• DocumentCode
    1929676
  • Title

    Content-based music classification

  • Author

    Lo, Yu-lung ; Lin, Vi-Chang

  • Author_Institution
    Dept. of Inf. Manage., Chaoyang Univ. of Technol., Taichung, Taiwan
  • Volume
    2
  • fYear
    2010
  • fDate
    9-11 July 2010
  • Firstpage
    112
  • Lastpage
    116
  • Abstract
    The music classification techniques can be discriminated into two categories - based by music content-based classification and training by learning machine classification. Both have their advantages and disadvantages. For music content-based classifications, most of the approaches are based on single music feature, such as melody or chord, and the accuracy is up to 70% in few genres of music. However, the accuracy for classification of most music genres is lower. In this paper, we study the features of music content and use the multiple features of music data to improve the accuracy of music classification. Our performance studies shown that the higher accuracy can be achieved for classification of classical music by using multiple features of music content for classification.
  • Keywords
    content-based retrieval; learning (artificial intelligence); music; pattern classification; content-based music classification; learning machine classification; Indexes; content-based retrieval; digital music; multimedia database; music classification; music database;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-5537-9
  • Type

    conf

  • DOI
    10.1109/ICCSIT.2010.5563642
  • Filename
    5563642