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On Detecting Target Acoustic Signals Based on Non-negative Matrix Factorization

Yu Gwang JIN, Nam Soo KIM

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Summary :

In this paper, we propose a novel target acoustic signal detection approach which is based on non-negative matrix factorization (NMF). Target basis vectors are trained from the target signal database through NMF, and input vectors are projected onto the subspace spanned by these target basis vectors. By analyzing the distribution of time-varying normalized projection error, the optimal threshold can be calculated to detect the target signal intervals during the entire input signal. Experimental results show that the proposed algorithm can detect the target signal successfully under various signal environments.

Publication
IEICE TRANSACTIONS on Information Vol.E93-D No.4 pp.922-925
Publication Date
2010/04/01
Publicized
Online ISSN
1745-1361
DOI
10.1587/transinf.E93.D.922
Type of Manuscript
LETTER
Category
Pattern Recognition

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