On tempo tracking: Tempogram representation and Kalman filtering
Berlin : The Berliner Kulturveranstaltungs GmbH
InZannos, I. (ed.), Proceedings of 2000 International Computer Music Conference, pp. 352-355
Article in monograph or in proceedings
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SW OZ DCC AI
Zannos, I. (ed.), Proceedings of 2000 International Computer Music Conference
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.
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