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Grammars leak: Modeling how phonotactic generalizations interact within the grammar

Published online by Cambridge University Press:  19 February 2026

Andrew Martin
Andrew Martin*
Affiliation:
RIKEN Brain Science Institute
*
Laboratory for Language Development RIKEN Brain Science Institute 2-1 Hirosawa, Wako-shi, Saitama 351-0198 Japan, [amartin@brain.riken.jp]
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Abstract

I present evidence from Navajo and English that weaker, gradient versions of morpheme-internal phonotactic constraints, such as the ban on geminate consonants in English, hold even across prosodic word boundaries. I argue that these lexical biases are the result of a maximum entropy phonotactic learning algorithm that maximizes the probability of the learning data, but that also contains a smoothing term that penalizes complex grammars. When this learner attempts to construct a grammar in which some constraints are blind to morphological structure, it underpredicts the frequency of compounds that violate a morpheme-internal phonotactic. I further show how, over time, this learning bias could plausibly lead to the lexical biases seen in Navajo and English.

Keywords

phonotactic learningmaximum entropymorphologylanguage changeNavajoEnglish

Information

Type
Research Article
Information
Language , Volume 87 , Issue 4 , December 2011 , pp. 751 - 770
Copyright
Copyright © 2011 Linguistic Society of America

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