• DocumentCode
    548969
  • Title

    Detection of glottal closure instants from Bessel features using AM-FM signal

  • Author

    Prakash, Chetana ; Dhananjaya, N. ; Gangashetty, Suryakanth V.

  • Author_Institution
    Speech & Vision Lab., Int. Inst. of Inf. Technol., Hyderabad, India
  • fYear
    2011
  • fDate
    16-18 June 2011
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Glottal closure instants (GCI) information is useful for accurate speech analysis. In particular accurate spectrum analysis is performed by considering the speech in the intervals of glottal closure. In this paper we propose an approach for detection of GCI based on Bessel features, amplitude and frequency modulated (AM-FM) signal. Using appropriate range of Bessel coefficients, the narrow band, band limited signal is obtained for the given signal. The bandlimited signal is considered as a AM-FM signal. The signal is band limited for 0-300 Hz to remove effect of formants. Amplitude Envelope (AE) function of the AM-FM signal model has been estimated by the discrete energy separation algorithm (DESA). We experimentally evaluated our approach to detect GCI on CMU-Arctic database. The corresponding electro-glottograph (EGG) signals are used as a reference for the validation of the detected GCI locations.
  • Keywords
    Bessel functions; amplitude modulation; frequency modulation; speech processing; AM-FM signal; Bessel features; CMU-Arctic database; EGG signals; amplitude envelope function; amplitude modulated signal; discrete energy separation algorithm; electro-glottograph signals; frequency modulated signal; glottal closure instants information; spectrum analysis; speech analysis; Databases; Electronic mail; Estimation; Frequency modulation; Speech; Speech processing; Time frequency analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Signals and Image Processing (IWSSIP), 2011 18th International Conference on
  • Conference_Location
    Sarajevo
  • ISSN
    2157-8672
  • Print_ISBN
    978-1-4577-0074-3
  • Type

    conf

  • Filename
    5977382