Typological gaps in iambic nonfinality correlate with learning difficulty
DOI:
https://doi.org/10.3765/amp.v9i0.5175Keywords:
Computational Phonology, Stress, Typology, LearningAbstract
This paper discusses gaps in stress typology that are unexpected from the perspective of a foot-based theory and shows that the patterns pose difficulties for a computationally implemented learning algorithm. The unattested patterns result from combining theoretical elements whose effects are generally well-attested, including iambic footing, nonfinality, word edge alignment and a foot binarity requirement. The patterns can be found amongst the 124 target stress systems constructed by Tesar and Smolensky (2000) as a test of their approach to hidden structure learning. A learner with a Maximum Entropy grammar that uses a form of Expectation Maximization to deal with hidden structure was found to often fail on these unattested languages.
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Published by the LSA with permission of the author(s) under a CC BY 3.0 license.