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([简体中文](./PPASR_cn.md)|English)
# PP-ASR
## Catalogue
- [1. Introduction](#1)
- [2. Characteristic](#2)
- [3. Tutorials](#3)
- [3.1 Pre-trained Models](#31)
- [3.2 Training](#32)
- [3.3 Inference](#33)
- [3.4 Service Deployment](#33)
- [3.5 Customized Auto Speech Recognition and Deployment](#33)
- [4. Quick Start](#4)
<a name="1"></a>
## 1. Introduction
PP-ASR is a tool to provide ASR(Automatic speech recognition) function. It provides a variety of Chinese and English models and supports model training. It also supports model inference using the command line. In addition, PP-ASR supports the deployment of streaming models and customized ASR.
<a name="2"></a>
## 2. Characteristic
The basic process of ASR is shown in the figure below:
<center><img src=https://user-images.githubusercontent.com/87408988/168259962-cbe2008b-47b6-443d-9566-d77a5ca2eb25.png width="800" ></center>
The main characteristics of PP-ASR are shown below:
- Provides pre-trained models on Chinese/English open source datasets: aishell(Chinese), wenetspeech(Chinese) and librispeech(English). The models include deepspeech2 and conformer/transformer.
- Support model training on Chinese/English datasets.
- Support model inference using the command line. You can use to use `paddlespeech asr --model xxx --input xxx.wav` to use the pre-trained model to do model inference.
- Support deployment of streaming ASR server. Besides ASR function, the server supports timestamp function.
- Support customized auto speech recognition and deployment.
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## 3. Tutorials
<a name="31"></a>
## 3.1 Pre-trained Models
The support pre-trained model list: [released_model](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/docs/source/released_model.md).
The model with good effect are Ds2 Online Wenetspeech ASR0 Model and Conformer Online Wenetspeech ASR1 Model. Both two models support streaming ASR.
For more information about model design, you can refer to the aistudio tutorial:
- [Deepspeech2](https://aistudio.baidu.com/aistudio/projectdetail/3866807)
- [Transformer](https://aistudio.baidu.com/aistudio/projectdetail/3470110)
<a name="32"></a>
## 3.2 Training
The referenced script for model training is stored in [examples](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples) and stored according to "examples/dataset/model". The dataset mainly supports aishell and librispeech. The model supports deepspeech2 and u2(conformer/transformer).
The specific steps of executing the script are recorded in `run.sh`.
For more information, you can refer to [asr1](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/aishell/asr1)
<a name="33"></a>
## 3.3 Inference
PP-ASR supports use `paddlespeech asr --model xxx --input xxx.wav` to use the pre-trained model to do model inference after install `paddlespeech` by `pip install paddlespeech`.
Specific supported functions include:
- Prediction of single audio
- Use the pipe to predict multiple audio
- Support RTF calculation
For specific usage, please refer to: [speech_recognition](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/demos/speech_recognition/README_cn.md)
<a name="34"></a>
## 3.4 Service Deployment
PP-ASR supports the service deployment of streaming ASR. Support the simultaneous use of speech recognition and punctuation processing.
Demo of ASR Server: [streaming_asr_server](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/demos/streaming_asr_server)
![image](https://user-images.githubusercontent.com/87408988/168255342-1fc790c0-16f4-4540-a861-db239076727c.png)
Display of using ASR server on Web page: [streaming_asr_demo_video](https://paddlespeech.readthedocs.io/en/latest/streaming_asr_demo_video.html)
For more information about service deployment, you can refer to the aistudio tutorial:
- [Streaming service - model part](https://aistudio.baidu.com/aistudio/projectdetail/3839884)
- [Streaming service](https://aistudio.baidu.com/aistudio/projectdetail/4017905)
<a name="35"></a>
## 3.5 Customized Auto Speech Recognition and Deployment
For customized auto speech recognition and deployment, PP-ASR provides feature extraction(fbank) => Inference modelScoring Library=> C++ program of TLGWFST, token, lexion, grammer). For specific usage, please refer to: [speechx](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/speechx)
If you want to quickly use it, you can refer to [custom_streaming_asr](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/demos/custom_streaming_asr/README_cn.md)
For more information about customized auto speech recognition and deployment, you can refer to the aistudio tutorial:
- [Customized Auto Speech Recognition](https://aistudio.baidu.com/aistudio/projectdetail/4021561)
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## 4. Quick Start
To use PP-ASR, you can see here [install](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/docs/source/install_cn.md), It supplies three methods to install `paddlespeech`, which are **Easy**, **Medium** and **Hard**. If you want to experience the inference function of paddlespeech, you can use **Easy** installation method.

@ -1,3 +1,6 @@
(简体中文|[English](./PPASR.md))
# PP-ASR
## 目录
- [1. 简介](#1)
- [2. 特点](#2)
@ -12,7 +15,7 @@
<a name="1"></a>
## 1. 简介
PP-ASR 是一个 提供 ASR 功能的工具。其提供了多种中文和英文的模型,支持模型的训练,并且支持使用命令行的方式进行模型的推理。 PP-ASR也支持流式模型的部署以及个性化场景的部署。
PP-ASR 是一个 提供 ASR 功能的工具。其提供了多种中文和英文的模型,支持模型的训练,并且支持使用命令行的方式进行模型的推理。 PP-ASR 也支持流式模型的部署,以及个性化场景的部署。
<a name="2"></a>
## 2. 特点
@ -23,7 +26,7 @@ PP-ASR 是一个 提供 ASR 功能的工具。其提供了多种中文和英文
PP-ASR 的主要特点如下:
- 提供在中/英文开源数据集 aishell 中文wenetspeech中文librispeech (英文)上的预训练模型。模型包含 deepspeech2 模型以及 conformer/transformer 模型。
- 支持中/英文的模型训练功能。
- 支持命令行方式的模型推理, `paddlespeech asr --input xxx.wav` 方式调用各个预训练模型进行推理。
- 支持命令行方式的模型推理,可使用 `paddlespeech asr --model xxx --input xxx.wav` 方式调用各个预训练模型进行推理。
- 支持流式 ASR 的服务部署,也支持输出时间戳。
- 支持个性化场景的部署。
@ -32,21 +35,23 @@ PP-ASR 的主要特点如下:
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## 3.1 预训练模型
支持的预训练模型列表:[released_model.md](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/docs/source/released_model.md)。
支持的预训练模型列表:[released_model](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/docs/source/released_model.md)。
其中效果较好的模型为 Ds2 Online Wenetspeech ASR0 Model 以及 Conformer Online Wenetspeech ASR1 Model。 两个模型都支持流式 ASR。
更多关于模型设计的部分,可以参考 AIStudio 教程:
- [Deepspeech2](https://aistudio.baidu.com/aistudio/projectdetail/3866807)
- [Transformer](https://aistudio.baidu.com/aistudio/projectdetail/3470110)
<a name="32"></a>
## 3.2 模型训练
模型的训练的参考脚本存放在 examples 中,并按照 `examples/数据集/模型` 存放,数据集主要支持 aishell 和 librispeech模型支持 deepspeech2 模型和 u2 (conformer/transformer) 模型。
具体的执行脚本的步骤记录在 run.sh 当中。具体可参考[这里](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/aishell/asr1)
模型的训练的参考脚本存放在 [examples](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples) 中,并按照 `examples/数据集/模型` 存放,数据集主要支持 aishell 和 librispeech模型支持 deepspeech2 模型和 u2 (conformer/transformer) 模型。
具体的执行脚本的步骤记录在 `run.sh` 当中。具体可参考: [asr1](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/aishell/asr1)
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## 3.3 模型推理
PPASR 支持在使用`pip install paddlespeech`后 使用命令行的方式来使用预训练模型进行推理。
PP-ASR 支持在使用`pip install paddlespeech`后 使用命令行的方式来使用预训练模型进行推理。
具体支持的功能包括:
@ -54,26 +59,38 @@ PPASR 支持在使用`pip install paddlespeech`后 使用命令行的方式来
- 使用管道的方式对多条音频进行预测
- 支持 RTF 的计算
具体的使用方式可以参考[这里](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/demos/speech_recognition/README_cn.md)
具体的使用方式可以参考 [speech_recognition](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/demos/speech_recognition/README_cn.md)
<a name="34"></a>
## 3.4 服务部署
PPASR 支持流式ASR的服务部署。支持 语音识别 + 标点处理两个功能同时使用。
PP-ASR 支持流式ASR的服务部署。支持 语音识别 + 标点处理两个功能同时使用。
server 的 demo [链接](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/demos/streaming_asr_server)
server 的 demo [streaming_asr_server](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/demos/streaming_asr_server)
![image](https://user-images.githubusercontent.com/87408988/168255342-1fc790c0-16f4-4540-a861-db239076727c.png)
网页上使用 asr server 的效果展示:[streaming_asr_demo_video](https://paddlespeech.readthedocs.io/en/latest/streaming_asr_demo_video.html)
关于服务部署方面的更多资料,可以参考 AIStudio 教程:
- [流式服务-模型部分](https://aistudio.baidu.com/aistudio/projectdetail/3839884)
- [流式服务](https://aistudio.baidu.com/aistudio/projectdetail/4017905)
<a name="35"></a>
## 3.5 支持个性化场景部署
针对个性化场景部署,提供了 特征提取fbank => 推理模型(打分库)=> TLGWFST token, lexion, grammer的 C++ 程序。具体参考[这里](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/speechx)
针对个性化场景部署提供了特征提取fbank => 推理模型(打分库)=> TLGWFST token, lexion, grammer的 C++ 程序。具体参考 [speechx](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/speechx)。
如果想快速了解和使用,可以参考: [custom_streaming_asr](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/demos/custom_streaming_asr/README_cn.md)
关于支持个性化场景部署的更多资料,可以参考 AIStudio 教程:
- [定制化识别](https://aistudio.baidu.com/aistudio/projectdetail/4021561)
<a name="4"></a>
## 4. 快速开始
关于如果使用 PPASR可以看这里的[安装文档](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/docs/source/install_cn.md),其中提供了 **简单**、**中等**、**困难** 三种安装方式。如果想体验paddlespeech 的推理功能,可以用 **简单** 安装方式。
关于如果使用 PP-ASR可以看这里的 [install](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/docs/source/install_cn.md),其中提供了 **简单**、**中等**、**困难** 三种安装方式。如果想体验 paddlespeech 的推理功能,可以用 **简单** 安装方式。

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