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Ronai, Eszter; Xiang, Ming – Cognitive Science, 2023
Memory limitations and probabilistic expectations are two key factors that have been posited to play a role in the incremental processing of natural language. Relative clauses (RCs) have long served as a key proving ground for such theories of language processing. Across three self-paced reading experiments, we test the online comprehension of…
Descriptors: Memory, Expectation, Language Processing, Syntax
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Garrido Rodriguez, Gabriela; Norcliffe, Elisabeth; Brown, Penelope; Huettig, Falk; Levinson, Stephen C. – Cognitive Science, 2023
We present a visual world eye-tracking study on Tseltal (a Mayan language) and investigate whether verbal information can be used to anticipate an upcoming referent. Basic word order in transitive sentences in Tseltal is Verb--Object--Subject (VOS). The verb is usually encountered first, making argument structure and syntactic information…
Descriptors: Mayan Languages, Eye Movements, Word Order, Verbs
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Evan Kidd; Gabriela Garrido Rodríguez; Sasha Wilmoth; Javier E. Garrido Guillén; Rachel Nordlinger – Cognitive Science, 2025
Sentence production is a stage-like process of mapping a conceptual representation to the linear speech signal via grammatical rules. While the typological diversity of languages is vast and thus must necessarily influence sentence production, psycholinguistic studies of diverse languages are comparatively rare. Here, we present data from a…
Descriptors: Language Planning, Language Processing, Eye Movements, Word Order
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Culbertson, Jennifer; Smolensky, Paul – Cognitive Science, 2012
In this article, we develop a hierarchical Bayesian model of learning in a general type of artificial language-learning experiment in which learners are exposed to a mixture of grammars representing the variation present in real learners' input, particularly at times of language change. The modeling goal is to formalize and quantify hypothesized…
Descriptors: Models, Bayesian Statistics, Artificial Languages, Language Acquisition
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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