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+# ONNXRuntime-cpp
+
+## Export the model
+### Install [modelscope and funasr](https://github.com/alibaba-damo-academy/FunASR#installation)
+
+```shell
+# pip3 install torch torchaudio
+pip install -U modelscope funasr
+# For the users in China, you could install with the command:
+# pip install -U modelscope funasr -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html -i https://mirror.sjtu.edu.cn/pypi/web/simple
+```
+
+### Export [onnx model](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/export)
+
+```shell
+python -m funasr.export.export_model --model-name damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch --export-dir ./export --type onnx --quantize True
+```
+
+## Building for Linux/Unix
+
+### Download onnxruntime
+```shell
+# download an appropriate onnxruntime from https://github.com/microsoft/onnxruntime/releases/tag/v1.14.0
+# here we get a copy of onnxruntime for linux 64
+wget https://github.com/microsoft/onnxruntime/releases/download/v1.14.0/onnxruntime-linux-x64-1.14.0.tgz
+tar -zxvf onnxruntime-linux-x64-1.14.0.tgz
+```
+
+### Install openblas
+```shell
+sudo apt-get install libopenblas-dev #ubuntu
+# sudo yum -y install openblas-devel #centos
+```
+
+### Build runtime
+```shell
+git clone https://github.com/alibaba-damo-academy/FunASR.git && cd funasr/runtime/onnxruntime
+mkdir build && cd build
+cmake  -DCMAKE_BUILD_TYPE=release .. -DONNXRUNTIME_DIR=/path/to/onnxruntime-linux-x64-1.14.0
+make
+```
+## Run the demo
+
+```shell
+./funasr-onnx-offline     [--wav-scp <string>] [--wav-path <string>]
+                          [--punc-config <string>] [--punc-model <string>]
+                          --am-config <string> --am-cmvn <string>
+                          --am-model <string> [--vad-config <string>]
+                          [--vad-cmvn <string>] [--vad-model <string>] [--]
+                          [--version] [-h]
+Where:
+   --wav-scp <string>
+     wave scp path
+   --wav-path <string>
+     wave file path
+
+   --punc-config <string>
+     punc config path
+   --punc-model <string>
+     punc model path
+
+   --am-config <string>
+     (required)  am config path
+   --am-cmvn <string>
+     (required)  am cmvn path
+   --am-model <string>
+     (required)  am model path
+
+   --vad-config <string>
+     vad config path
+   --vad-cmvn <string>
+     vad cmvn path
+   --vad-model <string>
+     vad model path
+  
+   Required: --am-config <string> --am-cmvn <string> --am-model <string> 
+   If use vad, please add: [--vad-config <string>] [--vad-cmvn <string>] [--vad-model <string>]
+   If use punc, please add: [--punc-config <string>] [--punc-model <string>] 
+```
+
+## Acknowledge
+1. This project is maintained by [FunASR community](https://github.com/alibaba-damo-academy/FunASR).
+2. We acknowledge mayong for contributing the onnxruntime of Paraformer and CT_Transformer, [repo-asr](https://github.com/RapidAI/RapidASR/tree/main/cpp_onnx), [repo-punc](https://github.com/RapidAI/RapidPunc).
+3. We acknowledge [ChinaTelecom](https://github.com/zhuzizyf/damo-fsmn-vad-infer-httpserver) for contributing the VAD runtime.
+4. We borrowed a lot of code from [FastASR](https://github.com/chenkui164/FastASR) for audio frontend and text-postprocess.