Localization and tracking for simultaneous speakers based on time-frequency method and Probability Hypothesis Density filter

Abstract

In this paper we present the two steps system of localization and tracking to work in context of simultaneous speakers. The localization algorithm is based on time-frequency method which uses an array of three microphones and it enables to locate multiple sound sources in a single time-frame. Localization results with missing detection and clutter are post-processed by the Probability Hypothesis Density (PHD) filter - based tracking algorithm to estimate the smoothed trajectory of each speaker. The experiments carried out on real data recording show that our method outperforms the multi-target particle filter (MTPF) - based algorithm and is effective in practical application of human-robot interaction.