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PaddleSpeech/demos/whisper/README.md

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([简体中文](./README_cn.md)|English)
## Introduction
Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition as well as speech translation and language identification.
Whisper model trained by OpenAI whisper https://github.com/openai/whisper
## Usage
### 1. Installation
see [installation](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/docs/source/install.md).
You can choose one way from easy, meduim and hard to install paddlespeech.
### 2. Prepare Input File
The input of this demo should be a WAV file(`.wav`), and the sample rate must be the same as the model.
Here are sample files for this demo that can be downloaded:
```bash
wget -c https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav
```
### 3. Usage
- Command Line(Recommended)
```bash
# to recognize text
paddlespeech whisper --task transcribe --input ./zh.wav
# to change model English-Only base size model
paddlespeech whisper --lang en --size base --task transcribe --input ./en.wav
# to recognize text and translate to English
paddlespeech whisper --task translate --input ./zh.wav
```
Usage:
```bash
paddlespeech whisper --help
```
Arguments:
- `input`(required): Audio file to recognize.
- `model`: Model type of asr task. Default: `whisper-large`.
- `task`: Output type. Default: `transcribe`.
- `lang`: Model language. Default: ``. Use `en` to choice English-only model. Now [medium,base,small,tiny] size can support English-only.
- `size`: Model size for decode. Defalut: `large`. Now can support [large,medium,base,small,tiny].
- `language`: Set decode language. Default: `None`. Forcibly set the recognized language, which is determined by the model itself by default.
- `sample_rate`: Sample rate of the model. Default: `16000`. Other sampling rates are not supported now.
- `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.
- Python API
```python
import paddle
from paddlespeech.cli.whisper import WhisperExecutor
whisper_executor = WhisperExecutor()
# to recognize text
text = whisper_executor(
model='whisper',
task='transcribe',
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))
# to recognize text and translate to English
feature = whisper_executor(
model='whisper',
task='translate',
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('Representation: \n{}'.format(feature))
```
Output:
```bash
Transcribe Result:
Detected language: Chinese
[00:00.000 --> 00:05.000] 我认为跑步最重要的就是给我带来了身体健康
{'text': '我认为跑步最重要的就是给我带来了身体健康', 'segments': [{'id': 0, 'seek': 0, 'start': 0.0, 'end': 5.0, 'text': '我认为跑步最重要的就是给我带来了身体健康', 'tokens': [50364, 1654, 7422, 97, 13992, 32585, 31429, 8661, 24928, 1546, 5620, 49076, 4845, 99, 34912, 19847, 29485, 44201, 6346, 115, 50614], 'temperature': 0.0, 'avg_logprob': -0.23577967557040128, 'compression_ratio': 0.28169014084507044, 'no_speech_prob': 0.028302080929279327}], 'language': 'zh'}
Translate Result:
Detected language: Chinese
[00:00.000 --> 00:05.000] I think the most important thing about running is that it brings me good health.
{'text': ' I think the most important thing about running is that it brings me good health.', 'segments': [{'id': 0, 'seek': 0, 'start': 0.0, 'end': 5.0, 'text': ' I think the most important thing about running is that it brings me good health.', 'tokens': [50364, 286, 519, 264, 881, 1021, 551, 466, 2614, 307, 300, 309, 5607, 385, 665, 1585, 13, 50614], 'temperature': 0.0, 'avg_logprob': -0.47945233395225123, 'compression_ratio': 1.095890410958904, 'no_speech_prob': 0.028302080929279327}], 'language': 'zh'}