• DocumentCode
    2052945
  • Title

    Pitch Oriented Automatic Singer Identification in Pop Music

  • Author

    Chang, Peichen

  • Author_Institution
    Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA
  • fYear
    2009
  • fDate
    14-16 Sept. 2009
  • Firstpage
    161
  • Lastpage
    166
  • Abstract
    In this paper, we proposed two novel methods used to distinguish the singer of a pop music. We focused on a single singer and single track case. These two methods are ldquoPitch Extractionrdquo method and ldquo1/12 OFCCrdquo method. The Pitch Extraction method is composed of three stages and they are Singing pitch estimation stage, Exact pitch calculation stage and GMM classification stage. ldquo1/12 OFCCrdquo method is composed of ldquoPitch Feature Calculationrdquo and GMM classification. We also compare these two methods with OFCC based method. With ldquoPitch Extractionrdquo and ldquo1/12 OFCCrdquo method, we have some improvement on works of singer identification using single feature.
  • Keywords
    music; speaker recognition; automatic singer identification; pitch calculation; pitch extraction; pitch feature calculation; pop music; singing pitch estimation; Cepstrum; Data mining; Hidden Markov models; Human voice; Information filtering; Information filters; Instruments; Interference; Mel frequency cepstral coefficient; USA Councils; GMM; pitch; singer identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Semantic Computing, 2009. ICSC '09. IEEE International Conference on
  • Conference_Location
    Berkeley, CA
  • Print_ISBN
    978-1-4244-4962-0
  • Electronic_ISBN
    978-0-7695-3800-6
  • Type

    conf

  • DOI
    10.1109/ICSC.2009.28
  • Filename
    5298607