TY - GEN
T1 - Contrapuntal Composition and Autonomous Style Development of Organum Motets By using AntsOMG
AU - Chang, Chun Yien
AU - Chen, Ying Ping
N1 - Publisher Copyright:
© 2021 IEEE
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85124624692&partnerID=8YFLogxK
U2 - 10.1109/CEC45853.2021.9504881
DO - 10.1109/CEC45853.2021.9504881
M3 - Conference contribution
AN - SCOPUS:85124624692
T3 - 2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings
SP - 2023
EP - 2030
BT - 2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE Congress on Evolutionary Computation, CEC 2021
Y2 - 28 June 2021 through 1 July 2021
ER -