
  - [语音合成自定义训练](./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)
    - [测试语音样本](https://paddlespeech.readthedocs.io/en/latest/tts/demo.html)
  - [声音分类](./demos/audio_tagging/README_cn.md)
  - [声纹识别](./demos/speaker_verification/README_cn.md)
  - [语音翻译](./demos/speech_translation/README_cn.md)
- [模型列表](#模型列表)
  - [语音识别](#语音识别模型)
  - [语音合成](#语音合成模型)
  - [声音分类](#声音分类模型)
- [技术交流群](#技术交流群)
- [欢迎贡献](#欢迎贡献)
- [License](#License)


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。
```text
@misc{ppspeech2021,
title={PaddleSpeech, a toolkit for audio processing based on PaddlePaddle.},
author={PaddlePaddle Authors},
howpublished = {\url{https://github.com/PaddlePaddle/PaddleSpeech}},
year={2021}
}

@inproceedings{zheng2021fused,
  title={Fused acoustic and text encoding for multimodal bilingual pretraining and speech translation},
  author={Zheng, Renjie and Chen, Junkun and Ma, Mingbo and Huang, Liang},
  booktitle={International Conference on Machine Learning},
  pages={12736--12746},
  year={2021},
  organization={PMLR}
}
```

<a name="欢迎贡献"></a>
## 参与 PaddleSpeech 的开发

热烈欢迎您在[Discussions](https://github.com/PaddlePaddle/PaddleSpeech/discussions) 中提交问题，并在[Issues](https://github.com/PaddlePaddle/PaddleSpeech/issues) 中指出发现的 bug。此外，我们非常希望您参与到 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>
<a href="https://github.com/chrisxu2016"><img src="https://avatars.githubusercontent.com/u/18379485?v=4" width=75 height=75></a>
<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>
<a href="https://github.com/wanghaoshuang"><img src="https://avatars.githubusercontent.com/u/7534971?v=4" width=75 height=75></a>
<a href="https://github.com/gongel"><img src="https://avatars.githubusercontent.com/u/24390500?v=4" width=75 height=75></a>
<a href="https://github.com/mmglove"><img src="https://avatars.githubusercontent.com/u/38800877?v=4" width=75 height=75></a>
<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>
<a href="https://github.com/qingqing01"><img src="https://avatars.githubusercontent.com/u/7845005?v=4" width=75 height=75></a>
<a href="https://github.com/ericxk"><img src="https://avatars.githubusercontent.com/u/4719594?v=4" width=75 height=75></a>
<a href="https://github.com/kvinwang"><img src="https://avatars.githubusercontent.com/u/6442159?v=4" width=75 height=75></a>
<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)/[PPASR](https://github.com/yeyupiaoling/PPASR)/[PaddlePaddle-DeepSpeech](https://github.com/yeyupiaoling/PaddlePaddle-DeepSpeech)/[VoiceprintRecognition-PaddlePaddle](https://github.com/yeyupiaoling/VoiceprintRecognition-PaddlePaddle)/[AudioClassification-PaddlePaddle](https://github.com/yeyupiaoling/AudioClassification-PaddlePaddle) 多年来的关注和建议，以及在诸多问题上的帮助。
- 非常感谢 [mymagicpower](https://github.com/mymagicpower) 采用PaddleSpeech 对 ASR 的[短语音](https://github.com/mymagicpower/AIAS/tree/main/3_audio_sdks/asr_sdk)及[长语音](https://github.com/mymagicpower/AIAS/tree/main/3_audio_sdks/asr_long_audio_sdk)进行 Java 实现。
- 非常感谢 [JiehangXie](https://github.com/JiehangXie)/[PaddleBoBo](https://github.com/JiehangXie/PaddleBoBo) 采用 PaddleSpeech 语音合成功能实现 Virtual Uploader(VUP)/Virtual YouTuber(VTuber) 虚拟主播。
- 非常感谢 [745165806](https://github.com/745165806)/[PaddleSpeechTask](https://github.com/745165806/PaddleSpeechTask) 贡献标点重建相关模型。
- 非常感谢 [kslz](https://github.com/kslz) 补充中文文档。
- 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。

  
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。
