The Ai Music Generation Challenge 2020: Double Jigs in the Style of O'Neill's ``1001''

Q2 Arts and Humanities Journal of Creative Music Systems Pub Date : 2021-10-22 DOI:10.5920/jcms.950
Bob L. Sturm, H. Maruri-Aguilar
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引用次数: 6

Abstract

The Ai Music Generation Challenge 2020 had three objectives: 1) to promote meaningful approaches to evaluating artificial intelligence (Ai) applied to music;2) to see how music Ai research can benefit from considering traditional music, and how traditional music might benefit from music Ai research; and 3)to facilitate discussions about the ethics of music Ai research applied to traditional music practices.There were six participants and a benchmark in the challenge, each competing to build an artificial system that generates the most plausible double jigs, as judged against the 365 published in solved'', but that the evaluation of such systems can be done in meaningful ways.The article ends by reflecting on the challenge and considering the coming 2021 challenge.
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2020 Ai音乐世代挑战:奥尼尔“1001”风格的双跳
2020年人工智能音乐生成挑战赛有三个目标:1)促进有意义的方法来评估应用于音乐的人工智能(Ai);2)看看音乐人工智能研究如何从考虑传统音乐中受益,以及传统音乐如何从音乐人工智能研究中受益;3)促进对应用于传统音乐实践的音乐伦理研究的讨论。这项挑战有六名参与者和一个基准,每个人都在竞争建立一个人工系统,产生最合理的双夹具,与发表在《解决》杂志上的365个结论相比较,但对这些系统的评估可以以有意义的方式完成。文章最后反思了这一挑战,并考虑了即将到来的2021年挑战。
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来源期刊
Journal of Creative Music Systems
Journal of Creative Music Systems Arts and Humanities-Music
CiteScore
1.20
自引率
0.00%
发文量
8
审稿时长
12 weeks
期刊最新文献
Title Pending 1311 Oktoechos Classification and Generation of Liturgical Music using Deep Learning Frameworks Editorial: JCMS Special Issue of the first Conference on AI Music Creativity Contemporary music genre rhythm generation with machine learning Deep Music Information Dynamics Novel Framework for Reduced Neural-Network Music Representation with Applications to Midi and Audio Analysis and Improvisation
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