Merge branch 'develop' into u2pp_export

pull/2425/head
Hui Zhang 2 years ago
commit bdf876ea7b

@ -19,8 +19,6 @@
<div align="center"> <div align="center">
<h4> <h4>
<a href="#quick-start"> Quick Start </a> <a href="#quick-start"> Quick Start </a>
| <a href="#quick-start-server"> Quick Start Server </a>
| <a href="#quick-start-streaming-server"> Quick Start Streaming Server</a>
| <a href="#documents"> Documents </a> | <a href="#documents"> Documents </a>
| <a href="#model-list"> Models List </a> | <a href="#model-list"> Models List </a>
| <a href="https://aistudio.baidu.com/aistudio/education/group/info/25130"> AIStudio Courses </a> | <a href="https://aistudio.baidu.com/aistudio/education/group/info/25130"> AIStudio Courses </a>
@ -159,6 +157,8 @@ Via the easy-to-use, efficient, flexible and scalable implementation, our vision
- 🧩 *Cascaded models application*: as an extension of the typical traditional audio tasks, we combine the workflows of the aforementioned tasks with other fields like Natural language processing (NLP) and Computer Vision (CV). - 🧩 *Cascaded models application*: as an extension of the typical traditional audio tasks, we combine the workflows of the aforementioned tasks with other fields like Natural language processing (NLP) and Computer Vision (CV).
### Recent Update ### Recent Update
- 🔥 2022.09.26: Add Voice Cloning, TTS finetune, and ERNIE-SAT in [PaddleSpeech Web Demo](./demos/speech_web).
- ⚡ 2022.09.09: Add AISHELL-3 Voice Cloning [example](./examples/aishell3/vc2) with ECAPA-TDNN speaker encoder.
- ⚡ 2022.08.25: Release TTS [finetune](./examples/other/tts_finetune/tts3) example. - ⚡ 2022.08.25: Release TTS [finetune](./examples/other/tts_finetune/tts3) example.
- 🔥 2022.08.22: Add ERNIE-SAT models: [ERNIE-SAT-vctk](./examples/vctk/ernie_sat)、[ERNIE-SAT-aishell3](./examples/aishell3/ernie_sat)、[ERNIE-SAT-zh_en](./examples/aishell3_vctk/ernie_sat). - 🔥 2022.08.22: Add ERNIE-SAT models: [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: Add [g2pW](https://github.com/GitYCC/g2pW) into TTS Chinese Text Frontend. - 🔥 2022.08.15: Add [g2pW](https://github.com/GitYCC/g2pW) into TTS Chinese Text Frontend.
@ -705,7 +705,7 @@ PaddleSpeech supports a series of most popular models. They are summarized in [r
<tbody> <tbody>
<tr> <tr>
<td>Speaker Verification</td> <td>Speaker Verification</td>
<td>VoxCeleb12</td> <td>VoxCeleb1/2</td>
<td>ECAPA-TDNN</td> <td>ECAPA-TDNN</td>
<td> <td>
<a href = "./examples/voxceleb/sv0">ecapa-tdnn-voxceleb12</a> <a href = "./examples/voxceleb/sv0">ecapa-tdnn-voxceleb12</a>
@ -714,6 +714,31 @@ PaddleSpeech supports a series of most popular models. They are summarized in [r
</tbody> </tbody>
</table> </table>
<a name="SpeakerDiarization"></a>
**Speaker Diarization**
<table style="width:100%">
<thead>
<tr>
<th> Task </th>
<th> Dataset </th>
<th> Model Type </th>
<th> Example </th>
</tr>
</thead>
<tbody>
<tr>
<td>Speaker Diarization</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="PunctuationRestoration"></a> <a name="PunctuationRestoration"></a>
**Punctuation Restoration** **Punctuation Restoration**
@ -767,6 +792,7 @@ Normally, [Speech SoTA](https://paperswithcode.com/area/speech), [Audio SoTA](ht
- [Text-to-Speech](#TextToSpeech) - [Text-to-Speech](#TextToSpeech)
- [Audio Classification](#AudioClassification) - [Audio Classification](#AudioClassification)
- [Speaker Verification](#SpeakerVerification) - [Speaker Verification](#SpeakerVerification)
- [Speaker Diarization](#SpeakerDiarization)
- [Punctuation Restoration](#PunctuationRestoration) - [Punctuation Restoration](#PunctuationRestoration)
- [Community](#Community) - [Community](#Community)
- [Welcome to contribute](#contribution) - [Welcome to contribute](#contribution)

@ -19,10 +19,8 @@
</p> </p>
<div align="center"> <div align="center">
<h4> <h4>
<a href="#安装"> 安装 </a> <a href="#安装"> 安装 </a>
| <a href="#快速开始"> 快速开始 </a> | <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>
| <a href="#快速使用流式服务"> 快速使用流式服务 </a>
| <a href="#教程文档"> 教程文档 </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="#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://aistudio.baidu.com/aistudio/education/group/info/25130"> AIStudio 课程 </a>
@ -181,6 +179,8 @@
</div> </div>
### 近期更新 ### 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。 - ⚡ 2022.08.25: 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)。 - 🔥 2022.08.22: 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。 - 🔥 2022.08.15: 将 [g2pW](https://github.com/GitYCC/g2pW) 引入 TTS 中文文本前端。
@ -717,8 +717,8 @@ PaddleSpeech 的 **语音合成** 主要包含三个模块:文本前端、声
</thead> </thead>
<tbody> <tbody>
<tr> <tr>
<td>Speaker Verification</td> <td>声纹识别</td>
<td>VoxCeleb12</td> <td>VoxCeleb1/2</td>
<td>ECAPA-TDNN</td> <td>ECAPA-TDNN</td>
<td> <td>
<a href = "./examples/voxceleb/sv0">ecapa-tdnn-voxceleb12</a> <a href = "./examples/voxceleb/sv0">ecapa-tdnn-voxceleb12</a>
@ -727,6 +727,31 @@ PaddleSpeech 的 **语音合成** 主要包含三个模块:文本前端、声
</tbody> </tbody>
</table> </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> <a name="标点恢复模型"></a>
**标点恢复** **标点恢复**
@ -786,6 +811,7 @@ PaddleSpeech 的 **语音合成** 主要包含三个模块:文本前端、声
- [语音合成](#语音合成模型) - [语音合成](#语音合成模型)
- [声音分类](#声音分类模型) - [声音分类](#声音分类模型)
- [声纹识别](#声纹识别模型) - [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) - [标点恢复](#标点恢复模型)
- [技术交流群](#技术交流群) - [技术交流群](#技术交流群)
- [欢迎贡献](#欢迎贡献) - [欢迎贡献](#欢迎贡献)

@ -13,4 +13,7 @@
*.pdmodel *.pdmodel
*/source/* */source/*
*/PaddleSpeech/* */PaddleSpeech/*
*/tmp*/*
*/duration.txt
*/oov_info.txt

@ -1,55 +1,82 @@
# Paddle Speech Demo # Paddle Speech Demo
PaddleSpeechDemo 是一个以 PaddleSpeech 的语音交互功能为主体开发的 Demo 展示项目,用于帮助大家更好的上手 PaddleSpeech 以及使用 PaddleSpeech 构建自己的应用。 ## 简介
Paddle Speech Demo 是一个以 PaddleSpeech 的语音交互功能为主体开发的 Demo 展示项目,用于帮助大家更好的上手 PaddleSpeech 以及使用 PaddleSpeech 构建自己的应用。
智能语音交互部分使用 PaddleSpeech对话以及信息抽取部分使用 PaddleNLP网页前端展示部分基于 Vue3 进行开发 智能语音交互部分使用 PaddleSpeech对话以及信息抽取部分使用 PaddleNLP网页前端展示部分基于 Vue3 进行开发
主要功能: 主要功能:
`main.py` 中包含功能
+ 语音聊天PaddleSpeech 的语音识别能力+语音合成能力,对话部分基于 PaddleNLP 的闲聊功能 + 语音聊天PaddleSpeech 的语音识别能力+语音合成能力,对话部分基于 PaddleNLP 的闲聊功能
+ 声纹识别PaddleSpeech 的声纹识别功能展示 + 声纹识别PaddleSpeech 的声纹识别功能展示
+ 语音识别:支持【实时语音识别】,【端到端识别】,【音频文件识别】三种模式 + 语音识别:支持【实时语音识别】,【端到端识别】,【音频文件识别】三种模式
+ 语音合成:支持【流式合成】与【端到端合成】两种方式 + 语音合成:支持【流式合成】与【端到端合成】两种方式
+ 语音指令:基于 PaddleSpeech 的语音识别能力与 PaddleNLP 的信息抽取,实现交通费的智能报销 + 语音指令:基于 PaddleSpeech 的语音识别能力与 PaddleNLP 的信息抽取,实现交通费的智能报销
`vc.py` 中包含功能
+ 一句话合成:基于 GE2E 和 ECAPA-TDNN 模型的一句话合成方案,可以模仿输入的音频的音色进行合成任务
+ GE2E 音色克隆方案可以参考: [【FastSpeech2 + AISHELL-3 Voice Cloning】](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/aishell3/vc1)
+ ECAPA-TDNN 音色克隆方案可以参考: [【FastSpeech2 + AISHELL-3 Voice Cloning (ECAPA-TDNN)】](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/aishell3/vc2)
+ 小数据微调基于小数据集的微调方案内置用12句话标贝中文女声微调示例你也可以通过一键重置录制自己的声音注意在安静环境下录制效果会更好。你可以在 [【Finetune your own AM based on FastSpeech2 with AISHELL-3】](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/other/tts_finetune/tts3)中尝试使用自己的数据集进行微调。
+ ENIRE-SAT语言-语音跨模态大模型 ENIRE-SAT 可视化展示示例,支持个性化合成,跨语言语音合成(音频为中文则输入英文文本进行合成),语音编辑(修改音频文字中间的结果)功能。 ENIRE-SAT 更多实现细节,可以参考:
+ [【ERNIE-SAT with AISHELL-3 dataset】](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/aishell3/ernie_sat)
+ [【ERNIE-SAT with with AISHELL3 and VCTK datasets】](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/aishell3_vctk/ernie_sat)
+ [【ERNIE-SAT with VCTK dataset】](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/vctk/ernie_sat)
运行效果: 运行效果:
![效果](docs/效果展示.png) ![效果](https://user-images.githubusercontent.com/30135920/192155349-9ef93d20-730b-413d-8d50-412fedf11d4b.png)
## 安装
### 后端环境安装
``` ## 基础环境安装
# 安装环境
cd speech_server
pip install -r requirements.txt
# 下载 ie 模型,针对地点进行微调,效果更好,不下载的话会使用其它版本,效果没有这个好 ### 后端环境安装
cd source ```bash
mkdir model # 需要先安装 PaddleSpeech
cd model cd speech_server
wget https://bj.bcebos.com/paddlenlp/applications/speech-cmd-analysis/finetune/model_state.pdparams pip install -r requirements.txt -i https://mirror.baidu.com/pypi/simple
cd ../
``` ```
### 前端环境安装 ### 前端环境安装
前端依赖 `node.js` ,需要提前安装,确保 `npm` 可用,`npm` 测试版本 `8.3.1`,建议下载[官网](https://nodejs.org/en/)稳定版的 `node.js` 前端依赖 `node.js` ,需要提前安装,确保 `npm` 可用,`npm` 测试版本 `8.3.1`,建议下载[官网](https://nodejs.org/en/)稳定版的 `node.js`
``` 如果因为网络问题,无法下载依赖库,可以参考 FAQ 部分,`npm / yarn 下载速度慢问题`
```bash
# 进入前端目录 # 进入前端目录
cd web_client cd web_client
# 安装 `yarn`,已经安装可跳过 # 安装 `yarn`,已经安装可跳过
npm install -g yarn npm install -g yarn
# 使用yarn安装前端依赖 # 使用yarn安装前端依赖
yarn install yarn install
cd ../
``` ```
## 启动服务 ## 启动服务
【注意】目前只支持 `main.py``vc.py` 两者中选择开启一个后端服务。
### 启动 `main.py` 后端服务
#### 下载相关模型
只需手动下载语音指令所需模型即可,其他模型会自动下载。
### 开启后端服务 ```bash
cd speech_server
mkdir -p source/model
cd source/model
# 下载IE模型
wget https://bj.bcebos.com/paddlenlp/applications/speech-cmd-analysis/finetune/model_state.pdparams
cd ../../../
```
#### 启动后端服务
``` ```
cd speech_server cd speech_server
@ -57,14 +84,116 @@ cd speech_server
python main.py --port 8010 python main.py --port 8010
``` ```
### 开启前端服务
### 启动 `vc.py` 后端服务
参照下面的步骤自行配置项目所需环境。
Aistudio 在线体验小样本合成后端功能:[【PaddleSpeech进阶】PaddleSpeech小样本合成方案体验](https://aistudio.baidu.com/aistudio/projectdetail/4573549?sUid=2470186&shared=1&ts=1664174385948)
#### 下载相关模型和音频
```bash
cd speech_server
# 已创建则跳过
mkdir -p source/model
cd source
# 下载 & 解压 wav 包含VC测试音频
wget https://paddlespeech.bj.bcebos.com/demos/speech_web/wav_vc.zip
unzip wav_vc.zip
cd model
# 下载 GE2E 相关模型
wget https://bj.bcebos.com/paddlespeech/Parakeet/released_models/ge2e/ge2e_ckpt_0.3.zip
unzip ge2e_ckpt_0.3.zip
wget https://paddlespeech.bj.bcebos.com/Parakeet/released_models/pwgan/pwg_aishell3_ckpt_0.5.zip
unzip pwg_aishell3_ckpt_0.5.zip
wget https://paddlespeech.bj.bcebos.com/Parakeet/released_models/fastspeech2/fastspeech2_nosil_aishell3_vc1_ckpt_0.5.zip
unzip fastspeech2_nosil_aishell3_vc1_ckpt_0.5.zip
# 下载 ECAPA-TDNN 相关模型
wget https://paddlespeech.bj.bcebos.com/Parakeet/released_models/fastspeech2/fastspeech2_aishell3_ckpt_vc2_1.2.0.zip
unzip fastspeech2_aishell3_ckpt_vc2_1.2.0.zip
# 下载 ERNIE-SAT 相关模型
# aishell3 ERNIE-SAT
wget https://paddlespeech.bj.bcebos.com/Parakeet/released_models/ernie_sat/erniesat_aishell3_ckpt_1.2.0.zip
unzip erniesat_aishell3_ckpt_1.2.0.zip
# vctk ERNIE-SAT
wget https://paddlespeech.bj.bcebos.com/Parakeet/released_models/ernie_sat/erniesat_vctk_ckpt_1.2.0.zip
unzip erniesat_vctk_ckpt_1.2.0.zip
# aishell3_vctk ERNIE-SAT
wget https://paddlespeech.bj.bcebos.com/Parakeet/released_models/ernie_sat/erniesat_aishell3_vctk_ckpt_1.2.0.zip
unzip erniesat_aishell3_vctk_ckpt_1.2.0.zip
# 下载 finetune 相关模型
wget https://paddlespeech.bj.bcebos.com/Parakeet/released_models/fastspeech2/fastspeech2_aishell3_ckpt_1.1.0.zip
unzip fastspeech2_aishell3_ckpt_1.1.0.zip
# 下载声码器
wget https://paddlespeech.bj.bcebos.com/Parakeet/released_models/hifigan/hifigan_aishell3_ckpt_0.2.0.zip
unzip hifigan_aishell3_ckpt_0.2.0.zip
wget https://paddlespeech.bj.bcebos.com/Parakeet/released_models/hifigan/hifigan_vctk_ckpt_0.2.0.zip
unzip hifigan_vctk_ckpt_0.2.0.zip
cd ../../../
```
#### ERNIE-SAT 环境配置
ERNIE-SAT 体验依赖于 [examples/aishell3_vctk/ernie_sat](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/aishell3_vctk/ernie_sat) 的环境。参考 `examples/aishell3_vctk/ernie_sat` 下的 `README.md` 确保 `examples/aishell3_vctk/ernie_sat``run.sh` 相关示例代码有效。
运行好 `examples/aishell3_vctk/ernie_sat` 后,回到当前目录,创建环境:
```bash
cd speech_server
ln -snf ../../../examples/aishell3_vctk/ernie_sat/download .
ln -snf ../../../examples/aishell3_vctk/ernie_sat/tools .
cd ../
```
#### finetune 环境配置
`finetune` 需要解压 `tools/aligner` 中的 `aishell3_model.zip`finetune 过程需要使用到 `tools/aligner/aishell3_model/meta.yaml` 文件。
```bash
cd speech_server/tools/aligner
unzip aishell3_model.zip
cd -
```
#### 启动后端服务
```
cd speech_server
# 默认8010端口
python vc.py --port 8010
```
### 启动前端服务
``` ```
cd web_client cd web_client
yarn dev --port 8011 yarn dev --port 8011
``` ```
默认配置下,前端中配置的后台地址信息是 localhost确保后端服务器和打开页面的游览器在同一台机器上不在一台机器的配置方式见下方的 FAQ【后端如果部署在其它机器或者别的端口如何修改】 默认配置下,前端配置的后台地址信息是 `localhost`,确保后端服务器和打开页面的游览器在同一台机器上,不在一台机器的配置方式见下方的 FAQ【后端如果部署在其它机器或者别的端口如何修改】
#### 关于前端的一些说明
为了方便后期的维护,这里并没有给出打包好的 HTML 文件,而是 Vue3 的项目,使用 `yarn dev --port 8011` 的方式启动测试方便大家debug相当于是启动了一个前端服务器。
比如我们在本机启动的这个前端服务(运行 `yarn dev --port 8011` ),我们就可以通过在游览器中通过 `http://localhost:8011` 访问前端页面
如果我们在其它服务器上(例如:`*.*.*.*` )启动这个前端服务(运行 `yarn dev --port 8011` ),我们就可以通过在游览器中访问 `http://*.*.*.*:8011` 访问前端页面
那前端跟后端是什么关系呢? 两个是独立的,只要前端能够通过代理访问到后端的接口,那就没有问题。你可以在 A 机器上部署后端服务,然后在 B 机器上部署前端服务。我们在 `./web_client/vite.config.js` 中将 `/api` 映射到的是 `http://localhost:8010`,你可以把它配置成任意你想要访问后端地址。
当前端在以 `*.*.*.*` 这类以 IP 地址形式的网页中访问时,由于游览器的安全限制,会禁止录音,需要重新配置游览器的安全策略, 可以看下面 FAQ 部分: [【前端以IP地址的形式访问无法录音】]
## FAQ ## FAQ
#### Q: 如何安装node.js #### Q: 如何安装node.js
@ -75,7 +204,7 @@ A node.js的安装可以参考[【菜鸟教程】](https://www.runoob.com/nod
A后端的配置地址有分散在两个文件中 A后端的配置地址有分散在两个文件中
修改第一个文件 `PaddleSpeechWebClient/vite.config.js` 修改第一个文件 `./web_client/vite.config.js`
``` ```
server: { server: {
@ -90,7 +219,7 @@ server: {
} }
``` ```
修改第二个文件 `PaddleSpeechWebClient/src/api/API.js` Websocket 代理配置失败,所以需要在这个文件中修改) 修改第二个文件 `./web_client/src/api/API.js` Websocket 代理配置失败,所以需要在这个文件中修改)
``` ```
// websocket (这里改成后端所在的接口) // websocket (这里改成后端所在的接口)
@ -99,12 +228,24 @@ ASR_SOCKET_RECORD: 'ws://localhost:8010/ws/asr/onlineStream', // Stream ASR 接
TTS_SOCKET_RECORD: 'ws://localhost:8010/ws/tts/online', // Stream TTS 接口 TTS_SOCKET_RECORD: 'ws://localhost:8010/ws/tts/online', // Stream TTS 接口
``` ```
#### Q后端以IP地址的形式前端无法录音 #### Q前端以IP地址的形式访问无法录音
A这里主要是游览器安全策略的限制需要配置游览器后重启。游览器修改配置可参考[使用js-audio-recorder报浏览器不支持getUserMedia](https://blog.csdn.net/YRY_LIKE_YOU/article/details/113745273) A这里主要是游览器安全策略的限制需要配置游览器后重启。游览器修改配置可参考[使用js-audio-recorder报浏览器不支持getUserMedia](https://blog.csdn.net/YRY_LIKE_YOU/article/details/113745273)
chrome设置地址: chrome://flags/#unsafely-treat-insecure-origin-as-secure chrome设置地址: chrome://flags/#unsafely-treat-insecure-origin-as-secure
#### Q: npm / yarn 配置淘宝镜像源
A: 配置淘宝镜像源,详细可以参考 [【yarn npm 设置淘宝镜像】](https://www.jianshu.com/p/f6f43e8f9d6b)
```bash
# npm 配置淘宝镜像源
npm config set registry https://registry.npmmirror.com
# yarn 配置淘宝镜像源
yarn config set registry http://registry.npm.taobao.org/
```
## 参考资料 ## 参考资料
vue实现录音参考资料https://blog.csdn.net/qq_41619796/article/details/107865602#t1 vue实现录音参考资料https://blog.csdn.net/qq_41619796/article/details/107865602#t1

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@ -3,10 +3,10 @@
########################################################### ###########################################################
# Set to -1 to indicate that the parameter is the same as the pretrained model configuration # Set to -1 to indicate that the parameter is the same as the pretrained model configuration
batch_size: -1 batch_size: 10
learning_rate: 0.0001 # learning rate learning_rate: 0.0001 # learning rate
num_snapshots: -1 num_snapshots: -1
# frozen_layers should be a list # frozen_layers should be a list
# if you don't need to freeze, set frozen_layers to [] # if you don't need to freeze, set frozen_layers to []
frozen_layers: ["encoder", "duration_predictor"] frozen_layers: ["encoder"]

@ -1,8 +1,3 @@
# todo:
# 1. 开启服务
# 2. 接收录音音频,返回识别结果
# 3. 接收ASR识别结果返回NLP对话结果
# 4. 接收NLP对话结果返回TTS音频
import argparse import argparse
import base64 import base64
import datetime import datetime
@ -32,6 +27,7 @@ from starlette.requests import Request
from starlette.responses import FileResponse from starlette.responses import FileResponse
from starlette.websockets import WebSocketState as WebSocketState from starlette.websockets import WebSocketState as WebSocketState
from paddlespeech.cli.tts.infer import TTSExecutor
from paddlespeech.server.engine.asr.online.python.asr_engine import PaddleASRConnectionHanddler from paddlespeech.server.engine.asr.online.python.asr_engine import PaddleASRConnectionHanddler
from paddlespeech.server.utils.audio_process import float2pcm from paddlespeech.server.utils.audio_process import float2pcm
@ -55,7 +51,7 @@ asr_config = "conf/ws_conformer_wenetspeech_application_faster.yaml"
asr_init_path = "source/demo/demo.wav" asr_init_path = "source/demo/demo.wav"
db_path = "source/db/vpr.sqlite" db_path = "source/db/vpr.sqlite"
ie_model_path = "source/model" ie_model_path = "source/model"
tts_model = TTSExecutor()
# 路径配置 # 路径配置
UPLOAD_PATH = "source/vpr" UPLOAD_PATH = "source/vpr"
WAV_PATH = "source/wav" WAV_PATH = "source/wav"
@ -72,6 +68,14 @@ manager = ConnectionManager()
aumanager = AudioMannger(chatbot) aumanager = AudioMannger(chatbot)
aumanager.init() aumanager.init()
vpr = VPR(db_path, dim=192, top_k=5) vpr = VPR(db_path, dim=192, top_k=5)
# 初始化下载模型
tts_model(
text="今天天气准不错",
output="test.wav",
am='fastspeech2_mix',
spk_id=174,
voc='hifigan_csmsc',
lang='mix', )
# 服务配置 # 服务配置
@ -331,6 +335,7 @@ async def ieOffline(nlp_base: NlpBase):
##################################################################### #####################################################################
# 端到端合成
@app.post("/tts/offline") @app.post("/tts/offline")
async def text2speechOffline(tts_base: TtsBase): async def text2speechOffline(tts_base: TtsBase):
text = tts_base.text text = tts_base.text
@ -340,8 +345,14 @@ async def text2speechOffline(tts_base: TtsBase):
now_name = "tts_" + datetime.datetime.strftime( now_name = "tts_" + datetime.datetime.strftime(
datetime.datetime.now(), '%Y%m%d%H%M%S') + randName() + ".wav" datetime.datetime.now(), '%Y%m%d%H%M%S') + randName() + ".wav"
out_file_path = os.path.join(WAV_PATH, now_name) out_file_path = os.path.join(WAV_PATH, now_name)
# 保存为文件再转成base64传输 # 使用中英混合CLI
chatbot.text2speech(text, outpath=out_file_path) tts_model(
text=text,
output=out_file_path,
am='fastspeech2_mix',
spk_id=174,
voc='hifigan_csmsc',
lang='mix')
with open(out_file_path, "rb") as f: with open(out_file_path, "rb") as f:
data_bin = f.read() data_bin = f.read()
base_str = base64.b64encode(data_bin) base_str = base64.b64encode(data_bin)

@ -1,13 +1,8 @@
aiofiles aiofiles
faiss-cpu faiss-cpu
fastapi praatio==5.0.0
librosa
numpy
paddlenlp
paddlepaddle
paddlespeech
pydantic pydantic
python-multipartscikit_learn python-multipart
SoundFile scikit_learn
starlette starlette
uvicorn uvicorn

@ -0,0 +1,198 @@
import os
from .util import get_ngpu
from .util import MAIN_ROOT
from .util import run_cmd
class SAT:
def __init__(self):
# pretrain model path
self.zh_pretrain_model_path = os.path.realpath(
"source/model/erniesat_aishell3_ckpt_1.2.0")
self.en_pretrain_model_path = os.path.realpath(
"source/model/erniesat_vctk_ckpt_1.2.0")
self.cross_pretrain_model_path = os.path.realpath(
"source/model/erniesat_aishell3_vctk_ckpt_1.2.0")
self.zh_voc_model_path = os.path.realpath(
"source/model/hifigan_aishell3_ckpt_0.2.0")
self.eb_voc_model_path = os.path.realpath(
"source/model/hifigan_vctk_ckpt_0.2.0")
self.cross_voc_model_path = os.path.realpath(
"source/model/hifigan_aishell3_ckpt_0.2.0")
self.BIN_DIR = os.path.join(MAIN_ROOT,
"paddlespeech/t2s/exps/ernie_sat")
def zh_synthesize_edit(self,
old_str: str,
new_str: str,
input_name: os.PathLike,
output_name: os.PathLike,
task_name: str="synthesize",
erniesat_ckpt_name: str="snapshot_iter_289500.pdz"):
if task_name not in ['synthesize', 'edit']:
print("task name only in ['edit', 'synthesize']")
return None
# 推理文件配置
config_path = os.path.join(self.zh_pretrain_model_path, "default.yaml")
phones_dict = os.path.join(self.zh_pretrain_model_path,
"phone_id_map.txt")
erniesat_ckpt = os.path.join(self.zh_pretrain_model_path,
erniesat_ckpt_name)
erniesat_stat = os.path.join(self.zh_pretrain_model_path,
"speech_stats.npy")
voc = "hifigan_aishell3"
voc_config = os.path.join(self.zh_voc_model_path, "default.yaml")
voc_ckpt = os.path.join(self.zh_voc_model_path,
"snapshot_iter_2500000.pdz")
voc_stat = os.path.join(self.zh_voc_model_path, "feats_stats.npy")
cmd = self.get_cmd(
task_name=task_name,
input_name=input_name,
old_str=old_str,
new_str=new_str,
config_path=config_path,
phones_dict=phones_dict,
erniesat_ckpt=erniesat_ckpt,
erniesat_stat=erniesat_stat,
voc=voc,
voc_config=voc_config,
voc_ckpt=voc_ckpt,
voc_stat=voc_stat,
output_name=output_name,
source_lang="zh",
target_lang="zh")
return run_cmd(cmd, output_name)
def crossclone(self,
old_str: str,
new_str: str,
input_name: os.PathLike,
output_name: os.PathLike,
source_lang: str,
target_lang: str,
erniesat_ckpt_name: str="snapshot_iter_489000.pdz"):
# 推理文件配置
config_path = os.path.join(self.cross_pretrain_model_path,
"default.yaml")
phones_dict = os.path.join(self.cross_pretrain_model_path,
"phone_id_map.txt")
erniesat_ckpt = os.path.join(self.cross_pretrain_model_path,
erniesat_ckpt_name)
erniesat_stat = os.path.join(self.cross_pretrain_model_path,
"speech_stats.npy")
voc = "hifigan_aishell3"
voc_config = os.path.join(self.cross_voc_model_path, "default.yaml")
voc_ckpt = os.path.join(self.cross_voc_model_path,
"snapshot_iter_2500000.pdz")
voc_stat = os.path.join(self.cross_voc_model_path, "feats_stats.npy")
task_name = "synthesize"
cmd = self.get_cmd(
task_name=task_name,
input_name=input_name,
old_str=old_str,
new_str=new_str,
config_path=config_path,
phones_dict=phones_dict,
erniesat_ckpt=erniesat_ckpt,
erniesat_stat=erniesat_stat,
voc=voc,
voc_config=voc_config,
voc_ckpt=voc_ckpt,
voc_stat=voc_stat,
output_name=output_name,
source_lang=source_lang,
target_lang=target_lang)
return run_cmd(cmd, output_name)
def en_synthesize_edit(self,
old_str: str,
new_str: str,
input_name: os.PathLike,
output_name: os.PathLike,
task_name: str="synthesize",
erniesat_ckpt_name: str="snapshot_iter_199500.pdz"):
# 推理文件配置
config_path = os.path.join(self.en_pretrain_model_path, "default.yaml")
phones_dict = os.path.join(self.en_pretrain_model_path,
"phone_id_map.txt")
erniesat_ckpt = os.path.join(self.en_pretrain_model_path,
erniesat_ckpt_name)
erniesat_stat = os.path.join(self.en_pretrain_model_path,
"speech_stats.npy")
voc = "hifigan_aishell3"
voc_config = os.path.join(self.zh_voc_model_path, "default.yaml")
voc_ckpt = os.path.join(self.zh_voc_model_path,
"snapshot_iter_2500000.pdz")
voc_stat = os.path.join(self.zh_voc_model_path, "feats_stats.npy")
cmd = self.get_cmd(
task_name=task_name,
input_name=input_name,
old_str=old_str,
new_str=new_str,
config_path=config_path,
phones_dict=phones_dict,
erniesat_ckpt=erniesat_ckpt,
erniesat_stat=erniesat_stat,
voc=voc,
voc_config=voc_config,
voc_ckpt=voc_ckpt,
voc_stat=voc_stat,
output_name=output_name,
source_lang="en",
target_lang="en")
return run_cmd(cmd, output_name)
def get_cmd(self,
task_name: str,
input_name: str,
old_str: str,
new_str: str,
config_path: str,
phones_dict: str,
erniesat_ckpt: str,
erniesat_stat: str,
voc: str,
voc_config: str,
voc_ckpt: str,
voc_stat: str,
output_name: str,
source_lang: str,
target_lang: str):
ngpu = get_ngpu()
cmd = f"""
FLAGS_allocator_strategy=naive_best_fit \
FLAGS_fraction_of_gpu_memory_to_use=0.01 \
python3 {self.BIN_DIR}/synthesize_e2e.py \
--task_name={task_name} \
--wav_path={input_name} \
--old_str='{old_str}' \
--new_str='{new_str}' \
--source_lang={source_lang} \
--target_lang={target_lang} \
--erniesat_config={config_path} \
--phones_dict={phones_dict} \
--erniesat_ckpt={erniesat_ckpt} \
--erniesat_stat={erniesat_stat} \
--voc={voc} \
--voc_config={voc_config} \
--voc_ckpt={voc_ckpt} \
--voc_stat={voc_stat} \
--output_name={output_name} \
--ngpu={ngpu}
"""
return cmd

@ -0,0 +1,127 @@
import os
from .util import get_ngpu
from .util import MAIN_ROOT
from .util import run_cmd
def find_max_ckpt(model_path):
max_ckpt = 0
for filename in os.listdir(model_path):
if filename.endswith('.pdz'):
files = filename[:-4]
a1, a2, it = files.split("_")
if int(it) > max_ckpt:
max_ckpt = int(it)
return max_ckpt
class FineTune:
def __init__(self):
self.now_file_path = os.path.dirname(__file__)
self.PYTHONPATH = os.path.join(MAIN_ROOT,
"examples/other/tts_finetune/tts3")
self.BIN_DIR = os.path.join(MAIN_ROOT,
"paddlespeech/t2s/exps/fastspeech2")
self.pretrained_model_dir = os.path.realpath(
"source/model/fastspeech2_aishell3_ckpt_1.1.0")
self.voc_model_dir = os.path.realpath(
"source/model/hifigan_aishell3_ckpt_0.2.0")
self.finetune_config = os.path.join("conf/tts3_finetune.yaml")
def finetune(self, input_dir, exp_dir='temp', epoch=100):
"""
use cmd follow examples/other/tts_finetune/tts3/run.sh
"""
newdir_name = "newdir"
new_dir = os.path.join(input_dir, newdir_name)
mfa_dir = os.path.join(exp_dir, 'mfa_result')
dump_dir = os.path.join(exp_dir, 'dump')
output_dir = os.path.join(exp_dir, 'exp')
lang = "zh"
ngpu = get_ngpu()
cmd = f"""
# check oov
python3 {self.PYTHONPATH}/local/check_oov.py \
--input_dir={input_dir} \
--pretrained_model_dir={self.pretrained_model_dir} \
--newdir_name={newdir_name} \
--lang={lang}
# get mfa result
python3 {self.PYTHONPATH}/local/get_mfa_result.py \
--input_dir={new_dir} \
--mfa_dir={mfa_dir} \
--lang={lang}
# generate durations.txt
python3 {self.PYTHONPATH}/local/generate_duration.py \
--mfa_dir={mfa_dir}
# extract feature
python3 {self.PYTHONPATH}/local/extract_feature.py \
--duration_file="./durations.txt" \
--input_dir={new_dir} \
--dump_dir={dump_dir} \
--pretrained_model_dir={self.pretrained_model_dir}
# create finetune env
python3 {self.PYTHONPATH}/local/prepare_env.py \
--pretrained_model_dir={self.pretrained_model_dir} \
--output_dir={output_dir}
# finetune
python3 {self.PYTHONPATH}/local/finetune.py \
--pretrained_model_dir={self.pretrained_model_dir} \
--dump_dir={dump_dir} \
--output_dir={output_dir} \
--ngpu={ngpu} \
--epoch=100 \
--finetune_config={self.finetune_config}
"""
print(cmd)
return run_cmd(cmd, exp_dir)
def synthesize(self, text, wav_name, out_wav_dir, exp_dir='temp'):
voc = "hifigan_aishell3"
dump_dir = os.path.join(exp_dir, 'dump')
output_dir = os.path.join(exp_dir, 'exp')
text_path = os.path.join(exp_dir, 'sentences.txt')
lang = "zh"
ngpu = get_ngpu()
model_path = f"{output_dir}/checkpoints"
ckpt = find_max_ckpt(model_path)
# 生成对应的语句
with open(text_path, "w", encoding='utf8') as f:
f.write(wav_name + " " + text)
cmd = f"""
FLAGS_allocator_strategy=naive_best_fit \
FLAGS_fraction_of_gpu_memory_to_use=0.01 \
python3 {self.BIN_DIR}/../synthesize_e2e.py \
--am=fastspeech2_aishell3 \
--am_config={self.pretrained_model_dir}/default.yaml \
--am_ckpt={output_dir}/checkpoints/snapshot_iter_{ckpt}.pdz \
--am_stat={self.pretrained_model_dir}/speech_stats.npy \
--voc={voc} \
--voc_config={self.voc_model_dir}/default.yaml \
--voc_ckpt={self.voc_model_dir}/snapshot_iter_2500000.pdz \
--voc_stat={self.voc_model_dir}/feats_stats.npy \
--lang={lang} \
--text={text_path} \
--output_dir={out_wav_dir} \
--phones_dict={dump_dir}/phone_id_map.txt \
--speaker_dict={dump_dir}/speaker_id_map.txt \
--spk_id=0 \
--ngpu={ngpu}
"""
out_path = os.path.join(out_wav_dir, f"{wav_name}.wav")
return run_cmd(cmd, out_path)

@ -0,0 +1,60 @@
import os
import shutil
from .util import get_ngpu
from .util import MAIN_ROOT
from .util import run_cmd
class VoiceCloneGE2E():
def __init__(self):
# Path 到指定路径上
self.BIN_DIR = os.path.join(MAIN_ROOT, "paddlespeech/t2s/exps")
# am
self.am = "fastspeech2_aishell3"
self.am_config = "source/model/fastspeech2_nosil_aishell3_vc1_ckpt_0.5/default.yaml"
self.am_ckpt = "source/model/fastspeech2_nosil_aishell3_vc1_ckpt_0.5/snapshot_iter_96400.pdz"
self.am_stat = "source/model/fastspeech2_nosil_aishell3_vc1_ckpt_0.5/speech_stats.npy"
self.phones_dict = "source/model/fastspeech2_nosil_aishell3_vc1_ckpt_0.5/phone_id_map.txt"
# voc
self.voc = "pwgan_aishell3"
self.voc_config = "source/model/pwg_aishell3_ckpt_0.5/default.yaml"
self.voc_ckpt = "source/model/pwg_aishell3_ckpt_0.5/snapshot_iter_1000000.pdz"
self.voc_stat = "source/model/pwg_aishell3_ckpt_0.5/feats_stats.npy"
# ge2e
self.ge2e_params_path = "source/model/ge2e_ckpt_0.3/step-3000000.pdparams"
def vc(self, text, input_wav, out_wav):
# input wav 需要形成临时单独文件夹
_, full_file_name = os.path.split(input_wav)
ref_audio_dir = os.path.realpath("tmp_dir/ge2e")
if os.path.exists(ref_audio_dir):
shutil.rmtree(ref_audio_dir)
os.makedirs(ref_audio_dir, exist_ok=True)
shutil.copy(input_wav, ref_audio_dir)
output_dir = os.path.dirname(out_wav)
ngpu = get_ngpu()
cmd = f"""
python3 {self.BIN_DIR}/voice_cloning.py \
--am={self.am} \
--am_config={self.am_config} \
--am_ckpt={self.am_ckpt} \
--am_stat={self.am_stat} \
--voc={self.voc} \
--voc_config={self.voc_config} \
--voc_ckpt={self.voc_ckpt} \
--voc_stat={self.voc_stat} \
--ge2e_params_path={self.ge2e_params_path} \
--text="{text}" \
--input-dir={ref_audio_dir} \
--output-dir={output_dir} \
--phones-dict={self.phones_dict} \
--ngpu={ngpu}
"""
output_name = os.path.join(output_dir, full_file_name)
return run_cmd(cmd, output_name=output_name)

@ -0,0 +1,56 @@
import os
import shutil
from .util import get_ngpu
from .util import MAIN_ROOT
from .util import run_cmd
class VoiceCloneTDNN():
def __init__(self):
# Path 到指定路径上
self.BIN_DIR = os.path.join(MAIN_ROOT, "paddlespeech/t2s/exps")
self.am = "fastspeech2_aishell3"
self.am_config = "source/model/fastspeech2_aishell3_ckpt_vc2_1.2.0/default.yaml"
self.am_ckpt = "source/model/fastspeech2_aishell3_ckpt_vc2_1.2.0/snapshot_iter_96400.pdz"
self.am_stat = "source/model/fastspeech2_aishell3_ckpt_vc2_1.2.0/speech_stats.npy"
self.phones_dict = "source/model/fastspeech2_aishell3_ckpt_vc2_1.2.0/phone_id_map.txt"
# voc
self.voc = "pwgan_aishell3"
self.voc_config = "source/model/pwg_aishell3_ckpt_0.5/default.yaml"
self.voc_ckpt = "source/model/pwg_aishell3_ckpt_0.5/snapshot_iter_1000000.pdz"
self.voc_stat = "source/model/pwg_aishell3_ckpt_0.5/feats_stats.npy"
def vc(self, text, input_wav, out_wav):
# input wav 需要形成临时单独文件夹
_, full_file_name = os.path.split(input_wav)
ref_audio_dir = os.path.realpath("tmp_dir/tdnn")
if os.path.exists(ref_audio_dir):
shutil.rmtree(ref_audio_dir)
os.makedirs(ref_audio_dir, exist_ok=True)
shutil.copy(input_wav, ref_audio_dir)
output_dir = os.path.dirname(out_wav)
ngpu = get_ngpu()
cmd = f"""
python3 {self.BIN_DIR}/voice_cloning.py \
--am={self.am} \
--am_config={self.am_config} \
--am_ckpt={self.am_ckpt} \
--am_stat={self.am_stat} \
--voc={self.voc} \
--voc_config={self.voc_config} \
--voc_ckpt={self.voc_ckpt} \
--voc_stat={self.voc_stat} \
--text="{text}" \
--input-dir={ref_audio_dir} \
--output-dir={output_dir} \
--phones-dict={self.phones_dict} \
--use_ecapa=True \
--ngpu={ngpu}
"""
output_name = os.path.join(output_dir, full_file_name)
return run_cmd(cmd, output_name=output_name)

@ -1,4 +1,18 @@
import os
import random import random
import subprocess
import paddle
NOW_FILE_PATH = os.path.dirname(__file__)
MAIN_ROOT = os.path.realpath(os.path.join(NOW_FILE_PATH, "../../../../"))
def get_ngpu():
if paddle.device.get_device() == "cpu":
return 0
else:
return 1
def randName(n=5): def randName(n=5):
@ -11,3 +25,20 @@ def SuccessRequest(result=None, message="ok"):
def ErrorRequest(result=None, message="error"): def ErrorRequest(result=None, message="error"):
return {"code": -1, "result": result, "message": message} return {"code": -1, "result": result, "message": message}
def run_cmd(cmd, output_name):
p = subprocess.Popen(cmd, shell=True)
res = p.wait()
print(cmd)
print("运行结果:", res)
if res == 0:
# 运行成功
if os.path.exists(output_name):
return output_name
else:
# 合成的文件不存在
return None
else:
# 运行失败
return None

@ -0,0 +1,550 @@
import argparse
import base64
import datetime
import json
import os
from typing import List
import aiofiles
import librosa
import soundfile as sf
import uvicorn
from fastapi import FastAPI
from fastapi import UploadFile
from pydantic import BaseModel
from src.ernie_sat import SAT
from src.finetune import FineTune
from src.ge2e_clone import VoiceCloneGE2E
from src.tdnn_clone import VoiceCloneTDNN
from src.util import *
from starlette.responses import FileResponse
from paddlespeech.server.utils.audio_process import float2pcm
# 解析配置
parser = argparse.ArgumentParser(prog='PaddleSpeechDemo', add_help=True)
parser.add_argument(
"--port",
action="store",
type=int,
help="port of the app",
default=8010,
required=False)
args = parser.parse_args()
port = args.port
# 这里会对finetune产生影响所以finetune使用了cmd
vc_model = VoiceCloneGE2E()
vc_model_tdnn = VoiceCloneTDNN()
sat_model = SAT()
ft_model = FineTune()
# 配置文件
tts_config = "conf/tts_online_application.yaml"
asr_config = "conf/ws_conformer_wenetspeech_application_faster.yaml"
asr_init_path = "source/demo/demo.wav"
db_path = "source/db/vc.sqlite"
ie_model_path = "source/model"
# 路径配置
VC_UPLOAD_PATH = "source/wav/vc/upload"
VC_OUT_PATH = "source/wav/vc/out"
FT_UPLOAD_PATH = "source/wav/finetune/upload"
FT_OUT_PATH = "source/wav/finetune/out"
FT_LABEL_PATH = "source/wav/finetune/label.json"
FT_LABEL_TXT_PATH = "source/wav/finetune/labels.txt"
FT_DEFAULT_PATH = "source/wav/finetune/default"
FT_EXP_BASE_PATH = "tmp_dir/finetune"
SAT_UPLOAD_PATH = "source/wav/SAT/upload"
SAT_OUT_PATH = "source/wav/SAT/out"
SAT_LABEL_PATH = "source/wav/SAT/label.json"
# SAT 标注结果初始化
if os.path.exists(SAT_LABEL_PATH):
with open(SAT_LABEL_PATH, "r", encoding='utf8') as f:
sat_label_dic = json.load(f)
else:
sat_label_dic = {}
# ft 标注结果初始化
if os.path.exists(FT_LABEL_PATH):
with open(FT_LABEL_PATH, "r", encoding='utf8') as f:
ft_label_dic = json.load(f)
else:
ft_label_dic = {}
# 新建文件夹
base_sources = [
VC_UPLOAD_PATH,
VC_OUT_PATH,
FT_UPLOAD_PATH,
FT_OUT_PATH,
FT_DEFAULT_PATH,
SAT_UPLOAD_PATH,
SAT_OUT_PATH,
]
for path in base_sources:
os.makedirs(path, exist_ok=True)
#####################################################################
########################### APP初始化 ###############################
#####################################################################
app = FastAPI()
######################################################################
########################### 接口类型 #################################
#####################################################################
# 接口结构
class VcBase(BaseModel):
wavName: str
wavPath: str
class VcBaseText(BaseModel):
wavName: str
wavPath: str
text: str
func: str
class VcBaseSAT(BaseModel):
old_str: str
new_str: str
language: str
function: str
wav: str # base64编码
filename: str
class FTPath(BaseModel):
dataPath: str
class VcBaseFT(BaseModel):
wav: str # base64编码
filename: str
wav_path: str
class VcBaseFTModel(BaseModel):
wav_path: str
class VcBaseFTSyn(BaseModel):
exp_path: str
text: str
######################################################################
########################### 文件列表查询与保存服务 #################################
#####################################################################
def getVCList(path):
VC_FileDict = []
# 查询upload路径下的wav文件名
for root, dirs, files in os.walk(path, topdown=False):
for name in files:
# print(os.path.join(root, name))
VC_FileDict.append({'name': name, 'path': os.path.join(root, name)})
VC_FileDict = sorted(VC_FileDict, key=lambda x: x['name'], reverse=True)
return VC_FileDict
async def saveFiles(files, SavePath):
right = 0
error = 0
error_info = "错误文件:"
for file in files:
try:
if 'blob' in file.filename:
out_file_path = os.path.join(
SavePath,
datetime.datetime.strftime(datetime.datetime.now(),
'%H%M') + randName(3) + ".wav")
else:
out_file_path = os.path.join(SavePath, file.filename)
print("上传文件名:", out_file_path)
async with aiofiles.open(out_file_path, 'wb') as out_file:
content = await file.read() # async read
await out_file.write(content) # async write
# 将文件转成24k, 16bit类型的wav文件
wav, sr = librosa.load(out_file_path, sr=16000)
sf.write(out_file_path, data=wav, samplerate=sr)
right += 1
except Exception as e:
error += 1
error_info = error_info + file.filename + " " + str(e) + "\n"
continue
return f"上传成功:{right}, 上传失败:{error}, 失败原因: {error_info}"
# 音频下载
@app.post("/vc/download")
async def VcDownload(base: VcBase):
if os.path.exists(base.wavPath):
return FileResponse(base.wavPath)
else:
return ErrorRequest(message="下载请求失败,文件不存在")
# 音频下载base64
@app.post("/vc/download_base64")
async def VcDownloadBase64(base: VcBase):
if os.path.exists(base.wavPath):
# 将文件转成16k, 16bit类型的wav文件
wav, sr = librosa.load(base.wavPath, sr=16000)
wav = float2pcm(wav) # float32 to int16
wav_bytes = wav.tobytes() # to bytes
wav_base64 = base64.b64encode(wav_bytes).decode('utf8')
return SuccessRequest(result=wav_base64)
else:
return ErrorRequest(message="播放请求失败,文件不存在")
######################################################################
########################### VC 服务 #################################
#####################################################################
# 上传文件
@app.post("/vc/upload")
async def VcUpload(files: List[UploadFile]):
# res = saveFiles(files, VC_UPLOAD_PATH)
right = 0
error = 0
error_info = "错误文件:"
for file in files:
try:
if 'blob' in file.filename:
out_file_path = os.path.join(
VC_UPLOAD_PATH,
datetime.datetime.strftime(datetime.datetime.now(),
'%H%M') + randName(3) + ".wav")
else:
out_file_path = os.path.join(VC_UPLOAD_PATH, file.filename)
print("上传文件名:", out_file_path)
async with aiofiles.open(out_file_path, 'wb') as out_file:
content = await file.read() # async read
await out_file.write(content) # async write
# 将文件转成24k, 16bit类型的wav文件
wav, sr = librosa.load(out_file_path, sr=16000)
sf.write(out_file_path, data=wav, samplerate=sr)
right += 1
except Exception as e:
error += 1
error_info = error_info + file.filename + " " + str(e) + "\n"
continue
return SuccessRequest(
result=f"上传成功:{right}, 上传失败:{error}, 失败原因: {error_info}")
# 获取文件列表
@app.get("/vc/list")
async def VcList():
res = getVCList(VC_UPLOAD_PATH)
return SuccessRequest(result=res)
# 获取音频文件
@app.post("/vc/file")
async def VcFileGet(base: VcBase):
if os.path.exists(base.wavPath):
return FileResponse(base.wavPath)
else:
return ErrorRequest(result="获取文件失败")
# 删除音频文件
@app.post("/vc/del")
async def VcFileDel(base: VcBase):
if os.path.exists(base.wavPath):
os.remove(base.wavPath)
return SuccessRequest(result="删除成功")
else:
return ErrorRequest(result="删除失败")
# 声音克隆G2P
@app.post("/vc/clone_g2p")
async def VcCloneG2P(base: VcBaseText):
if os.path.exists(base.wavPath):
try:
if base.func == 'ge2e':
wavName = base.wavName
wavPath = os.path.join(VC_OUT_PATH, wavName)
wavPath = vc_model.vc(
text=base.text, input_wav=base.wavPath, out_wav=wavPath)
else:
wavName = base.wavName
wavPath = os.path.join(VC_OUT_PATH, wavName)
wavPath = vc_model_tdnn.vc(
text=base.text, input_wav=base.wavPath, out_wav=wavPath)
if wavPath:
res = {"wavName": wavName, "wavPath": wavPath}
return SuccessRequest(result=res)
else:
return ErrorRequest(message="克隆失败,检查克隆脚本是否有效")
except Exception as e:
print(e)
return ErrorRequest(message="克隆失败,合成过程报错")
else:
return ErrorRequest(message="克隆失败,音频不存在")
######################################################################
########################### SAT 服务 #################################
#####################################################################
# 声音克隆SAT
@app.post("/vc/clone_sat")
async def VcCloneSAT(base: VcBaseSAT):
# 重新整理 sat_label_dict
if base.filename not in sat_label_dic or sat_label_dic[
base.filename] != base.old_str:
sat_label_dic[base.filename] = base.old_str
with open(SAT_LABEL_PATH, "w", encoding='utf8') as f:
json.dump(sat_label_dic, f, ensure_ascii=False, indent=4)
input_file_path = base.wav
# 选择任务
if base.language == "zh":
# 中文
if base.function == "synthesize":
output_file_path = os.path.join(SAT_OUT_PATH,
"sat_syn_zh_" + base.filename)
# 中文克隆
sat_result = sat_model.zh_synthesize_edit(
old_str=base.old_str,
new_str=base.new_str,
input_name=os.path.realpath(input_file_path),
output_name=os.path.realpath(output_file_path),
task_name="synthesize")
elif base.function == "edit":
output_file_path = os.path.join(SAT_OUT_PATH,
"sat_edit_zh_" + base.filename)
# 中文语音编辑
sat_result = sat_model.zh_synthesize_edit(
old_str=base.old_str,
new_str=base.new_str,
input_name=os.path.realpath(input_file_path),
output_name=os.path.realpath(output_file_path),
task_name="edit")
elif base.function == "crossclone":
output_file_path = os.path.join(SAT_OUT_PATH,
"sat_cross_zh_" + base.filename)
# 中文跨语言
sat_result = sat_model.crossclone(
old_str=base.old_str,
new_str=base.new_str,
input_name=os.path.realpath(input_file_path),
output_name=os.path.realpath(output_file_path),
source_lang="zh",
target_lang="en")
else:
return ErrorRequest(
message="请检查功能选项是否正确,仅支持:synthesize, edit, crossclone")
elif base.language == "en":
if base.function == "synthesize":
output_file_path = os.path.join(SAT_OUT_PATH,
"sat_syn_zh_" + base.filename)
# 英文语音克隆
sat_result = sat_model.en_synthesize_edit(
old_str=base.old_str,
new_str=base.new_str,
input_name=os.path.realpath(input_file_path),
output_name=os.path.realpath(output_file_path),
task_name="synthesize")
elif base.function == "edit":
output_file_path = os.path.join(SAT_OUT_PATH,
"sat_edit_zh_" + base.filename)
# 英文语音编辑
sat_result = sat_model.en_synthesize_edit(
old_str=base.old_str,
new_str=base.new_str,
input_name=os.path.realpath(input_file_path),
output_name=os.path.realpath(output_file_path),
task_name="edit")
elif base.function == "crossclone":
output_file_path = os.path.join(SAT_OUT_PATH,
"sat_cross_zh_" + base.filename)
# 英文跨语言
sat_result = sat_model.crossclone(
old_str=base.old_str,
new_str=base.new_str,
input_name=os.path.realpath(input_file_path),
output_name=os.path.realpath(output_file_path),
source_lang="en",
target_lang="zh")
else:
return ErrorRequest(
message="请检查功能选项是否正确,仅支持:synthesize, edit, crossclone")
else:
return ErrorRequest(message="请检查功能选项是否正确,仅支持中文和英文")
if sat_result:
return SuccessRequest(result=sat_result, message="SAT合成成功")
else:
return ErrorRequest(message="SAT 合成失败,请从后台检查错误信息!")
# SAT 文件列表
@app.get("/sat/list")
async def SatList():
res = []
filelist = getVCList(SAT_UPLOAD_PATH)
for fileitem in filelist:
if fileitem['name'] in sat_label_dic:
fileitem['label'] = sat_label_dic[fileitem['name']]
else:
fileitem['label'] = ""
res.append(fileitem)
return SuccessRequest(result=res)
# 上传 SAT 音频
# 上传文件
@app.post("/sat/upload")
async def SATUpload(files: List[UploadFile]):
right = 0
error = 0
error_info = "错误文件:"
for file in files:
try:
if 'blob' in file.filename:
out_file_path = os.path.join(
SAT_UPLOAD_PATH,
datetime.datetime.strftime(datetime.datetime.now(),
'%H%M') + randName(3) + ".wav")
else:
out_file_path = os.path.join(SAT_UPLOAD_PATH, file.filename)
print("上传文件名:", out_file_path)
async with aiofiles.open(out_file_path, 'wb') as out_file:
content = await file.read() # async read
await out_file.write(content) # async write
# 将文件转成24k, 16bit类型的wav文件
wav, sr = librosa.load(out_file_path, sr=16000)
sf.write(out_file_path, data=wav, samplerate=sr)
right += 1
except Exception as e:
error += 1
error_info = error_info + file.filename + " " + str(e) + "\n"
continue
return SuccessRequest(
result=f"上传成功:{right}, 上传失败:{error}, 失败原因: {error_info}")
######################################################################
########################### FinueTune 服务 #################################
#####################################################################
# finetune 文件列表
@app.post("/finetune/list")
async def FineTuneList(Path: FTPath):
dataPath = Path.dataPath
if dataPath == "default":
# 默认路径
FT_PATH = FT_DEFAULT_PATH
else:
FT_PATH = dataPath
res = []
filelist = getVCList(FT_PATH)
for name, value in ft_label_dic.items():
wav_path = os.path.join(FT_PATH, name)
if not os.path.exists(wav_path):
wav_path = ""
d = {'text': value['text'], 'name': name, 'path': wav_path}
res.append(d)
return SuccessRequest(result=res)
# 一键重置,获取新的文件地址
@app.get('/finetune/newdir')
async def FTGetNewDir():
new_path = os.path.join(FT_UPLOAD_PATH, randName(3))
if not os.path.exists(new_path):
os.makedirs(new_path, exist_ok=True)
# 把 labels.txt 复制进去
cmd = f"cp {FT_LABEL_TXT_PATH} {new_path}"
os.system(cmd)
return SuccessRequest(result=new_path)
# finetune 上传文件
@app.post("/finetune/upload")
async def FTUpload(base: VcBaseFT):
try:
# 文件夹是否存在
if not os.path.exists(base.wav_path):
os.makedirs(base.wav_path)
# 保存音频文件
out_file_path = os.path.join(base.wav_path, base.filename)
wav_b = base64.b64decode(base.wav)
async with aiofiles.open(out_file_path, 'wb') as out_file:
await out_file.write(wav_b) # async write
return SuccessRequest(result="上传成功")
except Exception as e:
return ErrorRequest(result="上传失败")
# finetune 微调
@app.post("/finetune/clone_finetune")
async def FTModel(base: VcBaseFTModel):
# 先检查 wav_path 是否有效
if base.wav_path == 'default':
data_path = FT_DEFAULT_PATH
else:
data_path = base.wav_path
if not os.path.exists(data_path):
return ErrorRequest(message="数据文件夹不存在")
data_base = data_path.split(os.sep)[-1]
exp_dir = os.path.join(FT_EXP_BASE_PATH, data_base)
try:
exp_dir = ft_model.finetune(
input_dir=os.path.realpath(data_path),
exp_dir=os.path.realpath(exp_dir))
if exp_dir:
return SuccessRequest(result=exp_dir)
else:
return ErrorRequest(message="微调失败")
except Exception as e:
print(e)
return ErrorRequest(message="微调失败")
# finetune 合成
@app.post("/finetune/clone_finetune_syn")
async def FTSyn(base: VcBaseFTSyn):
try:
if not os.path.exists(base.exp_path):
return ErrorRequest(result="模型路径不存在")
wav_name = randName(5)
wav_path = ft_model.synthesize(
text=base.text,
wav_name=wav_name,
out_wav_dir=os.path.realpath(FT_OUT_PATH),
exp_dir=os.path.realpath(base.exp_path))
if wav_path:
res = {"wavName": wav_name + ".wav", "wavPath": wav_path}
return SuccessRequest(result=res)
else:
return ErrorRequest(message="音频合成失败")
except Exception as e:
return ErrorRequest(message="音频合成失败")
if __name__ == '__main__':
uvicorn.run(app=app, host='0.0.0.0', port=port)

@ -8,6 +8,7 @@
"preview": "vite preview" "preview": "vite preview"
}, },
"dependencies": { "dependencies": {
"@element-plus/icons-vue": "^2.0.9",
"ant-design-vue": "^2.2.8", "ant-design-vue": "^2.2.8",
"axios": "^0.26.1", "axios": "^0.26.1",
"element-plus": "^2.1.9", "element-plus": "^2.1.9",
@ -18,6 +19,7 @@
}, },
"devDependencies": { "devDependencies": {
"@vitejs/plugin-vue": "^2.3.0", "@vitejs/plugin-vue": "^2.3.0",
"vite": "^2.9.0" "vite": "^2.9.13",
"@vue/compiler-sfc": "^3.1.0"
} }
} }

@ -19,6 +19,26 @@ export const apiURL = {
CHAT_SOCKET_RECORD: 'ws://localhost:8010/ws/asr/offlineStream', // ChatBot websocket 接口 CHAT_SOCKET_RECORD: 'ws://localhost:8010/ws/asr/offlineStream', // ChatBot websocket 接口
ASR_SOCKET_RECORD: 'ws://localhost:8010/ws/asr/onlineStream', // Stream ASR 接口 ASR_SOCKET_RECORD: 'ws://localhost:8010/ws/asr/onlineStream', // Stream ASR 接口
TTS_SOCKET_RECORD: 'ws://localhost:8010/ws/tts/online', // Stream TTS 接口 TTS_SOCKET_RECORD: 'ws://localhost:8010/ws/tts/online', // Stream TTS 接口
// voice clone
// Voice Clone
VC_List: '/api/vc/list',
SAT_List: '/api/sat/list',
FineTune_List: '/api/finetune/list',
VC_Upload: '/api/vc/upload',
SAT_Upload: '/api/sat/upload',
FineTune_Upload: '/api/finetune/upload',
FineTune_NewDir: '/api/finetune/newdir',
VC_Download: '/api/vc/download',
VC_Download_Base64: '/api/vc/download_base64',
VC_Del: '/api/vc/del',
VC_CloneG2p: '/api/vc/clone_g2p',
VC_CloneSAT: '/api/vc/clone_sat',
VC_CloneFineTune: '/api/finetune/clone_finetune',
VC_CloneFineTuneSyn: '/api/finetune/clone_finetune_syn',
} }

@ -0,0 +1,88 @@
import axios from 'axios'
import {apiURL} from "./API.js"
// 上传音频-vc
export async function vcUpload(params){
const result = await axios.post(apiURL.VC_Upload, params);
return result
}
// 上传音频-sat
export async function satUpload(params){
const result = await axios.post(apiURL.SAT_Upload, params);
return result
}
// 上传音频-finetune
export async function fineTuneUpload(params){
const result = await axios.post(apiURL.FineTune_Upload, params);
return result
}
// 删除音频
export async function vcDel(params){
const result = await axios.post(apiURL.VC_Del, params);
return result
}
// 获取音频列表vc
export async function vcList(){
const result = await axios.get(apiURL.VC_List);
return result
}
// 获取音频列表Sat
export async function satList(){
const result = await axios.get(apiURL.SAT_List);
return result
}
// 获取音频列表fineTune
export async function fineTuneList(params){
const result = await axios.post(apiURL.FineTune_List, params);
return result
}
// fineTune 一键重置 获取新的文件夹
export async function fineTuneNewDir(){
const result = await axios.get(apiURL.FineTune_NewDir);
return result
}
// 获取音频数据
export async function vcDownload(params){
const result = await axios.post(apiURL.VC_Download, params);
return result
}
// 获取音频数据Base64
export async function vcDownloadBase64(params){
const result = await axios.post(apiURL.VC_Download_Base64, params);
return result
}
// 克隆合成G2P
export async function vcCloneG2P(params){
const result = await axios.post(apiURL.VC_CloneG2p, params);
return result
}
// 克隆合成SAT
export async function vcCloneSAT(params){
const result = await axios.post(apiURL.VC_CloneSAT, params);
return result
}
// 克隆合成 - finetune 微调
export async function vcCloneFineTune(params){
const result = await axios.post(apiURL.VC_CloneFineTune, params);
return result
}
// 克隆合成 - finetune 合成
export async function vcCloneFineTuneSyn(params){
const result = await axios.post(apiURL.VC_CloneFineTuneSyn, params);
return result
}

@ -4,7 +4,7 @@
飞桨-PaddleSpeech 飞桨-PaddleSpeech
</div> </div>
<div className="speech_header_describe"> <div className="speech_header_describe">
PaddleSpeech 是基于飞桨 PaddlePaddle 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欢迎大家Star收藏鼓励 PaddleSpeech 是基于飞桨 PaddlePaddle 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支持语音识别语音合成声纹识别声音分类语音唤醒语音翻译等多种语音任务荣获 NAACL2022 Best Demo Award 如果你喜欢这个示例欢迎在 github star 收藏鼓励
</div> </div>
<div className="speech_header_link_box"> <div className="speech_header_link_box">
<a href="https://github.com/PaddlePaddle/PaddleSpeech" className="speech_header_link" target='_blank' rel='noreferrer' key={index}> <a href="https://github.com/PaddlePaddle/PaddleSpeech" className="speech_header_link" target='_blank' rel='noreferrer' key={index}>

@ -43,6 +43,7 @@
margin-bottom: 40px; margin-bottom: 40px;
display: flex; display: flex;
align-items: center; align-items: center;
margin-top: 40px;
}; };
.speech_header_link { .speech_header_link {
display: block; display: block;

@ -6,6 +6,10 @@ import TTST from './SubMenu/TTS/TTST.vue'
import VPRT from './SubMenu/VPR/VPRT.vue' import VPRT from './SubMenu/VPR/VPRT.vue'
import IET from './SubMenu/IE/IET.vue' import IET from './SubMenu/IE/IET.vue'
import VoiceCloneT from './SubMenu/VoiceClone/VoiceClone.vue'
import ENIRE_SATT from './SubMenu/ENIRE_SAT/ENIRE_SAT.vue'
import FineTuneT from './SubMenu/FineTune/FineTune.vue'
</script> </script>
<template> <template>
@ -37,6 +41,15 @@ import IET from './SubMenu/IE/IET.vue'
<el-tab-pane label="语音指令" key="5"> <el-tab-pane label="语音指令" key="5">
<IET></IET> <IET></IET>
</el-tab-pane> </el-tab-pane>
<el-tab-pane label="一句话合成" key="6">
<VoiceCloneT></VoiceCloneT>
</el-tab-pane>
<el-tab-pane label="小数据微调" key="7">
<FineTuneT></FineTuneT>
</el-tab-pane>
<el-tab-pane label="ENIRE-SAT" key="8">
<ENIRE_SATT></ENIRE_SATT>
</el-tab-pane>
</el-tabs> </el-tabs>
</div> </div>
</div> </div>

@ -58,9 +58,6 @@ export default {
mounted () { mounted () {
this.wsUrl = apiURL.ASR_SOCKET_RECORD this.wsUrl = apiURL.ASR_SOCKET_RECORD
this.ws = new WebSocket(this.wsUrl) this.ws = new WebSocket(this.wsUrl)
if(this.ws.readyState === this.ws.CONNECTING){
this.$message.success("实时识别 Websocket 连接成功")
}
var _that = this var _that = this
this.ws.addEventListener('message', function (event) { this.ws.addEventListener('message', function (event) {
var temp = JSON.parse(event.data); var temp = JSON.parse(event.data);
@ -78,7 +75,7 @@ export default {
// websocket // websocket
// debugger // debugger
if(this.ws.readyState != this.ws.OPEN){ if(this.ws.readyState != this.ws.OPEN){
this.$message.error("websocket 链接失败,请检查链接地址是否正确") this.$message.error("websocket 链接失败,请检查 Websocket 后端服务是否正确开启")
return return
} }

@ -1,298 +0,0 @@
<template>
<div class="chatbox">
<h3>语音聊天</h3>
<div class="home" style="margin:1vw;">
<el-button :type="recoType" @click="startRecorder()" style="margin:1vw;">{{ recoText }}</el-button>
<!-- <el-button :type="playType" @click="playRecorder()" style="margin:1vw;"> {{ playText }}</el-button> -->
<el-button :type="envType" @click="envRecorder()" style="margin:1vw;"> {{ envText }}</el-button>
<!-- <el-button :type="envType" @click="getTts(ttsd)" style="margin:1vw;"> TTS </el-button> -->
<el-button type="warning" @click="clearChat()" style="margin:1vw;"> 清空聊天</el-button>
</div>
<div v-for="Result in allResultList">
<h3>{{Result}}</h3>
</div>
</div>
</template>
<script>
import Recorder from 'js-audio-recorder'
const recorder = new Recorder({
sampleBits: 16, // 8 1616
sampleRate: 16000, // 110251600022050240004410048000chrome48000
numChannels: 1, // 1 2 1
compiling: true
})
export default {
name: 'home',
data () {
return {
recoType: "primary",
recoText: "开始录音",
playType: "success",
playText: "播放录音",
envType: "success",
envText: "环境采样",
asrResultList: [],
nlpResultList: [],
ttsResultList: [],
allResultList: [],
webSocketRes: "websocket",
drawRecordId: null,
onReco: false,
onPlay: false,
onRecoPause: false,
ws: '',
ttsd: "你的名字叫什么,你的名字叫什么,你的名字叫什么你的名字叫什么",
audioCtx: '',
source: '',
typedArray: '',
ttsResult: '',
}
},
mounted () {
//
var AudioContext = window.AudioContext || window.webkitAudioContext;
this.audioCtx = new AudioContext({
latencyHint: 'interactive',
sampleRate: 24000,
});
// play
recorder.onplayend = () => {
this.onPlay = false
this.playText = "播放录音"
this.playType = "success"
this.$nextTick(()=>{})
}
// ws
this.ws = new WebSocket("ws://localhost:8010/ws/asr/offlineStream");
//
var _that = this
this.ws.addEventListener('message', function (event) {
_that.allResultList.push("asr:" + event.data)
_that.$nextTick(()=>{})
_that.getNlp(event.data)
})
},
methods: {
//
clearChat(){
this.allResultList = []
},
//
startRecorder () {
if(!this.onReco){
this.resumeRecordOnline()
recorder.start().then(() => {
setInterval(() => {
//
let newData = recorder.getNextData();
if (!newData.length) {
return;
}
// 1
this.uploadChunk(newData)
}, 500)
}, (error) => {
console.log("录音出错");
})
this.onReco = true
this.recoType = "danger"
this.recoText = "结束录音"
this.$nextTick(()=>{
})
} else {
//
recorder.stop()
this.onReco = false
this.recoType = "primary"
this.recoText = "开始录音"
this.$nextTick(()=>{})
recorder.clear()
// wav,
// const wavs = recorder.getWAVBlob()
// this.uploadFile(wavs, "/api/asr/offline")
// console.log(wavs)
// ,
this.stopRecordOnline()
}
},
//
envRecorder () {
if(!this.onReco){
recorder.start().then(() => {
}, (error) => {
console.log("录音出错");
})
this.onReco = true
this.envType = "danger"
this.envText = "结束采样"
this.$nextTick(()=>{
})
} else {
//
recorder.stop()
this.onReco = false
this.envType = "success"
this.envText = "环境采样"
this.$nextTick(()=>{})
const wavs = recorder.getWAVBlob()
this.uploadFile(wavs, "/api/asr/collectEnv")
}
},
//
playRecorder () {
if(!this.onPlay){
//
recorder.play()
this.onPlay = true
this.playText = "结束播放"
this.playType = "warning"
this.$nextTick(()=>{})
} else {
recorder.stopPlay()
this.onPlay = false
this.playText = "播放录音"
this.playType = "success"
this.$nextTick(()=>{})
}
},
//
async uploadFile(file, post_url){
const formData = new FormData()
formData.append('files', file)
const result = await this.$http.post(post_url, formData);
if (result.data.code === 0) {
this.asrResultList.push(result.data.result)
// this.$message.success(result.data.message);
} else {
this.$message.error(result.data.message);
}
},
// chunk
async uploadChunk(chunkDatas) {
chunkDatas.forEach((chunkData) => {
this.ws.send(chunkData)
})
},
// ,pcm
async stopRecordOnline(){
const result = await this.$http.get("/api/asr/stopRecord");
if (result.data.code === 0) {
console.log("Online 录音停止成功")
} else {
// console.log("chunk ")
}
},
//
async resumeRecordOnline(){
const result = await this.$http.get("/api/asr/resumeRecord");
if (result.data.code === 0) {
console.log("chunk 发送成功")
} else {
// console.log("chunk ")
}
},
// NLP
async getNlp(asrText){
//
this.onRecoPause = true
recorder.pause()
this.stopRecordOnline()
console.log('录音暂停')
const result = await this.$http.post("/api/nlp/chat", { chat: asrText});
if (result.data.code === 0) {
this.allResultList.push("nlp:" + result.data.result)
this.getTts(result.data.result)
// this.$message.success(result.data.message);
} else {
this.$message.error(result.data.message);
}
// console.log("")
},
base64ToUint8Array(base64String) {
const padding = '='.repeat((4 - base64String.length % 4) % 4);
const base64 = (base64String + padding)
.replace(/-/g, '+')
.replace(/_/g, '/');
const rawData = window.atob(base64);
const outputArray = new Uint8Array(rawData.length);
for (let i = 0; i < rawData.length; ++i) {
outputArray[i] = rawData.charCodeAt(i);
}
return outputArray;
},
// TTS
async getTts(nlpText){
// base64
this.ttsResult = await this.$http.post("/api/tts/offline", { text : nlpText});
this.typedArray = this.base64ToUint8Array(this.ttsResult.data.result)
// console.log("chat", this.typedArray.buffer)
this.playAudioData( this.typedArray.buffer )
},
// play
playAudioData( wav_buffer ) {
this.audioCtx.decodeAudioData(wav_buffer, buffer => {
this.source = this.audioCtx.createBufferSource();
this.source.onended = () => {
//
if(this.onRecoPause){
console.log("恢复录音")
this.onRecoPause = false
//
recorder.resume()
//
this.resumeRecordOnline()
}
}
this.source.buffer = buffer;
this.source.connect(this.audioCtx.destination);
this.source.start();
}, function(e) {
Recorder.throwError(e);
});
}
},
}
</script>
<style lang='less' scoped>
.chatbox {
border: 4px solid #F00;
// position: fixed;
width: 100%;
height: 20%;
overflow: auto;
}
</style>

@ -91,6 +91,10 @@ export default {
methods: { methods: {
// //
startRecorder(){ startRecorder(){
if(this.ws.readyState != this.ws.OPEN){
this.$message.error("websocket 链接失败,请检查 Websocket 后端服务是否正确开启")
return
}
this.allResultList = [] this.allResultList = []
if(!this.onReco){ if(!this.onReco){
this.asrResult = this.speakingText this.asrResult = this.speakingText

@ -0,0 +1,487 @@
<template>
<div class="sat">
<el-row :gutter="20">
<el-col :span="12"><div class="grid-content ep-bg-purple" />
<el-row :gutter="60" class="btn_row_wav" justify="center">
<el-button class="ml-3" v-if="onEnrollRec === 0" @click="startRecorderEnroll()" type="primary"></el-button>
<el-button class="ml-3" v-else-if="onEnrollRec === 1" @click="stopRecorderEnroll()" type="danger">停止录音</el-button>
<el-button class="ml-3" v-else @click="uploadRecord()" type="success">上传录音</el-button>
<a>&#12288</a>
<el-upload
:multiple="false"
:accept="'.wav'"
:auto-upload="false"
:on-change="handleChange"
:show-file-list="false"
>
<el-button class="ml-3" type="success">上传音频文件</el-button>
</el-upload>
</el-row>
<div class="recording_table">
<el-table :data="vcDatas" border class="recording_table_box" scrollbar-always-on max-height="250px">
<!-- <el-table-column prop="wavId" label="序号" width="60"/> -->
<el-table-column prop="wavName" label="文件名" width="150"/>
<el-table-column label="文本">
<template #default="scope">
<el-input
v-model="scope.row.label"
:autosize="{ minRows: 8, maxRows: 13 }"
placeholder="Please input"
/>
</template>
</el-table-column>
<el-table-column label="操作" width="80">
<template #default="scope">
<div class="flex justify-space-between mb-4 flex-wrap gap-4">
<a @click="PlayTable(scope.row.wavId)"><el-icon><VideoPlay /></el-icon></a>
<a>&#12288</a>
<a @click="delWav(scope.row.wavId)"><el-icon><DeleteFilled /></el-icon></a>
</div>
</template>
</el-table-column>
<el-table-column fixed="right" label="选择" width="70">
<template #default="scope">
<el-switch v-model="scope.row.status" @click="choseWav(scope.row.wavId)"/>
</template>
</el-table-column>
</el-table>
</div>
</el-col>
<el-col :span="8"><div class="grid-content ep-bg-purple" />
<el-space direction="vertical">
<el-card class="box-card" style="width: 250px; height:310px">
<template #header>
<div class="card-header">
<span>功能选择</span>
</div>
</template>
<el-radio-group v-model="funcMode">
<el-radio label="1" size="middle" border style="margin-bottom: 10px">个性化语音合成</el-radio>
<el-input
v-if="funcMode === '1'"
v-model="ttsText"
:autosize="{ minRows: 2, maxRows: 2 }"
type="textarea"
placeholder="Please input"
style="margin-bottom: 10px"
/>
<el-radio label="2" size="middle" border style="margin-bottom: 10px">跨语言语音合成</el-radio>
<el-input
v-if="funcMode === '2'"
v-model="ttsText"
:autosize="{ minRows: 2, maxRows: 2 }"
type="textarea"
placeholder="Please input"
style="margin-bottom: 10px"
/>
<el-radio label="3" size="middle" border style="margin-bottom: 10px">语音编辑</el-radio>
<el-input
v-if="funcMode === '3'"
v-model="ttsText"
:autosize="{ minRows: 2, maxRows: 2 }"
type="textarea"
placeholder="Please input"
style="margin-bottom: 10px"
/>
</el-radio-group>
</el-card>
</el-space>
</el-col>
<el-col :span="4"><div class="grid-content ep-bg-purple" />
<div class="play_board">
<el-space direction="vertical">
<el-row :gutter="20">
<el-button size="large" v-if="onSyn === 0" type="primary" @click="SatSyn()"></el-button>
<el-button size="large" v-else :loading-icon="Eleme" type="danger">合成中</el-button>
</el-row>
<el-row :gutter="20">
<el-button v-if='this.cloneWav' type="success" @click="PlaySyn()"></el-button>
<el-button v-else disabled type="primary" @click="PlaySyn()"></el-button>
<el-button v-if='this.cloneWav' type="primary" @click="downLoadCloneWav()"></el-button>
<el-button v-else disabled type="primary" @click="downLoadCloneWav()"></el-button>
</el-row>
</el-space>
</div>
</el-col>
</el-row>
</div>
</template>
<script>
import { vcCloneSAT, vcDownload, vcDownloadBase64, satUpload, satList, vcDel } from '../../../api/ApiVC'
import Recorder from 'js-audio-recorder'
let audioCtx = new AudioContext({
latencyHint: 'interactive',
sampleRate: 24000,
});
//
const recorder = new Recorder({
sampleBits: 16, // 8 1616
sampleRate: 16000, // 110251600022050240004410048000chrome48000
numChannels: 1, // 1 2 1
compiling: true
})
export default {
name:"",
data(){
return {
uploadStatus : 0,
recognitionStatus : 0,
asrResult : "",
indicator : "",
filename: "",
upfile: "",
mode: 1,
language: 1,
wav_input: "卡尔普陪外孙玩滑梯",
new_input: "卡尔普陪外孙打滑梯",
received_file:"",
// 线
onEnrollRec: 0,
onSyn:0,
vcDatas: [],
funcMode: '1',
selected_Id: -1,
ttsText: '',
cloneWav: '',
wav:''
}
},
mounted () {
this.GetList()
},
methods:{
//
async GetList(){
this.vcDatas =[]
const result = await satList();
console.log("List: ", result);
for(let i=0; i < result.data.result.length; i++){
this.vcDatas.push({
wavName: result.data.result[i]['name'],
wavId: i,
wavPath: result.data.result[i]['path'],
status: false,
label: result.data.result[i]['label']
})
}
console.log("vcDatas: ", this.vcDatas);
this.$nextTick(()=>{})
},
//
async handleChange(file, fileList){
for(let i=0; i<fileList.length; i++){
this.uploadFile(fileList[i])
}
this.GetList()
},
async uploadFile(file){
let formData = new FormData();
formData.append('files', file.raw);
const result = await satUpload(formData);
if (result.data.code === 0) {
this.$message.success("音频上传成功")
} else {
this.$message.error("音频上传失败")
}
},
//
startRecorderEnroll(){
this.onEnrollRec = 1
recorder.clear()
recorder.start()
},
//
stopRecorderEnroll(){
this.onEnrollRec = 2
recorder.stop()
this.wav = recorder.getWAVBlob()
},
//
async uploadRecord(){
this.onEnrollRec = 0
if(this.wav === ""){
this.$message.error("未检测到录音,录音失败,请重新录制")
return
} else {
if(this.wav === ''){
this.$message.error("请先完成录音");
this.onEnrollRec = 0
return
} else {
let formData = new FormData();
formData.append('files', this.wav);
const result = await satUpload(formData);
console.log(result)
this.GetList()
}
this.$message.success("录音上传成功")
}
},
//
async delWav(wavId){
console.log('wavId', wavId)
//
const result = await vcDel(
{
wavName: this.vcDatas[wavId]['wavName'],
wavPath: this.vcDatas[wavId]['wavPath']
}
);
if(!result.data.code){
this.$message.success("删除成功")
} else {
this.$message.error(result.data.msg)
}
this.GetList()
this.reset()
},
//
async PlayTable(wavId){
this.Play(this.vcDatas[wavId])
},
//
async Play(wavBase){
//
const result = await vcDownloadBase64(wavBase);
// console.log('play result', result)
if (result.data.code === 0) {
// base
let typedArray = this.base64ToUint8Array(result.data.result)
// wav
let view = new DataView(typedArray.buffer);
view = Recorder.encodeWAV(view, 16000, 16000, 1, 16, true);
//
this.playAudioData(view.buffer);
};
},
// chose wav
choseWav(wavId){
this.cloneWav = ''
this.nowFile = this.vcDatas[wavId].wavName
this.nowIndex = wavId
// only wavId is true else false
for(let i=0; i<this.vcDatas.length; i++){
if(i==wavId){
this.vcDatas[wavId].status = true
this.selected_Id = wavId
this.ttsText = this.vcDatas[wavId]['label']
} else {
this.vcDatas[i].status = false
}
}
this.$nextTick(()=>{})
},
//
playAudioData(wav_buffer){
audioCtx.decodeAudioData(wav_buffer, buffer => {
let source = audioCtx.createBufferSource();
source.buffer = buffer
source.connect(audioCtx.destination);
source.start();
}, function (e) {
});
},
base64ToUint8Array(base64String){
const padding = '='.repeat((4 - base64String.length % 4) % 4);
const base64 = (base64String + padding)
.replace(/-/g, '+')
.replace(/_/g, '/');
const rawData = window.atob(base64);
const outputArray = new Uint8Array(rawData.length);
for (let i = 0; i < rawData.length; ++i) {
outputArray[i] = rawData.charCodeAt(i);
}
return outputArray;
},
//
hasChinese(str) {
return /[\u4E00-\u9FA5]+/g.test(str)
},
// SAT
async SatSyn(){
// select id
if(this.selected_Id < 0){
return this.$message.error("请先选择音频文件!")
}
//
if(!this.vcDatas[this.selected_Id]['label']){
return this.$message.error("音频对应文本不可以为空!")
}
//
if(!this.ttsText){
return this.$message.error("合成文本不可以为空!")
}
//
this.onSyn = 1
// clone wav
this.cloneWav = ""
const old_str = this.vcDatas[this.selected_Id]['label']
const new_str = this.ttsText
let language = ""
//
if(this.hasChinese(old_str)){
language = "zh"
} else{
language = "en"
}
//
let func = ""
if(this.funcMode === '1') {
func = "synthesize"
} else if(this.funcMode === '2'){
func = "crossclone"
} else {
func = "edit"
}
let wav_path = this.vcDatas[this.selected_Id]['wavPath']
let filename = this.vcDatas[this.selected_Id]['wavName']
const data = {
old_str: old_str,
new_str: new_str,
language: language,
function: func,
wav: wav_path,
filename: filename
}
console.log("sat data: ", data)
// sat
const result = await vcCloneSAT(data)
//
this.onSyn = 0
console.log(result);
// debugger
if (result.data.code === 0) {
this.$message.success(result.data.message)
//
this.cloneWav = result.data.result
console.log("cloneWave", this.cloneWav);
} else {
this.$message.error(result.data.message)
};
},
//
//
async PlaySyn(){
//
const data = {
wavName: "sat_"+this.filename,
wavPath: this.cloneWav
}
const result = await vcDownloadBase64(data);
// console.log('play result', result)
if (result.data.code === 0) {
// base
let typedArray = this.base64ToUint8Array(result.data.result)
// wav
let view = new DataView(typedArray.buffer);
view = Recorder.encodeWAV(view, 16000, 16000, 1, 16, true);
//
this.playAudioData(view.buffer);
};
},
//
async downLoadCloneWav(){
if(this.cloneWav === ""){
this.$message.error("音频合成完毕后再下载!")
} else {
// const result = await vcDownload(this.cloneWav);
//
const data = {
wavName: "sat_"+this.filename,
wavPath: this.cloneWav
}
const result = await vcDownloadBase64(data);
let view;
// console.log('play result', result)
if (result.data.code === 0) {
// base
let typedArray = this.base64ToUint8Array(result.data.result)
// wav
view = new DataView(typedArray.buffer);
view = Recorder.encodeWAV(view, 16000, 16000, 1, 16, true);
//
// this.playAudioData(view.buffer);
}
console.log(view.buffer)
// debugger
const blob = new Blob([view.buffer], { type: 'audio/wav' });
const fileName = new Date().getTime() + '.wav';
const down = document.createElement('a');
down.download = fileName;
down.style.display = 'none';//,
down.href = URL.createObjectURL(blob);
document.body.appendChild(down);
down.click();
URL.revokeObjectURL(down.href); // URL
document.body.removeChild(down);//
}
},
}
}
</script>
<style lang="less" scoped>
// @import "./style.less";
.sat {
width: 1200px;
height: 410px;
background: #FFFFFF;
padding: 5px 80px 56px 80px;
box-sizing: border-box;
}
.el-row {
margin-bottom: 20px;
}
.grid-content {
border-radius: 4px;
min-height: 36px;
}
.play_board{
height: 100%;
display: flex;
align-items: center;
}
</style>

@ -0,0 +1,427 @@
<template>
<div class="finetune">
<el-row :gutter="20">
<el-col :span="12"><div class="grid-content ep-bg-purple" />
<el-row :gutter="60" class="btn_row_wav" justify="center">
<el-button class="ml-3" @click="clearAll()" type="primary">一键重置</el-button>
<el-button class="ml-3" @click="resetDefault()" type="primary">默认示例</el-button>
<el-button v-if='onFinetune === 0' class="ml-3" @click="fineTuneModel()" type="primary">一键微调</el-button>
<el-button v-else-if='onFinetune === 1' class="ml-3" @click="fineTuneModel()" type="danger">微调中</el-button>
<el-button v-else-if='onFinetune === 2' class="ml-3" @click="resetFinetuneBtn()" type="success">微调成功</el-button>
<el-button v-else class="ml-3" @click="resetFinetuneBtn()" type="success">微调失败</el-button>
<!-- <el-button class="ml-3" @click="chooseHistory()" type="warning">历史数据选择</el-button> -->
</el-row>
<div class="recording_table">
<el-table :data="vcDatas" border class="recording_table_box" scrollbar-always-on max-height="250px">
<el-table-column prop="wavId" label="序号" width="60"/>
<el-table-column prop="text" label="文本" />
<el-table-column label="音频" width="80">
<template #default="scope">
<a v-if="scope.row.wavPath != ''">{{ scope.row.wavName }}</a>
<a v-else>
<el-button class="ml-3" v-if="onEnrollRec === 0" @click="startRecorderEnroll()" type="primary" circle>
<el-icon><Microphone /></el-icon>
</el-button>
<el-button class="ml-3" v-else-if="onEnrollRec === 1" @click="stopRecorderEnroll()" type="danger" circle>
<el-icon><Microphone /></el-icon>
</el-button>
<el-button class="ml-3" v-else @click="uploadRecord(scope.row.wavId)" type="success" circle>
<el-icon><Upload /></el-icon>
</el-button>
</a>
</template>
</el-table-column>
<el-table-column label="操作" width="80" fixed="right">
<template #default="scope">
<div class="flex justify-space-between mb-4 flex-wrap gap-4">
<a @click="PlayTable(scope.row.wavId)"><el-icon><VideoPlay /></el-icon></a>
<a>&#12288</a>
<a @click="delWav(scope.row.wavId)"><el-icon><DeleteFilled /></el-icon></a>
</div>
</template>
</el-table-column>
</el-table>
</div>
</el-col>
<el-col :span="8"><div class="grid-content ep-bg-purple" />
<el-space direction="vertical">
<el-card class="box-card" style="width: 250px; height:310px">
<template #header>
<div class="card-header">
<span>试验路径</span>
<el-input
v-model="expPath"
:autosize="{ minRows: 2, maxRows: 3 }"
type="textarea"
placeholder="一键微调自动生成,可使用历史试验路径"
/>
</div>
</template>
<span>请输入中文文本</span>
<el-input
v-model="ttsText"
:autosize="{ minRows: 5, maxRows: 6 }"
type="textarea"
placeholder="请输入待合成文本"
/>
</el-card>
</el-space>
</el-col>
<el-col :span="4"><div class="grid-content ep-bg-purple" />
<div class="play_board">
<el-space direction="vertical">
<el-row :gutter="20">
<el-button size="large" v-if="onSyn === 0" type="primary" @click="fineTuneSyn()"></el-button>
<el-button size="large" v-else :loading-icon="Eleme" type="danger">合成中</el-button>
</el-row>
<el-row :gutter="20">
<el-button v-if='this.cloneWav' type="success" @click="PlaySyn()"></el-button>
<el-button v-else disabled type="primary" @click="PlaySyn()"></el-button>
<el-button v-if='this.cloneWav' type="primary" @click="downLoadCloneWav()"></el-button>
<el-button v-else disabled type="primary" @click="downLoadCloneWav()"></el-button>
</el-row>
</el-space>
</div>
</el-col>
</el-row>
</div>
</template>
<script>
import Recorder from 'js-audio-recorder'
import { vcDownload, vcDownloadBase64, vcCloneFineTune, vcCloneFineTuneSyn, fineTuneList, vcDel, fineTuneUpload, fineTuneNewDir } from '../../../api/ApiVC';
//
const recorder = new Recorder({
sampleBits: 16, // 8 1616
sampleRate: 16000, // 110251600022050240004410048000chrome48000
numChannels: 1, // 1 2 1
compiling: true
})
//
const audioCtx = new AudioContext({
latencyHint: 'interactive',
sampleRate: 16000,
});
function blobToDataURL(blob, callback) {
let a = new FileReader();
a.onload = function (e) { callback(e.target.result); }
a.readAsDataURL(blob);
}
export default {
data(){
return {
vcDatas:[],
defaultDataPath: 'default',
nowDataPath: '',
expPath: '',
wav: '',
wav_base64: '',
ttsText: '欢迎使用飞桨语音套件',
cloneWav: '',
onEnrollRec: 0, //
onFinetune: 0, //
onSyn: 0, //
}
},
mounted () {
this.nowDataPath = this.defaultDataPath
this.GetList()
},
methods: {
// btn
resetFinetuneBtn(){
this.onFinetune = 0
},
//
async clearAll(){
this.vcDatas = []
const result = await fineTuneNewDir()
console.log("clearALL: ", result.data.result);
this.nowDataPath = result.data.result
this.expPath = ''
this.onFinetune = 0
await this.GetList()
},
//
async resetDefault(){
this.nowDataPath = this.defaultDataPath
await this.GetList()
this.expPath = ''
},
//
startRecorderEnroll(){
this.onEnrollRec = 1
recorder.clear()
recorder.start()
},
//
stopRecorderEnroll(){
this.onEnrollRec = 2
recorder.stop()
this.wav = recorder.getWAVBlob()
},
//
async uploadRecord(wavId){
this.onEnrollRec = 0
if(this.wav === ""){
this.$message.error("未检测到录音,录音失败,请重新录制")
return
} else {
if(this.wav === ''){
this.$message.error("请先完成录音");
this.onEnrollRec = 0
return
} else {
let fileRes = ""
let fileString = ""
fileRes = await this.readFile(this.wav);
fileString = fileRes.result;
const audioBase64type = (fileString.match(/data:[^;]*;base64,/))?.[0] ?? '';
const isBase64 = !!fileString.match(/data:[^;]*;base64,/);
const uploadBase64 = fileString.substr(audioBase64type.length);
//
const data = {
'wav': uploadBase64,
'filename': this.vcDatas[wavId]['wavName'],
'wav_path': this.nowDataPath
}
const result = await fineTuneUpload(data);
console.log(result)
this.GetList()
}
this.$message.success("录音上传成功")
}
},
// Blob
readFile(file) {
return new Promise((resolve, reject) => {
const fileReader = new FileReader();
fileReader.onload = function () {
resolve(fileReader);
};
fileReader.onerror = function (err) {
reject(err);
};
fileReader.readAsDataURL(file);
});
},
//
async GetList(){
this.vcDatas = []
const result = await fineTuneList({
dataPath: this.nowDataPath
});
console.log(result, result.data.result);
for(let i=0; i<result.data.result.length; i++){
this.vcDatas.push({
wavId: i,
text: result.data.result[i]['text'],
wavName: result.data.result[i]['name'],
wavPath: result.data.result[i]['path'],
})
}
this.$nextTick(()=>{})
},
//
playAudioData( wav_buffer ) {
audioCtx.decodeAudioData(wav_buffer, buffer => {
var source = audioCtx.createBufferSource();
source.buffer = buffer;
source.connect(audioCtx.destination);
source.start();
}, function(e) {
Recorder.throwError(e);
})
},
// base64
base64ToUint8Array(base64String) {
const padding = '='.repeat((4 - base64String.length % 4) % 4);
const base64 = (base64String + padding)
.replace(/-/g, '+')
.replace(/_/g, '/');
const rawData = window.atob(base64);
const outputArray = new Uint8Array(rawData.length);
for (let i = 0; i < rawData.length; ++i) {
outputArray[i] = rawData.charCodeAt(i);
}
return outputArray;
},
//
async PlayTable(wavId){
this.Play(this.vcDatas[wavId])
},
//
async PlaySyn(){
if(this.cloneWav === ""){
this.$message.error("请合成音频后再播放!!")
return
} else {
this.Play(this.cloneWav)
}
},
//
async Play(wavBase){
//
const result = await vcDownloadBase64(wavBase);
// console.log('play result', result)
if (result.data.code === 0) {
// base
let typedArray = this.base64ToUint8Array(result.data.result)
// wav
let view = new DataView(typedArray.buffer);
view = Recorder.encodeWAV(view, 16000, 16000, 1, 16, true);
//
this.playAudioData(view.buffer);
} else {
this.$message.error("获取音频文件失败")
}
},
//
async downLoadCloneWav(){
if(this.cloneWav === ""){
this.$message.error("音频合成完毕后再下载!")
} else {
// const result = await vcDownload(this.cloneWav);
//
const result = await vcDownloadBase64(this.cloneWav);
let view;
// console.log('play result', result)
if (result.data.code === 0) {
// base
let typedArray = this.base64ToUint8Array(result.data.result)
// wav
view = new DataView(typedArray.buffer);
view = Recorder.encodeWAV(view, 16000, 16000, 1, 16, true);
//
// this.playAudioData(view.buffer);
}
console.log(view.buffer)
// debugger
const blob = new Blob([view.buffer], { type: 'audio/wav' });
const fileName = new Date().getTime() + '.wav';
const down = document.createElement('a');
down.download = fileName;
down.style.display = 'none';//,
down.href = URL.createObjectURL(blob);
document.body.appendChild(down);
down.click();
URL.revokeObjectURL(down.href); // URL
document.body.removeChild(down);//
}
},
//
async delWav(wavId){
if(this.nowDataPath === this.defaultDataPath){
this.$message.error("默认音频不允许删除,可以一键重置,重新录音")
return
}
console.log('wavId', wavId)
//
const result = await vcDel(
{
wavName: this.vcDatas[wavId]['wavName'],
wavPath: this.vcDatas[wavId]['wavPath']
}
);
if(!result.data.code){
this.$message.success("删除成功")
this.GetList()
} else {
this.$message.error("文件删除失败")
}
},
//
async fineTuneModel(){
//
for(let i=0; i < this.vcDatas.length; i++){
if(this.vcDatas['wavPath'] === ''){
return this.$message.error("还有录音未完成,请先完成录音!")
}
}
this.onFinetune = 1
const result = await vcCloneFineTune(
{
wav_path: this.nowDataPath,
}
);
if(!result.data.code){
this.onFinetune = 2
this.expPath = result.data.result
console.log("this.expPath: ", this.expPath)
this.$message.success("小数据微调成功")
} else {
this.onFinetune = 3
this.$message.error(result.data.msg)
}
},
//
async fineTuneSyn(){
if(!this.expPath){
return this.$message.error("请先微调生成模型后再生成!")
}
//
this.onSyn = 1
const result = await vcCloneFineTuneSyn(
{
exp_path: this.expPath,
text: this.ttsText
}
);
this.onSyn = 0
if(!result.data.code){
this.cloneWav = result.data.result
console.log("clone wav: ", this.cloneWav)
this.$message.success("音色克隆成功")
} else {
this.$message.error(result.data.msg)
}
this.$nextTick(()=>{})
}
},
};
</script>
<style lang="less" scoped>
// @import "./style.less";
.finetune {
width: 1200px;
height: 410px;
background: #FFFFFF;
padding: 5px 80px 56px 80px;
box-sizing: border-box;
}
.el-row {
margin-bottom: 20px;
}
.grid-content {
border-radius: 4px;
min-height: 36px;
}
.play_board{
height: 100%;
display: flex;
align-items: center;
}
</style>

@ -1,125 +0,0 @@
<template>
<div class="iebox">
<h1>信息抽取体验</h1>
<el-button :type="recoType" @click="startRecorder()" style="margin:1vw;">{{ recoText }}</el-button>
<h3>识别结果: {{ asrResultOffline }}</h3>
<h4>时间{{ time }}</h4>
<h4>出发地{{ outset }}</h4>
<h4>目的地{{ destination }}</h4>
<h4>费用{{ amount }}</h4>
</div>
</template>
<script>
import Recorder from 'js-audio-recorder'
const recorder = new Recorder({
sampleBits: 16, // 8 1616
sampleRate: 16000, // 110251600022050240004410048000chrome48000
numChannels: 1, // 1 2 1
compiling: true
})
export default {
name: "IE",
data(){
return {
streamAsrResult: '',
recoType: "primary",
recoText: "开始录音",
playType: "success",
asrResultOffline: '',
onReco: false,
ws:'',
time: '',
outset: '',
destination: '',
amount: ''
}
},
methods: {
startRecorder () {
if(!this.onReco){
recorder.clear()
recorder.start().then(() => {
}, (error) => {
console.log("录音出错");
})
this.onReco = true
this.recoType = "danger"
this.recoText = "结束录音"
this.time = ''
this.outset=''
this.destination = ''
this.amount = ''
this.$nextTick(()=>{
})
} else {
//
recorder.stop()
this.onReco = false
this.recoType = "primary"
this.recoText = "开始录音"
this.$nextTick(()=>{})
// wav,
const wavs = recorder.getWAVBlob()
this.uploadFile(wavs, "/api/asr/offline")
}
},
async uploadFile(file, post_url){
const formData = new FormData()
formData.append('files', file)
const result = await this.$http.post(post_url, formData);
if (result.data.code === 0) {
this.asrResultOffline = result.data.result
this.$nextTick(()=>{})
this.$message.success(result.data.message);
this.informationExtract()
} else {
this.$message.error(result.data.message);
}
},
async informationExtract(){
const postdata = {
chat: this.asrResultOffline
}
const result = await this.$http.post('/api/nlp/ie', postdata)
console.log("ie", result)
if(result.data.result[0]['时间']){
this.time = result.data.result[0]['时间'][0]['text']
}
if(result.data.result[0]['出发地']){
this.outset = result.data.result[0]['出发地'][0]['text']
}
if(result.data.result[0]['目的地']){
this.destination = result.data.result[0]['目的地'][0]['text']
}
if(result.data.result[0]['费用']){
this.amount = result.data.result[0]['费用'][0]['text']
}
}
},
}
</script>
<style lang="less" scoped>
.iebox {
border: 4px solid #F00;
top:80%;
width: 100%;
height: 20%;
overflow: auto;
}
</style>

@ -228,6 +228,10 @@ export default {
}, },
// WS // WS
async getTtsChunkWavWS(){ async getTtsChunkWavWS(){
if(this.ws.readyState != this.ws.OPEN){
this.$message.error("websocket 链接失败,请检查 Websocket 后端服务是否正确开启")
return
}
// chunks // chunks
chunks = [] chunks = []
chunk_index = 0 chunk_index = 0

@ -1,178 +0,0 @@
<template>
<div class="vprbox">
<div>
<h1>声纹识别展示</h1>
<el-input
v-model="spk_id"
class="w-50 m-2"
size="large"
placeholder="spk_id"
/>
<el-button :type="recoType" @click="startRecorder()" style="margin:1vw;">{{ recoText }}</el-button>
<el-button type="primary" @click="Enroll(spk_id)" style="margin:1vw;"> 注册 </el-button>
<el-button type="primary" @click="Recog()" style="margin:1vw;"> 识别 </el-button>
</div>
<div>
<h2>声纹得分结果</h2>
<el-table :data="score_result" style="width: 40%">
<el-table-column prop="spkId" label="spk_id" />
<el-table-column prop="score" label="score" />
</el-table>
</div>
<div>
<h2>声纹数据列表</h2>
<el-table :data="vpr_datas" style="width: 40%">
<el-table-column prop="spkId" label="spk_id" />
<el-table-column label="wav">
<template #default="scope2">
<audio :src="'/VPR/vpr/data/?vprId='+scope2.row.vprId" controls>
</audio>
</template>
</el-table-column>
<el-table-column fixed="right" label="Operations">
<template #default="scope">
<el-button @click="Del(scope.row.spkId)" type="text" size="small">Delete</el-button>
</template>
</el-table-column>
</el-table>
</div>
</div>
</template>
<script>
import Recorder from 'js-audio-recorder'
const recorder = new Recorder({
sampleBits: 16, // 8 1616
sampleRate: 16000, // 110251600022050240004410048000chrome48000
numChannels: 1, // 1 2 1
compiling: true
})
export default {
name: "VPR",
data () {
return {
url_enroll: '/VPR/vpr/enroll', //
url_recog: '/VPR/vpr/recog', //
url_del: '/VPR/vpr/del', //
url_list: '/VPR/vpr/list', //
url_data: '/VPR/vpr/data', //
spk_id: 'sss',
onRecord: false,
recoType: "primary",
recoText: "开始录音",
wav: '',
score_result: [],
vpr_datas: []
}
},
mounted () {
this.GetList()
},
methods: {
startRecorder () {
this.score_result = []
if(!this.onReco){
recorder.start().then(() => {
}, (error) => {
console.log("录音出错");
})
this.onReco = true
this.recoType = "danger"
this.recoText = "结束录音"
this.$nextTick(()=>{
})
} else {
//
recorder.stop()
this.onReco = false
this.recoType = "primary"
this.recoText = "开始录音"
this.$nextTick(()=>{})
// wav,
this.wav = recorder.getWAVBlob()
}
},
async Enroll(spk_id){
if(this.wav === ''){
this.$message.error("请先完成录音");
return
}
let formData = new FormData()
formData.append('spk_id', this.spk_id)
formData.append('audio', this.wav)
console.log("formData", formData)
console.log("spk_id", this.spk_id)
const result = await this.$http.post(this.url_enroll, formData);
if(result.data.status){
this.$message.success("声纹注册成功")
} else {
this.$message.error(result.data.msg)
}
console.log(result)
this.GetList()
},
async Recog(){
this.score_result = []
if(this.wav === ''){
this.$message.error("请先完成录音");
return
}
let formData = new FormData()
formData.append('audio', this.wav)
const result = await this.$http.post(this.url_recog, formData);
console.log(result)
result.data.forEach(dat => {
this.score_result.push({
spkId: dat[0],
score: dat[1][1]
})
});
},
async Del(spkId){
console.log('spkId', spkId)
//
const result = await this.$http.post(this.url_del, {spk_id: spkId});
if(result.data.status){
this.$message.success("删除成功")
} else {
this.$message.error(result.data.msg)
}
this.GetList()
},
async GetList(){
this.vpr_datas =[]
const result = await this.$http.get(this.url_list);
console.log("list", result)
for(let i=0; i<result.data[0].length; i++){
this.vpr_datas.push({
spkId: result.data[0][i],
vprId: result.data[1][i]
})
}
this.$nextTick(()=>{})
},
GetData(){},
},
}
</script>
<style lang='less' scoped>
.vprbox {
border: 4px solid #F00;
// position: fixed;
top:60%;
width: 100%;
height: 20%;
overflow: auto;
}
</style>

@ -216,12 +216,15 @@ export default {
formData.append('audio', this.wav) formData.append('audio', this.wav)
const result = await vprEnroll(formData) const result = await vprEnroll(formData)
if (!result){
this.$message.error("请检查后端服务是否正确开启")
return
}
if(result.data.status){ if(result.data.status){
this.$message.success("声纹注册成功") this.$message.success("声纹注册成功")
} else { } else {
this.$message.error(result.data.msg) this.$message.error(result.data.msg)
} }
// console.log(result)
this.GetList() this.GetList()
this.wav = '' this.wav = ''
this.randomSpkId() this.randomSpkId()

@ -0,0 +1,380 @@
<template>
<div class="voiceclone">
<el-row :gutter="20">
<el-col :span="12"><div class="grid-content ep-bg-purple" />
<el-row :gutter="60" class="btn_row_wav" justify="center">
<el-button class="ml-3" v-if="onEnrollRec === 0" @click="startRecorderEnroll()" type="primary"></el-button>
<el-button class="ml-3" v-else-if="onEnrollRec === 1" @click="stopRecorderEnroll()" type="danger">停止录音</el-button>
<el-button class="ml-3" v-else @click="uploadRecord()" type="success">上传录音</el-button>
<a>&#12288</a>
<el-upload
:multiple="false"
:accept="'.wav'"
:auto-upload="false"
:on-change="handleChange"
:show-file-list="false"
>
<el-button class="ml-3" type="success">上传音频文件</el-button>
</el-upload>
</el-row>
<div class="recording_table">
<el-table :data="vcDatas" border class="recording_table_box" scrollbar-always-on max-height="250px">
<el-table-column prop="wavId" label="序号" width="60"/>
<el-table-column prop="wavName" label="文件名" />
<el-table-column label="操作" width="80">
<template #default="scope">
<div class="flex justify-space-between mb-4 flex-wrap gap-4">
<a @click="PlayTable(scope.row.wavId)"><el-icon><VideoPlay /></el-icon></a>
<a>&#12288</a>
<a @click="delWav(scope.row.wavId)"><el-icon><DeleteFilled /></el-icon></a>
</div>
</template>
</el-table-column>
<el-table-column fixed="right" label="选择" width="70">
<template #default="scope">
<el-switch v-model="scope.row.status" @click="choseWav(scope.row.wavId)"/>
</template>
</el-table-column>
</el-table>
</div>
</el-col>
<el-col :span="8"><div class="grid-content ep-bg-purple" />
<el-space direction="vertical">
<el-card class="box-card" style="width: 250px; height:310px">
<template #header>
<div class="card-header">
<span>请输入中文文本</span>
</div>
</template>
<div class="mb-2 flex items-center text-sm">
<el-radio-group v-model="func_radio" class="ml-4">
<el-radio label="1" size="large">GE2E</el-radio>
<el-radio label="2" size="large">ECAPA-TDNN</el-radio>
</el-radio-group>
</div>
<el-input
v-model="ttsText"
:autosize="{ minRows: 8, maxRows: 13 }"
type="textarea"
placeholder="Please input"
/>
</el-card>
</el-space>
</el-col>
<el-col :span="4"><div class="grid-content ep-bg-purple" />
<div class="play_board">
<el-space direction="vertical">
<el-row :gutter="20">
<el-button size="large" v-if="g2pOnSys === 0" type="primary" @click="g2pClone()"></el-button>
<el-button size="large" v-else :loading-icon="Eleme" type="danger">合成中</el-button>
</el-row>
<el-row :gutter="20">
<el-button v-if='this.cloneWav' type="success" @click="PlaySyn()"></el-button>
<el-button v-else disabled type="primary" @click="PlaySyn()"></el-button>
<el-button v-if='this.cloneWav' type="primary" @click="downLoadCloneWav()"></el-button>
<el-button v-else disabled type="primary" @click="downLoadCloneWav()"></el-button>
</el-row>
</el-space>
</div>
</el-col>
</el-row>
</div>
</template>
<script>
import Recorder from 'js-audio-recorder'
import { vcCloneG2P, vcCloneSAT, vcDel, vcUpload, vcList, vcDownload, vcDownloadBase64 } from '../../../api/ApiVC';
//
const recorder = new Recorder({
sampleBits: 16, // 8 1616
sampleRate: 16000, // 110251600022050240004410048000chrome48000
numChannels: 1, // 1 2 1
compiling: true
})
//
const audioCtx = new AudioContext({
latencyHint: 'interactive',
sampleRate: 16000,
});
export default {
data(){
return {
onEnrollRec: 0, //
wav: '', //
vcDatas: [], //
nowFile: "", //
ttsText: "欢迎使用飞桨语音套件",
nowIndex: -1,
cloneWav: "",
g2pOnSys: 0,
func_radio: '1',
}
},
mounted () {
this.GetList()
},
methods:{
//
reset(){
this.onEnrollRec = 0
this.wav = ''
this.vcDatas = []
this.nowFile = ""
this.ttsText = "欢迎使用飞桨语音套件"
this.nowIndex = -1
},
//
startRecorderEnroll(){
this.onEnrollRec = 1
recorder.clear()
recorder.start()
},
//
stopRecorderEnroll(){
this.onEnrollRec = 2
recorder.stop()
this.wav = recorder.getWAVBlob()
},
// chose wav
choseWav(wavId){
this.cloneWav = ''
this.nowFile = this.vcDatas[wavId].wavName
this.nowIndex = wavId
// only wavId is true else false
for(let i=0; i<this.vcDatas.length; i++){
if(i==wavId){
this.vcDatas[wavId].status = true
} else {
this.vcDatas[i].status = false
}
}
this.$nextTick(()=>{})
},
//
async uploadRecord(){
this.onEnrollRec = 0
if(this.wav === ""){
this.$message.error("未检测到录音,录音失败,请重新录制")
return
} else {
if(this.wav === ''){
this.$message.error("请先完成录音");
this.onEnrollRec = 0
return
} else {
let formData = new FormData();
formData.append('files', this.wav);
const result = await vcUpload(formData);
console.log(result)
this.GetList()
}
this.$message.success("录音上传成功")
}
},
//
async handleChange(file, fileList){
for(let i=0; i<fileList.length; i++){
this.uploadFile(fileList[i])
}
},
//
async uploadFile(file){
let formData = new FormData();
formData.append('files', file.raw);
const result = await vcUpload(formData);
if (result.data.code === 0) {
this.$message.success("音频上传成功")
this.GetList()
} else {
this.$message.error("音频上传失败")
}
},
//
async GetList(){
this.vcDatas =[]
const result = await vcList();
for(let i=0; i<result.data.result.length; i++){
this.vcDatas.push({
wavName: result.data.result[i]['name'],
wavId: i,
wavPath: result.data.result[i]['path'],
status: false
})
}
this.$nextTick(()=>{})
},
//
async delWav(wavId){
console.log('wavId', wavId)
//
const result = await vcDel(
{
wavName: this.vcDatas[wavId]['wavName'],
wavPath: this.vcDatas[wavId]['wavPath']
}
);
if(!result.data.code){
this.$message.success("删除成功")
} else {
this.$message.error(result.data.msg)
}
this.GetList()
this.reset()
},
//
async downLoadCloneWav(){
if(this.cloneWav === ""){
this.$message.error("音频合成完毕后再下载!")
} else {
// const result = await vcDownload(this.cloneWav);
//
const result = await vcDownloadBase64(this.cloneWav);
let view;
// console.log('play result', result)
if (result.data.code === 0) {
// base
let typedArray = this.base64ToUint8Array(result.data.result)
// wav
view = new DataView(typedArray.buffer);
view = Recorder.encodeWAV(view, 16000, 16000, 1, 16, true);
//
// this.playAudioData(view.buffer);
}
console.log(view.buffer)
// debugger
const blob = new Blob([view.buffer], { type: 'audio/wav' });
const fileName = new Date().getTime() + '.wav';
const down = document.createElement('a');
down.download = fileName;
down.style.display = 'none';//,
down.href = URL.createObjectURL(blob);
document.body.appendChild(down);
down.click();
URL.revokeObjectURL(down.href); // URL
document.body.removeChild(down);//
}
},
// g2p voice clone
async g2pClone(){
if(this.nowIndex === -1){
return this.$message.error("请先录音并上传,选择音频后再点击合成")
} else if (this.ttsText === ""){
return this.$message.error("合成文本不可以为空")
} else if (this.nowIndex >= this.vcDatas.length){
return this.$message.error("当前序号不可以超过音频个数")
}
this.cloneWav = ""
let func = ''
if(this.func_radio === '1'){
func = 'ge2e'
} else {
func = 'ecapa_tdnn'
}
console.log('func', func)
//
this.g2pOnSys = 1
const result = await vcCloneG2P(
{
wavName: this.vcDatas[this.nowIndex]['wavName'],
wavPath: this.vcDatas[this.nowIndex]['wavPath'],
text: this.ttsText,
func: func
}
);
this.g2pOnSys = 0
if(result.data.code == 0){
this.cloneWav = result.data.result
console.log("clone wav: ", this.cloneWav)
this.$message.success("音频合成成功")
} else {
this.$message.error("音频合成失败,请检查后台错误后重试!")
}
},
//
async PlayTable(wavId){
this.Play(this.vcDatas[wavId])
},
//
async PlaySyn(){
if(this.cloneWav === ""){
this.$message.error("请合成音频后再播放!!")
return
} else {
this.Play(this.cloneWav)
}
},
//
async Play(wavBase){
//
const result = await vcDownloadBase64(wavBase);
// console.log('play result', result)
if (result.data.code === 0) {
// base
let typedArray = this.base64ToUint8Array(result.data.result)
// wav
let view = new DataView(typedArray.buffer);
view = Recorder.encodeWAV(view, 16000, 16000, 1, 16, true);
//
this.playAudioData(view.buffer);
};
},
// base64
base64ToUint8Array(base64String) {
const padding = '='.repeat((4 - base64String.length % 4) % 4);
const base64 = (base64String + padding)
.replace(/-/g, '+')
.replace(/_/g, '/');
const rawData = window.atob(base64);
const outputArray = new Uint8Array(rawData.length);
for (let i = 0; i < rawData.length; ++i) {
outputArray[i] = rawData.charCodeAt(i);
}
return outputArray;
},
//
playAudioData( wav_buffer ) {
audioCtx.decodeAudioData(wav_buffer, buffer => {
var source = audioCtx.createBufferSource();
source.buffer = buffer;
source.connect(audioCtx.destination);
source.start();
}, function(e) {
Recorder.throwError(e);
})
},
},
}
</script>
<style lang="less" scoped>
// @import "./style.less";
.voiceclone {
width: 1200px;
height: 410px;
background: #FFFFFF;
padding: 5px 80px 56px 80px;
box-sizing: border-box;
}
.el-row {
margin-bottom: 20px;
}
.grid-content {
border-radius: 4px;
min-height: 36px;
}
.play_board{
height: 100%;
display: flex;
align-items: center;
}
</style>

@ -1,5 +1,6 @@
import { createApp } from 'vue' import { createApp } from 'vue'
import ElementPlus from 'element-plus' import ElementPlus from 'element-plus'
import * as ElementPlusIconsVue from '@element-plus/icons-vue'
import 'element-plus/dist/index.css' import 'element-plus/dist/index.css'
import Antd from 'ant-design-vue'; import Antd from 'ant-design-vue';
import 'ant-design-vue/dist/antd.css'; import 'ant-design-vue/dist/antd.css';
@ -9,5 +10,8 @@ import axios from 'axios'
const app = createApp(App) const app = createApp(App)
app.config.globalProperties.$http = axios app.config.globalProperties.$http = axios
for (const [key, component] of Object.entries(ElementPlusIconsVue)) {
app.component(key, component)
}
app.use(ElementPlus).use(Antd) app.use(ElementPlus).use(Antd)
app.mount('#app') app.mount('#app')

@ -44,6 +44,11 @@
resolved "https://registry.npmmirror.com/@element-plus/icons-vue/-/icons-vue-1.1.4.tgz" resolved "https://registry.npmmirror.com/@element-plus/icons-vue/-/icons-vue-1.1.4.tgz"
integrity sha512-Iz/nHqdp1sFPmdzRwHkEQQA3lKvoObk8azgABZ81QUOpW9s/lUyQVUSh0tNtEPZXQlKwlSh7SPgoVxzrE0uuVQ== integrity sha512-Iz/nHqdp1sFPmdzRwHkEQQA3lKvoObk8azgABZ81QUOpW9s/lUyQVUSh0tNtEPZXQlKwlSh7SPgoVxzrE0uuVQ==
"@element-plus/icons-vue@^2.0.9":
version "2.0.9"
resolved "https://registry.npmmirror.com/@element-plus/icons-vue/-/icons-vue-2.0.9.tgz#b7777c57534522e387303d194451d50ff549d49a"
integrity sha512-okdrwiVeKBmW41Hkl0eMrXDjzJwhQMuKiBOu17rOszqM+LS/yBYpNQNV5Jvoh06Wc+89fMmb/uhzf8NZuDuUaQ==
"@floating-ui/core@^0.6.1": "@floating-ui/core@^0.6.1":
version "0.6.1" version "0.6.1"
resolved "https://registry.npmmirror.com/@floating-ui/core/-/core-0.6.1.tgz" resolved "https://registry.npmmirror.com/@floating-ui/core/-/core-0.6.1.tgz"

@ -20,6 +20,7 @@ onnxruntime==1.10.0
opencc opencc
paddlenlp paddlenlp
paddlepaddle>=2.2.2 paddlepaddle>=2.2.2
paddlespeech_ctcdecoders
paddlespeech_feat paddlespeech_feat
pandas pandas
pathos == 0.2.8 pathos == 0.2.8
@ -27,8 +28,8 @@ pattern_singleton
Pillow>=9.0.0 Pillow>=9.0.0
praatio==5.0.0 praatio==5.0.0
prettytable prettytable
pypinyin<=0.44.0
pypinyin-dict pypinyin-dict
pypinyin<=0.44.0
python-dateutil python-dateutil
pyworld==0.2.12 pyworld==0.2.12
recommonmark>=0.5.0 recommonmark>=0.5.0

@ -1,7 +0,0 @@
paddlespeech.cls.exps.panns.deploy.predict module
=================================================
.. automodule:: paddlespeech.cls.exps.panns.deploy.predict
:members:
:undoc-members:
:show-inheritance:

@ -12,4 +12,3 @@ Submodules
.. toctree:: .. toctree::
:maxdepth: 4 :maxdepth: 4
paddlespeech.cls.exps.panns.deploy.predict

@ -1,7 +0,0 @@
paddlespeech.cls.exps.panns.export\_model module
================================================
.. automodule:: paddlespeech.cls.exps.panns.export_model
:members:
:undoc-members:
:show-inheritance:

@ -1,7 +0,0 @@
paddlespeech.cls.exps.panns.predict module
==========================================
.. automodule:: paddlespeech.cls.exps.panns.predict
:members:
:undoc-members:
:show-inheritance:

@ -20,6 +20,3 @@ Submodules
.. toctree:: .. toctree::
:maxdepth: 4 :maxdepth: 4
paddlespeech.cls.exps.panns.export_model
paddlespeech.cls.exps.panns.predict
paddlespeech.cls.exps.panns.train

@ -1,7 +0,0 @@
paddlespeech.cls.exps.panns.train module
========================================
.. automodule:: paddlespeech.cls.exps.panns.train
:members:
:undoc-members:
:show-inheritance:

@ -1,7 +0,0 @@
paddlespeech.kws.exps.mdtc.plot\_det\_curve module
==================================================
.. automodule:: paddlespeech.kws.exps.mdtc.plot_det_curve
:members:
:undoc-members:
:show-inheritance:

@ -14,6 +14,5 @@ Submodules
paddlespeech.kws.exps.mdtc.collate paddlespeech.kws.exps.mdtc.collate
paddlespeech.kws.exps.mdtc.compute_det paddlespeech.kws.exps.mdtc.compute_det
paddlespeech.kws.exps.mdtc.plot_det_curve
paddlespeech.kws.exps.mdtc.score paddlespeech.kws.exps.mdtc.score
paddlespeech.kws.exps.mdtc.train paddlespeech.kws.exps.mdtc.train

@ -13,5 +13,4 @@ Submodules
:maxdepth: 4 :maxdepth: 4
paddlespeech.s2t.decoders.ctcdecoder.decoders_deprecated paddlespeech.s2t.decoders.ctcdecoder.decoders_deprecated
paddlespeech.s2t.decoders.ctcdecoder.scorer_deprecated
paddlespeech.s2t.decoders.ctcdecoder.swig_wrapper paddlespeech.s2t.decoders.ctcdecoder.swig_wrapper

@ -1,7 +0,0 @@
paddlespeech.s2t.decoders.ctcdecoder.scorer\_deprecated module
==============================================================
.. automodule:: paddlespeech.s2t.decoders.ctcdecoder.scorer_deprecated
:members:
:undoc-members:
:show-inheritance:

@ -1,7 +0,0 @@
paddlespeech.s2t.decoders.recog\_bin module
===========================================
.. automodule:: paddlespeech.s2t.decoders.recog_bin
:members:
:undoc-members:
:show-inheritance:

@ -23,5 +23,4 @@ Submodules
:maxdepth: 4 :maxdepth: 4
paddlespeech.s2t.decoders.recog paddlespeech.s2t.decoders.recog
paddlespeech.s2t.decoders.recog_bin
paddlespeech.s2t.decoders.utils paddlespeech.s2t.decoders.utils

@ -1,7 +0,0 @@
paddlespeech.s2t.decoders.scorers.ngram module
==============================================
.. automodule:: paddlespeech.s2t.decoders.scorers.ngram
:members:
:undoc-members:
:show-inheritance:

@ -15,5 +15,4 @@ Submodules
paddlespeech.s2t.decoders.scorers.ctc paddlespeech.s2t.decoders.scorers.ctc
paddlespeech.s2t.decoders.scorers.ctc_prefix_score paddlespeech.s2t.decoders.scorers.ctc_prefix_score
paddlespeech.s2t.decoders.scorers.length_bonus paddlespeech.s2t.decoders.scorers.length_bonus
paddlespeech.s2t.decoders.scorers.ngram
paddlespeech.s2t.decoders.scorers.scorer_interface paddlespeech.s2t.decoders.scorers.scorer_interface

@ -1,7 +0,0 @@
paddlespeech.s2t.exps.deepspeech2.bin.deploy.client module
==========================================================
.. automodule:: paddlespeech.s2t.exps.deepspeech2.bin.deploy.client
:members:
:undoc-members:
:show-inheritance:

@ -1,7 +0,0 @@
paddlespeech.s2t.exps.deepspeech2.bin.deploy.record module
==========================================================
.. automodule:: paddlespeech.s2t.exps.deepspeech2.bin.deploy.record
:members:
:undoc-members:
:show-inheritance:

@ -12,8 +12,5 @@ Submodules
.. toctree:: .. toctree::
:maxdepth: 4 :maxdepth: 4
paddlespeech.s2t.exps.deepspeech2.bin.deploy.client
paddlespeech.s2t.exps.deepspeech2.bin.deploy.record
paddlespeech.s2t.exps.deepspeech2.bin.deploy.runtime paddlespeech.s2t.exps.deepspeech2.bin.deploy.runtime
paddlespeech.s2t.exps.deepspeech2.bin.deploy.send
paddlespeech.s2t.exps.deepspeech2.bin.deploy.server paddlespeech.s2t.exps.deepspeech2.bin.deploy.server

@ -1,7 +0,0 @@
paddlespeech.s2t.exps.deepspeech2.bin.deploy.send module
========================================================
.. automodule:: paddlespeech.s2t.exps.deepspeech2.bin.deploy.send
:members:
:undoc-members:
:show-inheritance:

@ -21,4 +21,3 @@ Submodules
:maxdepth: 4 :maxdepth: 4
paddlespeech.s2t.exps.u2.model paddlespeech.s2t.exps.u2.model
paddlespeech.s2t.exps.u2.trainer

@ -1,7 +0,0 @@
paddlespeech.s2t.exps.u2.trainer module
=======================================
.. automodule:: paddlespeech.s2t.exps.u2.trainer
:members:
:undoc-members:
:show-inheritance:

@ -1,7 +0,0 @@
paddlespeech.s2t.exps.u2\_kaldi.bin.recog module
================================================
.. automodule:: paddlespeech.s2t.exps.u2_kaldi.bin.recog
:members:
:undoc-members:
:show-inheritance:

@ -12,6 +12,5 @@ Submodules
.. toctree:: .. toctree::
:maxdepth: 4 :maxdepth: 4
paddlespeech.s2t.exps.u2_kaldi.bin.recog
paddlespeech.s2t.exps.u2_kaldi.bin.test paddlespeech.s2t.exps.u2_kaldi.bin.test
paddlespeech.s2t.exps.u2_kaldi.bin.train paddlespeech.s2t.exps.u2_kaldi.bin.train

@ -15,5 +15,3 @@ Submodules
paddlespeech.s2t.training.extensions.evaluator paddlespeech.s2t.training.extensions.evaluator
paddlespeech.s2t.training.extensions.extension paddlespeech.s2t.training.extensions.extension
paddlespeech.s2t.training.extensions.plot paddlespeech.s2t.training.extensions.plot
paddlespeech.s2t.training.extensions.snapshot
paddlespeech.s2t.training.extensions.visualizer

@ -1,7 +0,0 @@
paddlespeech.s2t.training.extensions.snapshot module
====================================================
.. automodule:: paddlespeech.s2t.training.extensions.snapshot
:members:
:undoc-members:
:show-inheritance:

@ -1,7 +0,0 @@
paddlespeech.s2t.training.extensions.visualizer module
======================================================
.. automodule:: paddlespeech.s2t.training.extensions.visualizer
:members:
:undoc-members:
:show-inheritance:

@ -13,5 +13,4 @@ Submodules
:maxdepth: 4 :maxdepth: 4
paddlespeech.s2t.training.updaters.standard_updater paddlespeech.s2t.training.updaters.standard_updater
paddlespeech.s2t.training.updaters.trainer
paddlespeech.s2t.training.updaters.updater paddlespeech.s2t.training.updaters.updater

@ -1,7 +0,0 @@
paddlespeech.s2t.training.updaters.trainer module
=================================================
.. automodule:: paddlespeech.s2t.training.updaters.trainer
:members:
:undoc-members:
:show-inheritance:

@ -1,7 +0,0 @@
paddlespeech.s2t.transform.add\_deltas module
=============================================
.. automodule:: paddlespeech.s2t.transform.add_deltas
:members:
:undoc-members:
:show-inheritance:

@ -1,7 +0,0 @@
paddlespeech.s2t.transform.channel\_selector module
===================================================
.. automodule:: paddlespeech.s2t.transform.channel_selector
:members:
:undoc-members:
:show-inheritance:

@ -1,7 +0,0 @@
paddlespeech.s2t.transform.cmvn module
======================================
.. automodule:: paddlespeech.s2t.transform.cmvn
:members:
:undoc-members:
:show-inheritance:

@ -1,7 +0,0 @@
paddlespeech.s2t.transform.functional module
============================================
.. automodule:: paddlespeech.s2t.transform.functional
:members:
:undoc-members:
:show-inheritance:

@ -1,7 +0,0 @@
paddlespeech.s2t.transform.perturb module
=========================================
.. automodule:: paddlespeech.s2t.transform.perturb
:members:
:undoc-members:
:show-inheritance:

@ -1,24 +0,0 @@
paddlespeech.s2t.transform package
==================================
.. automodule:: paddlespeech.s2t.transform
:members:
:undoc-members:
:show-inheritance:
Submodules
----------
.. toctree::
:maxdepth: 4
paddlespeech.s2t.transform.add_deltas
paddlespeech.s2t.transform.channel_selector
paddlespeech.s2t.transform.cmvn
paddlespeech.s2t.transform.functional
paddlespeech.s2t.transform.perturb
paddlespeech.s2t.transform.spec_augment
paddlespeech.s2t.transform.spectrogram
paddlespeech.s2t.transform.transform_interface
paddlespeech.s2t.transform.transformation
paddlespeech.s2t.transform.wpe

@ -1,7 +0,0 @@
paddlespeech.s2t.transform.spec\_augment module
===============================================
.. automodule:: paddlespeech.s2t.transform.spec_augment
:members:
:undoc-members:
:show-inheritance:

@ -1,7 +0,0 @@
paddlespeech.s2t.transform.spectrogram module
=============================================
.. automodule:: paddlespeech.s2t.transform.spectrogram
:members:
:undoc-members:
:show-inheritance:

@ -1,7 +0,0 @@
paddlespeech.s2t.transform.transform\_interface module
======================================================
.. automodule:: paddlespeech.s2t.transform.transform_interface
:members:
:undoc-members:
:show-inheritance:

@ -1,7 +0,0 @@
paddlespeech.s2t.transform.transformation module
================================================
.. automodule:: paddlespeech.s2t.transform.transformation
:members:
:undoc-members:
:show-inheritance:

@ -1,7 +0,0 @@
paddlespeech.s2t.transform.wpe module
=====================================
.. automodule:: paddlespeech.s2t.transform.wpe
:members:
:undoc-members:
:show-inheritance:

@ -1,7 +0,0 @@
paddlespeech.server.engine.acs.python.acs\_engine module
========================================================
.. automodule:: paddlespeech.server.engine.acs.python.acs_engine
:members:
:undoc-members:
:show-inheritance:

@ -12,4 +12,3 @@ Submodules
.. toctree:: .. toctree::
:maxdepth: 4 :maxdepth: 4
paddlespeech.server.engine.acs.python.acs_engine

@ -1,7 +0,0 @@
paddlespeech.server.utils.log module
====================================
.. automodule:: paddlespeech.server.utils.log
:members:
:undoc-members:
:show-inheritance:

@ -30,10 +30,10 @@ Submodules
paddlespeech.t2s.exps.inference paddlespeech.t2s.exps.inference
paddlespeech.t2s.exps.inference_streaming paddlespeech.t2s.exps.inference_streaming
paddlespeech.t2s.models.vits.monotonic_align
paddlespeech.t2s.exps.ort_predict paddlespeech.t2s.exps.ort_predict
paddlespeech.t2s.exps.ort_predict_e2e paddlespeech.t2s.exps.ort_predict_e2e
paddlespeech.t2s.exps.ort_predict_streaming paddlespeech.t2s.exps.ort_predict_streaming
paddlespeech.t2s.exps.stream_play_tts
paddlespeech.t2s.exps.syn_utils paddlespeech.t2s.exps.syn_utils
paddlespeech.t2s.exps.synthesize paddlespeech.t2s.exps.synthesize
paddlespeech.t2s.exps.synthesize_e2e paddlespeech.t2s.exps.synthesize_e2e

@ -1,7 +0,0 @@
paddlespeech.t2s.exps.stream\_play\_tts module
==============================================
.. automodule:: paddlespeech.t2s.exps.stream_play_tts
:members:
:undoc-members:
:show-inheritance:

@ -1,7 +0,0 @@
paddlespeech.t2s.models.ernie\_sat.mlm module
=============================================
.. automodule:: paddlespeech.t2s.models.ernie_sat.mlm
:members:
:undoc-members:
:show-inheritance:

@ -1,7 +0,0 @@
paddlespeech.t2s.models.vits.monotonic\_align.core module
=========================================================
.. automodule:: paddlespeech.t2s.models.vits.monotonic_align.core
:members:
:undoc-members:
:show-inheritance:

@ -1,16 +0,0 @@
paddlespeech.t2s.models.vits.monotonic\_align package
=====================================================
.. automodule:: paddlespeech.t2s.models.vits.monotonic_align
:members:
:undoc-members:
:show-inheritance:
Submodules
----------
.. toctree::
:maxdepth: 4
paddlespeech.t2s.models.vits.monotonic_align.core
paddlespeech.t2s.models.vits.monotonic_align.setup

@ -1,7 +0,0 @@
paddlespeech.t2s.models.vits.monotonic\_align.setup module
==========================================================
.. automodule:: paddlespeech.t2s.models.vits.monotonic_align.setup
:members:
:undoc-members:
:show-inheritance:

@ -12,7 +12,6 @@ Subpackages
.. toctree:: .. toctree::
:maxdepth: 4 :maxdepth: 4
paddlespeech.t2s.models.vits.monotonic_align
paddlespeech.t2s.models.vits.wavenet paddlespeech.t2s.models.vits.wavenet
Submodules Submodules

File diff suppressed because it is too large Load Diff

@ -19,7 +19,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
<tr> <tr>
<td>早上好今天是2020/10/29最低温度是-3°C。</td> <td>早上好今天是2020/10/29最低温度是-3°C。</td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/001.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/001.wav"
type="audio/wav"> type="audio/wav">
@ -27,7 +27,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
</audio> </audio>
</td> </td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/001.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/001.wav"
type="audio/wav"> type="audio/wav">
@ -38,7 +38,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
<tr> <tr>
<td>你好我的编号是37249很高兴为您服务。</td> <td>你好我的编号是37249很高兴为您服务。</td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/002.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/002.wav"
type="audio/wav"> type="audio/wav">
@ -46,7 +46,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
</audio> </audio>
</td> </td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/002.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/002.wav"
type="audio/wav"> type="audio/wav">
@ -57,7 +57,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
<tr> <tr>
<td>我们公司有37249个人。</td> <td>我们公司有37249个人。</td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/003.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/003.wav"
type="audio/wav"> type="audio/wav">
@ -65,7 +65,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
</audio> </audio>
</td> </td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/003.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/003.wav"
type="audio/wav"> type="audio/wav">
@ -76,7 +76,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
<tr> <tr>
<td>我出生于2005年10月8日。</td> <td>我出生于2005年10月8日。</td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/004.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/004.wav"
type="audio/wav"> type="audio/wav">
@ -84,7 +84,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
</audio> </audio>
</td> </td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/004.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/004.wav"
type="audio/wav"> type="audio/wav">
@ -95,7 +95,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
<tr> <tr>
<td>我们习惯在12:30吃中午饭。</td> <td>我们习惯在12:30吃中午饭。</td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/005.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/005.wav"
type="audio/wav"> type="audio/wav">
@ -103,7 +103,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
</audio> </audio>
</td> </td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/005.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/005.wav"
type="audio/wav"> type="audio/wav">
@ -114,7 +114,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
<tr> <tr>
<td>只要有超过3/4的人投票同意你就会成为我们的新班长。</td> <td>只要有超过3/4的人投票同意你就会成为我们的新班长。</td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/006.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/006.wav"
type="audio/wav"> type="audio/wav">
@ -122,7 +122,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
</audio> </audio>
</td> </td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/006.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/006.wav"
type="audio/wav"> type="audio/wav">
@ -133,7 +133,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
<tr> <tr>
<td>我要买一只价值999.9元的手表。</td> <td>我要买一只价值999.9元的手表。</td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/007.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/007.wav"
type="audio/wav"> type="audio/wav">
@ -141,7 +141,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
</audio> </audio>
</td> </td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/007.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/007.wav"
type="audio/wav"> type="audio/wav">
@ -152,7 +152,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
<tr> <tr>
<td>我的手机号是18544139121欢迎来电。</td> <td>我的手机号是18544139121欢迎来电。</td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/008.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/008.wav"
type="audio/wav"> type="audio/wav">
@ -160,7 +160,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
</audio> </audio>
</td> </td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/008.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/008.wav"
type="audio/wav"> type="audio/wav">
@ -171,7 +171,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
<tr> <tr>
<td>明天有62%的概率降雨。</td> <td>明天有62%的概率降雨。</td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/009.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/009.wav"
type="audio/wav"> type="audio/wav">
@ -179,7 +179,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
</audio> </audio>
</td> </td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/009.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/009.wav"
type="audio/wav"> type="audio/wav">
@ -190,7 +190,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
<tr> <tr>
<td>手表厂有五种好产品。</td> <td>手表厂有五种好产品。</td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/010.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/010.wav"
type="audio/wav"> type="audio/wav">
@ -198,7 +198,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
</audio> </audio>
</td> </td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/010.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/010.wav"
type="audio/wav"> type="audio/wav">
@ -209,7 +209,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
<tr> <tr>
<td>跑马场有五百匹很勇敢的千里马。</td> <td>跑马场有五百匹很勇敢的千里马。</td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/011.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/011.wav"
type="audio/wav"> type="audio/wav">
@ -217,7 +217,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
</audio> </audio>
</td> </td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/011.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/011.wav"
type="audio/wav"> type="audio/wav">
@ -228,7 +228,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
<tr> <tr>
<td>有一天,我看到了一栋楼,我顿感不妙,因为我看不清里面有没有人。</td> <td>有一天,我看到了一栋楼,我顿感不妙,因为我看不清里面有没有人。</td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/012.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/012.wav"
type="audio/wav"> type="audio/wav">
@ -236,7 +236,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
</audio> </audio>
</td> </td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/012.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/012.wav"
type="audio/wav"> type="audio/wav">
@ -247,7 +247,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
<tr> <tr>
<td>史小姐拿着小雨伞去找她的老保姆了。</td> <td>史小姐拿着小雨伞去找她的老保姆了。</td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/013.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/013.wav"
type="audio/wav"> type="audio/wav">
@ -255,7 +255,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
</audio> </audio>
</td> </td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/013.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/013.wav"
type="audio/wav"> type="audio/wav">
@ -266,7 +266,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
<tr> <tr>
<td>不要相信这个老奶奶说的话,她一点儿也不好。</td> <td>不要相信这个老奶奶说的话,她一点儿也不好。</td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/014.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/espent/014.wav"
type="audio/wav"> type="audio/wav">
@ -274,7 +274,7 @@ FastSpeech2 + Parallel WaveGAN in CSMSC
</audio> </audio>
</td> </td>
<td> <td>
<audio controls="controls"> <audio controls="controls" style="width: 220px;">
<source <source
src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/014.wav" src="https://paddlespeech.bj.bcebos.com/Parakeet/docs/demos/parakeet_espnet_fs2_pwg_demo/tn_g2p/parakeet/014.wav"
type="audio/wav"> type="audio/wav">

@ -26,6 +26,10 @@ if [ ${seed} != 0 ]; then
export FLAGS_cudnn_deterministic=True export FLAGS_cudnn_deterministic=True
fi fi
# default memeory allocator strategy may case gpu training hang
# for no OOM raised when memory exhaused
export FLAGS_allocator_strategy=naive_best_fit
if [ ${ngpu} == 0 ]; then if [ ${ngpu} == 0 ]; then
python3 -u ${BIN_DIR}/train.py \ python3 -u ${BIN_DIR}/train.py \
--ngpu ${ngpu} \ --ngpu ${ngpu} \

@ -35,6 +35,10 @@ echo ${ips_config}
mkdir -p exp mkdir -p exp
# default memeory allocator strategy may case gpu training hang
# for no OOM raised when memory exhaused
export FLAGS_allocator_strategy=naive_best_fit
if [ ${ngpu} == 0 ]; then if [ ${ngpu} == 0 ]; then
python3 -u ${BIN_DIR}/train.py \ python3 -u ${BIN_DIR}/train.py \
--ngpu ${ngpu} \ --ngpu ${ngpu} \

@ -1,4 +1,4 @@
# ERNIE-SAT with VCTK dataset # ERNIE-SAT with AISHELL-3 dataset
ERNIE-SAT speech-text joint pretraining framework, which achieves SOTA results in cross-lingual multi-speaker speech synthesis and cross-lingual speech editing tasks, It can be applied to a series of scenarios such as Speech Editing, personalized Speech Synthesis, and Voice Cloning. ERNIE-SAT speech-text joint pretraining framework, which achieves SOTA results in cross-lingual multi-speaker speech synthesis and cross-lingual speech editing tasks, It can be applied to a series of scenarios such as Speech Editing, personalized Speech Synthesis, and Voice Cloning.
## Model Framework ## Model Framework

@ -4,8 +4,6 @@ config_path=$1
train_output_path=$2 train_output_path=$2
ckpt_name=$3 ckpt_name=$3
FLAGS_allocator_strategy=naive_best_fit \
FLAGS_fraction_of_gpu_memory_to_use=0.01 \
python3 ${BIN_DIR}/../synthesize.py \ python3 ${BIN_DIR}/../synthesize.py \
--am=tacotron2_aishell3 \ --am=tacotron2_aishell3 \
--am_config=${config_path} \ --am_config=${config_path} \

@ -6,8 +6,6 @@ ckpt_name=$3
ge2e_params_path=$4 ge2e_params_path=$4
ref_audio_dir=$5 ref_audio_dir=$5
FLAGS_allocator_strategy=naive_best_fit \
FLAGS_fraction_of_gpu_memory_to_use=0.01 \
python3 ${BIN_DIR}/../voice_cloning.py \ python3 ${BIN_DIR}/../voice_cloning.py \
--am=tacotron2_aishell3 \ --am=tacotron2_aishell3 \
--am_config=${config_path} \ --am_config=${config_path} \

@ -4,8 +4,6 @@ config_path=$1
train_output_path=$2 train_output_path=$2
ckpt_name=$3 ckpt_name=$3
FLAGS_allocator_strategy=naive_best_fit \
FLAGS_fraction_of_gpu_memory_to_use=0.01 \
python3 ${BIN_DIR}/../synthesize.py \ python3 ${BIN_DIR}/../synthesize.py \
--am=fastspeech2_aishell3 \ --am=fastspeech2_aishell3 \
--am_config=${config_path} \ --am_config=${config_path} \

@ -6,8 +6,6 @@ ckpt_name=$3
ge2e_params_path=$4 ge2e_params_path=$4
ref_audio_dir=$5 ref_audio_dir=$5
FLAGS_allocator_strategy=naive_best_fit \
FLAGS_fraction_of_gpu_memory_to_use=0.01 \
python3 ${BIN_DIR}/../voice_cloning.py \ python3 ${BIN_DIR}/../voice_cloning.py \
--am=fastspeech2_aishell3 \ --am=fastspeech2_aishell3 \
--am_config=${config_path} \ --am_config=${config_path} \

@ -4,8 +4,6 @@ config_path=$1
train_output_path=$2 train_output_path=$2
ckpt_name=$3 ckpt_name=$3
FLAGS_allocator_strategy=naive_best_fit \
FLAGS_fraction_of_gpu_memory_to_use=0.01 \
python3 ${BIN_DIR}/../synthesize.py \ python3 ${BIN_DIR}/../synthesize.py \
--am=fastspeech2_aishell3 \ --am=fastspeech2_aishell3 \
--am_config=${config_path} \ --am_config=${config_path} \

@ -5,8 +5,6 @@ train_output_path=$2
ckpt_name=$3 ckpt_name=$3
ref_audio_dir=$4 ref_audio_dir=$4
FLAGS_allocator_strategy=naive_best_fit \
FLAGS_fraction_of_gpu_memory_to_use=0.01 \
python3 ${BIN_DIR}/../voice_cloning.py \ python3 ${BIN_DIR}/../voice_cloning.py \
--am=fastspeech2_aishell3 \ --am=fastspeech2_aishell3 \
--am_config=${config_path} \ --am_config=${config_path} \

@ -1,4 +1,4 @@
# ERNIE-SAT with VCTK dataset # ERNIE-SAT with AISHELL-3 and VCTK dataset
ERNIE-SAT speech-text joint pretraining framework, which achieves SOTA results in cross-lingual multi-speaker speech synthesis and cross-lingual speech editing tasks, It can be applied to a series of scenarios such as Speech Editing, personalized Speech Synthesis, and Voice Cloning. ERNIE-SAT speech-text joint pretraining framework, which achieves SOTA results in cross-lingual multi-speaker speech synthesis and cross-lingual speech editing tasks, It can be applied to a series of scenarios such as Speech Editing, personalized Speech Synthesis, and Voice Cloning.
## Model Framework ## Model Framework

@ -0,0 +1,44 @@
###########################################################
# DATA SETTING #
###########################################################
dataset_type: Ernie
train_path: data/iwslt2012_zh/train.txt
dev_path: data/iwslt2012_zh/dev.txt
test_path: data/iwslt2012_zh/test.txt
batch_size: 64
num_workers: 2
data_params:
pretrained_token: ernie-3.0-base-zh
punc_path: data/iwslt2012_zh/punc_vocab
seq_len: 100
###########################################################
# MODEL SETTING #
###########################################################
model_type: ErnieLinear
model:
pretrained_token: ernie-3.0-base-zh
num_classes: 4
###########################################################
# OPTIMIZER SETTING #
###########################################################
optimizer_params:
weight_decay: 1.0e-6 # weight decay coefficient.
scheduler_params:
learning_rate: 1.0e-5 # learning rate.
gamma: 0.9999 # scheduler gamma must between(0.0, 1.0) and closer to 1.0 is better.
###########################################################
# TRAINING SETTING #
###########################################################
max_epoch: 20
num_snapshots: 5
###########################################################
# OTHER SETTING #
###########################################################
num_snapshots: 10 # max number of snapshots to keep while training
seed: 42 # random seed for paddle, random, and np.random

@ -0,0 +1,44 @@
###########################################################
# DATA SETTING #
###########################################################
dataset_type: Ernie
train_path: data/iwslt2012_zh/train.txt
dev_path: data/iwslt2012_zh/dev.txt
test_path: data/iwslt2012_zh/test.txt
batch_size: 64
num_workers: 2
data_params:
pretrained_token: ernie-3.0-medium-zh
punc_path: data/iwslt2012_zh/punc_vocab
seq_len: 100
###########################################################
# MODEL SETTING #
###########################################################
model_type: ErnieLinear
model:
pretrained_token: ernie-3.0-medium-zh
num_classes: 4
###########################################################
# OPTIMIZER SETTING #
###########################################################
optimizer_params:
weight_decay: 1.0e-6 # weight decay coefficient.
scheduler_params:
learning_rate: 1.0e-5 # learning rate.
gamma: 0.9999 # scheduler gamma must between(0.0, 1.0) and closer to 1.0 is better.
###########################################################
# TRAINING SETTING #
###########################################################
max_epoch: 20
num_snapshots: 5
###########################################################
# OTHER SETTING #
###########################################################
num_snapshots: 10 # max number of snapshots to keep while training
seed: 42 # random seed for paddle, random, and np.random

@ -0,0 +1,44 @@
###########################################################
# DATA SETTING #
###########################################################
dataset_type: Ernie
train_path: data/iwslt2012_zh/train.txt
dev_path: data/iwslt2012_zh/dev.txt
test_path: data/iwslt2012_zh/test.txt
batch_size: 64
num_workers: 2
data_params:
pretrained_token: ernie-3.0-mini-zh
punc_path: data/iwslt2012_zh/punc_vocab
seq_len: 100
###########################################################
# MODEL SETTING #
###########################################################
model_type: ErnieLinear
model:
pretrained_token: ernie-3.0-mini-zh
num_classes: 4
###########################################################
# OPTIMIZER SETTING #
###########################################################
optimizer_params:
weight_decay: 1.0e-6 # weight decay coefficient.
scheduler_params:
learning_rate: 1.0e-5 # learning rate.
gamma: 0.9999 # scheduler gamma must between(0.0, 1.0) and closer to 1.0 is better.
###########################################################
# TRAINING SETTING #
###########################################################
max_epoch: 20
num_snapshots: 5
###########################################################
# OTHER SETTING #
###########################################################
num_snapshots: 10 # max number of snapshots to keep while training
seed: 42 # random seed for paddle, random, and np.random

@ -0,0 +1,44 @@
###########################################################
# DATA SETTING #
###########################################################
dataset_type: Ernie
train_path: data/iwslt2012_zh/train.txt
dev_path: data/iwslt2012_zh/dev.txt
test_path: data/iwslt2012_zh/test.txt
batch_size: 64
num_workers: 2
data_params:
pretrained_token: ernie-3.0-nano-zh
punc_path: data/iwslt2012_zh/punc_vocab
seq_len: 100
###########################################################
# MODEL SETTING #
###########################################################
model_type: ErnieLinear
model:
pretrained_token: ernie-3.0-nano-zh
num_classes: 4
###########################################################
# OPTIMIZER SETTING #
###########################################################
optimizer_params:
weight_decay: 1.0e-6 # weight decay coefficient.
scheduler_params:
learning_rate: 1.0e-5 # learning rate.
gamma: 0.9999 # scheduler gamma must between(0.0, 1.0) and closer to 1.0 is better.
###########################################################
# TRAINING SETTING #
###########################################################
max_epoch: 20
num_snapshots: 5
###########################################################
# OTHER SETTING #
###########################################################
num_snapshots: 10 # max number of snapshots to keep while training
seed: 42 # random seed for paddle, random, and np.random

@ -0,0 +1,44 @@
###########################################################
# DATA SETTING #
###########################################################
dataset_type: Ernie
train_path: data/iwslt2012_zh/train.txt
dev_path: data/iwslt2012_zh/dev.txt
test_path: data/iwslt2012_zh/test.txt
batch_size: 64
num_workers: 2
data_params:
pretrained_token: ernie-tiny
punc_path: data/iwslt2012_zh/punc_vocab
seq_len: 100
###########################################################
# MODEL SETTING #
###########################################################
model_type: ErnieLinear
model:
pretrained_token: ernie-tiny
num_classes: 4
###########################################################
# OPTIMIZER SETTING #
###########################################################
optimizer_params:
weight_decay: 1.0e-6 # weight decay coefficient.
scheduler_params:
learning_rate: 1.0e-5 # learning rate.
gamma: 0.9999 # scheduler gamma must between(0.0, 1.0) and closer to 1.0 is better.
###########################################################
# TRAINING SETTING #
###########################################################
max_epoch: 20
num_snapshots: 5
###########################################################
# OTHER SETTING #
###########################################################
num_snapshots: 10 # max number of snapshots to keep while training
seed: 42 # random seed for paddle, random, and np.random

@ -26,6 +26,10 @@ if [ ${seed} != 0 ]; then
export FLAGS_cudnn_deterministic=True export FLAGS_cudnn_deterministic=True
fi fi
# default memeory allocator strategy may case gpu training hang
# for no OOM raised when memory exhaused
export FLAGS_allocator_strategy=naive_best_fit
if [ ${ngpu} == 0 ]; then if [ ${ngpu} == 0 ]; then
python3 -u ${BIN_DIR}/train.py \ python3 -u ${BIN_DIR}/train.py \
--ngpu ${ngpu} \ --ngpu ${ngpu} \

@ -29,6 +29,10 @@ fi
# export FLAGS_cudnn_exhaustive_search=true # export FLAGS_cudnn_exhaustive_search=true
# export FLAGS_conv_workspace_size_limit=4000 # export FLAGS_conv_workspace_size_limit=4000
# default memeory allocator strategy may case gpu training hang
# for no OOM raised when memory exhaused
export FLAGS_allocator_strategy=naive_best_fit
if [ ${ngpu} == 0 ]; then if [ ${ngpu} == 0 ]; then
python3 -u ${BIN_DIR}/train.py \ python3 -u ${BIN_DIR}/train.py \
--ngpu ${ngpu} \ --ngpu ${ngpu} \

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