([简体中文](./README_cn.md)|English)

# Speech Server

## Introduction
This demo is an implementation of starting the voice service and accessing the service. It can be achieved with a single command using `paddlespeech_server` and `paddlespeech_client` or a few lines of code in python.


## 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 config File
The configuration file contains the service-related configuration files and the model configuration related to the voice tasks contained in the service. They are all under the `conf` folder. 

**Note: The configuration of `engine_backend` in `application.yaml` represents all speech tasks included in the started service. **
If the service you want to start contains only a certain speech task, then you need to comment out the speech tasks that do not need to be included. For example, if you only want to use the speech recognition (ASR) service, then you can comment out the speech synthesis (TTS) service, as in the following example:
```bash
engine_backend:
    asr: 'conf/asr/asr.yaml'
    #tts: 'conf/tts/tts.yaml'
```

**Note: The configuration file of `engine_backend` in `application.yaml` needs to match the configuration type of `engine_type`. **
When the configuration file of `engine_backend` is `XXX.yaml`, the configuration type of `engine_type` needs to be set to `python`; when the configuration file of `engine_backend` is `XXX_pd.yaml`, the configuration of `engine_type` needs to be set type is `inference`;

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

Here are sample files for thisASR client 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. Server Usage
- Command Line (Recommended)

  ```bash
  # start the service
  paddlespeech_server start --config_file ./conf/application.yaml
  ```

  Usage:
  
  ```bash
  paddlespeech_server start --help
  ```
  Arguments:
  - `config_file`: yaml file of the app, defalut: ./conf/application.yaml
  - `log_file`: log file. Default: ./log/paddlespeech.log

  Output:
  ```bash
  [2022-02-23 11:17:32] [INFO] [server.py:64] Started server process [6384]
  INFO:     Waiting for application startup.
  [2022-02-23 11:17:32] [INFO] [on.py:26] Waiting for application startup.
  INFO:     Application startup complete.
  [2022-02-23 11:17:32] [INFO] [on.py:38] Application startup complete.
  INFO:     Uvicorn running on http://0.0.0.0:8090 (Press CTRL+C to quit)
  [2022-02-23 11:17:32] [INFO] [server.py:204] Uvicorn running on http://0.0.0.0:8090 (Press CTRL+C to quit)

  ```

- Python API
  ```python
  from paddlespeech.server.bin.paddlespeech_server import ServerExecutor

  server_executor = ServerExecutor()
  server_executor(
      config_file="./conf/application.yaml", 
      log_file="./log/paddlespeech.log")
  ```

  Output:
  ```bash
  INFO:     Started server process [529]
  [2022-02-23 14:57:56] [INFO] [server.py:64] Started server process [529]
  INFO:     Waiting for application startup.
  [2022-02-23 14:57:56] [INFO] [on.py:26] Waiting for application startup.
  INFO:     Application startup complete.
  [2022-02-23 14:57:56] [INFO] [on.py:38] Application startup complete.
  INFO:     Uvicorn running on http://0.0.0.0:8090 (Press CTRL+C to quit)
  [2022-02-23 14:57:56] [INFO] [server.py:204] Uvicorn running on http://0.0.0.0:8090 (Press CTRL+C to quit)

  ```


### 4. ASR Client Usage
**Note:** The response time will be slightly longer when using the client for the first time
- Command Line (Recommended)
   ```
   paddlespeech_client asr --server_ip 127.0.0.1 --port 8090 --input ./zh.wav
   ```

  Usage:
  
  ```bash
  paddlespeech_client asr --help
  ```
  Arguments:
  - `server_ip`: server ip. Default: 127.0.0.1
  - `port`: server port. Default: 8090
  - `input`(required): Audio file to be recognized.
  - `sample_rate`: Audio ampling rate, default: 16000.
  - `lang`: Language. Default: "zh_cn".
  - `audio_format`: Audio format. Default: "wav".

  Output:
  ```bash
  [2022-02-23 18:11:22,819] [    INFO] - {'success': True, 'code': 200, 'message': {'description': 'success'}, 'result': {'transcription': '我认为跑步最重要的就是给我带来了身体健康'}}
  [2022-02-23 18:11:22,820] [    INFO] - time cost 0.689145 s.

  ```

- Python API
  ```python
  from paddlespeech.server.bin.paddlespeech_client import ASRClientExecutor

  asrclient_executor = ASRClientExecutor()
  asrclient_executor(
      input="./zh.wav",
      server_ip="127.0.0.1",
      port=8090,
      sample_rate=16000,
      lang="zh_cn",
      audio_format="wav")
  ```

  Output:
  ```bash
  {'success': True, 'code': 200, 'message': {'description': 'success'}, 'result': {'transcription': '我认为跑步最重要的就是给我带来了身体健康'}}
  time cost 0.604353 s.
  ```
 
### 5. TTS Client Usage
**Note:** The response time will be slightly longer when using the client for the first time
- Command Line (Recommended)
   ```bash
   paddlespeech_client tts --server_ip 127.0.0.1 --port 8090 --input "您好，欢迎使用百度飞桨语音合成服务。" --output output.wav
   ```
     Usage:
  
    ```bash
    paddlespeech_client tts --help
    ```
    Arguments:
    - `server_ip`: server ip. Default: 127.0.0.1
    - `port`: server port. Default: 8090
    - `input`(required): Input text to generate.
    - `spk_id`: Speaker id for multi-speaker text to speech. Default: 0
    - `speed`: Audio speed, the value should be set between 0 and 3. Default: 1.0
    - `volume`: Audio volume, the value should be set between 0 and 3. Default: 1.0
    - `sample_rate`: Sampling rate, choice: [0, 8000, 16000], the default is the same as the model. Default: 0
    - `output`: Output wave filepath. Default: `output.wav`.

    Output:
    ```bash
    [2022-02-23 15:20:37,875] [    INFO] - {'description': 'success.'}
    [2022-02-23 15:20:37,875] [    INFO] - Save synthesized audio successfully on output.wav.
    [2022-02-23 15:20:37,875] [    INFO] - Audio duration: 3.612500 s.
    [2022-02-23 15:20:37,875] [    INFO] - Response time: 0.348050 s.

    ```

- Python API
  ```python
  from paddlespeech.server.bin.paddlespeech_client import TTSClientExecutor

  ttsclient_executor = TTSClientExecutor()
  ttsclient_executor(
      input="您好，欢迎使用百度飞桨语音合成服务。",
      server_ip="127.0.0.1",
      port=8090,
      spk_id=0,
      speed=1.0,
      volume=1.0,
      sample_rate=0,
      output="./output.wav")
  ```

  Output:
  ```bash
  {'description': 'success.'}
  Save synthesized audio successfully on ./output.wav.
  Audio duration: 3.612500 s.
  Response time: 0.388317 s.

  ```


## Models supported by the service
### ASR model
Get all models supported by the ASR service via `paddlespeech_server stats --task asr`, where static models can be used for paddle inference inference.

### TTS model
Get all models supported by the TTS service via `paddlespeech_server stats --task tts`, where static models can be used for paddle inference inference.