Abstract
A simple note onset detection system for music is presented in this work. To detect onsets, a 1/12 octave filterbank is simulated in the frequency domain and the band derivatives in time are considered. The first harmonics of a tuned instrument are close to the center frequency of these bands and, in most instruments, these harmonics are those with the highest amplitudes. The goal of this work is to make a musically motivated system which is sensitive on onsets in music but robust against the spectrum variations that occur at times that do not represent onsets. Therefore, the system tries to find semitone variations, which correspond to note onsets. Promising results are presented for this real time onset detection system.
Keywords
- Actual Onset
- Onset Detection
- Octave Band
- Voice Behaviour
- Music Information Retrieval
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Chapter PDF
References
Klapuri, A.: Sound Onset Detection by Applying Psychoacoustic Knowledge. In: IEEE Int. Conf. on Acoustics, Speech and Signal Processing, ICASSP, Phoenix, USA, March 15-19, pp. 3089–3092 (1999)
Goto, M., Muraoka, Y.: Beat tracking based on multiple-agent architecture — A real-time beat tracking system for audio signals. In: Proc. of the Second Int. Conf. on Multi-Agent Systems, pp. 103–110 (December 1996)
Bello, J.P., Daudet, L., Abdallah, S., Duxbury, C., Davies, M., Sandler, M.B.: A tutorial on onset detection in music signals. IEEE Transactions on Speech and Audio Processing 13(5), 1035–1047 (2005)
Scheirer, E.D.: Tempo and beat analysis of acoustic musical signals. J. Acoust. Soc. Am. 103(1), 588–601 (1998)
Duxbury, C., Sandler, M., Davies, M.: A hybrid approach to musical note onset detection. In: Proc. Digital Audio Effects Conference, DAFX (2002)
Goto, M., Muraoka, Y.: A Real-Time Beat Tracking System for Audio Signals. In: Proc. of the 1995 Int. Computer Music Conference, pp. 171–174 (1995)
Bilmes, J.: Timing is of the Essence: Perceptual and Computational Techniques for Representing, Learning and Reproducing Expressive Timing in Percusive Rhythm. MSc Thesis, MIT (1993)
Goto, M.: RWC music database, published RWC-MDB/, at http://staff.aist.go.jp/m.goto/
Moore, B.C.J.: An introduction to the Psychology of Hearing, 5th edn. Academic Press, London (1997)
Young, S., Kershaw, D., Odell, J., Ollason, D., Valtchev, V., Woodland, P.: The HTK book (for HTK version 3.1) Cambridge University (2000)
Leveau, P., Daudet, L., Richard, G.: Methodology and tools for the evaluation of automatic onset detection algorithms in music. In: Proc. of the Int. Symposium on Music Information Retrieval (ISMIR), Barcelona (2004)
Rodet, X., Escribe, J., Durignon, S.: Improving score to audio alignment: Percussion alignment and Precise Onset Estimation. In: Proc. of the 2004 Int. Computer Music Conference, pp. 450–453 (November 2004)
Lerch, A., Klich, I.: On the Evaluation of Automatic Onset Tracking Systems. In: White Paper, Berlin, Germany (April 2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pertusa, A., Klapuri, A., Iñesta, J.M. (2005). Recognition of Note Onsets in Digital Music Using Semitone Bands. In: Sanfeliu, A., Cortés, M.L. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2005. Lecture Notes in Computer Science, vol 3773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11578079_90
Download citation
DOI: https://doi.org/10.1007/11578079_90
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29850-2
Online ISBN: 978-3-540-32242-9
eBook Packages: Computer ScienceComputer Science (R0)
Publish with us
-
Published in cooperation with
http://www.iapr.org/
