Our vision is to offer an out-of-box engineering implementation for ASR.

A cpp implementation of recognize-onnx.py in Wenet-asr in which it implements the inference with ONNXRuntime. For a version of pure CPP code, we need to do a bit of work to rewrite some components.

Just offline mode, not support stream mode, aka separate files can be recognized.

• CTC_GREEDY_SEARCH
• CTC_RPEFIX_BEAM_SEARCH
• ATTENSION_RESCORING

• Linux
• Mac
• Android
• Windows

The model is original from https://github.com/wenet-e2e/wenet/tree/main/examples/wenetspeech/s0 and tested with recognize-onnx.py.

Download:

URL：https://pan.baidu.com/s/1BTR-uR_8WWBFpvOisNR_PA 
CODE：9xjz 

• Sample Rate:

16000Hz

• sample Depth:

16bits

• channel:

single

• Linux

TBD

• Windows

Visual studio 2019 & cmake 3.20



cd thirdpart
build_win.cmd x86|x64

The project is under the protection of GPL V2 and commercial license.

For a commercial license, please contact us: [email protected]

For a commercial user, we offer a library to resample input data including mp3, mp4, mkv and so on.

Please visit: https://github.com/RapidAI/RapidAudioKit