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A Conditional Random Field system for beat tracking

  • Thomas Fillon
  • , Cyril Joder
  • , Simon Durand
  • , Slim Essid
  • PARISSON
  • European Patent Office
  • Institut Mines-Télécom

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 Citations (Scopus)

Abstract

In the present work, we introduce a new probabilistic model for the task of estimating beat positions in a musical audio recording, instantiating the Conditional Random Field (CRF) framework. Our approach takes its strength from a sophisticated temporal modeling of the audio observations, accounting for local tempo variations which are readily represented in the CRF model proposed using well-chosen potentials. The system is experimentally evaluated by studying its performance on 3 datasets of 1394 music excerpts of various western music styles and comparatively to 4 reference systems in the light of 6 reference evaluation metrics. The results show that the proposed system tracks perceptively coherent pulses and is very effective in estimating the beat positions while further work is needed to find the correct salient tempo.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages424-428
Number of pages5
ISBN (Electronic)9781467369978
DOIs
Publication statusPublished - 4 Aug 2015
Externally publishedYes
Event40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Brisbane, Australia
Duration: 19 Apr 2014 → 24 Apr 2014

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2015-August
ISSN (Print)1520-6149

Conference

Conference40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015
Country/TerritoryAustralia
CityBrisbane
Period19/04/14 → 24/04/14

Keywords

  • Beat tracking
  • Conditional Random Fields
  • Music Information Retrieval

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