Voice Onset Time in the Production of English Stops: A Comparative Study of Native and Arabic-Speaking EFL Learners

Authors

  • Hesham Al-Damen

    Department of English Language and Literature, School of Foreign Languages, University of Jordan, Amman 11942, Jordan
  • Mohamad Almashour

    Department of English Language and Literature, School of Foreign Languages, University of Jordan, Amman 11942, Jordan
  • Mutasim Al-Deaibes

    Department of English Language and Literature, Faculty of Arts, Yarmouk University, Irbid 21163, Jordan
  • Rami Alsharefeen

    Academic Affairs Section, Rabdan Academy, Abu Dhabi 22401, United Arab Emirates

DOI:

https://doi.org/10.30564/fls.v7i7.9466
Received: 12 April 2025 | Revised: 13 May 2025 | Accepted: 19 June 2025 | Published Online: 16 July 2025

Abstract

This study examines the production of Voice Onset Time (VOT) in English stop consonants by native speakers of American English and Arabic-speaking English as a Foreign Language (EFL) learners at two proficiency levels. VOT, an acoustic parameter, is an essential feature in distinguishing between voiced and voiceless stops. Drawing on Flege’s Speech Learning Model (SLM), the research investigates whether learners differentiate between voiceless and voiced stops (/p/ vs. /b/) and apply appropriate aspiration in /sp/ clusters, and whether proficiency influences VOT patterns. Data were collected from 29 native English speakers and 58 Arabic-speaking learners, who produced minimal pairs and /sp/ cluster words embedded in carrier sentences. All tokens were annotated manually in Praat and analyzed using linear mixed effects models. Results showed that native speakers maintained robust VOT distinctions, while Novice-High learners exhibited overlapping distributions between /p/ and /b/ and inappropriate aspiration in clusters. Intermediate-High learners produced more target-like patterns, suggesting early stages of L2 category formation. Findings support the SLM’s predictions and underscore the need for explicit instruction on VOT contrasts and improvements in AI-assisted pronunciation feedback tools. The study concludes with some pedagogical implications for pronunciation instruction. For example, teachers working with Arabic-speaking learners should highlight the role of aspiration in English voicing contrasts and explicitly address its absence in /sp/ clusters.

Keywords:

Voice Onset Time (VOT); Speech Learning Model (SLM); Arabic EFL Learners; Second Language Phonetics; Aspiration; Phonetic Category Formation; Acoustic Analysis; Pronunciation Instruction; AI in Language Learning

References

[1] Lisker, L., Abramson, A.S., 1964. A cross-language study of voicing in initial stops: Acoustical measurements. Word. 20(3), 384–422. DOI: https://doi.org/10.1080/00437956.1964.11659830

[2] Li, F., 2013. The effect of speakers' sex on voice onset time in Mandarin stops. The Journal of the Acoustical Society of America. 133(2), EL142-EL147. DOI: https://doi.org/10.1121/1.4778281

[3] Morris, R.J., McCrea, C.R., Herring, K.D., 2008. Voice onset time differences between adult males and females: Isolated syllables. Journal of Phonetics. 36, 308–317. DOI: https://doi.org/10.1016/j.wocn.2007.06.003

[4] Oh, E., 2019. Effects of gender on voice onset time and fundamental frequency cues in perception and production of English stops. Linguist Res. 36(1), 67–89. DOI: https://doi.org/10.17250/khisli.36.1.201903.003

[5] Cho, T., Ladefoged, P., 1999. Variation and universals in VOT: evidence from 18 languages. Journal of Phonetics. 27(2), 207–29. DOI: https://doi.org/10.1006/jpho.1999.0094

[6] Zampini, M.L., 1998. The relationship between the production and perception of L2 Spanish stops. Texas papers in foreign language education. 3(3), 85–100.

[7] Al-Deaibes, M., Alsharefeen, R., Rabab’ah, G., et al., 2025. Voice onset time in the Emirati Arabic dialect. Cogent Arts Humanit. 12(1), 2483604. DOI: https://doi.org/10.1080/23311983.2025.2483604

[8] Li, M., He, L., Luo, Y., et al., 2021. AI-based pronunciation feedback and L2 fluency: Advancing individualized instruction in computer-assisted language learning. Computer Assisted Language Learning. 34(3), 303–328.

[9] Boersma, P., Weenink, D., 2024. Praat: Doing phonetics by computer [Computer program]. Version 2.7. Available from: https://www.praat.org ( cited 3 April 2025).

[10] Flege, J.E., 2020. The revised Speech Learning Model (SLM-r). In: Munro, M.J., Bohn, O.-S. (eds.). The Oxford Handbook of Language Phonology. Oxford University Press: Oxford, UK. pp. 3–24.

[11] Yeni-Komshian, G.H., Caramaza, A., Preston, M.S., 1977. A study of voicing in Lebanese Arabic. Journal of Phonetics. 5(1), 35–48. DOI: https://doi.org/10.1016/S0095-4470(19)31112-X

[12] Mitleb, F., 2001. Voice onset time of Jordanian Arabic stops. The Journal of the Acoustical Society of America. 109(5), 2474. DOI: https://doi.org/10.1121/1.4744787

[13] Almbark, R., Bouchhioua, N., Hellmuth, S., 2014. Acquisition of English VOT by Syrian Arabic and French speakers. In Proceedings of the 18th International Congress of Phonetic Sciences (ICPhS). Publisher: Glasgow, UK.

[14] Flege, J.E., 1995. Second language speech learning: Theory, findings, and problems. In: Strange W., (eds.). Speech perception and linguistic experience: Issues in cross-language research. York Press: Timonium, MD, USA. pp. 233–277.

[15] Al-Deaibes, M., Jarrah, M., 2023. Production of Arabic geminates by English speakers. J Psycholinguist Res. 52(6), 2877–2902. DOI: https://doi.org/10.1007/s10936-023-10025-w

[16] Best, C.T., Tyler, M.D., 2007. Nonnative and second-language speech perception: Commonalities and complementarities. In: Bohn, O.-S., Munro, M.J. (eds.). Language experience in second language speech learning: In honor of James Emil Flege. John Benjamins: Amsterdam, Netherlands. pp. 13–34.

[17] Mashaqba, B., Huneety, A., Al-Khawaldeh, N., et al., 2023. Acoustics of long vowels in Arabic-speaking children with hearing impairments. Humanit Soc Sci Commun. 10(1), 1–11. DOI: https://doi.org/10.1057/s41599-023-01778-9

[18] Boersma, P., Weenink, D., 2024. Praat: doing phonetics by computer. Available from: https://www.fon.hum.uva.nl/praat/ (cited 2 April 2025).

[19] Aldamen, H., Al-Deaibes, M., 2023. Arabic emphatic consonants as produced by English speakers: An acoustic study. Heliyon. 9(2), 1–12. DOI: https://doi.org/10.1016/j.heliyon.2023.e13401

[20] Aldamen, H., Al-Deaibes, M., 2023. Perception and production of L2 Arabic emphatic consonants: The role of communicative and traditional form-based approaches. Ampersand. 10, 100105. DOI: https://doi.org/10.1016/j.amper.2022.100105

[21] Levis, J.M., Moyer, A., 2021. Intelligibility in Pronunciation: Research and Practice. Cambridge University Press: Cambridge, UK.

[22] Cho, T., Ladefoged, P., 1999. Variation and universals in VOT: Evidence from 18 languages. Journal of Phonetics. 27, 207–229. DOI: https://doi.org/10.1006/jpho.1999.0094

[23] Rabab’ah, G., Cheikh, M., Al-Deaibes, M., 2024. Unraveling Conversational Implicatures: A Study on Arabic EFL Learners. Open Cultural Studies. 8(1), 20240006. DOI: https://doi.org/10.1515/culture-2024-0006

[24] Zampini, M.L., 1998. The relationship between the production and perception of L2 Spanish stops. Tex Papers in Foreign Language Education. 3(3), 85–100.

Downloads

How to Cite

Al-Damen, H., Almashour, M., Al-Deaibes, M., & Alsharefeen, R. (2025). Voice Onset Time in the Production of English Stops: A Comparative Study of Native and Arabic-Speaking EFL Learners. Forum for Linguistic Studies, 7(7), 747–757. https://doi.org/10.30564/fls.v7i7.9466

Issue

Vol. 7 , Iss. 7 (July 2025): In progress

Article Type

Article

License

Copyright © 2025 Hesham Al-Damen, Mohamad Almashour, Mutasim Al-Deaibes, Rami Alsharefeen

Creative Commons License

This is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.