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PaddleSpeech/demos/speech_translation/README.md

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([简体中文](./README_cn.md)|English)
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# Speech Translation
## Introduction
Speech translation is the process by which conversational spoken phrases are instantly translated and spoken aloud in a second language.
This demo is an implementation to recognize text from a specific audio file and translate it to the target language. It can be done by a single command or a few lines in python using `PaddleSpeech`.
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## Usage
### 1. Installation
see [installation](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/docs/source/install.md).
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You can choose one way from easy, meduim and hard to install paddlespeech.
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### 2. Prepare Input File
The input of this demo should be a WAV file(`.wav`).
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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
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```
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### 3. Usage (not support for Windows now)
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- Command Line(Recommended)
```bash
paddlespeech st --input ./en.wav
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```
Usage:
```bash
paddlespeech st --help
```
Arguments:
- `input`(required): Audio file to recognize and translate.
- `model`: Model type of st task. Default: `fat_st_ted`.
- `src_lang`: Source language. Default: `en`.
- `tgt_lang`: Target language. Default: `zh`.
- `sample_rate`: Sample rate of the model. Default: `16000`.
- `config`: Config of st 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
[2021-12-09 11:13:03,178] [ INFO] [utils.py] [L225] - ST Result: ['我 在 这栋 建筑 的 古老 门上 敲门 。']
```
- Python API
```python
import paddle
from paddlespeech.cli.st import STExecutor
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st_executor = STExecutor()
text = st_executor(
model='fat_st_ted',
src_lang='en',
tgt_lang='zh',
sample_rate=16000,
config=None, # Set `config` and `ckpt_path` to None to use pretrained model.
ckpt_path=None,
audio_file='./en.wav',
device=paddle.get_device())
print('ST Result: \n{}'.format(text))
```
Output:
```bash
ST Result:
['我 在 这栋 建筑 的 古老 门上 敲门 。']
```
### 4.Pretrained Models
Here is a list of pretrained models released by PaddleSpeech that can be used by command and python API:
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| Model | Source Language | Target Language
| :--- | :---: | :---: |
| fat_st_ted| en| zh