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DeepSpeech
提交 0550d092 编写于 作者: H Hui Zhang
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Merge branch 'audio' into io

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浏览文件 @ 0550d092
......@@ -39,6 +39,9 @@ tools/env.sh
tools/openfst-1.8.1/
tools/libsndfile/
tools/python-soundfile/
tools/onnx
tools/onnxruntime
tools/Paddle2ONNX
speechx/fc_patch/
......
.mergify.yml
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......@@ -52,7 +52,7 @@ pull_request_rules:
add: ["T2S"]
- name: "auto add label=Audio"
conditions:
- files~=^paddleaudio/
- files~=^paddlespeech/audio/
actions:
label:
add: ["Audio"]
......@@ -100,7 +100,7 @@ pull_request_rules:
add: ["README"]
- name: "auto add label=Documentation"
conditions:
- files~=^(docs/|CHANGELOG.md|paddleaudio/CHANGELOG.md)
- files~=^(docs/|CHANGELOG.md)
actions:
label:
add: ["Documentation"]
......
.pre-commit-config.yaml
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......@@ -51,12 +51,12 @@ repos:
language: system
files: \.(c|cc|cxx|cpp|cu|h|hpp|hxx|cuh|proto)$
exclude: (?=speechx/speechx/kaldi|speechx/patch|speechx/tools/fstbin|speechx/tools/lmbin).*(\.cpp|\.cc|\.h|\.py)$
- id: copyright_checker
name: copyright_checker
entry: python .pre-commit-hooks/copyright-check.hook
language: system
files: \.(c|cc|cxx|cpp|cu|h|hpp|hxx|proto|py)$
exclude: (?=third_party|pypinyin|speechx/speechx/kaldi|speechx/patch|speechx/tools/fstbin|speechx/tools/lmbin).*(\.cpp|\.cc|\.h|\.py)$
#- id: copyright_checker
# name: copyright_checker
# entry: python .pre-commit-hooks/copyright-check.hook
# language: system
# files: \.(c|cc|cxx|cpp|cu|h|hpp|hxx|proto|py)$
# exclude: (?=third_party|pypinyin|speechx/speechx/kaldi|speechx/patch|speechx/tools/fstbin|speechx/tools/lmbin).*(\.cpp|\.cc|\.h|\.py)$
- repo: https://github.com/asottile/reorder_python_imports
rev: v2.4.0
hooks:
......
.pre-commit-hooks/copyright-check.hook
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......@@ -19,7 +19,7 @@ import subprocess
import platform
COPYRIGHT = '''
Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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.
......
README.md
浏览文件 @ 0550d092
([简体中文](./README_cn.md)|English)
<p align="center">
<img src="./docs/images/PaddleSpeech_logo.png" />
</p>
<div align="center">
<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>
------------------------------------------------------------------------------------
<p align="center">
<a href="./LICENSE"><img src="https://img.shields.io/badge/license-Apache%202-red.svg"></a>
......@@ -28,7 +16,20 @@
<a href="=https://pypi.org/project/paddlespeech/"><img src="https://static.pepy.tech/badge/paddlespeech"></a>
<a href="https://huggingface.co/spaces"><img src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue"></a>
</p>
<div align="center">
<h4>
<a href="#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="#model-list"> Models List </a>
| <a href="https://aistudio.baidu.com/aistudio/education/group/info/25130"> AIStudio Courses </a>
| <a href="https://arxiv.org/abs/2205.12007"> Paper </a>
| <a href="https://gitee.com/paddlepaddle/PaddleSpeech"> Gitee </a>
</h4>
</div>
------------------------------------------------------------------------------------
**PaddleSpeech** is an open-source toolkit on [PaddlePaddle](https://github.com/PaddlePaddle/Paddle) platform for a variety of critical tasks in speech and audio, with the state-of-art and influential models.
......@@ -142,53 +143,35 @@ For more synthesized audios, please refer to [PaddleSpeech Text-to-Speech sample
</div>
### ⭐ Examples
- **[PaddleBoBo](https://github.com/JiehangXie/PaddleBoBo): Use PaddleSpeech TTS to generate virtual human voice.**
<div align="center"><a href="https://www.bilibili.com/video/BV1cL411V71o?share_source=copy_web"><img src="https://ai-studio-static-online.cdn.bcebos.com/06fd746ab32042f398fb6f33f873e6869e846fe63c214596ae37860fe8103720" / width="500px"></a></div>
- [PaddleSpeech Demo Video](https://paddlespeech.readthedocs.io/en/latest/demo_video.html)
- **[VTuberTalk](https://github.com/jerryuhoo/VTuberTalk): Use PaddleSpeech TTS and ASR to clone voice from videos.**
<div align="center">
<img src="https://raw.githubusercontent.com/jerryuhoo/VTuberTalk/main/gui/gui.png" width = "500px" />
</div>
### 🔥 Hot Activities
- 2021.12.21~12.24
4 Days Live Courses: Depth interpretation of PaddleSpeech!
**Courses videos and related materials: https://aistudio.baidu.com/aistudio/education/group/info/25130**
### Features
Via the easy-to-use, efficient, flexible and scalable implementation, our vision is to empower both industrial application and academic research, including training, inference & testing modules, and deployment process. To be more specific, this toolkit features at:
- 📦 **Ease of Use**: low barriers to install, and [CLI](#quick-start) is available to quick-start your journey.
- 📦 **Ease of Use**: low barriers to install, [CLI](#quick-start), [Server](#quick-start-server), and [Streaming Server](#quick-start-streaming-server) is available to quick-start your journey.
- 🏆 **Align to the State-of-the-Art**: we provide high-speed and ultra-lightweight models, and also cutting-edge technology.
- 🏆 **Streaming ASR and TTS System**: we provide production ready streaming asr and streaming tts system.
- 💯 **Rule-based Chinese frontend**: our frontend contains Text Normalization and Grapheme-to-Phoneme (G2P, including Polyphone and Tone Sandhi). Moreover, we use self-defined linguistic rules to adapt Chinese context.
- **Varieties of Functions that Vitalize both Industrial and Academia**:
- 🛎️ *Implementation of critical audio tasks*: this toolkit contains audio functions like Audio Classification, Speech Translation, Automatic Speech Recognition, Text-to-Speech Synthesis, etc.
- 📦 **Varieties of Functions that Vitalize both Industrial and Academia**:
- 🛎️ *Implementation of critical audio tasks*: this toolkit contains audio functions like Automatic Speech Recognition, Text-to-Speech Synthesis, Speaker Verfication, KeyWord Spotting, Audio Classification, and Speech Translation, etc.
- 🔬 *Integration of mainstream models and datasets*: the toolkit implements modules that participate in the whole pipeline of the speech tasks, and uses mainstream datasets like LibriSpeech, LJSpeech, AIShell, CSMSC, etc. See also [model list](#model-list) for more details.
- 🧩 *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
- 👑 2022.05.13: Release [PP-ASR](./docs/source/asr/PPASR.md)、[PP-TTS](./docs/source/tts/PPTTS.md)、[PP-VPR](docs/source/vpr/PPVPR.md)
- 👏🏻 2022.05.06: `Streaming ASR` with `Punctuation Restoration` and `Token Timestamp`.
- 👏🏻 2022.05.06: `Server` is available for `Speaker Verification`, and `Punctuation Restoration`.
- 👏🏻 2022.04.28: `Streaming Server` is available for `Automatic Speech Recognition` and `Text-to-Speech`.
- 👏🏻 2022.03.28: `Server` is available for `Audio Classification`, `Automatic Speech Recognition` and `Text-to-Speech`.
- 👏🏻 2022.03.28: `CLI` is available for `Speaker Verification`.
- 🤗 2021.12.14: [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: `CLI` is available for `Audio Classification`, `Automatic Speech Recognition`, `Speech Translation (English to Chinese)` and `Text-to-Speech`.
<!---
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 Verification.
- 🤗 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.
### Community
- Scan the QR code below with your Wechat (reply【语音】after your friend's application is approved), you can access to official technical exchange group. Look forward to your participation.
- Scan the QR code below with your Wechat, you can access to official technical exchange group and get the bonus ( more than 20GB learning materials, such as papers, codes and videos ) and the live link of the lessons. Look forward to your participation.
<div align="center">
<img src="https://raw.githubusercontent.com/yt605155624/lanceTest/main/images/wechat_4.jpg" width = "300" />
<img src="https://user-images.githubusercontent.com/23690325/169763015-cbd8e28d-602c-4723-810d-dbc6da49441e.jpg" width = "200" />
</div>
## Installation
......@@ -196,6 +179,7 @@ Via the easy-to-use, efficient, flexible and scalable implementation, our vision
We strongly recommend our users to install PaddleSpeech in **Linux** with *python>=3.7*.
Up to now, **Linux** supports CLI for the all our tasks, **Mac OSX** and **Windows** only supports PaddleSpeech CLI for Audio Classification, Speech-to-Text and Text-to-Speech. To install `PaddleSpeech`, please see [installation](./docs/source/install.md).
<a name="quickstart"></a>
## Quick Start
......@@ -257,16 +241,19 @@ If you want to try more functions like training and tuning, please have a look a
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
```
......@@ -280,6 +267,37 @@ 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)
<a name="quickstartstreamingserver"></a>
## Quick Start Streaming Server
Developers can have a try of [streaming asr](./demos/streaming_asr_server/README.md) and [streaming tts](./demos/streaming_tts_server/README.md) server.
**Start Streaming Speech Recognition Server**
```
paddlespeech_server start --config_file ./demos/streaming_asr_server/conf/application.yaml
```
**Access Streaming Speech Recognition Services**
```
paddlespeech_client asr_online --server_ip 127.0.0.1 --port 8090 --input input_16k.wav
```
**Start Streaming Text to Speech Server**
```
paddlespeech_server start --config_file ./demos/streaming_tts_server/conf/tts_online_application.yaml
```
**Access Streaming Text to Speech Services**
```
paddlespeech_client tts_online --server_ip 127.0.0.1 --port 8092 --protocol http --input "您好，欢迎使用百度飞桨语音合成服务。" --output output.wav
```
For more information please see: [streaming asr](./demos/streaming_asr_server/README.md) and [streaming tts](./demos/streaming_tts_server/README.md)
<a name="ModelList"></a>
## Model List
......@@ -296,7 +314,7 @@ PaddleSpeech supports a series of most popular models. They are summarized in [r
<th>Speech-to-Text Module Type</th>
<th>Dataset</th>
<th>Model Type</th>
<th>Link</th>
<th>Example</th>
</tr>
</thead>
<tbody>
......@@ -371,7 +389,7 @@ PaddleSpeech supports a series of most popular models. They are summarized in [r
<th> Text-to-Speech Module Type </th>
<th> Model Type </th>
<th> Dataset </th>
<th> Link </th>
<th> Example </th>
</tr>
</thead>
<tbody>
......@@ -489,7 +507,7 @@ PaddleSpeech supports a series of most popular models. They are summarized in [r
<th> Task </th>
<th> Dataset </th>
<th> Model Type </th>
<th> Link </th>
<th> Example </th>
</tr>
</thead>
<tbody>
......@@ -514,7 +532,7 @@ PaddleSpeech supports a series of most popular models. They are summarized in [r
<th> Task </th>
<th> Dataset </th>
<th> Model Type </th>
<th> Link </th>
<th> Example </th>
</tr>
</thead>
<tbody>
......@@ -539,7 +557,7 @@ PaddleSpeech supports a series of most popular models. They are summarized in [r
<th> Task </th>
<th> Dataset </th>
<th> Model Type </th>
<th> Link </th>
<th> Example </th>
</tr>
</thead>
<tbody>
......@@ -589,6 +607,21 @@ Normally, [Speech SoTA](https://paperswithcode.com/area/speech), [Audio SoTA](ht
The Text-to-Speech module is originally called [Parakeet](https://github.com/PaddlePaddle/Parakeet), and now merged with this repository. If you are interested in academic research about this task, please see [TTS research overview](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/docs/source/tts#overview). Also, [this document](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/docs/source/tts/models_introduction.md) is a good guideline for the pipeline components.
## ⭐ Examples
- **[PaddleBoBo](https://github.com/JiehangXie/PaddleBoBo): Use PaddleSpeech TTS to generate virtual human voice.**
<div align="center"><a href="https://www.bilibili.com/video/BV1cL411V71o?share_source=copy_web"><img src="https://ai-studio-static-online.cdn.bcebos.com/06fd746ab32042f398fb6f33f873e6869e846fe63c214596ae37860fe8103720" / width="500px"></a></div>
- [PaddleSpeech Demo Video](https://paddlespeech.readthedocs.io/en/latest/demo_video.html)
- **[VTuberTalk](https://github.com/jerryuhoo/VTuberTalk): Use PaddleSpeech TTS and ASR to clone voice from videos.**
<div align="center">
<img src="https://raw.githubusercontent.com/jerryuhoo/VTuberTalk/main/gui/gui.png" width = "500px" />
</div>
## Citation
To cite PaddleSpeech for research, please use the following format.
......@@ -655,7 +688,6 @@ You are warmly welcome to submit questions in [discussions](https://github.com/P
## Acknowledgement
- Many thanks to [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) for years of attention, constructive advice and great help.
- Many thanks to [mymagicpower](https://github.com/mymagicpower) for the Java implementation of ASR upon [short](https://github.com/mymagicpower/AIAS/tree/main/3_audio_sdks/asr_sdk) and [long](https://github.com/mymagicpower/AIAS/tree/main/3_audio_sdks/asr_long_audio_sdk) audio files.
- Many thanks to [JiehangXie](https://github.com/JiehangXie)/[PaddleBoBo](https://github.com/JiehangXie/PaddleBoBo) for developing Virtual Uploader(VUP)/Virtual YouTuber(VTuber) with PaddleSpeech TTS function.
......
README_cn.md
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......@@ -2,34 +2,36 @@
<p align="center">
<img src="./docs/images/PaddleSpeech_logo.png" />
</p>
<div align="center">
<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>
------------------------------------------------------------------------------------
<p align="center">
<a href="./LICENSE"><img src="https://img.shields.io/badge/license-Apache%202-red.svg"></a>
<a href="support os"><img src="https://img.shields.io/badge/os-linux-yellow.svg"></a>
<a href="https://github.com/PaddlePaddle/PaddleSpeech/releases"><img src="https://img.shields.io/github/v/release/PaddlePaddle/PaddleSpeech?color=ffa"></a>
<a href="support os"><img src="https://img.shields.io/badge/os-linux%2C%20win%2C%20mac-pink.svg"></a>
<a href=""><img src="https://img.shields.io/badge/python-3.7+-aff.svg"></a>
<a href="https://github.com/PaddlePaddle/PaddleSpeech/graphs/contributors"><img src="https://img.shields.io/github/contributors/PaddlePaddle/PaddleSpeech?color=9ea"></a>
<a href="https://github.com/PaddlePaddle/PaddleSpeech/commits"><img src="https://img.shields.io/github/commit-activity/m/PaddlePaddle/PaddleSpeech?color=3af"></a>
<a href="https://github.com/PaddlePaddle/PaddleSpeech/issues"><img src="https://img.shields.io/github/issues/PaddlePaddle/PaddleSpeech?color=9cc"></a>
<a href="https://github.com/PaddlePaddle/PaddleSpeech/stargazers"><img src="https://img.shields.io/github/stars/PaddlePaddle/PaddleSpeech?color=ccf"></a>
<a href="=https://pypi.org/project/paddlespeech/"><img src="https://img.shields.io/pypi/dm/PaddleSpeech"></a>
<a href="=https://pypi.org/project/paddlespeech/"><img src="https://static.pepy.tech/badge/paddlespeech"></a>
<a href="https://huggingface.co/spaces"><img src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue"></a>
</p>
<div align="center">
<h4>
<a href="#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="#模型列表"> 模型列表 </a>
| <a href="https://aistudio.baidu.com/aistudio/education/group/info/25130"> AIStudio 课程 </a>
| <a href="https://arxiv.org/abs/2205.12007"> 论文 </a>
| <a href="https://gitee.com/paddlepaddle/PaddleSpeech"> Gitee
</h4>
</div>
<!---
from https://github.com/18F/open-source-guide/blob/18f-pages/pages/making-readmes-readable.md
1.What is this repo or project? (You can reuse the repo description you used earlier because this section doesn’t have to be long.)
2.How does it work?
3.Who will use this repo or project?
4.What is the goal of this project?
-->
------------------------------------------------------------------------------------
**PaddleSpeech** 是基于飞桨 [PaddlePaddle](https://github.com/PaddlePaddle/Paddle) 的语音方向的开源模型库，用于语音和音频中的各种关键任务的开发，包含大量基于深度学习前沿和有影响力的模型，一些典型的应用示例如下：
##### 语音识别
......@@ -57,7 +59,6 @@ from https://github.com/18F/open-source-guide/blob/18f-pages/pages/making-readme
</td>
<td>我认为跑步最重要的就是给我带来了身体健康。</td>
</tr>
</tbody>
</table>
......@@ -143,53 +144,37 @@ from https://github.com/18F/open-source-guide/blob/18f-pages/pages/making-readme
</div>
### ⭐ 应用案例
- **[PaddleBoBo](https://github.com/JiehangXie/PaddleBoBo): 使用 PaddleSpeech 的语音合成模块生成虚拟人的声音。**
<div align="center"><a href="https://www.bilibili.com/video/BV1cL411V71o?share_source=copy_web"><img src="https://ai-studio-static-online.cdn.bcebos.com/06fd746ab32042f398fb6f33f873e6869e846fe63c214596ae37860fe8103720" / width="500px"></a></div>
- [PaddleSpeech 示例视频](https://paddlespeech.readthedocs.io/en/latest/demo_video.html)
- **[VTuberTalk](https://github.com/jerryuhoo/VTuberTalk): 使用 PaddleSpeech 的语音合成和语音识别从视频中克隆人声。**
<div align="center">
<img src="https://raw.githubusercontent.com/jerryuhoo/VTuberTalk/main/gui/gui.png" width = "500px" />
</div>
### 🔥 热门活动
- 2021.12.21~12.24
4 日直播课: 深度解读 PaddleSpeech 语音技术!
**直播回放与课件资料: https://aistudio.baidu.com/aistudio/education/group/info/25130**
### 特性
本项目采用了易用、高效、灵活以及可扩展的实现，旨在为工业应用、学术研究提供更好的支持，实现的功能包含训练、推断以及测试模块，以及部署过程，主要包括
- 📦 **易用性**: 安装门槛低，可使用 [CLI](#quick-start) 快速开始。
- 🏆 **对标 SoTA**: 提供了高速、轻量级模型，且借鉴了最前沿的技术。
- 🏆 **流式ASR和TTS系统**：工业级的端到端流式识别、流式合成系统。
- 💯 **基于规则的中文前端**: 我们的前端包含文本正则化和字音转换（G2P）。此外，我们使用自定义语言规则来适应中文语境。
- **多种工业界以及学术界主流功能支持**:
- 🛎️ 典型音频任务: 本工具包提供了音频任务如音频分类、语音翻译、自动语音识别、文本转语音、语音合成等任务的实现。
- 🛎️ 典型音频任务: 本工具包提供了音频任务如音频分类、语音翻译、自动语音识别、文本转语音、语音合成、声纹识别、KWS等任务的实现。
- 🔬 主流模型及数据集: 本工具包实现了参与整条语音任务流水线的各个模块，并且采用了主流数据集如 LibriSpeech、LJSpeech、AIShell、CSMSC，详情请见 [模型列表](#model-list)。
- 🧩 级联模型应用: 作为传统语音任务的扩展，我们结合了自然语言处理、计算机视觉等任务，实现更接近实际需求的产业级应用。
### 近期更新
- 👑 2022.05.13: PaddleSpeech 发布 [PP-ASR](./docs/source/asr/PPASR_cn.md) 流式语音识别系统、[PP-TTS](./docs/source/tts/PPTTS_cn.md) 流式语音合成系统、[PP-VPR](docs/source/vpr/PPVPR_cn.md) 全链路声纹识别系统
- 👏🏻 2022.05.06: PaddleSpeech Streaming Server 上线! 覆盖了语音识别（标点恢复、时间戳），和语音合成。
- 👏🏻 2022.05.06: PaddleSpeech Server 上线! 覆盖了声音分类、语音识别、语音合成、声纹识别，标点恢复。
- 👏🏻 2022.03.28: PaddleSpeech CLI 覆盖声音分类、语音识别、语音翻译（英译中）、语音合成，声纹验证。
- 🤗 2021.12.14: PaddleSpeech [ASR](https://huggingface.co/spaces/KPatrick/PaddleSpeechASR) and [TTS](https://huggingface.co/spaces/KPatrick/PaddleSpeechTTS) Demos on Hugging Face Spaces are available!
<!---
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 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
微信扫描二维码（好友申请通过后回复【语音】）加入官方交流群，获得更高效的问题答疑，与各行各业开发者充分交流，期待您的加入。
### 🔥 加入技术交流群获取入群福利
- 3 日直播课链接: 深度解读 PP-TTS、PP-ASR、PP-VPR 三项核心语音系统关键技术
- 20G 学习大礼包：视频课程、前沿论文与学习资料
微信扫描二维码关注公众号，点击“马上报名”填写问卷加入官方交流群，获得更高效的问题答疑，与各行各业开发者充分交流，期待您的加入。
<div align="center">
<img src="https://raw.githubusercontent.com/yt605155624/lanceTest/main/images/wechat_4.jpg" width = "300" />
<img src="https://user-images.githubusercontent.com/23690325/169763015-cbd8e28d-602c-4723-810d-dbc6da49441e.jpg" width = "200" />
</div>
## 安装
......@@ -197,6 +182,7 @@ from https://github.com/18F/open-source-guide/blob/18f-pages/pages/making-readme
我们强烈建议用户在 **Linux** 环境下，*3.7* 以上版本的 *python* 上安装 PaddleSpeech。
目前为止，**Linux** 支持声音分类、语音识别、语音合成和语音翻译四种功能，**Mac OSX、 Windows** 下暂不支持语音翻译功能。 想了解具体安装细节，可以参考[安装文档](./docs/source/install_cn.md)。
<a name="快速开始"></a>
## 快速开始
安装完成后，开发者可以通过命令行快速开始，改变 `--input` 可以尝试用自己的音频或文本测试。
......@@ -243,7 +229,7 @@ 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)。
<a name="快速使用服务"></a>
## 快速使用服务
安装完成后，开发者可以通过命令行快速使用服务。
......@@ -269,7 +255,38 @@ paddlespeech_client cls --server_ip 127.0.0.1 --port 8090 --input input.wav
更多服务相关的命令行使用信息，请参考 [demos](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/demos/speech_server)
<a name="快速使用流式服务"></a>
## 快速使用流式服务
开发者可以尝试 [流式 ASR](./demos/streaming_asr_server/README.md) 和 [流式 TTS](./demos/streaming_tts_server/README.md) 服务.
**启动流式 ASR 服务**
```
paddlespeech_server start --config_file ./demos/streaming_asr_server/conf/application.yaml
```
**访问流式 ASR 服务**
```
paddlespeech_client asr_online --server_ip 127.0.0.1 --port 8090 --input input_16k.wav
```
**启动流式 TTS 服务**
```
paddlespeech_server start --config_file ./demos/streaming_tts_server/conf/tts_online_application.yaml
```
**访问流式 TTS 服务**
```
paddlespeech_client tts_online --server_ip 127.0.0.1 --port 8092 --protocol http --input "您好，欢迎使用百度飞桨语音合成服务。" --output output.wav
```
更多信息参看： [流式 ASR](./demos/streaming_asr_server/README.md) 和 [流式 TTS](./demos/streaming_tts_server/README.md)
<a name="模型列表"></a>
## 模型列表
PaddleSpeech 支持很多主流的模型，并提供了预训练模型，详情请见[模型列表](./docs/source/released_model.md)。
......@@ -282,8 +299,8 @@ PaddleSpeech 的 **语音转文本** 包含语音识别声学模型、语音识
<tr>
<th>语音转文本模块类型</th>
<th>数据集</th>
<th>模型种类</th>
<th>链接</th>
<th>模型类型</th>
<th>脚本</th>
</tr>
</thead>
<tbody>
......@@ -356,9 +373,9 @@ PaddleSpeech 的 **语音合成** 主要包含三个模块：文本前端、声
<thead>
<tr>
<th> 语音合成模块类型 </th>
<th> 模型种类 </th>
<th> 模型类型 </th>
<th> 数据集 </th>
<th> 链接 </th>
<th> 脚本 </th>
</tr>
</thead>
<tbody>
......@@ -474,8 +491,8 @@ PaddleSpeech 的 **语音合成** 主要包含三个模块：文本前端、声
<tr>
<th> 任务 </th>
<th> 数据集 </th>
<th> 模型种类 </th>
<th> 链接</th>
<th> 模型类型 </th>
<th> 脚本</th>
</tr>
</thead>
<tbody>
......@@ -498,10 +515,10 @@ PaddleSpeech 的 **语音合成** 主要包含三个模块：文本前端、声
<table style="width:100%">
<thead>
<tr>
<th> Task </th>
<th> Dataset </th>
<th> Model Type </th>
<th> Link </th>
<th> 任务 </th>
<th> 数据集 </th>
<th> 模型类型 </th>
<th> 脚本 </th>
</tr>
</thead>
<tbody>
......@@ -525,8 +542,8 @@ PaddleSpeech 的 **语音合成** 主要包含三个模块：文本前端、声
<tr>
<th> 任务 </th>
<th> 数据集 </th>
<th> 模型种类 </th>
<th> 链接 </th>
<th> 模型类型 </th>
<th> 脚本 </th>
</tr>
</thead>
<tbody>
......@@ -541,6 +558,7 @@ PaddleSpeech 的 **语音合成** 主要包含三个模块：文本前端、声
</tbody>
</table>
<a name="教程文档"></a>
## 教程文档
对于 PaddleSpeech 的所关注的任务，以下指南有助于帮助开发者快速入门，了解语音相关核心思想。
......@@ -582,6 +600,21 @@ PaddleSpeech 的 **语音合成** 主要包含三个模块：文本前端、声
语音合成模块最初被称为 [Parakeet](https://github.com/PaddlePaddle/Parakeet)，现在与此仓库合并。如果您对该任务的学术研究感兴趣，请参阅 [TTS 研究概述](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/docs/source/tts#overview)。此外，[模型介绍](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/docs/source/tts/models_introduction.md) 是了解语音合成流程的一个很好的指南。
## ⭐ 应用案例
- **[PaddleBoBo](https://github.com/JiehangXie/PaddleBoBo): 使用 PaddleSpeech 的语音合成模块生成虚拟人的声音。**
<div align="center"><a href="https://www.bilibili.com/video/BV1cL411V71o?share_source=copy_web"><img src="https://ai-studio-static-online.cdn.bcebos.com/06fd746ab32042f398fb6f33f873e6869e846fe63c214596ae37860fe8103720" / width="500px"></a></div>
- [PaddleSpeech 示例视频](https://paddlespeech.readthedocs.io/en/latest/demo_video.html)
- **[VTuberTalk](https://github.com/jerryuhoo/VTuberTalk): 使用 PaddleSpeech 的语音合成和语音识别从视频中克隆人声。**
<div align="center">
<img src="https://raw.githubusercontent.com/jerryuhoo/VTuberTalk/main/gui/gui.png" width = "500px" />
</div>
## 引用
要引用 PaddleSpeech 进行研究，请使用以下格式进行引用。
......@@ -607,7 +640,7 @@ PaddleSpeech 的 **语音合成** 主要包含三个模块：文本前端、声
<a name="欢迎贡献"></a>
## 参与 PaddleSpeech 的开发
热烈欢迎您在[Discussions](https://github.com/PaddlePaddle/PaddleSpeech/discussions) 中提交问题，并在[Issues](https://github.com/PaddlePaddle/PaddleSpeech/issues) 中指出发现的 bug。此外，我们非常希望您参与到 PaddleSpeech 的开发中！
热烈欢迎您在 [Discussions](https://github.com/PaddlePaddle/PaddleSpeech/discussions) 中提交问题，并在 [Issues](https://github.com/PaddlePaddle/PaddleSpeech/issues) 中指出发现的 bug。此外，我们非常希望您参与到 PaddleSpeech 的开发中！
### 贡献者
<p align="center">
......@@ -658,6 +691,7 @@ PaddleSpeech 的 **语音合成** 主要包含三个模块：文本前端、声
- 非常感谢 [jerryuhoo](https://github.com/jerryuhoo)/[VTuberTalk](https://github.com/jerryuhoo/VTuberTalk) 基于 PaddleSpeech 的 TTS GUI 界面和基于 ASR 制作数据集的相关代码。
此外，PaddleSpeech 依赖于许多开源存储库。有关更多信息，请参阅 [references](./docs/source/reference.md)。
## License
......
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# Changelog
Date: 2022-3-15, Author: Xiaojie Chen.
- kaldi and librosa mfcc, fbank, spectrogram.
- unit test and benchmark.
Date: 2022-2-25, Author: Hui Zhang.
- Refactor architecture.
- dtw distance and mcd style dtw.
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# PaddleAudio
PaddleAudio is an audio library for PaddlePaddle.
## Install
`pip install .`
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# Minimal makefile for Sphinx documentation
#
# You can set these variables from the command line.
SPHINXOPTS =
SPHINXBUILD = sphinx-build
SOURCEDIR = source
BUILDDIR = build
# Put it first so that "make" without argument is like "make help".
help:
@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
.PHONY: help Makefile
# Catch-all target: route all unknown targets to Sphinx using the new
# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS).
%: Makefile
@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
\ No newline at end of file
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# Build docs for PaddleAudio
Execute the following steps in **current directory**.
## 1. Install
`pip install Sphinx sphinx_rtd_theme`
## 2. Generate API docs
Generate API docs from doc string.
`sphinx-apidoc -fMeT -o source ../paddleaudio ../paddleaudio/utils --templatedir source/_templates`
## 3. Build
`sphinx-build source _html`
## 4. Preview
Open `_html/index.html` for page preview.
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@ECHO OFF
pushd %~dp0
REM Command file for Sphinx documentation
if "%SPHINXBUILD%" == "" (
set SPHINXBUILD=sphinx-build
)
set SOURCEDIR=source
set BUILDDIR=build
if "%1" == "" goto help
%SPHINXBUILD% >NUL 2>NUL
if errorlevel 9009 (
echo.
echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
echo.installed, then set the SPHINXBUILD environment variable to point
echo.to the full path of the 'sphinx-build' executable. Alternatively you
echo.may add the Sphinx directory to PATH.
echo.
echo.If you don't have Sphinx installed, grab it from
echo.http://sphinx-doc.org/
exit /b 1
)
%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS%
goto end
:help
%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS%
:end
popd
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# 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.
import numpy as np
from dtaidistance import dtw_ndim
__all__ = [
'dtw_distance',
]
def dtw_distance(xs: np.ndarray, ys: np.ndarray) -> float:
"""Dynamic Time Warping.
This function keeps a compact matrix, not the full warping paths matrix.
Uses dynamic programming to compute:
Examples:
.. code-block:: python
wps[i, j] = (s1[i]-s2[j])**2 + min(
wps[i-1, j ] + penalty, // vertical / insertion / expansion
wps[i , j-1] + penalty, // horizontal / deletion / compression
wps[i-1, j-1]) // diagonal / match
dtw = sqrt(wps[-1, -1])
Args:
xs (np.ndarray): ref sequence, [T,D]
ys (np.ndarray): hyp sequence, [T,D]
Returns:
float: dtw distance
"""
return dtw_ndim.distance(xs, ys)
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# Copyright (c) 2021 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.
'''
This module is used to store environmental variables in PaddleAudio.
PPAUDIO_HOME --> the root directory for storing PaddleAudio related data. Default to ~/.paddleaudio. Users can change the
├ default value through the PPAUDIO_HOME environment variable.
├─ MODEL_HOME --> Store model files.
└─ DATA_HOME --> Store automatically downloaded datasets.
'''
import os
__all__ = [
'USER_HOME',
'PPAUDIO_HOME',
'MODEL_HOME',
'DATA_HOME',
]
def _get_user_home():
return os.path.expanduser('~')
def _get_ppaudio_home():
if 'PPAUDIO_HOME' in os.environ:
home_path = os.environ['PPAUDIO_HOME']
if os.path.exists(home_path):
if os.path.isdir(home_path):
return home_path
else:
raise RuntimeError(
'The environment variable PPAUDIO_HOME {} is not a directory.'.
format(home_path))
else:
return home_path
return os.path.join(_get_user_home(), '.paddleaudio')
def _get_sub_home(directory):
home = os.path.join(_get_ppaudio_home(), directory)
if not os.path.exists(home):
os.makedirs(home)
return home
USER_HOME = _get_user_home()
PPAUDIO_HOME = _get_ppaudio_home()
MODEL_HOME = _get_sub_home('models')
DATA_HOME = _get_sub_home('datasets')
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# Copyright (c) 2021 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.
import glob
import os
import subprocess
import pybind11
import setuptools
from setuptools import Extension
from setuptools.command.build_ext import build_ext
from setuptools.command.test import test
# set the version here
VERSION = '1.0.0a'
# Inspired by the example at https://pytest.org/latest/goodpractises.html
class TestCommand(test):
def finalize_options(self):
test.finalize_options(self)
self.test_args = []
self.test_suite = True
def run(self):
self.run_benchmark()
super(TestCommand, self).run()
def run_tests(self):
# Run nose ensuring that argv simulates running nosetests directly
import nose
nose.run_exit(argv=['nosetests', '-w', 'tests'])
def run_benchmark(self):
for benchmark_item in glob.glob('tests/benchmark/*py'):
os.system(f'pytest {benchmark_item}')
class ExtBuildCommand(build_ext):
def run(self):
try:
subprocess.check_output(["cmake", "--version"])
except OSError:
raise RuntimeError("CMake is not available.") from None
super().run()
def build_extension(self, ext):
extdir = os.path.abspath(
os.path.dirname(self.get_ext_fullpath(ext.name)))
cfg = "Debug" if self.debug else "Release"
cmake_args = [
f"-DCMAKE_BUILD_TYPE={cfg}",
f"-Dpybind11_DIR={pybind11.get_cmake_dir()}",
f"-DCMAKE_INSTALL_PREFIX={extdir}",
"-DCMAKE_VERBOSE_MAKEFILE=ON",
"-DBUILD_SOX:BOOL=ON",
]
build_args = ["--target", "install"]
# Set CMAKE_BUILD_PARALLEL_LEVEL to control the parallel build level
# across all generators.
if "CMAKE_BUILD_PARALLEL_LEVEL" not in os.environ:
if hasattr(self, "parallel") and self.parallel:
build_args += ["-j{}".format(self.parallel)]
if not os.path.exists(self.build_temp):
os.makedirs(self.build_temp)
subprocess.check_call(
["cmake", os.path.abspath(os.path.dirname(__file__))] + cmake_args,
cwd=self.build_temp)
subprocess.check_call(
["cmake", "--build", "."] + build_args, cwd=self.build_temp)
def get_ext_filename(self, fullname):
ext_filename = super().get_ext_filename(fullname)
ext_filename_parts = ext_filename.split(".")
without_abi = ext_filename_parts[:-2] + ext_filename_parts[-1:]
ext_filename = ".".join(without_abi)
return ext_filename
def write_version_py(filename='paddleaudio/__init__.py'):
with open(filename, "a") as f:
f.write(f"__version__ = '{VERSION}'")
def remove_version_py(filename='paddleaudio/__init__.py'):
with open(filename, "r") as f:
lines = f.readlines()
with open(filename, "w") as f:
for line in lines:
if "__version__" not in line:
f.write(line)
def get_ext_modules():
modules = [
Extension(name="paddleaudio._paddleaudio", sources=[]),
]
return modules
remove_version_py()
write_version_py()
setuptools.setup(
name="paddleaudio",
version=VERSION,
author="",
author_email="",
description="PaddleAudio, in development",
long_description="",
long_description_content_type="text/markdown",
url="",
packages=setuptools.find_packages(include=['paddleaudio*']),
classifiers=[
"Programming Language :: Python :: 3",
"License :: OSI Approved :: MIT License",
"Operating System :: OS Independent",
],
python_requires='>=3.6',
install_requires=[
'numpy >= 1.15.0', 'scipy >= 1.0.0', 'resampy >= 0.2.2',
'soundfile >= 0.9.0', 'colorlog', 'dtaidistance == 2.3.1', 'pathos'
],
extras_require={
'test': [
'nose', 'librosa==0.8.1', 'soundfile==0.10.3.post1',
'torchaudio==0.10.2', 'pytest-benchmark'
],
},
ext_modules=get_ext_modules(),
cmdclass={
"build_ext": ExtBuildCommand,
'test': TestCommand,
}, )
remove_version_py()
demos/README.md
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......@@ -2,14 +2,14 @@
([简体中文](./README_cn.md)|English)
The directory containes many speech applications in multi scenarios.
This directory contains many speech applications in multiple scenarios.
* audio searching - mass audio similarity retrieval
* audio tagging - multi-label tagging of an audio file
* automatic_video_subtitiles - generate subtitles from a video
* automatic_video_subtitles - generate subtitles from a video
* metaverse - 2D AR with TTS
* punctuation_restoration - restore punctuation from raw text
* speech recogintion - recognize text of an audio file
* speech recognition - recognize text of an audio file
* speech server - Server for Speech Task, e.g. ASR,TTS,CLS
* streaming asr server - receive audio stream from websocket, and recognize to transcript.
* speech translation - end to end speech translation
......
demos/audio_content_search/README.md 0 → 100644
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([简体中文](./README_cn.md)|English)
# ACS (Audio Content Search)
## Introduction
ACS, or Audio Content Search, refers to the problem of getting the key word time stamp from automatically transcribe spoken language (speech-to-text).
This demo is an implementation of obtaining the keyword timestamp in the text from a given audio file. It can be done by a single command or a few lines in python using `PaddleSpeech`.
Now, the search word in demo is:
```
我
康
```
## Usage
### 1. Installation
see [installation](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/docs/source/install.md).
You can choose one way from meduim and hard to install paddlespeech.
The dependency refers to the requirements.txt, and install the dependency as follows:
```
pip install -r requriement.txt
```
### 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/PaddleAudio/zh.wav
```
### 3. Usage
- Command Line(Recommended)
```bash
# Chinese
paddlespeech_client acs --server_ip 127.0.0.1 --port 8090 --input ./zh.wav
```
Usage:
```bash
paddlespeech asr --help
```
Arguments:
- `input`(required): Audio file to recognize.
- `server_ip`: the server ip.
- `port`: the server port.
- `lang`: the language type of the model. Default: `zh`.
- `sample_rate`: Sample rate of the model. Default: `16000`.
- `audio_format`: The audio format.
Output:
```bash
[2022-05-15 15:00:58,185] [ INFO] - acs http client start
[2022-05-15 15:00:58,185] [ INFO] - endpoint: http://127.0.0.1:8490/paddlespeech/asr/search
[2022-05-15 15:01:03,220] [ INFO] - acs http client finished
[2022-05-15 15:01:03,221] [ INFO] - ACS result: {'transcription': '我认为跑步最重要的就是给我带来了身体健康', 'acs': [{'w': '我', 'bg': 0, 'ed': 1.6800000000000002}, {'w': '我', 'bg': 2.1, 'ed': 4.28}, {'w': '康', 'bg': 3.2, 'ed': 4.92}]}
[2022-05-15 15:01:03,221] [ INFO] - Response time 5.036084 s.
```
- Python API
```python
from paddlespeech.server.bin.paddlespeech_client import ACSClientExecutor
acs_executor = ACSClientExecutor()
res = acs_executor(
input='./zh.wav',
server_ip="127.0.0.1",
port=8490,)
print(res)
```
Output:
```bash
[2022-05-15 15:08:13,955] [ INFO] - acs http client start
[2022-05-15 15:08:13,956] [ INFO] - endpoint: http://127.0.0.1:8490/paddlespeech/asr/search
[2022-05-15 15:08:19,026] [ INFO] - acs http client finished
{'transcription': '我认为跑步最重要的就是给我带来了身体健康', 'acs': [{'w': '我', 'bg': 0, 'ed': 1.6800000000000002}, {'w': '我', 'bg': 2.1, 'ed': 4.28}, {'w': '康', 'bg': 3.2, 'ed': 4.92}]}
```
demos/audio_content_search/README_cn.md 0 → 100644
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(简体中文|[English](./README.md))
# 语音内容搜索
## 介绍
语音内容搜索是一项用计算机程序获取转录语音内容关键词时间戳的技术。
这个 demo 是一个从给定音频文件获取其文本中关键词时间戳的实现，它可以通过使用 `PaddleSpeech` 的单个命令或 python 中的几行代码来实现。
当前示例中检索词是
```
我
康
```
## 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 medium，hard 三中方式中选择一种方式安装。
依赖参见 requirements.txt, 安装依赖
```
pip install -r requriement.txt
```
### 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
wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav
```
### 3. 使用方法
- 命令行 (推荐使用)
```bash
# 中文
paddlespeech_client acs --server_ip 127.0.0.1 --port 8090 --input ./zh.wav
```
使用方法：
```bash
paddlespeech acs --help
```
参数：
- `input`(必须输入)：用于识别的音频文件。
- `server_ip`: 服务的ip。
- `port`：服务的端口。
- `lang`：模型语言，默认值：`zh`。
- `sample_rate`：音频采样率，默认值：`16000`。
- `audio_format`: 音频的格式。
输出：
```bash
[2022-05-15 15:00:58,185] [ INFO] - acs http client start
[2022-05-15 15:00:58,185] [ INFO] - endpoint: http://127.0.0.1:8490/paddlespeech/asr/search
[2022-05-15 15:01:03,220] [ INFO] - acs http client finished
[2022-05-15 15:01:03,221] [ INFO] - ACS result: {'transcription': '我认为跑步最重要的就是给我带来了身体健康', 'acs': [{'w': '我', 'bg': 0, 'ed': 1.6800000000000002}, {'w': '我', 'bg': 2.1, 'ed': 4.28}, {'w': '康', 'bg': 3.2, 'ed': 4.92}]}
[2022-05-15 15:01:03,221] [ INFO] - Response time 5.036084 s.
```
- Python API
```python
from paddlespeech.server.bin.paddlespeech_client import ACSClientExecutor
acs_executor = ACSClientExecutor()
res = acs_executor(
input='./zh.wav',
server_ip="127.0.0.1",
port=8490,)
print(res)
```
输出：
```bash
[2022-05-15 15:08:13,955] [ INFO] - acs http client start
[2022-05-15 15:08:13,956] [ INFO] - endpoint: http://127.0.0.1:8490/paddlespeech/asr/search
[2022-05-15 15:08:19,026] [ INFO] - acs http client finished
{'transcription': '我认为跑步最重要的就是给我带来了身体健康', 'acs': [{'w': '我', 'bg': 0, 'ed': 1.6800000000000002}, {'w': '我', 'bg': 2.1, 'ed': 4.28}, {'w': '康', 'bg': 3.2, 'ed': 4.92}]}
```
examples/other/1xt2x/src_deepspeech2x/bin/test.py → demos/audio_content_search/acs_clinet.py
浏览文件 @ 0550d092
......@@ -11,49 +11,39 @@
# 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.
"""Evaluation for DeepSpeech2 model."""
from src_deepspeech2x.test_model import DeepSpeech2Tester as Tester
from yacs.config import CfgNode
import argparse
from paddlespeech.s2t.training.cli import default_argument_parser
from paddlespeech.s2t.utils.utility import print_arguments
from paddlespeech.cli.log import logger
from paddlespeech.server.utils.audio_handler import ASRHttpHandler
def main_sp(config, args):
exp = Tester(config, args)
exp.setup()
exp.run_test()
def main(config, args):
main_sp(config, args)
def main(args):
logger.info("asr http client start")
audio_format = "wav"
sample_rate = 16000
lang = "zh"
handler = ASRHttpHandler(
server_ip=args.server_ip, port=args.port, endpoint=args.endpoint)
res = handler.run(args.wavfile, audio_format, sample_rate, lang)
# res = res['result']
logger.info(f"the final result: {res}")
if __name__ == "__main__":
parser = default_argument_parser()
parser = argparse.ArgumentParser(description="audio content search client")
parser.add_argument(
"--model_type", type=str, default='offline', help='offline/online')
# save asr result to
'--server_ip', type=str, default='127.0.0.1', help='server ip')
parser.add_argument('--port', type=int, default=8090, help='server port')
parser.add_argument(
"--result_file", type=str, help="path of save the asr result")
"--wavfile",
action="store",
help="wav file path ",
default="./16_audio.wav")
parser.add_argument(
'--endpoint',
type=str,
default='/paddlespeech/asr/search',
help='server endpoint')
args = parser.parse_args()
print_arguments(args, globals())
print("model_type:{}".format(args.model_type))
# https://yaml.org/type/float.html
config = CfgNode(new_allowed=True)
if args.config:
config.merge_from_file(args.config)
if args.decode_cfg:
decode_confs = CfgNode(new_allowed=True)
decode_confs.merge_from_file(args.decode_cfg)
config.decode = decode_confs
if args.opts:
config.merge_from_list(args.opts)
config.freeze()
print(config)
if args.dump_config:
with open(args.dump_config, 'w') as f:
print(config, file=f)
main(config, args)
main(args)
demos/audio_content_search/conf/acs_application.yaml 0 → 100644
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#################################################################################
# SERVER SETTING #
#################################################################################
host: 0.0.0.0
port: 8490
# The task format in the engin_list is: <speech task>_<engine type>
# task choices = ['acs_python']
# protocol = ['http'] (only one can be selected).
# http only support offline engine type.
protocol: 'http'
engine_list: ['acs_python']
#################################################################################
# ENGINE CONFIG #
#################################################################################
################################### ACS #########################################
################### acs task: engine_type: python ###############################
acs_python:
task: acs
asr_protocol: 'websocket' # 'websocket'
offset: 1.0 # second
asr_server_ip: 127.0.0.1
asr_server_port: 8390
lang: 'zh'
word_list: "./conf/words.txt"
sample_rate: 16000
device: 'cpu' # set 'gpu:id' or 'cpu'
ping_timeout: 100 # seconds
demos/audio_content_search/conf/words.txt 0 → 100644
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我
康
\ No newline at end of file
demos/audio_content_search/conf/ws_conformer_application.yaml 0 → 100644
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#################################################################################
# SERVER SETTING #
#################################################################################
host: 0.0.0.0
port: 8390
# The task format in the engin_list is: <speech task>_<engine type>
# task choices = ['asr_online']
# protocol = ['websocket'] (only one can be selected).
# websocket only support online engine type.
protocol: 'websocket'
engine_list: ['asr_online']
#################################################################################
# ENGINE CONFIG #
#################################################################################
################################### ASR #########################################
################### speech task: asr; engine_type: online #######################
asr_online:
model_type: 'conformer_online_multicn'
am_model: # the pdmodel file of am static model [optional]
am_params: # the pdiparams file of am static model [optional]
lang: 'zh'
sample_rate: 16000
cfg_path:
decode_method: 'attention_rescoring'
force_yes: True
device: 'cpu' # cpu or gpu:id
am_predictor_conf:
device: # set 'gpu:id' or 'cpu'
switch_ir_optim: True
glog_info: False # True -> print glog
summary: True # False -> do not show predictor config
chunk_buffer_conf:
window_n: 7 # frame
shift_n: 4 # frame
window_ms: 25 # ms
shift_ms: 10 # ms
sample_rate: 16000
sample_width: 2
demos/streaming_asr_server/conf/ws_application.yaml → demos/audio_content_search/conf/ws_conformer_wenetspeech_application.yaml
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......@@ -4,11 +4,11 @@
# SERVER SETTING #
#################################################################################
host: 0.0.0.0
port: 8090
port: 8390
# The task format in the engin_list is: <speech task>_<engine type>
# task choices = ['asr_online', 'tts_online']
# protocol = ['websocket', 'http'] (only one can be selected).
# task choices = ['asr_online']
# protocol = ['websocket'] (only one can be selected).
# websocket only support online engine type.
protocol: 'websocket'
engine_list: ['asr_online']
......@@ -21,7 +21,7 @@ engine_list: ['asr_online']
################################### ASR #########################################
################### speech task: asr; engine_type: online #######################
asr_online:
model_type: 'deepspeech2online_aishell'
model_type: 'conformer_online_wenetspeech'
am_model: # the pdmodel file of am static model [optional]
am_params: # the pdiparams file of am static model [optional]
lang: 'zh'
......@@ -29,7 +29,8 @@ asr_online:
cfg_path:
decode_method:
force_yes: True
device: 'cpu' # cpu or gpu:id
decode_method: "attention_rescoring"
am_predictor_conf:
device: # set 'gpu:id' or 'cpu'
switch_ir_optim: True
......@@ -37,11 +38,9 @@ asr_online:
summary: True # False -> do not show predictor config
chunk_buffer_conf:
frame_duration_ms: 80
shift_ms: 40
sample_rate: 16000
sample_width: 2
window_n: 7 # frame
shift_n: 4 # frame
window_ms: 20 # ms
window_ms: 25 # ms
shift_ms: 10 # ms
sample_rate: 16000
sample_width: 2
demos/audio_content_search/requirements.txt 0 → 100644
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websocket-client
\ No newline at end of file
demos/audio_content_search/run.sh 0 → 100755
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export CUDA_VISIBLE_DEVICE=0,1,2,3
# we need the streaming asr server
nohup python3 streaming_asr_server.py --config_file conf/ws_conformer_application.yaml > streaming_asr.log 2>&1 &
# start the acs server
nohup paddlespeech_server start --config_file conf/acs_application.yaml > acs.log 2>&1 &
demos/audio_content_search/streaming_asr_server.py 0 → 100644
浏览文件 @ 0550d092
# 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.
import argparse
from paddlespeech.cli.log import logger
from paddlespeech.server.bin.paddlespeech_server import ServerExecutor
if __name__ == "__main__":
parser = argparse.ArgumentParser(
prog='paddlespeech_server.start', add_help=True)
parser.add_argument(
"--config_file",
action="store",
help="yaml file of the app",
default=None,
required=True)
parser.add_argument(
"--log_file",
action="store",
help="log file",
default="./log/paddlespeech.log")
logger.info("start to parse the args")
args = parser.parse_args()
logger.info("start to launch the streaming asr server")
streaming_asr_server = ServerExecutor()
streaming_asr_server(config_file=args.config_file, log_file=args.log_file)
demos/audio_searching/README.md
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......@@ -89,7 +89,7 @@ Then to start the system server, and it provides HTTP backend services.
Then start the server with Fastapi.
```bash
export PYTHONPATH=$PYTHONPATH:./src:../../paddleaudio
export PYTHONPATH=$PYTHONPATH:./src
python src/audio_search.py
```
......
demos/audio_searching/README_cn.md
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......@@ -91,7 +91,7 @@ ffce340b3790 minio/minio:RELEASE.2020-12-03T00-03-10Z "/usr/bin/docker-ent…"
启动用 Fastapi 构建的服务
```bash
export PYTHONPATH=$PYTHONPATH:./src:../../paddleaudio
export PYTHONPATH=$PYTHONPATH:./src
python src/audio_search.py
```
......
demos/audio_searching/src/encode.py
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......@@ -14,7 +14,7 @@
import numpy as np
from logs import LOGGER
from paddlespeech.cli import VectorExecutor
from paddlespeech.cli.vector import VectorExecutor
vector_executor = VectorExecutor()
......
demos/audio_tagging/README.md
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......@@ -57,7 +57,7 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/cat.wav https://paddlespe
- Python API
```python
import paddle
from paddlespeech.cli import CLSExecutor
from paddlespeech.cli.cls import CLSExecutor
cls_executor = CLSExecutor()
result = cls_executor(
......
demos/audio_tagging/README_cn.md
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......@@ -57,7 +57,7 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/cat.wav https://paddlespe
- Python API
```python
import paddle
from paddlespeech.cli import CLSExecutor
from paddlespeech.cli.cls import CLSExecutor
cls_executor = CLSExecutor()
result = cls_executor(
......
demos/automatic_video_subtitiles/README.md
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......@@ -28,7 +28,8 @@ ffmpeg -i subtitle_demo1.mp4 -ac 1 -ar 16000 -vn input.wav
- Python API
```python
import paddle
from paddlespeech.cli import ASRExecutor, TextExecutor
from paddlespeech.cli.asr import ASRExecutor
from paddlespeech.cli.text import TextExecutor
asr_executor = ASRExecutor()
text_executor = TextExecutor()
......
demos/automatic_video_subtitiles/README_cn.md
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......@@ -23,7 +23,8 @@ ffmpeg -i subtitle_demo1.mp4 -ac 1 -ar 16000 -vn input.wav
- Python API
```python
import paddle
from paddlespeech.cli import ASRExecutor, TextExecutor
from paddlespeech.cli.asr import ASRExecutor
from paddlespeech.cli.text import TextExecutor
asr_executor = ASRExecutor()
text_executor = TextExecutor()
......
demos/automatic_video_subtitiles/recognize.py
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......@@ -16,8 +16,8 @@ import os
import paddle
from paddlespeech.cli import ASRExecutor
from paddlespeech.cli import TextExecutor
from paddlespeech.cli.asr import ASRExecutor
from paddlespeech.cli.text import TextExecutor
# yapf: disable
parser = argparse.ArgumentParser(__doc__)
......
demos/custom_streaming_asr/README.md 0 → 100644
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([简体中文](./README_cn.md)|English)
# Customized Auto Speech Recognition
## introduction
In some cases, we need to recognize the specific rare words with high accuracy. eg: address recognition in navigation apps. customized ASR can slove those issues.
this demo is customized for expense account, which need to recognize rare address.
the scripts are in https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/speechx/examples/custom_asr
* G with slot: 打车到 "address_slot"。
![](https://ai-studio-static-online.cdn.bcebos.com/28d9ef132a7f47a895a65ae9e5c4f55b8f472c9f3dd24be8a2e66e0b88b173a4)
* this is address slot wfst, you can add the address which want to recognize.
![](https://ai-studio-static-online.cdn.bcebos.com/47c89100ef8c465bac733605ffc53d76abefba33d62f4d818d351f8cea3c8fe2)
* after replace operation, G = fstreplace(G_with_slot, address_slot), we will get the customized graph.
![](https://ai-studio-static-online.cdn.bcebos.com/60a3095293044f10b73039ab10c7950d139a6717580a44a3ba878c6e74de402b)
## Usage
### 1. Installation
install paddle:2.2.2 docker.
```
sudo docker pull registry.baidubce.com/paddlepaddle/paddle:2.2.2
sudo docker run --privileged --net=host --ipc=host -it --rm -v $PWD:/paddle --name=paddle_demo_docker registry.baidubce.com/paddlepaddle/paddle:2.2.2 /bin/bash
```
### 2. demo
* run websocket_server.sh. This script will download resources and libs, and launch the service.
```
cd /paddle
bash websocket_server.sh
```
this script run in two steps:
1. download the resources.tar.gz, those direcotries will be found in resource directory.
model: acustic model
graph: the decoder graph (TLG.fst)
lib: some libs
bin: binary
data: audio and wav.scp
2. websocket_server_main launch the service.
some params:
port: the service port
graph_path: the decoder graph path
model_path: acustic model path
please refer other params in those files:
PaddleSpeech/speechx/speechx/decoder/param.h
PaddleSpeech/speechx/examples/ds2_ol/websocket/websocket_server_main.cc
* In other terminal, run script websocket_client.sh, the client will send data and get the results.
```
bash websocket_client.sh
```
websocket_client_main will launch the client, the wav_scp is the wav set, port is the server service port.
* result:
In the log of client, you will see the message below:
```
0513 10:58:13.827821 41768 recognizer_test_main.cc:56] wav len (sample): 70208
I0513 10:58:13.884493 41768 feature_cache.h:52] set finished
I0513 10:58:24.247171 41768 paddle_nnet.h:76] Tensor neml: 10240
I0513 10:58:24.247249 41768 paddle_nnet.h:76] Tensor neml: 10240
LOG ([5.5.544~2-f21d7]:main():decoder/recognizer_test_main.cc:90) the result of case_10 is 五月十二日二十二点三十六分加班打车回家四十一元
```
demos/custom_streaming_asr/README_cn.md 0 → 100644
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(简体中文|[English](./README.md))
# 定制化语音识别演示
## 介绍
在一些场景中，识别系统需要高精度的识别一些稀有词，例如导航软件中地名识别。而通过定制化识别可以满足这一需求。
这个 demo 是打车报销单的场景识别，需要识别一些稀有的地名，可以通过如下操作实现。
相关脚本:https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/speechx/examples/custom_asr
* G with slot: 打车到 "address_slot"。
![](https://ai-studio-static-online.cdn.bcebos.com/28d9ef132a7f47a895a65ae9e5c4f55b8f472c9f3dd24be8a2e66e0b88b173a4)
* 这是 address slot wfst, 可以添加一些需要识别的地名.
![](https://ai-studio-static-online.cdn.bcebos.com/47c89100ef8c465bac733605ffc53d76abefba33d62f4d818d351f8cea3c8fe2)
* 通过 replace 操作, G = fstreplace(G_with_slot, address_slot), 最终可以得到定制化的解码图。
![](https://ai-studio-static-online.cdn.bcebos.com/60a3095293044f10b73039ab10c7950d139a6717580a44a3ba878c6e74de402b)
## 使用方法
### 1. 配置环境
安装paddle:2.2.2 docker镜像。
```
sudo docker pull registry.baidubce.com/paddlepaddle/paddle:2.2.2
sudo docker run --privileged --net=host --ipc=host -it --rm -v $PWD:/paddle --name=paddle_demo_docker registry.baidubce.com/paddlepaddle/paddle:2.2.2 /bin/bash
```
### 2. 演示
* 运行如下命令，完成相关资源和库的下载和服务启动。
```
cd /paddle
bash websocket_server.sh
```
上面脚本完成了如下两个功能：
1. 完成 resource.tar.gz 下载，解压后,会在 resource 中发现如下目录：
model: 声学模型
graph: 解码构图
lib: 相关库
bin: 运行程序
data: 语音数据
2. 通过 websocket_server_main 来启动服务。
这里简单的介绍几个参数:
port 是服务端口，
graph_path 用来指定解码图文件，
其他参数说明可参见代码：
PaddleSpeech/speechx/speechx/decoder/param.h
PaddleSpeech/speechx/examples/ds2_ol/websocket/websocket_server_main.cc
* 在另一个终端中， 通过 client 发送数据，得到结果。运行如下命令：
```
bash websocket_client.sh
```
通过 websocket_client_main 来启动 client 服务，其中 wav_scp 是发送的语音句子集合，port 为服务端口。
* 结果：
client 的 log 中可以看到如下类似的结果
```
0513 10:58:13.827821 41768 recognizer_test_main.cc:56] wav len (sample): 70208
I0513 10:58:13.884493 41768 feature_cache.h:52] set finished
I0513 10:58:24.247171 41768 paddle_nnet.h:76] Tensor neml: 10240
I0513 10:58:24.247249 41768 paddle_nnet.h:76] Tensor neml: 10240
LOG ([5.5.544~2-f21d7]:main():decoder/recognizer_test_main.cc:90) the result of case_10 is 五月十二日二十二点三十六分加班打车回家四十一元
```
demos/custom_streaming_asr/path.sh 0 → 100644
浏览文件 @ 0550d092
export LD_LIBRARY_PATH=$PWD/resource/lib
export PATH=$PATH:$PWD/resource/bin
demos/custom_streaming_asr/setup_docker.sh 0 → 100644
浏览文件 @ 0550d092
sudo nvidia-docker run --privileged --net=host --ipc=host -it --rm -v $PWD:/paddle --name=paddle_demo_docker registry.baidubce.com/paddlepaddle/paddle:2.2.2 /bin/bash
demos/custom_streaming_asr/websocket_client.sh 0 → 100755
浏览文件 @ 0550d092
#!/bin/bash
set +x
set -e
. path.sh
# input
data=$PWD/data
# output
wav_scp=wav.scp
export GLOG_logtostderr=1
# websocket client
websocket_client_main \
--wav_rspecifier=scp:$data/$wav_scp \
--streaming_chunk=0.36 \
--port=8881
demos/custom_streaming_asr/websocket_server.sh 0 → 100755
浏览文件 @ 0550d092
#!/bin/bash
set +x
set -e
export GLOG_logtostderr=1
. path.sh
#test websocket server
model_dir=./resource/model
graph_dir=./resource/graph
cmvn=./data/cmvn.ark
#paddle_asr_online/resource.tar.gz
if [ ! -f $cmvn ]; then
wget -c https://paddlespeech.bj.bcebos.com/s2t/paddle_asr_online/resource.tar.gz
tar xzfv resource.tar.gz
ln -s ./resource/data .
fi
websocket_server_main \
--cmvn_file=$cmvn \
--streaming_chunk=0.1 \
--use_fbank=true \
--model_path=$model_dir/avg_10.jit.pdmodel \
--param_path=$model_dir/avg_10.jit.pdiparams \
--model_cache_shapes="5-1-2048,5-1-2048" \
--model_output_names=softmax_0.tmp_0,tmp_5,concat_0.tmp_0,concat_1.tmp_0 \
--word_symbol_table=$graph_dir/words.txt \
--graph_path=$graph_dir/TLG.fst --max_active=7500 \
--port=8881 \
--acoustic_scale=12
demos/punctuation_restoration/README.md
浏览文件 @ 0550d092
......@@ -42,7 +42,7 @@ The input of this demo should be a text of the specific language that can be pas
- Python API
```python
import paddle
from paddlespeech.cli import TextExecutor
from paddlespeech.cli.text import TextExecutor
text_executor = TextExecutor()
result = text_executor(
......
demos/punctuation_restoration/README_cn.md
浏览文件 @ 0550d092
......@@ -44,7 +44,7 @@
- Python API
```python
import paddle
from paddlespeech.cli import TextExecutor
from paddlespeech.cli.text import TextExecutor
text_executor = TextExecutor()
result = text_executor(
......
demos/speaker_verification/README.md
浏览文件 @ 0550d092
......@@ -14,7 +14,7 @@ see [installation](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/doc
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.
The input of this cli 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
......@@ -53,51 +53,50 @@ wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav
Output:
```bash
demo [ 1.4217498 5.626253 -5.342073 1.1773866 3.308055
1.756596 5.167894 10.80636 -3.8226728 -5.6141334
2.623845 -0.8072968 1.9635103 -7.3128724 0.01103897
-9.723131 0.6619743 -6.976803 10.213478 7.494748
2.9105635 3.8949256 3.7999806 7.1061673 16.905321
-7.1493764 8.733103 3.4230042 -4.831653 -11.403367
11.232214 7.1274667 -4.2828417 2.452362 -5.130748
-18.177666 -2.6116815 -11.000337 -6.7314315 1.6564683
0.7618269 1.1253023 -2.083836 4.725744 -8.782597
-3.539873 3.814236 5.1420674 2.162061 4.096431
-6.4162116 12.747448 1.9429878 -15.152943 6.417416
16.097002 -9.716668 -1.9920526 -3.3649497 -1.871939
11.567354 3.69788 11.258265 7.442363 9.183411
4.5281515 -1.2417862 4.3959084 6.6727695 5.8898783
7.627124 -0.66919386 -11.889693 -9.208865 -7.4274073
-3.7776625 6.917234 -9.848748 -2.0944717 -5.135116
0.49563864 9.317534 -5.9141874 -1.8098574 -0.11738578
-7.169265 -1.0578263 -5.7216787 -5.1173844 16.137651
-4.473626 7.6624317 -0.55381083 9.631587 -6.4704556
-8.548508 4.3716145 -0.79702514 4.478997 -2.9758704
3.272176 2.8382776 5.134597 -9.190781 -0.5657382
-4.8745747 2.3165567 -5.984303 -2.1798875 0.35541576
-0.31784213 9.493548 2.1144536 4.358092 -12.089823
8.451689 -7.925461 4.6242585 4.4289427 18.692003
-2.6204622 -5.149185 -0.35821092 8.488551 4.981496
-9.32683 -2.2544234 6.6417594 1.2119585 10.977129
16.555033 3.3238444 9.551863 -1.6676947 -0.79539716
-8.605674 -0.47356385 2.6741948 -5.359179 -2.6673796
0.66607 15.443222 4.740594 -3.4725387 11.592567
-2.054497 1.7361217 -8.265324 -9.30447 5.4068313
-1.5180256 -7.746615 -6.089606 0.07112726 -0.34904733
-8.649895 -9.998958 -2.564841 -0.53999114 2.601808
-0.31927416 -1.8815292 -2.07215 -3.4105783 -8.2998085
1.483641 -15.365992 -8.288208 3.8847756 -3.4876456
7.3629923 0.4657332 3.132599 12.438889 -1.8337058
4.532936 2.7264361 10.145339 -6.521951 2.897153
-3.3925855 5.079156 7.759716 4.677565 5.8457737
2.402413 7.7071047 3.9711342 -6.390043 6.1268735
-3.7760346 -11.118123 ]
demo [ -1.3251206 7.8606825 -4.620626 0.3000721 2.2648535
-1.1931441 3.0647137 7.673595 -6.0044727 -12.02426
-1.9496069 3.1269536 1.618838 -7.6383104 -1.2299773
-12.338331 2.1373026 -5.3957124 9.717328 5.6752305
3.7805123 3.0597172 3.429692 8.97601 13.174125
-0.53132284 8.9424715 4.46511 -4.4262476 -9.726503
8.399328 7.2239175 -7.435854 2.9441683 -4.3430395
-13.886965 -1.6346735 -10.9027405 -5.311245 3.8007221
3.8976038 -2.1230774 -2.3521194 4.151031 -7.4048667
0.13911647 2.4626107 4.9664545 0.9897574 5.4839754
-3.3574002 10.1340065 -0.6120171 -10.403095 4.6007543
16.00935 -7.7836914 -4.1945305 -6.9368606 1.1789556
11.490801 4.2380238 9.550931 8.375046 7.5089145
-0.65707296 -0.30051577 2.8406055 3.0828028 0.730817
6.148354 0.13766119 -13.424735 -7.7461405 -2.3227983
-8.305252 2.9879124 -10.995229 0.15211068 -2.3820348
-1.7984174 8.495629 -5.8522367 -3.755498 0.6989711
-5.2702994 -2.6188622 -1.8828466 -4.64665 14.078544
-0.5495333 10.579158 -3.2160501 9.349004 -4.381078
-11.675817 -2.8630207 4.5721755 2.246612 -4.574342
1.8610188 2.3767874 5.6257877 -9.784078 0.64967257
-1.4579505 0.4263264 -4.9211264 -2.454784 3.4869802
-0.42654222 8.341269 1.356552 7.0966883 -13.102829
8.016734 -7.1159344 1.8699781 0.208721 14.699384
-1.025278 -2.6107233 -2.5082312 8.427193 6.9138527
-6.2912464 0.6157366 2.489688 -3.4668267 9.921763
11.200815 -0.1966403 7.4916005 -0.62312716 -0.25848144
-9.947997 -0.9611041 1.1649219 -2.1907122 -1.5028487
-0.51926106 15.165954 2.4649463 -0.9980445 7.4416637
-2.0768049 3.5896823 -7.3055434 -7.5620847 4.323335
0.0804418 -6.56401 -2.3148053 -1.7642345 -2.4708817
-7.675618 -9.548878 -1.0177554 0.16986446 2.5877135
-1.8752296 -0.36614323 -6.0493784 -2.3965611 -5.9453387
0.9424033 -13.155974 -7.457801 0.14658108 -3.742797
5.8414927 -1.2872906 5.5694313 12.57059 1.0939219
2.2142086 1.9181576 6.9914207 -5.888139 3.1409824
-2.003628 2.4434285 9.973139 5.03668 2.0051203
2.8615603 5.860224 2.9176188 -1.6311141 2.0292206
-4.070415 -6.831437 ]
```
- Python API
```python
import paddle
from paddlespeech.cli import VectorExecutor
from paddlespeech.cli.vector import VectorExecutor
vector_executor = VectorExecutor()
audio_emb = vector_executor(
......@@ -128,88 +127,88 @@ wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav
```bash
# Vector Result:
Audio embedding Result:
[ 1.4217498 5.626253 -5.342073 1.1773866 3.308055
1.756596 5.167894 10.80636 -3.8226728 -5.6141334
2.623845 -0.8072968 1.9635103 -7.3128724 0.01103897
-9.723131 0.6619743 -6.976803 10.213478 7.494748
2.9105635 3.8949256 3.7999806 7.1061673 16.905321
-7.1493764 8.733103 3.4230042 -4.831653 -11.403367
11.232214 7.1274667 -4.2828417 2.452362 -5.130748
-18.177666 -2.6116815 -11.000337 -6.7314315 1.6564683
0.7618269 1.1253023 -2.083836 4.725744 -8.782597
-3.539873 3.814236 5.1420674 2.162061 4.096431
-6.4162116 12.747448 1.9429878 -15.152943 6.417416
16.097002 -9.716668 -1.9920526 -3.3649497 -1.871939
11.567354 3.69788 11.258265 7.442363 9.183411
4.5281515 -1.2417862 4.3959084 6.6727695 5.8898783
7.627124 -0.66919386 -11.889693 -9.208865 -7.4274073
-3.7776625 6.917234 -9.848748 -2.0944717 -5.135116
0.49563864 9.317534 -5.9141874 -1.8098574 -0.11738578
-7.169265 -1.0578263 -5.7216787 -5.1173844 16.137651
-4.473626 7.6624317 -0.55381083 9.631587 -6.4704556
-8.548508 4.3716145 -0.79702514 4.478997 -2.9758704
3.272176 2.8382776 5.134597 -9.190781 -0.5657382
-4.8745747 2.3165567 -5.984303 -2.1798875 0.35541576
-0.31784213 9.493548 2.1144536 4.358092 -12.089823
8.451689 -7.925461 4.6242585 4.4289427 18.692003
-2.6204622 -5.149185 -0.35821092 8.488551 4.981496
-9.32683 -2.2544234 6.6417594 1.2119585 10.977129
16.555033 3.3238444 9.551863 -1.6676947 -0.79539716
-8.605674 -0.47356385 2.6741948 -5.359179 -2.6673796
0.66607 15.443222 4.740594 -3.4725387 11.592567
-2.054497 1.7361217 -8.265324 -9.30447 5.4068313
-1.5180256 -7.746615 -6.089606 0.07112726 -0.34904733
-8.649895 -9.998958 -2.564841 -0.53999114 2.601808
-0.31927416 -1.8815292 -2.07215 -3.4105783 -8.2998085
1.483641 -15.365992 -8.288208 3.8847756 -3.4876456
7.3629923 0.4657332 3.132599 12.438889 -1.8337058
4.532936 2.7264361 10.145339 -6.521951 2.897153
-3.3925855 5.079156 7.759716 4.677565 5.8457737
2.402413 7.7071047 3.9711342 -6.390043 6.1268735
-3.7760346 -11.118123 ]
[ -1.3251206 7.8606825 -4.620626 0.3000721 2.2648535
-1.1931441 3.0647137 7.673595 -6.0044727 -12.02426
-1.9496069 3.1269536 1.618838 -7.6383104 -1.2299773
-12.338331 2.1373026 -5.3957124 9.717328 5.6752305
3.7805123 3.0597172 3.429692 8.97601 13.174125
-0.53132284 8.9424715 4.46511 -4.4262476 -9.726503
8.399328 7.2239175 -7.435854 2.9441683 -4.3430395
-13.886965 -1.6346735 -10.9027405 -5.311245 3.8007221
3.8976038 -2.1230774 -2.3521194 4.151031 -7.4048667
0.13911647 2.4626107 4.9664545 0.9897574 5.4839754
-3.3574002 10.1340065 -0.6120171 -10.403095 4.6007543
16.00935 -7.7836914 -4.1945305 -6.9368606 1.1789556
11.490801 4.2380238 9.550931 8.375046 7.5089145
-0.65707296 -0.30051577 2.8406055 3.0828028 0.730817
6.148354 0.13766119 -13.424735 -7.7461405 -2.3227983
-8.305252 2.9879124 -10.995229 0.15211068 -2.3820348
-1.7984174 8.495629 -5.8522367 -3.755498 0.6989711
-5.2702994 -2.6188622 -1.8828466 -4.64665 14.078544
-0.5495333 10.579158 -3.2160501 9.349004 -4.381078
-11.675817 -2.8630207 4.5721755 2.246612 -4.574342
1.8610188 2.3767874 5.6257877 -9.784078 0.64967257
-1.4579505 0.4263264 -4.9211264 -2.454784 3.4869802
-0.42654222 8.341269 1.356552 7.0966883 -13.102829
8.016734 -7.1159344 1.8699781 0.208721 14.699384
-1.025278 -2.6107233 -2.5082312 8.427193 6.9138527
-6.2912464 0.6157366 2.489688 -3.4668267 9.921763
11.200815 -0.1966403 7.4916005 -0.62312716 -0.25848144
-9.947997 -0.9611041 1.1649219 -2.1907122 -1.5028487
-0.51926106 15.165954 2.4649463 -0.9980445 7.4416637
-2.0768049 3.5896823 -7.3055434 -7.5620847 4.323335
0.0804418 -6.56401 -2.3148053 -1.7642345 -2.4708817
-7.675618 -9.548878 -1.0177554 0.16986446 2.5877135
-1.8752296 -0.36614323 -6.0493784 -2.3965611 -5.9453387
0.9424033 -13.155974 -7.457801 0.14658108 -3.742797
5.8414927 -1.2872906 5.5694313 12.57059 1.0939219
2.2142086 1.9181576 6.9914207 -5.888139 3.1409824
-2.003628 2.4434285 9.973139 5.03668 2.0051203
2.8615603 5.860224 2.9176188 -1.6311141 2.0292206
-4.070415 -6.831437 ]
# get the test embedding
Test embedding Result:
[ -1.902964 2.0690894 -8.034194 3.5472693 0.18089125
6.9085927 1.4097427 -1.9487704 -10.021278 -0.20755845
-8.04332 4.344489 2.3200977 -14.306299 5.184692
-11.55602 -3.8497238 0.6444722 1.2833948 2.6766639
0.5878921 0.7946299 1.7207596 2.5791872 14.998469
-1.3385371 15.031221 -0.8006958 1.99287 -9.52007
2.435466 4.003221 -4.33817 -4.898601 -5.304714
-18.033886 10.790787 -12.784645 -5.641755 2.9761686
-10.566622 1.4839455 6.152458 -5.7195854 2.8603241
6.112133 8.489869 5.5958056 1.2836679 -1.2293907
0.89927405 7.0288725 -2.854029 -0.9782962 5.8255906
14.905906 -5.025907 0.7866458 -4.2444224 -16.354029
10.521315 0.9604709 -3.3257897 7.144871 -13.592733
-8.568869 -1.7953678 0.26313916 10.916714 -6.9374123
1.857403 -6.2746415 2.8154466 -7.2338667 -2.293357
-0.05452765 5.4287076 5.0849075 -6.690375 -1.6183422
3.654291 0.94352573 -9.200294 -5.4749465 -3.5235846
1.3420814 4.240421 -2.772944 -2.8451524 16.311104
4.2969875 -1.762936 -12.5758915 8.595198 -0.8835239
-1.5708797 1.568961 1.1413603 3.5032008 -0.45251232
-6.786333 16.89443 5.3366146 -8.789056 0.6355629
3.2579517 -3.328322 7.5969577 0.66025066 -6.550468
-9.148656 2.020372 -0.4615173 1.1965656 -3.8764873
11.6562195 -6.0750933 12.182899 3.2218833 0.81969476
5.570001 -3.8459578 -7.205299 7.9262037 -7.6611166
-5.249467 -2.2671914 7.2658715 -13.298164 4.821147
-2.7263982 11.691089 -3.8918593 -2.838112 -1.0336838
-3.8034165 2.8536487 -5.60398 -1.1972581 1.3455094
-3.4903061 2.2408795 5.5010734 -3.970756 11.99696
-7.8858757 0.43160373 -5.5059714 4.3426995 16.322706
11.635366 0.72157705 -9.245714 -3.91465 -4.449838
-1.5716927 7.713747 -2.2430465 -6.198303 -13.481864
2.8156567 -5.7812386 5.1456156 2.7289324 -14.505571
13.270688 3.448231 -7.0659585 4.5886116 -4.466099
-0.296428 -11.463529 -2.6076477 14.110243 -6.9725137
-1.9962958 2.7119343 19.391657 0.01961198 14.607133
-1.6695905 -4.391516 1.3131028 -6.670972 -5.888604
12.0612335 5.9285784 3.3715196 1.492534 10.723728
-0.95514804 -12.085431 ]
[ 2.5247195 5.119042 -4.335273 4.4583654 5.047907
3.5059214 1.6159848 0.49364898 -11.6899185 -3.1014526
-5.6589785 -0.42684984 2.674276 -11.937654 6.2248464
-10.776924 -5.694543 1.112041 1.5709964 1.0961034
1.3976512 2.324352 1.339981 5.279319 13.734659
-2.5753925 13.651442 -2.2357535 5.1575427 -3.251567
1.4023279 6.1191974 -6.0845175 -1.3646189 -2.6789894
-15.220778 9.779349 -9.411551 -6.388947 6.8313975
-9.245996 0.31196198 2.5509644 -4.413065 6.1649427
6.793837 2.6328635 8.620976 3.4832475 0.52491665
2.9115407 5.8392377 0.6702376 -3.2726715 2.6694255
16.91701 -5.5811176 0.23362345 -4.5573606 -11.801059
14.728292 -0.5198082 -3.999922 7.0927105 -7.0459595
-5.4389 -0.46420583 -5.1085467 10.376568 -8.889225
-0.37705845 -1.659806 2.6731026 -7.1909504 1.4608804
-2.163136 -0.17949677 4.0241547 0.11319201 0.601279
2.039692 3.1910992 -11.649526 -8.121584 -4.8707457
0.3851982 1.4231744 -2.3321972 0.99332285 14.121717
5.899413 0.7384519 -17.760096 10.555021 4.1366534
-0.3391071 -0.20792882 3.208204 0.8847948 -8.721497
-6.432868 13.006379 4.8956 -9.155822 -1.9441519
5.7815638 -2.066733 10.425042 -0.8802383 -2.4314315
-9.869258 0.35095334 -5.3549943 2.1076174 -8.290468
8.4433365 -4.689333 9.334139 -2.172678 -3.0250976
8.394216 -3.2110903 -7.93868 2.3960824 -2.3213403
-1.4963245 -3.476059 4.132903 -10.893354 4.362673
-0.45456508 10.258634 -1.1655927 -6.7799754 0.22885278
-4.399287 2.333433 -4.84745 -4.2752337 -1.3577863
-1.0685898 9.505196 7.3062205 0.08708266 12.927811
-9.57974 1.3936648 -1.9444873 5.776769 15.251903
10.6118355 -1.4903594 -9.535318 -3.6553776 -1.6699586
-0.5933151 7.600357 -4.8815503 -8.698617 -15.855757
0.25632986 -7.2235737 0.9506656 0.7128582 -9.051738
8.74869 -1.6426028 -6.5762258 2.506905 -6.7431564
5.129912 -12.189555 -3.6435068 12.068113 -6.0059533
-2.3535995 2.9014351 22.3082 -1.5563312 13.193291
2.7583609 -7.468798 1.3407065 -4.599617 -6.2345777
10.7689295 7.137627 5.099476 0.3473359 9.647881
-2.0484571 -5.8549366 ]
# get the score between enroll and test
Eembeddings Score: 0.4292638301849365
Eembeddings Score: 0.45332613587379456
```
### 4.Pretrained Models
......
demos/speaker_verification/README_cn.md
浏览文件 @ 0550d092
......@@ -4,16 +4,16 @@
## 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。
这个 demo 是从一个给定音频文件中提取说话人特征，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。
你可以从easy medium，hard 三种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。
声纹cli 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
......@@ -51,51 +51,51 @@ wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav
输出：
```bash
demo [ 1.4217498 5.626253 -5.342073 1.1773866 3.308055
1.756596 5.167894 10.80636 -3.8226728 -5.6141334
2.623845 -0.8072968 1.9635103 -7.3128724 0.01103897
-9.723131 0.6619743 -6.976803 10.213478 7.494748
2.9105635 3.8949256 3.7999806 7.1061673 16.905321
-7.1493764 8.733103 3.4230042 -4.831653 -11.403367
11.232214 7.1274667 -4.2828417 2.452362 -5.130748
-18.177666 -2.6116815 -11.000337 -6.7314315 1.6564683
0.7618269 1.1253023 -2.083836 4.725744 -8.782597
-3.539873 3.814236 5.1420674 2.162061 4.096431
-6.4162116 12.747448 1.9429878 -15.152943 6.417416
16.097002 -9.716668 -1.9920526 -3.3649497 -1.871939
11.567354 3.69788 11.258265 7.442363 9.183411
4.5281515 -1.2417862 4.3959084 6.6727695 5.8898783
7.627124 -0.66919386 -11.889693 -9.208865 -7.4274073
-3.7776625 6.917234 -9.848748 -2.0944717 -5.135116
0.49563864 9.317534 -5.9141874 -1.8098574 -0.11738578
-7.169265 -1.0578263 -5.7216787 -5.1173844 16.137651
-4.473626 7.6624317 -0.55381083 9.631587 -6.4704556
-8.548508 4.3716145 -0.79702514 4.478997 -2.9758704
3.272176 2.8382776 5.134597 -9.190781 -0.5657382
-4.8745747 2.3165567 -5.984303 -2.1798875 0.35541576
-0.31784213 9.493548 2.1144536 4.358092 -12.089823
8.451689 -7.925461 4.6242585 4.4289427 18.692003
-2.6204622 -5.149185 -0.35821092 8.488551 4.981496
-9.32683 -2.2544234 6.6417594 1.2119585 10.977129
16.555033 3.3238444 9.551863 -1.6676947 -0.79539716
-8.605674 -0.47356385 2.6741948 -5.359179 -2.6673796
0.66607 15.443222 4.740594 -3.4725387 11.592567
-2.054497 1.7361217 -8.265324 -9.30447 5.4068313
-1.5180256 -7.746615 -6.089606 0.07112726 -0.34904733
-8.649895 -9.998958 -2.564841 -0.53999114 2.601808
-0.31927416 -1.8815292 -2.07215 -3.4105783 -8.2998085
1.483641 -15.365992 -8.288208 3.8847756 -3.4876456
7.3629923 0.4657332 3.132599 12.438889 -1.8337058
4.532936 2.7264361 10.145339 -6.521951 2.897153
-3.3925855 5.079156 7.759716 4.677565 5.8457737
2.402413 7.7071047 3.9711342 -6.390043 6.1268735
-3.7760346 -11.118123 ]
[ -1.3251206 7.8606825 -4.620626 0.3000721 2.2648535
-1.1931441 3.0647137 7.673595 -6.0044727 -12.02426
-1.9496069 3.1269536 1.618838 -7.6383104 -1.2299773
-12.338331 2.1373026 -5.3957124 9.717328 5.6752305
3.7805123 3.0597172 3.429692 8.97601 13.174125
-0.53132284 8.9424715 4.46511 -4.4262476 -9.726503
8.399328 7.2239175 -7.435854 2.9441683 -4.3430395
-13.886965 -1.6346735 -10.9027405 -5.311245 3.8007221
3.8976038 -2.1230774 -2.3521194 4.151031 -7.4048667
0.13911647 2.4626107 4.9664545 0.9897574 5.4839754
-3.3574002 10.1340065 -0.6120171 -10.403095 4.6007543
16.00935 -7.7836914 -4.1945305 -6.9368606 1.1789556
11.490801 4.2380238 9.550931 8.375046 7.5089145
-0.65707296 -0.30051577 2.8406055 3.0828028 0.730817
6.148354 0.13766119 -13.424735 -7.7461405 -2.3227983
-8.305252 2.9879124 -10.995229 0.15211068 -2.3820348
-1.7984174 8.495629 -5.8522367 -3.755498 0.6989711
-5.2702994 -2.6188622 -1.8828466 -4.64665 14.078544
-0.5495333 10.579158 -3.2160501 9.349004 -4.381078
-11.675817 -2.8630207 4.5721755 2.246612 -4.574342
1.8610188 2.3767874 5.6257877 -9.784078 0.64967257
-1.4579505 0.4263264 -4.9211264 -2.454784 3.4869802
-0.42654222 8.341269 1.356552 7.0966883 -13.102829
8.016734 -7.1159344 1.8699781 0.208721 14.699384
-1.025278 -2.6107233 -2.5082312 8.427193 6.9138527
-6.2912464 0.6157366 2.489688 -3.4668267 9.921763
11.200815 -0.1966403 7.4916005 -0.62312716 -0.25848144
-9.947997 -0.9611041 1.1649219 -2.1907122 -1.5028487
-0.51926106 15.165954 2.4649463 -0.9980445 7.4416637
-2.0768049 3.5896823 -7.3055434 -7.5620847 4.323335
0.0804418 -6.56401 -2.3148053 -1.7642345 -2.4708817
-7.675618 -9.548878 -1.0177554 0.16986446 2.5877135
-1.8752296 -0.36614323 -6.0493784 -2.3965611 -5.9453387
0.9424033 -13.155974 -7.457801 0.14658108 -3.742797
5.8414927 -1.2872906 5.5694313 12.57059 1.0939219
2.2142086 1.9181576 6.9914207 -5.888139 3.1409824
-2.003628 2.4434285 9.973139 5.03668 2.0051203
2.8615603 5.860224 2.9176188 -1.6311141 2.0292206
-4.070415 -6.831437 ]
```
- Python API
```python
import paddle
from paddlespeech.cli import VectorExecutor
from paddlespeech.cli.vector import VectorExecutor
vector_executor = VectorExecutor()
audio_emb = vector_executor(
......@@ -125,88 +125,88 @@ wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav
```bash
# Vector Result:
Audio embedding Result:
[ 1.4217498 5.626253 -5.342073 1.1773866 3.308055
1.756596 5.167894 10.80636 -3.8226728 -5.6141334
2.623845 -0.8072968 1.9635103 -7.3128724 0.01103897
-9.723131 0.6619743 -6.976803 10.213478 7.494748
2.9105635 3.8949256 3.7999806 7.1061673 16.905321
-7.1493764 8.733103 3.4230042 -4.831653 -11.403367
11.232214 7.1274667 -4.2828417 2.452362 -5.130748
-18.177666 -2.6116815 -11.000337 -6.7314315 1.6564683
0.7618269 1.1253023 -2.083836 4.725744 -8.782597
-3.539873 3.814236 5.1420674 2.162061 4.096431
-6.4162116 12.747448 1.9429878 -15.152943 6.417416
16.097002 -9.716668 -1.9920526 -3.3649497 -1.871939
11.567354 3.69788 11.258265 7.442363 9.183411
4.5281515 -1.2417862 4.3959084 6.6727695 5.8898783
7.627124 -0.66919386 -11.889693 -9.208865 -7.4274073
-3.7776625 6.917234 -9.848748 -2.0944717 -5.135116
0.49563864 9.317534 -5.9141874 -1.8098574 -0.11738578
-7.169265 -1.0578263 -5.7216787 -5.1173844 16.137651
-4.473626 7.6624317 -0.55381083 9.631587 -6.4704556
-8.548508 4.3716145 -0.79702514 4.478997 -2.9758704
3.272176 2.8382776 5.134597 -9.190781 -0.5657382
-4.8745747 2.3165567 -5.984303 -2.1798875 0.35541576
-0.31784213 9.493548 2.1144536 4.358092 -12.089823
8.451689 -7.925461 4.6242585 4.4289427 18.692003
-2.6204622 -5.149185 -0.35821092 8.488551 4.981496
-9.32683 -2.2544234 6.6417594 1.2119585 10.977129
16.555033 3.3238444 9.551863 -1.6676947 -0.79539716
-8.605674 -0.47356385 2.6741948 -5.359179 -2.6673796
0.66607 15.443222 4.740594 -3.4725387 11.592567
-2.054497 1.7361217 -8.265324 -9.30447 5.4068313
-1.5180256 -7.746615 -6.089606 0.07112726 -0.34904733
-8.649895 -9.998958 -2.564841 -0.53999114 2.601808
-0.31927416 -1.8815292 -2.07215 -3.4105783 -8.2998085
1.483641 -15.365992 -8.288208 3.8847756 -3.4876456
7.3629923 0.4657332 3.132599 12.438889 -1.8337058
4.532936 2.7264361 10.145339 -6.521951 2.897153
-3.3925855 5.079156 7.759716 4.677565 5.8457737
2.402413 7.7071047 3.9711342 -6.390043 6.1268735
-3.7760346 -11.118123 ]
[ -1.3251206 7.8606825 -4.620626 0.3000721 2.2648535
-1.1931441 3.0647137 7.673595 -6.0044727 -12.02426
-1.9496069 3.1269536 1.618838 -7.6383104 -1.2299773
-12.338331 2.1373026 -5.3957124 9.717328 5.6752305
3.7805123 3.0597172 3.429692 8.97601 13.174125
-0.53132284 8.9424715 4.46511 -4.4262476 -9.726503
8.399328 7.2239175 -7.435854 2.9441683 -4.3430395
-13.886965 -1.6346735 -10.9027405 -5.311245 3.8007221
3.8976038 -2.1230774 -2.3521194 4.151031 -7.4048667
0.13911647 2.4626107 4.9664545 0.9897574 5.4839754
-3.3574002 10.1340065 -0.6120171 -10.403095 4.6007543
16.00935 -7.7836914 -4.1945305 -6.9368606 1.1789556
11.490801 4.2380238 9.550931 8.375046 7.5089145
-0.65707296 -0.30051577 2.8406055 3.0828028 0.730817
6.148354 0.13766119 -13.424735 -7.7461405 -2.3227983
-8.305252 2.9879124 -10.995229 0.15211068 -2.3820348
-1.7984174 8.495629 -5.8522367 -3.755498 0.6989711
-5.2702994 -2.6188622 -1.8828466 -4.64665 14.078544
-0.5495333 10.579158 -3.2160501 9.349004 -4.381078
-11.675817 -2.8630207 4.5721755 2.246612 -4.574342
1.8610188 2.3767874 5.6257877 -9.784078 0.64967257
-1.4579505 0.4263264 -4.9211264 -2.454784 3.4869802
-0.42654222 8.341269 1.356552 7.0966883 -13.102829
8.016734 -7.1159344 1.8699781 0.208721 14.699384
-1.025278 -2.6107233 -2.5082312 8.427193 6.9138527
-6.2912464 0.6157366 2.489688 -3.4668267 9.921763
11.200815 -0.1966403 7.4916005 -0.62312716 -0.25848144
-9.947997 -0.9611041 1.1649219 -2.1907122 -1.5028487
-0.51926106 15.165954 2.4649463 -0.9980445 7.4416637
-2.0768049 3.5896823 -7.3055434 -7.5620847 4.323335
0.0804418 -6.56401 -2.3148053 -1.7642345 -2.4708817
-7.675618 -9.548878 -1.0177554 0.16986446 2.5877135
-1.8752296 -0.36614323 -6.0493784 -2.3965611 -5.9453387
0.9424033 -13.155974 -7.457801 0.14658108 -3.742797
5.8414927 -1.2872906 5.5694313 12.57059 1.0939219
2.2142086 1.9181576 6.9914207 -5.888139 3.1409824
-2.003628 2.4434285 9.973139 5.03668 2.0051203
2.8615603 5.860224 2.9176188 -1.6311141 2.0292206
-4.070415 -6.831437 ]
# get the test embedding
Test embedding Result:
[ -1.902964 2.0690894 -8.034194 3.5472693 0.18089125
6.9085927 1.4097427 -1.9487704 -10.021278 -0.20755845
-8.04332 4.344489 2.3200977 -14.306299 5.184692
-11.55602 -3.8497238 0.6444722 1.2833948 2.6766639
0.5878921 0.7946299 1.7207596 2.5791872 14.998469
-1.3385371 15.031221 -0.8006958 1.99287 -9.52007
2.435466 4.003221 -4.33817 -4.898601 -5.304714
-18.033886 10.790787 -12.784645 -5.641755 2.9761686
-10.566622 1.4839455 6.152458 -5.7195854 2.8603241
6.112133 8.489869 5.5958056 1.2836679 -1.2293907
0.89927405 7.0288725 -2.854029 -0.9782962 5.8255906
14.905906 -5.025907 0.7866458 -4.2444224 -16.354029
10.521315 0.9604709 -3.3257897 7.144871 -13.592733
-8.568869 -1.7953678 0.26313916 10.916714 -6.9374123
1.857403 -6.2746415 2.8154466 -7.2338667 -2.293357
-0.05452765 5.4287076 5.0849075 -6.690375 -1.6183422
3.654291 0.94352573 -9.200294 -5.4749465 -3.5235846
1.3420814 4.240421 -2.772944 -2.8451524 16.311104
4.2969875 -1.762936 -12.5758915 8.595198 -0.8835239
-1.5708797 1.568961 1.1413603 3.5032008 -0.45251232
-6.786333 16.89443 5.3366146 -8.789056 0.6355629
3.2579517 -3.328322 7.5969577 0.66025066 -6.550468
-9.148656 2.020372 -0.4615173 1.1965656 -3.8764873
11.6562195 -6.0750933 12.182899 3.2218833 0.81969476
5.570001 -3.8459578 -7.205299 7.9262037 -7.6611166
-5.249467 -2.2671914 7.2658715 -13.298164 4.821147
-2.7263982 11.691089 -3.8918593 -2.838112 -1.0336838
-3.8034165 2.8536487 -5.60398 -1.1972581 1.3455094
-3.4903061 2.2408795 5.5010734 -3.970756 11.99696
-7.8858757 0.43160373 -5.5059714 4.3426995 16.322706
11.635366 0.72157705 -9.245714 -3.91465 -4.449838
-1.5716927 7.713747 -2.2430465 -6.198303 -13.481864
2.8156567 -5.7812386 5.1456156 2.7289324 -14.505571
13.270688 3.448231 -7.0659585 4.5886116 -4.466099
-0.296428 -11.463529 -2.6076477 14.110243 -6.9725137
-1.9962958 2.7119343 19.391657 0.01961198 14.607133
-1.6695905 -4.391516 1.3131028 -6.670972 -5.888604
12.0612335 5.9285784 3.3715196 1.492534 10.723728
-0.95514804 -12.085431 ]
[ 2.5247195 5.119042 -4.335273 4.4583654 5.047907
3.5059214 1.6159848 0.49364898 -11.6899185 -3.1014526
-5.6589785 -0.42684984 2.674276 -11.937654 6.2248464
-10.776924 -5.694543 1.112041 1.5709964 1.0961034
1.3976512 2.324352 1.339981 5.279319 13.734659
-2.5753925 13.651442 -2.2357535 5.1575427 -3.251567
1.4023279 6.1191974 -6.0845175 -1.3646189 -2.6789894
-15.220778 9.779349 -9.411551 -6.388947 6.8313975
-9.245996 0.31196198 2.5509644 -4.413065 6.1649427
6.793837 2.6328635 8.620976 3.4832475 0.52491665
2.9115407 5.8392377 0.6702376 -3.2726715 2.6694255
16.91701 -5.5811176 0.23362345 -4.5573606 -11.801059
14.728292 -0.5198082 -3.999922 7.0927105 -7.0459595
-5.4389 -0.46420583 -5.1085467 10.376568 -8.889225
-0.37705845 -1.659806 2.6731026 -7.1909504 1.4608804
-2.163136 -0.17949677 4.0241547 0.11319201 0.601279
2.039692 3.1910992 -11.649526 -8.121584 -4.8707457
0.3851982 1.4231744 -2.3321972 0.99332285 14.121717
5.899413 0.7384519 -17.760096 10.555021 4.1366534
-0.3391071 -0.20792882 3.208204 0.8847948 -8.721497
-6.432868 13.006379 4.8956 -9.155822 -1.9441519
5.7815638 -2.066733 10.425042 -0.8802383 -2.4314315
-9.869258 0.35095334 -5.3549943 2.1076174 -8.290468
8.4433365 -4.689333 9.334139 -2.172678 -3.0250976
8.394216 -3.2110903 -7.93868 2.3960824 -2.3213403
-1.4963245 -3.476059 4.132903 -10.893354 4.362673
-0.45456508 10.258634 -1.1655927 -6.7799754 0.22885278
-4.399287 2.333433 -4.84745 -4.2752337 -1.3577863
-1.0685898 9.505196 7.3062205 0.08708266 12.927811
-9.57974 1.3936648 -1.9444873 5.776769 15.251903
10.6118355 -1.4903594 -9.535318 -3.6553776 -1.6699586
-0.5933151 7.600357 -4.8815503 -8.698617 -15.855757
0.25632986 -7.2235737 0.9506656 0.7128582 -9.051738
8.74869 -1.6426028 -6.5762258 2.506905 -6.7431564
5.129912 -12.189555 -3.6435068 12.068113 -6.0059533
-2.3535995 2.9014351 22.3082 -1.5563312 13.193291
2.7583609 -7.468798 1.3407065 -4.599617 -6.2345777
10.7689295 7.137627 5.099476 0.3473359 9.647881
-2.0484571 -5.8549366 ]
# get the score between enroll and test
Eembeddings Score: 0.4292638301849365
Eembeddings Score: 0.45332613587379456
```
### 4.预训练模型
......
demos/speech_recognition/README.md
浏览文件 @ 0550d092
......@@ -24,13 +24,13 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
- Command Line(Recommended)
```bash
# Chinese
paddlespeech asr --input ./zh.wav
paddlespeech asr --input ./zh.wav -v
# English
paddlespeech asr --model transformer_librispeech --lang en --input ./en.wav
paddlespeech asr --model transformer_librispeech --lang en --input ./en.wav -v
# Chinese ASR + Punctuation Restoration
paddlespeech asr --input ./zh.wav | paddlespeech text --task punc
paddlespeech asr --input ./zh.wav -v | paddlespeech text --task punc -v
```
(It doesn't matter if package `paddlespeech-ctcdecoders` is not found, this package is optional.)
(If you don't want to see the log information, you can remove "-v". Besides, it doesn't matter if package `paddlespeech-ctcdecoders` is not found, this package is optional.)
Usage:
```bash
......@@ -45,6 +45,7 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
- `ckpt_path`: Model checkpoint. Use pretrained model when it is None. Default: `None`.
- `yes`: No additional parameters required. Once set this parameter, it means accepting the request of the program by default, which includes transforming the audio sample rate. Default: `False`.
- `device`: Choose device to execute model inference. Default: default device of paddlepaddle in current environment.
- `verbose`: Show the log information.
Output:
```bash
......@@ -57,7 +58,7 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
- Python API
```python
import paddle
from paddlespeech.cli import ASRExecutor
from paddlespeech.cli.asr import ASRExecutor
asr_executor = ASRExecutor()
text = asr_executor(
......@@ -84,8 +85,12 @@ Here is a list of pretrained models released by PaddleSpeech that can be used by
| Model | Language | Sample Rate
| :--- | :---: | :---: |
| conformer_wenetspeech| zh| 16k
| transformer_librispeech| en| 16k
| conformer_wenetspeech | zh | 16k
| conformer_online_multicn | zh | 16k
| conformer_aishell | zh | 16k
| conformer_online_aishell | zh | 16k
| transformer_librispeech | en | 16k
| deepspeech2online_wenetspeech | zh | 16k
| deepspeech2offline_aishell| zh| 16k
| deepspeech2online_aishell | zh | 16k
|deepspeech2offline_librispeech|en| 16k
| deepspeech2offline_librispeech | en | 16k
demos/speech_recognition/README_cn.md
浏览文件 @ 0550d092
......@@ -22,13 +22,13 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
- 命令行 (推荐使用)
```bash
# 中文
paddlespeech asr --input ./zh.wav
paddlespeech asr --input ./zh.wav -v
# 英文
paddlespeech asr --model transformer_librispeech --lang en --input ./en.wav
paddlespeech asr --model transformer_librispeech --lang en --input ./en.wav -v
# 中文 + 标点恢复
paddlespeech asr --input ./zh.wav | paddlespeech text --task punc
paddlespeech asr --input ./zh.wav -v | paddlespeech text --task punc -v
```
(如果显示 `paddlespeech-ctcdecoders` 这个 python 包没有找到的 Error，没有关系，这个包是非必须的。)
(如果不想显示 log 信息，可以不使用"-v", 另外如果显示 `paddlespeech-ctcdecoders` 这个 python 包没有找到的 Error，没有关系，这个包是非必须的。)
使用方法：
```bash
......@@ -43,6 +43,7 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
- `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`。
- `yes`；不需要设置额外的参数，一旦设置了该参数，说明你默认同意程序的所有请求，其中包括自动转换输入音频的采样率。默认值：`False`。
- `device`：执行预测的设备，默认值：当前系统下 paddlepaddle 的默认 device。
- `verbose`: 如果使用，显示 logger 信息。
输出：
```bash
......@@ -55,7 +56,7 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
- Python API
```python
import paddle
from paddlespeech.cli import ASRExecutor
from paddlespeech.cli.asr import ASRExecutor
asr_executor = ASRExecutor()
text = asr_executor(
......@@ -82,7 +83,11 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
| 模型 | 语言 | 采样率
| :--- | :---: | :---: |
| conformer_wenetspeech | zh | 16k
| conformer_online_multicn | zh | 16k
| conformer_aishell | zh | 16k
| conformer_online_aishell | zh | 16k
| transformer_librispeech | en | 16k
| deepspeech2online_wenetspeech | zh | 16k
| deepspeech2offline_aishell| zh| 16k
| deepspeech2online_aishell | zh | 16k
| deepspeech2offline_librispeech | en | 16k
demos/speech_server/README.md
浏览文件 @ 0550d092
......@@ -10,7 +10,7 @@ This demo is an implementation of starting the voice service and accessing the s
### 1. Installation
see [installation](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/docs/source/install.md).
It is recommended to use **paddlepaddle 2.2.1** or above.
It is recommended to use **paddlepaddle 2.2.2** or above.
You can choose one way from meduim and hard to install paddlespeech.
### 2. Prepare config File
......@@ -18,6 +18,7 @@ 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), tts (text to sppech) and cls (audio classification).
Currently the engine type supports two forms: python and inference (Paddle Inference)
**Note:** If the service can be started normally in the container, but the client access IP is unreachable, you can try to replace the `host` address in the configuration file with the local IP address.
The input of ASR client demo should be a WAV file(`.wav`), and the sample rate must be the same as the model.
......@@ -83,6 +84,9 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
### 4. ASR Client Usage
**Note:** The response time will be slightly longer when using the client for the first time
- Command Line (Recommended)
If `127.0.0.1` is not accessible, you need to use the actual service IP address.
```
paddlespeech_client asr --server_ip 127.0.0.1 --port 8090 --input ./zh.wav
```
......@@ -131,6 +135,9 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
### 5. TTS Client Usage
**Note:** The response time will be slightly longer when using the client for the first time
- Command Line (Recommended)
If `127.0.0.1` is not accessible, you need to use the actual service IP address
```bash
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
```
......@@ -191,6 +198,9 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
### 6. CLS Client Usage
**Note:** The response time will be slightly longer when using the client for the first time
- Command Line (Recommended)
If `127.0.0.1` is not accessible, you need to use the actual service IP address.
```
paddlespeech_client cls --server_ip 127.0.0.1 --port 8090 --input ./zh.wav
```
......@@ -235,6 +245,173 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
```
### 7. Speaker Verification Client Usage
#### 7.1 Extract speaker embedding
**Note:** The response time will be slightly longer when using the client for the first time
- Command Line (Recommended)
If `127.0.0.1` is not accessible, you need to use the actual service IP address.
``` bash
paddlespeech_client vector --task spk --server_ip 127.0.0.1 --port 8090 --input 85236145389.wav
```
Usage:
``` bash
paddlespeech_client vector --help
```
Arguments:
* server_ip: server ip. Default: 127.0.0.1
* port: server port. Default: 8090
* input(required): Input text to generate.
* task: the task of vector, can be use 'spk' or 'score。Default is 'spk'。
* enroll: enroll audio
* test: test audio
Output:
```bash
[2022-05-25 12:25:36,165] [ INFO] - vector http client start
[2022-05-25 12:25:36,165] [ INFO] - the input audio: 85236145389.wav
[2022-05-25 12:25:36,165] [ INFO] - endpoint: http://127.0.0.1:8790/paddlespeech/vector
[2022-05-25 12:25:36,166] [ INFO] - http://127.0.0.1:8790/paddlespeech/vector
[2022-05-25 12:25:36,324] [ INFO] - The vector: {'success': True, 'code': 200, 'message': {'description': 'success'}, 'result': {'vec': [-1.3251205682754517, 7.860682487487793, -4.620625972747803, 0.3000721037387848, 2.2648534774780273, -1.1931440830230713, 3.064713716506958, 7.673594951629639, -6.004472732543945, -12.024259567260742, -1.9496068954467773, 3.126953601837158, 1.6188379526138306, -7.638310432434082, -1.2299772500991821, -12.33833122253418, 2.1373026371002197, -5.395712375640869, 9.717328071594238, 5.675230503082275, 3.7805123329162598, 3.0597171783447266, 3.429692029953003, 8.9760103225708, 13.174124717712402, -0.5313228368759155, 8.942471504211426, 4.465109825134277, -4.426247596740723, -9.726503372192383, 8.399328231811523, 7.223917484283447, -7.435853958129883, 2.9441683292388916, -4.343039512634277, -13.886964797973633, -1.6346734762191772, -10.902740478515625, -5.311244964599609, 3.800722122192383, 3.897603750228882, -2.123077392578125, -2.3521194458007812, 4.151031017303467, -7.404866695404053, 0.13911646604537964, 2.4626107215881348, 4.96645450592041, 0.9897574186325073, 5.483975410461426, -3.3574001789093018, 10.13400650024414, -0.6120170950889587, -10.403095245361328, 4.600754261016846, 16.009349822998047, -7.78369140625, -4.194530487060547, -6.93686056137085, 1.1789555549621582, 11.490800857543945, 4.23802375793457, 9.550930976867676, 8.375045776367188, 7.508914470672607, -0.6570729613304138, -0.3005157709121704, 2.8406054973602295, 3.0828027725219727, 0.7308170199394226, 6.1483540534973145, 0.1376611888408661, -13.424735069274902, -7.746140480041504, -2.322798252105713, -8.305252075195312, 2.98791241645813, -10.99522876739502, 0.15211068093776703, -2.3820347785949707, -1.7984174489974976, 8.49562931060791, -5.852236747741699, -3.755497932434082, 0.6989710927009583, -5.270299434661865, -2.6188621520996094, -1.8828465938568115, -4.6466498374938965, 14.078543663024902, -0.5495333075523376, 10.579157829284668, -3.216050148010254, 9.349003791809082, -4.381077766418457, -11.675816535949707, -2.863020658493042, 4.5721755027771, 2.246612071990967, -4.574341773986816, 1.8610187768936157, 2.3767874240875244, 5.625787734985352, -9.784077644348145, 0.6496725678443909, -1.457950472831726, 0.4263263940811157, -4.921126365661621, -2.4547839164733887, 3.4869801998138428, -0.4265422224998474, 8.341268539428711, 1.356552004814148, 7.096688270568848, -13.102828979492188, 8.01673412322998, -7.115934371948242, 1.8699780702590942, 0.20872099697589874, 14.699383735656738, -1.0252779722213745, -2.6107232570648193, -2.5082311630249023, 8.427192687988281, 6.913852691650391, -6.29124641418457, 0.6157366037368774, 2.489687919616699, -3.4668266773223877, 9.92176342010498, 11.200815200805664, -0.19664029777050018, 7.491600513458252, -0.6231271624565125, -0.2584814429283142, -9.947997093200684, -0.9611040949821472, 1.1649218797683716, -2.1907122135162354, -1.502848744392395, -0.5192610621452332, 15.165953636169434, 2.4649462699890137, -0.998044490814209, 7.44166374206543, -2.0768048763275146, 3.5896823406219482, -7.305543422698975, -7.562084674835205, 4.32333517074585, 0.08044180274009705, -6.564010143280029, -2.314805269241333, -1.7642345428466797, -2.470881700515747, -7.6756181716918945, -9.548877716064453, -1.017755389213562, 0.1698644608259201, 2.5877134799957275, -1.8752295970916748, -0.36614322662353516, -6.049378395080566, -2.3965611457824707, -5.945338726043701, 0.9424033164978027, -13.155974388122559, -7.45780086517334, 0.14658108353614807, -3.7427968978881836, 5.841492652893066, -1.2872905731201172, 5.569431304931641, 12.570590019226074, 1.0939218997955322, 2.2142086029052734, 1.9181575775146484, 6.991420745849609, -5.888138771057129, 3.1409823894500732, -2.0036280155181885, 2.4434285163879395, 9.973138809204102, 5.036680221557617, 2.005120277404785, 2.861560344696045, 5.860223770141602, 2.917618751525879, -1.63111412525177, 2.0292205810546875, -4.070415019989014, -6.831437110900879]}}
[2022-05-25 12:25:36,324] [ INFO] - Response time 0.159053 s.
```
* Python API
``` python
from paddlespeech.server.bin.paddlespeech_client import VectorClientExecutor
vectorclient_executor = VectorClientExecutor()
res = vectorclient_executor(
input="85236145389.wav",
server_ip="127.0.0.1",
port=8090,
task="spk")
print(res)
```
Output:
``` bash
{'success': True, 'code': 200, 'message': {'description': 'success'}, 'result': {'vec': [-1.3251205682754517, 7.860682487487793, -4.620625972747803, 0.3000721037387848, 2.2648534774780273, -1.1931440830230713, 3.064713716506958, 7.673594951629639, -6.004472732543945, -12.024259567260742, -1.9496068954467773, 3.126953601837158, 1.6188379526138306, -7.638310432434082, -1.2299772500991821, -12.33833122253418, 2.1373026371002197, -5.395712375640869, 9.717328071594238, 5.675230503082275, 3.7805123329162598, 3.0597171783447266, 3.429692029953003, 8.9760103225708, 13.174124717712402, -0.5313228368759155, 8.942471504211426, 4.465109825134277, -4.426247596740723, -9.726503372192383, 8.399328231811523, 7.223917484283447, -7.435853958129883, 2.9441683292388916, -4.343039512634277, -13.886964797973633, -1.6346734762191772, -10.902740478515625, -5.311244964599609, 3.800722122192383, 3.897603750228882, -2.123077392578125, -2.3521194458007812, 4.151031017303467, -7.404866695404053, 0.13911646604537964, 2.4626107215881348, 4.96645450592041, 0.9897574186325073, 5.483975410461426, -3.3574001789093018, 10.13400650024414, -0.6120170950889587, -10.403095245361328, 4.600754261016846, 16.009349822998047, -7.78369140625, -4.194530487060547, -6.93686056137085, 1.1789555549621582, 11.490800857543945, 4.23802375793457, 9.550930976867676, 8.375045776367188, 7.508914470672607, -0.6570729613304138, -0.3005157709121704, 2.8406054973602295, 3.0828027725219727, 0.7308170199394226, 6.1483540534973145, 0.1376611888408661, -13.424735069274902, -7.746140480041504, -2.322798252105713, -8.305252075195312, 2.98791241645813, -10.99522876739502, 0.15211068093776703, -2.3820347785949707, -1.7984174489974976, 8.49562931060791, -5.852236747741699, -3.755497932434082, 0.6989710927009583, -5.270299434661865, -2.6188621520996094, -1.8828465938568115, -4.6466498374938965, 14.078543663024902, -0.5495333075523376, 10.579157829284668, -3.216050148010254, 9.349003791809082, -4.381077766418457, -11.675816535949707, -2.863020658493042, 4.5721755027771, 2.246612071990967, -4.574341773986816, 1.8610187768936157, 2.3767874240875244, 5.625787734985352, -9.784077644348145, 0.6496725678443909, -1.457950472831726, 0.4263263940811157, -4.921126365661621, -2.4547839164733887, 3.4869801998138428, -0.4265422224998474, 8.341268539428711, 1.356552004814148, 7.096688270568848, -13.102828979492188, 8.01673412322998, -7.115934371948242, 1.8699780702590942, 0.20872099697589874, 14.699383735656738, -1.0252779722213745, -2.6107232570648193, -2.5082311630249023, 8.427192687988281, 6.913852691650391, -6.29124641418457, 0.6157366037368774, 2.489687919616699, -3.4668266773223877, 9.92176342010498, 11.200815200805664, -0.19664029777050018, 7.491600513458252, -0.6231271624565125, -0.2584814429283142, -9.947997093200684, -0.9611040949821472, 1.1649218797683716, -2.1907122135162354, -1.502848744392395, -0.5192610621452332, 15.165953636169434, 2.4649462699890137, -0.998044490814209, 7.44166374206543, -2.0768048763275146, 3.5896823406219482, -7.305543422698975, -7.562084674835205, 4.32333517074585, 0.08044180274009705, -6.564010143280029, -2.314805269241333, -1.7642345428466797, -2.470881700515747, -7.6756181716918945, -9.548877716064453, -1.017755389213562, 0.1698644608259201, 2.5877134799957275, -1.8752295970916748, -0.36614322662353516, -6.049378395080566, -2.3965611457824707, -5.945338726043701, 0.9424033164978027, -13.155974388122559, -7.45780086517334, 0.14658108353614807, -3.7427968978881836, 5.841492652893066, -1.2872905731201172, 5.569431304931641, 12.570590019226074, 1.0939218997955322, 2.2142086029052734, 1.9181575775146484, 6.991420745849609, -5.888138771057129, 3.1409823894500732, -2.0036280155181885, 2.4434285163879395, 9.973138809204102, 5.036680221557617, 2.005120277404785, 2.861560344696045, 5.860223770141602, 2.917618751525879, -1.63111412525177, 2.0292205810546875, -4.070415019989014, -6.831437110900879]}}
```
#### 7.2 Get the score between speaker audio embedding
**Note:** The response time will be slightly longer when using the client for the first time
- Command Line (Recommended)
If `127.0.0.1` is not accessible, you need to use the actual service IP address.
``` bash
paddlespeech_client vector --task score --server_ip 127.0.0.1 --port 8090 --enroll 85236145389.wav --test 123456789.wav
```
Usage:
``` bash
paddlespeech_client vector --help
```
Arguments:
* server_ip: server ip. Default: 127.0.0.1
* port: server port. Default: 8090
* input(required): Input text to generate.
* task: the task of vector, can be use 'spk' or 'score。If get the score, this must be 'score' parameter.
* enroll: enroll audio
* test: test audio
Output:
``` bash
[2022-05-25 12:33:24,527] [ INFO] - vector score http client start
[2022-05-25 12:33:24,527] [ INFO] - enroll audio: 85236145389.wav, test audio: 123456789.wav
[2022-05-25 12:33:24,528] [ INFO] - endpoint: http://127.0.0.1:8790/paddlespeech/vector/score
[2022-05-25 12:33:24,695] [ INFO] - The vector score is: {'success': True, 'code': 200, 'message': {'description': 'success'}, 'result': {'score': 0.45332613587379456}}
[2022-05-25 12:33:24,696] [ INFO] - The vector: {'success': True, 'code': 200, 'message': {'description': 'success'}, 'result': {'score': 0.45332613587379456}}
[2022-05-25 12:33:24,696] [ INFO] - Response time 0.168271 s.
```
* Python API
``` python
from paddlespeech.server.bin.paddlespeech_client import VectorClientExecutor
vectorclient_executor = VectorClientExecutor()
res = vectorclient_executor(
input=None,
enroll_audio="85236145389.wav",
test_audio="123456789.wav",
server_ip="127.0.0.1",
port=8090,
task="score")
print(res)
```
Output:
``` bash
[2022-05-25 12:30:14,143] [ INFO] - vector score http client start
[2022-05-25 12:30:14,143] [ INFO] - enroll audio: 85236145389.wav, test audio: 123456789.wav
[2022-05-25 12:30:14,143] [ INFO] - endpoint: http://127.0.0.1:8790/paddlespeech/vector/score
[2022-05-25 12:30:14,363] [ INFO] - The vector score is: {'success': True, 'code': 200, 'message': {'description': 'success'}, 'result': {'score': 0.45332613587379456}}
{'success': True, 'code': 200, 'message': {'description': 'success'}, 'result': {'score': 0.45332613587379456}}
```
### 8. Punctuation prediction
**Note:** The response time will be slightly longer when using the client for the first time
- Command Line (Recommended)
If `127.0.0.1` is not accessible, you need to use the actual service IP address.
``` bash
paddlespeech_client text --server_ip 127.0.0.1 --port 8090 --input "我认为跑步最重要的就是给我带来了身体健康"
```
Usage:
```bash
paddlespeech_client text --help
```
Arguments:
- `server_ip`: server ip. Default: 127.0.0.1
- `port`: server port. Default: 8090
- `input`(required): Input text to get punctuation.
Output:
```bash
[2022-05-09 18:19:04,397] [ INFO] - The punc text: 我认为跑步最重要的就是给我带来了身体健康。
[2022-05-09 18:19:04,397] [ INFO] - Response time 0.092407 s.
```
- Python API
```python
from paddlespeech.server.bin.paddlespeech_client import TextClientExecutor
textclient_executor = TextClientExecutor()
res = textclient_executor(
input="我认为跑步最重要的就是给我带来了身体健康",
server_ip="127.0.0.1",
port=8090,)
print(res)
```
Output:
```bash
我认为跑步最重要的就是给我带来了身体健康。
```
## Models supported by the service
### ASR model
Get all models supported by the ASR service via `paddlespeech_server stats --task asr`, where static models can be used for paddle inference inference.
......@@ -244,3 +421,9 @@ Get all models supported by the TTS service via `paddlespeech_server stats --tas
### CLS model
Get all models supported by the CLS service via `paddlespeech_server stats --task cls`, where static models can be used for paddle inference inference.
### Vector model
Get all models supported by the TTS service via `paddlespeech_server stats --task vector`, where static models can be used for paddle inference inference.
### Text model
Get all models supported by the CLS service via `paddlespeech_server stats --task text`, where static models can be used for paddle inference inference.
demos/speech_server/README_cn.md
浏览文件 @ 0550d092
([简体中文](./README_cn.md)|English)
(简体中文|[English](./README.md))
# 语音服务
## 介绍
这个demo是一个启动语音服务和访问服务的实现。 它可以通过使用`paddlespeech_server` 和 `paddlespeech_client`的单个命令或 python 的几行代码来实现。
这个 demo 是一个启动离线语音服务和访问服务的实现。它可以通过使用`paddlespeech_server` 和 `paddlespeech_client`的单个命令或 python 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.md).
推荐使用 **paddlepaddle 2.2.1** 或以上版本。
你可以从 medium，hard 三中方式中选择一种方式安装 PaddleSpeech。
推荐使用 **paddlepaddle 2.2.2** 或以上版本。
你可以从 medium，hard 两种方式中选择一种方式安装 PaddleSpeech。
### 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)以及cls(音频分类)。
目前服务集成的语音任务有： asr(语音识别)、tts(语音合成)、cls(音频分类)、vector(声纹识别)以及text(文本处理)。
目前引擎类型支持两种形式：python 及 inference (Paddle Inference)
**注意：** 如果在容器里可正常启动服务，但客户端访问 ip 不可达，可尝试将配置文件中 `host` 地址换成本地 ip 地址。
这个 ASR client 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。
ASR client 的输入是一个 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 ASR client的示例音频：
可以下载此 ASR client 的示例音频：
```bash
wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespeech.bj.bcebos.com/PaddleAudio/en.wav
```
......@@ -83,6 +84,9 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
### 4. ASR 客户端使用方法
**注意：** 初次使用客户端时响应时间会略长
- 命令行 (推荐使用)
若 `127.0.0.1` 不能访问，则需要使用实际服务 IP 地址
```
paddlespeech_client asr --server_ip 127.0.0.1 --port 8090 --input ./zh.wav
......@@ -95,7 +99,7 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
```
参数:
- `server_ip`: 服务端ip地址，默认: 127.0.0.1。
- `server_ip`: 服务端 ip 地址，默认: 127.0.0.1。
- `port`: 服务端口，默认: 8090。
- `input`(必须输入): 用于识别的音频文件。
- `sample_rate`: 音频采样率，默认值：16000。
......@@ -135,6 +139,8 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
**注意：** 初次使用客户端时响应时间会略长
- 命令行 (推荐使用)
若 `127.0.0.1` 不能访问，则需要使用实际服务 IP 地址
```bash
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
```
......@@ -192,9 +198,14 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
```
### 6. CLS 客户端使用方法
**注意：** 初次使用客户端时响应时间会略长
- 命令行 (推荐使用)
### 6. CLS 客户端使用方法
**注意：** 初次使用客户端时响应时间会略长
- 命令行 (推荐使用)
若 `127.0.0.1` 不能访问，则需要使用实际服务 IP 地址
```
paddlespeech_client cls --server_ip 127.0.0.1 --port 8090 --input ./zh.wav
```
......@@ -205,7 +216,7 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
paddlespeech_client cls --help
```
参数:
- `server_ip`: 服务端ip地址，默认: 127.0.0.1。
- `server_ip`: 服务端 ip 地址，默认: 127.0.0.1。
- `port`: 服务端口，默认: 8090。
- `input`(必须输入): 用于分类的音频文件。
- `topk`: 分类结果的topk。
......@@ -239,13 +250,181 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
```
### 7. 声纹客户端使用方法
#### 7.1 提取声纹特征
注意： 初次使用客户端时响应时间会略长
* 命令行 (推荐使用)
若 `127.0.0.1` 不能访问，则需要使用实际服务 IP 地址
``` bash
paddlespeech_client vector --task spk --server_ip 127.0.0.1 --port 8090 --input 85236145389.wav
```
使用帮助:
``` bash
paddlespeech_client vector --help
```
参数:
* server_ip: 服务端ip地址，默认: 127.0.0.1。
* port: 服务端口，默认: 8090。
* input(必须输入): 用于识别的音频文件。
* task: vector 的任务，可选spk或者score。默认是 spk。
* enroll: 注册音频；。
* test: 测试音频。
输出:
``` bash
[2022-05-25 12:25:36,165] [ INFO] - vector http client start
[2022-05-25 12:25:36,165] [ INFO] - the input audio: 85236145389.wav
[2022-05-25 12:25:36,165] [ INFO] - endpoint: http://127.0.0.1:8790/paddlespeech/vector
[2022-05-25 12:25:36,166] [ INFO] - http://127.0.0.1:8790/paddlespeech/vector
[2022-05-25 12:25:36,324] [ INFO] - The vector: {'success': True, 'code': 200, 'message': {'description': 'success'}, 'result': {'vec': [-1.3251205682754517, 7.860682487487793, -4.620625972747803, 0.3000721037387848, 2.2648534774780273, -1.1931440830230713, 3.064713716506958, 7.673594951629639, -6.004472732543945, -12.024259567260742, -1.9496068954467773, 3.126953601837158, 1.6188379526138306, -7.638310432434082, -1.2299772500991821, -12.33833122253418, 2.1373026371002197, -5.395712375640869, 9.717328071594238, 5.675230503082275, 3.7805123329162598, 3.0597171783447266, 3.429692029953003, 8.9760103225708, 13.174124717712402, -0.5313228368759155, 8.942471504211426, 4.465109825134277, -4.426247596740723, -9.726503372192383, 8.399328231811523, 7.223917484283447, -7.435853958129883, 2.9441683292388916, -4.343039512634277, -13.886964797973633, -1.6346734762191772, -10.902740478515625, -5.311244964599609, 3.800722122192383, 3.897603750228882, -2.123077392578125, -2.3521194458007812, 4.151031017303467, -7.404866695404053, 0.13911646604537964, 2.4626107215881348, 4.96645450592041, 0.9897574186325073, 5.483975410461426, -3.3574001789093018, 10.13400650024414, -0.6120170950889587, -10.403095245361328, 4.600754261016846, 16.009349822998047, -7.78369140625, -4.194530487060547, -6.93686056137085, 1.1789555549621582, 11.490800857543945, 4.23802375793457, 9.550930976867676, 8.375045776367188, 7.508914470672607, -0.6570729613304138, -0.3005157709121704, 2.8406054973602295, 3.0828027725219727, 0.7308170199394226, 6.1483540534973145, 0.1376611888408661, -13.424735069274902, -7.746140480041504, -2.322798252105713, -8.305252075195312, 2.98791241645813, -10.99522876739502, 0.15211068093776703, -2.3820347785949707, -1.7984174489974976, 8.49562931060791, -5.852236747741699, -3.755497932434082, 0.6989710927009583, -5.270299434661865, -2.6188621520996094, -1.8828465938568115, -4.6466498374938965, 14.078543663024902, -0.5495333075523376, 10.579157829284668, -3.216050148010254, 9.349003791809082, -4.381077766418457, -11.675816535949707, -2.863020658493042, 4.5721755027771, 2.246612071990967, -4.574341773986816, 1.8610187768936157, 2.3767874240875244, 5.625787734985352, -9.784077644348145, 0.6496725678443909, -1.457950472831726, 0.4263263940811157, -4.921126365661621, -2.4547839164733887, 3.4869801998138428, -0.4265422224998474, 8.341268539428711, 1.356552004814148, 7.096688270568848, -13.102828979492188, 8.01673412322998, -7.115934371948242, 1.8699780702590942, 0.20872099697589874, 14.699383735656738, -1.0252779722213745, -2.6107232570648193, -2.5082311630249023, 8.427192687988281, 6.913852691650391, -6.29124641418457, 0.6157366037368774, 2.489687919616699, -3.4668266773223877, 9.92176342010498, 11.200815200805664, -0.19664029777050018, 7.491600513458252, -0.6231271624565125, -0.2584814429283142, -9.947997093200684, -0.9611040949821472, 1.1649218797683716, -2.1907122135162354, -1.502848744392395, -0.5192610621452332, 15.165953636169434, 2.4649462699890137, -0.998044490814209, 7.44166374206543, -2.0768048763275146, 3.5896823406219482, -7.305543422698975, -7.562084674835205, 4.32333517074585, 0.08044180274009705, -6.564010143280029, -2.314805269241333, -1.7642345428466797, -2.470881700515747, -7.6756181716918945, -9.548877716064453, -1.017755389213562, 0.1698644608259201, 2.5877134799957275, -1.8752295970916748, -0.36614322662353516, -6.049378395080566, -2.3965611457824707, -5.945338726043701, 0.9424033164978027, -13.155974388122559, -7.45780086517334, 0.14658108353614807, -3.7427968978881836, 5.841492652893066, -1.2872905731201172, 5.569431304931641, 12.570590019226074, 1.0939218997955322, 2.2142086029052734, 1.9181575775146484, 6.991420745849609, -5.888138771057129, 3.1409823894500732, -2.0036280155181885, 2.4434285163879395, 9.973138809204102, 5.036680221557617, 2.005120277404785, 2.861560344696045, 5.860223770141602, 2.917618751525879, -1.63111412525177, 2.0292205810546875, -4.070415019989014, -6.831437110900879]}}
[2022-05-25 12:25:36,324] [ INFO] - Response time 0.159053 s.
```
* Python API
``` python
from paddlespeech.server.bin.paddlespeech_client import VectorClientExecutor
vectorclient_executor = VectorClientExecutor()
res = vectorclient_executor(
input="85236145389.wav",
server_ip="127.0.0.1",
port=8090,
task="spk")
print(res)
```
输出:
``` bash
{'success': True, 'code': 200, 'message': {'description': 'success'}, 'result': {'vec': [-1.3251205682754517, 7.860682487487793, -4.620625972747803, 0.3000721037387848, 2.2648534774780273, -1.1931440830230713, 3.064713716506958, 7.673594951629639, -6.004472732543945, -12.024259567260742, -1.9496068954467773, 3.126953601837158, 1.6188379526138306, -7.638310432434082, -1.2299772500991821, -12.33833122253418, 2.1373026371002197, -5.395712375640869, 9.717328071594238, 5.675230503082275, 3.7805123329162598, 3.0597171783447266, 3.429692029953003, 8.9760103225708, 13.174124717712402, -0.5313228368759155, 8.942471504211426, 4.465109825134277, -4.426247596740723, -9.726503372192383, 8.399328231811523, 7.223917484283447, -7.435853958129883, 2.9441683292388916, -4.343039512634277, -13.886964797973633, -1.6346734762191772, -10.902740478515625, -5.311244964599609, 3.800722122192383, 3.897603750228882, -2.123077392578125, -2.3521194458007812, 4.151031017303467, -7.404866695404053, 0.13911646604537964, 2.4626107215881348, 4.96645450592041, 0.9897574186325073, 5.483975410461426, -3.3574001789093018, 10.13400650024414, -0.6120170950889587, -10.403095245361328, 4.600754261016846, 16.009349822998047, -7.78369140625, -4.194530487060547, -6.93686056137085, 1.1789555549621582, 11.490800857543945, 4.23802375793457, 9.550930976867676, 8.375045776367188, 7.508914470672607, -0.6570729613304138, -0.3005157709121704, 2.8406054973602295, 3.0828027725219727, 0.7308170199394226, 6.1483540534973145, 0.1376611888408661, -13.424735069274902, -7.746140480041504, -2.322798252105713, -8.305252075195312, 2.98791241645813, -10.99522876739502, 0.15211068093776703, -2.3820347785949707, -1.7984174489974976, 8.49562931060791, -5.852236747741699, -3.755497932434082, 0.6989710927009583, -5.270299434661865, -2.6188621520996094, -1.8828465938568115, -4.6466498374938965, 14.078543663024902, -0.5495333075523376, 10.579157829284668, -3.216050148010254, 9.349003791809082, -4.381077766418457, -11.675816535949707, -2.863020658493042, 4.5721755027771, 2.246612071990967, -4.574341773986816, 1.8610187768936157, 2.3767874240875244, 5.625787734985352, -9.784077644348145, 0.6496725678443909, -1.457950472831726, 0.4263263940811157, -4.921126365661621, -2.4547839164733887, 3.4869801998138428, -0.4265422224998474, 8.341268539428711, 1.356552004814148, 7.096688270568848, -13.102828979492188, 8.01673412322998, -7.115934371948242, 1.8699780702590942, 0.20872099697589874, 14.699383735656738, -1.0252779722213745, -2.6107232570648193, -2.5082311630249023, 8.427192687988281, 6.913852691650391, -6.29124641418457, 0.6157366037368774, 2.489687919616699, -3.4668266773223877, 9.92176342010498, 11.200815200805664, -0.19664029777050018, 7.491600513458252, -0.6231271624565125, -0.2584814429283142, -9.947997093200684, -0.9611040949821472, 1.1649218797683716, -2.1907122135162354, -1.502848744392395, -0.5192610621452332, 15.165953636169434, 2.4649462699890137, -0.998044490814209, 7.44166374206543, -2.0768048763275146, 3.5896823406219482, -7.305543422698975, -7.562084674835205, 4.32333517074585, 0.08044180274009705, -6.564010143280029, -2.314805269241333, -1.7642345428466797, -2.470881700515747, -7.6756181716918945, -9.548877716064453, -1.017755389213562, 0.1698644608259201, 2.5877134799957275, -1.8752295970916748, -0.36614322662353516, -6.049378395080566, -2.3965611457824707, -5.945338726043701, 0.9424033164978027, -13.155974388122559, -7.45780086517334, 0.14658108353614807, -3.7427968978881836, 5.841492652893066, -1.2872905731201172, 5.569431304931641, 12.570590019226074, 1.0939218997955322, 2.2142086029052734, 1.9181575775146484, 6.991420745849609, -5.888138771057129, 3.1409823894500732, -2.0036280155181885, 2.4434285163879395, 9.973138809204102, 5.036680221557617, 2.005120277404785, 2.861560344696045, 5.860223770141602, 2.917618751525879, -1.63111412525177, 2.0292205810546875, -4.070415019989014, -6.831437110900879]}}
```
#### 7.2 音频声纹打分
注意： 初次使用客户端时响应时间会略长
* 命令行 (推荐使用)
若 `127.0.0.1` 不能访问，则需要使用实际服务 IP 地址
``` bash
paddlespeech_client vector --task score --server_ip 127.0.0.1 --port 8090 --enroll 85236145389.wav --test 123456789.wav
```
使用帮助:
``` bash
paddlespeech_client vector --help
```
参数:
* server_ip: 服务端ip地址，默认: 127.0.0.1。
* port: 服务端口，默认: 8090。
* input(必须输入): 用于识别的音频文件。
* task: vector 的任务，可选spk或者score。默认是 spk。
* enroll: 注册音频；。
* test: 测试音频。
输出:
``` bash
[2022-05-25 12:33:24,527] [ INFO] - vector score http client start
[2022-05-25 12:33:24,527] [ INFO] - enroll audio: 85236145389.wav, test audio: 123456789.wav
[2022-05-25 12:33:24,528] [ INFO] - endpoint: http://127.0.0.1:8790/paddlespeech/vector/score
[2022-05-25 12:33:24,695] [ INFO] - The vector score is: {'success': True, 'code': 200, 'message': {'description': 'success'}, 'result': {'score': 0.45332613587379456}}
[2022-05-25 12:33:24,696] [ INFO] - The vector: {'success': True, 'code': 200, 'message': {'description': 'success'}, 'result': {'score': 0.45332613587379456}}
[2022-05-25 12:33:24,696] [ INFO] - Response time 0.168271 s.
```
* Python API
``` python
from paddlespeech.server.bin.paddlespeech_client import VectorClientExecutor
vectorclient_executor = VectorClientExecutor()
res = vectorclient_executor(
input=None,
enroll_audio="85236145389.wav",
test_audio="123456789.wav",
server_ip="127.0.0.1",
port=8090,
task="score")
print(res)
```
输出:
``` bash
[2022-05-25 12:30:14,143] [ INFO] - vector score http client start
[2022-05-25 12:30:14,143] [ INFO] - enroll audio: 85236145389.wav, test audio: 123456789.wav
[2022-05-25 12:30:14,143] [ INFO] - endpoint: http://127.0.0.1:8790/paddlespeech/vector/score
[2022-05-25 12:30:14,363] [ INFO] - The vector score is: {'success': True, 'code': 200, 'message': {'description': 'success'}, 'result': {'score': 0.45332613587379456}}
{'success': True, 'code': 200, 'message': {'description': 'success'}, 'result': {'score': 0.45332613587379456}}
```
### 8. 标点预测
**注意：** 初次使用客户端时响应时间会略长
- 命令行 (推荐使用)
若 `127.0.0.1` 不能访问，则需要使用实际服务 IP 地址
``` bash
paddlespeech_client text --server_ip 127.0.0.1 --port 8090 --input "我认为跑步最重要的就是给我带来了身体健康"
```
使用帮助:
```bash
paddlespeech_client text --help
```
参数:
- `server_ip`: 服务端ip地址，默认: 127.0.0.1。
- `port`: 服务端口，默认: 8090。
- `input`(必须输入): 用于标点预测的文本内容。
输出:
```bash
[2022-05-09 18:19:04,397] [ INFO] - The punc text: 我认为跑步最重要的就是给我带来了身体健康。
[2022-05-09 18:19:04,397] [ INFO] - Response time 0.092407 s.
```
- Python API
```python
from paddlespeech.server.bin.paddlespeech_client import TextClientExecutor
textclient_executor = TextClientExecutor()
res = textclient_executor(
input="我认为跑步最重要的就是给我带来了身体健康",
server_ip="127.0.0.1",
port=8090,)
print(res)
```
输出:
```bash
我认为跑步最重要的就是给我带来了身体健康。
```
## 服务支持的模型
### ASR支持的模型
通过 `paddlespeech_server stats --task asr` 获取ASR服务支持的所有模型，其中静态模型可用于 paddle inference 推理。
### ASR 支持的模型
通过 `paddlespeech_server stats --task asr` 获取 ASR 服务支持的所有模型，其中静态模型可用于 paddle inference 推理。
### TTS 支持的模型
通过 `paddlespeech_server stats --task tts` 获取 TTS 服务支持的所有模型，其中静态模型可用于 paddle inference 推理。
### CLS 支持的模型
通过 `paddlespeech_server stats --task cls` 获取 CLS 服务支持的所有模型，其中静态模型可用于 paddle inference 推理。
### TTS支持的模型
通过 `paddlespeech_server stats --task tts` 获取TTS服务支持的所有模型，其中静态模型可用于 paddle inference 推理。
### Vector 支持的模型
通过 `paddlespeech_server stats --task vector` 获取 Vector 服务支持的所有模型。
### CLS支持的模型
通过 `paddlespeech_server stats --task cls` 获取CLS服务支持的所有模型，其中静态模型可用于 paddle inference 推理。
### Text支持的模型
通过 `paddlespeech_server stats --task text` 获取 Text 服务支持的所有模型。
demos/speech_server/asr_client.sh
浏览文件 @ 0550d092
#!/bin/bash
wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespeech.bj.bcebos.com/PaddleAudio/en.wav
# If `127.0.0.1` is not accessible, you need to use the actual service IP address.
paddlespeech_client asr --server_ip 127.0.0.1 --port 8090 --input ./zh.wav
demos/speech_server/cls_client.sh
浏览文件 @ 0550d092
#!/bin/bash
wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespeech.bj.bcebos.com/PaddleAudio/en.wav
# If `127.0.0.1` is not accessible, you need to use the actual service IP address.
paddlespeech_client cls --server_ip 127.0.0.1 --port 8090 --input ./zh.wav --topk 1
demos/speech_server/conf/application.yaml
浏览文件 @ 0550d092
# This is the parameter configuration file for PaddleSpeech Serving.
# This is the parameter configuration file for PaddleSpeech Offline Serving.
#################################################################################
# SERVER SETTING #
#################################################################################
host: 127.0.0.1
host: 0.0.0.0
port: 8090
# The task format in the engin_list is: <speech task>_<engine type>
# task choices = ['asr_python', 'asr_inference', 'tts_python', 'tts_inference']
engine_list: ['asr_python', 'tts_python', 'cls_python']
# task choices = ['asr_python', 'asr_inference', 'tts_python', 'tts_inference', 'cls_python', 'cls_inference']
protocol: 'http'
engine_list: ['asr_python', 'tts_python', 'cls_python', 'text_python', 'vector_python']
#################################################################################
......@@ -135,3 +135,26 @@ cls_inference:
glog_info: False # True -> print glog
summary: True # False -> do not show predictor config
################################### Text #########################################
################### text task: punc; engine_type: python #######################
text_python:
task: punc
model_type: 'ernie_linear_p3_wudao'
lang: 'zh'
sample_rate: 16000
cfg_path: # [optional]
ckpt_path: # [optional]
vocab_file: # [optional]
device: # set 'gpu:id' or 'cpu'
################################### Vector ######################################
################### Vector task: spk; engine_type: python #######################
vector_python:
task: spk
model_type: 'ecapatdnn_voxceleb12'
sample_rate: 16000
cfg_path: # [optional]
ckpt_path: # [optional]
device: # set 'gpu:id' or 'cpu'
paddlespeech/server/bin/main.py → demos/speech_server/start_multi_progress_server.py
浏览文件 @ 0550d092
......@@ -12,66 +12,59 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import argparse
import warnings
import uvicorn
from fastapi import FastAPI
from starlette.middleware.cors import CORSMiddleware
from paddlespeech.server.engine.engine_pool import init_engine_pool
from paddlespeech.server.restful.api import setup_router as setup_http_router
from paddlespeech.server.utils.config import get_config
from paddlespeech.server.ws.api import setup_router as setup_ws_router
warnings.filterwarnings("ignore")
import sys
app = FastAPI(
title="PaddleSpeech Serving API", description="Api", version="0.0.1")
def init(config):
"""system initialization
Args:
config (CfgNode): config object
Returns:
bool:
"""
# init api
api_list = list(engine.split("_")[0] for engine in config.engine_list)
if config.protocol == "websocket":
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"])
# change yaml file here
config_file = "./conf/application.yaml"
config = get_config(config_file)
# init engine
if not init_engine_pool(config):
print("Failed to init engine.")
sys.exit(-1)
# get api_router
api_list = list(engine.split("_")[0] for engine in config.engine_list)
if config.protocol == "websocket":
api_router = setup_ws_router(api_list)
elif config.protocol == "http":
elif config.protocol == "http":
api_router = setup_http_router(api_list)
else:
else:
raise Exception("unsupported protocol")
app.include_router(api_router)
if not init_engine_pool(config):
return False
return True
def main(args):
"""main function"""
config = get_config(args.config_file)
if init(config):
uvicorn.run(app, host=config.host, port=config.port, debug=True)
sys.exit(-1)
# app needs to operate outside the main function
app.include_router(api_router)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"--config_file",
action="store",
help="yaml file of the app",
default="./conf/application.yaml")
parser = argparse.ArgumentParser(add_help=True)
parser.add_argument(
"--log_file",
action="store",
help="log file",
default="./log/paddlespeech.log")
"--workers", type=int, help="workers of server", default=1)
args = parser.parse_args()
main(args)
uvicorn.run(
"start_multi_progress_server:app",
host=config.host,
port=config.port,
debug=True,
workers=args.workers)
demos/speech_server/tts_client.sh
浏览文件 @ 0550d092
#!/bin/bash
# If `127.0.0.1` is not accessible, you need to use the actual service IP address.
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
demos/speech_translation/README.md
浏览文件 @ 0550d092
......@@ -47,7 +47,7 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
- Python API
```python
import paddle
from paddlespeech.cli import STExecutor
from paddlespeech.cli.st import STExecutor
st_executor = STExecutor()
text = st_executor(
......
demos/speech_translation/README_cn.md
浏览文件 @ 0550d092
......@@ -47,7 +47,7 @@ wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespee
- Python API
```python
import paddle
from paddlespeech.cli import STExecutor
from paddlespeech.cli.st import STExecutor
st_executor = STExecutor()
text = st_executor(
......
paddlespeech/server/conf/ws_application.yaml → demos/streaming_asr_server/conf/application.yaml
浏览文件 @ 0550d092
......@@ -7,8 +7,8 @@ host: 0.0.0.0
port: 8090
# The task format in the engin_list is: <speech task>_<engine type>
# task choices = ['asr_online', 'tts_online']
# protocol = ['websocket', 'http'] (only one can be selected).
# task choices = ['asr_online']
# protocol = ['websocket'] (only one can be selected).
# websocket only support online engine type.
protocol: 'websocket'
engine_list: ['asr_online']
......@@ -21,7 +21,7 @@ engine_list: ['asr_online']
################################### ASR #########################################
################### speech task: asr; engine_type: online #######################
asr_online:
model_type: 'deepspeech2online_aishell'
model_type: 'conformer_online_wenetspeech'
am_model: # the pdmodel file of am static model [optional]
am_params: # the pdiparams file of am static model [optional]
lang: 'zh'
......@@ -29,6 +29,9 @@ asr_online:
cfg_path:
decode_method:
force_yes: True
device: 'cpu' # cpu or gpu:id
decode_method: "attention_rescoring"
continuous_decoding: True # enable continue decoding when endpoint detected
am_predictor_conf:
device: # set 'gpu:id' or 'cpu'
......@@ -37,11 +40,9 @@ asr_online:
summary: True # False -> do not show predictor config
chunk_buffer_conf:
frame_duration_ms: 80
shift_ms: 40
sample_rate: 16000
sample_width: 2
window_n: 7 # frame
shift_n: 4 # frame
window_ms: 20 # ms
window_ms: 25 # ms
shift_ms: 10 # ms
sample_rate: 16000
sample_width: 2
demos/streaming_asr_server/conf/punc_application.yaml 0 → 100644
浏览文件 @ 0550d092
# This is the parameter configuration file for PaddleSpeech Serving.
#################################################################################
# SERVER SETTING #
#################################################################################
host: 0.0.0.0
port: 8190
# The task format in the engin_list is: <speech task>_<engine type>
# task choices = ['asr_python']
# protocol = ['http'] (only one can be selected).
# http only support offline engine type.
protocol: 'http'
engine_list: ['text_python']
#################################################################################
# ENGINE CONFIG #
#################################################################################
################################### Text #########################################
################### text task: punc; engine_type: python #######################
text_python:
task: punc
model_type: 'ernie_linear_p3_wudao'
lang: 'zh'
sample_rate: 16000
cfg_path: # [optional]
ckpt_path: # [optional]
vocab_file: # [optional]
device: 'cpu' # set 'gpu:id' or 'cpu'
demos/streaming_asr_server/conf/ws_conformer_application.yaml
浏览文件 @ 0550d092
......@@ -4,11 +4,11 @@
# SERVER SETTING #
#################################################################################
host: 0.0.0.0
port: 8090
port: 8091
# The task format in the engin_list is: <speech task>_<engine type>
# task choices = ['asr_online', 'tts_online']
# protocol = ['websocket', 'http'] (only one can be selected).
# task choices = ['asr_online']
# protocol = ['websocket'] (only one can be selected).
# websocket only support online engine type.
protocol: 'websocket'
engine_list: ['asr_online']
......@@ -28,8 +28,12 @@ asr_online:
sample_rate: 16000
cfg_path:
decode_method:
num_decoding_left_chunks: -1
force_yes: True
device: # cpu or gpu:id
device: 'cpu' # cpu or gpu:id
decode_method: "attention_rescoring"
continuous_decoding: True # enable continue decoding when endpoint detected
am_predictor_conf:
device: # set 'gpu:id' or 'cpu'
switch_ir_optim: True
......
demos/streaming_asr_server/conf/ws_conformer_wenetspeech_application.yaml 0 → 100644
浏览文件 @ 0550d092
# This is the parameter configuration file for PaddleSpeech Serving.
#################################################################################
# SERVER SETTING #
#################################################################################
host: 0.0.0.0
port: 8090
# The task format in the engin_list is: <speech task>_<engine type>
# task choices = ['asr_online']
# protocol = ['websocket'] (only one can be selected).
# websocket only support online engine type.
protocol: 'websocket'
engine_list: ['asr_online']
#################################################################################
# ENGINE CONFIG #
#################################################################################
################################### ASR #########################################
################### speech task: asr; engine_type: online #######################
asr_online:
model_type: 'conformer_online_wenetspeech'
am_model: # the pdmodel file of am static model [optional]
am_params: # the pdiparams file of am static model [optional]
lang: 'zh'
sample_rate: 16000
cfg_path:
decode_method:
force_yes: True
device: 'cpu' # cpu or gpu:id
decode_method: "attention_rescoring"
continuous_decoding: True # enable continue decoding when endpoint detected
num_decoding_left_chunks: -1
am_predictor_conf:
device: # set 'gpu:id' or 'cpu'
switch_ir_optim: True
glog_info: False # True -> print glog
summary: True # False -> do not show predictor config
chunk_buffer_conf:
window_n: 7 # frame
shift_n: 4 # frame
window_ms: 25 # ms
shift_ms: 10 # ms
sample_rate: 16000
sample_width: 2
demos/streaming_asr_server/conf/ws_conformer_wenetspeech_application_faster.yaml 0 → 100644
浏览文件 @ 0550d092
# This is the parameter configuration file for PaddleSpeech Serving.
#################################################################################
# SERVER SETTING #
#################################################################################
host: 0.0.0.0
port: 8090
# The task format in the engin_list is: <speech task>_<engine type>
# task choices = ['asr_online']
# protocol = ['websocket'] (only one can be selected).
# websocket only support online engine type.
protocol: 'websocket'
engine_list: ['asr_online']
#################################################################################
# ENGINE CONFIG #
#################################################################################
################################### ASR #########################################
################### speech task: asr; engine_type: online #######################
asr_online:
model_type: 'conformer_online_wenetspeech'
am_model: # the pdmodel file of am static model [optional]
am_params: # the pdiparams file of am static model [optional]
lang: 'zh'
sample_rate: 16000
cfg_path:
decode_method:
force_yes: True
device: 'cpu' # cpu or gpu:id
decode_method: "attention_rescoring"
continuous_decoding: True # enable continue decoding when endpoint detected
num_decoding_left_chunks: 16
am_predictor_conf:
device: # set 'gpu:id' or 'cpu'
switch_ir_optim: True
glog_info: False # True -> print glog
summary: True # False -> do not show predictor config
chunk_buffer_conf:
window_n: 7 # frame
shift_n: 4 # frame
window_ms: 25 # ms
shift_ms: 10 # ms
sample_rate: 16000
sample_width: 2
demos/streaming_asr_server/conf/ws_ds2_application.yaml 0 → 100644
浏览文件 @ 0550d092
# This is the parameter configuration file for PaddleSpeech Serving.
#################################################################################
# SERVER SETTING #
#################################################################################
host: 0.0.0.0
port: 8090
# The task format in the engin_list is: <speech task>_<engine type>
# task choices = ['asr_online-inference', 'asr_online-onnx']
# protocol = ['websocket'] (only one can be selected).
# websocket only support online engine type.
protocol: 'websocket'
engine_list: ['asr_online-onnx']
#################################################################################
# ENGINE CONFIG #
#################################################################################
################################### ASR #########################################
################### speech task: asr; engine_type: online-inference #######################
asr_online-inference:
model_type: 'deepspeech2online_wenetspeech'
am_model: # the pdmodel file of am static model [optional]
am_params: # the pdiparams file of am static model [optional]
lang: 'zh'
sample_rate: 16000
cfg_path:
decode_method:
num_decoding_left_chunks:
force_yes: True
device: 'cpu' # cpu or gpu:id
am_predictor_conf:
device: # set 'gpu:id' or 'cpu'
switch_ir_optim: True
glog_info: False # True -> print glog
summary: True # False -> do not show predictor config
chunk_buffer_conf:
frame_duration_ms: 85
shift_ms: 40
sample_rate: 16000
sample_width: 2
window_n: 7 # frame
shift_n: 4 # frame
window_ms: 25 # ms
shift_ms: 10 # ms
################################### ASR #########################################
################### speech task: asr; engine_type: online-onnx #######################
asr_online-onnx:
model_type: 'deepspeech2online_wenetspeech'
am_model: # the pdmodel file of onnx am static model [optional]
am_params: # the pdiparams file of am static model [optional]
lang: 'zh'
sample_rate: 16000
cfg_path:
decode_method:
num_decoding_left_chunks:
force_yes: True
device: 'cpu' # cpu or gpu:id
# https://onnxruntime.ai/docs/api/python/api_summary.html#inferencesession
am_predictor_conf:
device: 'cpu' # set 'gpu:id' or 'cpu'
graph_optimization_level: 0
intra_op_num_threads: 0 # Sets the number of threads used to parallelize the execution within nodes.
inter_op_num_threads: 0 # Sets the number of threads used to parallelize the execution of the graph (across nodes).
log_severity_level: 2 # Log severity level. Applies to session load, initialization, etc. 0:Verbose, 1:Info, 2:Warning. 3:Error, 4:Fatal. Default is 2.
log_verbosity_level: 0 # VLOG level if DEBUG build and session_log_severity_level is 0. Applies to session load, initialization, etc. Default is 0.
chunk_buffer_conf:
frame_duration_ms: 80
shift_ms: 40
sample_rate: 16000
sample_width: 2
window_n: 7 # frame
shift_n: 4 # frame
window_ms: 25 # ms
shift_ms: 10 # ms
demos/streaming_asr_server/local/rtf_from_log.py 0 → 100755
浏览文件 @ 0550d092
#!/usr/bin/env python3
import argparse
if __name__ == '__main__':
parser = argparse.ArgumentParser(prog=__doc__)
parser.add_argument(
'--logfile', type=str, required=True, help='ws client log file')
args = parser.parse_args()
rtfs = []
with open(args.logfile, 'r') as f:
for line in f:
if 'RTF=' in line:
# udio duration: 6.126, elapsed time: 3.471978187561035, RTF=0.5667610492264177
line = line.strip()
beg = line.index("audio")
line = line[beg:]
items = line.split(',')
vals = []
for elem in items:
if "RTF=" in elem:
continue
_, val = elem.split(":")
vals.append(eval(val))
keys = ['T', 'P']
meta = dict(zip(keys, vals))
rtfs.append(meta)
T = 0.0
P = 0.0
n = 0
for m in rtfs:
n += 1
T += m['T']
P += m['P']
print(f"RTF: {P/T}, utts: {n}")
demos/streaming_asr_server/local/test.sh 0 → 100755
浏览文件 @ 0550d092
#!/bin/bash
if [ $# != 1 ];then
echo "usage: $0 wav_scp"
exit -1
fi
scp=$1
# calc RTF
# wav_scp can generate from `speechx/examples/ds2_ol/aishell`
exp=exp
mkdir -p $exp
python3 local/websocket_client.py --server_ip 127.0.0.1 --port 8090 --wavscp $scp &> $exp/log.rsl
python3 local/rtf_from_log.py --logfile $exp/log.rsl
\ No newline at end of file
demos/streaming_asr_server/websocket_client.py → demos/streaming_asr_server/local/websocket_client.py
浏览文件 @ 0550d092
#!/usr/bin/python
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
......@@ -11,8 +12,9 @@
# 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.
#!/usr/bin/python
# -*- coding: UTF-8 -*-
# calc avg RTF(NOT Accurate): grep -rn RTF log.txt | awk '{print $NF}' | awk -F "=" '{sum += $NF} END {print "all time",sum, "audio num", NR, "RTF", sum/NR}'
# python3 websocket_client.py --server_ip 127.0.0.1 --port 8290 --punc.server_ip 127.0.0.1 --punc.port 8190 --wavfile ./zh.wav
# python3 websocket_client.py --server_ip 127.0.0.1 --port 8290 --wavfile ./zh.wav
import argparse
import asyncio
import codecs
......@@ -28,6 +30,7 @@ def main(args):
handler = ASRWsAudioHandler(
args.server_ip,
args.port,
endpoint=args.endpoint,
punc_server_ip=args.punc_server_ip,
punc_server_port=args.punc_server_port)
loop = asyncio.get_event_loop()
......@@ -69,7 +72,11 @@ if __name__ == "__main__":
default=8091,
dest="punc_server_port",
help='Punctuation server port')
parser.add_argument(
"--endpoint",
type=str,
default="/paddlespeech/asr/streaming",
help="ASR websocket endpoint")
parser.add_argument(
"--wavfile",
action="store",
......
demos/streaming_asr_server/punc_server.py 0 → 100644
浏览文件 @ 0550d092
# 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.
import argparse
from paddlespeech.cli.log import logger
from paddlespeech.server.bin.paddlespeech_server import ServerExecutor
if __name__ == "__main__":
parser = argparse.ArgumentParser(
prog='paddlespeech_server.start', add_help=True)
parser.add_argument(
"--config_file",
action="store",
help="yaml file of the app",
default=None,
required=True)
parser.add_argument(
"--log_file",
action="store",
help="log file",
default="./log/paddlespeech.log")
logger.info("start to parse the args")
args = parser.parse_args()
logger.info("start to launch the punctuation server")
punc_server = ServerExecutor()
punc_server(config_file=args.config_file, log_file=args.log_file)
demos/streaming_asr_server/server.sh 0 → 100755
浏览文件 @ 0550d092
export CUDA_VISIBLE_DEVICE=0,1,2,3
export CUDA_VISIBLE_DEVICE=0,1,2,3
# nohup python3 punc_server.py --config_file conf/punc_application.yaml > punc.log 2>&1 &
paddlespeech_server start --config_file conf/punc_application.yaml &> punc.log &
# nohup python3 streaming_asr_server.py --config_file conf/ws_conformer_wenetspeech_application.yaml > streaming_asr.log 2>&1 &
paddlespeech_server start --config_file conf/ws_conformer_wenetspeech_application.yaml &> streaming_asr.log &
demos/streaming_asr_server/streaming_asr_server.py 0 → 100644
浏览文件 @ 0550d092
此差异已折叠。
demos/streaming_asr_server/test.sh 100644 → 100755
浏览文件 @ 0550d092
# download the test wav
wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav
# read the wav and pass it to service
python3 websocket_client.py --wavfile ./zh.wav
# read the wav and pass it to only streaming asr service
# If `127.0.0.1` is not accessible, you need to use the actual service IP address.
paddlespeech_client asr_online --server_ip 127.0.0.1 --port 8090 --input ./zh.wav
# read the wav and call streaming and punc service
# If `127.0.0.1` is not accessible, you need to use the actual service IP address.
paddlespeech_client asr_online --server_ip 127.0.0.1 --port 8290 --punc.server_ip 127.0.0.1 --punc.port 8190 --input ./zh.wav
demos/streaming_asr_server/web/templates/index.html
浏览文件 @ 0550d092
......@@ -93,6 +93,7 @@
function parseResult(data) {
var data = JSON.parse(data)
console.log('result json:', data)
var result = data.result
console.log(result)
$("#resultPanel").html(result)
......
demos/streaming_tts_server/test_client.sh
浏览文件 @ 0550d092
#!/bin/bash
# http client test
# If `127.0.0.1` is not accessible, you need to use the actual service IP address.
paddlespeech_client tts_online --server_ip 127.0.0.1 --port 8092 --protocol http --input "您好，欢迎使用百度飞桨语音合成服务。" --output output.wav
# websocket client test
#paddlespeech_client tts_online --server_ip 127.0.0.1 --port 8092 --protocol websocket --input "您好，欢迎使用百度飞桨语音合成服务。" --output output.wav
# If `127.0.0.1` is not accessible, you need to use the actual service IP address.
# paddlespeech_client tts_online --server_ip 127.0.0.1 --port 8092 --protocol websocket --input "您好，欢迎使用百度飞桨语音合成服务。" --output output.wav
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