Context variability promotes generalization in reading aloud: Insight from a neural network simulation
dc.contributor.author | Miller, ID | |
dc.contributor.author | Dumay, N | |
dc.contributor.author | Pitt, M | |
dc.contributor.author | Lam, B | |
dc.contributor.author | Armstrong, BC | |
dc.date.accessioned | 2021-01-12T09:32:54Z | |
dc.date.issued | 2020-08-01 | |
dc.description.abstract | How do neural network models of quasiregular domains learn to represent knowledge that varies in its consistency with the domain, and generalize this knowledge appropriately? Recent work focusing on spelling-to-sound correspondences in English proposes that a graded “warping” mechanism determines the extent to which the pronunciation of a newly learned word should generalize to its orthographic neighbors. We explored the micro-structure of this proposal by training a network to pronounce new made-up words that were consistent with the dominant pronunciation (regulars), were comprised of a completely unfamiliar pronunciation (exceptions), or were consistent with a subordinate pronunciation in English (ambiguous). Crucially, by training the same spelling-to-sound mapping with either one or multiple items, we tested whether variation in adjacent, within-item context made a given pronunciation more able to generalize. This is exactly what we found. Context variability, therefore, appears to act as a modulator of the warping in quasiregular domains. | en_GB |
dc.description.sponsorship | Economic and Social Research Council (ESRC) | en_GB |
dc.description.sponsorship | NSERC | en_GB |
dc.description.sponsorship | CFI | en_GB |
dc.identifier.citation | COGSCI 2020: 42nd Annual Meeting of the Cognitive Science Society. Virtual, 29 July - 1 August 2020, pp. 363 - 369 | en_GB |
dc.identifier.grantnumber | ES/R006288/1 | en_GB |
dc.identifier.grantnumber | DG 502584 | en_GB |
dc.identifier.grantnumber | JELF/ORF 36578 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/124367 | |
dc.language.iso | en | en_GB |
dc.publisher | Cognitive Science Society | en_GB |
dc.relation.url | https://cognitivesciencesociety.org/cogsci-2020/ | en_GB |
dc.relation.url | https://cogsci.mindmodeling.org/2020/ | en_GB |
dc.rights | ©2020 The Author(s). Open access. This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY). | en_GB |
dc.subject | quasiregularity | en_GB |
dc.subject | neural network models | en_GB |
dc.subject | context variability | en_GB |
dc.subject | read aloud | en_GB |
dc.subject | spelling-to-sound correspondences | en_GB |
dc.subject | reading acquisition | en_GB |
dc.title | Context variability promotes generalization in reading aloud: Insight from a neural network simulation | en_GB |
dc.type | Conference paper | en_GB |
dc.date.available | 2021-01-12T09:32:54Z | |
dc.description | This is the final version. Available from the Cognitive Science Society via the link in this record | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
exeter.funder | ::Economic and Social Research Council (ESRC) | en_GB |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2020-08-01 | |
rioxxterms.type | Conference Paper/Proceeding/Abstract | en_GB |
refterms.dateFCD | 2021-01-12T09:28:48Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2021-01-12T09:32:58Z | |
refterms.panel | A | en_GB |
refterms.depositException | publishedGoldOA |
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