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Hartshorne, Joshua K. – First Language, 2020
Ambridge argues that the existence of exemplar models for individual phenomena (words, inflection rules, etc.) suggests the feasibility of a unified, exemplars-everywhere model that eschews abstraction. The argument would be strengthened by a description of such a model. However, none is provided. I show that any attempt to do so would immediately…
Descriptors: Models, Language Acquisition, Language Processing, Bayesian Statistics
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
Phillips, Lawrence; Pearl, Lisa – Cognitive Science, 2015
The informativity of a computational model of language acquisition is directly related to how closely it approximates the actual acquisition task, sometimes referred to as the model's "cognitive plausibility." We suggest that though every computational model necessarily idealizes the modeled task, an informative language acquisition…
Descriptors: Language Acquisition, Models, Computational Linguistics, Credibility
Wellwood, Alexis; Gagliardi, Annie; Lidz, Jeffrey – Language Learning and Development, 2016
Acquiring the correct meanings of words expressing quantities ("seven, most") and qualities ("red, spotty") present a challenge to learners. Understanding how children succeed at this requires understanding, not only of what kinds of data are available to them, but also the biases and expectations they bring to the learning…
Descriptors: Syntax, Computational Linguistics, Task Analysis, Prediction
Beekhuizen, Barend; Bod, Rens; Zuidema, Willem – Language and Speech, 2013
In this paper we present three design principles of language--experience, heterogeneity and redundancy--and present recent developments in a family of models incorporating them, namely Data-Oriented Parsing/Unsupervised Data-Oriented Parsing. Although the idea of some form of redundant storage has become part and parcel of parsing technologies and…
Descriptors: Language Acquisition, Models, Bayesian Statistics, Computational Linguistics
Rabagliati, Hugh; Pylkkanen, Liina; Marcus, Gary F. – Developmental Psychology, 2013
Language is rife with ambiguity. Do children and adults meet this challenge in similar ways? Recent work suggests that while adults resolve syntactic ambiguities by integrating a variety of cues, children are less sensitive to top-down evidence. We test whether this top-down insensitivity is specific to syntax or a general feature of children's…
Descriptors: Ambiguity (Semantics), Syntax, Psycholinguistics, Infants
Kazemzadeh, Abe – ProQuest LLC, 2013
This dissertation studies how people describe emotions with language and how computers can simulate this descriptive behavior. Although many non-human animals can express their current emotions as social signals, only humans can communicate about emotions symbolically. This symbolic communication of emotion allows us to talk about emotions that we…
Descriptors: Natural Language Processing, Psychological Patterns, Computer Simulation, Discourse Analysis