| | |
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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_asr_nat-zh-cn-16k-common-vocab8404-online', |
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| | | model_revision='v1.0.4' |
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| | | model_revision='v1.0.6', |
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| | | mode='paraformer_streaming' |
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| | | ) |
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| | | import soundfile |
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| | | speech, sample_rate = soundfile.read("example/asr_example.wav") |
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| | |
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| | | Full code of demo, please ref to [demo](https://github.com/alibaba-damo-academy/FunASR/discussions/241) |
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| | | |
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| | | #### [UniASR Model](https://www.modelscope.cn/models/damo/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online/summary) |
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| | | There are three decoding mode for UniASR model(`fast`、`normal`、`offline`), for more model detailes, please refer to [docs](https://www.modelscope.cn/models/damo/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online/summary) |
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| | | There are three decoding mode for UniASR model(`fast`、`normal`、`offline`), for more model details, please refer to [docs](https://www.modelscope.cn/models/damo/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online/summary) |
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| | | ```python |
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| | | decoding_model = "fast" # "fast"、"normal"、"offline" |
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| | | inference_pipeline = pipeline( |
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| | |
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| | | Undo |
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| | | |
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| | | #### [MFCCA Model](https://www.modelscope.cn/models/NPU-ASLP/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/summary) |
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| | | For more model detailes, please refer to [docs](https://www.modelscope.cn/models/NPU-ASLP/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/summary) |
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| | | For more model details, please refer to [docs](https://www.modelscope.cn/models/NPU-ASLP/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/summary) |
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| | | ```python |
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| | | from modelscope.pipelines import pipeline |
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| | | from modelscope.utils.constant import Tasks |
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