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Báo cáo hóa học: "Research Article Note Onset Detection via Nonnegative Factorization of Magnitude Spectrum"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Note Onset Detection via Nonnegative Factorization of Magnitude Spectrum | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008 Article ID 231367 15 pages doi 10.1155 2008 231367 Research Article Note Onset Detection via Nonnegative Factorization of Magnitude Spectrum Wenwu Wang 1 Yuhui Luo 2 3 Jonathon A. Chambers 4 and Saeid Sanei5 1 Centre for Vision Speech and Signal Processing University of Surrey Guildford GU2 7XH United Kingdom 2 Samsung Electronics Research Institute Communication House Staines TW18 4QE United Kingdom 3 Winton Capital Management Ltd. London W8 6LS United Kingdom 4 Advanced Signal Processing Research Group Department of Electronic and Electrical Engineering Loughborough University Loughborough Leics LE11 3TU United Kingdom 5 Centre of Digital Signal Processing Cardiff University Cardiff CF24 3AA United Kingdom Correspondence should be addressed to Wenwu Wang w.wang@surrey.ac.uk Received 6 November 2007 Revised 20 February 2008 Accepted 6 May 2008 Recommended by Sergios Theodoridis 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 .