Binaural speech segregation based on pitch and azimuth tracking

Abstract

We propose an approach to binaural speech segregation in reverberation based on pitch and azimuth cues. These cues are integrated within a statistical tracking framework to estimate up to two concurrent pitch frequencies and three concurrent azimuth angles. The tracking framework implicitly estimates binary time-frequency masks by solving a data association problem, thereby performing speech segregation. Experimental results show that the proposed approach compares favorably to existing two-microphone systems in spite of less prior information. The benefit of the proposed approach is most pronounced in conditions with substantial reverberation or for closely spaced sources.