Deep neural network based audio source separation
Alfredo Zermini, Yang Fan Yu, Yong Xu, Mark D. Plumbley, Wenwu Wang · Surrey Research Insight Open Access (The University of Surrey) · 2016
Audio source separation aims to extract individual sources from mixtures of multiple sound sources. Many techniques have been developed such as independent compo- nent analysis, computational auditory scene analysis, and non-negative matrix factorisa- tion. A method based on Deep Neural Networks (DNNs) and time-frequency (T-F) mask- ing has been recently developed for binaural audio source separation. In this method, the DNNs are used to predict the Direction Of Arrival (DOA) of the audio sources with respect to the listener which is then used to generate soft T-F masks for the recovery/estimation of the individual audio sources.