Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 1 |
Since 2016 (last 10 years) | 7 |
Since 2006 (last 20 years) | 10 |
Descriptor
Source
Cognitive Science | 10 |
Author
Arunachalam, Sudha | 1 |
Boroditsky, Lera | 1 |
Choi, Soonja | 1 |
Delle Luche, Claire | 1 |
Frank, Michael C. | 1 |
Gleitman, Lila R. | 1 |
Hung, Jinyi | 1 |
Kaufmann, Stefan | 1 |
Lev-Ari, Shiri | 1 |
Noveck, Ira A. | 1 |
Ouyang, Long | 1 |
More ▼ |
Publication Type
Journal Articles | 10 |
Reports - Research | 9 |
Reports - Descriptive | 1 |
Education Level
Audience
Location
Massachusetts (Boston) | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
de Varda, Andrea Gregor; Strapparava, Carlo – Cognitive Science, 2022
The present paper addresses the study of non-arbitrariness in language within a deep learning framework. We present a set of experiments aimed at assessing the pervasiveness of different forms of non-arbitrary phonological patterns across a set of typologically distant languages. Different sequence-processing neural networks are trained in a set…
Descriptors: Learning Processes, Phonology, Language Patterns, Language Classification
Yun, Hongoak; Choi, Soonja – Cognitive Science, 2018
This study has two goals. First, we present much-needed empirical linguistic data and systematic analyses on the spatial semantic systems in English and Korean, two languages that have been extensively compared to date in the debate on spatial language and spatial cognition. We conduct our linguistic investigation comprehensively, encompassing the…
Descriptors: Semantics, Spatial Ability, Contrastive Linguistics, Korean
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
Arunachalam, Sudha – Cognitive Science, 2017
Children have difficulty comprehending novel verbs in the double object dative (e.g., "Fred blicked the dog a stick") as compared to the prepositional dative (e.g., "Fred blicked a stick to the dog"). We explored this pattern with 3 and 4 year olds (N = 60). In Experiment 1, we replicated the documented difficulty with the…
Descriptors: Preschool Children, Language Acquisition, Semantics, Verbs
Ouyang, Long; Boroditsky, Lera; Frank, Michael C. – Cognitive Science, 2017
Computational models have shown that purely statistical knowledge about words' linguistic contexts is sufficient to learn many properties of words, including syntactic and semantic category. For example, models can infer that "postman" and "mailman" are semantically similar because they have quantitatively similar patterns of…
Descriptors: Semiotics, Computational Linguistics, Syntax, Semantics
Lev-Ari, Shiri – Cognitive Science, 2016
People differ in the size of their social network, and thus in the properties of the linguistic input they receive. This article examines whether differences in social network size influence individuals' linguistic skills in their native language, focusing on global comprehension of evaluative language. Study 1 exploits the natural variation in…
Descriptors: Social Networks, Semantics, Language Processing, Dining Facilities
Kaufmann, Stefan – Cognitive Science, 2013
The rise of causality and the attendant graph-theoretic modeling tools in the study of counterfactual reasoning has had resounding effects in many areas of cognitive science, but it has thus far not permeated the mainstream in linguistic theory to a comparable degree. In this study I show that a version of the predominant framework for the formal…
Descriptors: Semantics, Linguistic Theory, Form Classes (Languages), Causal Models
Reilly, Jamie; Hung, Jinyi; Westbury, Chris – Cognitive Science, 2017
Arbitrary symbolism is a linguistic doctrine that predicts an orthogonal relationship between word forms and their corresponding meanings. Recent corpora analyses have demonstrated violations of arbitrary symbolism with respect to concreteness, a variable characterizing the sensorimotor salience of a word. In addition to qualitative semantic…
Descriptors: Computational Linguistics, Semantics, Word Recognition, Auditory Perception
Ramscar, Michael; Yarlett, Daniel – Cognitive Science, 2007
In a series of studies children show increasing mastery of irregular plural forms (such as "mice") simply by producing erroneous over-regularized versions of them (such as "mouses"). We explain this phenomenon in terms of successive approximation in imitation: Children over-regularize early in acquisition because the representations of frequent,…
Descriptors: Form Classes (Languages), Morphemes, Linguistics, Feedback (Response)
Politzer, Guy; Van der Henst, Jean-Baptiste; Delle Luche, Claire; Noveck, Ira A. – Cognitive Science, 2006
We present a set-theoretic model of the mental representation of classically quantified sentences (All P are Q, Some P are Q, Some P are not Q, and No P are Q). We take inclusion, exclusion, and their negations to be primitive concepts. We show that although these sentences are known to have a diagrammatic expression (in the form of the Gergonne…
Descriptors: Models, Sentence Structure, Semantics, Prediction