tools/asr/funasr_asr.py

# -*- coding:utf-8 -*-

import argparse
import os
import traceback
from tqdm import tqdm
# from funasr.utils import version_checker
# version_checker.check_for_update = lambda: None
from funasr import AutoModel


def only_asr(input_file):
    try:
        text = model.generate(input=input_file)[0]["text"]
    except:
        text = ''
        print(traceback.format_exc())
    return text

def execute_asr(input_folder, output_folder, model_size, language):
    input_file_names = os.listdir(input_folder)
    input_file_names.sort()
    
    output = []
    output_file_name = os.path.basename(input_folder)

    for file_name in tqdm(input_file_names):
        try:
            print(file_name)
            file_path = os.path.join(input_folder, file_name)
            text = model.generate(input=file_path)[0]["text"]
            output.append(f"{file_path}|{output_file_name}|{language.upper()}|{text}")
        except:
            print(traceback.format_exc())

    output_folder = output_folder or "output/asr_opt"
    os.makedirs(output_folder, exist_ok=True)
    output_file_path = os.path.abspath(f'{output_folder}/{output_file_name}.list')

    with open(output_file_path, "w", encoding="utf-8") as f:
        f.write("\n".join(output))
        print(f"ASR 任务完成->标注文件路径: {output_file_path}\n")
    return output_file_path


parser = argparse.ArgumentParser()
parser.add_argument("-i", "--input_folder", type=str, required=True,
                    help="Path to the folder containing WAV files.")
parser.add_argument("-o", "--output_folder", type=str, required=True,
                    help="Output folder to store transcriptions.")
parser.add_argument("-s", "--model_size", type=str, default='large',
                    help="Model Size of FunASR is Large")
parser.add_argument("-l", "--language", type=str, default='zh', choices=['zh','yue','auto'],
                    help="Language of the audio files.")
parser.add_argument("-p", "--precision", type=str, default='float16', choices=['float16','float32'],
                    help="fp16 or fp32")#还没接入

cmd = parser.parse_args()

path_vad = 'tools/asr/models/speech_fsmn_vad_zh-cn-16k-common-pytorch'
path_punc = 'tools/asr/models/punc_ct-transformer_zh-cn-common-vocab272727-pytorch'
path_vad = path_vad if os.path.exists(path_vad) else "iic/speech_fsmn_vad_zh-cn-16k-common-pytorch"
path_punc = path_punc if os.path.exists(path_punc) else "iic/punc_ct-transformer_zh-cn-common-vocab272727-pytorch"
vad_model_revision=punc_model_revision="v2.0.4"

if(cmd.language=="zh"):
    path_asr = 'tools/asr/models/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch'
    path_asr = path_asr if os.path.exists(path_asr) else "iic/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch"
    model_revision="v2.0.4"
else:
    path_asr = 'tools/asr/models/speech_UniASR_asr_2pass-cantonese-CHS-16k-common-vocab1468-tensorflow1-online'
    path_asr = path_asr if os.path.exists(path_asr) else "iic/speech_UniASR_asr_2pass-cantonese-CHS-16k-common-vocab1468-tensorflow1-online"
    model_revision="master"
    path_vad=path_punc=vad_model_revision=punc_model_revision=None###友情提示：粤语带VAD识别可能会有少量shape不对报错的，但是不带VAD可以.不带vad只能分阶段单独加标点。不过标点模型对粤语效果真的不行…

model = AutoModel(
    model=path_asr,
    model_revision=model_revision,
    vad_model=path_vad,
    vad_model_revision=vad_model_revision,
    punc_model=path_punc,
    punc_model_revision=punc_model_revision,
)

if __name__ == '__main__':
    execute_asr(
        input_folder  = cmd.input_folder,
        output_folder = cmd.output_folder,
        model_size    = cmd.model_size,
        language      = cmd.language,
    )