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
Link To Document :
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