Single-channel blind separation using L 1-sparse complex non-negative matrix factorization for acoustic signals

P. Parathai, W. L. Woo*, S. S. Dlay, Bin Gao

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

25 Citations (Scopus)

Abstract

An innovative method of single-channel blind source separation is proposed. The proposed method is a complex-valued non-negative matrix factorization with probabilistically optimal L1-norm sparsity. This preserves the phase information of the source signals and enforces the inherent structures of the temporal codes to be optimally sparse, thus resulting in more meaningful parts factorization. An efficient algorithm with closed-form expression to compute the parameters of the model including the sparsity has been developed. Real-time acoustic mixtures recorded from a single-channel are used to verify the effectiveness of the proposed method.

Original languageEnglish
Pages (from-to)EL124-EL129
JournalJournal of the Acoustical Society of America
Volume137
Issue number1
Early online date6 Jan 2015
DOIs
Publication statusPublished - 2015

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