Blind Separation of Moving Speech Sources using Short-Time LOD Based ICA Method

This paper describes the application of an effective short-time ICA method for blind speech separation of a moving-speaker system. For the situation where time-varying mixture exists, adaptive ICA techniques encounter difficulties due to the collapse of sources independence assumption under short-time analysis. In this paper, we propose a method based on the short-time local optima distribution (LOD) of feasible separation region to alleviate such problems. Based on the characteristics of these distributions, information is obtained for avoiding local traps and approaching the desired global optimum of the de-mixing matrix. Simulation tests of the proposed method show its effectiveness for blind separation of moving speech sources.