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ASR (Automatic Speech Recognition)

Introduction

ASR, or Automatic Speech Recognition, refers to the problem of getting a program to automatically transcribe spoken language (speech-to-text).

This demo is an implementation to recognize text from a specific audio file. It can be done by a single command or a few lines in python using PaddleSpeech.

Usage

1. Installation

see installation.

You can choose one way from easy, meduim and hard to install paddlespeech.

2. Prepare Input File

The input of this demo should be a WAV file(.wav), and the sample rate must be the same as the model.

Here are sample files for this demo that can be downloaded:

wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespeech.bj.bcebos.com/PaddleAudio/en.wav https://paddlespeech.bj.bcebos.com/PaddleAudio/ch_zh_mix.wav

3. Usage

Command Line(Recommended)
```
# Chinese
paddlespeech asr --input ./zh.wav -v
# English
paddlespeech asr --model transformer_librispeech --lang en --input ./en.wav -v
# Code-Switch
paddlespeech asr --model conformer_talcs --lang zh_en --codeswitch True --input ./ch_zh_mix.wav -v 
# Chinese ASR + Punctuation Restoration
paddlespeech asr --input ./zh.wav -v | paddlespeech text --task punc -v
```
(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:
```
paddlespeech asr --help
```
Arguments:
- input(required): Audio file to recognize.
- model: Model type of asr task. Default: conformer_wenetspeech.
- lang: Model language. Default: zh.
- codeswitch: Code Swith Model. Default: False
- sample_rate: Sample rate of the model. Default: 16000.
- config: Config of asr task. Use pretrained model when it is None. Default: None.
- 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:
```
# Chinese
[2021-12-08 13:12:34,063] [    INFO] [utils.py] [L225] - ASR Result: 我认为跑步最重要的就是给我带来了身体健康
# English
[2022-01-12 11:51:10,815] [    INFO] - ASR Result: i knocked at the door on the ancient side of the building
```

Python API

import paddle
from paddlespeech.cli.asr import ASRExecutor

asr_executor = ASRExecutor()
text = asr_executor(
    model='conformer_wenetspeech',
    lang='zh',
    sample_rate=16000,
    config=None,  # Set `config` and `ckpt_path` to None to use pretrained model.
    ckpt_path=None,
    audio_file='./zh.wav',
    force_yes=False,
    device=paddle.get_device())
print('ASR Result: \n{}'.format(text))

Output:

ASR Result:
我认为跑步最重要的就是给我带来了身体健康

4.Pretrained Models

Here is a list of pretrained models released by PaddleSpeech that can be used by command and python API:

Model	Code Switch	Language	Sample Rate
conformer_wenetspeech	False	zh	16k
conformer_online_multicn	False	zh	16k
conformer_aishell	False	zh	16k
conformer_online_aishell	False	zh	16k
transformer_librispeech	False	en	16k
deepspeech2online_wenetspeech	False	zh	16k
deepspeech2offline_aishell	False	zh	16k
deepspeech2online_aishell	False	zh	16k
deepspeech2offline_librispeech	False	en	16k
conformer_talcs	True	zh_en	16k

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