Developing an AI-Powered Pronunciation Application to Improve English Pronunciation of Thai ESP Learners

This study examined the effects of using specially designed AI-mediated pronunciation application in enhancing the production of English fricative consonants among Thai English for Specific Purposes (ESP) learners. The research utilized a quasi-experimental design involving intact classes of 74 undergraduate students majoring in Thai Dance and Music Education, divided into control (N = 38) and experimental (N = 36) groups. Grounded in Skill Acquisition Theory, the experimental group received pronunciation training via a custom-designed AI application leveraging automatic speech recognition (ASR), offering ESP contextualized practices, real-time, and individualized feedback. In contrast, the control group underwent traditional teacher-led articulatory and teacher-assisted feedback. Pre- and post-test evaluations measured pronunciation for nine target fricatives in ESP-relevant contexts. The statistical analyses revealed significant improvements in both groups, with the AI-mediated group demonstrating substantially greater gains, particularly on challenging sounds absent in Thai, such as /θ/, /ð/, /z/, /ʃ/, and /h/. The findings underscore the potential of AI-driven interventions to address language-specific phonological challenges through personalized, immediate feedback and adaptive practices. The study provides empirical evidence for integrating advanced technology into ESP pronunciation pedagogy, informing future curriculum design for EFL contexts. Implications for theory, practice, and future research are discussed, emphasizing tailored technological solutions for language learners with specific phonological profiles.