Using Statistical Models of Morphology in the Search for Optimal Units of Representation in the Human Mental Lexicon

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Virpioja , S P , Lehtonen , M , Hultén , A , Kivikari , H , Salmelin , R & Lagus , K 2018 , ' Using Statistical Models of Morphology in the Search for Optimal Units of Representation in the Human Mental Lexicon ' , Cognitive Science , vol. 42 , no. 3 , pp. 939-973 . https://doi.org/10.1111/cogs.12576

Title: Using Statistical Models of Morphology in the Search for Optimal Units of Representation in the Human Mental Lexicon
Author: Virpioja, Sami Petteri; Lehtonen, Minna; Hultén, Annika; Kivikari, Henna; Salmelin, Riitta; Lagus, Krista
Contributor organization: Cognitive Brain Research Unit
Department of Psychology and Logopedics
Department of Social Research (2010-2017)
Date: 2018-04
Language: eng
Number of pages: 35
Belongs to series: Cognitive Science
ISSN: 0364-0213
DOI: https://doi.org/10.1111/cogs.12576
URI: http://hdl.handle.net/10138/310146
Abstract: Determining optimal units of representing morphologically complex words in the mental lexicon is a central question in psycholinguistics. Here, we utilize advances in computational sciences to study human morphological processing using statistical models of morphology, particularly the unsupervised Morfessor model that works on the principle of optimization. The aim was to see what kind of model structure corresponds best to human word recognition costs for multimorphemic Finnish nouns: a model incorporating units resembling linguistically defined morphemes, a whole-word model, or a model that seeks for an optimal balance between these two extremes. Our results showed that human word recognition was predicted best by a combination of two models: a model that decomposes words at some morpheme boundaries while keeping others unsegmented and a whole-word model. The results support dual-route models that assume that both decomposed and full-form representations are utilized to optimally process complex words within the mental lexicon.
Subject: 6162 Cognitive science
Mental lexicon
Lexical decision
Word recognition
Psycholinguistics
113 Computer and information sciences
statistical language modeing
minimum description length principle
unsupervised learning
6121 Languages
morphology
Peer reviewed: Yes
Rights: cc_by_nc
Usage restriction: openAccess
Self-archived version: publishedVersion


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