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Author Sun, Qing ♦ Zhang, Deyun ♦ Fan, Yifeng ♦ Zhang, Kaizhong ♦ Ma, Bin
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2010
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Classification ♦ Feature selection ♦ Guqin music ♦ Support vector machine
Abstract The Chinese zither, called guqin, has existed for over 3,000 years and always played an important role in Chinese social history. An interesting but unfortunate fact is that the traditional notation of guqin music does not provide the duration information for each music note which requires the player to learn from his teacher and memorize. As a result, among several thousands of compositions that have been created and recorded with guqin music notation, only around 100 of them are still being played today. In this article we use a machine learning method to study the guqin music recovery problem which tries to use the guqin music notation to recover the duration of each music note. Information provided by the music note is used as features to predict the duration information with a support vector machine. The experimental result shows that our system can predict with fair accuracy, and can be used as a valuable reference for human guqin masters to recover guqin music.
ISSN 15564673
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2010-10-07
Publisher Place New York
e-ISSN 15564711
Journal Journal on Computing and Cultural Heritage (JOCCH)
Volume Number 3
Issue Number 2
Page Count 12
Starting Page 1
Ending Page 12

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Source: ACM Digital Library