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
- Python
- 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