Complex network structure of musical compositions: Algorithmic generation of appealing music

Xiao Fan Liu, Chi Kong Tse, Michael Small

Research output: Journal article publicationJournal articleAcademic researchpeer-review

44 Citations (Scopus)

Abstract

In this paper we construct networks for music and attempt to compose music artificially. Networks are constructed with nodes and edges corresponding to musical notes and their co-occurring connections. We analyze classical music from Bach, Mozart, Chopin, as well as other types of music such as Chinese pop music. We observe remarkably similar properties in all networks constructed from the selected compositions. We conjecture that preserving the universal network properties is a necessary step in artificial composition of music. Power-law exponents of node degree, node strength and/or edge weight distributions, mean degrees, clustering coefficients, mean geodesic distances, etc. are reported. With the network constructed, music can be composed artificially using a controlled random walk algorithm, which begins with a randomly chosen note and selects the subsequent notes according to a simple set of rules that compares the weights of the edges, weights of the nodes, and/or the degrees of nodes. By generating a large number of compositions, we find that this algorithm generates music which has the necessary qualities to be subjectively judged as appealing.
Original languageEnglish
Pages (from-to)126-132
Number of pages7
JournalPhysica A: Statistical Mechanics and its Applications
Volume389
Issue number1
DOIs
Publication statusPublished - 1 Jan 2010

Keywords

  • Complex networks
  • Music
  • Music composition
  • Random walk
  • Scale-free distribution

ASJC Scopus subject areas

  • Statistics and Probability
  • Condensed Matter Physics

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