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Canalization of Language Structure From Environmental Constraints: A Computational Model of Word Learning From Multiple Cues
Author(s) -
Monaghan Padraic
Publication year - 2017
Publication title -
topics in cognitive science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.191
H-Index - 56
eISSN - 1756-8765
pISSN - 1756-8757
DOI - 10.1111/tops.12239
Subject(s) - robustness (evolution) , computer science , language acquisition , artificial intelligence , language model , natural language processing , variation (astronomy) , computational model , cognitive psychology , psychology , biochemistry , chemistry , physics , mathematics education , astrophysics , gene
There is substantial variation in language experience, yet there is surprising similarity in the language structure acquired. Constraints on language structure may be external modulators that result in this canalization of language structure, or else they may derive from the broader, communicative environment in which language is acquired. In this paper, the latter perspective is tested for its adequacy in explaining robustness of language learning to environmental variation. A computational model of word learning from cross‐situational, multimodal information was constructed and tested. Key to the model's robustness was the presence of multiple, individually unreliable information sources to support learning. This “degeneracy” in the language system has a detrimental effect on learning, compared to a noise‐free environment, but has a critically important effect on acquisition of a canalized system that is resistant to environmental noise in communication.