Multiple sound sources localization using the spatially mapped GCC functions

A variety of methods for sound source localization have been developed recently and applied to several applications such as surveillance, auditory scene analysis for hearing aids, robot auditory system and so on. In the previous work, we proposed the sound source localization using the spatially mapped GCC functions based on TDOA under the single source assumption for robot auditory system. However, multi-talker case is general in human-robot interaction. Therefore, multiple source localization approaches are necessary. In this paper, we confirm the feasibility of multiple sources localization of the proposed method with white noise signals. Experimental results with white noise signals show that it is possible for the proposed method to estimate the multiple sources location when sources are uncorrelated and we can kwon that peak value of the summed GCC function depends on the source power. Moreover, experiments with human speeches in the real environment are carried out to evaluate the performance of the proposed method. These results observe that the proposed method can estimate the multiple source locations precisely and simultaneously.