Title: Algorithm composition of Chinese folk music based on swarm intelligence

Authors: Xiaomei Zheng; Lei Wang; Dongyang Li; Lin Shen; Yanyuan Gao; Weian Guo; Yushan Wang

Addresses: College of Electronics and Information Engineering, Tongji University, Shanghai 201804, China; College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China ' College of Electronics and Information Engineering, Tongji University, Shanghai 201804, China ' College of Electronics and Information Engineering, Tongji University, Shanghai 201804, China ' Music College, Shanghai Normal University, Shanghai 200234, China ' Music College, Shanghai Normal University, Shanghai 200234, China ' Sino-German College of Applied Sciences, Tongji University, Shanghai 201804, China ' College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China

Abstract: Particle swarm optimisation (PSO), which is a kind of typical swarm intelligent algorithm, simulates the process of birds searching for food to solve optimisation problems. In this paper, a Chinese folk composition model based on PSO algorithm is put forward. The concept of multi-melody space is constructed for the traditional pentatonic music creation. The multi-melody space PSO algorithm called MSPA searches the solution in melody space. Experimental results show that the model is feasible and effective in the process of Chinese folk music composition.

Keywords: algorithmic composition; Chinese folk music; pentatonic mode; particle swarm optimisation; PSO; multi-melody space.

DOI: 10.1504/IJCSM.2017.088015

International Journal of Computing Science and Mathematics, 2017 Vol.8 No.5, pp.437 - 446

Received: 16 Aug 2016
Accepted: 10 May 2017
Published online: 14 Nov 2017 *

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