86 lines
2.1 KiB
Python
86 lines
2.1 KiB
Python
#!/usr/bin/env python3
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"""FunASR 音频转录脚本"""
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import sys
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import os
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import json
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try:
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from funasr import AutoModel
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except ImportError:
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print("❌ 错误：未找到 funasr 模块")
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print("")
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print("请先安装 FunASR：")
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print(" bash ~/.openclaw/workspace/skills/funasr-transcribe/scripts/install.sh")
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sys.exit(1)
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def transcribe_audio(audio_path):
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"""使用 FunASR 转录音频"""
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print(f"正在处理音频: {audio_path}")
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print("首次运行会自动下载模型，可能需要几分钟...")
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# 加载模型
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model = AutoModel(
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model="damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch",
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vad_model="damo/speech_fsmn_vad_zh-cn-16k-common-pytorch",
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punc_model="damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch",
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device="cpu" # 使用 CPU，如果有 GPU 可以改为 "cuda:0"
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)
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# 进行语音识别
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res = model.generate(
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input=audio_path,
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batch_size_s=300
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)
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return res
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def main():
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if len(sys.argv) < 2:
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print("用法: python3 transcribe.py <audio_file>")
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sys.exit(1)
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audio_path = sys.argv[1]
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# 检查文件是否存在
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if not os.path.exists(audio_path):
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print(f"❌ 错误：文件不存在: {audio_path}")
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sys.exit(1)
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# 转录
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try:
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result = transcribe_audio(audio_path)
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except Exception as e:
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print(f"❌ 转录失败: {e}")
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sys.exit(1)
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# 输出结果
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text = ""
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if isinstance(result, list) and len(result) > 0:
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text = result[0].get("text", "")
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if not text:
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print("⚠️ 未识别到文本")
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sys.exit(0)
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print("\n" + "="*50)
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print("转录结果:")
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print("="*50)
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print(text)
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# 保存到文件
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output_path = os.path.splitext(audio_path)[0] + ".txt"
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try:
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with open(output_path, "w", encoding="utf-8") as f:
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f.write(text)
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print("")
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print(f"✓ 已保存到: {output_path}")
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except Exception as e:
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print(f"\n⚠️ 保存文件失败: {e}")
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if __name__ == "__main__":
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main()
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