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dc.contributor.authorYela, DFen_US
dc.contributor.authorStowell, Den_US
dc.contributor.authorSandler, Men_US
dc.date.accessioned2019-05-16T09:45:47Z
dc.identifier.urihttps://qmro.qmul.ac.uk/xmlui/handle/123456789/57578
dc.descriptionSource code available at https://github.com/delialia/vgspectra Updated Figure 1 (thanks Daniel Stoller!)en_US
dc.descriptionEuropean Signal Processing Conference (EUSIPCO)en_US
dc.description.abstractGraph theory is emerging as a new source of tools for time series analysis. One promising method is to transform a signal into its visibility graph, a representation which captures many interesting aspects of the signal. Here we introduce the visibility graph for audio spectra and propose a novel representation for audio analysis: the spectral visibility graph degree. Such representation inherently captures the harmonic content of the signal whilst being resilient to broadband noise. We present experiments demonstrating its utility to measure robust similarity between harmonic signals in real and synthesised audio data. The source code is available online.en_US
dc.subjectcs.SDen_US
dc.subjectcs.SDen_US
dc.subjecteess.ASen_US
dc.titleSpectral Visibility Graphs: Application to Similarity of Harmonic Signalsen_US
dc.typeConference Proceeding
dc.rights.holder© The Author(s) 2019
pubs.author-urlhttp://arxiv.org/abs/1903.01976v3en_US
pubs.notesNot knownen_US
rioxxterms.funderDefault funderen_US
rioxxterms.identifier.projectDefault projecten_US


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