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import argparse |
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import json |
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import os |
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from funasr import AutoModel |
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def read_wav_scp(wav_scp_file: str): |
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"""读取 wav.scp 文件,返回 (id, wav_path) 元组列表。""" |
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wav_files = [] |
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with open(wav_scp_file, 'r') as f: |
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for line in f: |
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id, wav_path = line.strip().split(" ", 1) |
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wav_files.append((id, wav_path)) |
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return wav_files |
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def save_results(results, output_file: str): |
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"""将推理结果保存到指定的文件中,格式为 'key text' 每行一条。""" |
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with open(output_file, 'w') as f: |
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for result in results: |
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key = result.get("key", "") |
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text = result.get("text", "") |
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f.write(f"{key} {text}\n") |
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def main(): |
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parser = argparse.ArgumentParser(description="Run speech recognition inference") |
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parser.add_argument('--model', type=str, required=True, help="Model name or path") |
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parser.add_argument('--wav_scp_file', type=str, required=True, help="Path to wav.scp file") |
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parser.add_argument('--output_dir', type=str, required=True, help="Directory to save inference results") |
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parser.add_argument('--device', type=str, default="cpu", choices=["cpu", "cuda"], help="Device to run inference on") |
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parser.add_argument('--output_file', type=str, required=True, help="File to save the inference results") |
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args = parser.parse_args() |
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print(f"Initializing model {args.model}...") |
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model = AutoModel(model=args.model, device=args.device) |
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wav_files = read_wav_scp(args.wav_scp_file) |
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all_results = [] |
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for id, wav_path in wav_files: |
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print(f"正在处理音频文件 {id}: {wav_path}") |
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res = model.generate(wav_path) |
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print(f"推理结果: {res}") |
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if res: |
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key = id |
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text = res[0].get("text", "") |
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all_results.append({"key": key, "text": text}) |
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save_results(all_results, args.output_file) |
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print(f"推理结果已保存到 {args.output_file}") |
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if __name__ == "__main__": |
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main() |
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