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Note onset detection using rhythmic structure

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4 Author(s)
Degara, N. ; Signal Theor. & Commun. Dept., Univ. of Vigo, Vigo, Spain ; Pena, A. ; Davies, M.E.P. ; Plumbley, M.D.

In this paper we explore the relationship between the temporal and rhythmic structure of musical audio signals. Using automatically extracted rhythmic structure we present a rhythmically-aware method to combine note onset detection techniques. Our method uses top-down knowledge of repetitions of musical events to improve detection performance by modelling the temporal distribution of onset locations. Results on a publicly available database demonstrate that using musical knowledge in this way can lead to significant improvements by reducing the number of missed and spurious detections.

Published in:

Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on

Date of Conference:

14-19 March 2010