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| | | # Real-time Speech Transcription Service Development Guide |
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| | | ([简体中文](SDK_advanced_guide_online_zh.md)|English) |
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| | | FunASR provides a real-time speech transcription service that can be easily deployed on local or cloud servers, with the FunASR runtime-SDK as the core. It integrates the speech endpoint detection (VAD), Paraformer-large non-streaming speech recognition (ASR), Paraformer-large streaming speech recognition (ASR), punctuation (PUNC), and other related capabilities open-sourced by the speech laboratory of DAMO Academy on the Modelscope community. The software package can perform real-time speech-to-text transcription, and can also accurately transcribe text at the end of sentences for high-precision output. The output text contains punctuation and supports high-concurrency multi-channel requests. |
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| | | [//]: # (FunASR provides a real-time speech transcription service that can be easily deployed on local or cloud servers, with the FunASR runtime-SDK as the core. It integrates the speech endpoint detection (VAD), Paraformer-large non-streaming speech recognition (ASR), Paraformer-large streaming speech recognition (ASR), punctuation (PUNC), and other related capabilities open-sourced by the speech laboratory of DAMO Academy on the Modelscope community. The software package can perform real-time speech-to-text transcription, and can also accurately transcribe text at the end of sentences for high-precision output. The output text contains punctuation and supports high-concurrency multi-channel requests.) |
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| | | FunASR Real-time Speech Recognition Software Package integrates real-time versions of speech endpoint detection model, speech recognition model, punctuation prediction model, and so on. By using multiple models collaboratively, it can perform real-time speech-to-text conversion, as well as high-precision transcription correction at the end of a sentence, with punctuation included in the output text. It supports multiple concurrent requests. Depending on the user's scenarios, it supports three service modes: real-time speech recognition service (online), non-real-time single-sentence transcription (offline), and real-time and non-real-time integrated collaboration (2pass). The software package provides client libraries in various programming languages such as HTML, Python, C++, Java, and C#, allowing users to use and further develop the software. |
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| | | <img src="images/online_structure.png" width="900"/> |
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| | | --punc-quant: True for quantized PUNC model, False for non-quantized PUNC model. Default is True. |
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| | | --itn-dir modelscope model ID or local model path. |
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| | | --port: Port number that the server listens on. Default is 10095. |
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| | | --decoder-thread-num: Number of inference threads that the server starts. Default is 8. |
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| | | --decoder-thread-num: The number of thread pools on the server side that can handle concurrent requests. The default value is 8. |
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| | | --model-thread-num: The number of internal threads for each recognition route to control the parallelism of the ONNX model. |
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| | | The default value is 1. It is recommended that decoder-thread-num * model-thread-num equals the total number of threads. |
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| | | --io-thread-num: Number of IO threads that the server starts. Default is 1. |
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| | | --certfile <string>: SSL certificate file. Default is ../../../ssl_key/server.crt. If you want to close ssl，set 0 |
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| | | --keyfile <string>: SSL key file. Default is ../../../ssl_key/server.key. |
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