Title :
Speech segmentation by variance fractal dimension
Author :
Grieder, W. ; Kinsner, W.
Author_Institution :
Dept. of Electr. & Comput. Eng., Manitoba Univ., Winnipeg, Man., Canada
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;
Conference_Titel :
Electrical and Computer Engineering, 1994. Conference Proceedings. 1994 Canadian Conference on
Conference_Location :
Halifax, NS
Print_ISBN :
0-7803-2416-1
DOI :
10.1109/CCECE.1994.405793
