Robust Tracking of Multiple Sound Sources by Spatial Integration of Room And Robot Microphone Arrays

Abstract

Sound source tracking is an important function for a robot operating in a daily environment, because the robot should recognize where a sound event such as speech, music and other environmental sounds originates from. This paper addresses sound source tracking by integrating a room and a robot microphone array. The room microphone array consists of 64 microphones attached to the walls. It provides 2D (x-y) sound source localization based on a weighted delay-and-sum beamforming method. The robot microphone array consists of eight microphones installed on a robot head, and localizes multiple sound sources in azimuth. The localization results are integrated to track sound sources by using a particle filter for multiple sound sources. The experimental results show that particle filter based integration reduces localization errors and provides accurate and robust 2D sound source tracking.