A tutorial on onset detection in music signals

Juan Pablo Bello, Laurent Daudet, Samer Abdallah, Chris Duxbury, Mike Davies, Mark B. Sandler

Research output: Contribution to journalArticle

Abstract

Note onset detection and localization is useful in a number of analysis and indexing techniques for musical signals. The usual way to detect onsets is to look for "transient" regions in the signal, a notion that leads to many definitions: a sudden burst of energy, a change in the short-time spectrum of the signal or in the statistical properties, etc. The goal of this paper is to review, categorize, and compare some of the most commonly used techniques for onset detection, and to present possible enhancements. We discuss methods based on the use of explicitly predefined signal features: the signal's amplitude envelope, spectral magnitudes and phases, time-frequency representations; and methods based on probabilistic signal models: model-based change point detection, surprise signals, etc. Using a choice of test cases, we provide some guidelines for choosing the appropriate method for a given application.

Original languageEnglish (US)
Pages (from-to)1035-1046
Number of pages12
JournalIEEE Transactions on Speech and Audio Processing
Volume13
Issue number5
DOIs
StatePublished - Sep 1 2005

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Keywords

  • Attack transcients
  • Audio
  • Note segmentation
  • Novelty detection

ASJC Scopus subject areas

  • Software
  • Acoustics and Ultrasonics
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

Cite this

Bello, J. P., Daudet, L., Abdallah, S., Duxbury, C., Davies, M., & Sandler, M. B. (2005). A tutorial on onset detection in music signals. IEEE Transactions on Speech and Audio Processing, 13(5), 1035-1046. https://doi.org/10.1109/TSA.2005.851998