Source tracking using moving microphone arrays for robot audition - Evers,C; Dorfan,Y; Gannot,S; Naylor,PA (IEEE, 2017)
Intuitive spoken dialogues are a prerequisite for human-robot inter-action. In many practical situations, robots must be able to identifyand focus on sources of interest in the presence of interfering speak-ers. Techniques such as spatial filtering and blind source separa-tion are therefore often used, but rely on accurate knowledge of thesource location. In practice, sound emitted in enclosed environmentsis subject to reverberation and noise. Hence, sound source localiza-tion must be robust to both diffuse noise due to late reverberation, aswell as spurious detections due to early reflections. For improvedrobustness against reverberation, this paper proposes a novel ap-proach for sound source tracking that constructively exploits the spa-tial diversity of a microphone array installed in a moving robot. Inprevious work, we developed speaker localization approaches usingexpectation-maximization (EM) approaches and using Bayesian ap-proaches. In this paper we propose to combine the EM and Bayesianapproach in one framework for improved robustness against rever-beration and noise.