English as Second Language (ESL) learners often struggle with pronunciation, which can hinder academic success and social integration. This study investigates the effectiveness of a speech-to-text artificial intelligence (AI) system in improving pronunciation accuracy among ESL learners. Using a phoneme-matching approach, the system provided real- time corrective feedback to students in semi-urban learning environments. Data were collected through pre- and post-tests measuring accuracy, precision, recall, and F1-score. Results revealed a 15% improvement in pronunciation accuracy, supported by consistent gains across all performance metrics. Learners also demonstrated increased confidence and sustained engagement, highlighting the motivational value of instant AI-based feedback. These findings suggest that speech- to-text AI can complement traditional instruction by offering personalized and continuous pronunciation training. Future research should explore long-term retention and integration with immersive technologies such as virtual and augmented reality.
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Prakash et al. (Wed,) studied this question.
www.synapsesocial.com/papers/68c1d60654b1d3bfb60f95b7 — DOI: https://doi.org/10.38124/ijisrt/25aug1065
T. L. Prakash
S. Kausalya
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