基于人工智能的情感音乐生成系统:方法与挑战综述

IF 23.8 1区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS ACM Computing Surveys Pub Date : 2024-06-17 DOI:10.1145/3672554
Adyasha Dash, Kathleen Agres
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引用次数: 0

摘要

音乐是改变听众情绪状态的强大媒介。近年来,随着计算能力的大幅提升,基于人工智能(AI)的方法已成为创建情感音乐生成(AMG)系统的流行方法。娱乐、医疗保健和传感器集成互动系统设计是基于人工智能的情感音乐生成(AI-AMG)系统可能产生重大影响的几个领域。鉴于人们对这一主题的兴趣激增,本文旨在对可控人工智能情感音乐生成系统进行全面评述。文章讨论了人工智能-AMG 系统的主要构件,并根据音乐生成所使用的核心算法对现有系统进行了正式分类。此外,本文还讨论了用于创作情感音乐的主要音乐特征,以及用于调整这些特征的基于人工智能的方法。最后,本文提出了这一领域的主要挑战和悬而未决的问题,以及潜在的解决方案,以指导未来的研究。我们希望这篇综述能帮助读者了解人工智能-AMG 系统的最新进展,并对开发这些系统所使用的方法有一个全面的认识,从而帮助他们在未来探索这一领域。
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AI-Based Affective Music Generation Systems: A Review of Methods and Challenges

Music is a powerful medium for altering the emotional state of the listener. In recent years, with significant advancements in computing capabilities, artificial intelligence-based (AI-based) approaches have become popular for creating affective music generation (AMG) systems. Entertainment, healthcare, and sensor-integrated interactive system design are a few of the areas in which AI-based affective music generation (AI-AMG) systems may have a significant impact. Given the surge of interest in this topic, this article aims to provide a comprehensive review of controllable AI-AMG systems. The main building blocks of an AI-AMG system are discussed, and existing systems are formally categorized based on the core algorithm used for music generation. In addition, this article discusses the main musical features employed to compose affective music, along with the respective AI-based approaches used for tailoring them. Lastly, the main challenges and open questions in this field, as well as their potential solutions, are presented to guide future research. We hope that this review will be useful for readers seeking to understand the state-of-the-art in AI-AMG systems, and gain an overview of the methods used for developing them, thereby helping them explore this field in the future.

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来源期刊
ACM Computing Surveys
ACM Computing Surveys 工程技术-计算机:理论方法
CiteScore
33.20
自引率
0.60%
发文量
372
审稿时长
12 months
期刊介绍: ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.
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