infer.py

import os
import shutil
import argparse
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks

def modelscope_infer(args):
    os.environ['CUDA_VISIBLE_DEVICES'] = str(args.gpuid)
    if args.add_punc:
        inference_pipeline = pipeline(
            task=Tasks.auto_speech_recognition,
            model=args.model,
            output_dir=args.output_dir,
            batch_size=args.batch_size,
            vad_model='damo/speech_fsmn_vad_zh-cn-16k-common-pytorch',
            vad_model_revision="v1.1.8",
            punc_model='iic/punc_ct-transformer_cn-en-common-vocab471067-large',
            param_dict={"decoding_model": args.decoding_mode, "hotword": args.hotword_txt}
        )
    else:
        inference_pipeline = pipeline(
            task=Tasks.auto_speech_recognition,
            model=args.model,
            output_dir=args.output_dir,
            batch_size=args.batch_size,
            param_dict={"decoding_model": args.decoding_mode, "hotword": args.hotword_txt}
        )
    inference_pipeline(audio_in=args.audio_in)

if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    parser.add_argument('--model', type=str, default="damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch")
    parser.add_argument('--audio_in', type=str, default="./data/test/wav.scp")
    parser.add_argument('--output_dir', type=str, default="./results/")
    parser.add_argument('--decoding_mode', type=str, default="normal")
    parser.add_argument('--hotword_txt', type=str, default=None)
    parser.add_argument('--batch_size', type=int, default=64)
    parser.add_argument('--gpuid', type=str, default="0")
    parser.add_argument('--add_punc', type=int, default=0)
    args = parser.parse_args()
    modelscope_infer(args)