How to Cite
Abstract
Advances in artificial intelligence (AI) have significantly reshaped contemporary language pedagogy, particularly in the domain of oral communication. Among the core components of speaking proficiency, pronunciation remains one of the most challenging skills to develop due to its inherently individualised, practice-intensive, and feedback-dependent nature. Traditional classroom methods often struggle to provide learners with the consistent, precise, and personalised feedback necessary for mastery. This study explores pedagogically sound and technologically supported methods for enhancing pronunciation skills through AI-driven tools, including automatic speech recognition, machine-learning-based accent analysis, adaptive tutoring, and gamified practice.
References
1. Celce-Murcia, M., Brinton, D. M., & Goodwin, J. M. (2010). Teaching pronunciation: A course book and reference guide (2nd ed.). Cambridge University Press.
2. Derwing, T. M., & Munro, M. J. (2015). Pronunciation fundamentals: Evidencebased perspectives for L2 teaching and research. John Benjamins.
3. Levis, J. M. (2018). Intelligibility, oral communication, and the teaching of pronunciation. In S. Gass & A. Mackey (Eds.), The Routledge handbook of second language acquisition (pp. 421–435). Routledge.
4. Trofimovich, P., & Gatbonton, E. (2006). Repetition and focus on form in second language pronunciation learning. Language Learning, 56(3), 397–430. https://doi.org/10.1111/j.1467-9922.2006.00385.x
5. Shin, D., & Son, J. B. (2021). Artificial intelligence in language learning: Implications for teaching and research. Language Learning & Technology, 25(2), 1–19. https://doi.org/10.1016/j.langtec.2021.03.001
This work is licensed under a Creative Commons Attribution 4.0 International License.
