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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
Hudson Kam, Carla L. – Language Learning and Development, 2019
The phenomenon of regularization -- learners imposing systematicity on inconsistent variation in language input -- is complex. Studies show that children are more likely to regularize than adults, but adults will also regularize under certain circumstances. Exactly why we see the pattern of behaviour that we do is not well understood, however.…
Descriptors: Language Variation, Linguistic Input, Interference (Learning), Language Acquisition

Yang, Lynne R.; Givon, T. – Studies in Second Language Acquisition, 1997
Examines the effects of simplified input in early second language (L2) acquisition of English by experimentally manipulating language input to two groups of learners and then assessing their acquisition longitudinally within a controlled laboratory setting. Findings reveal that the dual task of acquiring vocabulary and grammar does not hinder…
Descriptors: Artificial Languages, Control Groups, Grammar, Language Research