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  4. Linguistic Pitch Analysis Using Functional Principal Component Mixed Effect Models
 
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Linguistic Pitch Analysis Using Functional Principal Component Mixed Effect Models

Journal
Journal of the Royal Statistical Society Series C: Applied Statistics
Journal Volume
59
Journal Issue
2
Start Page
297-317
ISSN
0035-9254
1467-9876
Date Issued
2009-10-22
Author(s)
John A. D. Aston
Jeng-Min Chiou  
Jonathan P. Evans
DOI
10.1111/j.1467-9876.2009.00689.x
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/720688
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. © 2010 Royal Statistical Society.
Subjects
Functional response models
Fundamental frequency
Phonetics
Principal component analysis
Random-effect models
Publisher
Oxford University Press (OUP)
Type
journal article

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