AI-Driven Innovation in Remote Music Education Models

Abstract

This study explores the innovation and application of a remote music education model driven by artificial intelligence (AI) and analyses the main application scenarios of AI technology in remote music education and the innovation of teaching models it brings. First, the study outlines the rapid development of AI in the field of education, especially its role in promoting music education in terms of real-time feedback, personalised learning and enhanced interactivity. Then, the main characteristics and challenges of the current remote music education model are analysed, including technical issues such as sound quality and delay, as well as the requirements for teachers' information technology skills. Through the analysis of application cases of AI music education platforms at home and abroad, it shows how AI can provide students with a high-quality and personalised learning experience through technologies such as audio analysis, intelligent recommendation and virtual accompaniment. This study shows that the AI-driven remote music education model not only improves the problems of lack of interactivity and lack of personalisation in traditional teaching but also promotes the optimal allocation of educational resources, providing a feasible solution for remote music education.