Do Compact SSL Backbones Matter for Audio Deepfake Detection? A Controlled Study with RAPTOR

Researchers introduced RAPTOR, a study comparing compact SSL models for audio deepfake detection, finding that multilingual HuBERT pre-training enables smaller 100M parameter models to match larger commercial systems. The study reveals that pre-training approach matters more than model size, with WavLM variants showing overconfident miscalibration issues compared to HuBERT models.