| from typing import List |
| import argparse |
| import torch |
| from speechbrain.pretrained import EncoderDecoderASR |
|
|
|
|
| def asr_model_inference(asr_model: EncoderDecoderASR, audios: List[str]) -> List[str]: |
| return [asr_model.transcribe_file(audio) for audio in audios] |
|
|
|
|
| if __name__ == "__main__": |
| parser = argparse.ArgumentParser() |
| parser.add_argument("-I", dest="audio_file", required=True) |
|
|
| args = parser.parse_args() |
|
|
| asr_model = EncoderDecoderASR.from_hparams( |
| source="./infernce", hparams_file="hyperparams.yaml", savedir="inference", run_opts={"device": "cpu"}) |
|
|
| print(asr_model_inference(asr_model, [args.audio_file])) |
