A methodology for efficiency estimation of the speech signal feature extraction methods
This paper deals with a basis of methodology for speech signal feature description. Speech signal is described by three sets of features (the set of all descriptive features, the set of all selected features, and the set of all characteristic features). Feature description methods are described by three sets of maps (descriptive feature map, selected feature map, and characteristic feature map). As an example two feature description methods are considered — zero — crossing method and method of formant frequency energy classes (variant a and b). Efficiency of a single method being used in the recognition process has been estimated on the basis of experimental results. It is shown that the Fourier transformation as a map of descriptive features is more convenient as a measurement of time interval lenght. The mapping rule in variant b of the method of formant frequency energy classes gives a more convenient map of selected features than the mapping rule in variant a. With these maps the smallest features overlapping and consequently a better average recognition accuracy (greater than 92.5 %) can be achieved.
KeywordsFeature Vector Speech Signal Discrete Fourier Transformation Recognition Accuracy Descriptive Feature
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- P.Willich, "Putting speech recognizers to work", IEEE Spectrum, april 1987, pp. 55–57.Google Scholar
- F. Fallside and W. A. Woods, Computer speech processing, Prentice-Hall, Englewood Cliffs, NJ, 1985.Google Scholar
- R. De Mori and C. Y. Suen, New Systems and Arhitectures for Automatic Speech Recognition and Synthesis, Springer-Verlag, Berlin, 1985.Google Scholar
- R. W. Ramirez, The FFT, Prentice-Hall, Englewod Cliffs, NJ, 1985.Google Scholar
- J. C. Simon, Spoken Language Generation and Understanding, D. Reidel Publishing Company, 1980, pp. 129–145Google Scholar
- James C. Anderson, "Improved zero — crossing method enhances digital speech", EDN Magazine, vol.27, No.20, Oct.13 1982, pp.171–174.Google Scholar
- R.J. Niederjohn and P.F. Castelaz, "Zero-crossing analysis methods and their use for automatic speech recognition", Proc. IEEE Comp. Soc. Workshop on Pat. Recog. and Artif. Intelligence, 1978.Google Scholar