FunASR/funasr/runtime/websocket/readme.md

(简体中文|English)

Service with websocket-cpp

Quick Start

Docker Image start

Pull and start the FunASR runtime-SDK Docker image using the following command:

sudo docker pull registry.cn-hangzhou.aliyuncs.com/funasr_repo/funasr:funasr-runtime-sdk-cpu-0.1.0

sudo docker run -p 10095:10095 -it --privileged=true -v /root:/workspace/models registry.cn-hangzhou.aliyuncs.com/funasr_repo/funasr:funasr-runtime-sdk-cpu-0.1.0

If you have not installed Docker, please refer to Docker Installation.

Server Start

After Docker is started, start the funasr-wss-server service program:

cd FunASR/funasr/runtime
./run_server.sh \
  --download-model-dir /workspace/models \
  --vad-dir damo/speech_fsmn_vad_zh-cn-16k-common-onnx \
  --model-dir damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-onnx  \
  --punc-dir damo/punc_ct-transformer_zh-cn-common-vocab272727-onnx

For detailed server parameters, please refer to [Server Parameter Introduction](#Server Parameter Introduction).

Client Testing and Usage

Download the client test tool directory samples:

wget https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/sample/funasr_samples.tar.gz

We take the Python language client as an example to explain. It supports various audio formats (.wav, .pcm, .mp3, etc.), video input (.mp4, etc.), and multi-file list wav.scp input. For other versions of clients, please refer to the (docs).

python3 wss_client_asr.py --host "127.0.0.1" --port 10095 --mode offline --audio_in "../audio/asr_example.wav"

Detailed Steps

Dependencies Download and Install

The third-party libraries have been pre-installed in Docker. If not using Docker, please download and install them manually (Download and Install Third-Party Libraries).

Build runtime

git clone https://github.com/alibaba-damo-academy/FunASR.git && cd FunASR/funasr/runtime/websocket
mkdir build && cd build
cmake  -DCMAKE_BUILD_TYPE=release .. -DONNXRUNTIME_DIR=/path/to/onnxruntime-linux-x64-1.14.0 -DFFMPEG_DIR=/path/to/ffmpeg-N-111383-g20b8688092-linux64-gpl-shared
make

Start Service Deployment

API-reference：

--download-model-dir Model download address, download the model from Modelscope by setting the model ID. If starting from a local model, this parameter can be left out.
--model-dir ASR model ID in Modelscope or the absolute path of local model
--quantize True for quantized ASR model, False for non-quantized ASR model. Default is True.
--vad-dir VAD model ID in Modelscope or the absolute path of local model
--vad-quant True for quantized VAD model, False for non-quantized VAD model. Default is True.
--punc-dir PUNC model ID in Modelscope or the absolute path of local model
--punc-quant True for quantized PUNC model, False for non-quantized PUNC model. Default is True.
--port Port number for the server to listen on. Default is 10095.
--decoder-thread-num Number of inference threads started by the server. Default is 8.
--io-thread-num Number of IO threads started by the server. Default is 1.
--certfile SSL certificate file. Default is: ../../../ssl_key/server.crt.
--keyfile SSL key file. Default is: ../../../ssl_key/server.key.

Example of Starting from Modelscope

./funasr-wss-server  \
  --download-model-dir /workspace/models \
  --model-dir damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-onnx \
  --vad-dir damo/speech_fsmn_vad_zh-cn-16k-common-onnx \
  --punc-dir damo/punc_ct-transformer_zh-cn-common-vocab272727-onnx

Note: In the above example, model-dir，vad-dir，punc-dir are the model names in Modelscope, downloaded directly from Modelscope and exported as quantized onnx. If starting from a local model, please change the parameter to the absolute path of the local model.

Example of Starting from Local Model

Export the Model

python -m funasr.export.export_model \
--export-dir ./export \
--type onnx \
--quantize True \
--model-name damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch \
--model-name damo/speech_fsmn_vad_zh-cn-16k-common-pytorch \
--model-name damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch

Export Detailed Introduction（docs）

Start the Service

./funasr-wss-server  \
  --download-model-dir /workspace/models \
  --model-dir ./exportdamo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-onnx \
  --vad-dir ./exportdamo/speech_fsmn_vad_zh-cn-16k-common-onnx \
  --punc-dir ./export/damo/punc_ct-transformer_zh-cn-common-vocab272727-onnx

Start the 2pass Service

./funasr-wss-server-2pass  \
  --download-model-dir /workspace/models \
  --model-dir ./exportdamo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-onnx \
  --vad-dir ./exportdamo/speech_fsmn_vad_zh-cn-16k-common-onnx \
  --punc-dir ./export/damo/punc_ct-transformer_zh-cn-common-vocab272727-onnx \
  --online-model-dir ./exportdamo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online \
  --quantize false

Client Usage

Download the client test tool directory samples

wget https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/sample/funasr_samples.tar.gz

After deploying the FunASR service on the server, you can test and use the offline file transcription service through the following steps. Currently, the following programming language client is supported:

• Python
• CPP
• html
• Java

python-client

If you want to run the client directly for testing, you can refer to the following simple instructions, taking the Python version as an example:

python3 wss_client_asr.py --host "127.0.0.1" --port 10095 --mode offline --audio_in "../audio/asr_example.wav" --output_dir "./results"

API-reference

--host: IP address of the machine where FunASR runtime-SDK service is deployed. The default value is the IP address of the local machine (127.0.0.1). If the client and service are not on the same server, it needs to be changed to the IP address of the deployment machine.
--port: The port number of the deployed service is 10095.
--mode: "offline" means offline file transcription.
--audio_in: The audio file that needs to be transcribed, which supports file path and file list (wav.scp).
--output_dir: The path to save the recognition result.

cpp-client

After entering the directory samples/cpp, you can test it with CPP, as follows:

./funasr-wss-client --server-ip 127.0.0.1 --port 10095 --wav-path ../audio/asr_example.wav

API-reference:

--server-ip: The IP address of the machine where FunASR runtime-SDK service is deployed. The default value is the IP address of the local machine (127.0.0.1). If the client and service are not on the same server, it needs to be changed to the IP address of the deployment machine.
--port: The port number of the deployed service is 10095.
--wav-path: The audio file that needs to be transcribed, which supports file path.

Html-client

Open html/static/index.html in the browser, and you can see the following page, which supports microphone input and file upload for direct experience.

Java-client

FunasrWsClient --host localhost --port 10095 --audio_in ./asr_example.wav --mode offline

For more details, please refer to the documentation

Acknowledge

1. This project is maintained by FunASR community.
2. We acknowledge zhaoming for contributing the websocket(cpp-api).