The first step in rhythm analysis is data reduction. The goal is to eliminate high-frequency information (pitch) so as to study low-frequency information (rhythm). Our data reduction is based on methods used by Sethares and Sheirer in the following articles. We are especially indebted to William Sethares for sharing his Matlab data reduction routines.
Here is an example of how the data reduction works. The original track is the first 10 seconds of ``Hristianova Kopanitsa'' from the CD Balkanology by Ivo Papasov and his Orchestra (Hannibal HNCD 1363, 1991).
Hristianova Kopanitsa, 10 second clip. A kopanitsa is a dance in 11/8 rhythm.
One method of data reduction is to filter out the high frequencies (anything perceived as pitch, say 20 Hz and above). The resulting low-frequency envelope is applied to white noise to produce a rather unpleasant sound. The rhythm is barely discernible.
Hristianova Kopanitsa, rhythm envelope applied to white noise.
Scheirer's article explains how the sound can be first separated into
21 bands of roughly half an octave. A rhythm vector is formed for
each band and used as an envelope for a typical sound of that frequency
range. The bands are numbered from low to high.
Hristianova Kopanitsa, sum of 21 rhythm bands.
Finally, let's hear the original track combined with the rhythm track above.
Hristianova Kopanitsa, original recording combined with rhythm track.