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A Statistical Comparison of Written Language and Nonlinguistic Symbol Systems

Published online by Cambridge University Press:  01 January 2026

Richard Sproat
Richard Sproat*
Affiliation:
Google, Inc.
*
Google, Inc., 76 9th Avenue, New York, NY 10011, [rws@google.com]
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Abstract

Are statistical methods useful in distinguishing written language from nonlinguistic symbol systems? Some recent articles (Rao et al. 2009a, Lee et al. 2010a) have claimed so. Both of these previous articles use measures based at least in part on bigram conditional entropy, and subsequent work by one of the authors (Rao) has used other entropic measures. In both cases the authors have argued that the methods proposed either are useful for discriminating between linguistic and nonlinguistic systems (Lee et al.), or at least count as evidence of a more ‘inductive’ kind for the status of a system (Rao et al.).

Using a larger set of nonlinguistic and comparison linguistic corpora than were used in these and other studies, I show that none of the previously proposed methods are useful as published. However, one of the measures proposed by Lee and colleagues (2010a) (with a different cut-off value) and a novel measure based on repetition turn out to be good measures for classifying symbol systems into the two categories. For the two ancient symbol systems of interest to Rao and colleagues (2009a) and Lee and colleagues (2010a)—Indus Valley inscriptions and Pictish symbols, respectively—both of these measures classify them as nonlinguistic, contradicting the findings of those previous works.

Keywords

symbol systemsnonlinguistic symbolswriting systemsstatistical models of language

Information

Type
Research Article
Information
Language , Volume 90 , Issue 2 , June 2014, pp. 457 - 481
Copyright
Copyright © 2014 Linguistic Society of America

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