DocumentCode
1612474
Title
The music analysis method based on melody analysis
Author
Endo, Tsukasa ; Ito, Shin-ichi ; Mitsukura, Yasue ; Fukumi, Minoru
Author_Institution
Bio Applic. Syst. Eng., Tokyo Univ. of Agric. & Technol., Koganei
fYear
2008
Firstpage
2559
Lastpage
2562
Abstract
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.
Keywords
audio signal processing; data visualisation; feature extraction; music; signal classification; support vector machines; acoustic feature extraction; computer technology; melody analysis; multiclass music classification; music analysis method; phonetic analysis; support vector machine; time-varying speech model; visualization method; Automatic control; Control systems; Data mining; Data visualization; Feature extraction; Music; Signal analysis; Speech analysis; Support vector machine classification; Support vector machines; Melody analysis; Music analysis; Support vector machine; Time-varying complex speech analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Control, Automation and Systems, 2008. ICCAS 2008. International Conference on
Conference_Location
Seoul
Print_ISBN
978-89-950038-9-3
Electronic_ISBN
978-89-93215-01-4
Type
conf
DOI
10.1109/ICCAS.2008.4694287
Filename
4694287
Link To Document