Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/105683
Citations
Scopus Web of Science® Altmetric
?
?
Type: Journal article
Title: Language learning, language use and the evolution of linguistic variation
Author: Smith, K.
Perfors, A.
Fehér, O.
Samara, A.
Swoboda, K.
Wonnacott, E.
Citation: Philosophical Transactions of the Royal Society B: Biological Sciences, 2017; 372(1711):20160051-1-20160051-13
Publisher: Royal Society
Issue Date: 2017
ISSN: 0962-8436
1471-2970
Statement of
Responsibility: 
Kenny Smith, Amy Perfors, Olga Fehér, Anna Samara, Kate Swoboda, Elizabeth Wonnacott
Abstract: 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'.
Keywords: iterated learning
language
learning
Rights: © 2016 The Authors. 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.
DOI: 10.1098/rstb.2016.0051
Grant ID: http://purl.org/au-research/grants/arc/DP150103280
Appears in Collections:Aurora harvest 8
Linguistics publications

Files in This Item:
File Description SizeFormat 
hdl_105683.pdfPublished version852.61 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.