Blind source separation using structured neural networks

Deep learning is the core technique for blind source separation. Its application is well-studied and advanced rapidly. On the contrary, deep neural networks with guaranteed properties (e.g., perfect reconstruction and iterative behavior) have not been studied well in audio source separation. In this presentation, we introduce our recent approach to blind source separation using structured neural networks that are constructed to have some mathematical properties with theoretical guarantee.