• DocumentCode
    3162820
  • Title

    Speech segmentation by variance fractal dimension

  • Author

    Grieder, W. ; Kinsner, W.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Manitoba Univ., Winnipeg, Man., Canada
  • fYear
    1994
  • fDate
    25-28 Sep 1994
  • Firstpage
    481
  • Abstract
    This paper describes an implementation of the variance fractal dimension algorithm as a technique for the analysis of speech waveforms. The technique produces a fractal dimension trajectory which can be used for the detection of boundaries of an utterance in noise. The approach is superior to any other energy-based boundary-detection technique. It can also be used to segment speech utterances into sentences, words, or even phonemes. These observations are based on extensive experimental results on speech digitized at 44.1 kilosamples per second, with 16 bits in each sample
  • Keywords
    fractals; speech processing; speech recognition; 16 bit; automatic speech recognition; boundaries detection; energy-based boundary-detection technique; experimental results; fractal dimension trajectory; noise; phonemes; sentences; speech segmentation; speech utterances; speech waveforms analysis; variance fractal dimension algorithm; words; Fractals; Speech analysis; Speech recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Computer Engineering, 1994. Conference Proceedings. 1994 Canadian Conference on
  • Conference_Location
    Halifax, NS
  • Print_ISBN
    0-7803-2416-1
  • Type

    conf

  • DOI
    10.1109/CCECE.1994.405793
  • Filename
    405793