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Linguistic pitch analysis using functional principal component mixed effect models

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Aston, John A. D., Chiou, Jeng-Min and Evans, Jonathan. (2010) Linguistic pitch analysis using functional principal component mixed effect models. Journal of the Royal Statistical Society Series C: Applied Statistics, Vol.59 (No.2). pp. 297-317. ISSN 0035-9254

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Official URL: http://dx.doi.org/10.1111/j.1467-9876.2009.00689.x

Abstract

Fundamental frequency (F0, broadly 'pitch') is an integral part of spoken human language; however, a comprehensive quantitative model for F0 can be a challenge to formulate owing to the large number of effects and interactions between effects that lie behind the human voice's production of F0, and the very nature of the data being a contour rather than a point. The paper presents a semiparametric functional response model for F0 by incorporating linear mixed effects models through the functional principal component scores. This model is applied to the problem of modelling F0 in the tone language Qiang, a language in which relative pitch information is part of each word's dictionary entry.

Item Type:	Journal Article
Subjects:	Q Science > QA Mathematics
Divisions:	Faculty of Science > Statistics
Library of Congress Subject Headings (LCSH):	Intonation (Phonetics) -- Mathematical models, Multilevel models (Statistics)
Journal or Publication Title:	Journal of the Royal Statistical Society Series C: Applied Statistics
Publisher:	Wiley-Blackwell Publishing, Inc
ISSN:	0035-9254
Date:	March 2010
Volume:	Vol.59
Number:	No.2
Number of Pages:	21
Page Range:	pp. 297-317
Identification Number:	10.1111/j.1467-9876.2009.00689.x
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
Funder:	Guo jia ke xue wei yuan hui [National Science Council (Taiwan)], Engineering and Physical Sciences Research Council (EPSRC), Higher Education Funding Council for England (HEFCE)
Grant number:	95-2411-H-001-077 (NSC)
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URI:	http://wrap.warwick.ac.uk/id/eprint/6417