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Exploring British accents : modelling the trap–bath split with functional data analysis
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Koshy, Aranya and Tavakoli, Shahin (2022) Exploring British accents : modelling the trap–bath split with functional data analysis. Journal of the Royal Statistical Society: Series C (Applied Statistics) . doi:10.1111/rssc.12555 ISSN 0035-9254.
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Official URL: https://doi.org/10.1111/rssc.12555
Abstract
The sound of our speech is influenced by the places we come from. Great Britain contains a wide variety of distinctive accents which are of interest to linguistics. In particular, the ‘a’ vowel in words like ‘class’ is pronounced differently in the North and the South. Speech recordings of this vowel can be represented as formant curves or as mel‐frequency cepstral coefficient curves. Functional data analysis and generalised additive models offer techniques to model the variation in these curves. Our first aim was to model the difference between typical Northern and Southern vowels /æ/ and /ɑ/, by training two classifiers on the North‐South Class Vowels dataset collected for this paper. Our second aim is to visualise geographical variation of accents in Great Britain. For this we use speech recordings from a second dataset, the British National Corpus (BNC) audio edition. The trained models are used to predict the accent of speakers in the BNC, and then we model the geographical patterns in these predictions using a soap film smoother. This work demonstrates a flexible and interpretable approach to modelling phonetic accent variation in speech recordings.
Item Type: | Journal Article | ||||||
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Subjects: | P Language and Literature > PE English | ||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||||
SWORD Depositor: | Library Publications Router | ||||||
Library of Congress Subject Headings (LCSH): | English language -- Phonology, Formants (Speech), English language -- Variation -- Great Britain, English language -- Accents and accentuation | ||||||
Journal or Publication Title: | Journal of the Royal Statistical Society: Series C (Applied Statistics) | ||||||
Publisher: | Wiley-Blackwell Publishing Ltd. | ||||||
ISSN: | 0035-9254 | ||||||
Official Date: | 21 April 2022 | ||||||
Dates: |
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DOI: | 10.1111/rssc.12555 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||
Date of first compliant deposit: | 19 May 2022 | ||||||
Date of first compliant Open Access: | 19 May 2022 | ||||||
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