Bayesian Real-time Adaptation for Interactive Performance Systems

نویسندگان

  • Ali Taylan Cemgil
  • Hilbert J. Kappen
چکیده

We introduce Bayesian online learning for real time parameter adaptation on a tempo tracking task. We employ a variational extension of the Expectation-Maximization algorithm for online parameter estimation. Simulation results on a real dataset indicate that online adaptation has the potential of capturing performer specific features in real time.

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تاریخ انتشار 2001