TY - GEN
T1 - The music analysis method based on melody analysis
AU - Endo, Tsukasa
AU - Ito, Shin Ichi
AU - Mitsukura, Yasue
AU - Fukumi, Minoru
PY - 2008/12/1
Y1 - 2008/12/1
N2 - Recently, we can have large amounts of music thanks to the development of the computer technology. However, as the data of the music becomes larger, it is a hassle to classify the music based on the music content manually. We think that it is necessary to categorize the music automatically based on our mood. In this paper, we propose a novel method to analyze the music automatically based on melody analysis. The proposed method considers music genres as the measure of music analysis. We extract the acoustic features to characterize the music. Then, we classify music using multi-class classifiers based on the support vector machine (SVM). We adopt two approaches to the multi-class classification method. Furthermore, we propose a visualization method to specify the musical structure on the music genres from the classification result. Finally, computer simulations are done by using real music data in order to prove the effectiveness of the proposed method.
AB - Recently, we can have large amounts of music thanks to the development of the computer technology. However, as the data of the music becomes larger, it is a hassle to classify the music based on the music content manually. We think that it is necessary to categorize the music automatically based on our mood. In this paper, we propose a novel method to analyze the music automatically based on melody analysis. The proposed method considers music genres as the measure of music analysis. We extract the acoustic features to characterize the music. Then, we classify music using multi-class classifiers based on the support vector machine (SVM). We adopt two approaches to the multi-class classification method. Furthermore, we propose a visualization method to specify the musical structure on the music genres from the classification result. Finally, computer simulations are done by using real music data in order to prove the effectiveness of the proposed method.
KW - Melody analysis
KW - Music analysis
KW - Support vector machine
KW - Time-varying complex speech analysis
UR - http://www.scopus.com/inward/record.url?scp=58149099648&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=58149099648&partnerID=8YFLogxK
U2 - 10.1109/ICCAS.2008.4694287
DO - 10.1109/ICCAS.2008.4694287
M3 - Conference contribution
AN - SCOPUS:58149099648
SN - 9788995003893
T3 - 2008 International Conference on Control, Automation and Systems, ICCAS 2008
SP - 2559
EP - 2562
BT - 2008 International Conference on Control, Automation and Systems, ICCAS 2008
T2 - 2008 International Conference on Control, Automation and Systems, ICCAS 2008
Y2 - 14 October 2008 through 17 October 2008
ER -