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* add hotword for deploy_tools * Support wfst decoder and contextual biasing (#1039) * Support wfst decoder and contextual biasing * Turn on fstbin compilation --------- Co-authored-by: gongbo.gb <gongbo.gb@alibaba-inc.com> * mv funasr/runtime runtime * Fix crash caused by OOV in hotwords list * funasr infer * funasr infer * funasr infer * funasr infer * funasr infer * fix some bugs about fst hotword; support wfst for websocket server and clients; mv runtime out of funasr; modify relative docs * del onnxruntime/include/gflags * update tensor.h * update run_server.sh * update deploy tools * update deploy tools * update websocket-server * update funasr-wss-server * Remove self loop propagation * Update websocket_protocol_zh.md * Update websocket_protocol_zh.md * update hotword protocol * author zhaomingwork: change hotwords for h5 and java * update hotword protocol * catch exception for json_fst_hws * update hotword on message * update onnx benchmark for ngram&hotword * update docs * update funasr-wss-serve * add NONE for LM_DIR * update docs * update run_server.sh * add whats-new * modify whats-new * update whats-new * update whats-new * Support decoder option for beam searching * update benchmark_onnx_cpp * Support decoder option for websocket * fix bug of CompileHotwordEmbedding * update html client * update docs --------- Co-authored-by: gongbo.gb <35997837+aibulamusi@users.noreply.github.com> Co-authored-by: gongbo.gb <gongbo.gb@alibaba-inc.com> Co-authored-by: 游雁 <zhifu.gzf@alibaba-inc.com>
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FunASR Runtime Roadmap
中文文档（点击此处）
FunASR is a speech recognition framework developed by the Speech Lab of DAMO Academy, which integrates industrial-level models in the fields of speech endpoint detection, speech recognition, punctuation segmentation, and more. It has attracted many developers to participate in experiencing and developing. To solve the last mile of industrial landing and integrate models into business, we have developed the FunASR runtime-SDK. The SDK supports several service deployments, including:
- File transcription service, Mandarin, CPU version, done
- The real-time transcription service, Mandarin (CPU), done
- File transcription service, English, CPU version, done
- File transcription service, Mandarin, GPU version, in progress
- and more.
File Transcription Service, English (CPU)
Currently, the FunASR runtime-SDK supports the deployment of file transcription service, English (CPU version), with a complete speech recognition chain that can transcribe tens of hours of audio into punctuated text, and supports recognition for more than a hundred concurrent streams.
To meet the needs of different users, we have prepared different tutorials with text and images for both novice and advanced developers.
Whats-new
- 2023/11/08: Adaptation to runtime structure changes (FunASR/funasr/runtime -> FunASR/runtime), docker image version funasr-runtime-sdk-en-cpu-0.1.1 ().
- 2023/10/16: English File Transcription Service 1.0 released, docker image version funasr-runtime-sdk-en-cpu-0.1.0 (e0de03eb0163), refer to the detailed documentation（here）
Technical Principles
The technical principles and documentation behind FunASR explain the underlying technology, recognition accuracy, computational efficiency, and core advantages of the framework, including convenience, high precision, high efficiency, and support for long audio chains. For detailed information, please refer to the documentation available by docs.
Deployment Tutorial
The documentation mainly targets novice users who have no need for modifications or customization. It supports downloading model deployments from modelscope and also supports deploying models that users have fine-tuned. For detailed tutorials, please refer to docs.
Advanced Development Guide
The documentation mainly targets advanced developers who require modifications and customization of the service. It supports downloading model deployments from modelscope and also supports deploying models that users have fine-tuned. For detailed information, please refer to the documentation available by docs
The real-time transcription service, Mandarin (CPU)
The FunASR real-time speech-to-text service software package not only performs real-time speech-to-text conversion, but also allows high-precision transcription text correction at the end of each sentence and outputs text with punctuation, supporting high-concurrency multiple requests. In order to meet the needs of different users for different scenarios, different tutorials are prepared:
Whats-new
- 2023/11/08: Real-time Transcription Service 1.4 released, supporting server-side loading of hotwords (updated hotword communication protocol), adaptation to runtime structure changes (FunASR/funasr/runtime -> FunASR/runtime), docker image version funasr-runtime-sdk-online-cpu-0.1.4().
- 2023/09/19: Real-time Transcription Service 1.2 released, supporting hotwords, timestamps, and ITN model in 2pass mode, docker image version funasr-runtime-sdk-online-cpu-0.1.2 (7222c5319bcf).
- 2023/08/11: Real-time Transcription Service 1.1 released, addressing some known bugs (including server crashes), docker image version funasr-runtime-sdk-online-cpu-0.1.1 (bdbdd0b27dee).
- 2023/08/07: Real-time Transcription Service 1.0 released, docker image version funasr-runtime-sdk-online-cpu-0.1.0(bdbdd0b27dee), refer to the detailed documentation（here）
Convenient Deployment Tutorial
This is suitable for scenarios where there is no need to modify the service deployment SDK and the deployed model comes from ModelScope or is finetuned by the user. For detailed tutorials, please refer to docs
Development Guide
This is suitable for scenarios where there is a need to modify the service deployment SDK and the deployed model comes from ModelScope or is finetuned by the user. For detailed documentation, please refer to docs
Technology Principles Revealed
The document introduces the technology principles behind the service, recognition accuracy, computing efficiency, and core advantages: convenience, high precision, high efficiency, and long audio chain. For detailed documentation, please refer to docs.
File Transcription Service, Mandarin (CPU)
Currently, the FunASR runtime-SDK supports the deployment of file transcription service, Mandarin (CPU version), with a complete speech recognition chain that can transcribe tens of hours of audio into punctuated text, and supports recognition for more than a hundred concurrent streams.
To meet the needs of different users, we have prepared different tutorials with text and images for both novice and advanced developers.
Whats-new
2023/11/08: File Transcription Service 3.0 released, supporting punctuation large model, Ngram model, fst hotwords (updated hotword communication protocol), server-side loading of hotwords, adaptation to runtime structure changes (FunASR/funasr/runtime -> FunASR/runtime), docker image version funasr-runtime-sdk-cpu-0.3.0 (), refer to the detailed documentation （here） 2023/09/19: File Transcription Service 2.2 released, supporting ITN model, docker image version funasr-runtime-sdk-cpu-0.2.2 (2c5286be13e9). 2023/08/22: File Transcription Service 2.0 released, integrated ffmpeg to support various audio and video inputs, supporting hotword model and timestamp model, docker image version funasr-runtime-sdk-cpu-0.2.0 (1ad3d19e0707), refer to the detailed documentation （here） 2023/07/03: File Transcription Service 1.0 released, docker image version funasr-runtime-sdk-cpu-0.1.0 (1ad3d19e0707), refer to the detailed documentation （here）
Technical Principles
The technical principles and documentation behind FunASR explain the underlying technology, recognition accuracy, computational efficiency, and core advantages of the framework, including convenience, high precision, high efficiency, and support for long audio chains. For detailed information, please refer to the documentation available by docs.
Deployment Tutorial
The documentation mainly targets novice users who have no need for modifications or customization. It supports downloading model deployments from modelscope and also supports deploying models that users have fine-tuned. For detailed tutorials, please refer to docs.
Advanced Development Guide
The documentation mainly targets advanced developers who require modifications and customization of the service. It supports downloading model deployments from modelscope and also supports deploying models that users have fine-tuned. For detailed information, please refer to the documentation available by docs