Multiple sound sources localization with perception sensor network

Abstract

This paper presents a general framework for localization of multiple sound sources in Cartesian coordinate with perception sensor network (PSN). PSN consists of Kinect sensor that has a color camera, a depth camera, and an internal microphone array and our experimental pan-tilt-zoom camera with attached microphone array. Sound localization with PSN is based on three-stage analysis. Short-time narrowband directional sound localization based on Phase difference of arrival (PDOA) is obtained in every time-frequency points, utilizing the sparseness assumption of audio mixtures. Multi-sensor directional localizations are transformed to Cartesian coordinate by a simple triangulation. The results are accumulated in all frequency bins for a block of frames and then clustered to obtain mid-term broadband localization. Furthermore, the framework is able to integrate any Bayesian filtering algorithms for long-term localization. Simulation results with four arrays (each has four microphone) show that the proposed framework successfully localize three simultaneous sources where the distance among sources is about one meter.