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 |
| Item ID: | 151933 |
| Date Deposited: | 01 Jul 2010 10:54 |
| Last Modified: | 11 Sep 2012 13:52 |
| Contributors: | Blumensath, T. (Author) Davies, M. E. (Author) |
| Date: | July 2005 |
| Status: | Published |
| Publisher: | Institute of Electrical and Electronics Engineers |
| URI: | http://eprints.soton.ac.uk/id/eprint/151933 |
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