Improved Wideband Blind Adaptive System Identification Using Decorrelation Filters for the Localization of Multiple Speakers

This paper addresses the TDOA extraction problem for localizing multiple sources in noisy and reverberant environments with emphasis on speech excitation. TDOAs are estimated by performing blind adaptive MIMO system identification using a gradient-based BSS variant of the TRINICON framework. We present a novel method to improve the TDOA estimation for signals with lowpass-like spectral characteristics such as speech, for which the standard approach achieves only imperfect system identification. To this end, we propose to combine the BSS algorithm with decorrelation filters, thereby achieving a greatly improved wideband identification of the acoustical system. The approach is verified in a number of scenarios, where it provides more accurate TDOA estimates for the speaker localization at a negligible additional computational cost.