Blind signal decompositions for automatic transcription of polyphonic music: NMF and K-SVD on the benchmark

Abstract : This paper investigates on the behavior of two blind signal decomposition algorithms, non negative matrix factorization (NMF) and non negative K-SVD (NKSVD), in a polyphonic music transcription task. State-of-the-art transcription systems are based on a frame-byframe, low-level approach; blind systems could be an alternative to them. Two raw but effective audio-to-MIDI systems are proposed and evaluated. Performances are similar, but in favor of NMF, which is more robust to initialization, choice of the order and computationnally less costly.
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Communication dans un congrès
Proc. of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2007, Honolulu, Hawaii, United States. 1, pp.65--68, 2007
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Nancy Bertin, Roland Badeau, Gaël Richard. Blind signal decompositions for automatic transcription of polyphonic music: NMF and K-SVD on the benchmark. Proc. of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2007, Honolulu, Hawaii, United States. 1, pp.65--68, 2007. 〈hal-00945282〉

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