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A Spatial Modeling Approach for Linguistic Object Data: Analyzing Dialect Sound Variations Across Great Britain

Research output: Contribution to journalArticle

Shahin Tavakoli, Davide Pigoli, John Aston, John S. Coleman

Original languageEnglish
Pages (from-to)1081-1096
Number of pages16
JournalJournal of American statistical association
Volume114
Issue number527
Early online date25 Sep 2019
DOIs
Accepted/In press26 Jun 2018
E-pub ahead of print25 Sep 2019
Published2019

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Abstract

Dialect variation is of considerable interest in linguistics and other social sciences. However, traditionally it has been studied using proxies (transcriptions) rather than acoustic recordings directly. We introduce novel statistical techniques to analyze geolocalized speech recordings and to explore the spatial variation of pronunciations continuously over the region of interest, as opposed to traditional isoglosses, which provide a discrete partition of the region. Data of this type require an explicit modeling of the variation in the mean and the covariance. Usual Euclidean metrics are not appropriate, and we therefore introduce the concept of d-covariance, which allows consistent estimation both in space and at individual locations. We then propose spatial smoothing for these objects which accounts for the possibly nonconvex geometry of the domain of interest. We apply the proposed method to data from the spoken part of the British National Corpus, deposited at the British Library, London, and we produce maps of the dialect variation over Great Britain. In addition, the methods allow for acoustic reconstruction across the domain of interest, allowing researchers to listen to the statistical analysis. Supplementary materials for this article are available online.

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