| | |
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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_zh.wav') |
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| | | print(rec_result) |
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| | | ``` |
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| | | #### Paraformer-online |
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| | | ```python |
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| | | inference_pipeline = pipeline( |
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| | | task=Tasks.auto_speech_recognition, |
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| | | model='damo/speech_paraformer_asr_nat-zh-cn-16k-common-vocab8404-online', |
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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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| | | param_dict = {"cache": dict(), "is_final": False} |
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| | | chunk_stride = 7680# 480ms |
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| | | # first chunk, 480ms |
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| | | speech_chunk = speech[0:chunk_stride] |
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| | | rec_result = inference_pipeline(audio_in=speech_chunk, param_dict=param_dict) |
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| | | # next chunk, 480ms |
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| | | speech_chunk = speech[chunk_stride:chunk_stride+chunk_stride] |
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| | | rec_result = inference_pipeline(audio_in=speech_chunk, param_dict=param_dict) |
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| | | |
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| | | print(rec_result) |
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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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| | | #### API-reference |
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| | | ##### define pipeline |
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| | |
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| | | In this case of `wav.scp` input, `output_dir` must be set to save the output results |
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| | | - `audio_fs`: audio sampling rate, only set when audio_in is pcm audio |
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| | | |
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| | | |
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| | | #### Inference with you data |
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| | | |
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| | | #### Inference with multi-threads on CPU |
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