Home Dynamic specification of vowels in Hijazi Arabic
Article
Licensed
Unlicensed Requires Authentication

Dynamic specification of vowels in Hijazi Arabic

  • Wael Almurashi EMAIL logo , Jalal Al-Tamimi ORCID logo and Ghada Khattab
Published/Copyright: February 15, 2024

Abstract

Research on various languages shows that dynamic approaches to vowel acoustics – in particular Vowel-Inherent Spectral Change (VISC) – can play a vital role in characterising and classifying monophthongal vowels compared with a static model. This study’s aim was to investigate whether dynamic cues also allow for better description and classification of the Hijazi Arabic (HA) vowel system, a phonological system based on both temporal and spectral distinctions. Along with static and dynamic F1 and F2 patterns, we evaluated the extent to which vowel duration, F0, and F3 contribute to increased/decreased discriminability among vowels. Data were collected from 20 native HA speakers (10 females and 10 males) producing eight HA monophthongal vowels in a word list with varied consonantal contexts. Results showed that dynamic cues provide further insights regarding HA vowels that are not normally gleaned from static measures alone. Using discriminant analysis, the dynamic cues (particularly the seven-point model) had relatively higher classification rates, and vowel duration was found to play a significant role as an additional cue. Our results are in line with dynamic approaches and highlight the importance of looking beyond static cues and beyond the first two formants for further insights into the description and classification of vowel systems.


Corresponding author: Wael Almurashi, Department of Languages and Translations, Taibah University, Madinah 344, Saudi Arabia, E-mail:

Funding source: Taibah University

Funding source: IdEx Université Paris Cité

Award Identifier / Grant number: (ANR-18-IDEX-0001)

Acknowledgments

This work was supported by Taibah University to the first author (WA) and partially supported by a public grant overseen by the IdEx Université Paris Cité (ANR-18-IDEX-0001) as part of the Labex Empirical Foundations of Linguistics – EFL to the second author (JA). We thank all of our subjects who participated in this study.

  1. Ethical approval: Ethical Approval to collect this study was obtained from Newcastle University Ethics Committee (Ref: 2427/2017).

  2. Author contributions: The authors confirm contribution to the paper as follows: WA: Data collection; WA and JAT: Data analysis tools (e.g., PRAAT, R and RStudio); WA, JA, and GK: Made a substantial contribution to the conceptualisation of the article, the analysis and interpretation of data, revising the article critically for important intellectual content, and approving the version to be published.

  3. Conflict of interest: The authors have no conflicts of interest to declare.

Appendix
Table A1:

The set of target words that were used for the HA.

HA vowels
HA vowel Place of articulation IPA HA word English gloss
/uː/ Bilabial_ Alveolar /buːsi/

/buːz/
بُوسيa

بُوز
A female name

Mouth
Alveolar_Alveolar /duːd/

/tuːt/
دُود

تُوت
Worms

Blueberry
Velar_Alveolar /kuːsa/

/kuːra/
كُوسة

كُورة
Zucchini

Ball
/u/ Bilabial_ Alveolar /burj/

/burr/
بُرج

بُر
Tower

Wheat
Alveolar_Alveolar /duss/

/durj/
دُس

دُرج
Hide

Drawer
Velar_Alveolar /kull/

/guddaːm/
كُل

قُدام
Eat

Deal
/iː/ Bilabial_ Alveolar /biːsaːn/

/biːr/
بِيسان

بِير
A female name

Well
Alveolar_Alveolar /ʒadiːd/

/diːdaːn/
جَديد

دِيدان
New

Worms
Velar_Alveolar /kiːs/

/giːss/
كِيس

قِيس
Bag

Measure
/i/ Bilabial_ Alveolar /biss/

/bilaːl/
بِس

بِلال
Cat

A male name
Alveolar_Alveolar /diss/

/dirham/
دِس

دِرهم
Hide

Dirham (Currency)
Velar_Alveolar /kidd/

/kilma/
كِد

كِلمة
To work hard

Word
/aː/ Bilabial_ Alveolar /baːss/

/baːt/
باس

بات
Kissed

Slept
Alveolar_Alveolar /daːs/

/miħtaːs/
داس

مِحتاس
Step

Messy
Velar_Alveolar /kaːs/

/kaːsir/
كاس

كاسر
Cup

Breaker
/a/ Bilabial_ Alveolar /bass/

/bard/
بَسْ

بَرد
Enough

Cold
Alveolar_Alveolar /dall/

/dass/
دَل

دَس
Guide

Hid
Velar_Alveolar /kadd/

/katt/
كَد

كَت
Worked hard

Threw something (Liquid)
/oː/ Bilabial_ Alveolar /boːse/

/boːt/
بَوس

بَوت
Kiss

Football boot
Alveolar_Alveolar /doːla/

/doːriː/
دَولة

دَوري
Country

League
Velar_Alveolar /koːt/

/koːla/
كَوت

كولا
Jacket

Cola
/eː/ Bilabial_ Alveolar /beːt/

/beːz/
بَيت

بَيز
House

Oven mitts
Alveolar_Alveolar /deːsam/

/teːss/
دَيسم

تَيس
A male name

Male-goat
Velar_Alveolar /geːd/

/keːd/
قَيد

كَيد
Constraint

Cunning
  1. aIn the Arabic script, ħarakāt (“diacritics”) are used to indicate the short vowels and placed below or above the root consonants.

Table A2:

Average of the formant frequencies (at 20, 30, 40, 50, 60, 70, and 80 %) and vowel duration for each Hijazi Arabic vowel.

F0 (Hz) F1 (Hz) F2 (Hz) F3 (Hz) Duration (ms)
/uː/ 20 % 180 428 992 2,663 169
30 % 181 431 954 2,689
40 % 182 432 932 2,709
50 % 184 435 924 2,720
60 % 185 440 966 2,732
70 % 186 446 1,021 2,729
80 % 186 452 1,133 2,714
/iː/ 20 % 174 379 2,173 2,757 169
30 % 174 381 2,193 2,770
40 % 175 379 2,197 2,763
50 % 176 380 2,220 2,756
60 % 177 384 2,206 2,751
70 % 178 390 2,173 2,723
80 % 179 393 2,153 2,704
/aː/ 20 % 173 633 1,573 2,571 175
30 % 173 670 1,538 2,548
40 % 174 688 1,500 2,533
50 % 175 702 1,491 2,514
60 % 175 716 1,471 2,538
70 % 176 716 1,464 2,538
80 % 178 700 1,462 2,510
/eː/ 20 % 176 507 1,941 2,610 187
30 % 178 496 1,999 2,605
40 % 180 480 2,046 2,610
50 % 183 464 2,089 2,622
60 % 186 449 2,107 2,639
70 % 187 436 2,105 2,645
80 % 187 426 2,121 2,654
/oː/ 20 % 178 515 1,194 2,608 172
30 % 179 522 1,139 2,629
40 % 180 518 1,090 2,658
50 % 181 510 1,037 2,663
60 % 183 506 1,040 2,669
70 % 184 502 1,065 2,674
80 % 185 499 1,136 2,653
/u/ 20 % 181 466 1,213 2,614 80
30 % 181 476 1,206 2,613
40 % 182 482 1,203 2,606
50 % 183 488 1,214 2,607
60 % 184 491 1,230 2,611
70 % 186 491 1,243 2,610
80 % 186 487 1,249 2,604
/i/ 20 % 177 444 1,969 2,642 79
30 % 177 455 1,968 2,644
40 % 177 463 1,962 2,644
50 % 178 469 1,953 2,648
60 % 179 472 1,947 2,640
70 % 180 471 1,915 2,627
80 % 181 467 1,901 2,630
/a/ 20 % 176 547 1,720 2,582 92
30 % 177 568 1,721 2,565
40 % 177 581 1,723 2,559
50 % 179 586 1,727 2,544
60 % 180 586 1,725 2,546
70 % 182 577 1,720 2,528
80 % 184 563 1,731 2,517
Table A3:

The statistical results of the acoustic cues of Hijazi Arabic vowels; grey cells denote non-significant results.

F0 F1 F2 F3
Diff p< Diff p< Diff p< Diff p<
/aː/ vs. /a/ Static model −4.03 0.9832 115.1 0.0001 −235.4 0.0001 −29.7 0.9392
Offset model 0.78 0.9964 27.8 0.0001 81.4 0.0001 32.3 0.5303
Slope model −0.05 0.0001 0.28 0.0001 −0.8 0.0001 0.36 0.5565
Direction model (two-point) −4.53 0.9689 111.6 0.0001 −208.2 0.0001 −9.03 0.9999
Direction model (three-point) −4.36 0.7543 112.8 0.0001 −217.3 0.0001 −15.9 0.9940
Direction model (seven-point) −4.44 0.0686 116.5 0.0001 −224.0 0.0001 −12.7 0.9249
/uː/ vs. /u/ Static model 0.20 1.0000 −53.1 0.0001 −290.3 0.0001 −112.9 0.0002
Offset model −0.63 0.9991 1.02 0.9999 −43.6 0.0679 −12.2 0.9960
Slope model −0.01 0.9922 −0.07 0.5969 0.30 0.7266 0.27 0.8425
Direction model (two-point) −0.46 1.0000 −36.4 0.0001 −167.9 0.0001 −79.2 0.0001
Direction model (three-point) −0.24 1.0000 −42.0 0.0001 −208.7 0.0001 −90.4 0.0001
Direction model (seven-point) −0.03 1.0000 −45.1 0.0003 −233.5 0.0001 −98.7 0.0001
/iː/ vs. /i/ Static model −2.45 0.9992 −89.1 0.0001 −266.6 0.0001 −108.0 0.0005
Offset model 1.68 0.7876 2.78 0.9954 26.8 0.5976 4.23 0.9999
Slope model −0.01 0.9890 −0.19 0.0001 0.6 0.0001 −0.15 0.9933
Direction model (two-point) −2.74 0.9982 −68.8 0.0001 −228.1 0.0001 −94.8 0.0001
Direction model (three-point) −2.64 0.9742 −75.6 0.0001 −240.9 0.0001 −99.1 0.0001
Direction model (seven-point) −2.60 0.5824 −79.1 0.0001 −243.0 0.0001 −107.2 0.0001
/oː/ vs. /eː/ Static model −1.88 0.9998 45.7 0.0001 −1,051.7 0.0001 40.9 0.7404
Offset model −3.9 0.0001 −35.9 0.0001 19.2 0.8929 −13.4 0.9931
Slope model −0.01 0.8251 0.39 0.0001 −1.3 0.0001 0.01 1.0000
Direction model (two-point) −0.46 1.0000 41.3 0.0001 −865.8 0.0001 79.2 0.3511
Direction model (three-point) −0.82 0.9999 42.1 0.0001 −927.8 0.0001 12.7 0.9985
Direction model (seven-point) −1.08 0.9935 44.7 0.0001 −958.1 0.0001 24.4 0.3007
/eː/ vs. /i/ Static model −4.74 0.9584 4.31 0.9942 −135.6 0.0001 26.2 0.9694
Offset model −6.69 0.0001 −55.4 0.0001 −105.7 0.0001 −33.3 0.4902
Slope model −0.02 0.1979 0.71 0.0001 −1.81 0.0001 −0.42 0.3351
Direction model (two-point) −2.57 0.9988 −11.4 0.9998 −112.1 0.0006 3.91 1.0000
Direction model (three-point) −3.29 0.9225 −6.17 0.9999 −117.3 0.0001 11.3 0.9992
Direction model (seven-point) −3.73 0.1567 −2.50 0.9999 −120.1 0.0001 12.8 0.9195
/oː/ vs. /u/ Static model 2.08 0.9997 −19.4 0.0831 177.3 0.0001 −56.1 0.3436
Offset model −0.90 0.9916 −24.2 0.0001 15.9 0.9586 −30.2 0.6174
Slope model 0.01 1.0000 0.27 0.0001 1.06 0.0001 −0.33 0.6564
Direction model (two-point) 2.35 0.9993 −25.7 0.0001 123.4 0.0001 −21.4 0.9964
Direction model (three-point) 2.26 0.9892 −28.6 0.0001 153.0 0.0001 −33.0 0.7804
Direction model (seven-point) −0.03 1.0000 −30.2 0.0001 160.9 0.0001 −41.5 0.0056

References

Abdoh, Eman. 2011. A study of the phonological structure and representation of first words in Arabic. Leicester, UK: University of Leicester PhD thesis.Search in Google Scholar

Adank, Patti, Roel Smits & Roeland van Hout. 2004a. A comparison of vowel normalization procedures for language variation research. The Journal of the Acoustical Society of America 116(5). 3099–3107. https://doi.org/10.1121/1.1795335.Search in Google Scholar

Adank, Patti, Roeland van Hout & Roel Smits. 2004b. An acoustic description of the vowels of Northern and Southern Standard Dutch. The Journal of the Acoustical Society of America 116(3). 1729–1738. https://doi.org/10.1121/1.1779271.Search in Google Scholar

Al-Mazrouei, Aisha, Aisha Negm & Vladimir Kulikov. 2023. The vowel system of Qatari Arabic: Evidence for peripheral/non-peripheral distinction between long and short vowels. Journal of the International Phonetic Association 53(3). 1–19. https://doi.org/10.1017/S0025100323000117.Search in Google Scholar

Almbark, Rana & Sam Hellmuth. 2015. Acoustic analysis of the Syrian vowel system. Proceedings of the 18th International Congress of Phonetic Sciences (ICPhS). Glasgow, UK: The University of Glasgow.Search in Google Scholar

Almurashi, Wael, Jalal Al-Tamimi & Ghada Khattab. 2020. Static and dynamic cues in vowel production in Hijazi Arabic. The Journal of the Acoustical Society of America 147(4). 2917–2927. https://doi.org/10.1121/10.0001004.Search in Google Scholar

Al-Tamimi, Jalal. 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). Lyon, France: University Lyon PhD research. Available at: http://theses.univ-lyon2.fr/documents/lyon2/2007/al-tamimi_je.Search in Google Scholar

Al-Tamimi, Jalal. 2007b. Static and dynamic cues in vowel production: A cross dialectal study in Jordanian and Moroccan Arabic. In Proceedings of the 16th ICPhS, 541–544. Saarbrücken, Germany: Saarland University.Search in Google Scholar

Al-Tamimi, Jalal & Emmanuel Ferragne. 2005. Does vowel space size depend on language vowel inventories? Evidence from two Arabic dialects and French. Proceedings of the 9th European conference on speech communication and technology, 2465–2468. Lisbon, Portugal: International Speech Communication Association.10.21437/Interspeech.2005-756Search in Google Scholar

Alzaidi, Muhammad. 2014. Information structure and intonation in Hijazi Arabic. Colchester, UK: University of Essex PhD thesis.Search in Google Scholar

Arnaud, Vincent, Caroline Sigouina & Johanna-Pascale Roy. 2011. Acoustic description of Quebec French high vowels: First results. Proceedings of the 17th ICPhS, 244–247. Hong Kong, China: ‏City University of Hong Kong.Search in Google Scholar

Baayen, Harald, Douglas Davidson & Douglas Bates. 2008. Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory and Language 59(4). 390–412. https://doi.org/10.1016/j.jml.2007.12.005.Search in Google Scholar

Barr, Dale. 2013. Random effects structure for testing interactions in linear mixed-effects models. Quantitative Psychology and Measurement 4. 1–2. https://doi.org/10.3389/fpsyg.2013.00328.Search in Google Scholar

Barr, Dale, Roger Levy, Christoph Scheepers & Harry Tily. 2013. Random effects structure for confirmatory hypothesis testing: Keep it maximal. Journal of Memory and Language 68(3). 255–278. https://doi.org/10.1016/j.jml.2012.11.001.Search in Google Scholar

Bates, Douglas, Martin Mächler, Ben Bolker & Steve Walker. 2015. Fitting linear mixed-effects models using lme4. Journal of Statistical Software 67(1). 1–48. https://doi.org/10.18637/jss.v067.i01.Search in Google Scholar

Boersma, Paul & David Weenink. 2022. Praat: Doing phonetics by computer. Available at: http://www.praat.org.Search in Google Scholar

Cardoso, Amanda. 2015. Dialectology, phonology, diachrony: Liverpool English realisations of PRICE and MOUTH. Edinburgh, UK: University of Edinburgh PhD research.Search in Google Scholar

Chladkova, Kateřina & Silke Hamann. 2011. High vowels in Southern British English: /u/-fronting does not result in merger. Proceedings of the 17th ICPhS, 476–479. Hong Kong, China: City University of Hong Kong.Search in Google Scholar

Clopper, Cynthia & David Pisoni. 2004. Some acoustic cues for the perceptual categorization of American English regional dialects. Journal of Phonetics 32(1). 111–140. https://doi.org/10.1016/S0095-4470(03)00009-3.Search in Google Scholar

Darcy, Isabelle & Joan Mora. 2015. Tongue movement in a second language: The case of Spanish/ei/-/e/ for English learners of Spanish. Proceedings of the 18th ICPhS. Glasgow, UK: The University of Glasgow.Search in Google Scholar

Elvin, Jaydene, Daniel Williams & Paola Escudero. 2016. Dynamic acoustic properties of monophthongs and diphthongs in Western Sydney Australian English. The Journal of the Acoustical Society of America 140(1). 576–581. https://doi.org/10.1121/1.4952387.Search in Google Scholar

Fabricius, Anne, Dominic Watt & Daniel Johnson. 2009. A comparison of three speaker-intrinsic vowel formant frequency normalization algorithms for sociophonetics. Language Variation and Change 21(3). 413–435. https://doi.org/10.1017/S0954394509990160.Search in Google Scholar

Farrington, Charlie, Tyler Kendall & Valerie Fridland. 2018. Vowel dynamics in the southern vowel shift. American Speech: A Quarterly of Linguistic Usage 93(2). 186–222. https://doi.org/10.1215/00031283-6926157.Search in Google Scholar

Ferguson, Sarah & Diane Kewley-Port. 2002. Vowel intelligibility in clear and conversational speech for normal-hearing and hearing-impaired listeners. The Journal of the Acoustical Society of America 112(1). 259–271. https://doi.org/10.1121/1.1482078.Search in Google Scholar

Fox, Robert. 1983. Perceptual structure of monophthongs and diphthongs in English. Language and Speech 26(1). 21–60. https://doi.org/10.1177/002383098302600103.Search in Google Scholar

Fox, Robert & Ewa Jacewicz. 2009. Cross-dialectal variation in formant dynamics of American English vowels. The Journal of the Acoustical Society of America 126(5). 2603–2618. https://doi.org/10.1121/1.3212921.Search in Google Scholar

Gottfried, Michael, James Miller & Donald Meyer. 1993. Three approaches to the classification of American English vowels. Journal of Phonetics 21(3). 205–229. https://doi.org/10.1016/S0095-4470(19)31337-3.Search in Google Scholar

Harrington, Jonathan & Stephen Cassidy. 1994. Dynamic and target theories of vowel classification: Evidence from monophthongs and diphthongs in Australian English. Language and Speech 37(4). 357–373. https://doi.org/10.1177/002383099403700402.Search in Google Scholar

Hillenbrand, James. 2013. Static and dynamic approaches to vowel perception. In Geoffrey Morrison & Peter Assmann (eds.), Vowel inherent spectral change, 9–30. Berlin: Springer.10.1007/978-3-642-14209-3_2Search in Google Scholar

Hillenbrand, James, Michael Clark & Terrance Nearey. 2001. Effects of consonant environment on vowel formant patterns. The Journal of the Acoustical Society of America 109(2). 748–763. https://doi.org/10.1121/1.1337959.Search in Google Scholar

Hillenbrand, James, Laura Getty, Michael Clark & Kimberlee Wheeler. 1995. Acoustic characteristics of American English vowels. The Journal of the Acoustical Society of America 97(5). 3099–3111. https://doi.org/10.1121/1.411872.Search in Google Scholar

Hillenbrand, James & Terrance Nearey. 1999. Identification of resynthesized /hvd/ utterances: Effects of formant contour. The Journal of the Acoustical Society of America 105(6). 3509–3523. https://doi.org/10.1121/1.424676.Search in Google Scholar

Hothorn, Torsten, Frank Bretz, Peter Westfall, Richard Heiberger, Andre Schuetzenmeister & Susan Scheibe. 2016. Package “multcomp”: Simultaneous inference in general parametric models. R package version 1.4-16. Available at: http://cran.stat.sfu.ca/web/packages/multcomp/multcomp.pdf.Search in Google Scholar

Huang, Caroline. 1992. Modelling human vowel identification using aspects of formant trajectory and context. In Yoh’ichi Tohkura, Eric Vatikiotis-Bateson & Yoshinori Sagisaka (eds.), Speech perception, production and linguistic structure, 43–61. Amsterdam: IOS Press.Search in Google Scholar

Jin, Su-Hyun & Chang Liu. 2013. The vowel inherent spectral change of English vowels spoken by native and non-native speakers. The Journal of the Acoustical Society of America 133(5). 363–369. https://doi.org/10.1121/1.4798620.Search in Google Scholar

Khattab, Ghada. 2007. A phonetic study of gemination in Lebanese Arabic. Proceedings of the 16th ICPhS, 153–158. Saarbrücken, Germany: Saarland University.Search in Google Scholar

Khattab, Ghada & Jalal Al-Tamimi. 2008. Durational cues for gemination in Lebanese Arabic. Language and Linguistics 11(22). 39–55.Search in Google Scholar

Lobanov, Boris. 1971. Classification of Russian vowels spoken by different speakers. The Journal of the Acoustical Society of America 49. 606–608. https://doi.org/10.1121/1.1912396.Search in Google Scholar

Manuel, Sharon. 1990. The role of contrast in limiting vowel-to-vowel coarticulation in different languages. The Journal of the Acoustical Society of America 88(3). 1286–1298. https://doi.org/10.1121/1.399705.Search in Google Scholar

McDougall, Kirsty. 2002. Speaker-characterising properties of formant dynamics: A case study. Proceedings of the 9th Australian international conference on speech science and technology, 403–408. Melbourne: Australian Speech Science and Technology Association.Search in Google Scholar

McDougall, Kirsty. 2006. Dynamic features of speech and the characterisation of speakers: Towards a new approach using formant frequencies. International Journal of Speech Language and the Law 13(1). 89–126. https://doi.org/10.1558/sll.2006.13.1.89.Search in Google Scholar

McDougall, Kirsty & Francis Nolan. 2007. Discrimination of speakers using the formant dynamics of /uː/ in British English. Proceedings of the 16th ICPhS, 1825–1828. Saarbrücken, Germany: Saarland University.Search in Google Scholar

Meunier, Christine, Cheryl Frenck-Mestre, Taissia Lelekov-Boissard & Martine Le Besnerais. 2003. Production and perception of vowels: Does the density of the system play a role? Proceedings of the 15th ICPhS, 723–726. Barcelona, Spain: Causal Productions.Search in Google Scholar

Mok, Peggy. 2013. Does vowel inventory density affect vowel-to-vowel coarticulation? Language and Speech 56(2). 191–209. https://doi.org/10.1177/0023830912443948.Search in Google Scholar

Morrison, Geoffrey & Peter Assmann. 2013. Vowel inherent spectral change. Berlin: Springer.10.1007/978-3-642-14209-3Search in Google Scholar

Morrison, Geoffrey & Terrance Nearey. 2007. Testing theories of vowel inherent spectral change. The Journal of the Acoustical Society of America 122(1). 15–22. https://doi.org/10.1121/1.2739111.Search in Google Scholar

Nearey, Terrance. 2013. Vowel inherent spectral change in vowels in North American English. In Geoffrey Morrison & Peter Assmann (eds.), Vowel inherent spectral change, 49–85. Berlin: Springer.10.1007/978-3-642-14209-3_4Search in Google Scholar

Nearey, Terrance & Peter Assmann. 1986. Modeling the role of inherent spectral change in vowel identification. The Journal of the Acoustical Society of America 80(5). 1297–1308. https://doi.org/10.1121/1.394433.Search in Google Scholar

Neel, Amy. 2004. Formant detail needed for vowel identification. Acoustics Research Letters Online 5(4). 125–131. https://doi.org/10.1121/1.1764452.Search in Google Scholar

Oh, Eunjin. 2013. Dynamic spectral patterns of American English front monophthong vowels produced by Korean-English bilingual speakers and Korean late learners of English. Linguistic Research 30(2). 293–312. https://doi.org/10.17250/khisli.30.2.201308.007.Search in Google Scholar

Peterson, Gordon & Harold Barney. 1952. Control methods used in a study of the vowels. The Journal of the Acoustical Society of America 24(2). 175–184. https://doi.org/10.1121/1.1906875.Search in Google Scholar

Pinheiro, José, Douglas Bates, Saikat DebRoy, Deepayan Sarkar, Siem Heisterkamp & Bert Van Willigen. 2017. Package “nlme”. Linear and nonlinear mixed effects models. R package version 3.1-152. Available at: https://CRAN.R-project.org/package=nlme.Search in Google Scholar

R Core Team. 2022. R: A language and environment for statistical computing (version 4.0.4). Vienna, Austria: R Foundation for Statistical Computing. [Software Resource]. Available at: https://www.R-project.org/.Search in Google Scholar

Rosner, Burton & John Pickering. 1994. Vowel perception and production. Oxford: Oxford University Press.10.1093/acprof:oso/9780198521389.001.0001Search in Google Scholar

RStudio. 2022. Rstudio: Integrated development environment for R (version 1.4.1103). Boston, MA: RStudio. [Software Resource]. Available at: https://rstudio.com/.Search in Google Scholar

Schwartz, Geoffrey. 2021. The phonology of vowel VISC-osity–acoustic evidence and representational implications. Glossa: A Journal of General Linguistics 6(1). 1–30. https://doi.org/10.5334/gjgl.1182.Search in Google Scholar

Singmann, Henrik, Ben Bolker, Jake Westfall, Frederik Aust, Mattan Ben-Shachar, Søren Højsgaard, John Fox, Michael Lawrence, Ulf Mertens, Jonathon Love, Russell Lenth & Rune Christensen. 2018. afex: Analysis of factorial experiments. R Package Version 0.28-1. Available at: https://CRAN.R-project.org/package=afex.Search in Google Scholar

Slifka, Janet. 2003. Tense/lax vowel classification using dynamic spectral cues. Proceedings of the 15th ICPhS, 921–924. Barcelona, Spain: Causal Productions.Search in Google Scholar

Stevens, Kenneth & Arthur S. House. 1963. Perturbation of vowel articulations by consonantal context: An acoustical study. Journal of Speech and Hearing Research 6(2). 111–128. https://doi.org/10.1044/jshr.0602.111.Search in Google Scholar

Tiffany, William. 1953. Vowel recognition as a function of duration, frequency modulation and phonetic context. The Journal of Speech and Hearing Disorders 18(3). 289–301. https://doi.org/10.1044/jshd.1803.289.Search in Google Scholar

Van Son, Rob & Louis Pols. 1992. Formant movements of Dutch vowels in a text, read at normal and fast rate. The Journal of the Acoustical Society of America 92(1). 121–127. https://doi.org/10.1121/1.404277.Search in Google Scholar

Venables, Bill & Brian Ripley. 2002. Modern applied statistics with S, 4th edn. New York: Springer. R package version 7.3-53.1.10.1007/978-0-387-21706-2Search in Google Scholar

Watson, Catherine & Jonathan Harrington. 1999. Acoustic evidence for dynamic formant trajectories in Australian English vowels. The Journal of the Acoustical Society of America 106(1). 458–468. https://doi.org/10.1121/1.427069.Search in Google Scholar

Wickham, Hadley. 2016. ggplot2: Elegant graphics for data analysis. New York: Springer-Verlag. R package version 3.3.3. Available at: https://ggplot2.tidyverse.org.Search in Google Scholar

Wickham, Hadley. 2017. Package tidyverse: Easily install and load the “tidyverse”. R package version 1.3.0. Available at: https://cran.r-project.org/web/packages/tidyverse/tidyverse.pdf.10.32614/CRAN.package.tidyverseSearch in Google Scholar

Wickham, Hadley, Romain François, Lionel Henry & Kirill Müller. 2019. Dplyr: A grammar of data manipulation. R package version 1.0.4. Available at: https://CRAN.R-project.org/package=dplyr.Search in Google Scholar

Williams, Daniel & Paola Escudero. 2014. A cross-dialectal acoustic comparison of vowels in Northern and Southern British English. The Journal of the Acoustical Society of America 136(5). 2751–2761. https://doi.org/10.1121/1.4896471.Search in Google Scholar

Wood, Simon. 2015. Package “mgcv”. R package version 1.8-34. Available at: http://cran.r-project.org/web/packages/mgcv/mgcv.pdf.Search in Google Scholar

Yang, Byunggon. 1996. A comparative study of American English and Korean vowels produced by male and female speakers. Journal of Phonetics 24(2). 245–261. https://doi.org/10.1006/jpho.1996.0013.Search in Google Scholar

Yuan, Jiahong. 2013. The spectral dynamics of vowels in Mandarin Chinese. Proceedings of the 14th annual conference of the International Speech Communication Association, 1193–1197. Lyon, France: International Speech Communication Association.10.21437/Interspeech.2013-18Search in Google Scholar

Zahorian, Stephen & Amir Jagharghi. 1993. Spectral-shape features versus formants as acoustic correlates for vowels. The Journal of the Acoustical Society of America 94(4). 1966–1982. https://doi.org/10.1121/1.407520.Search in Google Scholar

Received: 2023-04-27
Accepted: 2024-01-16
Published Online: 2024-02-15
Published in Print: 2024-04-25

© 2024 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 19.9.2025 from https://www.degruyterbrill.com/document/doi/10.1515/phon-2023-0013/html
Scroll to top button