Abstract
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.
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Jensen, K., Andersen, T.H. (2004). Real-Time Beat EstimationUsing Feature Extraction. In: Wiil, U.K. (eds) Computer Music Modeling and Retrieval. CMMR 2003. Lecture Notes in Computer Science, vol 2771. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39900-1_2
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DOI: https://doi.org/10.1007/978-3-540-39900-1_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20922-5
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