A method for directionally-disjoint source separation in convolutive environment

We propose a new method for source separation that is based on directionally- disjoint estimation of the transfer functions between microphones and sources at different frequencies and at multiple times. The directions are estimated from eigenvectors of the microphones´ correlation matrix. Smoothing and association of transfer function parameters across different frequencies is achieved by simultaneous Kalman filtering of the noisy amplitude and phase estimates. This approach allows estimating transfer functions even in the case where the difference between the sources is in delay only and it can operate both for wideband and narrowband sources. Simulation results show superior performance in comparison to other, existing methods.