A time-frequency blind signal separation method applicable to underdetermined mixtures of dependent sources

In this paper.. we propose a new blind source separation (BSS) method called Thne-Frequency Ratio Of Mixtures (TIFROM) which uses time-frequency (TF) information to cancel source signal contributions from a set of linear instantaneous mixtures of these sources. Unlike previously reported TF BSS methods, the proposed approach only requires slight differences in the TF distributions of the considered signals: it mainly requests the sources to be cancelled to be "visible". i.e. to occur alone in a tiny area of the TF plane, while they may overlap in all the remainder of this plane. By using TF ratios of mixed signals, it automatically determines these single-source TF areas and identifies the corresponding parts of the mixing matrix. This approach sets no conditions on the stationarity, independence or non-Gaussianity of the sources, unlike classical independent component analysis methods. It achieves complete or partial BSS, depending on the numbers N and P of sources and observations and on the number of visible sources. It is therefore of interest for underdetermined mixtures (i.e. N > P), which cannot be processed with classical methods. Detailed results concerning mixtures of speech and music signals are presented and show that this approach yields very good performance. (c) 2005 Elsevier B.V. All rights reserved.