阿里达摩院:FunASR - onnxruntime 部署
阿里达摩院:FunASR - onnxruntime 部署
git clone https://github.com/alibaba/FunASR.git
切换到 onnxruntime
cd FunASR/runtime/onnxruntime
1下载 onnxruntime
wget https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/dep_libs/onnxruntime-linux-x64-1.14.0.tgz
tar -zxvf onnxruntime-linux-x64-1.14.0.tgz
/media/wmx/soft1/software/onnxruntime/onnxruntime-linux-x64-1.14.0
2下载 ffmpeg
wget https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/dep_libs/ffmpeg-master-latest-linux64-gpl-shared.tar.xz
tar -xvf ffmpeg-master-latest-linux64-gpl-shared.tar.xz
我这里用之前下载的 /media/wmx/ws1/ffmpeg-n6.0
3安装依赖
# openblas
sudo apt-get install libopenblas-dev #ubuntu
# sudo yum -y install openblas-devel #centos# openssl
apt-get install libssl-dev #ubuntu
# yum install openssl-devel #centos
4编译 onnxruntime 工程:
#cd FunASR/runtime/onnxruntime
mkdir build && cd build
cmake -DCMAKE_BUILD_TYPE=release .. -DONNXRUNTIME_DIR=/media/wmx/soft1/software/onnxruntime/onnxruntime-linux-x64-1.14.0 -DFFMPEG_DIR=/media/wmx/ws1/ffmpeg-n6.0
make -j 12
生成在 onnxruntime/build/bin/ 路径下:
5切换到websocket 工程:
#cd FunASR/runtime/websocket
mkdir build && cd build
cmake -DCMAKE_BUILD_TYPE=release .. -DONNXRUNTIME_DIR=/media/wmx/soft1/software/onnxruntime/onnxruntime-linux-x64-1.14.0 -DFFMPEG_DIR=/media/wmx/ws1/ffmpeg-n6.0
make -j 12
生成在路径下 FunASR/runtime/websocket/build/bin/
6手动下载模型
因为自动下载模型需要 FunASR 的python 环境和相关依赖,这里是runtime ,没有安装这些,所以手动下载
modelscope : https://www.modelscope.cn/models
直接搜索模型名称,然后下载,我放在modelscope配置的路径下 /media/wmx/soft1/huggingface_cache/hub
模型名称:
iic/speech_fsmn_vad_zh-cn-16k-common-onnx
iic/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch
iic/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-onnx
iic/punc_ct-transformer_cn-en-common-vocab471067-large-onnx
iic/speech_ngram_lm_zh-cn-ai-wesp-fst
thuduj12/fst_itn_zh
修改 FunASR/runtime/run_server.sh
指定模型路径,其中 gpu 、cpu 推理 2选1
download_model_dir="/media/wmx/soft1/huggingface_cache/hub"# 这是 gpu 推理
model_dir="iic/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch" # 这是 cpu 推理
#model_dir="iic/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-onnx" vad_dir="iic/speech_fsmn_vad_zh-cn-16k-common-onnx"
punc_dir="iic/punc_ct-transformer_cn-en-common-vocab471067-large-onnx"
itn_dir="thuduj12/fst_itn_zh"
lm_dir="iic/speech_ngram_lm_zh-cn-ai-wesp-fst"
7 准备音频文件
#cd FunASR/runtime/
wget https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav
8 运行server
#cd FunASR/runtime/./run_server.sh
9 运行client
#cd FunASR/runtime/
./websocket/build/bin/funasr-wss-client --server-ip 127.0.0.1 --port 10095 --wav-path ./asr_example_zh.wav
输出:
(base) wmx@wmx-ubuntu:/media/wmx/soft1/AI-model/FunASR/runtime$ ./websocket/build/bin/funasr-wss-client --server-ip 127.0.0.1 --port 10095 --wav-path /media/wmx/ws3/AI/data/audios/zh/asr_example.wavI20240912 23:57:06.561726 80170 funasr-wss-client.cpp:315] Thread: 127658211935744, sended data len=177572
I20240912 23:57:06.768560 80172 funasr-wss-client.cpp:101] Thread: 127658190964224, total_recv=1, on_message = {"is_final":false,"mode":"offline","stamp_sents":[{"end":5195,"punc":"。","start":880,"text_seg":"欢 迎 大 家 来 体 验 达 摩 院 推 出 的 语 音 识 别 模 型","ts_list":[[880,1120],[1120,1380],[1380,1540],[1540,1780],[1780,2020],[2020,2180],[2180,2480],[2480,2600],[2600,2780],[2780,3040],[3040,3240],[3240,3480],[3480,3699],[3699,3900],[3900,4180],[4180,4420],[4420,4620],[4620,4780],[4780,5195]]}],"text":"欢迎大家来体验达摩院推出的语音识别模型。","timestamp":"[[880,1120],[1120,1380],[1380,1540],[1540,1780],[1780,2020],[2020,2180],[2180,2480],[2480,2600],[2600,2780],[2780,3040],[3040,3240],[3240,3480],[3480,3699],[3699,3900],[3900,4180],[4180,4420],[4420,4620],[4620,4780],[4780,5195]]","wav_name":"wav_default_id"}
I20240912 23:57:06.768589 80172 funasr-wss-client.cpp:106] Thread: 127658190964224, close client thread
on_message 返回的就是 json :
{"is_final":false,"mode":"offline","stamp_sents":[{"end":5195,"punc":"。","start":880,"text_seg":"欢 迎 大 家 来 体 验 达 摩 院 推 出 的 语 音 识 别 模 型","ts_list":[[880,1120],[1120,1380],[1380,1540],[1540,1780],[1780,2020],[2020,2180],[2180,2480],[2480,2600],[2600,2780],[2780,3040],[3040,3240],[3240,3480],[3480,3699],[3699,3900],[3900,4180],[4180,4420],[4420,4620],[4620,4780],[4780,5195]]}],"text":"欢迎大家来体验达摩院推出的语音识别模型。","timestamp":"[[880,1120],[1120,1380],[1380,1540],[1540,1780],[1780,2020],[2020,2180],[2180,2480],[2480,2600],[2600,2780],[2780,3040],[3040,3240],[3240,3480],[3480,3699],[3699,3900],[3900,4180],[4180,4420],[4420,4620],[4620,4780],[4780,5195]]","wav_name":"wav_default_id"}
提取其中的 text
字段的值,就是解码结果 "欢迎大家来体验达摩院推出的语音识别模型。"