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Language learning, language use and the evolution of linguistic variation

Linguistic universals arise from the interaction between the processes of language learning and language use. A test case for the relationship between these factors is linguistic variation, which tends to be conditioned on linguistic or sociolinguistic criteria. How can we explain the scarcity of un...

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Autores principales: Smith, Kenny, Perfors, Amy, Fehér, Olga, Samara, Anna, Swoboda, Kate, Wonnacott, Elizabeth
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5124077/
https://www.ncbi.nlm.nih.gov/pubmed/27872370
http://dx.doi.org/10.1098/rstb.2016.0051
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author Smith, Kenny
Perfors, Amy
Fehér, Olga
Samara, Anna
Swoboda, Kate
Wonnacott, Elizabeth
author_facet Smith, Kenny
Perfors, Amy
Fehér, Olga
Samara, Anna
Swoboda, Kate
Wonnacott, Elizabeth
author_sort Smith, Kenny
collection PubMed
description Linguistic universals arise from the interaction between the processes of language learning and language use. A test case for the relationship between these factors is linguistic variation, which tends to be conditioned on linguistic or sociolinguistic criteria. How can we explain the scarcity of unpredictable variation in natural language, and to what extent is this property of language a straightforward reflection of biases in statistical learning? We review three strands of experimental work exploring these questions, and introduce a Bayesian model of the learning and transmission of linguistic variation along with a closely matched artificial language learning experiment with adult participants. Our results show that while the biases of language learners can potentially play a role in shaping linguistic systems, the relationship between biases of learners and the structure of languages is not straightforward. Weak biases can have strong effects on language structure as they accumulate over repeated transmission. But the opposite can also be true: strong biases can have weak or no effects. Furthermore, the use of language during interaction can reshape linguistic systems. Combining data and insights from studies of learning, transmission and use is therefore essential if we are to understand how biases in statistical learning interact with language transmission and language use to shape the structural properties of language. This article is part of the themed issue ‘New frontiers for statistical learning in the cognitive sciences’.
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spelling pubmed-51240772017-01-05 Language learning, language use and the evolution of linguistic variation Smith, Kenny Perfors, Amy Fehér, Olga Samara, Anna Swoboda, Kate Wonnacott, Elizabeth Philos Trans R Soc Lond B Biol Sci Articles Linguistic universals arise from the interaction between the processes of language learning and language use. A test case for the relationship between these factors is linguistic variation, which tends to be conditioned on linguistic or sociolinguistic criteria. How can we explain the scarcity of unpredictable variation in natural language, and to what extent is this property of language a straightforward reflection of biases in statistical learning? We review three strands of experimental work exploring these questions, and introduce a Bayesian model of the learning and transmission of linguistic variation along with a closely matched artificial language learning experiment with adult participants. Our results show that while the biases of language learners can potentially play a role in shaping linguistic systems, the relationship between biases of learners and the structure of languages is not straightforward. Weak biases can have strong effects on language structure as they accumulate over repeated transmission. But the opposite can also be true: strong biases can have weak or no effects. Furthermore, the use of language during interaction can reshape linguistic systems. Combining data and insights from studies of learning, transmission and use is therefore essential if we are to understand how biases in statistical learning interact with language transmission and language use to shape the structural properties of language. This article is part of the themed issue ‘New frontiers for statistical learning in the cognitive sciences’. The Royal Society 2017-01-05 /pmc/articles/PMC5124077/ /pubmed/27872370 http://dx.doi.org/10.1098/rstb.2016.0051 Text en © 2016 The Authors. http://creativecommons.org/licenses/by/4.0/ Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
spellingShingle Articles
Smith, Kenny
Perfors, Amy
Fehér, Olga
Samara, Anna
Swoboda, Kate
Wonnacott, Elizabeth
Language learning, language use and the evolution of linguistic variation
title Language learning, language use and the evolution of linguistic variation
title_full Language learning, language use and the evolution of linguistic variation
title_fullStr Language learning, language use and the evolution of linguistic variation
title_full_unstemmed Language learning, language use and the evolution of linguistic variation
title_short Language learning, language use and the evolution of linguistic variation
title_sort language learning, language use and the evolution of linguistic variation
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5124077/
https://www.ncbi.nlm.nih.gov/pubmed/27872370
http://dx.doi.org/10.1098/rstb.2016.0051
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