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eess.AS2022★ 2 cited
Exploring Self-Attention Mechanisms for Speech Separation
Cem Subakan, Mirco Ravanelli, Samuele Cornell +2
Transformers have enabled impressive improvements in deep learning. They often outperform recurrent and convolutional models in many tasks while taking advantage of parallel proces…
eess.AS2020★ 10 cited
Attention is All You Need in Speech Separation
Cem Subakan, Mirco Ravanelli, Samuele Cornell +2
Recurrent Neural Networks (RNNs) have long been the dominant architecture in sequence-to-sequence learning. RNNs, however, are inherently sequential models that do not allow parall…