Using funasr with libtorch

FunASR hopes to build a bridge between academic research and industrial applications on speech recognition. By supporting the training & finetuning of the industrial-grade speech recognition model released on ModelScope, researchers and developers can conduct research and production of speech recognition models more conveniently, and promote the development of speech recognition ecology. ASR for Fun！

Introduction

• Model comes from speech_paraformer.

Steps:

1. Export the model.

• Command: (Tips: torch >= 1.11.0 is required.)

  More details ref to (export docs)

  • e.g., Export model from modelscope
    shell python -m funasr.export.export_model --model-name damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch --export-dir ./export --type torch --quantize False
  • e.g., Export model from local path, the model'name must be model.pb.
    shell python -m funasr.export.export_model --model-name ./damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch --export-dir ./export --type torch --quantize False

1. Install the funasr_torch.

   install from pip
   shell pip install --upgrade funasr_torch -i https://pypi.Python.org/simple
   or install from source code

   git clone https://github.com/alibaba/FunASR.git && cd FunASR
   cd funasr/runtime/python/funasr_torch
   python setup.py build
   python setup.py install
   

2. Run the demo.

• Model_dir: the model path, which contains model.torchscripts, config.yaml, am.mvn.
• Input: wav formt file, support formats: str, np.ndarray, List[str]
• Output: List[str]: recognition result.

• Example:
  ```python
  from funasr_torch import Paraformer

  model_dir = "/nfs/zhifu.gzf/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch"
  model = Paraformer(model_dir, batch_size=1)
  
  wav_path = ['/nfs/zhifu.gzf/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/example/asr_example.wav']
  
  result = model(wav_path)
  print(result)
  ```
  

Performance benchmark

Please ref to benchmark

Speed

Environment：Intel(R) Xeon(R) Platinum 8163 CPU @ 2.50GHz

Test wav, 5.53s, 100 times avg.

Acknowledge

This project is maintained by FunASR community.