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Learning phonological categories

Published online by Cambridge University Press:  19 February 2026

John Goldsmith  and
Aris Xanthos
John Goldsmith*
Affiliation:
University of Chicago
Aris Xanthos*
Affiliation:
University of Lausanne
*
Goldsmith, University of Chicago, Departments of Linguistics and Computer Science, 1010 East 59th St., Chicago, IL 60637 [goldsmith@uchicago.edu]
Xanthos, University of Lausanne, Department of Computer Science and Mathematical Methods, Anthropole, CH-1015 Lausanne, Switzerland [aris.xanthos@unil.ch]
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Abstract

This article describes in detail several explicit computational methods for approaching such questions in phonology as the vowel/consonant distinction, the nature of vowel harmony systems, and syllable structure, appealing solely to distributional information. Beginning with the vowel/consonant distinction, we consider a method for its discovery by the Russian linguist Boris Sukhotin, and compare it to two newer methods of more general interest, both computational and theoretical, today. The first is based on spectral decomposition of matrices, allowing for dimensionality reduction in a finely controlled way, and the second is based on finding parameters for maximum likelihood in a hidden Markov model. While all three methods work for discovering the fairly robust vowel/consonant distinction, we extend the newer ones to the discovery of vowel harmony, and in the case of the probabilistic model, to the discovery of some aspects of syllable structure.

Keywords

categorizationmachine learninghidden Markov modelsspectral graph theoryvowel harmonyphonology

Information

Type
Research Article
Information
Language , Volume 85 , Issue 1 , March 2009 , pp. 4 - 38
Copyright
Copyright © 2009 by Linguistic Society of America

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