voice_translation_test.py 1.5 KB

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  1. from funasr import AutoModel
  2. import time
  3. def vocal_text(input_video_path):
  4. model = AutoModel(model="./Voice_translation", model_revision="v2.0.4",
  5. vad_model="./Endpoint_detection", vad_model_revision="v2.0.4",
  6. punc_model="./Ct_punc", punc_model_revision="v2.0.4",
  7. use_cuda=True,use_fast = True,
  8. )
  9. res = model.generate(input_video_path,
  10. batch_size_s=30,
  11. hotword='test')
  12. texts = [item['text'] for item in res]
  13. result = ' '.join(texts)
  14. return result
  15. if __name__ == "__main__":
  16. start_time = time.time()
  17. model = AutoModel(model="./Voice_translation", model_revision="v2.0.4",
  18. vad_model="./Endpoint_detection", vad_model_revision="v2.0.4",
  19. punc_model="./Ct_punc", punc_model_revision="v2.0.4",
  20. )
  21. res = model.generate(input="./data/audio/5bf77846-0193-4f35-92f7-09ce51ee3793.mp3",
  22. batch_size_s=30,
  23. hotword='test')
  24. print(res)
  25. texts = [item['text'] for item in res]
  26. print(texts)
  27. result = ' '.join(texts)
  28. print(result)
  29. # def save(input,savepath):
  30. # outputs = open(savepath, 'w', encoding='utf-8')
  31. # outputs.write(input+'\n')
  32. # outputs.close()
  33. # save(input=result,savepath=r"F:\work\voice_translation\datasets\1.txt")
  34. end_time = time.time()
  35. # 计算时间差
  36. elapsed_time = end_time - start_time
  37. print(f"耗时: {elapsed_time} 秒")