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feat: refactor Wav2Vec2 character ASR to support quantization and improve model loading
c5ca6dc
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feat: implement Wav2Vec2 character-level ASR with ONNX and Transformers support, add phoneme comparison and feedback generation
cef1d4a -
fix: update import statement for BaseModel in agent.py and add timing logs in speaking_controller.py
1a5420f -
Add Wav2Vec2 model conversion and inference to ONNX format
- Implemented Wav2Vec2ONNXConverter class for converting Wav2Vec2 models to ONNX format, including model loading, conversion, and verification. - Added Wav2Vec2ONNXInference class for performing inference using the converted ONNX model. - Included methods for softmax calculation and transcription of audio files. - Added utility functions for creating compatible models and exporting with fallback options for different ONNX opset versions. - Introduced optimization function for ONNX models. - Created helper function to convert numpy types to native Python types for better compatibility.df380ff