Using Gemini Voice-To-Text in Facilitating Pronunciation Awareness Through Self-Correction Among Eighth-Grade Students

Authors

  • Mutiara Nimah Universitas Negeri Surabaya; Indonesia
  • Widyastuti Widyastuti Universitas Negeri Surabaya; Indonesia
  • Ahmad Munir Universitas Negeri Surabaya; Indonesia

DOI:

https://doi.org/10.37680/scaffolding.v8i3.10884

Keywords:

Artificial Intelligence, EFL Learning, Gemini Voice-to-Text, Pronunciation Awareness, Self-Correction

Abstract

This study aims to investigate how Gemini Voice-to-Text facilitates pronunciation awareness through self-correction among eighth-grade students in an English as a Foreign Language (EFL) classroom context. Specifically, it examines students’ experiences using the tool, how AI-generated transcription supports their awareness of pronunciation differences, and the practical benefits and challenges experienced during implementation. This study used a qualitative case study design. The participants in the study were eight eighth-grade students from SMP Negeri 16 Surabaya, East Java, Indonesia. These students participated in pronunciation activities using Gemini Voice-to-Text. Data were collected through classroom observation, semi-structured interviews, and documentation of the AI-generated transcription output. Analysis of the collected data was conducted thematically with data familiarization, coding, categorization, and developing themes. The findings revealed that students used Gemini Voice-to-Text through three interconnected processes: accessing the tool during speaking activities, reviewing AI-generated transcription, and comparing their spoken production with the recognized output. These processes provided students with opportunities to notice pronunciation differences and engage in self-correction through repetition and modification of their pronunciation. Students also perceived the tool as beneficial because it provided immediate feedback, supported independent practice, and increased opportunities for repeated pronunciation practice.  On the other hand, there were some problems with using the tool, especially regarding mistakes in the transcription due to varying ways people say words, how fast someone speaks, and the amount of noise in the classroom. This research concludes that Gemini Voice-to-Text can facilitate pronunciation awareness through self-correction when its feedback is critically interpreted by students and supported by teacher guidance.

References

Bashori, M., van Hout, R., Strik, H., & Cucchiarini, C. (2024). I Can Speak: Improving English Pronunciation Through Automatic Speech Recognition-Based Language Learning Systems. Innovation in Language Learning and Teaching, 18(5), 443-461. https://doi.org/10.1080/17501229.2024.2315101

Baskara, F. X. R. (2025). ChatGPT and Google Gemini in EFL Education: A Qualitative Exploration of Pedagogical Efficacy among Indonesian Sophomores. JOLLT Journal of Languages and Language Teaching, 13(1), 436-447. https://doi.org/10.33394/jollt.v13i1.9926

Carless, D., & Winstone, N. (2023). Teacher Feedback Literacy and its Interplay with Student Feedback Literacy. Teaching in Higher Education, 28(1), 150-163. https://doi.org/10.1080/13562517.2020.1782372

Celce-Murcia, M., Brinton, D. M., & Goodwin, J. M. (2010). Teaching Pronunciation Hardback with Audio CDs (2): A Course Book and Reference Guide. Cambridge University Press.

Dai, Y., & Wu, Z. (2022). Mobile-Assisted Peer Feedback on EFL Pronunciation: Outcome Effects, Interactional Processes, and Shaping Factors. System, 111, 102953. https://doi.org/10.1016/j.system.2022.102953

De Vrind, E., Janssen, F. J. J. M., Van Driel, J. H., & De Jong, N. H. (2024). Improving Self-Regulated Learning of Speaking Skills in Foreign Languages. The Modern Language Journal, 108(3), 601-624. https://doi.org/https://doi.org/10.1111/modl.12953

Du, J., & Daniel, B. K. (2024). Transforming Language Education: A Systematic Review of AI-Powered Chatbots for English as a Foreign Language Speaking Practice. Computers and Education: Artificial Intelligence, 6, 100230. https://doi.org/https://doi.org/10.1016/j.caeai.2024.100230

Ebedy, H. G. M. (2025). The Effect of Self-Monitoring Strategy in Developing Pronunciation Among EFL Majors: Links to self-esteem. Bsu-Journal of Pedagogy and Curriculum, 4(7), 1-25. https://doi.org/10.21608/bsujpc.2025.351432.1062

Emara, I., & Shaker, N. (2024). The impact of non-native English Speakers' Phonological and Prosodic Features on Automatic Speech Recognition Accuracy. Speech Communication. https://doi.org/10.1016/j.specom.2024.103038

Evers, K., & Chen, S. (2022). Effects of an Automatic Speech Recognition System with Peer Feedback on Pronunciation Instruction for Adults. Computer Assisted Language Learning, 35, 1869-1889.

Fathi, J., Rahimi, M., & Derakhshan, A. (2024). Improving EFL Learners’ Speaking Skills and Willingness to Communicate Via Artificial Intelligence-Mediated Interactions. System, 121, 103254. https://doi.org/https://doi.org/10.1016/j.system.2024.103254

Galante, A., & Piccardo, E. (2022). Teaching Pronunciation: Toward Intelligibility and comprehensibility. ELT Journal, 76(3), 375-386. https://doi.org/10.1093/elt/ccab060

Henry, J. (2025). Speech-To-Text Technology as a Tool For Pronunciation Assessment and Self-Correction in EFL Contexts: A Pilot Study. Elite: English and Literature Journal, 12(1), 68-79.

Huang, J. (2024). Enhancing EFL Speaking Feedback with ChatGPT's Voice Prompts. International Journal of TESOL Studies, 6(3), 4-23. https://doi.org/10.58304/ijts.20240302

Inceoglu, S., Chen, W.-H., & Lim, H. (2023). Assessment of L2 intelligibility: Comparing L1 listeners and Automatic Speech Recognition. Recall, 35(1), 89-104. https://doi.org/10.1017/S0958344022000192

Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F.,…Kasneci, G. (2023). ChatGPT for good? On opportunities and Challenges of Large Language Models for Education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274

Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). ChatGPT for Language Teaching and Learning. Relc Journal, 54(2), 537-550. https://doi.org/10.1177/00336882231162868

Leow, R. P. (2023). Noticing hypothesis. The TESOL Encyclopedia of English Language Teaching. https://doi. org/10.1002/9781118784235. eelt0086. pub2.

Levis, J. M. (2018). Intelligibility, Oral Communication, and the Teaching of Pronunciation. Cambridge University Press.

Liu, Y., binti Ab Rahman, F., & binti Mohamad Zain, F. (2025). A Systematic Literature Review of Research on Automatic Speech Recognition in EFL Pronunciation. Cogent Education, 12(1), 2466288.

Loewen, S., & Sato, M. (2024). Pronunciation. In S. Loewen & M. Sato (Eds.), A Practical Guide to Second Language Teaching and Learning (pp. 142-162). Cambridge University Press. https://doi.org/DOI: 10.1017/9781108780520.008

Marpaung, N. R., & Fithriani, R. (2023). English Speaking Anxiety Among Indonesian Junior High School Students: Unveiling Causes and Solutions. Tell-us Journal, 9(1), 146-163. https://doi.org/10.22202/tus.2023.v9i1.6678

Mompean, J. A. (2024). ChatGPT for L2 Pronunciation Teaching and Learning. ELT Journal. https://doi.org/10.1093/elt/ccae050

Mora, J. C., Mora-Plaza, I., & Bermejo Miranda, G. (2024). Speaking Anxiety and Task Complexity Effects on Second Language Speech. International Journal of Applied Linguistics, 34(1), 292-315. https://doi.org/https://doi.org/10.1111/ijal.12494

Ngo, T. T.-N., Chen, H. H.-J., & Lai, K. K.-W. (2024). The Effectiveness of Automatic Speech Recognition in ESL/EFL Pronunciation: A Meta-Analysis. Recall, 36(1), 4-21.

Nurilahiah, S., Hasim, W., & Dewi, S. (2026). Exploring Indonesian EFL Students’ Perceptions of Gemini AI in Developing English Speaking Skills. Pendas: Jurnal Ilmiah Pendidikan Dasar, 11, 279-286. https://doi.org/ https://doi.org/10.23969/jp.v11i02.48598

Panadero, E. (2017). A Review of Self-regulated Learning: Six Models and Four Directions for Research [Review]. Frontiers in Psychology, Volume 8 - 2017. https://doi.org/10.3389/fpsyg.2017.00422

Saito, K. (2019). Individual Differences in Second Language Speech Learning in Classroom Settings: Roles of Awareness in the Longitudinal Development of Japanese Learners’ English /ɹ/ pronunciation. Second Language Research, 35(2), 149-172. https://doi.org/10.1177/0267658318768342

Schmidt, R. W. (1990). The Role of Consciousness in Second Language Learning1. Applied Linguistics, 11(2), 129-158. https://doi.org/10.1093/applin/11.2.129

Shadiev, R., & Yang, M. (2020). Review of Studies on Technology-Enhanced Language Learning and Teaching. Sustainable Education and Approaches, 12(2), 524. https://doi.org/https://doi.org/10.3390/su12020524

Sun, W. (2023). The Impact of Automatic Speech Recognition Technology on Second Language Pronunciation and Speaking Skills of EFL Learners: A Mixed Methods Investigation. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1210187

Tai, T. Y., & Chen, H. H. J. (2024). Improving elementary EFL Speaking Skills with Generative AI Chatbots: Exploring Individual and Paired Interactions. Computers & Education, 220, 105112. https://doi.org/10.1016/j.compedu.2024.105112

Tong, F., Li, T., Liao, D., Xia, S., Li, S., Hong, Q., & Li, L. (2022). The Xmuspeech System for Accented English Automatic Speech Recognition. 12(3). https://doi.org/https://doi.org/10.3390/app12031478

Wang, X., & Hamill, C. (2021, 13-17 Dec. 2021). Automatic Generation of Diagnostic Content Feedback in Spoken Language Learning and Assessment. 2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU),

Widodo, A., Vivianti, V., Karim, S. A., & Polim, H. (2026). Task-Based Learning Reimagined: How Gemini AI Enhances EFL Students’ Speaking Fluency in Self-Directed Learning. JOLLT Journal of Languages and Language Teaching, 14(2), 596-611. https://doi.org/10.33394/jollt.v14i2.18207

Xodabande, I., Shiri, S., & Zohrabi, M. (2025). Exploring the Impacts of an AI-driven Instructional Intervention on Iranian EFL Learners' Pronunciation Skill Development. Discover Education, 4, 307. https://doi.org/10.1007/s44217-025-00782-2

Yan, H., Singh, M. K. S., & Rawian, R. M. (2024). AI-Based Corrective Feedback in EFL Interactive Speaking: Insights from Interactionist SLA Theory. Educational Sciences: Theory&Practice, 24(No. 1 (2024): Educational Sciences: Theory and Practice. https://doi.org/https://doi.org/10.12738/

Yaniafari, R. P., Olivia, V., & Suharyadi. (2022). The potential of ASR for improving English pronunciation: A review. KnE Social Sciences.

Zhang, & Meifang. (2024). Enhancing Self-Regulation and Learner Engagement in L2 Speaking: Exploring the Potential of Intelligent Personal Assistants Within a Learning-Oriented Feedback Framework. BMC Psychology, 12(421). https://doi.org/10.1186/s40359-024-01917-0

Zhang, Z. (2022). Noticing in Second Language Acquisition. BCP Education & Psychology, 7, 184-190. https://doi.org/10.54691/bcpep.v7i.2634

Zheng, L., & Yang, Y. (2024). Research Perspectives and Trends in Artificial Intelligence-Enhanced Language Education: A review. Heliyon, 10(19), e38617. https://doi.org/10.1016/j.heliyon.2024.e38617

Zimmerman, B. (2002). Becoming a Self-Regulated Learner: An Overview. Theory Into Practice, 41, 64-70. https://doi.org/10.1207/s15430421tip4102_2

Zou, B., Wang, C., Yan, Y., Du, X., & Ji, Y. (2024). Exploring English as a Foreign Language Learners’ Adoption and Utilisation of ChatGPT for Speaking Practice Through an Extended Technology Acceptance Model. International Journal of Applied Linguistics, 35(2), 689-704. https://doi.org/10.1111/ijal.12658

Published

2026-10-29