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Non-negative Matrix Factorisation incorporating greedy Hellinger sparse coding applied to polyphonic music transcription

O'Hanlon, K, Plumbley, MD and Sandler, M (2015) Non-negative Matrix Factorisation incorporating greedy Hellinger sparse coding applied to polyphonic music transcription In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2015), 2015-04-19 - 2015-04-24, Brisbane.

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Abstract

Non-negative Matrix Factorisation (NMF) is a commonly used tool in many musical signal processing tasks, including Automatic Music Transcription (AMT). However unsupervised NMF is seen to be problematic in this context, and harmonically constrained variants of NMF have been proposed. While useful, the harmonic constraints may be constrictive in mixed signals. We have previously observed that recovery of overlapping signal elements using NMF is improved through introduction of a sparse coding step, and propose here the incorporation of a sparse coding step using the Hellinger distance into a NMF algorithm. Improved AMT results for unsupervised NMF are reported.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
AuthorsEmailORCID
O'Hanlon, KUNSPECIFIEDUNSPECIFIED
Plumbley, MDUNSPECIFIEDUNSPECIFIED
Sandler, MUNSPECIFIEDUNSPECIFIED
Date : 19 April 2015
Identification Number : 10.1109/ICASSP.2015.7178364
Additional Information : © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Depositing User : Symplectic Elements
Date Deposited : 12 Jan 2016 16:17
Last Modified : 12 Jan 2016 16:17
URI: http://epubs.surrey.ac.uk/id/eprint/807550

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