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Music Signal Separation by Orthogonality and Maximum-Distance Constrained Nonnegative Matrix Factorization with Target Signal Information

In this paper, we address the separation of multiple instrumental sources based on semi-supervised nonnegative matrix factorization (SNMF) and propose a new constrained SNMF. Recently, various types of SNMF have been proposed. In particular, we focus our attention on one type of SNMF that utilizes information on a priori bases. Indeed, this type of SNMF can achieve better separation performance. However, SNMF without are any constraint between a priori bases and other bases often degrades separation performance. Thus, we propose a new SNMF that imposes a constraint between a priori bases and other bases. An experimental result shows the efficacy of the proposed constrained SNMF.

Authors: Yagi, Kosuke; Takahashi, Yu; Saruwatari, Hiroshi; Shikano, Kiyohiro; Kondo, Kazunobu
Affiliations: Nara Institute of Science and Technology, Nara, Japan; Yamaha Corporate Research & Development Center, Shizuoka, Japan(See document for exact affiliation information.)
AES Conference:45th International Conference: Applications of Time-Frequency Processing in Audio (March 2012)
Paper Number:2-5 Import into BibTeX
Subject:Representation of Audio

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