Autocorrelation-based beat estimation adaptive to drastic tempo change in a song

Automatic beat estimation is an essential technology not only for fundamental analysis of music, but also for the development of advanced music applications such as DJ mixing. In this paper, we propose an autocorrelation based beat estimation method, which, unlike existing methods, is capable of accurately detecting the position of beats, even from songs with drastic change of tempo. Our proposal consists of two major steps. First, the approximate positions of the beats are pre-estimated by a long-sized analysis window. Next, the preestimated beats are verified by using a short analysis window. These steps are repetitively executed until the beat estimation results converge. Experiments conducted with audio signals and songs with artificially applied tempo changes have proved that our proposal can detect beats with high accuracy.