• DocumentCode
    2043359
  • Title

    Pitch determination of music signals using the generalized spectrum

  • Author

    Black, Tim R. ; Donohue, Kevin D.

  • Author_Institution
    Dept. of Electr. Eng., Kentucky Univ., Lexington, KY, USA
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    104
  • Lastpage
    109
  • Abstract
    This paper presents an algorithm for detecting and estimating pitch in acoustic audio signals using the generalized spectrum (CS). A performance evaluation of a GS-based and two classical (autocorrelation- and cepstrum-based) pitch determination algorithms was conducted on a set of wavetable-synthesized musical signals. The experiment separately evaluates the tasks of pitch detection and estimation. Pitch estimation performance is presented in terms of gross pitch errors (indicating algorithm stability) and mean-squared fine pitch error. The pitch detection performance is evaluated by a receiver operating characteristic analysis of the detection statistics. Results demonstrate that the GS-based estimator generally performs worse than the autocorrelation and cepstrum-based methods. However, the GS-based method performed consistently better for the detection problem, especially at low signal-to-noise values
  • Keywords
    acoustic signal processing; audio signal processing; correlation methods; mean square error methods; music; noise; numerical stability; parameter estimation; receivers; signal detection; spectral analysis; statistical analysis; SNR; acoustic audio signals; algorithm stability; autocorrelation-based pitch determination algorithm; cepstrum-based pitch determination algorithm; detection statistics; experiment; generalized spectrum; gross pitch errors; low signal-to-noise; mean-squared fine pitch error; music signals; performance evaluation; pitch detection; pitch estimation; pitch estimation performance; receiver operating characteristic analysis; wavetable-synthesized musical signals; Acoustic signal detection; Autocorrelation; Discrete Fourier transforms; Frequency; Multiple signal classification; Personal digital assistants; Scattering; Signal processing; Signal processing algorithms; Speech synthesis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Southeastcon 2000. Proceedings of the IEEE
  • Conference_Location
    Nashville, TN
  • Print_ISBN
    0-7803-6312-4
  • Type

    conf

  • DOI
    10.1109/SECON.2000.845433
  • Filename
    845433