Binaural Speech Source Localization Using Template Matching of Interaural Time Difference Patterns

Abstract

In this paper we present a template based algorithm for localizing speech sources from a binaural recording. Binaural recordings are associated with head related transfer functions (HRTFs) for each direction which are specific to the object, say head, in between the two microphones. So, using these HRTFs and time-frequency representations of the binaural signals, we learn direction specific two dimensional reference templates using histograms of interaural time difference (ITD) in each frequency subband. These are called ITD pattern templates (IPTs). Test templates are then compared with each of the reference IPTs. The reference IPT, that matches best with the test template, provides the estimated direction of arrival for the test speech source. Experimental results obtained using subject_003 from the CIPIC database show that IPT based localization performs better than existing methods where the ITD distribution is modeled using Gaussian mixture model. Given n time-frequency points, we also present a method with complexity O( n) to compute the IPT, thus making it computationally efficient.