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Modeling a phonotactic approach to segment recovery: The case of Japanese high vowels

James Whang (Seoul National University)
Kakeru Yazawa (University of Tsukuba) 

Abstract
Japanese listeners often have difficulties perceiving consonant clusters accurately and 
report hearing a vowel between the consonants, despite Japanese speakers producing 
numerous consonant clusters that result from a highly productive high vowel devoicing 
process. This poses a substantial challenge for phonological learning, as the task is to 
learn the strong CVCV preference in Japanese based on surface consonant clusters that 
violate this very preference. The current study investigates this learnability issue by 
building a computational model that induces Optimality Theoretic (OT) phonotactic 
constraints based strictly on overt speech. Two versions of the model are tested: one 
with classic OT-style faithfulness constraints that penalize violations, and one with 
positive constraints that reward sequences conforming to the constraints. Both have 
traditional  markedness  constraints. The  results  show  that  positive  constraints  are 
superior to faithfulness constraints in modeling phonotactic repair.

Keywords 
acquisition, computational phonology, Japanese, perceptual repair 


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