Artificial Intelligence in Vocal Pedagogy: A Critical Review of Tools, Pedagogical Functions, and Research Trends

Özet

Artificial intelligence (AI) is now used in vocal pedagogy for performance analysis, automated assessment, feedback, and individualized practice. The literature, however, does not support treating computational output as self-evidently pedagogical. This critical review examines 15 verified English-language academic studies published between 2022 and 2026, comparing the technologies employed, the vocal skills targeted, the forms of feedback provided, and the pedagogical roles assigned to AI. The studies show a field broadening from classification and automated scoring toward deep learning, large-language-model dialogue, explainable AI, adaptive recommendation, and multimodal systems. Pitch, rhythm, timbre, and pronunciation receive the greatest attention because they are comparatively tractable computationally; reflective learning and self-regulation are less developed. Cultural-stylistic validity is treated here not merely as an nclusivity concern but as a measurement-validity problem whenever the system’s reference norm does not match the musical tradition being evaluated. Drawing on these patterns, the review proposes the Vocal-AI Pedagogical Function Framework (VAPFF), which treats human interpretation and pedagogical action as necessary links between technical analysis and learning. AI in vocal pedagogy should therefore be judged not only by how accurately it measures performance, but by whether its output can be interpreted, situated within a pedagogical context, and used without weakening learner or teacher agency.

Bu makaleye atıf

Karlıdağ, B. A. (2026). Artificial Intelligence in Vocal Pedagogy: A Critical Review of Tools, Pedagogical Functions, and Research Trends. Müzikist Akademik Dergisi, 1(2), 6–19. https://muzikist.org/akademik-dergi/2-2026-6-19

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