• DocumentCode
    2874649
  • Title

    Music Information Retrieval System Using Lyrics and Melody Information

  • Author

    Wang, Tao ; Kim, Dong-Ju ; Hong, Kwang-Seok ; Youn, Jeh-Seon

  • Author_Institution
    Sch. of Inf. & Commun. Eng., Sungkyunkwan Univ., Suwon, South Korea
  • Volume
    2
  • fYear
    2009
  • fDate
    18-19 July 2009
  • Firstpage
    601
  • Lastpage
    604
  • Abstract
    Multimedia content can be described in versatile ways as its essence is not limited to one side. For music data these multiple fields could be a songpsilas audio features as well as its lyrics. But most recent research revolves around melody information for retrieval. Therefore, we proposed an MIR system that utilizes the userpsilas acoustic signal from a singing voice and retrieves the music information using both lyrics and melody information. The lyrics recognition module uses a keyword spotting system based on text-content of the lyrics by an HMM comparison engine. The melody recognition module extracts pitch and MFCC features from the user singing input and then retrieves music by a GMM comparison engine. Consequently, the proposed MIR system consists of fusing the lyrics and melody recognition module in which the melody recognition especially operates to restrict recognition candidates. Experiments show that the proposed MIR system has recognition rate of 72.72% to 83.64% when the numbers of restricted recognition candidates are from 10 to 50.
  • Keywords
    Gaussian processes; hidden Markov models; information retrieval; music; Gaussian mixture model; hidden Markov model; keyword spotting system; lyrics recognition module; melody recognition module; multimedia content; music information retrieval system; Content based retrieval; Databases; Engines; Hidden Markov models; Indexes; Information processing; Multimedia systems; Multiple signal classification; Music information retrieval; Rhythm; MIR; keyword recognition; melody retrieval;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Processing, 2009. APCIP 2009. Asia-Pacific Conference on
  • Conference_Location
    Shenzhen
  • Print_ISBN
    978-0-7695-3699-6
  • Type

    conf

  • DOI
    10.1109/APCIP.2009.283
  • Filename
    5197270