Michael Enenkl

Improving music source separation based on deep neural networks through data augmentation and network blending

This paper deals with the separation of music into individual instrument tracks which is known to be a challenging problem. We describe two different deep neural network architectures for this task, a feed-forward and a recurrent one, and show that each of them yields themselves state-of-the art res…