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import argparse |
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import os |
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import traceback |
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from tqdm import tqdm |
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from funasr import AutoModel |
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path_asr = 'tools/asr/models/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch' |
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path_vad = 'tools/asr/models/speech_fsmn_vad_zh-cn-16k-common-pytorch' |
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path_punc = 'tools/asr/models/punc_ct-transformer_zh-cn-common-vocab272727-pytorch' |
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path_asr = path_asr if os.path.exists(path_asr) else "iic/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch" |
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path_vad = path_vad if os.path.exists(path_vad) else "iic/speech_fsmn_vad_zh-cn-16k-common-pytorch" |
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path_punc = path_punc if os.path.exists(path_punc) else "iic/punc_ct-transformer_zh-cn-common-vocab272727-pytorch" |
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model = AutoModel( |
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model = path_asr, |
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model_revision = "v2.0.4", |
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vad_model = path_vad, |
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vad_model_revision = "v2.0.4", |
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punc_model = path_punc, |
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punc_model_revision = "v2.0.4", |
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) |
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def only_asr(input_file): |
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try: |
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text = model.generate(input=input_file)[0]["text"] |
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except: |
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text = '' |
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print(traceback.format_exc()) |
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return text |
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def execute_asr(input_folder, output_folder, model_size, language): |
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input_file_names = os.listdir(input_folder) |
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input_file_names.sort() |
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output = [] |
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output_file_name = os.path.basename(input_folder) |
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for file_name in tqdm(input_file_names): |
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try: |
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file_path = os.path.join(input_folder, file_name) |
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text = model.generate(input=file_path)[0]["text"] |
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output.append(f"{file_path}|{output_file_name}|{language.upper()}|{text}") |
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except: |
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print(traceback.format_exc()) |
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output_folder = output_folder or "output/asr_opt" |
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os.makedirs(output_folder, exist_ok=True) |
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output_file_path = os.path.abspath(f'{output_folder}/{output_file_name}.list') |
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with open(output_file_path, "w", encoding="utf-8") as f: |
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f.write("\n".join(output)) |
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print(f"ASR 任务完成->标注文件路径: {output_file_path}\n") |
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return output_file_path |
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if __name__ == '__main__': |
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parser = argparse.ArgumentParser() |
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parser.add_argument("-i", "--input_folder", type=str, required=True, |
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help="Path to the folder containing WAV files.") |
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parser.add_argument("-o", "--output_folder", type=str, required=True, |
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help="Output folder to store transcriptions.") |
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parser.add_argument("-s", "--model_size", type=str, default='large', |
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help="Model Size of FunASR is Large") |
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parser.add_argument("-l", "--language", type=str, default='zh', choices=['zh'], |
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help="Language of the audio files.") |
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parser.add_argument("-p", "--precision", type=str, default='float16', choices=['float16','float32'], |
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help="fp16 or fp32") |
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cmd = parser.parse_args() |
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execute_asr( |
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input_folder = cmd.input_folder, |
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output_folder = cmd.output_folder, |
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model_size = cmd.model_size, |
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language = cmd.language, |
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) |
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