EM Localization and Separation using Interaural Level and Phase Cues

We describe a system for localizing and separating multiple sound sources from a reverberant two-channel recording. It consists of a probabilistic model of interaural level and phase differences and an EM algorithm for finding the maximum likelihood parameters of this model. By assigning points in the interaural spectrogram probabilistically to sources with the best-fitting parameters and then estimating the parameters of the sources from the points assigned to them, the system is able to separate and localize more sound sources than there are available channels. It is also able to estimate frequency-dependent level differences of sources in a mixture that correspond well to those measured in isolation. In experiments in simulated anechoic and reverberant environments, the proposed system improved the signal-to-noise ratio of target sources by 2.7 and 3.4dB more than two comparable algorithms on average.