Localization of Multiple Speakers in Echoic Environments Using BSS and Speech Features for Solution of Global Permutation Ambiguity

this paper, a new algorithm is introduced for localization of multiple speakers in echoic environments. The origin of localization is based on combination of TDOA estimates of each source obtained by the BSS algorithm in the time domain. A new BSS algorithm is proposed which improves the quality and channel identification compared to a reference technique and also reduces the computational cost in some cases. To solve the global permutation ambiguity of BSS algorithms, speech features are used. Simulation results show the effectiveness of these features for solving the later problem.