With the rapid development of Artificial Intelligence Generated Content (AIGC) technology, the creative methods, dissemination forms, and industrial ecology of the music industry have undergone profound changes. AIGC technology relies on deep learning and big data analysis to efficiently generate music works, meet personalized needs, and promote the deep integration of the music industry with fields such as film, television, and gaming. However, the traditional talent cultivation model in musicology is difficult to adapt to the new requirements of this technological change on the industry, exposing problems such as outdated curriculum design, weak practical links, insufficient teacher level, and insufficient collaboration with the industry. This article takes AIGC technology as the starting point, comprehensively analyzes its driving role in the music industry and changes in talent demand, and combines the pain points in current music education to propose an innovative training model and practical path based on AIGC, including optimizing the curriculum system, strengthening technical practice, building a collaborative mechanism between industry, academia, and research, and enhancing internationalization level. Through the deep integration of theory and practice, this article aims to explore music talent cultivation methods that meet the needs of the new era, provide feasible references for the digital transformation and high-quality development of the music industry, and also provide theoretical support and practical guidance for the reform of music education in universities, promoting the deep integration of technology and art.
Wu et al. (Tue,) studied this question.