Static cues such as formant measurements obtained at the vowel midpoint are usually taken as the main correlate for vowel identification. However, dynamic cues such as vowel-inherent spectral change have been shown to yield better classification of vowels using discriminant analysis. The aim of this study is to evaluate the role of static versus dynamic cues in Hijazi Arabic (HA) vowel classification, in addition to vowel duration and F3, which are not usually looked at. Data from 12 male HA speakers producing eight HA vowels in /hVd/ syllables were obtained, and classification accuracy was evaluated using discriminant analysis. Dynamic cues, particularly the three-point model, had higher classification rates (average 95.5%) than the remaining models (static model: 93.5%; other dynamic models: between 65.75% and 94.25%). Vowel duration had a significant role in classification accuracy (average +8%). These results are in line with dynamic approaches to vowel classification and highlight the relative importance of cues such as vowel duration across languages, particularly where it is prominent in the phonology.

1.
Abdoh
,
A.
(
2011
). “
A study of the phonological structure and representation of first words in Arabic
,” Ph.D. thsis,
University of Leicester
, Leicester, UK.
2.
Almbark
,
R.
, and
Hellmuth
,
S.
(
2015
). “
Acoustic analysis of the Syrian vowel system
,” in
Proceedings of the 18th International Congress of Phonetic Sciences (ICPhS)
, August 10–14, Glasgow, UK.
3.
Al-Tamimi
,
J.
(
2007a
). “
Indices dynamiques et perception des voyelles: étude translinguistique en arabe dialectal et en français” (“Dynamic indices and vowel perception: translinguistic study in Arabic and in French dialects”)
, Ph.D. dissertation,
University Lyon
,
Lyon, France
, http://theses.univ-lyon2.fr/documents/lyon2/2007/al-tamimi_je (11/20/2019).
4.
Al-Tamimi
,
J.
(
2007b
). “
Static and dynamic cues in vowel production: A cross dialectal study in Jordanian and Moroccan Arabic
,” in
Proceedings of the 16th ICPHS
, August 6–10, Saarbrücken, Germany, pp.
541
544
.
5.
Al-Tamimi
,
J.
, and
Ferragne
,
E.
(
2005
). “
Does vowel space size depend on language vowel inventories? Evidence from two Arabic dialects and French
,” in
Proceedings of the 9th EuroSpeech
, September 4–8, Lisbon, Portugal, pp.
2465
2468
.
6.
Alzaidi
,
M.
(
2014
). “
Information Structure and Intonation in Hijazi Arabic
,” Ph.D. thesis,
University of Essex
, Colchester, UK.
7.
Arnaud
,
V.
,
Sigouin
,
C.
, and
Roy
,
J. P.
(
2011
). “
Acoustic description of Quebec French high vowels: First results
,” in
Proceedings of the 17th ICPhS
, August 17–21, Hong Kong, pp.
244
247
.
8.
Bates
,
D.
,
Mächler
,
M.
,
Bolker
,
B.
, and
Walker
,
S.
(
2015
). “
Fitting linear mixed-effects models using lme4
,”
J. Stat Softw.
67
(
1
),
1
48
.
9.
Boersma
,
P.
, and
Weenink
,
D.
(
2019
). “
Praat: Doing phonetics by computer [computer program]
,” http://www.praat.org (11/22/2019).
10.
Cardoso
,
A. B.
(
2015
). “
Dialectology, phonology, diachrony: Liverpool English realisations of PRICE and MOUTH
,” Ph.D. thesis,
University of Edinburgh
,
Edinburgh, UK
.
11.
Chomsky
,
N.
, and
Halle
,
M.
(
1968
).
The Sound Pattern of English
(
Harper & Row
,
London)
.
12.
Elvin
,
J.
,
Williams
,
D.
, and
Escudero
,
P.
(
2016
). “
Dynamic acoustic properties of monophthongs and diphthongs in Western Sydney Australian English
,”
J. Acoust. Soc. Am.
140
(
1
),
576
581
.
13.
Ferguson
,
S. H.
, and
Kewley-Port
,
D.
(
2002
). “
Vowel intelligibility in clear and conversational speech for normal-hearing and hearing-impaired listeners
,”
J. Acoust. Soc. Am.
112
(
1
),
259
271
.
14.
Gottfried
,
M.
,
Miller
,
J. D.
, and
Meyer
,
D. J.
(
1993
). “
Three approaches to the classification of American English vowels
,”
J. Phone.
21
,
205
229
.
15.
Harrington
,
J.
, and
Cassidy
,
S.
(
1994
). “
Dynamic and target theories of vowel classification: Evidence from monophthongs and diphthongs in Australian English
,”
Lang. Speech
37
(
4
),
357
373
.
16.
Hillenbrand
,
J. M.
(
2013
). “
Static and dynamic approaches to vowel perception
,” in
Vowel Inherent Spectral Change
, edited by
G. S.
Morrison
and
P. F.
Assmann
(
Springer
,
Berlin)
, pp.
9
30
.
17.
Hillenbrand
,
J. M.
,
Clark
,
M. J.
, and
Nearey
,
T. M.
(
2001
). “
Effects of consonant environment on vowel formant patterns
,”
J. Acoust. Soc. Am.
109
(
2
),
748
763
.
18.
Hillenbrand
,
J. M.
,
Getty
,
L. A.
,
Clark
,
M. J.
, and
Wheeler
,
K.
(
1995
). “
Acoustic characteristics of American English vowels
,”
J. Acoust. Soc. Am.
97
,
3099
3111
.
19.
Hillenbrand
,
J. M.
, and
Nearey
,
T. M.
(
1999
). “
Identification of resynthesized /hvd/ utterances: Effects of formant contour
,”
J. Acoust. Soc. Am.
105
,
3509
3523
.
20.
Huang
,
C. B.
(
1992
). “
Modelling human vowel identification using aspects of formant trajectory and context
,” in
Speech Perception, Production and Linguistic Structure
, edited by
Y.
Tohkura
,
E.
Vatikiotis-Bateson
, and
Y.
Sagisaka
(
IOS
,
Amsterdam
), pp.
43
61
.
21.
Jarrah
,
M. A.
(
1993
). “
The phonology of Madina Hijazi Arabic: A non-linear analysis
,” Ph.D. thesis,
University of Essex
, Colchester, UK.
22.
Jin
,
S. H.
, and
Liu
,
C.
(
2013
). “
The vowel inherent spectral change of English vowels spoken by native and non-native speakers
,”
J. Acoust. Soc. Am.
133
(
5
),
363
369
.
23.
Length
,
R.
(
2019
). “emmeans: Estimated marginal means, aka least-squares means. R package version 1.3.5.1 [computer program],” https://CRAN.R-project.org/package=emmeans (11/23/2019).
24.
Manuel
,
S. Y.
(
1990
). “
The role of contrast in limiting vowel-to-vowel coarticulation in different languages
,”
J. Acoust. Soc. Am.
88
(
3
),
1286
1298
.
25.
Meunier
,
C.
,
Frenck-Mestre
,
C.
,
Lelekov-Boissard
,
T.
, and
Le Besnerais
,
M.
(
2003
). “
Production and perception of vowels: Does the density of the system play a role?
,” in
Proceedings of the 15th ICPhS
, August 3–9, Barcelona, Spain, pp.
723
726
.
26.
Morrison
,
S.
, and
Assmann
,
P.
(
2012
).
Vowel Inherent Spectral Change
(
Springer Science & Business Media
,
New York
).
27.
Morrison
,
G. S.
, and
Nearey
,
T. M.
(
2007
). “
Testing theories of vowel inherent spectral change
,”
J. Acoust. Soc. Am.
122
(
1
),
EL15
EL22
.
28.
Mousa
,
A.
(
1994
). “
The interphonolgy of Saudi learners of English
,” Ph.D. thesis,
University of Essex
, Colchester, UK.
29.
Munro
,
M. J.
(
1993
). “
Productions of English vowels by native speakers of Arabic: Acoustic measurements and accentedness ratings
,”
Lang. Speech
36
(
1
),
39
66
.
30.
Nearey
,
T. M.
, and
Assmann
,
P. F.
(
1986
). “
Modeling the role of inherent spectral change in vowel identification
,”
J. Acoust. Soc. Am.
80
(
5
),
1297
1308
.
31.
Newman
,
D.
, and
Verhoeven
,
J.
(
2002
). “
Frequency analysis of Arabic vowels in connected speech
,”
Antwerp Papers Ling.
100
,
77
86
.
32.
Oh
,
E.
(
2013
). “
Dynamic spectral patterns of American English front monophthong vowels produced by Korean-English bilingual speakers and Korean late learners of English
,”
Ling. Res.
30
(
2
),
293
312
.
33.
Peterson
,
G. E.
, and
Barney
,
H. L.
(
1952
). “
Control methods used in a study of the vowels
,”
J. Acoust. Soc. Am.
24
(
2
),
175
184
.
34.
R Core Team
(
2019
). “
R: A language and environment for statistical computing (version 3.6.1) [computer program]
,” Vienna, Austria: R Foundation for Statistical Computing, https://www.R-project.org/ (11/23/2019).
35.
RStudio
(
2019
). “
Rstudio: Integrated development environment for R (version 1.2.1335) [computer program]
,” https://rstudio.com/ (11/23/2019).
36.
Slifka
,
J.
(
2003
). “
Tense/lax vowel classification using dynamic spectral cues
,” in
Proceedings of the 15th ICPhS
, August 3–9, Barcelona, Spain, pp.
921
924
.
37.
Stevens
,
K. N.
, and
House
,
A. S.
(
1963
). “
Perturbation of vowel articulations by consonantal context: An acoustical study
,”
J. Speech Hear. Res.
6
,
111
128
.
38.
Strange
,
W.
(
1989
). “
Evolving theories of vowel perception
,”
J. Acoust. Soc. Am.
85
(
5
),
2081
2087
.
39.
Strange
,
W.
, and
Jenkins
,
J.
(
2013
). “
Dynamic specification of coarticulated vowels: Research chronology, theory, and hypotheses
,” in
Vowel Inherent Spectral Change
, edited by
G. S.
Morrison
and
P. F.
Assmann
(
Springer
,
Berlin
), pp.
87
115
.
40.
Venables
,
N.
, and
Ripley
,
D.
(
2002
).
Modern Applied Statistics with S
, 4th ed. (
Springer
,
New York
).
41.
Watson
,
C. I.
, and
Harrington
,
J.
(
1999
). “
Acoustic evidence for dynamic formant trajectories in Australian English vowels
,”
J. Acoust. Soc. Am.
106
,
458
468
.
42.
Wickham
,
H.
(
2016
).
ggplot2: Elegant Graphics for Data Analysis
(
Springer-Verlag
,
New York
).
43.
Wickham
,
H.
,
François
,
R.
,
Henry
,
L.
, and
Müller
,
K.
(
2019
). “
Dplyr: A grammar of data manipulation. R package version 0.8.3
,” https://CRAN.R-project.org/package=dplyr (11/23/2019).
44.
Yuan
,
J.
(
2013
). “
The spectral dynamics of vowels in Mandarin Chinese
,” in
Proceedings of the 14th Annual Conference of the International Speech Communication Association
, August 25–29,
Lyon, France
, pp.
1193
1197
.
45.
Zahorian
,
S. A.
, and
Jagharghi
,
A. J.
(
1993
). “
Spectral-shape features versus formants as acoustic correlates for vowels
,”
J. Acoust. Soc. Am.
94
(
4
),
1966
1982
.
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