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Erdin Mujezinovic; Vsevolod Kapatsinski; Ruben van de Vijver – Cognitive Science, 2024
A word often expresses many different morphological functions. Which part of a word contributes to which part of the overall meaning is not always clear, which raises the question as to how such functions are learned. While linguistic studies tacitly assume the co-occurrence of cues and outcomes to suffice in learning these functions (Baer-Henney,…
Descriptors: Morphology (Languages), Phonology, Morphemes, Cues
Stevens, Jon Scott; Gleitman, Lila R.; Trueswell, John C.; Yang, Charles – Cognitive Science, 2017
We evaluate here the performance of four models of cross-situational word learning: two global models, which extract and retain multiple referential alternatives from each word occurrence; and two local models, which extract just a single referent from each occurrence. One of these local models, dubbed "Pursuit," uses an associative…
Descriptors: Semantics, Associative Learning, Probability, Computational Linguistics
Demestre, Josep; Garcia-Albea, Jose E. – Cognitive Science, 2007
Event-related brain potentials were recorded while subjects listened to sentences containing a controlled infinitival complement. Subject and object control items were used, both with 2 potential antecedents in the upper clause. Half of the sentences had a gender agreement violation between the null subject of the infinitival complement and an…
Descriptors: Form Classes (Languages), Neurolinguistics, Language Processing, Error Analysis (Language)
Hale, John – Cognitive Science, 2006
A word-by-word human sentence processing complexity metric is presented. This metric formalizes the intuition that comprehenders have more trouble on words contributing larger amounts of information about the syntactic structure of the sentence as a whole. The formalization is in terms of the conditional entropy of grammatical continuations, given…
Descriptors: Sentences, Sentence Structure, Grammar, Prediction