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(简体中文|[English](./README.md))
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<p align="center">
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<img src="./docs/images/PaddleSpeech_logo.png" />
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</p>
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<p align="center">
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<a href="./LICENSE"><img src="https://img.shields.io/badge/license-Apache%202-red.svg"></a>
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<a href="https://github.com/PaddlePaddle/PaddleSpeech/releases"><img src="https://img.shields.io/github/v/release/PaddlePaddle/PaddleSpeech?color=ffa"></a>
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<a href="support os"><img src="https://img.shields.io/badge/os-linux%2C%20win%2C%20mac-pink.svg"></a>
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<a href=""><img src="https://img.shields.io/badge/python-3.7+-aff.svg"></a>
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<a href="https://github.com/PaddlePaddle/PaddleSpeech/graphs/contributors"><img src="https://img.shields.io/github/contributors/PaddlePaddle/PaddleSpeech?color=9ea"></a>
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<a href="https://github.com/PaddlePaddle/PaddleSpeech/commits"><img src="https://img.shields.io/github/commit-activity/m/PaddlePaddle/PaddleSpeech?color=3af"></a>
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<a href="https://github.com/PaddlePaddle/PaddleSpeech/issues"><img src="https://img.shields.io/github/issues/PaddlePaddle/PaddleSpeech?color=9cc"></a>
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<a href="https://github.com/PaddlePaddle/PaddleSpeech/stargazers"><img src="https://img.shields.io/github/stars/PaddlePaddle/PaddleSpeech?color=ccf"></a>
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<a href="=https://pypi.org/project/paddlespeech/"><img src="https://img.shields.io/pypi/dm/PaddleSpeech"></a>
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<a href="=https://pypi.org/project/paddlespeech/"><img src="https://static.pepy.tech/badge/paddlespeech"></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>
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</p>
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<div align="center">
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<h4>
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<a href="#安装"> 安装 </a>
|
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| <a href="#快速开始"> 快速开始 </a>
|
|
|
| <a href="#快速使用服务"> 快速使用服务 </a>
|
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|
| <a href="#快速使用流式服务"> 快速使用流式服务 </a>
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| <a href="#教程文档"> 教程文档 </a>
|
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|
| <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
|
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</h4>
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</div>
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------------------------------------------------------------------------------------
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|
**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:
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**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。
|
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### 效果展示
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##### 语音识别
|
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|
<div align = "center">
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|
|
<table style="width:100%">
|
|
|
<thead>
|
|
|
<tr>
|
|
|
<th> 输入音频 </th>
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|
<th width="550"> 识别结果 </th>
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|
|
</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>
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|
</td>
|
|
|
<td >I knocked at the door on the ancient side of the building.</td>
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|
|
</tr>
|
|
|
<tr>
|
|
|
<td align = "center">
|
|
|
<a href="https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav" rel="nofollow">
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|
|
<img align="center" src="./docs/images/audio_icon.png" width="200" style="max-width: 100%;"></a><br>
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|
</td>
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|
<td>我认为跑步最重要的就是给我带来了身体健康。</td>
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|
</tr>
|
|
|
</tbody>
|
|
|
</table>
|
|
|
|
|
|
</div>
|
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|
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|
|
##### 语音翻译 (英译中)
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|
|
|
|
<div align = "center">
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|
|
<table style="width:100%">
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|
|
<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。
|
|
|
|
|
|
|
|
|
### 近期更新
|
|
|
|
|
|
- 👑 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,声纹验证。
|
|
|
- 🤗 2021.12.14: PaddleSpeech [ASR](https://huggingface.co/spaces/KPatrick/PaddleSpeechASR) and [TTS](https://huggingface.co/spaces/KPatrick/PaddleSpeechTTS) Demos on Hugging Face Spaces are available!
|
|
|
|
|
|
|
|
|
### 🔥 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> (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> 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> 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> 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> 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> 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 ./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)
|
|
|
|
|
|
<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">   </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 / ZH_EN</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>
|
|
|
</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 + Tacotron2</td>
|
|
|
<td>AISHELL-3</td>
|
|
|
<td>
|
|
|
<a href = "./examples/aishell3/vc0">ge2e-tacotron2-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>
|
|
|
</tr>
|
|
|
<tr>
|
|
|
<td rowspan="3">端到端</td>
|
|
|
<td>VITS</td>
|
|
|
<td >CSMSC</td>
|
|
|
<td>
|
|
|
<a href = "./examples/csmsc/vits">VITS-csmsc</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>Speaker Verification</td>
|
|
|
<td>VoxCeleb12</td>
|
|
|
<td>ECAPA-TDNN</td>
|
|
|
<td>
|
|
|
<a href = "./examples/voxceleb/sv0">ecapa-tdnn-voxceleb12</a>
|
|
|
</td>
|
|
|
</tr>
|
|
|
</tbody>
|
|
|
</table>
|
|
|
|
|
|
<a name="标点恢复模型"></a>
|
|
|
|
|
|
**标点恢复**
|
|
|
|
|
|
<table style="width:100%">
|
|
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<thead>
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<tr>
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<th> 任务 </th>
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<th> 数据集 </th>
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<th> 模型类型 </th>
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<th> 脚本 </th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td>标点恢复</td>
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<td>IWLST2012_zh</td>
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<td>Ernie Linear</td>
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<td>
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<a href = "./examples/iwslt2012/punc0">iwslt2012-punc0</a>
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</td>
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</tr>
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</tbody>
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</table>
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<a name="教程文档"></a>
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## 教程文档
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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。
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- [下载安装](./docs/source/install_cn.md)
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- [快速开始](#快速开始)
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- Notebook基础教程
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- [声音分类](./docs/tutorial/cls/cls_tutorial.ipynb)
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- [语音识别](./docs/tutorial/asr/tutorial_transformer.ipynb)
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- [语音翻译](./docs/tutorial/st/st_tutorial.ipynb)
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- [声音合成](./docs/tutorial/tts/tts_tutorial.ipynb)
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- [示例Demo](./demos/README.md)
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- 进阶文档
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- [语音识别自定义训练](./docs/source/asr/quick_start.md)
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- [简介](./docs/source/asr/models_introduction.md)
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- [数据准备](./docs/source/asr/data_preparation.md)
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- [Ngram 语言模型](./docs/source/asr/ngram_lm.md)
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- [语音合成自定义训练](./docs/source/tts/quick_start.md)
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- [简介](./docs/source/tts/models_introduction.md)
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- [进阶用法](./docs/source/tts/advanced_usage.md)
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- [中文文本前端](./docs/source/tts/zh_text_frontend.md)
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- [测试语音样本](https://paddlespeech.readthedocs.io/en/latest/tts/demo.html)
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- 声纹识别
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- [声纹识别](./demos/speaker_verification/README_cn.md)
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- [音频检索](./demos/audio_searching/README_cn.md)
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- [声音分类](./demos/audio_tagging/README_cn.md)
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- [语音翻译](./demos/speech_translation/README_cn.md)
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- [服务化部署](./demos/speech_server/README_cn.md)
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- [模型列表](#模型列表)
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- [语音识别](#语音识别模型)
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- [语音合成](#语音合成模型)
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- [声音分类](#声音分类模型)
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- [声纹识别](#声纹识别模型)
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- [标点恢复](#标点恢复模型)
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- [技术交流群](#技术交流群)
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- [欢迎贡献](#欢迎贡献)
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- [License](#License)
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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。
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## ⭐ 应用案例
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- **[PaddleBoBo](https://github.com/JiehangXie/PaddleBoBo): 使用 PaddleSpeech 的语音合成模块生成虚拟人的声音。**
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<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>
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- [PaddleSpeech 示例视频](https://paddlespeech.readthedocs.io/en/latest/demo_video.html)
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- **[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。**
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<div align="center">
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<img src="https://raw.githubusercontent.com/jerryuhoo/VTuberTalk/main/gui/gui.png" width = "500px" />
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</div>
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## 引用
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要引用 PaddleSpeech 进行研究,请使用以下格式进行引用。
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```text
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@inproceedings{zhang2022paddlespeech,
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title = {PaddleSpeech: An Easy-to-Use All-in-One Speech Toolkit},
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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},
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booktitle = {Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demonstrations},
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year = {2022},
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publisher = {Association for Computational Linguistics},
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}
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@inproceedings{zheng2021fused,
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title={Fused acoustic and text encoding for multimodal bilingual pretraining and speech translation},
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author={Zheng, Renjie and Chen, Junkun and Ma, Mingbo and Huang, Liang},
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booktitle={International Conference on Machine Learning},
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pages={12736--12746},
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year={2021},
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organization={PMLR}
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}
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```
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<a name="欢迎贡献"></a>
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## 参与 PaddleSpeech 的开发
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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!
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### 贡献者
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<p align="center">
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<a href="https://github.com/zh794390558"><img src="https://avatars.githubusercontent.com/u/3038472?v=4" width=75 height=75></a>
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<a href="https://github.com/Jackwaterveg"><img src="https://avatars.githubusercontent.com/u/87408988?v=4" width=75 height=75></a>
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<a href="https://github.com/yt605155624"><img src="https://avatars.githubusercontent.com/u/24568452?v=4" width=75 height=75></a>
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<a href="https://github.com/kuke"><img src="https://avatars.githubusercontent.com/u/3064195?v=4" width=75 height=75></a>
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<a href="https://github.com/xinghai-sun"><img src="https://avatars.githubusercontent.com/u/7038341?v=4" width=75 height=75></a>
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<a href="https://github.com/pkuyym"><img src="https://avatars.githubusercontent.com/u/5782283?v=4" width=75 height=75></a>
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<a href="https://github.com/KPatr1ck"><img src="https://avatars.githubusercontent.com/u/22954146?v=4" width=75 height=75></a>
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<a href="https://github.com/LittleChenCc"><img src="https://avatars.githubusercontent.com/u/10339970?v=4" width=75 height=75></a>
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<a href="https://github.com/745165806"><img src="https://avatars.githubusercontent.com/u/20623194?v=4" width=75 height=75></a>
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<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/chrisxu2016"><img src="https://avatars.githubusercontent.com/u/18379485?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>
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<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/wanghaoshuang"><img src="https://avatars.githubusercontent.com/u/7534971?v=4" width=75 height=75></a>
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<a href="https://github.com/gongel"><img src="https://avatars.githubusercontent.com/u/24390500?v=4" width=75 height=75></a>
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<a href="https://github.com/mmglove"><img src="https://avatars.githubusercontent.com/u/38800877?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>
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<a href="https://github.com/ZeyuChen"><img src="https://avatars.githubusercontent.com/u/1371212?v=4" width=75 height=75></a>
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<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/qingqing01"><img src="https://avatars.githubusercontent.com/u/7845005?v=4" width=75 height=75></a>
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<a href="https://github.com/ericxk"><img src="https://avatars.githubusercontent.com/u/4719594?v=4" width=75 height=75></a>
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<a href="https://github.com/kvinwang"><img src="https://avatars.githubusercontent.com/u/6442159?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>
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<a href="https://github.com/AshishKarel"><img src="https://avatars.githubusercontent.com/u/58069375?v=4" width=75 height=75></a>
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<a href="https://github.com/chesterkuo"><img src="https://avatars.githubusercontent.com/u/6285069?v=4" width=75 height=75></a>
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<a href="https://github.com/tensor-tang"><img src="https://avatars.githubusercontent.com/u/21351065?v=4" width=75 height=75></a>
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<a href="https://github.com/hysunflower"><img src="https://avatars.githubusercontent.com/u/52739577?v=4" width=75 height=75></a>
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<a href="https://github.com/wwhu"><img src="https://avatars.githubusercontent.com/u/6081200?v=4" width=75 height=75></a>
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<a href="https://github.com/lispc"><img src="https://avatars.githubusercontent.com/u/2833376?v=4" width=75 height=75></a>
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<a href="https://github.com/jerryuhoo"><img src="https://avatars.githubusercontent.com/u/24245709?v=4" width=75 height=75></a>
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<a href="https://github.com/harisankarh"><img src="https://avatars.githubusercontent.com/u/1307053?v=4" width=75 height=75></a>
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<a href="https://github.com/Jackiexiao"><img src="https://avatars.githubusercontent.com/u/18050469?v=4" width=75 height=75></a>
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<a href="https://github.com/limpidezza"><img src="https://avatars.githubusercontent.com/u/71760778?v=4" width=75 height=75></a>
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</p>
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## 致谢
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- 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。
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- 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。
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- 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。
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- 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。
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- 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。
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- 非常感谢 [kslz](https://github.com/kslz) 补充中文文档。
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- 非常感谢 [awmmmm](https://github.com/awmmmm) 提供 fastspeech2 aishell3 conformer 预训练模型。
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|
- 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。
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- 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。
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- 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。
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- 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。
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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)。
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## License
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|
PaddleSpeech 在 [Apache-2.0 许可](./LICENSE) 下提供。
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