Music segment similarity using 2D-fourier magnitude coefficients

Oriol Nieto, Juan Pablo Bello

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Music segmentation is the task of automatically identifying the different segments of a piece. In this work we present a novel approach to cluster the musical segments based on their acoustic similarity by using 2D-Fourier Magnitude Coefficients (2D-FMCs). These coefficients, computed from a chroma representation, significantly simplify the problem of clustering the different segments since they are key transposition and phase shift invariant. We explore various strategies to obtain the 2D-FMC patches that represent entire segments and apply k-means to label them. Finally, we discuss possible ways of estimating k and compare our competitive results with the current state of the art.

Original languageEnglish (US)
Title of host publication2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages664-668
Number of pages5
ISBN (Print)9781479928927
DOIs
StatePublished - 2014
Event2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 - Florence, Italy
Duration: May 4 2014May 9 2014

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
CountryItaly
CityFlorence
Period5/4/145/9/14

Keywords

  • 2D-Fourier Transform
  • Clustering
  • Music Segmentation

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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  • Cite this

    Nieto, O., & Bello, J. P. (2014). Music segment similarity using 2D-fourier magnitude coefficients. In 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 (pp. 664-668). [6853679] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2014.6853679