• DocumentCode
    1968231
  • Title

    Music and symbolic dynamics: The science behind an art

  • Author

    Srinivasa, Shayan Garani ; Seshadri, H.

  • Author_Institution
    Dept. of Electron. Syst. Eng., Indian Inst. of Sci., Bangalore, India
  • fYear
    2013
  • fDate
    10-15 Feb. 2013
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    Music signals comprise of atomic notes drawn from a musical scale. The creation of musical sequences often involves splicing the notes in a constrained way resulting in aesthetically appealing patterns. We develop an approach for music signal representation based on symbolic dynamics by translating the lexicographic rules over a musical scale to constraints on a Markov chain. This source representation is useful for machine based music synthesis, in a way, similar to a musician producing original music. In order to mathematically quantify user listening experience, we study the correlation between the max-entropic rate of a musical scale and the subjective aesthetic component. We present our analysis with examples from the south Indian classical music system.
  • Keywords
    Markov processes; art; entropy; music; signal representation; Markov chain; aesthetically appealing patterns; art; atomic notes; lexicographic rules; machine based music synthesis; max-entropic rate; music dynamics; music signal representation; musical scale; musical sequences; notes splicing; source representation; south Indian classical music system; subjective aesthetic component; symbolic dynamics; user listening; Automata; Entropy; Markov processes; Multiple signal classification; Rhythm; Signal processing; Markov chains; music signal processing; symbolic dynamics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory and Applications Workshop (ITA), 2013
  • Conference_Location
    San Diego, CA
  • Print_ISBN
    978-1-4673-4648-1
  • Type

    conf

  • DOI
    10.1109/ITA.2013.6502948
  • Filename
    6502948