Deep Demixing: Source Separation with Deep Neural Networks

This paper introduces a deep learning approach to separate audio sources from a mixture. It uses deep neural networks to model the relationships between the mixture and the individual sources, enabling accurate separation even in complex scenarios. The method is particularly effective in separating vocals from music, demonstrating significant improvements over traditional techniques.