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In this letter we present a novel speech separation scheme using two microphones. The proposed method utilizes the estimation of interaural time difference (ITD) statistics for the separation of mixed speech sources. The novelties of this paper consist in the use of Generalized Gaussian Mixture Model (GGMM) for speech separation frame by frame and cross-correlation coefficient for distributed parameter selection. The proposed model can be extended to audio enhancement. Our objective quality evaluation experiments demonstrate the effectiveness of the proposed methods and show significant quality improvements over the conventional dual ITD based methods.

Dual-channel speech separation using interaural time difference with Generalized Gaussian Mixture Model