A New Sparse Blind Source Separation Method for Determined Linear Convolutive Mixtures in Time-Frequency Domain

This paper presents a new Blind Source Separation method for linear convolutive mixtures, which exploits the sparsity of source signals in the time-frequency domain. This method especially brings a solution to the artifacts problem that affects the quality of signals separated by existing time-frequency methods. These artifacts are in fact introduced by a time-frequency masking operation, used by all these methods. Indeed, by focusing on the case of determined mixtures, we show that this problem can be solved with much less restrictive sparsity assumptions than those of existing methods. Test results show the superiority of our new proposed method over existing ones based on time-frequency masking.