Distortion-Controlled Training for end-to-end Reverberant Speech Separation with Auxiliary Autoencoding Loss
Distortion-Controlled Training for end-to-end Reverberant Speech Separation with Auxiliary Autoencoding Loss
The performance of speech enhancement and separation systems in anechoic environments has been significantly advanced with the recent progress in end-to-end neural network architectures. However, the performance of such systems in reverberant environments is yet to be explored. A core problem in reverberant speech separation is about the training and …