Beamforming-based convolutive source separation

A robust independent component analysis (ICA) algorithm for blind separation of convolved mixtures of speech signals is introduced. It is based on two parallel frequency dependent beamforming stages, each of which cancels the signal from one interfering source by frequency dependent -beamforming. The zero-directions of the beamforming stages are optimized to yield maximally independent outputs, which is achieved via second and higher order statistics. Optimization is carried out in the frequency domain for each frequency band separately, so that phase distortions caused by the room impulse responses are compensated. In contrast to other frequency domain source separation algorithms, this structure does not suffer from permutation of frequency bands, while retaining the major advantage of blind methods, that do not require an external estimate of the direction of arrival (DOA).