Ancient Chinese Zither (Guqin) Music Recovery with Support Vector Machine

被引:2
作者
Sun, Qing [1 ]
Zhang, Deyun [2 ]
Fan, Yifeng [3 ]
Zhang, Kaizhong [4 ]
Ma, Bin [5 ]
机构
[1] Xian Univ Finance & Econ, Comp Sci Dept, 456 Mail Box,108 Chang An Zhong Rd, Xian 710061, Shaanxi, Peoples R China
[2] Xi An Jiao Tong Univ, Sch Elect & Informat Engn, Xian, Shaanxi, Peoples R China
[3] Xian Conservatory Mus, Chinese Natl Mus Dept, Xian, Shaanxi, Peoples R China
[4] Western Univ Ontario, Comp Sci Dept, London, ON, Canada
[5] Univ Waterloo, Sch Comp Sci, Waterloo, ON, Canada
来源
ACM JOURNAL ON COMPUTING AND CULTURAL HERITAGE | 2010年 / 3卷 / 02期
基金
加拿大自然科学与工程研究理事会;
关键词
Design; Human Factors; Verification; Classification; feature selection; guqin music; support vector machine;
D O I
10.1145/1841317.1841320
中图分类号
C [社会科学总论];
学科分类号
03 ; 0303 ;
摘要
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.
引用
收藏
页数:12
相关论文
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