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Stanojevic, Miloš; Brennan, Jonathan R.; Dunagan, Donald; Steedman, Mark; Hale, John T. – Cognitive Science, 2023
To model behavioral and neural correlates of language comprehension in naturalistic environments, researchers have turned to broad-coverage tools from natural-language processing and machine learning. Where syntactic structure is explicitly modeled, prior work has relied predominantly on context-free grammars (CFGs), yet such formalisms are not…
Descriptors: Correlation, Language Processing, Brain Hemisphere Functions, Natural Language Processing
Parsons, John-Dennis; Davies, Jim – Cognitive Science, 2022
Analogical reasoning is a core facet of higher cognition in humans. Creating analogies as we navigate the environment helps us learn. Analogies involve reframing novel encounters using knowledge of familiar, relationally similar contexts stored in memory. When an analogy links a novel encounter with a familiar context, it can aid in problem…
Descriptors: Correlation, Thinking Skills, Schemata (Cognition), Inferences
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
Brennan, Jonathan R.; Pylkkänen, Liina – Cognitive Science, 2017
Research investigating the brain basis of language comprehension has associated the left anterior temporal lobe (ATL) with sentence-level combinatorics. Using magnetoencephalography (MEG), we test the parsing strategy implemented in this brain region. The number of incremental parse steps from a predictive left-corner parsing strategy that is…
Descriptors: Brain, Sentences, Brain Hemisphere Functions, Language Processing
Castro, Nichol; Stella, Massimo; Siew, Cynthia S. Q. – Cognitive Science, 2020
Investigating instances where lexical selection fails can lead to deeper insights into the cognitive machinery and architecture supporting successful word retrieval and speech production. In this paper, we used a multiplex lexical network approach that combines semantic and phonological similarities among words to model the structure of the mental…
Descriptors: Semantics, Phonology, Aphasia, Brain Hemisphere Functions
Tabor, Whitney; Cho, Pyeong W.; Dankowicz, Harry – Cognitive Science, 2013
Human participants and recurrent ("connectionist") neural networks were both trained on a categorization system abstractly similar to natural language systems involving irregular ("strong") classes and a default class. Both the humans and the networks exhibited staged learning and a generalization pattern reminiscent of the…
Descriptors: Learning Processes, Task Analysis, Systems Approach, Geometric Concepts