Blind Speech Separation Using Parafac Analysis and Integer Least Squares

We propose a new two-step frequency domain algorithm for blind speech separation (BSS) for unknown channel order. This new approach employs parallel factor analysis (PARAFAC) to separate the speech signals and a novel integer-least-squares-based method for matching the arbitrary permutations in the frequency domain. The proposed algorithm offers guaranteed convergence and good separation performance, measured both quantitatively and in subjective tests. Performance gains in signal-to-interference ratio of up to 10 db are achieved for certain source-sensor geometries