• DocumentCode
    1973031
  • Title

    Estimating glottal aspiration noise via wavelet thresholding and best-basis thresholding

  • Author

    Lu, Hui-Ling ; Smith, Julius O., III

  • Author_Institution
    Center for Comput. Res. in Music & Acoust., Stanford Univ., CA, USA
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    11
  • Lastpage
    14
  • Abstract
    For the synthesized singing voice to sound breathy, aspiration noise is perceptually most important (see Klatt, D.H. and Klatt, L.C., 1990). We have recently proposed to use pitch-synchronous, amplitude-modulated Gaussian noise to model the aspiration component of the glottal excitation (see Lu, Hui-Ling and Smith, J.O., Proc. Int. Computer Music Conf., p.90-7, 2000). For proper parameterization of the noise residual model, we need to analyze the signal properties of the glottal aspiration noise estimated from real breathy singing recordings. Several wavelet thresholding and best-basis thresholding methods are studied and compared in order to obtain reliable estimates of the glottal aspiration noise. We conclude that the best-basis soft-thresholding method is the most effective way to extract the glottal aspiration noise
  • Keywords
    Gaussian noise; amplitude modulation; parameter estimation; speech synthesis; synchronisation; wavelet transforms; amplitude-modulated Gaussian noise; best-basis thresholding; breathy singing voice; glottal aspiration noise estimation; pitch-synchronous Gaussian noise; singing voice synthesis; soft-thresholding; wavelet thresholding; Acoustic noise; Gaussian noise; Human voice; Music; Noise reduction; Signal synthesis; Speech analysis; Speech synthesis; Synthesizers; White noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applications of Signal Processing to Audio and Acoustics, 2001 IEEE Workshop on the
  • Conference_Location
    New Platz, NY
  • Print_ISBN
    0-7803-7126-7
  • Type

    conf

  • DOI
    10.1109/ASPAA.2001.969530
  • Filename
    969530