Binaural speech segregation based on pitch and azimuth tracking

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.