KURTOSIS AND NORMALIZED VARIANCE AS MEASURES OF SPEECH SIGNALS CLIPPING VALUE

Abstract

It is shown that the kurtosis and the normalized variance can be used as a measures of the clipping value of speech signals. The use of the proposed measures makes it possible to significantly simplify and speed up the clipping value calculations compare to the methods where preliminarily estimation of the probability density function of the analyzed speech signal is required. Subjective estimates of the clipped speech signals quality were obtained. Matching maps between the proposed objective measures and the subjective estimates of the clipped speech signals quality have been built. It was shown that the maps can be well approximated by polynomials of small (1st–4th) order. This fact indicates the possibility of construction of simple, in computational sense, algorithms for the control of clipped speech signals quality.