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Title: Non-negative matrix factorization for note onset detection of audio signals
Authors: Wang, Wenwu
Luo, Yuhui
Chambers, Jonathon
Sanei, Saeid
Issue Date: 2006
Publisher: © IEEE
Citation: WANG, W. ... et al, 2006. Non-negative matrix factorization for note onset detection of audio signals. IN: Proceedings of the 16th IEEE Signal Processing Workshop on Machine Learning for Signal Processing, Arlington, VA, 11-14 September 2006, pp. 447-452
Abstract: A novel approach using non-negative matrix factorization (NMF) for onset detection of musical notes from audio signals is presented. Unlike most commonly used conventional approaches, the proposed method exploits a new detection function constructed from the linear temporal bases that are obtained from a non-negative matrix decomposition of musical spectra. Both first-order difference and psychoacoustically motivated relative difference functions of the temporal profile are considered. As the approach works directly on input data, no prior knowledge or statistical information is thereby required. A practical issue of the choice of the factorization rank is also examined experimentally. Numerical examples are provided to show the performance of the proposed method.
Description: This is a conference paper [© IEEE]. It is also available at: http://ieeexplore.ieee.org/ Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Version: Published
DOI: 10.1109/MLSP.2006.275592
URI: https://dspace.lboro.ac.uk/2134/5563
ISBN: 1424406560
ISSN: 1551-2541
Appears in Collections:Conference Papers and Contributions (Electronic, Electrical and Systems Engineering)

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