• DocumentCode
    1692777
  • Title

    A comparative study of pitch extraction algorithms on a large variety of singing sounds

  • Author

    Babacan, Onur ; Drugman, Thomas ; D´Alessandro, Nicolas ; Henrich, Nathalie ; Dutoit, Thierry

  • Author_Institution
    Circuit Theor. & Signal Process. Lab., Univ. of Mons, Mons, Belgium
  • fYear
    2013
  • Firstpage
    7815
  • Lastpage
    7819
  • Abstract
    The problem of pitch tracking has been extensively studied in the speech research community. The goal of this paper is to investigate how these techniques should be adapted to singing voice analysis, and to provide a comparative evaluation of the most representative state-of-the-art approaches. This study is carried out on a large database of annotated singing sounds with aligned EGG recordings, comprising a variety of singer categories and singing exercises. The algorithmic performance is assessed according to the ability to detect voicing boundaries and to accurately estimate pitch contour. First, we evaluate the usefulness of adapting existing methods to singing voice analysis. Then we compare the accuracy of several pitch-extraction algorithms, depending on singer category and laryngeal mechanism. Finally, we analyze their robustness to reverberation.
  • Keywords
    feature extraction; reverberation; speech synthesis; EGG recordings; annotated singing sounds; laryngeal mechanism; pitch contour; pitch extraction algorithms; pitch tracking; reverberation; singer category; singing voice analysis; voicing boundaries; Databases; Estimation; Hidden Markov models; Reverberation; Robustness; Speech; Speech processing; pitch extraction; singing analysis/synthesis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
  • Conference_Location
    Vancouver, BC
  • ISSN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2013.6639185
  • Filename
    6639185