Please use this identifier to cite or link to this item: https://open.uns.ac.rs/handle/123456789/200
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dc.contributor.authorFilipović-Đurđević Dušicaen_US
dc.contributor.authorMilin Petaren_US
dc.date.accessioned2019-09-23T10:04:58Z-
dc.date.available2019-09-23T10:04:58Z-
dc.date.issued2019-07-01-
dc.identifier.issn00109452en_US
dc.identifier.urihttps://open.uns.ac.rs/handle/123456789/200-
dc.description.abstract© 2018 Elsevier Ltd We investigated the processing of inflected Serbian adjective forms to bring together quantitative linguistic measures from two frameworks – information theory and discrimination learning. From each framework we derived several quantitative descriptions of an inflectional morphological system and fitted two separate regression models to the processing latencies that were elicited by inflected adjectival forms presented in a visual lexical decision task. The model, which was based on lexical distributional and information theory revealed a dynamic interplay of information. The information was sensitive to syntagmatic and paradigmatic dimensions of variation; the paradigmatic information (formalized as respective relative entropies) was also modulated by lemma frequency. The discrimination learning based model revealed an equally complex pattern, involving several learning-based variables. The two models revealed strikingly similar patterns of results, as confirmed by the very high proportion of shared variance in model predictions (85.83%). Our findings add to the body of research demonstrating that complex morphological phenomena can arise as a consequence of the basic principles of discrimination learning. Learning discriminatively about inflectional paradigms and classes, and about their contextual or syntagmatic embedding, sheds light on human language-processing efficiency and on the fascinating complexity of naturally emerged language systems.en
dc.relation.ispartofCortexen
dc.titleInformation and learning in processing adjective inflectionen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.doi10.1016/j.cortex.2018.07.020-
dc.identifier.scopus2-s2.0-85053046407-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85053046407-
dc.description.versionUnknownen_US
dc.relation.lastpage227en
dc.relation.firstpage209en
dc.relation.volume116en
item.grantfulltextnone-
item.fulltextNo Fulltext-
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