You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
PaddleSpeech/demos/speech_recognition/README.md

76 lines
2.3 KiB

([简体中文](./README_cn.md)|English)
3 years ago
# 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).
3 years ago
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
```bash
pip install paddlespeech
```
### 2. Prepare Input File
The input of this demo should be a WAV file(`.wav`), and the sample rate must be the same as the model.
Here are sample files for this demo that can be downloaded:
```bash
wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav https://paddlespeech.bj.bcebos.com/PaddleAudio/en.wav
```
### 3. Usage
- Command Line(Recommended)
```bash
paddlespeech asr --input ./zh.wav
```
Usage:
```bash
paddlespeech asr --help
```
Arguments:
- `input`(required): Audio file to recognize.
- `model`: Model type of asr task. Default: `conformer_wenetspeech`.
- `lang`: Model language. Default: `zh`.
3 years ago
- `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`.
- `device`: Choose device to execute model inference. Default: default device of paddlepaddle in current environment.
Output:
```bash
[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
```
- Python API
```python
import paddle
from paddlespeech.cli 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',
device=paddle.get_device())
print('ASR Result: \n{}'.format(text))
```
Output:
```bash
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 | Language | Sample Rate
| :--- | :---: | :---: |
| conformer_wenetspeech| zh| 16000