2024
Two-Step Knowledge Distillation for Tiny Speech Enhancement
ICASSP 2024accepted
Tiny, causal models are crucial for embedded audio machine learning applications. Model compression can be achieved via distilling knowledge from a large teacher into a smaller student model. In this work, we propose a novel two-step approach for tiny speech enhancement model distillation. In contra…