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Volume 32, Issue 3


Explaining vowel systems: dispersion theory vs natural selection

Bert Vaux / Bridget Samuels
  • Department of Linguistics & Cognitive Science, Pomona College, Claremont, CA, USA; Center for Craniofacial Molecular Biology, University of Southern California, Los Angeles, CA, USA
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Published Online: 2015-09-09 | DOI: https://doi.org/10.1515/tlr-2014-0028


We argue that the cross-linguistic distribution of vowel systems is best accounted for by grammar-external forces of learnability operating in tandem with cognitive constraints on phonological computation, as argued for other phonological phenomena by Blevins (2004). On this view, the range of possible vowel systems is constrained only by what is computable and learnable; the range of attested vowel systems is a subset of this, constrained by relative learnability (Hale and Reiss 2000a, Hale and Reiss 2000b; Newmeyer 2005). A system that is easier to learn (e.g., one whose members are more dispersed in perceptual space) is predicted by our model to become more common cross-linguistically over evolutionary time than its less learnable competitors. This analysis efficiently accounts for both the typological patterns found in vowel systems and the existence of a non-trivial number of “unnatural” systems in the world’s languages. We compare this model with the leading forms of Dispersion Theory (notably Flemming’s (1995) implementation in Optimality Theory), which seek to explain sound patterns in terms of interaction between conflicting functional constraints on maximization of perceptual contrast and minimization of articulatory effort. Dispersion Theory is shown to be unable to generate the attested range of vowel systems or predict their interesting properties, such as the centralization typically found in two-vowel systems and the quality of epenthetic segments.

Keywords: Vowel systems; dispersion theory; evolutionary phonology


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Published Online: 2015-09-09

Published in Print: 2015-09-01

Citation Information: The Linguistic Review, Volume 32, Issue 3, Pages 573–599, ISSN (Online) 1613-3676, ISSN (Print) 0167-6318, DOI: https://doi.org/10.1515/tlr-2014-0028.

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