from modelscope.pipelines import pipeline
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from modelscope.utils.constant import Tasks
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param_dict = dict()
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param_dict['hotword'] = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/hotword.txt"
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param_dict['clas_scale'] = 1.00 # 1.50 # set it larger if you want high recall (sacrifice general accuracy)
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# 13% relative recall raise over internal hotword test set (45%->51%)
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# CER might raise when utterance contains no hotword
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inference_pipeline = pipeline(
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task=Tasks.auto_speech_recognition,
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model="damo/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404",
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param_dict=param_dict)
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rec_result = inference_pipeline(audio_in='https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_hotword.wav')
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print(rec_result)
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