Wav2Small: Distilling Wav2Vec2 to 72K parameters for Low-Resource Speech
emotion recognition
Wav2Small: Distilling Wav2Vec2 to 72K parameters for Low-Resource Speech
emotion recognition
Speech Emotion Recognition (SER) needs high computational resources to overcome the challenge of substantial annotator disagreement. Today SER is shifting towards dimensional annotations of arousal, dominance, and valence (A/D/V). Universal metrics as the L2 distance prove unsuitable for evaluating A/D/V accuracy due to non converging consensus of annotator opinions. However, …