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Structural priming in artificial languages and the regularisation of unpredictable variation

Fehér, O; Wonnacott, E; Smith, K; (2016) Structural priming in artificial languages and the regularisation of unpredictable variation. Journal of Memory and Language 10.1016/j.jml.2016.06.002. (In press). Green open access

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Abstract

We present a novel experimental technique using artificial language learning to investigate the relationship between structural priming during communicative interaction, and linguistic regularity. We use unpredictable variation as a test-case, because it is a well-established paradigm to study learners’ biases during acquisition, transmission and interaction. We trained participants on artificial languages exhibiting unpredictable variation in word order, and subsequently had them communicate using these artificial languages. We found evidence for structural priming in two different grammatical constructions and across human-human and human-computer interaction. Priming occurred regardless of behavioral convergence: communication led to shared word order use only in human-human interaction, but priming was observed in all conditions. Furthermore, interaction resulted in the reduction of unpredictable variation in all conditions, suggesting a role for communicative interaction in eliminating unpredictable variation. Regularisation was strongest in human-human interaction and in a condition where participants believed they were interacting with a human but were in fact interacting with a computer. We suggest that participants recognize the counter-functional nature of unpredictable variation and thus act to eliminate this variability during communication. Furthermore, reciprocal priming occurring in human-human interaction drove some pairs of participants to converge on maximally regular, highly predictable linguistic systems. Our method offers potential benefits to both the artificial language learning and the structural priming fields, and provides a useful tool to investigate communicative processes that lead to language change and ultimately language design.

Type: Article
Title: Structural priming in artificial languages and the regularisation of unpredictable variation
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.jml.2016.06.002
Publisher version: http://dx.doi.org/10.1016/j.jml.2016.06.002
Language: English
Additional information: Copyright © 2016 The Author(s). Published by Elsevier Inc. This is an open access article under the Creative Commons Attribution 4.0 International (CC BY 4.0) license (http://creativecommons.org/licenses/by/4.0/)
Keywords: Structural priming; Artificial language learning; Unpredictable variation
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Language and Cognition
URI: https://discovery.ucl.ac.uk/id/eprint/1505828
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