Cemgil, T., Kappen, B., Desain, P., and Honing, H. (2000) On tempo tracking: Tempogram Representation and Kalman filtering. In Proceedings of the International Computer Music Conference, 352-355. San Francisco: ICMA. [Received distinguished paper award]

Abstract

We formulate tempo tracking in a Bayesian framework where a tempo tracker is modeled as a stochastic dynamical system. The tempo is modeled as a hidden state variable of the system and is estimated from a MIDI performance by Kalman filtering and smoothing. We also introduce the Tempogram representation, a wavelet-like multiscale expansion of a real performance, on which the Kalman filter operates.

Full paper (.pdf).

Beatles data-set (.zip)