• DocumentCode
    2372806
  • Title

    A classification approach to interpretation of traditional Chinese musical score

  • Author

    Li, Rongfeng ; Ding, Yelei ; Li, Wenxin ; Bi, Minghui

  • Author_Institution
    Key Lab. of Machine Perception (MOE), Peking Univ., Beijing, China
  • fYear
    2012
  • fDate
    23-25 March 2012
  • Firstpage
    655
  • Lastpage
    659
  • Abstract
    Gongchepu, one of the widely-used traditional Chinese musical scores, is hard to read due to the immeasurable rhythmic rule, which only presents a general rhythmic structure while the duration of each note is determined by performer according to the context of the melody. Experience of determining the duration of each note is passed down via oral tradition, and there are few experts who can read such musical score now. However, by capitalizing on classification methods, such as Naïve Bayes and Maximum Entropy Model, rhythms of gongchepu can be labeled and interpreted into staff automatically, making it much easier to read. A precision of 85.63% is achieved in experiments. As an attempt to solve the rhythmic immeasurability problem in the study of musical score with the application of statistical model, this work is conducive to the preservation of Chinese traditional cultural heritage.
  • Keywords
    Bayes methods; history; maximum entropy methods; music; natural language processing; pattern classification; Chinese musical score interpretation; Chinese traditional cultural heritage; classification approach; classification methods; general rhythmic structure; gongchepu; immeasurable rhythmic rule; maximum entropy model; naïve Bayes; rhythmic immeasurability problem; statistical model; widely-used traditional Chinese musical scores; Computational modeling; Context; Data models; Educational institutions; Entropy; Rhythm; Training data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Technology (ICIST), 2012 International Conference on
  • Conference_Location
    Hubei
  • Print_ISBN
    978-1-4577-0343-0
  • Type

    conf

  • DOI
    10.1109/ICIST.2012.6221727
  • Filename
    6221727