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The Effect of Phonotactics on Alternation Learning

Published online by Cambridge University Press:  01 January 2026

Adam J. Chong
Adam J. Chong*
Affiliation:
Queen Mary University of London
*
Department of Linguistics, School of Languages, Linguistics and Film, Queen Mary University of London, Mile End Road, E1 4NS London, UK, [a.chong@qmul.ac.uk]
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Abstract

This study investigates whether alternation learning is facilitated by a matching phonotactic generalization. In a series of artificial grammar learning experiments, English learners were trained on artificial languages evincing categorical vowel harmony alternations across morpheme boundaries. These languages differed in the degree of harmony within stems (disharmonic, semi-harmonic, and harmonic), and thus the degree of phonotactic support for the alternation. Results indicate that alternation learning was best when supported by matching stem phonotactics (harmonic language; experiment 1). Learners, however, were reluctant to extend a learned phonotactic constraint to novel unseen alternations (experiments 2 and 3). Taken together, the results are consistent with the hypothesis that alternation learning is facilitated by a matching static phonotactic generalization, but that learners are conservative in positing alternations in the absence of overt evidence for them.

Keywords

phonotacticsalternationsderived-environment effectsartificial grammarphonological learningvowel harmony

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Type
Research Article
Information
Language , Volume 97 , Issue 2 , June 2021 , pp. 213 - 244
Copyright
Copyright © 2021 Linguistic Society of America

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Footnotes

*

This work has benefited from discussion with and feedback from Megha Sundara, Kie Zuraw, Bruce Hayes, Robert Daland, Sharon Peperkamp, Karen Jesney, Stephanie Shih, Sharon Inkelas, Ricardo Bermúdez-Otero, Jamie White, and the audiences at the University of Melbourne, UCLA, the University of Hawai'i, NYU, QMUL, the University of Manchester, the Keio-ICU Colloquium, and LSA 2017 in Austin. I would also like to thank Eleanor Glewwe for recording stimuli, Audrey Kim for helping with the initial piloting of the experiment, and Michael Becker (Stony Brook) and Daniel Szeredi for assistance with Experigen. This work was funded by a UCLA Dissertation Year Fellowship and appeared as a chapter in the author's 2017 UCLA dissertation (Chong 2017). The study protocol was certified exempt by the UCLA Institutional Review Board: IRB#15-000223.

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