Suppr超能文献

计算创造力与音乐生成系统:技术现状介绍

Computational Creativity and Music Generation Systems: An Introduction to the State of the Art.

作者信息

Carnovalini Filippo, Rodà Antonio

机构信息

Department of Information Engineering, CSC - Centro di Sonologia Computazionale, University of Padova, Padua, Italy.

出版信息

Front Artif Intell. 2020 Apr 3;3:14. doi: 10.3389/frai.2020.00014. eCollection 2020.

Abstract

Computational Creativity is a multidisciplinary field that tries to obtain creative behaviors from computers. One of its most prolific subfields is that of Music Generation (also called Algorithmic Composition or Musical Metacreation), that uses computational means to compose music. Due to the multidisciplinary nature of this research field, it is sometimes hard to define precise goals and to keep track of what problems can be considered solved by state-of-the-art systems and what instead needs further developments. With this survey, we try to give a complete introduction to those who wish to explore Computational Creativity and Music Generation. To do so, we first give a picture of the research on the definition and the evaluation of creativity, both human and computational, needed to understand how computational means can be used to obtain creative behaviors and its importance within Artificial Intelligence studies. We then review the state of the art of Music Generation Systems, by citing examples for all the main approaches to music generation, and by listing the open challenges that were identified by previous reviews on the subject. For each of these challenges, we cite works that have proposed solutions, describing what still needs to be done and some possible directions for further research.

摘要

计算创造力是一个多学科领域,旨在使计算机具备创造性行为。其成果最为丰硕的子领域之一是音乐生成(也称为算法作曲或音乐元创作),即运用计算手段进行音乐创作。由于该研究领域具有多学科性质,有时很难明确精确的目标,也难以追踪哪些问题可被视为已由先进系统解决,哪些问题仍需进一步发展。通过本次综述,我们试图为那些希望探索计算创造力和音乐生成的人提供全面的介绍。为此,我们首先描绘了关于创造力定义与评估的研究情况,包括人类创造力和计算创造力,以理解如何运用计算手段来获得创造性行为及其在人工智能研究中的重要性。接着,我们通过列举音乐生成所有主要方法的示例,并列出先前关于该主题的综述所确定的开放性挑战,来回顾音乐生成系统的现状。针对这些挑战中的每一个,我们引用了提出解决方案的相关著作,阐述了仍需开展的工作以及一些可能的进一步研究方向。

相似文献

1
Computational Creativity and Music Generation Systems: An Introduction to the State of the Art.
Front Artif Intell. 2020 Apr 3;3:14. doi: 10.3389/frai.2020.00014. eCollection 2020.
2
Collaborative Musical Creativity: How Ensembles Coordinate Spontaneity.
Front Psychol. 2018 Jul 24;9:1285. doi: 10.3389/fpsyg.2018.01285. eCollection 2018.
3
Dimensions of Musical Creativity.
Front Neurosci. 2020 Nov 30;14:578932. doi: 10.3389/fnins.2020.578932. eCollection 2020.
4
Musical and poetic creativity and epilepsy.
Epilepsy Behav. 2016 Apr;57(Pt B):234-7. doi: 10.1016/j.yebeh.2015.12.042. Epub 2016 Feb 16.
6
Towards a standard model of musical improvisation.
Eur J Neurosci. 2020 Feb;51(3):840-849. doi: 10.1111/ejn.14567. Epub 2019 Sep 17.
7
Creative Activities in Music--A Genome-Wide Linkage Analysis.
PLoS One. 2016 Feb 24;11(2):e0148679. doi: 10.1371/journal.pone.0148679. eCollection 2016.
8
Creative Collaboration and Collaborative Creativity: A Systematic Literature Review.
Front Psychol. 2021 Aug 9;12:713445. doi: 10.3389/fpsyg.2021.713445. eCollection 2021.
9
The Role of Canalization and Plasticity in the Evolution of Musical Creativity.
Front Neurosci. 2021 Mar 16;15:607887. doi: 10.3389/fnins.2021.607887. eCollection 2021.
10
Happy creativity: Listening to happy music facilitates divergent thinking.
PLoS One. 2017 Sep 6;12(9):e0182210. doi: 10.1371/journal.pone.0182210. eCollection 2017.

引用本文的文献

1
AI-assisted feedback and reflection in vocal music training: effects on metacognition and singing performance.
Front Psychol. 2025 Aug 18;16:1598867. doi: 10.3389/fpsyg.2025.1598867. eCollection 2025.
2
Latent evolutionary signatures: a general framework for analysing music and cultural evolution.
J R Soc Interface. 2024 Mar;21(212):20230647. doi: 10.1098/rsif.2023.0647. Epub 2024 Mar 20.
4
A transformers-based approach for fine and coarse-grained classification and generation of MIDI songs and soundtracks.
PeerJ Comput Sci. 2023 Jun 19;9:e1410. doi: 10.7717/peerj-cs.1410. eCollection 2023.
5
AffectMachine-Classical: a novel system for generating affective classical music.
Front Psychol. 2023 Jun 6;14:1158172. doi: 10.3389/fpsyg.2023.1158172. eCollection 2023.
6
Am I (Deep) Blue? Music-Making AI and Emotional Awareness.
Front Neurorobot. 2022 Jun 21;16:897110. doi: 10.3389/fnbot.2022.897110. eCollection 2022.
7
Creativity in Generative Musical Networks: Evidence From Two Case Studies.
Front Robot AI. 2021 Aug 2;8:680586. doi: 10.3389/frobt.2021.680586. eCollection 2021.

本文引用的文献

1
Learning and Consolidation as Re-representation: Revising the Meaning of Memory.
Front Psychol. 2019 Apr 30;10:802. doi: 10.3389/fpsyg.2019.00802. eCollection 2019.
2
Quantifying reputation and success in art.
Science. 2018 Nov 16;362(6416):825-829. doi: 10.1126/science.aau7224. Epub 2018 Nov 8.
3
Creativity, information, and consciousness: The information dynamics of thinking.
Phys Life Rev. 2020 Dec;34-35:1-39. doi: 10.1016/j.plrev.2018.05.001. Epub 2018 May 7.
4
Modelling Creativity: Identifying Key Components through a Corpus-Based Approach.
PLoS One. 2016 Oct 5;11(10):e0162959. doi: 10.1371/journal.pone.0162959. eCollection 2016.
5
Consciousness in the universe: a review of the 'Orch OR' theory.
Phys Life Rev. 2014 Mar;11(1):39-78. doi: 10.1016/j.plrev.2013.08.002. Epub 2013 Aug 20.
6
PSYCHOLOGICAL STUDY OF CREATIVITY.
Psychol Bull. 1963 Nov;60:548-65. doi: 10.1037/h0041573.
7
Creative abilities in the arts.
Psychol Rev. 1957 Mar;64(2):110-8. doi: 10.1037/h0048280.
8
Self-similarity of the "1/f noise" called music.
Proc Natl Acad Sci U S A. 1991 Apr 15;88(8):3507-9. doi: 10.1073/pnas.88.8.3507.
9
Creativity. Cognitive, personal, developmental, and social aspects.
Am Psychol. 2000 Jan;55(1):151-8. doi: 10.1037//0003-066x.55.1.151.
10
Long short-term memory.
Neural Comput. 1997 Nov 15;9(8):1735-80. doi: 10.1162/neco.1997.9.8.1735.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验