2017
Supervised monaural source separation based on autoencoders
ICASSP 2017accepted
In this paper, we propose a new supervised monaural source separation based on autoencoders. We employ the autoencoder for the dictionary training such that the nonlinear network can encode the target source with high expressiveness. The dictionary is trained by each target source without the mixtur…