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Non-Negative Group Sparsity with Subspace Note Modelling for Polyphonic Transcription

O'Hanlon, K, Nagano, H, Keriven, N and Plumbley, MD (2016) Non-Negative Group Sparsity with Subspace Note Modelling for Polyphonic Transcription IEEE/ACM Transactions on Audio, Speech and Language Processing, 24 (3). pp. 530-542.

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Abstract

Automatic music transcription (AMT) can be performed by deriving a pitch-time representation through decomposition of a spectrogram with a dictionary of pitch-labelled atoms. Typically, non-negative matrix factorisation (NMF) methods are used to decompose magnitude spectrograms. One atom is often used to represent each note. However, the spectrum of a note may change over time. Previous research considered this variability using different atoms to model specific parts of a note, or large dictionaries comprised of datapoints from the spectrograms of full notes. In this paper, the use of subspace modelling of note spectra is explored, with group sparsity employed as a means of coupling activations of related atoms into a pitched subspace. Stepwise and gradient-based methods for non-negative group sparse decompositions are proposed. Finally, a group sparse NMF approach is used to tune a generic harmonic subspace dictionary, leading to improved NMF-based AMT results.

Item Type: Article
Subjects : Electronic Engineering
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
AuthorsEmailORCID
O'Hanlon, KUNSPECIFIEDUNSPECIFIED
Nagano, HUNSPECIFIEDUNSPECIFIED
Keriven, NUNSPECIFIEDUNSPECIFIED
Plumbley, MDUNSPECIFIEDUNSPECIFIED
Date : 1 March 2016
Identification Number : 10.1109/TASLP.2016.2515514
Copyright Disclaimer : © 2016 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.
Uncontrolled Keywords : Science & Technology, Technology, Acoustics, Engineering, Electrical & Electronic, Engineering, Automatic music transcription, group sparsity, non-negative matrix factorisation, stepwise optimal, MATRIX FACTORIZATION, MUSIC TRANSCRIPTION, ALGORITHMS, PURSUIT, DECOMPOSITION, SMOOTHNESS, DIVERGENCE, SEPARATION, EQUATIONS, RECOVERY
Related URLs :
Depositing User : Symplectic Elements
Date Deposited : 12 May 2016 08:59
Last Modified : 12 May 2016 08:59
URI: http://epubs.surrey.ac.uk/id/eprint/810679

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