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Exploring the front fricative contrast in Greek: A study of acoustic variability based on cepstral coefficients

Published online by Cambridge University Press:  03 June 2020

Jason Lilley Open the ORCID record for Jason Lilley [Opens in a new window] ,
Laura Spinu  and
Angeliki Athanasopoulou
Jason Lilley
Affiliation:
Center for Pediatric and Auditory Speech Sciences, Nemours Biomedical Research, Wilmington, DE, USAjason.lilley@nemours.org
Laura Spinu
Affiliation:
Department of Communications & Performing Arts, CUNY Kingsborough Community College, Brooklyn, NY, USAlspinu@kbcc.cuny.edu
Angeliki Athanasopoulou
Affiliation:
School of Languages, Linguistics, Literatures and Cultures, University of Calgary, Calgary, AB, Canadaangeliki.athanasopou@ucalgary.ca
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Abstract

In the current study, we explore the factors underlying the well-known difficulty in acoustic classification of front nonsibilant fricatives (Maniwa, Jongman & Wade 2009, McMurray & Jongman 2011) by applying a novel classification method to the production of Greek speakers. The Greek fricative inventory [f v θ ð s z ç ʝ x ɣ] includes voiced and voiceless segments from five distinct places of articulation. Our corpus contains all of the Greek fricatives produced by 29 monolingual speakers, but our focus is on the distinction between the front nonsibilant fricatives [f v θ ð]. For comparison, we also discuss the other places of articulation where relevant. We apply a relatively novel classification method based on cepstral coefficients, previously successful in categorizing English obstruent bursts (Bunnell, Polikoff & McNicholas 2004), English vowels (Ferragne & Pellegrino 2010), Romanian fricatives (Spinu & Lilley 2016), and Russian fricatives (Spinu, Kochetov & Lilley 2018). For this study, fricative boundaries were automatically aligned using Hidden Markov Models (HMMs) and then manually checked. Six Bark-frequency cepstral coefficients (c0–c5) were extracted from 20-millisecond Hann windows. HMMs were used to divide the fricatives and adjacent vowels into three regions of internally minimized variance. A multinomial logistic regression analysis then used the mean cepstral coefficients from each region as predictors for classification by consonant identity. Our method yields highly successful classification rates, exceeding the performance of previous methods. We discuss these results in light of the differences of the phonemic distributions of fricatives between English and Greek.

Keywords

fricativesGreekcepstral coefficientsHidden Markov modelsclassification
Type
Research Article
Information
Journal of the International Phonetic Association , Volume 51 , Issue 3 , December 2021 , pp. 393 - 424
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Copyright
© International Phonetic Association 2020

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