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Domain generalisation in artificial language learning*
Published online by Cambridge University Press: 20 February 2015
Abstract
Many languages have restrictions on word-final segments, such as a requirement that any word-final obstruent be voiceless. There is a phonetic basis for such restrictions at the ends of utterances, but not the ends of words. Historical linguists have long noted this mismatch, and have attributed it to an analogical generalisation of such restrictions from utterance-final to word-final position. To test whether language learners actually generalise in this way, two artificial language learning experiments were conducted. Participants heard nonsense utterances in which there was a restriction on utterance-final obstruents, but in which no information was available about word-final utterance-medial obstruents. They were then tested on utterances that included obstruents in both positions. They learned the pattern and generalised it to word-final utterance-medial position, confirming that learners are biased toward word-based distributional patterns.
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Footnotes
We would like to thank audiences at the annual meeting of the Linguistic Society of America (Pittsburgh, 2011), UC Berkeley Phorum, Stanford P-interest and UCSC Phlunch, as well as Megan Crowhurst (including for her help in creating stimuli), Maria Gouskova, Junko Ito, Danny Law, Grant McGuire, Richard Meier, Armin Mester, Deniz Rudin, Kristine Yu and the anonymous reviewers for helpful suggestions and stimulating discussion of this paper. We are also grateful to Angela Aiello, Kimberly Cooper, Tommy Denby, Saralynn Emery, Scott Gaudinier, Elanna Grossman, Sean Hayes, Jules Lacour, Jessica Magallan, Melissa Ottele, Tatiana Puente, Rémy Ullman, Aileen Villapudua, Blake Watkins, Stephen Welch, Nicholas Whittier and Akari Yamamura for their work in support of this project.
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