Tempo and beat analysis of acoustic musical signals.
A method is presented for using a small number of bandpass filters and banks of parallel comb filters to analyze the tempo of, and extract the beat from, musical signals of arbitrary polyphonic complexity and containing arbitrary timbres. This analysis is performed causally, and can be used predictively to guess when beats will occur in the future. Results in a short validation experiment demonstrate that the performance of the algorithm is similar to the performance of human listeners in a variety of musical situations. Aspects of the algorithm are discussed in relation to previous high-level cognitive models of beat tracking.
Scheirer
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Machine Listening Group, MIT Media Laboratory, Cambridge, Massachusetts 02139, USA. eds@media.mit.edu
D000162:Acoustics; D000465:Algorithms; D003071:Cognition / Q000502:physiology; D006801:Humans; D009146:Music; D010507:Periodicity