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A spatial modeling approach for linguistic object data : analysing dialect sound variations across Great Britain
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Tavakoli, Shahin, Pigoli, Davide , Aston, John A. D. and Coleman, John S. (2019) A spatial modeling approach for linguistic object data : analysing dialect sound variations across Great Britain. Journal of the American Statistical Association, 114 (527). pp. 1081-1096. doi:10.1080/01621459.2019.1607357 ISSN 0162-1459.
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Official URL: https://doi.org/10.1080/01621459.2019.1607357
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.
Item Type: | Journal Article | ||||||||
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||||||
Journal or Publication Title: | Journal of the American Statistical Association | ||||||||
Publisher: | American Statistical Association | ||||||||
ISSN: | 0162-1459 | ||||||||
Official Date: | 2019 | ||||||||
Dates: |
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Volume: | 114 | ||||||||
Number: | 527 | ||||||||
Page Range: | pp. 1081-1096 | ||||||||
DOI: | 10.1080/01621459.2019.1607357 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||
Date of first compliant deposit: | 28 June 2018 | ||||||||
Date of first compliant Open Access: | 25 September 2020 | ||||||||
RIOXX Funder/Project Grant: |
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