Multiple sound-source localization and identification with a spherical microphone array and lavalier microphone data

Abstract

Spherical microphone arrays have attained a considerable amount of interest for their dynamic beamforming and tracking capabilities. Although many robust algorithms have been developed to accurately localize individual sources, multiple source localization, especially for concurrent or colocated sources, has proved to be a challenging topic. This project demonstrates a technique to isolate individual concurrent sources by using lavalier microphone data to determine the relative difference in signal energy between sources. This data is then incorporated into the source-tracking algorithm governing the beamforming spherical array, a particle filter, by allowing the rejection of frames containing concurrent source information. This improves the tracking ability of the system. [Work supported by Rensselaer HASS Fellowship, NSF No. 1631674, and CISL.]