• DocumentCode
    1707723
  • Title

    AM-FM decomposition of speech signal using MWL criterion

  • Author

    Far, Reza Rashidi ; Gazor, Saeed

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Queen´´s Univ., Kingston, Ont., Canada
  • Volume
    3
  • fYear
    2004
  • Firstpage
    1769
  • Abstract
    Adaptive maximum windowed likelihood algorithm is introduced and adapted to decompose the speech signal as an amplitude modulated-frequency modulated (AM-FM) signal. Choosing the window length and type, the algorithm can be adjusted to decompose different pieces of speech signal. By tuning the step size for each frequency, the algorithm can be tuned for each formant frequency. Simulations for two phonemes and an all voiced piece of speech show that the algorithm is able to track the formant frequencies successfully unless it is used in highly changing formants where some treatments have been suggested.
  • Keywords
    adaptive filters; adaptive signal processing; amplitude modulation; frequency modulation; maximum likelihood estimation; speech processing; tuning; AM-FM speech signal decomposition; MWL criterion; adaptive filters; adaptive maximum windowed likelihood algorithm; algorithm tuning; all voiced speech piece; amplitude modulated-frequency modulated signal; formant frequency tracking; highly changing formants; phonemes; simulations; step size tuning; window length; window type; AWGN; Amplitude estimation; Amplitude modulation; Delay estimation; Frequency estimation; Signal processing; Signal processing algorithms; Signal synthesis; Speech processing; Speech synthesis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Computer Engineering, 2004. Canadian Conference on
  • ISSN
    0840-7789
  • Print_ISBN
    0-7803-8253-6
  • Type

    conf

  • DOI
    10.1109/CCECE.2004.1349758
  • Filename
    1349758