PRONUNCIATION TRAINING USING AI VOICE TECHNOLOGY
Keywords:
artificial intelligence, pronunciation training, speech recognition, language learning, phonetics.Abstract
The advancement of artificial intelligence (AI) has significantly transformed language learning methodologies, particularly in the domain of pronunciation training. Traditional approaches often rely on instructor feedback, which may be limited by time, subjectivity, and accessibility. AI voice technology offers a scalable, consistent, and data-driven alternative that enhances learners’ phonetic accuracy and communicative competence. This thesis examines the role of AI-powered speech recognition, synthesis, and feedback systems in improving pronunciation skills among second language learners. Drawing on recent empirical studies, the research highlights the effectiveness of AI tools in providing real-time corrective feedback, personalized learning pathways, and increased learner autonomy. The findings suggest that AI voice technology not only supplements traditional instruction but also redefines pronunciation pedagogy in contemporary language education.
References
Derwing, T. M., & Munro, M. J. (2015). Pronunciation fundamentals: Evidence-based perspectives for L2 teaching and research. John Benjamins.
Fouz-González, J. (2020). Using apps for pronunciation training: An empirical study. Computer Assisted Language Learning, 33(7), 1–24. https://doi.org/10.1080/09588221.2019.1595661
Leong, C. W., & Mak, B. (2014). Automatic pronunciation assessment: Recent trends and future directions. Speech Communication, 63–64, 1–18. https://doi.org/10.1016/j.specom.2014.05.001
Liakin, D., Cardoso, W., & Liakina, N. (2017). Learning L2 pronunciation with a mobile speech recognition app. CALICO Journal, 34(1), 1–25. https://doi.org/10.1558/cj.26744
McCrocklin, S. M. (2016). Pronunciation learner autonomy: The potential of automatic speech recognition. System, 57, 25–42. https://doi.org/10.1016/j.system.2015.12.013
Lutsenko, E. V. (n.d.). Intelligent scalable open interactive online environment for teaching and researching. Kuban State Agricultural University.
Caballé, S., Demetriadis, S., Gómez-Sánchez, E., Papadopoulos, P., & Weinberger, A. (Eds.). (2016). Intelligent systems and learning data analytics in online education. Academic Press.
Downloads
Published
How to Cite
Issue
Section
License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.