• DocumentCode
    1783872
  • Title

    Melody Extraction for Vocal Polyphonic Music Based on Bayesian Framework

  • Author

    Liming Song ; Ming Li ; Yonghong Yan

  • Author_Institution
    Key Lab. of Speech Acoust. & Content Understanding, Inst. of Acoust., Beijing, China
  • fYear
    2014
  • fDate
    27-29 Aug. 2014
  • Firstpage
    570
  • Lastpage
    573
  • Abstract
    In order to automatically extract the main melody contours from polyphonic music especially vocal melody songs, we present an effective approach based on a Bayesian framework. According to various information from the music signals, we use a pitch evolution model describing how pitch contour changes and an acoustic model representing the acoustic characteristics when the pitch is a hypothesized one, and obtain the optimal melody contour utilizing a Viterbi algorithm. The experimental results on the RWC popular music database indicate that the overall accuracy achieves 73.4%.
  • Keywords
    Bayes methods; acoustic signal processing; audio databases; feature extraction; information retrieval; music; Bayesian framework; RWC popular music database; Viterbi algorithm; acoustic model; automatic main melody contour extraction; music signals; optimal melody contour; pitch contour; pitch evolution model; vocal melody songs; vocal polyphonic music; Harmonic analysis; Instruments; Multiple signal classification; Music; Speech; Speech processing; Bayesian framework; Viterbi algorithm; melody extraction; polyphonic music;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2014 Tenth International Conference on
  • Conference_Location
    Kitakyushu
  • Print_ISBN
    978-1-4799-5389-9
  • Type

    conf

  • DOI
    10.1109/IIH-MSP.2014.147
  • Filename
    6998393