Combining localization cues and source model constraints for binaural source separation

We describe a system for separating multiple sources from a two-channel recording based on interaural cues and prior knowledge of the statistics of the underlying source signals. The proposed algorithm effectively combines information derived from low level perceptual cues, similar to those used by the human auditory system, with higher level information related to speaker identity. We combine a probabilistic model of the observed interaural level and phase differences with a prior model of the source statistics and derive an EM algorithm for finding the maximum likelihood parameters of the joint model. The system is able to separate more sound sources than there are observed channels in the presence of reverberation. In simulated mixtures of speech from two and three speakers the proposed algorithm gives a signal-to

• Type: Journal
• Year: 2011
• Where: SPEECH
• Authors: Ron J. Weiss, Michael I. Mandel, Daniel P. W. Ellis
• Keywords: Algorithm, Level Perceptual Cues, Observed Interaural Level, Security Privacy, SPEECH 2011