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Download fileNon-negative matrix factorization for note onset detection of audio signals
conference contribution
posted on 2009-12-02, 12:34 authored by Wenwu Wang, Yuhui Luo, Jonathon Chambers, Saeid SaneiA 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.
History
School
- Mechanical, Electrical and Manufacturing Engineering
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. 447-452Publisher
© IEEEVersion
- VoR (Version of Record)
Publication date
2006Notes
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.ISBN
1424406560ISSN
1551-2541Language
- en