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| | | from pathlib import Path |
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| | | model_dir = "damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch" |
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| | | model_dir = "damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch" |
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| | | model = Paraformer(model_dir, batch_size=1, quantize=True) |
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| | | # model_dir = "damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch" |
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| | | model = Paraformer(model_dir, batch_size=1, quantize=False) |
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| | | # model = Paraformer(model_dir, batch_size=1, device_id=0) # gpu |
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| | | |
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| | | # when using paraformer-large-vad-punc model, you can set plot_timestamp_to="./xx.png" to get figure of alignment besides timestamps |
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| | | # model = Paraformer(model_dir, batch_size=1, plot_timestamp_to="test.png") |
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| | | |
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| | | wav_path = ['{}/.cache/modelscope/hub/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/example/asr_example.wav'.format(Path.home())] |
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| | | wav_path = ['{}/.cache/modelscope/hub/{}/example/asr_example.wav'.format(Path.home(), model_dir)] |
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| | | |
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| | | result = model(wav_path) |
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| | | print(result) |
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