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Li, Jiangtian; Joanisse, Marc F. – Cognitive Science, 2021
Most words in natural languages are polysemous; that is, they have related but different meanings in different contexts. This one-to-many mapping of form to meaning presents a challenge to understanding how word meanings are learned, represented, and processed. Previous work has focused on solutions in which multiple static semantic…
Descriptors: Computational Linguistics, Semantics, Ambiguity (Semantics), Language Processing
King, Daniel; Gentner, Dedre – Cognitive Science, 2022
This paper explores the processes underlying verb metaphoric extension. Work on metaphor processing has largely focused on noun metaphor, despite evidence that verb metaphor is more common. Across three experiments, we collected paraphrases of simple intransitive sentences varying in semantic strain--for example, "The motor complained"…
Descriptors: Semantics, Verbs, Figurative Language, Phrase Structure
Trott, Sean; Jones, Cameron; Chang, Tyler; Michaelov, James; Bergen, Benjamin – Cognitive Science, 2023
Humans can attribute beliefs to others. However, it is unknown to what extent this ability results from an innate biological endowment or from experience accrued through child development, particularly exposure to language describing others' mental states. We test the viability of the language exposure hypothesis by assessing whether models…
Descriptors: Models, Language Processing, Beliefs, Child Development
Cassani, Giovanni; Bianchi, Federico; Marelli, Marco – Cognitive Science, 2021
In this study, we use temporally aligned word embeddings and a large diachronic corpus of English to quantify language change in a data-driven, scalable way, which is grounded in language use. We show a unique and reliable relation between measures of language change and age of acquisition ("AoA") while controlling for frequency,…
Descriptors: English, Language Usage, Language Acquisition, Computational Linguistics
Hoppe, Dorothée B.; Rij, Jacolien; Hendriks, Petra; Ramscar, Michael – Cognitive Science, 2020
Linguistic category learning has been shown to be highly sensitive to linear order, and depending on the task, differentially sensitive to the information provided by preceding category markers ("premarkers," e.g., gendered articles) or succeeding category markers ("postmarkers," e.g., gendered suffixes). Given that numerous…
Descriptors: Discrimination Learning, Computational Linguistics, Natural Language Processing, Artificial Languages
Andrea Bruera; Yuan Tao; Andrew Anderson; Derya Çokal; Janosch Haber; Massimo Poesio – Cognitive Science, 2023
The meaning of most words in language depends on their context. Understanding how the human brain extracts contextualized meaning, and identifying where in the brain this takes place, remain important scientific challenges. But technological and computational advances in neuroscience and artificial intelligence now provide unprecedented…
Descriptors: Neurosciences, Brain Hemisphere Functions, Artificial Intelligence, Diagnostic Tests
Johns, Brendan T.; Mewhort, Douglas J. K.; Jones, Michael N. – Cognitive Science, 2019
Distributional models of semantics learn word meanings from contextual co-occurrence patterns across a large sample of natural language. Early models, such as LSA and HAL (Landauer & Dumais, 1997; Lund & Burgess, 1996), counted co-occurrence events; later models, such as BEAGLE (Jones & Mewhort, 2007), replaced counting co-occurrences…
Descriptors: Semantics, Learning Processes, Models, Prediction
Quelhas, Ana Cristina; Rasga, Célia; Johnson-Laird, P. N. – Cognitive Science, 2018
What is the relation between factual conditionals: "If A happened then B happened," and counterfactual conditionals: "If A had happened then B would have happened?" Some theorists propose quite different semantics for the two. In contrast, the theory of mental models and its computer implementation interrelates them. It…
Descriptors: Semantics, Form Classes (Languages), Discourse Analysis, Correlation
Yadav, Himanshu; Vaidya, Ashwini; Shukla, Vishakha; Husain, Samar – Cognitive Science, 2020
Much previous work has suggested that word order preferences across languages can be explained by the dependency distance minimization constraint (Ferrer-i Cancho, 2008, 2015; Hawkins, 1994). Consistent with this claim, corpus studies have shown that the average distance between a head (e.g., verb) and its dependent (e.g., noun) tends to be short…
Descriptors: Word Order, Computational Linguistics, Contrastive Linguistics, Psycholinguistics
Paape, Dario; Avetisyan, Serine; Lago, Sol; Vasishth, Shravan – Cognitive Science, 2021
We present computational modeling results based on a self-paced reading study investigating number attraction effects in Eastern Armenian. We implement three novel computational models of agreement attraction in a Bayesian framework and compare their predictive fit to the data using k-fold cross-validation. We find that our data are better…
Descriptors: Computational Linguistics, Indo European Languages, Grammar, Bayesian Statistics
Ger, Ebru; You, Guanghao; Küntay, Aylin C.; Göksun, Tilbe; Stoll, Sabine; Daum, Moritz M. – Cognitive Science, 2022
Becoming productive with grammatical categories is a gradual process in children's language development. Here, we investigated this transition process by focusing on Turkish causatives. Previous research examining spontaneous and elicited production of Turkish causatives with familiar verbs attested the onset and early stages of productivity at…
Descriptors: Turkish, Morphology (Languages), Longitudinal Studies, Computational Linguistics
Brouwer, Harm; Crocker, Matthew W.; Venhuizen, Noortje J.; Hoeks, John C. J. – Cognitive Science, 2017
Ten years ago, researchers using event-related brain potentials (ERPs) to study language comprehension were puzzled by what looked like a "Semantic Illusion": Semantically anomalous, but structurally well-formed sentences did not affect the N400 component--traditionally taken to reflect semantic integration--but instead produced a P600…
Descriptors: Diagnostic Tests, Brain Hemisphere Functions, Language Processing, Semantics
Schouwstra, Marieke; Swart, Henriëtte; Thompson, Bill – Cognitive Science, 2019
Natural languages make prolific use of conventional constituent-ordering patterns to indicate "who did what to whom," yet the mechanisms through which these regularities arise are not well understood. A series of recent experiments demonstrates that, when prompted to express meanings through silent gesture, people bypass native language…
Descriptors: Nonverbal Communication, Language Acquisition, Bayesian Statistics, Preferences
Unger, Layla; Vales, Catarina; Fisher, Anna V. – Cognitive Science, 2020
The organization of our knowledge about the world into an interconnected network of concepts linked by relations profoundly impacts many facets of cognition, including attention, memory retrieval, reasoning, and learning. It is therefore crucial to understand how organized semantic representations are acquired. The present experiment investigated…
Descriptors: Semantics, Role, Schemata (Cognition), Language Processing
Lau, Jey Han; Clark, Alexander; Lappin, Shalom – Cognitive Science, 2017
The question of whether humans represent grammatical knowledge as a binary condition on membership in a set of well-formed sentences, or as a probabilistic property has been the subject of debate among linguists, psychologists, and cognitive scientists for many decades. Acceptability judgments present a serious problem for both classical binary…
Descriptors: Grammar, Probability, Sentences, Language Research
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