THE IMPACT OF HUMAN-MACHINE INTERACTION ON ENGLISH PRONUNCIATION AND FLUENCY: CASE STUDIES USING AI SPEECH ASSISTANTS

Abstract

This systematic review investigates the impact of human-machine interaction, specifically through AI-powered speech assistants, on the development of English pronunciation and fluency among second language learners. Drawing on 54 peer-reviewed studies published between 2005 and 2023, the review synthesizes findings from experimental, quasi-experimental, longitudinal, and mixed-method research that explore how tools such as Siri, Alexa, Google Assistant, and ELSA Speak influence oral language performance. The review follows the PRISMA 2020 guidelines to ensure methodological transparency, with eligibility criteria focusing on studies that employed measurable outcomes related to segmental and suprasegmental pronunciation features, temporal fluency metrics, acoustic analysis, and learner perceptions. The results reveal consistent improvements in phoneme articulation, word stress, intonation, speech rate, and pause reduction after sustained AI-mediated practice. Learners also demonstrated increased metacognitive awareness, greater confidence, and behavioral shifts toward self-regulated learning, particularly when interpreting implicit feedback from AI systems. Furthermore, the adaptability of AI speech tools across cultural contexts and learning settings highlights their scalability and pedagogical value. This review affirms the growing role of AI speech assistants as effective, accessible, and motivational tools for enhancing spoken English proficiency and offers recommendations for their integration into second language instruction and learner autonomy frameworks.