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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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<div align="center">
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<h3>
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<a href="#quick-start"> 快速开始 </a>
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| <a href="#documents"> 教程 </a>
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| <a href="#model-list"> 模型列表 </a>
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</div>
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------------------------------------------------------------------------------------
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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="support os"><img src="https://img.shields.io/badge/os-linux-yellow.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="Hugging Face 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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<!---
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from https://github.com/18F/open-source-guide/blob/18f-pages/pages/making-readmes-readable.md
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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.)
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2.How does it work?
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3.Who will use this repo or project?
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4.What is the goal of this project?
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-->
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**PaddleSpeech** 是基于飞桨 [PaddlePaddle](https://github.com/PaddlePaddle/Paddle) 深度学习开源框架平台上的一个开源模型库,用于语音和音频中的各种关键任务的开发,包含大量前沿和有影响力的模型,一些典型的应用示例如下:
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##### 语音识别
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<div align = "center">
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<table style="width:100%">
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<thead>
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<tr>
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<th> 输入音频 </th>
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<th width="550"> 识别结果 </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 align = "center">
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<a href="https://paddlespeech.bj.bcebos.com/PaddleAudio/en.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 >I knocked at the door on the ancient side of the building.</td>
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</tr>
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<tr>
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<td align = "center">
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<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>
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</tbody>
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</table>
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</div>
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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>
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<tr>
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<th> 输入音频 </th>
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<th width="550"> 翻译结果 </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 align = "center">
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<a href="https://paddlespeech.bj.bcebos.com/PaddleAudio/en.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 在 这栋 建筑 的 古老 门上 敲门。</td>
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</tr>
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</tbody>
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</table>
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</div>
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##### 文本转语音
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<div align = "center">
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<table style="width:100%">
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<thead>
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<tr>
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<th><img width="200" height="1"> 输入文本 <img width="200" height="1"> </th>
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<th>合成音频</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 >Life was like a box of chocolates, you never know what you're gonna get.</td>
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<td align = "center">
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<a href="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/transformer_tts_ljspeech_ckpt_0.4_waveflow_ljspeech_ckpt_0.3/001.wav" rel="nofollow">
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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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</tr>
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<tr>
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<td >早上好,今天是2020/10/29,最低温度是-3°C。</td>
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<td align = "center">
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<a href="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/001.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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</tr>
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</tbody>
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</table>
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</div>
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更多合成音频,可以参考 [PaddleSpeech文本转语音样本](https://paddlespeech.readthedocs.io/en/latest/tts/demo.html)。
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### 特性:
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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
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- 📦 **易用性**: 安装门槛低,可使用[CLI](#quick-start)快速开始。
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- 🏆 **对标SoTA**: 提供了高速、轻量级模型,且借鉴了最前沿的技术。
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- 💯 **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。
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- **多种工业界以及学术界主流功能支持**:
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- 🛎️ 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。
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- 🔬 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)。
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- 🧩 级联模型应用: 作为传统语音任务的扩展,我们结合了自然与语言处理、计算机视觉等任务,实现更接近实际需求的产业级应用。
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### 近期更新:
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<!---
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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).
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--->
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- 🤗 2021.12.14: 我们在 Hugging Face Spaces 上的 [ASR](https://huggingface.co/spaces/KPatrick/PaddleSpeechASR) 以及 [TTS](https://huggingface.co/spaces/akhaliq/paddlespeech) Demos 上线啦!
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- 👏🏻 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。
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### 交流
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欢迎加入以下微信群,直接和我们 PaddleSpeech 团队进行交流!
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<div align="center">
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<img src="./docs/images/wechat_group.png" width = "200" />
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</div>
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## 安装
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我们强烈建议用户在 **Linux** 环境下,*3.7* 以上版本的 *python* 上安装 PaddleSpeech。这种情况下安装 `paddlespeech` 只需要一条 `pip` 命令:
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```python
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pip install paddlepaddle paddlespeech
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```
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目前为止,对于**Mac OSX、 LiNUX** 支持声音分类、语音识别、语音合成和语音翻译四种功能,**Windows** 下暂不支持语音翻译功能。 想了解更多安装细节,可以参考[安装文档](./docs/source/install.md)。
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## 快速开始
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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。
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**声音分类**
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```shell
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paddlespeech cls --input input.wav
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```
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**语音识别**
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```shell
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paddlespeech asr --lang zh --input input_16k.wav
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```
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**语音翻译** (English to Chinese)
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```shell
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paddlespeech st --input input_16k.wav
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|
```
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**语音合成**
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|
```shell
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paddlespeech tts --input "你好,欢迎使用百度飞桨深度学习框架!" --output output.wav
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```
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> 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)。
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## 模型列表
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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)。
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**语音转文本** 包含声学模型和语言模型, 详情如下:
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<!---
|
|
|
The current hyperlinks redirect to [Previous Parakeet](https://github.com/PaddlePaddle/Parakeet/tree/develop/examples).
|
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|
-->
|
|
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|
|
|
<table style="width:100%">
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<thead>
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<tr>
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<th>语音转文本模块种类</th>
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<th>数据集</th>
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<th>模型种类</th>
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<th>链接</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 rowspan="3">语音识别</td>
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<td rowspan="2" >Aishell</td>
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<td >DeepSpeech2 RNN + Conv based Models</td>
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<td>
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<a href = "./examples/aishell/asr0">deepspeech2-aishell</a>
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</td>
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</tr>
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<tr>
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<td>基于Transformer的Attention模型 </td>
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<td>
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<a href = "./examples/aishell/asr1">u2.transformer.conformer-aishell</a>
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</td>
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</tr>
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<tr>
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<td> Librispeech</td>
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<td>基于Transformer的Attention模型 </td>
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<td>
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<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>
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</td>
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</td>
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</tr>
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<tr>
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<td>对齐</td>
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<td>THCHS30</td>
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<td>MFA</td>
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<td>
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<a href = ".examples/thchs30/align0">mfa-thchs30</a>
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</td>
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</tr>
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<tr>
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<td rowspan="2">语言模型</td>
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<td colspan = "2">Ngram 语言模型</td>
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<td>
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<a href = "./examples/other/ngram_lm">kenlm</a>
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</td>
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</tr>
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<tr>
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<td>TIMIT</td>
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<td>Unified Streaming & Non-streaming Two-pass</td>
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<td>
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<a href = "./examples/timit/asr1"> u2-timit</a>
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</td>
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</tr>
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<tr>
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<td rowspan="2">语音翻译(英译中)</td>
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<td rowspan="2">TED En-Zh</td>
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<td>Transformer + ASR MTL</td>
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<td>
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<a href = "./examples/ted_en_zh/st0">transformer-ted</a>
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</td>
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</tr>
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<tr>
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<td>FAT + Transformer + ASR MTL</td>
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<td>
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<a href = "./examples/ted_en_zh/st1">fat-st-ted</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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|
PaddleSpeech 中的 **文本转语音** 主要包含三个模块:*文本前端*、*声学模型* 和 *声码器*。声学模型和声码器模型如下:
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<table>
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<thead>
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<tr>
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<th> 文字转语音模块类型 <img width="110" height="1"> </th>
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<th> 模型种类 </th>
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<th> <img width="50" height="1"> 数据集 <img width="50" height="1"> </th>
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<th> <img width="101" height="1"> 链接 <img width="105" height="1"> </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> 文本前端</td>
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<td colspan="2">   </td>
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<td>
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<a href = "./examples/other/tn">tn</a> / <a href = "./examples/other/g2p">g2p</a>
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</td>
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</tr>
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<tr>
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<td rowspan="4">声学模型</td>
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<td >Tacotron2</td>
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|
<td rowspan="2" >LJSpeech</td>
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<td>
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<a href = "./examples/ljspeech/tts0">tacotron2-ljspeech</a>
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</td>
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</tr>
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<tr>
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<td>Transformer TTS</td>
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<td>
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<a href = "./examples/ljspeech/tts1">transformer-ljspeech</a>
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</td>
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</tr>
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<tr>
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<td>SpeedySpeech</td>
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<td>CSMSC</td>
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<td >
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<a href = "./examples/csmsc/tts2">speedyspeech-csmsc</a>
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</td>
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</tr>
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|
<tr>
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|
<td>FastSpeech2</td>
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<td>AISHELL-3 / VCTK / LJSpeech / CSMSC</td>
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<td>
|
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|
<a href = "./examples/aishell3/tts3">fastspeech2-aishell3</a> / <a href = "./examples/vctk/tts3">fastspeech2-vctk</a> / <a href = "./examples/ljspeech/tts3">fastspeech2-ljspeech</a> / <a href = "./examples/csmsc/tts3">fastspeech2-csmsc</a>
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</td>
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</tr>
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<tr>
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<td rowspan="3">Vocoder</td>
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<td >WaveFlow</td>
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<td >LJSpeech</td>
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<td>
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|
<a href = "./examples/ljspeech/voc0">waveflow-ljspeech</a>
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|
</td>
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|
</tr>
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<tr>
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|
|
<td >Parallel WaveGAN</td>
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<td >LJSpeech / VCTK / CSMSC</td>
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<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>
|
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</td>
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</tr>
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<tr>
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|
<td >Multi Band MelGAN</td>
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<td >CSMSC</td>
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<td>
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<a href = "./examples/csmsc/voc3">Multi Band MelGAN-csmsc</a>
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</td>
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</tr>
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<tr>
|
|
|
<td rowspan="3">Voice Cloning</td>
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<td>GE2E</td>
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<td >Librispeech, etc.</td>
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<td>
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<a href = "./examples/other/ge2e">ge2e</a>
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</td>
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</tr>
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<tr>
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<td>GE2E + Tactron2</td>
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<td>AISHELL-3</td>
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<td>
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<a href = "./examples/aishell3/vc0">ge2e-tactron2-aishell3</a>
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</td>
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</tr>
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<tr>
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<td>GE2E + FastSpeech2</td>
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<td>AISHELL-3</td>
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<td>
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<a href = "./examples/aishell3/vc1">ge2e-fastspeech2-aishell3</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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**声音分类**
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<table style="width:100%">
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<thead>
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<tr>
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<th> <img width="150" height="1">任务 <img width="150" height="1"></th>
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<th> <img width="110" height="1">数据集 <img width="110" height="1"></th>
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<th> <img width="110" height="1">模型种类 <img width="110" height="1"></th>
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<th> <img width="110" height="1">链接<img width="110" height="1"></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>Audio Classification</td>
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|
<td>ESC-50</td>
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<td>PANN</td>
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<td>
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|
<a href = "./examples/esc50/cls0">pann-esc50</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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## 文档
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[语音 SoTA](https://paperswithcode.com/area/speech)、[声音 SoTA](https://paperswithcode.com/area/audio)、[音乐 SoTA](https://paperswithcode.com/area/music) 概述了相关领域的热门学术话题。对于 PaddleSpeech 的所关注的任务,以下指南有助于掌握核心思想。
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- [安装](./docs/source/install.md)
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- Tutorials
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- [语音识别](./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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|
- [数据增强](./docs/source/asr/augmentation.md)
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|
|
- [Ngram 语言模型](./docs/source/asr/ngram_lm.md)
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|
|
- [语音合成](./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)
|
|
|
- [测试语音样本](https://paddlespeech.readthedocs.io/en/latest/tts/demo.html)
|
|
|
- 声音分类
|
|
|
- 语音翻译
|
|
|
- [模型](./docs/source/released_model.md)
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|
|
|
|
|
|
|
|
语音合成模块最初被称为 [Parakeet](https://github.com/PaddlePaddle/Parakeet),现在与此存库合并。如果您改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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## 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。
|
|
|
```tex
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|
|
@misc{ppspeech2021,
|
|
|
title={PaddleSpeech, a toolkit for audio processing based on PaddlePaddle.},
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|
|
author={PaddlePaddle Authors},
|
|
|
howpublished = {\url{https://github.com/PaddlePaddle/PaddleSpeech}},
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|
|
year={2021}
|
|
|
}
|
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|
```
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|
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|
|
|
## 参与PaddleSpeech的开发
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|
|
|
|
|
|
|
|
热烈欢迎您在[讨论](https://github.com/PaddlePaddle/PaddleSpeech/discussions) 中提交问题,并在[问题](https://github.com/PaddlePaddle/PaddleSpeech/issues) 中指出发现的bug。此外,我们非常希望您愿意参与到PaddleSpeech的开发中!
|
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|
|
### 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>
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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>
|
|
|
<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) 多年来的关注和建议,以及在诸多问题上的帮助。
|
|
|
- 非常感谢 [AK391](https://github.com/AK391) 在 Huggingface Spaces 上使用 Gradio 对我们的语音合成功能进行网页版演示。
|
|
|
|
|
|
此外,PaddleSpeech 依赖于许多开源存储库。有关更多信息,请参阅 [references](./docs/source/reference.md)。
|
|
|
|
|
|
## License
|
|
|
|
|
|
PaddleSpeech 在 [Apache-2.0 许可](./LICENSE) 下提供。
|