You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
PaddleSpeech/README_cn.md

958 lines
41 KiB

This file contains ambiguous Unicode characters!

This file contains ambiguous Unicode characters that may be confused with others in your current locale. If your use case is intentional and legitimate, you can safely ignore this warning. Use the Escape button to highlight these characters.

(简体中文|[English](./README.md))
<p align="center">
<img src="./docs/images/PaddleSpeech_logo.png" />
</p>
<p align="center">
<a href="./LICENSE"><img src="https://img.shields.io/badge/license-Apache%202-red.svg"></a>
<a href="https://github.com/PaddlePaddle/PaddleSpeech/releases"><img src="https://img.shields.io/github/v/release/PaddlePaddle/PaddleSpeech?color=ffa"></a>
<a href="support os"><img src="https://img.shields.io/badge/os-linux%2C%20win%2C%20mac-pink.svg"></a>
<a href=""><img src="https://img.shields.io/badge/python-3.7+-aff.svg"></a>
<a href="https://github.com/PaddlePaddle/PaddleSpeech/graphs/contributors"><img src="https://img.shields.io/github/contributors/PaddlePaddle/PaddleSpeech?color=9ea"></a>
<a href="https://github.com/PaddlePaddle/PaddleSpeech/commits"><img src="https://img.shields.io/github/commit-activity/m/PaddlePaddle/PaddleSpeech?color=3af"></a>
<a href="https://github.com/PaddlePaddle/PaddleSpeech/issues"><img src="https://img.shields.io/github/issues/PaddlePaddle/PaddleSpeech?color=9cc"></a>
<a href="https://github.com/PaddlePaddle/PaddleSpeech/stargazers"><img src="https://img.shields.io/github/stars/PaddlePaddle/PaddleSpeech?color=ccf"></a>
<a href="=https://pypi.org/project/paddlespeech/"><img src="https://img.shields.io/pypi/dm/PaddleSpeech"></a>
<a href="=https://pypi.org/project/paddlespeech/"><img src="https://static.pepy.tech/badge/paddlespeech"></a>
<a href="https://huggingface.co/spaces"><img src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue"></a>
</p>
<div align="center">
<h4>
<a href="#安装"> 安装 </a>
| <a href="#快速开始"> 快速开始 </a>
| <a href="#教程文档"> 教程文档 </a>
| <a href="#模型列表"> 模型列表 </a>
| <a href="https://aistudio.baidu.com/aistudio/education/group/info/25130"> AIStudio 课程 </a>
| <a href="https://arxiv.org/abs/2205.12007"> NAACL2022 论文 </a>
| <a href="https://gitee.com/paddlepaddle/PaddleSpeech"> Gitee
</h4>
</div>
------------------------------------------------------------------------------------
**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:
**PaddleSpeech** 荣获 [NAACL2022 Best Demo Award](https://2022.naacl.org/blog/best-demo-award/), 请访问 [Arxiv](https://arxiv.org/abs/2205.12007) 论文。
### 效果展示
##### 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>
### 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。
- 🏆 **流式 ASR 和 TTS 系统**:工业级的端到端流式识别、流式合成系统。
- 💯 **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、声纹识别、KWS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。
### 近期活动
❗️重磅❗️飞桨智慧金融行业系列直播课
✅ 覆盖智能风控、智能运维、智能营销、智能客服四大金融主流场景
📆 9月6日-9月29日每周二、四19:00
+ 智慧金融行业深入洞察
+ 8节理论+实践精品直播课
+ 10+真实产业场景范例教学及实践
+ 更有免费算力+结业证书等礼品等你来拿
扫码报名码住直播链接,与行业精英深度交流
<div align="center">
<img src="https://user-images.githubusercontent.com/30135920/188431897-a02f028f-dd13-41e8-8ff6-749468cdc850.jpg" width = "200" />
</div>
### 近期更新
- 🔥 2022.09.26: 新增 Voice Cloning, TTS finetune 和 ERNIE-SAT 到 [PaddleSpeech 网页应用](./demos/speech_web)。
- ⚡ 2022.09.09: 新增基于 ECAPA-TDNN 声纹模型的 AISHELL-3 Voice Cloning [示例](./examples/aishell3/vc2)。
- ⚡ 2022.08.25: 发布 TTS [finetune](./examples/other/tts_finetune/tts3) 示例。
- 🔥 2022.08.22: 新增 ERNIE-SAT 模型: [ERNIE-SAT-vctk](./examples/vctk/ernie_sat)、[ERNIE-SAT-aishell3](./examples/aishell3/ernie_sat)、[ERNIE-SAT-zh_en](./examples/aishell3_vctk/ernie_sat)。
- 🔥 2022.08.15: 将 [g2pW](https://github.com/GitYCC/g2pW) 引入 TTS 中文文本前端。
- 🔥 2022.08.09: 发布[中英文混合 TTS](./examples/zh_en_tts/tts3)。
- ⚡ 2022.08.03: TTS CLI 新增 ONNXRuntime 推理方式。
- 🎉 2022.07.18: 发布 VITS 模型: [VITS-csmsc](./examples/csmsc/vits)、[VITS-aishell3](./examples/aishell3/vits)、[VITS-VC](./examples/aishell3/vits-vc)。
- 🎉 2022.06.22: 所有 TTS 模型支持了 ONNX 格式。
- 🍀 2022.06.17: 新增 [PaddleSpeech 网页应用](./demos/speech_web)。
- 👑 2022.05.13: PaddleSpeech 发布 [PP-ASR](./docs/source/asr/PPASR_cn.md) 流式语音识别系统、[PP-TTS](./docs/source/tts/PPTTS_cn.md) 流式语音合成系统、[PP-VPR](docs/source/vpr/PPVPR_cn.md) 全链路声纹识别系统
- 👏🏻 2022.05.06: PaddleSpeech Streaming Server 上线!覆盖了语音识别(标点恢复、时间戳)和语音合成。
- 👏🏻 2022.05.06: PaddleSpeech Server 上线!覆盖了声音分类、语音识别、语音合成、声纹识别,标点恢复。
- 👏🏻 2022.03.28: PaddleSpeech CLI 覆盖声音分类、语音识别、语音翻译(英译中)、语音合成和声纹验证。
- 🤗 2021.12.14: PaddleSpeech [ASR](https://huggingface.co/spaces/KPatrick/PaddleSpeechASR) 和 [TTS](https://huggingface.co/spaces/KPatrick/PaddleSpeechTTS) 可在 Hugging Face Spaces 上体验!
- 👏🏻 2021.12.10: PaddleSpeech CLI 支持语音分类, 语音识别, 语音翻译(英译中)和语音合成。
### 🔥 加入技术交流群获取入群福利
- 3 日直播课链接: 深度解读 PP-TTS、PP-ASR、PP-VPR 三项核心语音系统关键技术
- 20G 学习大礼包:视频课程、前沿论文与学习资料
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。
<div align="center">
<img src="https://user-images.githubusercontent.com/23690325/169763015-cbd8e28d-602c-4723-810d-dbc6da49441e.jpg" width = "200" />
</div>
<a name="安装"></a>
## 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。
### 相关依赖
+ gcc >= 4.8.5
+ paddlepaddle >= 2.3.1
+ python >= 3.7
+ linux(推荐), mac, windows
PaddleSpeech 依赖于 paddlepaddle安装可以参考[ paddlepaddle 官网](https://www.paddlepaddle.org.cn/),根据自己机器的情况进行选择。这里给出 cpu 版本示例,其它版本大家可以根据自己机器的情况进行安装。
```shell
pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple
```
PaddleSpeech 快速安装方式有两种,一种是 pip 安装,一种是源码编译(推荐)。
### pip 安装
```shell
pip install pytest-runner
pip install paddlespeech
```
### 源码编译
```shell
git clone https://github.com/PaddlePaddle/PaddleSpeech.git
cd PaddleSpeech
pip install pytest-runner
pip install .
```
更多关于安装问题,如 conda 环境librosa 依赖的系统库gcc 环境问题kaldi 安装等,可以参考这篇[安装文档](docs/source/install_cn.md),如安装上遇到问题可以在 [#2150](https://github.com/PaddlePaddle/PaddleSpeech/issues/2150) 上留言以及查找相关问题
<a name="快速开始"></a>
## 快速开始
安装完成后,开发者可以通过命令行或者 Python 快速开始,命令行模式下改变 `--input` 可以尝试用自己的音频或文本测试,支持 16k wav 格式音频。
你也可以在 `aistudio` 中快速体验 👉🏻[一键预测,快速上手 Speech 开发任务](https://aistudio.baidu.com/aistudio/projectdetail/4353348?sUid=2470186&shared=1&ts=1660878142250)。
测试音频示例下载
```shell
wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav
wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/en.wav
```
### 语音识别
<details><summary>&emsp;(点击可展开)开源中文语音识别</summary>
命令行一键体验
```shell
paddlespeech asr --lang zh --input zh.wav
```
Python API 一键预测
```python
>>> from paddlespeech.cli.asr.infer import ASRExecutor
>>> asr = ASRExecutor()
>>> result = asr(audio_file="zh.wav")
>>> print(result)
我认为跑步最重要的就是给我带来了身体健康
```
</details>
### 语音合成
<details><summary>&emsp;开源中文语音合成</summary>
输出 24k 采样率wav格式音频
命令行一键体验
```shell
paddlespeech tts --input "你好,欢迎使用百度飞桨深度学习框架!" --output output.wav
```
Python API 一键预测
```python
>>> from paddlespeech.cli.tts.infer import TTSExecutor
>>> tts = TTSExecutor()
>>> tts(text="今天天气十分不错。", 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/KPatrick/PaddleSpeechTTS)
</details>
### 声音分类
<details><summary>&emsp;适配多场景的开放领域声音分类工具</summary>
基于 AudioSet 数据集 527 个类别的声音分类模型
命令行一键体验
```shell
paddlespeech cls --input zh.wav
```
python API 一键预测
```python
>>> from paddlespeech.cli.cls.infer import CLSExecutor
>>> cls = CLSExecutor()
>>> result = cls(audio_file="zh.wav")
>>> print(result)
Speech 0.9027186632156372
```
</details>
### 声纹提取
<details><summary>&emsp;工业级声纹提取工具</summary>
命令行一键体验
```shell
paddlespeech vector --task spk --input zh.wav
```
Python API 一键预测
```python
>>> from paddlespeech.cli.vector import VectorExecutor
>>> vec = VectorExecutor()
>>> result = vec(audio_file="zh.wav")
>>> print(result) # 187维向量
[ -0.19083306 9.474295 -14.122263 -2.0916545 0.04848729
4.9295826 1.4780062 0.3733844 10.695862 3.2697146
-4.48199 -0.6617882 -9.170393 -11.1568775 -1.2358263 ...]
```
</details>
### 标点恢复
<details><summary>&emsp;一键恢复文本标点可与ASR模型配合使用</summary>
命令行一键体验
```shell
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
```
Python API 一键预测
```python
>>> from paddlespeech.cli.text.infer import TextExecutor
>>> text_punc = TextExecutor()
>>> result = text_punc(text="今天的天气真不错啊你下午有空吗我想约你一起去吃饭")
今天的天气真不错啊你下午有空吗我想约你一起去吃饭
```
</details>
### 语音翻译
<details><summary>&emsp;端到端英译中语音翻译工具</summary>
使用预编译的 kaldi 相关工具,只支持在 Ubuntu 系统中体验
命令行一键体验
```shell
paddlespeech st --input en.wav
```
python API 一键预测
```python
>>> from paddlespeech.cli.st.infer import STExecutor
>>> st = STExecutor()
>>> result = st(audio_file="en.wav")
['我 在 这栋 建筑 的 古老 门上 敲门 。']
```
</details>
<a name="快速使用服务"></a>
## 快速使用服务
安装完成后,开发者可以通过命令行一键启动语音识别,语音合成,音频分类等多种服务。
你可以在 AI Studio 中快速体验:[SpeechServer 一键部署](https://aistudio.baidu.com/aistudio/projectdetail/4354592?sUid=2470186&shared=1&ts=1660878208266)
**启动服务**
```shell
paddlespeech_server start --config_file ./demos/speech_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)
<a name="快速使用流式服务"></a>
## 快速使用流式服务
开发者可以尝试 [流式 ASR](./demos/streaming_asr_server/README.md) 和 [流式 TTS](./demos/streaming_tts_server/README.md) 服务.
**启动流式 ASR 服务**
```
paddlespeech_server start --config_file ./demos/streaming_asr_server/conf/application.yaml
```
**访问流式 ASR 服务**
```
paddlespeech_client asr_online --server_ip 127.0.0.1 --port 8090 --input input_16k.wav
```
**启动流式 TTS 服务**
```
paddlespeech_server start --config_file ./demos/streaming_tts_server/conf/tts_online_application.yaml
```
**访问流式 TTS 服务**
```
paddlespeech_client tts_online --server_ip 127.0.0.1 --port 8092 --protocol http --input "您好,欢迎使用百度飞桨语音合成服务。" --output output.wav
```
更多信息参看: [流式 ASR](./demos/streaming_asr_server/README.md) 和 [流式 TTS](./demos/streaming_tts_server/README.md)
<a name="模型列表"></a>
## 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)。
<a name="语音识别模型"></a>
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>模型类型</th>
<th>脚本</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> 模型类型 </th>
<th> 数据集 </th>
<th> 脚本 </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="5">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 / ZH_EN / finetune</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> / <a href = "./examples/zh_en_tts/tts3">fastspeech2-zh_en</a> / <a href = "./examples/other/tts_finetune/tts3">fastspeech2-finetune</a>
</td>
</tr>
<tr>
<td>ERNIE-SAT</td>
<td>VCTK / AISHELL-3 / ZH_EN</td>
<td>
<a href = "./examples/vctk/ernie_sat">ERNIE-SAT-vctk</a> / <a href = "./examples/aishell3/ernie_sat">ERNIE-SAT-aishell3</a> / <a href = "./examples/aishell3_vctk/ernie_sat">ERNIE-SAT-zh_en</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="5">声音克隆</td>
<td>GE2E</td>
<td >Librispeech, etc.</td>
<td>
<a href = "./examples/other/ge2e">GE2E</a>
</td>
</tr>
<tr>
<td>SV2TTS (GE2E + Tacotron2)</td>
<td>AISHELL-3</td>
<td>
<a href = "./examples/aishell3/vc0">VC0</a>
</td>
</tr>
<tr>
<td>SV2TTS (GE2E + FastSpeech2)</td>
<td>AISHELL-3</td>
<td>
<a href = "./examples/aishell3/vc1">VC1</a>
</td>
</tr>
<tr>
<td>SV2TTS (ECAPA-TDNN + FastSpeech2)</td>
<td>AISHELL-3</td>
<td>
<a href = "./examples/aishell3/vc2">VC2</a>
</td>
</tr>
<tr>
<td>GE2E + VITS</td>
<td>AISHELL-3</td>
<td>
<a href = "./examples/aishell3/vits-vc">VITS-VC</a>
</td>
</tr>
<tr>
<td rowspan="3">端到端</td>
<td>VITS</td>
<td>CSMSC / AISHELL-3</td>
<td>
<a href = "./examples/csmsc/vits">VITS-csmsc</a> / <a href = "./examples/aishell3/vits">VITS-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> 模型类型 </th>
<th> 脚本</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>
<a name="声纹识别模型"></a>
**声纹识别**
<table style="width:100%">
<thead>
<tr>
<th> 任务 </th>
<th> 数据集 </th>
<th> 模型类型 </th>
<th> 脚本 </th>
</tr>
</thead>
<tbody>
<tr>
<td>声纹识别</td>
<td>VoxCeleb1/2</td>
<td>ECAPA-TDNN</td>
<td>
<a href = "./examples/voxceleb/sv0">ecapa-tdnn-voxceleb12</a>
</td>
</tr>
</tbody>
</table>
<a name="说话人日志模型"></a>
**说话人日志**
<table style="width:100%">
<thead>
<tr>
<th> 任务 </th>
<th> 数据集 </th>
<th> 模型类型 </th>
<th> 脚本 </th>
</tr>
</thead>
<tbody>
<tr>
<td>说话人日志</td>
<td>AMI</td>
<td>ECAPA-TDNN + AHC / SC</td>
<td>
<a href = "./examples/ami/sd0">ecapa-tdnn-ami</a>
</td>
</tr>
</tbody>
</table>
<a name="标点恢复模型"></a>
**标点恢复**
<table style="width:100%">
<thead>
<tr>
<th> 任务 </th>
<th> 数据集 </th>
<th> 模型类型 </th>
<th> 脚本 </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>
<a name="教程文档"></a>
## 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)
- 声纹识别
- [声纹识别](./demos/speaker_verification/README_cn.md)
- [音频检索](./demos/audio_searching/README_cn.md)
- [声音分类](./demos/audio_tagging/README_cn.md)
- [语音翻译](./demos/speech_translation/README_cn.md)
- [服务化部署](./demos/speech_server/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)
- [声纹识别](#声纹识别模型)
- [说话人日志](#说话人日志模型)
- [标点恢复](#标点恢复模型)
- [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。
## ⭐ 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>
## 引用
要引用 PaddleSpeech 进行研究,请使用以下格式进行引用。
```text
@inproceedings{zhang2022paddlespeech,
title = {PaddleSpeech: An Easy-to-Use All-in-One Speech Toolkit},
author = {Hui Zhang, Tian Yuan, Junkun Chen, Xintong Li, Renjie Zheng, Yuxin Huang, Xiaojie Chen, Enlei Gong, Zeyu Chen, Xiaoguang Hu, dianhai yu, Yanjun Ma, Liang Huang},
booktitle = {Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demonstrations},
year = {2022},
publisher = {Association for Computational Linguistics},
}
@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?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/Jackwaterveg"><img src="https://avatars.githubusercontent.com/u/87408988?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/yt605155624"><img src="https://avatars.githubusercontent.com/u/24568452?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/Honei"><img src="https://avatars.githubusercontent.com/u/11361692?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/KPatr1ck"><img src="https://avatars.githubusercontent.com/u/22954146?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/kuke"><img src="https://avatars.githubusercontent.com/u/3064195?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/lym0302"><img src="https://avatars.githubusercontent.com/u/34430015?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/SmileGoat"><img src="https://avatars.githubusercontent.com/u/56786796?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/xinghai-sun"><img src="https://avatars.githubusercontent.com/u/7038341?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/pkuyym"><img src="https://avatars.githubusercontent.com/u/5782283?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/LittleChenCc"><img src="https://avatars.githubusercontent.com/u/10339970?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/qingen"><img src="https://avatars.githubusercontent.com/u/3139179?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/D-DanielYang"><img src="https://avatars.githubusercontent.com/u/23690325?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/Mingxue-Xu"><img src="https://avatars.githubusercontent.com/u/92848346?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/745165806"><img src="https://avatars.githubusercontent.com/u/20623194?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/jerryuhoo"><img src="https://avatars.githubusercontent.com/u/24245709?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/WilliamZhang06"><img src="https://avatars.githubusercontent.com/u/97937340?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/chrisxu2016"><img src="https://avatars.githubusercontent.com/u/18379485?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/iftaken"><img src="https://avatars.githubusercontent.com/u/30135920?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/lfchener"><img src="https://avatars.githubusercontent.com/u/6771821?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/BarryKCL"><img src="https://avatars.githubusercontent.com/u/48039828?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/mmglove"><img src="https://avatars.githubusercontent.com/u/38800877?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/gongel"><img src="https://avatars.githubusercontent.com/u/24390500?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/luotao1"><img src="https://avatars.githubusercontent.com/u/6836917?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/wanghaoshuang"><img src="https://avatars.githubusercontent.com/u/7534971?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/kslz"><img src="https://avatars.githubusercontent.com/u/54951765?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/JiehangXie"><img src="https://avatars.githubusercontent.com/u/51190264?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/david-95"><img src="https://avatars.githubusercontent.com/u/15189190?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/THUzyt21"><img src="https://avatars.githubusercontent.com/u/91456992?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/buchongyu2"><img src="https://avatars.githubusercontent.com/u/29157444?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/iclementine"><img src="https://avatars.githubusercontent.com/u/16222986?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/phecda-xu"><img src="https://avatars.githubusercontent.com/u/46859427?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/freeliuzc"><img src="https://avatars.githubusercontent.com/u/23568094?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/ZeyuChen"><img src="https://avatars.githubusercontent.com/u/1371212?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/ccrrong"><img src="https://avatars.githubusercontent.com/u/101700995?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/AK391"><img src="https://avatars.githubusercontent.com/u/81195143?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/qingqing01"><img src="https://avatars.githubusercontent.com/u/7845005?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/0x45f"><img src="https://avatars.githubusercontent.com/u/23097963?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/vpegasus"><img src="https://avatars.githubusercontent.com/u/22723154?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/ericxk"><img src="https://avatars.githubusercontent.com/u/4719594?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/Betterman-qs"><img src="https://avatars.githubusercontent.com/u/61459181?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/sneaxiy"><img src="https://avatars.githubusercontent.com/u/32832641?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/Doubledongli"><img src="https://avatars.githubusercontent.com/u/20540661?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/apps/dependabot"><img src="https://avatars.githubusercontent.com/in/29110?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/kvinwang"><img src="https://avatars.githubusercontent.com/u/6442159?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/chenkui164"><img src="https://avatars.githubusercontent.com/u/34813030?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/PaddleZhang"><img src="https://avatars.githubusercontent.com/u/97284124?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/billishyahao"><img src="https://avatars.githubusercontent.com/u/96406262?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/BrightXiaoHan"><img src="https://avatars.githubusercontent.com/u/25839309?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/jiqiren11"><img src="https://avatars.githubusercontent.com/u/82639260?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/ryanrussell"><img src="https://avatars.githubusercontent.com/u/523300?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/GT-ZhangAcer"><img src="https://avatars.githubusercontent.com/u/46156734?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/tensor-tang"><img src="https://avatars.githubusercontent.com/u/21351065?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/hysunflower"><img src="https://avatars.githubusercontent.com/u/52739577?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/oyjxer"><img src="https://avatars.githubusercontent.com/u/16233945?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/JamesLim-sy"><img src="https://avatars.githubusercontent.com/u/61349199?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/limpidezza"><img src="https://avatars.githubusercontent.com/u/71760778?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/windstamp"><img src="https://avatars.githubusercontent.com/u/34057289?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/AshishKarel"><img src="https://avatars.githubusercontent.com/u/58069375?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/chesterkuo"><img src="https://avatars.githubusercontent.com/u/6285069?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/YDX-2147483647"><img src="https://avatars.githubusercontent.com/u/73375426?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/AdamBear"><img src="https://avatars.githubusercontent.com/u/2288870?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/wwhu"><img src="https://avatars.githubusercontent.com/u/6081200?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/lispc"><img src="https://avatars.githubusercontent.com/u/2833376?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/harisankarh"><img src="https://avatars.githubusercontent.com/u/1307053?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/pengzhendong"><img src="https://avatars.githubusercontent.com/u/10704539?s=60&v=4" width=75 height=75></a>
<a href="https://github.com/Jackiexiao"><img src="https://avatars.githubusercontent.com/u/18050469?s=60&v=4" width=75 height=75></a>
</p>
## 致谢
- 非常感谢 [HighCWu](https://github.com/HighCWu) 新增 [VITS-aishell3](./examples/aishell3/vits) 和 [VITS-VC](./examples/aishell3/vits-vc) 代码示例。
- 非常感谢 [david-95](https://github.com/david-95) 修复句尾多标点符号出错的问题,贡献补充多条程序和数据。
- 非常感谢 [BarryKCL](https://github.com/BarryKCL) 基于 [G2PW](https://github.com/GitYCC/g2pW) 对 TTS 中文文本前端的优化。
- 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。
- 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。
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。