Contrapuntal Composition and Autonomous Style Development of Organum Motets By using AntsOMG

Chun Yien Chang*, Ying Ping Chen

*此作品的通信作者

研究成果: Conference contribution同行評審

3 引文 斯高帕斯(Scopus)

摘要

Based on a previously proposed meta-framework, called ants on multiple graphs (AntsOMG), this paper further investigates into certain more complicated creative behavior, in which creators interact with their own creations in order to complete works and elevate the creation forms to a higher level, via computational mechanisms. Aiming to achieve the goal of this study, the target music genre, organum motets, is adopted because its composition process requires iterative interactions with composed music and quite resembles the creative behavior under investigation. AntsOMG is employed as a fundamental component for developing models and conducting creations according to the developed models. With the assistance of AntsOMG, the proposed approach firstly develops style models for section scheme planning and accordingly plans section schemes for the organum motets to be composed. Secondly, following the section scheme, cantus firmus is composed and also used to generate the graph models to be developed into the style models required for composing the corresponding contrapuntal parts for the polyphonic sections of the organum motets. For finalizing each contrapuntal section, a genetic algorithm is utilized to introduce variety and diversity. The outcomes demonstrate that contrapuntal composition and autonomous style development of organum motets can be achieved by the proposed approach. The contribution of this paper is twofold. First, the presented implementation is immediately applicable to compose unlimited amount of organum motets, which may not be possible for human composers. Second, the success of the proposal may shed light on gaining further understandings of complicated creative behavior.

原文English
主出版物標題2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
頁面2023-2030
頁數8
ISBN(電子)9781728183923
DOIs
出版狀態Published - 2021
事件2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Virtual, Krakow, Poland
持續時間: 28 6月 20211 7月 2021

出版系列

名字2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings

Conference

Conference2021 IEEE Congress on Evolutionary Computation, CEC 2021
國家/地區Poland
城市Virtual, Krakow
期間28/06/211/07/21

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