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  1. Feature Statistics Modulate the Activation of Meaning During Spoken Word Processing.Barry J. Devereux, Kirsten I. Taylor, Billi Randall, Jeroen Geertzen & Lorraine K. Tyler - 2016 - Cognitive Science 40 (2):325-350.
    Understanding spoken words involves a rapid mapping from speech to conceptual representations. One distributed feature-based conceptual account assumes that the statistical characteristics of concepts’ features—the number of concepts they occur in and likelihood of co-occurrence —determine conceptual activation. To test these claims, we investigated the role of distinctiveness/sharedness and correlational strength in speech-to-meaning mapping, using a lexical decision task and computational simulations. Responses were faster for concepts with higher sharedness, suggesting that shared features are facilitatory in tasks like lexical decision (...)
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  • Automatic Extraction of Property Norm‐Like Data From Large Text Corpora.Colin Kelly, Barry Devereux & Anna Korhonen - 2014 - Cognitive Science 38 (4):638-682.
    Traditional methods for deriving property-based representations of concepts from text have focused on either extracting only a subset of possible relation types, such as hyponymy/hypernymy (e.g., car is-a vehicle) or meronymy/metonymy (e.g., car has wheels), or unspecified relations (e.g., car—petrol). We propose a system for the challenging task of automatic, large-scale acquisition of unconstrained, human-like property norms from large text corpora, and discuss the theoretical implications of such a system. We employ syntactic, semantic, and encyclopedic information to guide our extraction, (...)
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  • The roles of shared vs. distinctive conceptual features in lexical access.Harrison E. Vieth, Katie L. McMahon & Greig I. de Zubicaray - 2014 - Frontiers in Psychology 5.
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