| | |
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| | | We can send streaming audio data to server in real-time with grpc client every 300 ms e.g., and get transcribed text when stop speaking. |
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| | | The audio data is in streaming, the asr inference process is in offline. |
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| | | |
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| | | # Steps |
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| | | |
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| | | ## For the Server |
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| | | |
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| | |
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| | | ```shell |
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| | | python ASR_server.py --host "0.0.0.0" --port 10095 --asr_model "damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch" |
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| | | ``` |
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| | | For the paraformer 2pass model |
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| | | |
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| | | ```shell |
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| | | python ASR_server_2pass.py --host "0.0.0.0" --port 10095 --asr_model "damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch" |
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| | | ``` |
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| | | |
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| | | ## For the client |
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| | | |
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| | |
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| | | Start client |
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| | | |
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| | | ```shell |
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| | | python ASR_client.py --host "127.0.0.1" --port 10095 --chunk_size 300 |
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| | | python ASR_client.py --host "127.0.0.1" --port 10095 --chunk_size 50 |
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| | | ``` |
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| | | |
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| | | ## Acknowledge |
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