With the growing prevalence of artificial intelligence (AI) in education, spoken English learning has undergone significant transformation. This literature review explores the effectiveness of AI-powered tools—including speech recognition, chatbots, and intelligent tutoring systems—in improving pronunciation, fluency, and learner engagement. Framed by Computer-Assisted Language Learning (CALL) and Second Language Acquisition (SLA) theories, the review synthesizes findings from over a decade of research. Evidence suggests that AI facilitates individualized learning and provides instant feedback that enhances oral proficiency. However, limitations persist, particularly in providing contextual feedback, accommodating diverse accents, and mitigating overreliance on AI systems. The review concludes by highlighting future directions such as context-aware AI systems, inclusive speech recognition, hybrid learning models, and metacognitive training. These insights inform pedagogical design and call for balanced integration of AI and human-led instruction to foster effective spoken English acquisition.
Bin et al. (2025) studied this question.