Performance analysis of dynamic acoustic source separation in reverberant rooms

We study the effect of reverberation and source movement on the performance of blind source separation and deconvolution (BSSD) algorithms. Using the model of statistical room acoustics we derive theoretical performance measures for a class of unmixing algorithms when these are used in a reverberant room. We specifically investigate the cases: 1) where separation of only direct paths is performed and 2) the case where unmixing of the full reverberant paths is attempted. We develop closed-form performance measures that are dependent on the geometry used and the chosen unmixing system. Using these measures allows us to draw general conclusions on the robustness to source movement of typical BSSD algorithms. Results indicate that performance of systems that show very good separation in static reverberant environments is significantly reduced when sources move, with performance degrading to that of simple direct-path separation