Having to build oral proficiency can be difficult for L2 learners, mainly because they often lacked enough chances to practice and receive feedback. While NLP tools presented potential for automated speaking practice, research on their effectiveness from the learner's viewpoint is still evolving. This study employed a quantitative research framework. Data was collected via Google Forms survey L2 learners using NLP tools (e.g., speech recognition, automated pronunciation evaluation, conversational AI). The survey examined improvements in fluency, precision, self-assurance, and participant contentment. The analysis was expected to reveal a strong positive correlation between NLP tool usage and self-reported speaking skill enhancements. Projected findings showed significant improvements in recognized pronunciation accuracy and spoken fluency. Results also demonstrated that immediate, automated feedback enhanced learner confidence and motivation for oral practice. The outcomes indicated that NLP tools were effective further resources for L2 speaking development. They offered scalable, personalized practice addressing limitations in traditional educational settings. In the long run, applying NLP-based speaking tools into language programs enabled learners to adopt a more proactive and confident approach to achieving oral proficiency
Published in: 8th IEOM Bangladesh International Conference on Industrial Engineering and Operations Management, Dhaka, Bangladesh
Publisher: IEOM Society International
Date of Conference: December 20
-21
, 2025
ISBN: 979-8-3507-4441-5
ISSN/E-ISSN: 2169-8767