test_asr_vad_punc_inference_pipeline.py 1.3 KB

123456789101112131415161718192021222324252627282930313233
  1. import unittest
  2. from modelscope.pipelines import pipeline
  3. from modelscope.utils.constant import Tasks
  4. from modelscope.utils.logger import get_logger
  5. logger = get_logger()
  6. class TestParaformerInferencePipelines(unittest.TestCase):
  7. def test_funasr_path(self):
  8. import funasr
  9. import os
  10. logger.info("run_dir:{0} ; funasr_path: {1}".format(os.getcwd(), funasr.__file__))
  11. def test_inference_pipeline(self):
  12. inference_pipeline = pipeline(
  13. task=Tasks.auto_speech_recognition,
  14. model='damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch',
  15. model_revision="v1.2.1",
  16. vad_model='damo/speech_fsmn_vad_zh-cn-16k-common-pytorch',
  17. vad_model_revision="v1.1.8",
  18. punc_model='damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch',
  19. punc_model_revision="v1.1.6",
  20. ngpu=1,
  21. )
  22. rec_result = inference_pipeline(
  23. audio_in='https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav')
  24. logger.info("asr_vad_punc inference result: {0}".format(rec_result))
  25. assert rec_result["text"] == "欢迎大家来体验达摩院推出的语音识别模型。"
  26. if __name__ == '__main__':
  27. unittest.main()