Real-Time Beat EstimationUsing Feature Extraction

  • Kristoffer Jensen
  • Tue Haste Andersen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2771)


This paper presents a novel method for the estimation of beat interval from audio files. As a first step, a feature extracted from the waveform is used to identify note onsets. The estimated note onsets are used as input to a beat induction algorithm, where the most probable beat interval is found. Several enhancements over existing beat estimation systems are proposed in this work, including methods for identifying the optimum audio feature and a novel weighting system in the beat induction algorithm. The resulting system works in real-time, and is shown to work well for a wide variety of contemporary and popular rhythmic music. Several real-time music control systems have been made using the presented beat estimation method.


Audio Feature Music Piece High Frequency Content Rhythmic Structure Peak Detection Algorithm 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Kristoffer Jensen
    • 1
  • Tue Haste Andersen
    • 1
  1. 1.Department of Computer ScienceUniversity of CopenhagenCopenhagenDenmark

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