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Sparse representations of polyphonic music

Sparse representations of polyphonic music
Sparse representations of polyphonic music
We consider two approaches for sparse decomposition of polyphonic music: a time-domain approach based on a shift-invariant model, and a frequency-domain approach based on phase-invariant power spectra. When trained on an example of a MIDI-controlled acoustic piano recording, both methods produce dictionary vectors or sets of vectors which represent underlying notes, and produce component activations related to the original MIDI score. The time-domain method is more computationally expensive, but produces sample-accurate spike-like activations and can be used for a direct time-domain reconstruction. The spectral-domain method discards phase information, but is faster than the time-domain method and retains more higher-frequency harmonics. These results suggest that these two methods would provide a powerful yet complementary approach to automatic music transcription or object-based coding of musical audio.

sparse coding, independent component analysis (ica), music signal processing, automatic music transcription
0165-1684
417-431
Plumbley, Mark D.
35f7bdaa-16bf-4f8a-8b08-7a70686a26b6
Abdallah, Samer A.
ea2c5d71-5d07-4195-8d07-d764f686de14
Blumensath, Thomas
470d9055-0373-457e-bf80-4389f8ec4ead
Davies, Michael E.
bbe1dd72-273c-445f-9540-507809816198
Plumbley, Mark D.
35f7bdaa-16bf-4f8a-8b08-7a70686a26b6
Abdallah, Samer A.
ea2c5d71-5d07-4195-8d07-d764f686de14
Blumensath, Thomas
470d9055-0373-457e-bf80-4389f8ec4ead
Davies, Michael E.
bbe1dd72-273c-445f-9540-507809816198

Plumbley, Mark D., Abdallah, Samer A., Blumensath, Thomas and Davies, Michael E. (2006) Sparse representations of polyphonic music. Signal Processing, 86 (3), 417-431. (doi:10.1016/j.sigpro.2005.06.007).

Record type: Article

Abstract

We consider two approaches for sparse decomposition of polyphonic music: a time-domain approach based on a shift-invariant model, and a frequency-domain approach based on phase-invariant power spectra. When trained on an example of a MIDI-controlled acoustic piano recording, both methods produce dictionary vectors or sets of vectors which represent underlying notes, and produce component activations related to the original MIDI score. The time-domain method is more computationally expensive, but produces sample-accurate spike-like activations and can be used for a direct time-domain reconstruction. The spectral-domain method discards phase information, but is faster than the time-domain method and retains more higher-frequency harmonics. These results suggest that these two methods would provide a powerful yet complementary approach to automatic music transcription or object-based coding of musical audio.

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More information

Published date: March 2006
Keywords: sparse coding, independent component analysis (ica), music signal processing, automatic music transcription
Organisations: Signal Processing & Control Grp

Identifiers

Local EPrints ID: 142529
URI: http://eprints.soton.ac.uk/id/eprint/142529
ISSN: 0165-1684
PURE UUID: 8c611868-f077-4a77-ae6a-d17f18e5c841
ORCID for Thomas Blumensath: ORCID iD orcid.org/0000-0002-7489-265X

Catalogue record

Date deposited: 08 Apr 2010 10:27
Last modified: 24 Mar 2022 02:39

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Contributors

Author: Mark D. Plumbley
Author: Samer A. Abdallah
Author: Michael E. Davies

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