Adopting AI-Based Speech Recognition for Enhancing Pronunciation Accuracy and Learner Confidence

This study examines the integration of AI–based speech recognition (ELSA Speak, Speechling) in a language centre and its effects on pronunciation accuracy and learner confidence. Two groups of intermediate EFL learners (N = 40) completed pre-test and post-test diagnostic pronunciation assessments, with the experimental group receiving support through AI-app usage analytics. The comparative results revealed that the AI-assisted group demonstrated significantly more positive outcomes than the control group (p < .001), thus achieving higher post-test scores and increased learner confidence in the pronunciation assessment in the experimental group (paired t, p < .001). Consistent engagement in AI-assisted pronunciation practice was associated with improved performance (r = .62, p < .01). Quantitative results showed that learners using AI tools achieved higher pronunciation scores and confidence, while qualitative findings indicated reduced speaking anxiety, sustained motivation, and enhanced learner autonomy, despite minor implementation challenges such as connectivity issues and occasional feedback perception mismatches. The findings show the effective integration of AI-based pronunciation tools with conventional language instruction through feedback and self-regulated learning scaffolds. However, the intact–class design, single-centre context, and short duration result in limiting generalizability, demanding a longitudinal, multi-site replication.       Conflict of interest: The authors have declared no potential conflicts of interest and falsification/fabrication of data with respect to the research, authorship, and/or publication of this article.