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Lookup NU author(s): Dr Bin Gao,
Dr Li Khor,
Dr Wai Lok Woo,
Professor Satnam Dlay,
Dr Cheng Chin
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We present a novel approach to solve the problem of single channel source separation (SCSS) based on filterbank technique and sparse non-negative matrix two dimensional deconvolution (SNMF2D). The proposed approach does not require training information of the sources and therefore, it is highly suited for practicality of SCSS. The major problem of most existing SCSS algorithms lies in their inability to resolve the mixing ambiguity in the single channel observation. Our proposed approach tackles this difficult problem by using filterbank which decomposes the mixed signal into sub-band domain. This will result the mixture in sub-band domain to be more separable. By incorporating SNMF2D algorithm, the spectral-temporal structure of the sources can be obtained more accurately. Real time test has been conducted and it is shown that the proposed method gives high quality source separation performance.
Author(s): Lu XY, Gao B, Khor LC, Woo WL, Dlay SS, Ling WK, Chin CS
Publication type: Article
Publication status: Published
Journal: Journal of Signal and Information Processing
Print publication date: 09/05/2013
ISSN (print): 2159-4465
ISSN (electronic): 2159-4481
Publisher: Scientific Research Publishing, Inc.
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