Development Status, Frontier Hotspots, and Technical Evaluations in the Field of AI Music Composition Since the 21st Century: A Systematic Review

Abstract

In recent years, “Artificial Intelligence (AI)” has become a focal point of discussion. AI music composition, an interdisciplinary field blending computer science and musicology, has emerged as a prominent area of research. Despite rapid advancements in AI music creation technology, there remains a dearth of comprehensive surveys addressing the core technologies within this domain. To address this gap, this study conducted a comprehensive search across multiple databases spanning a 23-year period (2000–2023) on the topic of “AI music composition.” Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standard for literature screening, the study systematically organized the development status, frontier hotspots, and technical evaluations of the field. Drawing from literature data, the study verified Price’s Law, Lotka’s Law, and Bradford’s Law—three scientific productivity laws—while summarizing the current landscape from four perspectives: authors, organizations, countries, and journals. Subsequently, utilizing VOSviewer and CiteSpace, two technical software tools, the study conducted an in-depth analysis consisting of four steps: clustering, time zone, burst words, and high-frequency referenced literature. The study presented the evolution trajectory of frontiers and hotspots through visualization maps. Finally, building upon quantitative statistical insights, the study qualitatively expanded research efforts by organizing and evaluating the latest AI music generation algorithm technologies. The systematic literature analysis, both quantitative and qualitative, aims to furnish researchers and practitioners in related fields with systematic references.

Keywords

• Artificial intelligence
• automatic music composition
• bibliometrics
• PRISMA