Computer Science ›› 2026, Vol. 53 ›› Issue (8): 229-244.doi: 10.11896/jsjkx.260700167

• Artificial Intelligence • Previous Articles     Next Articles

Review of Music Artificial Intelligence Driven by Large Language Models

LIU Jing   

  1. Chengdu University, Chengdu 610106, China
  • Received:2026-03-05 Revised:2026-05-24 Online:2026-08-15 Published:2026-08-17
  • About author:LIU Jing,born in 1990,Ph.D,lecturer,master’s supervisor.Her main research interests include music performance,music creation and music AI.

Abstract: Large language models and other emerging AI technologies are reshaping music AI from generation-oriented demonstrations toward systematic research on music understanding,interactive creation,and scenario-based applications.This review surveys music AI in the era of large models,covering multimodal understanding,human-AI collaborative creation,personalized and functional applications,industrial ecosystems,and copyright and ethical issues.Firstly,it examines how LLMs are integrated with symbolic music,audio representations,and cross-modal alignment,highlighting the persistent gap between symbolic reasoning and audio perception.Then,it summarizes interactive creation systems in terms of intention expression,control allocation,and human preference alignment,and discusses differences between professional and general users.Applications in conversational re-commendation,music therapy,educational support,and film scoring are reviewed,with emphasis on the limitations caused by inconsistent evaluation criteria and insufficient cross-scenario validation.Finally,AI music copyright ownership,training data tra-ceability,the boundaries of human creativity,and the risks to cultural diversity are discussed.Furthermore,future directions are identified,including audio-native music foundation models,music agents,long-range structural modeling,closed-loop evaluation,copyright governance,and cross-cultural music AI,providing reference for understanding the technological progress,application boundaries,and governance issues of music artificial intelligence.

Key words: Music artificial intelligence, Large language models, Cross-modal alignment, Copyright and ethics, Cultural diversity, Functional music

CLC Number: 

  • TP391
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