Note Onset Detection via Nonnegative Factorization of Magnitude Spectrum. (12th June 2008)

• Record Type: Journal Article
• Authors: Wang Wang, Wenwu Wenwu; Luo Luo, Yuhui Yuhui; Chambers Chambers, Jonathon A. Jonathon A.; Sanei Sanei, Saeid Saeid
• Other Names: Theodoridis Theodoridis Sergios Sergios Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2008(2008)
• Publication Date: 2008-06-12
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2008/231367
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : A novel approach for onset detection of musical notes from audio signals is presented. In contrast to most commonly used conventional approaches, the proposed method features new detection functions constructed from the linear temporal bases that are obtained from the decomposition of musical spectra using nonnegative matrix factorization (NMF). Three forms of detection function, namely, first-order difference function, psychoacoustically motivated relative difference function, and constant-balanced relative difference function, are considered. As the approach works directly on input data, no prior knowledge or statistical information is therefore required. Practical issues, including the choice of the factorization rank and detection robustness to instruments, are also examined experimentally. Due to the scalability issue with the generated nonnegative matrix, the proposed method is only applied to relatively short, single instrument (or voice) recordings. Numerical examples are provided to show the good performance of the proposed method, including comparisons between the three detection functions.