Abstract
Speech separation is still a challenging issue in acoustic signal processing. To deal with this problem, sparse methods are usually employed when there are more sources than sensors (underdetermined problem). In this paper, a two-microphone separation method is presented. The proposed algorithm is based on grouping time-frequency points with similar direction-of-arrival (DOA) using a multi-level thresholding approach. The thresholds are calculated via the maximization of the interclass variance between DOA estimates and allow to identify angular sections wherein the speakers are located with a strong likelihood. Separation is finally performed by means of time-frequency masks. Several experiments conducted under different mixing scenarios are discussed, showing the benefits of the proposed approach.
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