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Exceptionality and derived environment effects: a comparison of Korean and Turkish
Published online by Cambridge University Press: 20 January 2020
Morphologically derived environment effects (MDEEs) are well-known examples where phonotactic patterns in the lexicon mismatch with what is allowed at morphological boundaries – alternations. Analyses of MDEEs usually assume that the alternation is morphologically general, and that the sequences ‘repaired’ across morpheme boundaries are phonotactically well-formed in the lexicon. This paper examines the phonotactic patterns in the lexicon of two languages with MDEEs: Korean palatalisation and Turkish velar deletion. I show that Korean heteromorphemic sequences that undergo palatalisation are underattested in the lexicon. A computational learner learns a markedness constraint that drives palatalisation, suggesting a pattern of exceptional non-undergoing. This contrasts with Turkish, where the relevant constraint motivating velar deletion at the morpheme boundary is unavailable from phonotactic learning, and where the alternation is an example of exceptional triggering. These results indicate that MDEEs are not a unitary phenomenon, highlighting the need to examine these patterns in closer quantitative detail.
- Copyright © Cambridge University Press 2020
This work has benefited from discussion and feedback from Ricardo Bermúdez-Otero, Robert Daland, Bruce Hayes, Sharon Inkelas, Karen Jesney, Sharon Peperkamp, Stephanie Shih, Brian Smith, Megha Sundara, Kie Zuraw and audiences at the University of Melbourne, UC Berkeley, UCLA, University of Hawaii, NYU, QMUL, the University of Manchester, SCaMP 2016 at UCSD and AMP 2016 at USC. I am grateful to Joo Hee Oom for help processing parts of the NAKL corpus. Finally, I would also like to thank three anonymous reviewers, an associate editor and the editors at Phonology, whose comments and suggestions on earlier versions of this manuscript have greatly improved it. An earlier version of this work appeared as a chapter of Chong (2017). This work was funded by a UCLA Dissertation Year Fellowship. All remaining faults are my own.