Acquiring a language vs. inducing a grammar

Bibliographic Data

ID21306369
AuthorsG Dupre (0000-0001-9312-4691, University of California, Davis, corresponding author)
Year2024
Volume247
Pages105771
Publication date2024-06-01
Open AccessYes
TypeARTICLE
VenueCognition (JOURNAL)
Journal identifiersISSN: 0010-0277 • E-ISSN: 1873-7838
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.cognition.2024.105771
PMID38507944
OpenAlexW4392935650
LanguageEN
Citations received2
References cited26

Standard computational models of language acquisition treat acquiring a language as a process of inducing a set of string-generating rules from a collection of linguistic data assumed to be generated by these very rules. In this paper I give theoretical and empirical arguments that such a model is radically unlike what a human language learner must do to acquire their native language. Most centrally, I argue that such models presuppose that linguistic data is directly a product of a grammar, ignoring the myriad non-grammatical systems involved in the use of language. The significance of these non-target systems in shaping the linguistic data children are exposed to undermines any simple reverse inference from linguistic data to grammatical competence

Emergent grammar · Generative grammar · Grammar · Grammar induction · Inference · Language acquisition · Linguistic competence · Linguistic description · Linguistics · Natural language · Natural language processing · Object language · Artificial Intelligence · Computer Science · Language and cultural evolution · Natural Language Processing Techniques · Philosophy · Psychology · Topic Modeling

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