• 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