The Challenges and Issues in Artificial Intelligence (AI) in Vocal Performance Education: A Comprehensive Narrative Review

This narrative review examines the challenges that emerge when artificial intelligence enters vocal performance education, a domain where human expressiveness, cultural tradition, and interpersonal connection have always been central. While AI offers compelling possibilities like instant feedback and personalized learning paths, vocal training's inherently expressive and culturally embedded nature raises important questions about whether these technologies truly serve students and teachers effectively. Rather than simply cataloguing AI tools, this review takes a critical stance by comparing how different systems actually work, evaluating their pedagogical value across diverse musical contexts, and acknowledging that most current AI models reflect Western classical biases. We draw on examples from Indian classical music, Chinese opera, and Arabic maqam traditions to show how inclusivity matters, not just as an ethical add-on, but as essential to technical effectiveness. The review also proposes a framework for responsible AI integration that addresses curriculum design, data governance, and fair assessment practices.

Artificial Intelligence, Vocal Performance, Music Education, Pedagogy, Ethics, Cultural Inclusivity, Machine Learning

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