Hyb-DysNet: hybrid feature fusion (eGeMAPSv02 + Wav2Vec2-XLS-R + Librosa) and soft-voting ensemble for dysarthria severity classification in ALS patients.
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Updated
Apr 17, 2026 - Jupyter Notebook
Hyb-DysNet: hybrid feature fusion (eGeMAPSv02 + Wav2Vec2-XLS-R + Librosa) and soft-voting ensemble for dysarthria severity classification in ALS patients.
Audio features for ML: 47 extractors, MIT-licensed eGeMAPS, scikit-learn and PyTorch front ends, reproducible batch CLI.
Speaker-independent speech emotion recognition on RAVDESS: MFCC, eGeMAPS and ComParE vs frozen WavLM, HuBERT, XLS-R and Whisper under nested leave-one-speaker-out evaluation, with end-to-end fine-tuning, protocol-inflation and contamination checks, and a per-clip comparison with human listeners.
Interpretable classical ML for cross-lingual speech emotion recognition using hand-crafted acoustic features.
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