Development of English pronunciation skills: Use of digital tools and artificial intelligence for non-linguistic majors

The authors focus on the integration of digital tools and artificial intelligence (AI) in teaching English pronunciation to non-linguistic majors, addressing critical gaps in current pedagogical approaches. The research identifies key challenges in pronunciation acquisition, including grapheme-phoneme mismatches between English and Russian, lack of speaking practice, and insufficient classroom time dedicated to phonetic training (averaging 72 classroom hours in undergraduate curriculum). Through mixed-methods research conducted at Herzen State Pedagogical University of Russia in Saint Petersburg and Synergy University in Moscow, the study evaluates the effectiveness of AI-powered tools compared to traditional methods, employing pre- and post-testing, surveys, and speech analysis to measure progress in articulation accuracy, intonation, and phonological awareness. The experimental design incorporated three methodological phases: diagnostic assessment of students' baseline pronunciation skills using speech recognition software; implementation of a 12-week intervention combining AI tools (text-to-speech platforms and interactive chatbots) with classroom instruction across 8 academic majors; evaluation of learning outcomes through blinded expert ratings and student self-assessments. Results demonstrate a 28% improvement in pronunciation accuracy among experimental groups using AI scaffolding versus 11% in control groups, with particular efficacy observed for problematic phonemes like /0/ and /5/. However, the study reveals significant barriers: 32.1% of students reported technological difficulties, 43.6% emphasized the need for human emotional connection, and 16% expressed data privacy concerns; that is, highlighting the necessity for balanced implementation frameworks. The paper provides concrete methodological recommendations for educators: structured integration of tools for speech recording within a flipped classroom model; development of AI-mediated pronunciation clinics for individualized feedback; and curriculum designs that combine chatbot dialogues with live communicative practice. Comparative analysis shows that hybrid approaches yield 19% better retention than purely digital or traditional methods. The conclusion outlines three key implementation principles: AI as supplement rather than replacement for human instruction; mandatory digital literacy training for both students and faculty and ethical protocols for educational AI use. These findings contribute to evolving paradigms in L2 phonetics instruction while proposing actionable solutions for higher education institutions seeking to optimize limited classroom hours through technological augmentation. The authors declare no conflicts of interests.

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