Enforcing sparsity, shift-invariance and positivity in a bayesian model of polyphonic piano music


Blumensath, T. and Davies, M. E. (2005) Enforcing sparsity, shift-invariance and positivity in a bayesian model of polyphonic piano music. In, IEEE Workshop on Statistical Signal Processing, Bordeaux, FR, Institute of Electrical and Electronics Engineers . (doi:10.1109/SSP.2005.1628695 ).

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Description/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

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics
Q Science > QC Physics
Divisions: University Structure - Pre August 2011 > School of Mathematics
Faculty of Engineering and the Environment > Institute of Sound and Vibration Research > Signal Processing & Control Research Group
ePrint ID: 151933
Date Deposited: 01 Jul 2010 10:54
Last Modified: 27 Mar 2014 19:11
Publisher: Institute of Electrical and Electronics Engineers
URI: http://eprints.soton.ac.uk/id/eprint/151933

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