• DocumentCode
    2810760
  • Title

    Maximum likelihood pitch estimation using sinusoidal modeling

  • Author

    Mahadevan, Vijay ; Espy-Wilson, Carol Y.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Maryland, College Park, MD, USA
  • fYear
    2011
  • fDate
    10-12 Feb. 2011
  • Firstpage
    310
  • Lastpage
    314
  • Abstract
    An algorithm for optimal estimation of pitch frequency using a maximum likelihood formulation is presented. The speech waveform is modeled using sinusoidal basis functions that are harmonically tied together to explicitly capture the periodic structure of voiced speech. The problem of pitch estimation is casted as a model selection problem and the Akaike Information Criterion is used to estimate the pitch.
  • Keywords
    maximum likelihood estimation; speech processing; Akaike Information Criterion; maximum likelihood pitch estimation; optimal estimation; pitch estimation; sinusoidal basis function; sinusoidal modeling; speech waveform; Personal digital assistants; Akaike information criteria; fundamental frequency; maximum likelihood; pitch; sinusoidal modeling; voicing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications and Signal Processing (ICCSP), 2011 International Conference on
  • Conference_Location
    Calicut
  • Print_ISBN
    978-1-4244-9798-0
  • Type

    conf

  • DOI
    10.1109/ICCSP.2011.5739326
  • Filename
    5739326