SSP'05 -- Proceedings

	IEEE/SP 13th workshop on Statistical Signal Processing July, 17-20, 2005 - Bordeaux - France

Information regarding the paper

Title

Enforcing Sparsity, Shift-Invariance and Positivity in a Bayesian Model of Polyphonic Piano Music

Author(s)

Thomas Blumensath	Queen Mary University of London
Mike Davies	Queen Mary University of London

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Abstract

In this paper we develop a Bayesian method to extract individual notes from a polyphonic piano recording. The distribution of the note activation is non-negative and we therefore introduce a modified Rayleigh distribution to model this note behaviour. Sparseness of the note activation is achieved by a mixture distribution that is a mixture of a delta function and the modified Rayleigh distribution. The used learning rule requires integration over the note activations, which is done using a Gibbs Sampling Monte Carlo method. We analyse the behaviour of the algorithm using a simplified test signal as well as a real piano recording.