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Frontiers of Information Technology & Electronic Engineering

ISSN 2095-9184 (print), ISSN 2095-9230 (online)

2024 Vol.25 No.7 P.1025-1030

Suno: potential, prospects, and trends

Jiaxing YU, Songruoyao WU, Guanting LU, Zijin LI, Li ZHOU, Kejun ZHANG

College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China; Department of Music Artificial Intelligence and Music Information Technology, Central Conservatory of Music, Beijing 100031, China; School of Arts and Communication, China University of Geosciences (Wuhan), Wuhan 430074, China; Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing 314100, China

yujx@zju.edu.cn, wsry@zju.edu.cn, 3210105631@zju.edu.cn, lzijin@ccom.edu.cn, zhouli@cug.edu.cn, zhangkejun@zju.edu.cn

Abstract: Suno has attracted wide attention due to its impressive capabilities. It demonstrates technological advancements and opens up new possibilities for music composition, representing a milestone in the development of artificial intelligence (AI) music generation. In this paper, we first introduce the background and summarize the general technical framework of AI music generation, followed by an analysis of Suno’s advantages and disadvantages. Finally, we discuss the future trends in Music and AI.

Key words:

Chinese Summary  <8> Suno：潜力、前景与趋势

俞佳兴1，吴宋若瑶1，卢冠廷1，李子晋2，周莉3，张克俊1,4
1浙江大学计算机科学与技术学院，中国杭州市，310027
2中央音乐学院音乐人工智能与音乐信息科技系，中国北京市，100031
3中国地质大学（武汉）艺术与传媒学院，中国武汉市，430074
4浙江大学长三角智慧绿洲创新中心，中国嘉兴市，314100
摘要：Suno因其出色的音乐生成能力受到广泛关注，其不仅展现了音乐人工智能技术的进步，也为音乐创作开辟了新的可能，是音乐人工智能生成发展的一个里程碑。本文介绍音乐人工智能生成的技术背景，总结音乐人工智能生成的通用技术框架，分析Suno的优势和局限，并讨论音乐人工智能的未来趋势。

关键词组：音乐人工智能；音乐生成；音乐人工智能生成平台；Suno


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DOI:

10.1631/FITEE.2400299

CLC number:

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On-line Access:

2024-08-27

Received:

2023-10-17

Revision Accepted:

2024-05-08

Crosschecked:

2024-05-24

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