PRESERVING AND PEDAGOGIZING NATIONAL MUSIC HERITAGE: AN AI-DRIVEN APPROACH TO KARAKALPAK, UZBEK, AND TURKIC FOLK MUSIC IN MODERN EDUCATION

Abstract

This thesis explores the application of Artificial Intelligence (AI) for the preservation and pedagogical integration of Karakalpak, Uzbek, and broader Turkic folk music. These rich oral traditions face significant threats from globalization and declining intergenerational transmission. Drawing on a theoretical framework of ethnomusicology, digital humanities, and AI, this research provides a comparative analysis of these musical heritages, highlighting their shared characteristics and unique features. We propose a model for leveraging AI in three key areas: 1) Digitization and Archiving, using AI for audio restoration, automated metadata extraction, and Optical Music Recognition; 2) Analysis and Understanding, employing AI for pattern recognition and comparative musicological studies; and 3) Educational Integration, through AI-powered interactive learning platforms, generative tools for pedagogical purposes, and immersive VR/AR experiences. Case studies for a Digital Archive for Turkic Music, an AI-Powered Learning Module for the Karakalpak Kobyz, and an Uzbek Makom Analysis Tool are presented to illustrate practical implementation. The thesis also addresses the critical challenges and ethical considerations of this interdisciplinary approach, including data bias, authenticity, intellectual property, the digital divide, and cultural sensitivity. We conclude that a culturally informed and ethically responsible integration of AI can ensure the sustainable preservation and dynamic educational revitalization of these invaluable musical traditions for future generations.