Improving nonnative speech perception and production through an AI-powered application

While research on using artificial intelligence (AI) through various applications to enhance foreign language pronunciation is expanding, it has primarily focused on aspects such as comprehensibility and intelligibility, largely neglecting the improvement of individual speech sounds in both perception and production. This study seeks to address this gap by examining the impact of training with an AI-powered mobile application on nonnative sound perception and production, analyzed as separate tasks. Participants completed a pretest assessing their ability to discriminate the second language (L2) English /iː/–/ɪ/ contrast and produce these vowels in sentence contexts. The intervention involved training with the Speakometer mobile application, which incorporated recording tasks featuring the English vowels, along with pronunciation feedback and practice. Importantly, the training targeted production only and did not include vowel discrimination exercises. The posttest mirrored the pretest to measure changes in performance. The results indicated modest but statistically significant gains in discrimination accuracy and in some aspects of production of the target contrast following the intervention. Specifically, posttest performance showed greater acoustic separation of the vowels and a more native-like duration difference, although performance remained below native-speaker levels. These findings suggest that AI-powered applications may support L2 speech learning and may serve as a useful resource for personalized, interactive pronunciation practice beyond the classroom.