2024
Resource-Efficient Separation Transformer
Luca Della Libera, Cem Subakan, Mirco Ravanelli, Samuele Cornell, Frédéric Lepoutre, François Grondin
ICASSP 2024accepted
Transformers have recently achieved state-of-the-art performance in speech separation. These models, however, are computationally demanding and require a lot of learnable parameters. This paper explores Transformer-based speech separation with a reduced computational cost. Our main contribution is t…