Real-time multiple DOA estimation of speech sources in wireless acoustic sensor networks

Abstract

Indoor localization of multiple speech sources in wireless acoustic sensor networks (WASNs) is an open and interesting problem with many practical applications, but the presence of noise and reverberations complicates the problem. In this paper, a distributed algorithm for multiple DOA estimation of speech sources in WASNs is presented. The method exploits the sparsity of speech sources in the time-frequency domain to obtain DOA estimations locally in each node of the network. The DOA estimations of different nodes are further combined to increase the accuracy of the local DOA estimations. Since the local DOAs are estimated using only the microphones of the same node, the synchronization between input channels and localization of the microphones from different nodes are not an issue.