dc.contributor.author | Homer, ST | en_US |
dc.contributor.author | Harley, N | en_US |
dc.contributor.author | Wiggins, G | en_US |
dc.date.accessioned | 2024-04-02T14:32:52Z | |
dc.date.available | 2024-03-08 | en_US |
dc.identifier.issn | 2514-4820 | en_US |
dc.identifier.uri | https://qmro.qmul.ac.uk/xmlui/handle/123456789/95856 | |
dc.description.abstract | We present a novel approach to representing perceptual and cognitive knowledge, spectral knowledge representation, that is focused on the oscillatory behaviour of the brain. The model is presented in the context of a larger hypothetical cognitive architecture. The model uses literal representations of waves to describe the dynamics of neural assemblies as they process perceived input. We show how the model can be applied to representations of sound, and usefully model music perception, specifically harmonic distance. We demonstrate that the model naturally captures both pitch and chord/key distance as empirically measured by Krumhansl and Kessler, thereby providing an underlying mechanism from which their toroidal model might arise. We evaluate our model with respect to those of Milne and others. | en_US |
dc.format.extent | ? - ? (23) | en_US |
dc.language | English | en_US |
dc.publisher | Ubiquity Press | en_US |
dc.relation.ispartof | Journal of Cognition | en_US |
dc.subject | Music perception; spectral analysis; key affinity; key distance; resonance; cognitive modelling; knowledge representation; Hilbert space; dynamical systems | en_US |
dc.title | Modelling of Musical Perception using Spectral Knowledge Representation | en_US |
dc.type | Article | |
dc.rights.holder | © 2024 Published by Ubiquity Press | |
dc.identifier.doi | 10.5334/joc.356 | en_US |
pubs.notes | Not known | en_US |
pubs.publication-status | Accepted | en_US |
pubs.publisher-url | https://www.ubiquitypress.com/ | en_US |
dcterms.dateAccepted | 2024-03-08 | en_US |
rioxxterms.funder | Default funder | en_US |
rioxxterms.identifier.project | Default project | en_US |