Saikat Chatterjee

Contrastive learning can significantly enhance speech quality assessment models without the computational burden of multi-stage training.

Synthetic heart sounds generated by a diffusion model retain classification accuracy but miss critical abnormal acoustic features, highlighting a gap in current generation techniques.

Overlooking high-frequency information in multi-rate speech can significantly hinder speech quality assessment, but SA-SSL-MOS shows how to leverage it for improved generalization.