Merge branch 'database-search' of github.com:qingen/PaddleSpeech into database-search

README.md

@@ -7,6 +7,7 @@
 
   <h3>
   <a href="#quick-start"> Quick Start </a>
+  | <a href="#quick-start-server"> Quick Start Server </a>
   | <a href="#documents"> Documents </a>
   | <a href="#model-list"> Models List </a>
 </div>
@@ -178,6 +179,8 @@ Via the easy-to-use, efficient, flexible and scalable implementation, our vision
 <!---
 2021.12.14: We would like to have an online courses to introduce basics and research of speech, as well as code practice with `paddlespeech`. Please pay attention to our [Calendar](https://www.paddlepaddle.org.cn/live).
 --->
+- 👏🏻  2022.03.28: PaddleSpeech Server is available for Audio Classification, Automatic Speech Recognition and Text-to-Speech.
+- 👏🏻  2022.03.28: PaddleSpeech CLI is available for Speaker Verfication.
 - 🤗  2021.12.14: Our PaddleSpeech [ASR](https://huggingface.co/spaces/KPatrick/PaddleSpeechASR) and [TTS](https://huggingface.co/spaces/KPatrick/PaddleSpeechTTS) Demos on Hugging Face Spaces are available!
 - 👏🏻  2021.12.10: PaddleSpeech CLI is available for Audio Classification, Automatic Speech Recognition, Speech Translation (English to Chinese) and Text-to-Speech.
 
@@ -203,6 +206,11 @@ Developers can have a try of our models with [PaddleSpeech Command Line](./paddl
 paddlespeech cls --input input.wav
 ```
 
+**Speaker Verification**
+```
+paddlespeech vector --task spk --input input_16k.wav
+```
+
 **Automatic Speech Recognition**
 ```shell
 paddlespeech asr --lang zh --input input_16k.wav
@@ -242,6 +250,36 @@ For more command lines, please see: [demos](https://github.com/PaddlePaddle/Padd
 
 If you want to try more functions like training and tuning, please have a look at [Speech-to-Text Quick Start](./docs/source/asr/quick_start.md) and [Text-to-Speech Quick Start](./docs/source/tts/quick_start.md).
 
+
+<a name="quickstartserver"></a>
+## Quick Start Server
+
+Developers can have a try of our speech server with [PaddleSpeech Server Command Line](./paddlespeech/server/README.md).
+
+**Start server**     
+```shell
+paddlespeech_server start --config_file ./paddlespeech/server/conf/application.yaml
+```
+
+**Access Speech Recognition Services**     
+```shell
+paddlespeech_client asr --server_ip 127.0.0.1 --port 8090 --input input_16k.wav
+```
+
+**Access Text to Speech Services**     
+```shell
+paddlespeech_client tts --server_ip 127.0.0.1 --port 8090 --input "您好，欢迎使用百度飞桨语音合成服务。" --output output.wav
+```
+
+**Access Audio Classification Services**     
+```shell
+paddlespeech_client cls --server_ip 127.0.0.1 --port 8090 --input input.wav
+```
+
+
+For more information about server command lines, please see: [speech server demos](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/demos/speech_server)
+
+
 ## Model List
 
 PaddleSpeech supports a series of most popular models. They are summarized in [released models](./docs/source/released_model.md) and attached with available pretrained models.
@@ -458,6 +496,29 @@ PaddleSpeech supports a series of most popular models. They are summarized in [r
   </tbody>
 </table>
 
+**Speaker Verification**
+
+<table style="width:100%">
+  <thead>
+    <tr>
+      <th> Task </th>
+      <th> Dataset </th>
+      <th> Model Type </th>
+      <th> Link </th>
+    </tr>
+  </thead>
+  <tbody>
+  <tr>
+      <td>Speaker Verification</td>
+      <td>VoxCeleb12</td>
+      <td>ECAPA-TDNN</td>
+      <td>
+      <a href = "./examples/voxceleb/sv0">ecapa-tdnn-voxceleb12</a>
+      </td>
+    </tr>
+  </tbody>
+</table>
+
 **Punctuation Restoration**
 
 <table style="width:100%">
@@ -499,6 +560,7 @@ Normally, [Speech SoTA](https://paperswithcode.com/area/speech), [Audio SoTA](ht
     - [Chinese Rule Based Text Frontend](./docs/source/tts/zh_text_frontend.md)
     - [Test Audio Samples](https://paddlespeech.readthedocs.io/en/latest/tts/demo.html)
   - [Audio Classification](./demos/audio_tagging/README.md)
+  - [Speaker Verification](./demos/speaker_verification/README.md)
   - [Speech Translation](./demos/speech_translation/README.md)
 - [Released Models](./docs/source/released_model.md)
 - [Community](#Community)

README_cn.md

@@ -6,6 +6,7 @@
 
   <h3>
   <a href="#quick-start"> 快速开始 </a>
+  | <a href="#quick-start-server"> 快速使用服务 </a>
   | <a href="#documents"> 教程文档 </a>
   | <a href="#model-list"> 模型列表 </a>
 </div>
@@ -179,7 +180,9 @@ from https://github.com/18F/open-source-guide/blob/18f-pages/pages/making-readme
 <!---
 2021.12.14: We would like to have an online courses to introduce basics and research of speech, as well as code practice with `paddlespeech`. Please pay attention to our [Calendar](https://www.paddlepaddle.org.cn/live).
 --->
-- 🤗 2021.12.14: 我们在 Hugging Face Spaces 上的 [ASR](https://huggingface.co/spaces/KPatrick/PaddleSpeechASR) 以及 [TTS](https://huggingface.co/spaces/akhaliq/paddlespeech) Demos 上线啦!
+- 👏🏻 2022.03.28: PaddleSpeech Server 上线! 覆盖了声音分类、语音识别、以及语音合成。
+- 👏🏻 2022.03.28: PaddleSpeech CLI 上线声纹验证。
+- 🤗  2021.12.14: Our PaddleSpeech [ASR](https://huggingface.co/spaces/KPatrick/PaddleSpeechASR) and [TTS](https://huggingface.co/spaces/KPatrick/PaddleSpeechTTS) Demos on Hugging Face Spaces are available!
 - 👏🏻 2021.12.10: PaddleSpeech CLI 上线！覆盖了声音分类、语音识别、语音翻译（英译中）以及语音合成。
 
 ### 技术交流群
@@ -202,6 +205,10 @@ from https://github.com/18F/open-source-guide/blob/18f-pages/pages/making-readme
 ```shell
 paddlespeech cls --input input.wav
 ```
+**声纹识别**
+```shell
+paddlespeech vector --task spk --input input_16k.wav
+```
 **语音识别**
 ```shell
 paddlespeech asr --lang zh --input input_16k.wav
@@ -236,6 +243,33 @@ paddlespeech asr --input ./zh.wav | paddlespeech text --task punc
 更多命令行命令请参考 [demos](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/demos)
 > Note: 如果需要训练或者微调，请查看[语音识别](./docs/source/asr/quick_start.md)， [语音合成](./docs/source/tts/quick_start.md)。
 
+
+## 快速使用服务
+安装完成后，开发者可以通过命令行快速使用服务。
+
+**启动服务**     
+```shell
+paddlespeech_server start --config_file ./paddlespeech/server/conf/application.yaml
+```
+
+**访问语音识别服务**     
+```shell
+paddlespeech_client asr --server_ip 127.0.0.1 --port 8090 --input input_16k.wav
+```
+
+**访问语音合成服务**     
+```shell
+paddlespeech_client tts --server_ip 127.0.0.1 --port 8090 --input "您好，欢迎使用百度飞桨语音合成服务。" --output output.wav
+```
+
+**访问音频分类服务**     
+```shell
+paddlespeech_client cls --server_ip 127.0.0.1 --port 8090 --input input.wav
+```
+
+更多服务相关的命令行使用信息，请参考 [demos](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/demos/speech_server)
+
+
 ## 模型列表
 PaddleSpeech 支持很多主流的模型，并提供了预训练模型，详情请见[模型列表](./docs/source/released_model.md)。
 
@@ -453,6 +487,30 @@ PaddleSpeech 的 **语音合成** 主要包含三个模块：文本前端、声
   </tbody>
 </table>
 
+
+**声纹识别**
+
+<table style="width:100%">
+  <thead>
+    <tr>
+      <th> Task </th>
+      <th> Dataset </th>
+      <th> Model Type </th>
+      <th> Link </th>
+    </tr>
+  </thead>
+  <tbody>
+  <tr>
+      <td>Speaker Verification</td>
+      <td>VoxCeleb12</td>
+      <td>ECAPA-TDNN</td>
+      <td>
+      <a href = "./examples/voxceleb/sv0">ecapa-tdnn-voxceleb12</a>
+      </td>
+    </tr>
+  </tbody>
+</table>
+
 **标点恢复**
 
 <table style="width:100%">
@@ -499,6 +557,7 @@ PaddleSpeech 的 **语音合成** 主要包含三个模块：文本前端、声
     - [中文文本前端](./docs/source/tts/zh_text_frontend.md)
     - [测试语音样本](https://paddlespeech.readthedocs.io/en/latest/tts/demo.html)
   - [声音分类](./demos/audio_tagging/README_cn.md)
+  - [声纹识别](./demos/speaker_verification/README_cn.md)
   - [语音翻译](./demos/speech_translation/README_cn.md)
 - [模型列表](#模型列表)
   - [语音识别](#语音识别模型)
@@ -521,6 +580,15 @@ author={PaddlePaddle Authors},
 howpublished = {\url{https://github.com/PaddlePaddle/PaddleSpeech}},
 year={2021}
 }
+
+@inproceedings{zheng2021fused,
+  title={Fused acoustic and text encoding for multimodal bilingual pretraining and speech translation},
+  author={Zheng, Renjie and Chen, Junkun and Ma, Mingbo and Huang, Liang},
+  booktitle={International Conference on Machine Learning},
+  pages={12736--12746},
+  year={2021},
+  organization={PMLR}
+}
 ```
 
 <a name="欢迎贡献"></a>
@@ -568,7 +636,6 @@ year={2021}
 ## 致谢
 
 - 非常感谢 [yeyupiaoling](https://github.com/yeyupiaoling)/[PPASR](https://github.com/yeyupiaoling/PPASR)/[PaddlePaddle-DeepSpeech](https://github.com/yeyupiaoling/PaddlePaddle-DeepSpeech)/[VoiceprintRecognition-PaddlePaddle](https://github.com/yeyupiaoling/VoiceprintRecognition-PaddlePaddle)/[AudioClassification-PaddlePaddle](https://github.com/yeyupiaoling/AudioClassification-PaddlePaddle) 多年来的关注和建议，以及在诸多问题上的帮助。
-- 非常感谢 [AK391](https://github.com/AK391) 在 Huggingface Spaces 上使用 Gradio 对我们的语音合成功能进行网页版演示。
 - 非常感谢 [mymagicpower](https://github.com/mymagicpower) 采用PaddleSpeech 对 ASR 的[短语音](https://github.com/mymagicpower/AIAS/tree/main/3_audio_sdks/asr_sdk)及[长语音](https://github.com/mymagicpower/AIAS/tree/main/3_audio_sdks/asr_long_audio_sdk)进行 Java 实现。
 - 非常感谢 [JiehangXie](https://github.com/JiehangXie)/[PaddleBoBo](https://github.com/JiehangXie/PaddleBoBo) 采用 PaddleSpeech 语音合成功能实现 Virtual Uploader(VUP)/Virtual YouTuber(VTuber) 虚拟主播。
 - 非常感谢 [745165806](https://github.com/745165806)/[PaddleSpeechTask](https://github.com/745165806/PaddleSpeechTask) 贡献标点重建相关模型。

demos/speaker_verification/README.md

+([简体中文](./README_cn.md)|English)
+# Speech Verification)
+
+## Introduction
+
+Speaker Verification, refers to the problem of getting a speaker embedding from an audio. 
+
+This demo is an implementation to extract speaker embedding from a specific audio file. It can be done by a single command or a few lines in python using `PaddleSpeech`. 
+
+## Usage
+### 1. Installation
+see [installation](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/docs/source/install.md).
+
+You can choose one way from easy, meduim and hard to install paddlespeech.
+
+### 2. Prepare Input File
+The input of this demo should be a WAV file(`.wav`), and the sample rate must be the same as the model.
+
+Here are sample files for this demo that can be downloaded:
+```bash
+wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav
+```
+
+### 3. Usage
+- Command Line(Recommended)
+  ```bash
+  paddlespeech vector --task spk --input 85236145389.wav
+
+  echo -e "demo1 85236145389.wav" > vec.job
+  paddlespeech vector --task spk --input vec.job
+
+  echo -e "demo2 85236145389.wav \n demo3 85236145389.wav" | paddlespeech vector --task spk
+  ```
+  
+  Usage:
+  ```bash
+  paddlespeech vector --help
+  ```
+  Arguments:
+  - `input`(required): Audio file to recognize.
+  - `model`: Model type of vector task. Default: `ecapatdnn_voxceleb12`.
+  - `sample_rate`: Sample rate of the model. Default: `16000`.
+  - `config`: Config of vector task. Use pretrained model when it is None. Default: `None`.
+  - `ckpt_path`: Model checkpoint. Use pretrained model when it is None. Default: `None`.
+  - `device`: Choose device to execute model inference. Default: default device of paddlepaddle in current environment.
+
+  Output:
+
+```bash
+  demo  {'dim': 192, 'embedding': array([ -5.749211  ,   9.505463  ,  -8.200284  ,  -5.2075014 ,
+         5.3940268 ,  -3.04878   ,   1.611095  ,  10.127234  ,
+       -10.534177  , -15.821609  ,   1.2032688 ,  -0.35080156,
+         1.2629458 , -12.643498  ,  -2.5758228 , -11.343508  ,
+         2.3385992 ,  -8.719341  ,  14.213509  ,  15.404744  ,
+        -0.39327756,   6.338786  ,   2.688887  ,   8.7104025 ,
+        17.469526  ,  -8.77959   ,   7.0576906 ,   4.648855  ,
+        -1.3089896 , -23.294737  ,   8.013747  ,  13.891729  ,
+        -9.926753  ,   5.655307  ,  -5.9422326 , -22.842539  ,
+         0.6293588 , -18.46266   , -10.811862  ,   9.8192625 ,
+         3.0070958 ,   3.8072643 ,  -2.3861165 ,   3.0821571 ,
+       -14.739942  ,   1.7594414 ,  -0.6485091 ,   4.485623  ,
+         2.0207152 ,   7.264915  ,  -6.40137   ,  23.63524   ,
+         2.9711294 , -22.708025  ,   9.93719   ,  20.354511  ,
+       -10.324688  ,  -0.700492  ,  -8.783211  ,  -5.27593   ,
+        15.999649  ,   3.3004563 ,  12.747926  ,  15.429879  ,
+         4.7849145 ,   5.6699696 ,  -2.3826702 ,  10.605882  ,
+         3.9112158 ,   3.1500628 ,  15.859915  ,  -2.1832209 ,
+       -23.908653  ,  -6.4799504 ,  -4.5365124 ,  -9.224193  ,
+        14.568347  , -10.568833  ,   4.982321  ,  -4.342062  ,
+         0.0914714 ,  12.645902  ,  -5.74285   ,  -3.2141201 ,
+        -2.7173362 ,  -6.680575  ,   0.4757669 ,  -5.035051  ,
+        -6.7964664 ,  16.865469  , -11.54324   ,   7.681869  ,
+         0.44475392,   9.708182  ,  -8.932846  ,   0.4123232 ,
+        -4.361452  ,   1.3948607 ,   9.511665  ,   0.11667654,
+         2.9079323 ,   6.049952  ,   9.275183  , -18.078873  ,
+         6.2983274 ,  -0.7500531 ,  -2.725033  ,  -7.6027865 ,
+         3.3404543 ,   2.990815  ,   4.010979  ,  11.000591  ,
+        -2.8873312 ,   7.1352735 , -16.79663   ,  18.495346  ,
+       -14.293832  ,   7.89578   ,   2.2714825 ,  22.976387  ,
+        -4.875734  ,  -3.0836344 ,  -2.9999814 ,  13.751918  ,
+         6.448228  , -11.924197  ,   2.171869  ,   2.0423572 ,
+        -6.173772  ,  10.778437  ,  25.77281   ,  -4.9495463 ,
+        14.57806   ,   0.3044315 ,   2.6132357 ,  -7.591999  ,
+        -2.076944  ,   9.025118  ,   1.7834753 ,  -3.1799617 ,
+        -4.9401326 ,  23.465864  ,   5.1685796 ,  -9.018578  ,
+         9.037825  ,  -4.4150195 ,   6.859591  , -12.274467  ,
+        -0.88911164,   5.186309  ,  -3.9988663 , -13.638606  ,
+        -9.925445  ,  -0.06329413,  -3.6709652 , -12.397416  ,
+       -12.719869  ,  -1.395601  ,   2.1150916 ,   5.7381287 ,
+        -4.4691963 ,  -3.82819   ,  -0.84233856,  -1.1604277 ,
+       -13.490127  ,   8.731719  , -20.778936  , -11.495662  ,
+         5.8033476 ,  -4.752041  ,  10.833007  ,  -6.717991  ,
+         4.504732  ,  13.4244375 ,   1.1306485 ,   7.3435574 ,
+         1.400918  ,  14.704036  ,  -9.501399  ,   7.2315617 ,
+        -6.417456  ,   1.3333273 ,  11.872697  ,  -0.30664724,
+         8.8845    ,   6.5569253 ,   4.7948146 ,   0.03662816,
+        -8.704245  ,   6.224871  ,  -3.2701402 , -11.508579  ],
+      dtype=float32)}
+  ```
+
+- Python API
+  ```python
+  import paddle
+  from paddlespeech.cli import VectorExecutor
+
+  vector_executor = VectorExecutor()
+  audio_emb = vector_executor(
+      model='ecapatdnn_voxceleb12',
+      sample_rate=16000,
+      config=None, 
+      ckpt_path=None,
+      audio_file='./85236145389.wav',
+      force_yes=False,
+      device=paddle.get_device())
+  print('Audio embedding Result: \n{}'.format(audio_emb))
+  ```
+
+  Output:
+  ```bash
+  # Vector Result:
+   {'dim': 192, 'embedding': array([ -5.749211  ,   9.505463  ,  -8.200284  ,  -5.2075014 ,
+         5.3940268 ,  -3.04878   ,   1.611095  ,  10.127234  ,
+       -10.534177  , -15.821609  ,   1.2032688 ,  -0.35080156,
+         1.2629458 , -12.643498  ,  -2.5758228 , -11.343508  ,
+         2.3385992 ,  -8.719341  ,  14.213509  ,  15.404744  ,
+        -0.39327756,   6.338786  ,   2.688887  ,   8.7104025 ,
+        17.469526  ,  -8.77959   ,   7.0576906 ,   4.648855  ,
+        -1.3089896 , -23.294737  ,   8.013747  ,  13.891729  ,
+        -9.926753  ,   5.655307  ,  -5.9422326 , -22.842539  ,
+         0.6293588 , -18.46266   , -10.811862  ,   9.8192625 ,
+         3.0070958 ,   3.8072643 ,  -2.3861165 ,   3.0821571 ,
+       -14.739942  ,   1.7594414 ,  -0.6485091 ,   4.485623  ,
+         2.0207152 ,   7.264915  ,  -6.40137   ,  23.63524   ,
+         2.9711294 , -22.708025  ,   9.93719   ,  20.354511  ,
+       -10.324688  ,  -0.700492  ,  -8.783211  ,  -5.27593   ,
+        15.999649  ,   3.3004563 ,  12.747926  ,  15.429879  ,
+         4.7849145 ,   5.6699696 ,  -2.3826702 ,  10.605882  ,
+         3.9112158 ,   3.1500628 ,  15.859915  ,  -2.1832209 ,
+       -23.908653  ,  -6.4799504 ,  -4.5365124 ,  -9.224193  ,
+        14.568347  , -10.568833  ,   4.982321  ,  -4.342062  ,
+         0.0914714 ,  12.645902  ,  -5.74285   ,  -3.2141201 ,
+        -2.7173362 ,  -6.680575  ,   0.4757669 ,  -5.035051  ,
+        -6.7964664 ,  16.865469  , -11.54324   ,   7.681869  ,
+         0.44475392,   9.708182  ,  -8.932846  ,   0.4123232 ,
+        -4.361452  ,   1.3948607 ,   9.511665  ,   0.11667654,
+         2.9079323 ,   6.049952  ,   9.275183  , -18.078873  ,
+         6.2983274 ,  -0.7500531 ,  -2.725033  ,  -7.6027865 ,
+         3.3404543 ,   2.990815  ,   4.010979  ,  11.000591  ,
+        -2.8873312 ,   7.1352735 , -16.79663   ,  18.495346  ,
+       -14.293832  ,   7.89578   ,   2.2714825 ,  22.976387  ,
+        -4.875734  ,  -3.0836344 ,  -2.9999814 ,  13.751918  ,
+         6.448228  , -11.924197  ,   2.171869  ,   2.0423572 ,
+        -6.173772  ,  10.778437  ,  25.77281   ,  -4.9495463 ,
+        14.57806   ,   0.3044315 ,   2.6132357 ,  -7.591999  ,
+        -2.076944  ,   9.025118  ,   1.7834753 ,  -3.1799617 ,
+        -4.9401326 ,  23.465864  ,   5.1685796 ,  -9.018578  ,
+         9.037825  ,  -4.4150195 ,   6.859591  , -12.274467  ,
+        -0.88911164,   5.186309  ,  -3.9988663 , -13.638606  ,
+        -9.925445  ,  -0.06329413,  -3.6709652 , -12.397416  ,
+       -12.719869  ,  -1.395601  ,   2.1150916 ,   5.7381287 ,
+        -4.4691963 ,  -3.82819   ,  -0.84233856,  -1.1604277 ,
+       -13.490127  ,   8.731719  , -20.778936  , -11.495662  ,
+         5.8033476 ,  -4.752041  ,  10.833007  ,  -6.717991  ,
+         4.504732  ,  13.4244375 ,   1.1306485 ,   7.3435574 ,
+         1.400918  ,  14.704036  ,  -9.501399  ,   7.2315617 ,
+        -6.417456  ,   1.3333273 ,  11.872697  ,  -0.30664724,
+         8.8845    ,   6.5569253 ,   4.7948146 ,   0.03662816,
+        -8.704245  ,   6.224871  ,  -3.2701402 , -11.508579  ],
+      dtype=float32)}
+  ```
+
+### 4.Pretrained Models
+
+Here is a list of pretrained models released by PaddleSpeech that can be used by command and python API:
+
+| Model | Sample Rate
+| :--- | :---: |
+| ecapatdnn_voxceleb12 | 16k

demos/speaker_verification/README_cn.md

+(简体中文|[English](./README.md))
+
+# 声纹识别
+## 介绍
+声纹识别是一项用计算机程序自动提取说话人特征的技术。
+
+这个 demo 是一个从给定音频文件提取说话人特征，它可以通过使用 `PaddleSpeech` 的单个命令或 python 中的几行代码来实现。
+
+## 使用方法
+### 1. 安装
+请看[安装文档](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/docs/source/install_cn.md)。
+
+你可以从 easy，medium，hard 三中方式中选择一种方式安装。
+
+### 2. 准备输入
+这个 demo 的输入应该是一个 WAV 文件（`.wav`），并且采样率必须与模型的采样率相同。
+
+可以下载此 demo 的示例音频：
+```bash
+# 该音频的内容是数字串 85236145389
+wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav
+```
+### 3. 使用方法
+- 命令行 (推荐使用)
+  ```bash
+  paddlespeech vector --task spk --input 85236145389.wav
+
+  echo -e "demo1 85236145389.wav" > vec.job
+  paddlespeech vector --task spk --input vec.job
+
+  echo -e "demo2 85236145389.wav \n demo3 85236145389.wav" | paddlespeech vector --task spk
+  ```
+  
+  使用方法：
+  ```bash
+  paddlespeech vector --help
+  ```
+  参数：
+  - `input`(必须输入)：用于识别的音频文件。
+  - `model`：声纹任务的模型，默认值：`ecapatdnn_voxceleb12`。
+  - `sample_rate`：音频采样率，默认值：`16000`。
+  - `config`：声纹任务的参数文件，若不设置则使用预训练模型中的默认配置，默认值：`None`。
+  - `ckpt_path`：模型参数文件，若不设置则下载预训练模型使用，默认值：`None`。
+  - `device`：执行预测的设备，默认值：当前系统下 paddlepaddle 的默认 device。
+
+  输出：
+  ```bash
+  demo  {'dim': 192, 'embedding': array([ -5.749211  ,   9.505463  ,  -8.200284  ,  -5.2075014 ,
+         5.3940268 ,  -3.04878   ,   1.611095  ,  10.127234  ,
+       -10.534177  , -15.821609  ,   1.2032688 ,  -0.35080156,
+         1.2629458 , -12.643498  ,  -2.5758228 , -11.343508  ,
+         2.3385992 ,  -8.719341  ,  14.213509  ,  15.404744  ,
+        -0.39327756,   6.338786  ,   2.688887  ,   8.7104025 ,
+        17.469526  ,  -8.77959   ,   7.0576906 ,   4.648855  ,
+        -1.3089896 , -23.294737  ,   8.013747  ,  13.891729  ,
+        -9.926753  ,   5.655307  ,  -5.9422326 , -22.842539  ,
+         0.6293588 , -18.46266   , -10.811862  ,   9.8192625 ,
+         3.0070958 ,   3.8072643 ,  -2.3861165 ,   3.0821571 ,
+       -14.739942  ,   1.7594414 ,  -0.6485091 ,   4.485623  ,
+         2.0207152 ,   7.264915  ,  -6.40137   ,  23.63524   ,
+         2.9711294 , -22.708025  ,   9.93719   ,  20.354511  ,
+       -10.324688  ,  -0.700492  ,  -8.783211  ,  -5.27593   ,
+        15.999649  ,   3.3004563 ,  12.747926  ,  15.429879  ,
+         4.7849145 ,   5.6699696 ,  -2.3826702 ,  10.605882  ,
+         3.9112158 ,   3.1500628 ,  15.859915  ,  -2.1832209 ,
+       -23.908653  ,  -6.4799504 ,  -4.5365124 ,  -9.224193  ,
+        14.568347  , -10.568833  ,   4.982321  ,  -4.342062  ,
+         0.0914714 ,  12.645902  ,  -5.74285   ,  -3.2141201 ,
+        -2.7173362 ,  -6.680575  ,   0.4757669 ,  -5.035051  ,
+        -6.7964664 ,  16.865469  , -11.54324   ,   7.681869  ,
+         0.44475392,   9.708182  ,  -8.932846  ,   0.4123232 ,
+        -4.361452  ,   1.3948607 ,   9.511665  ,   0.11667654,
+         2.9079323 ,   6.049952  ,   9.275183  , -18.078873  ,
+         6.2983274 ,  -0.7500531 ,  -2.725033  ,  -7.6027865 ,
+         3.3404543 ,   2.990815  ,   4.010979  ,  11.000591  ,
+        -2.8873312 ,   7.1352735 , -16.79663   ,  18.495346  ,
+       -14.293832  ,   7.89578   ,   2.2714825 ,  22.976387  ,
+        -4.875734  ,  -3.0836344 ,  -2.9999814 ,  13.751918  ,
+         6.448228  , -11.924197  ,   2.171869  ,   2.0423572 ,
+        -6.173772  ,  10.778437  ,  25.77281   ,  -4.9495463 ,
+        14.57806   ,   0.3044315 ,   2.6132357 ,  -7.591999  ,
+        -2.076944  ,   9.025118  ,   1.7834753 ,  -3.1799617 ,
+        -4.9401326 ,  23.465864  ,   5.1685796 ,  -9.018578  ,
+         9.037825  ,  -4.4150195 ,   6.859591  , -12.274467  ,
+        -0.88911164,   5.186309  ,  -3.9988663 , -13.638606  ,
+        -9.925445  ,  -0.06329413,  -3.6709652 , -12.397416  ,
+       -12.719869  ,  -1.395601  ,   2.1150916 ,   5.7381287 ,
+        -4.4691963 ,  -3.82819   ,  -0.84233856,  -1.1604277 ,
+       -13.490127  ,   8.731719  , -20.778936  , -11.495662  ,
+         5.8033476 ,  -4.752041  ,  10.833007  ,  -6.717991  ,
+         4.504732  ,  13.4244375 ,   1.1306485 ,   7.3435574 ,
+         1.400918  ,  14.704036  ,  -9.501399  ,   7.2315617 ,
+        -6.417456  ,   1.3333273 ,  11.872697  ,  -0.30664724,
+         8.8845    ,   6.5569253 ,   4.7948146 ,   0.03662816,
+        -8.704245  ,   6.224871  ,  -3.2701402 , -11.508579  ],
+      dtype=float32)}
+  ```
+
+- Python API
+  ```python
+  import paddle
+  from paddlespeech.cli import VectorExecutor
+
+  vector_executor = VectorExecutor()
+  audio_emb = vector_executor(
+      model='ecapatdnn_voxceleb12',
+      sample_rate=16000,
+      config=None,  # Set `config` and `ckpt_path` to None to use pretrained model.
+      ckpt_path=None,
+      audio_file='./85236145389.wav',
+      force_yes=False,
+      device=paddle.get_device())
+  print('Audio embedding Result: \n{}'.format(audio_emb))
+  ```
+
+  输出：
+  ```bash
+  # Vector Result:
+   {'dim': 192, 'embedding': array([ -5.749211  ,   9.505463  ,  -8.200284  ,  -5.2075014 ,
+         5.3940268 ,  -3.04878   ,   1.611095  ,  10.127234  ,
+       -10.534177  , -15.821609  ,   1.2032688 ,  -0.35080156,
+         1.2629458 , -12.643498  ,  -2.5758228 , -11.343508  ,
+         2.3385992 ,  -8.719341  ,  14.213509  ,  15.404744  ,
+        -0.39327756,   6.338786  ,   2.688887  ,   8.7104025 ,
+        17.469526  ,  -8.77959   ,   7.0576906 ,   4.648855  ,
+        -1.3089896 , -23.294737  ,   8.013747  ,  13.891729  ,
+        -9.926753  ,   5.655307  ,  -5.9422326 , -22.842539  ,
+         0.6293588 , -18.46266   , -10.811862  ,   9.8192625 ,
+         3.0070958 ,   3.8072643 ,  -2.3861165 ,   3.0821571 ,
+       -14.739942  ,   1.7594414 ,  -0.6485091 ,   4.485623  ,
+         2.0207152 ,   7.264915  ,  -6.40137   ,  23.63524   ,
+         2.9711294 , -22.708025  ,   9.93719   ,  20.354511  ,
+       -10.324688  ,  -0.700492  ,  -8.783211  ,  -5.27593   ,
+        15.999649  ,   3.3004563 ,  12.747926  ,  15.429879  ,
+         4.7849145 ,   5.6699696 ,  -2.3826702 ,  10.605882  ,
+         3.9112158 ,   3.1500628 ,  15.859915  ,  -2.1832209 ,
+       -23.908653  ,  -6.4799504 ,  -4.5365124 ,  -9.224193  ,
+        14.568347  , -10.568833  ,   4.982321  ,  -4.342062  ,
+         0.0914714 ,  12.645902  ,  -5.74285   ,  -3.2141201 ,
+        -2.7173362 ,  -6.680575  ,   0.4757669 ,  -5.035051  ,
+        -6.7964664 ,  16.865469  , -11.54324   ,   7.681869  ,
+         0.44475392,   9.708182  ,  -8.932846  ,   0.4123232 ,
+        -4.361452  ,   1.3948607 ,   9.511665  ,   0.11667654,
+         2.9079323 ,   6.049952  ,   9.275183  , -18.078873  ,
+         6.2983274 ,  -0.7500531 ,  -2.725033  ,  -7.6027865 ,
+         3.3404543 ,   2.990815  ,   4.010979  ,  11.000591  ,
+        -2.8873312 ,   7.1352735 , -16.79663   ,  18.495346  ,
+       -14.293832  ,   7.89578   ,   2.2714825 ,  22.976387  ,
+        -4.875734  ,  -3.0836344 ,  -2.9999814 ,  13.751918  ,
+         6.448228  , -11.924197  ,   2.171869  ,   2.0423572 ,
+        -6.173772  ,  10.778437  ,  25.77281   ,  -4.9495463 ,
+        14.57806   ,   0.3044315 ,   2.6132357 ,  -7.591999  ,
+        -2.076944  ,   9.025118  ,   1.7834753 ,  -3.1799617 ,
+        -4.9401326 ,  23.465864  ,   5.1685796 ,  -9.018578  ,
+         9.037825  ,  -4.4150195 ,   6.859591  , -12.274467  ,
+        -0.88911164,   5.186309  ,  -3.9988663 , -13.638606  ,
+        -9.925445  ,  -0.06329413,  -3.6709652 , -12.397416  ,
+       -12.719869  ,  -1.395601  ,   2.1150916 ,   5.7381287 ,
+        -4.4691963 ,  -3.82819   ,  -0.84233856,  -1.1604277 ,
+       -13.490127  ,   8.731719  , -20.778936  , -11.495662  ,
+         5.8033476 ,  -4.752041  ,  10.833007  ,  -6.717991  ,
+         4.504732  ,  13.4244375 ,   1.1306485 ,   7.3435574 ,
+         1.400918  ,  14.704036  ,  -9.501399  ,   7.2315617 ,
+        -6.417456  ,   1.3333273 ,  11.872697  ,  -0.30664724,
+         8.8845    ,   6.5569253 ,   4.7948146 ,   0.03662816,
+        -8.704245  ,   6.224871  ,  -3.2701402 , -11.508579  ],
+      dtype=float32)}
+  ```
+
+### 4.预训练模型
+以下是 PaddleSpeech 提供的可以被命令行和 python API 使用的预训练模型列表：
+
+| 模型 | 采样率
+| :--- | :---: |
+| ecapatdnn_voxceleb12 | 16k

demos/speaker_verification/run.sh

+#!/bin/bash
+
+wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav
+
+# asr
+paddlespeech vector --task spk --input ./85236145389.wav
\ No newline at end of file

demos/speech_server/README.md

@@ -15,8 +15,8 @@ You can choose one way from meduim and hard to install paddlespeech.
 
 ### 2. Prepare config File
 The configuration file can be found in `conf/application.yaml` .
-Among them, `engine_list` indicates the speech engine that will be included in the service to be started, in the format of <speech task>_<engine type>.
-At present, the speech tasks integrated by the service include: asr (speech recognition) and tts (speech synthesis).
+Among them, `engine_list` indicates the speech engine that will be included in the service to be started, in the format of `<speech task>_<engine type>`.
+At present, the speech tasks integrated by the service include: asr (speech recognition), tts (text to sppech) and cls (audio classification).
 Currently the engine type supports two forms: python and inference (Paddle Inference)
 
 

demos/speech_server/README_cn.md

@@ -17,7 +17,7 @@
 ### 2. 准备配置文件
 配置文件可参见 `conf/application.yaml` 。
 其中，`engine_list`表示即将启动的服务将会包含的语音引擎，格式为 <语音任务>_<引擎类型>。
-目前服务集成的语音任务有： asr(语音识别)、tts(语音合成)。
+目前服务集成的语音任务有： asr(语音识别)、tts(语音合成)以及cls(音频分类)。
 目前引擎类型支持两种形式：python 及 inference (Paddle Inference)
 
 

docs/source/released_model.md

@@ -75,6 +75,12 @@ Model Type | Dataset| Example Link | Pretrained Models | Static Models
 PANN | Audioset| [audioset_tagging_cnn](https://github.com/qiuqiangkong/audioset_tagging_cnn) | [panns_cnn6.pdparams](https://bj.bcebos.com/paddleaudio/models/panns_cnn6.pdparams), [panns_cnn10.pdparams](https://bj.bcebos.com/paddleaudio/models/panns_cnn10.pdparams), [panns_cnn14.pdparams](https://bj.bcebos.com/paddleaudio/models/panns_cnn14.pdparams) | [panns_cnn6_static.tar.gz](https://paddlespeech.bj.bcebos.com/cls/inference_model/panns_cnn6_static.tar.gz)(18M), [panns_cnn10_static.tar.gz](https://paddlespeech.bj.bcebos.com/cls/inference_model/panns_cnn10_static.tar.gz)(19M), [panns_cnn14_static.tar.gz](https://paddlespeech.bj.bcebos.com/cls/inference_model/panns_cnn14_static.tar.gz)(289M) 
 PANN | ESC-50 |[pann-esc50](../../examples/esc50/cls0)|[esc50_cnn6.tar.gz](https://paddlespeech.bj.bcebos.com/cls/esc50/esc50_cnn6.tar.gz), [esc50_cnn10.tar.gz](https://paddlespeech.bj.bcebos.com/cls/esc50/esc50_cnn10.tar.gz), [esc50_cnn14.tar.gz](https://paddlespeech.bj.bcebos.com/cls/esc50/esc50_cnn14.tar.gz)
 
+## Speaker Verification Models
+
+Model Type | Dataset| Example Link | Pretrained Models | Static Models 
+:-------------:| :------------:| :-----: | :-----: | :-----:
+PANN | VoxCeleb| [voxceleb_ecapatdnn](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/voxceleb/sv0) | [ecapatdnn.tar.gz](https://paddlespeech.bj.bcebos.com/vector/voxceleb/sv0_ecapa_tdnn_voxceleb12_ckpt_0_1_1.tar.gz) | -
+
 ## Punctuation Restoration Models
 Model Type | Dataset| Example Link | Pretrained Models
 :-------------:| :------------:| :-----: | :-----:

examples/voxceleb/sv0/RESULT.md

+# VoxCeleb
+
+## ECAPA-TDNN 
+
+| Model | Number of Params | Release | Config | dim | Test set |  Cosine | Cosine + S-Norm | 
+| --- | --- | --- | --- | --- | --- | --- | ---- |
+| ECAPA-TDNN | 85M | 0.1.1 | conf/ecapa_tdnn.yaml |192 | test | 1.15 |  1.06 | 

paddlespeech/cli/README.md

@@ -13,6 +13,12 @@
  paddlespeech cls --input input.wav
  ```
 
+ ## Speaker Verification
+
+ ```bash
+ paddlespeech vector --task spk --input input_16k.wav
+ ```
+
  ## Automatic Speech Recognition
  ```
  paddlespeech asr --lang zh --input input_16k.wav

paddlespeech/cli/README_cn.md

@@ -12,6 +12,12 @@
  ## 声音分类
  ```bash
  paddlespeech cls --input input.wav
+ ```
+
+  ## 声纹识别
+
+ ```bash
+ paddlespeech vector --task spk --input input_16k.wav
  ```
 
  ## 语音识别

paddlespeech/cli/vector/infer.py

@@ -42,13 +42,15 @@ pretrained_models = {
     # "paddlespeech vector --task spk --model ecapatdnn_voxceleb12-16k --sr 16000 --input ./input.wav"
     "ecapatdnn_voxceleb12-16k": {
         'url':
-        'https://paddlespeech.bj.bcebos.com/vector/voxceleb/sv0_ecapa_tdnn_voxceleb12_ckpt_0_1_0.tar.gz',
+        'https://paddlespeech.bj.bcebos.com/vector/voxceleb/sv0_ecapa_tdnn_voxceleb12_ckpt_0_1_1.tar.gz',
         'md5':
-        '85ff08ce0ef406b8c6d7b5ffc5b2b48f',
+        'a1c0dba7d4de997187786ff517d5b4ec',
         'cfg_path':
-        'conf/model.yaml',
+        'conf/model.yaml',  # the yaml config path
         'ckpt_path':
-        'model/model',
+        'model/model',  # the format is ${dir}/{model_name}, 
+        # so the first 'model' is dir, the second 'model' is the name
+        # this means we have a model stored as model/model.pdparams
     },
 }
 
@@ -66,12 +68,13 @@ class VectorExecutor(BaseExecutor):
 
         self.parser = argparse.ArgumentParser(
             prog="paddlespeech.vector", add_help=True)
+
         self.parser.add_argument(
             "--model",
             type=str,
             default="ecapatdnn_voxceleb12",
             choices=["ecapatdnn_voxceleb12"],
-            help="Choose model type of asr task.")
+            help="Choose model type of vector task.")
         self.parser.add_argument(
             "--task",
             type=str,
@@ -79,7 +82,7 @@ class VectorExecutor(BaseExecutor):
             choices=["spk"],
             help="task type in vector domain")
         self.parser.add_argument(
-            "--input", type=str, default=None, help="Audio file to recognize.")
+            "--input", type=str, default=None, help="Audio file to extract embedding.")
         self.parser.add_argument(
             "--sample_rate",
             type=int,
@@ -173,22 +176,55 @@ class VectorExecutor(BaseExecutor):
                  sample_rate: int=16000,
                  config: os.PathLike=None,
                  ckpt_path: os.PathLike=None,
-                 force_yes: bool=False,
                  device=paddle.get_device()):
+        """Extract the audio embedding
+
+        Args:
+            audio_file (os.PathLike): audio path, 
+                                      whose format must be wav and sample rate must be matched the model
+            model (str, optional): mode type, which is been loaded from the pretrained model list. 
+                                   Defaults to 'ecapatdnn-voxceleb12'.
+            sample_rate (int, optional): model sample rate. Defaults to 16000.
+            config (os.PathLike, optional): yaml config. Defaults to None.
+            ckpt_path (os.PathLike, optional): pretrained model path. Defaults to None.
+            device (optional): paddle running host device. Defaults to paddle.get_device().
+
+        Returns:
+            dict: return the audio embedding and the embedding shape
+        """
+        # stage 0: check the audio format
         audio_file = os.path.abspath(audio_file)
         if not self._check(audio_file, sample_rate):
             sys.exit(-1)
 
+        # stage 1: set the paddle runtime host device
         logger.info(f"device type: {device}")
         paddle.device.set_device(device)
+
+        # stage 2: read the specific pretrained model
         self._init_from_path(model, sample_rate, config, ckpt_path)
+
+        # stage 3: preprocess the audio and get the audio feat
         self.preprocess(model, audio_file)
+
+        # stage 4: infer the model and get the audio embedding
         self.infer(model)
+
+        # stage 5: process the result and set them to output dict
         res = self.postprocess()
 
         return res
 
     def _get_pretrained_path(self, tag: str) -> os.PathLike:
+        """get the neural network path from the pretrained model list
+           we stored all the pretained mode in the variable `pretrained_models`
+
+        Args:
+            tag (str): model tag in the pretrained model list
+
+        Returns:
+            os.PathLike: the downloaded pretrained model path in the disk
+        """
         support_models = list(pretrained_models.keys())
         assert tag in pretrained_models, \
             'The model "{}" you want to use has not been supported,'\
@@ -210,15 +246,33 @@ class VectorExecutor(BaseExecutor):
                         sample_rate: int=16000,
                         cfg_path: Optional[os.PathLike]=None,
                         ckpt_path: Optional[os.PathLike]=None):
+        """Init the neural network from the model path
+
+        Args:
+            model_type (str, optional): model tag in the pretrained model list. 
+                                        Defaults to 'ecapatdnn_voxceleb12'.
+            sample_rate (int, optional): model sample rate. 
+                                         Defaults to 16000.
+            cfg_path (Optional[os.PathLike], optional): yaml config file path. 
+                                                        Defaults to None.
+            ckpt_path (Optional[os.PathLike], optional): the pretrained model path, which is stored in the disk. 
+                                                         Defaults to None.
+        """
+        # stage 0: avoid to init the mode again
         if hasattr(self, "model"):
             logger.info("Model has been initialized")
             return
 
         # stage 1: get the model and config path
+        #          if we want init the network from the model stored in the disk,
+        #          we must pass the config path and the ckpt model path
         if cfg_path is None or ckpt_path is None:
+            # get the mode from pretrained list
             sample_rate_str = "16k" if sample_rate == 16000 else "8k"
             tag = model_type + "-" + sample_rate_str
             logger.info(f"load the pretrained model: {tag}")
+            # get the model from the pretrained list
+            # we download the pretrained model and store it in the res_path
             res_path = self._get_pretrained_path(tag)
             self.res_path = res_path
 
@@ -227,6 +281,7 @@ class VectorExecutor(BaseExecutor):
             self.ckpt_path = os.path.join(
                 res_path, pretrained_models[tag]['ckpt_path'] + '.pdparams')
         else:
+            # get the model from disk
             self.cfg_path = os.path.abspath(cfg_path)
             self.ckpt_path = os.path.abspath(ckpt_path + ".pdparams")
             self.res_path = os.path.dirname(
@@ -241,7 +296,6 @@ class VectorExecutor(BaseExecutor):
         self.config.merge_from_file(self.cfg_path)
 
         # stage 3: get the model name to instance the model network with dynamic_import
-        # Noet: we use the '-' to get the model name instead of '_'
         logger.info("start to dynamic import the model class")
         model_name = model_type[:model_type.rindex('_')]
         logger.info(f"model name {model_name}")
@@ -262,31 +316,55 @@ class VectorExecutor(BaseExecutor):
 
     @paddle.no_grad()
     def infer(self, model_type: str):
+        """Infer the model to get the embedding
 
+        Args:
+            model_type (str): speaker verification model type
+        """
+        # stage 0: get the feat and length from _inputs
         feats = self._inputs["feats"]
         lengths = self._inputs["lengths"]
         logger.info("start to do backbone network model forward")
         logger.info(
             f"feats shape:{feats.shape}, lengths shape: {lengths.shape}")
+
+        # stage 1: get the audio embedding
         # embedding from (1, emb_size, 1) -> (emb_size)
         embedding = self.model.backbone(feats, lengths).squeeze().numpy()
         logger.info(f"embedding size: {embedding.shape}")
 
+        # stage 2: put the embedding and dim info to _outputs property
+        #          the embedding type is numpy.array
         self._outputs["embedding"] = embedding
 
     def postprocess(self) -> Union[str, os.PathLike]:
-        return self._outputs["embedding"]
+        """Return the audio embedding info
+
+        Returns:
+            Union[str, os.PathLike]: audio embedding info
+        """
+        embedding = self._outputs["embedding"]
+        dim = embedding.shape[0]
+        return {"dim": dim, "embedding": embedding}
 
     def preprocess(self, model_type: str, input_file: Union[str, os.PathLike]):
+        """Extract the audio feat
+
+        Args:
+            model_type (str): speaker verification model type
+            input_file (Union[str, os.PathLike]): audio file path
+        """
         audio_file = input_file
         if isinstance(audio_file, (str, os.PathLike)):
             logger.info(f"Preprocess audio file: {audio_file}")
 
-        # stage 1: load the audio
+        # stage 1: load the audio sample points
+        #    Note: this process must match the training process
         waveform, sr = load_audio(audio_file)
         logger.info(f"load the audio sample points, shape is: {waveform.shape}")
 
         # stage 2: get the audio feat
+        # Note: Now we only support fbank feature
         try:
             feat = melspectrogram(
                 x=waveform,
@@ -302,8 +380,13 @@ class VectorExecutor(BaseExecutor):
         feat = paddle.to_tensor(feat).unsqueeze(0)
         # in inference period, the lengths is all one without padding
         lengths = paddle.ones([1])
+
+        # stage 3: we do feature normalize,
+        #          Now we assume that the feat must do normalize
         feat = feature_normalize(feat, mean_norm=True, std_norm=False)
 
+        # stage 4: store the feat and length in the _inputs,
+        #          which will be used in other function
         logger.info(f"feats shape: {feat.shape}")
         self._inputs["feats"] = feat
         self._inputs["lengths"] = lengths
@@ -311,6 +394,15 @@ class VectorExecutor(BaseExecutor):
         logger.info("audio extract the feat success")
 
     def _check(self, audio_file: str, sample_rate: int):
+        """Check if the model sample match the audio sample rate 
+
+        Args:
+            audio_file (str): audio file path, which will be extracted the embedding
+            sample_rate (int): the desired model sample rate 
+
+        Returns:
+            bool: return if the audio sample rate matches the model sample rate
+        """
         self.sample_rate = sample_rate
         if self.sample_rate != 16000 and self.sample_rate != 8000:
             logger.error(

paddlespeech/server/README.md

@@ -10,7 +10,7 @@
  paddlespeech_server help
  ```
  ### Start the server
- First set the service-related configuration parameters, similar to `./conf/application.yaml`,
+ First set the service-related configuration parameters, similar to `./conf/application.yaml`. Set `engine_list`, which represents the speech tasks included in the service to be started
  Then start the service:
  ```bash
  paddlespeech_server start --config_file ./conf/application.yaml
@@ -23,7 +23,7 @@
  ```
  ### Access speech recognition services 
  ```
- paddlespeech_client asr --server_ip 127.0.0.1 --port 8090 --input ./tests/16_audio.wav
+ paddlespeech_client asr --server_ip 127.0.0.1 --port 8090 --input input_16k.wav
  ```
  
  ### Access text to speech services
@@ -31,3 +31,7 @@
  paddlespeech_client tts --server_ip 127.0.0.1 --port 8090 --input "你好，欢迎使用百度飞桨深度学习框架！" --output output.wav
  ```
  
+ ### Access audio classification services
+ ```bash
+ paddlespeech_client cls --server_ip 127.0.0.1 --port 8090 --input input.wav
+ ```

paddlespeech/server/README_cn.md

@@ -10,7 +10,7 @@
  paddlespeech_server help
  ```
  ### 启动服务
- 首先设置服务相关配置文件，类似于 `./conf/application.yaml`，同时设置服务配置中的语音任务模型相关配置，类似于 `./conf/tts/tts.yaml`。
+ 首先设置服务相关配置文件，类似于 `./conf/application.yaml`，设置 `engine_list`，该值表示即将启动的服务中包含的语音任务。
  然后启动服务：
  ```bash
  paddlespeech_server start --config_file ./conf/application.yaml
@@ -30,3 +30,8 @@
  ```bash
  paddlespeech_client tts --server_ip 127.0.0.1 --port 8090 --input "你好，欢迎使用百度飞桨深度学习框架！" --output output.wav
  ```
+
+ ### 访问音频分类服务
+ ```bash
+ paddlespeech_client cls --server_ip 127.0.0.1 --port 8090 --input input.wav
+ ```

paddlespeech/vector/cluster/__init__.py

+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.

paddlespeech/vector/io/__init__.py

+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.

paddlespeech/vector/modules/__init__.py

+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.

paddlespeech/vector/training/__init__.py

+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.

paddlespeech/vector/utils/__init__.py

+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.