Abstract
A novel single-channel blind source separation (SCBSS) algorithm using Cochleagram-mask based technique is presented in this paper. The proposed system offers benefits such as resemblance of a stereo signal concept given by one microphone, independent of initialization and a priori knowledge of the sources, improved performance with sources which do not strictly satisfy the windowed-disjoint orthogonality (WDO) condition and reduced computational complexity without the need for iterative optimizations. The separation process comprises three steps: 1) estimation of source characteristics, where the source signals are modelled by the autoregressive process and 2) construction of masks using only the single-channel mixture 3) binary TF masks modification through cochleagram processing 4) improve separation depth through independent component analysis (ICA). Experiment results revealed at least 3dB signal to interference ratio comparing to previous systems [1].
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