First International Workshop on Independent Component Analysis and Signal Separation (ICA'99) REAL WORLD BLIND SEPARATION OF CONVOLVED NON-STATIONARY SIGNALS

In this paper, a method of blind separation for convolved non-stationary signals (e.g., speech signals and music) is presented. Our method achieves blind separation by forcing mixed signals to uncorrelate with each other. The validity of the proposed method has been con rmed by a computer simulation and an experiment in an anechoic room [7]. In this paper, we apply our method to an experiment which extracts two source signals from their mixtures observed in a normal room. The experiment is implemented in a noisy environment. Moreover, we test our algorithm using the data obtained from Computational Neurobiology Lab.'s Blind Source Separation Web Page.