Using paraformer with ONNXRuntime

Introduction

• Model comes from speech_paraformer.

Steps:

1. Download the whole directory (funasr/runtime/python/onnxruntime) to the local.
2. Install the related packages.
   bash pip install requirements.txt
3. Export the model.
   • Export your model(docs), or Download Link
   • Put the model into the resources/models.
     text . ├── demo.py ├── rapid_paraformer │   ├── __init__.py │   ├── kaldifeat │   ├── __pycache__ │   ├── rapid_paraformer.py │   └── utils.py ├── README.md ├── requirements.txt ├── test_onnx.py ├── tests │   ├── __pycache__ │   └── test_infer.py └── test_wavs ├── 0478_00017.wav └── asr_example_zh.wav
4. Run the demo.

• Input: wav formt file, support formats: str, np.ndarray, List[str]
• Output: List[str]: recognition result.
• Example:
  ```python
  from paraformer_onnx import Paraformer

    config_path = 'resources/config.yaml'
    model = Paraformer(config_path)

    wav_path = ['example/asr_example.wav']

    result = model(wav_path)
    print(result)
    ```

Acknowledge

1. We acknowledge SWHL for contributing the onnxruntime(python api).