The smoothed pseudo-Wigner distribution in speech analysis
L. Khadra · The Journal of the Acoustical Society of America · 1988
Recently, a great deal of interest has been shown in applying the Wigner-Ville distribution to obtain time-frequency energy representation of nonstationary signals. The utility of the Wigner distribution has proved useful in analyzing monocomponent signals. In the case of multicomponent signals, the Wigner distribution adds cross terms without any physical significance to the time-frequency distribution. The presence of cross terms obscures the actual spectral features of interest and makes the results very misleading. To apply the Wigner-Ville distribution to speech signals, it is essential to remove all cross terms not of interest. This problem may be solved by smoothing the Wigner-Ville distribution independently in time and frequency directions using the “smoothed” pseudo-Wigner estimator. This estimator possesses several advantages over the short time periodogram. This presentation will concentrate on the application of the smoothed pseudo-Wigner distribution (SPWD) to speech signals and will demonstrate the ability of the SPWD to improve the quality of the time-frequency representation of speech signals. In particular, a comparison will be made between the spectrogram and the SPWD, and it will be shown how high-frequency spectral features may be easily detected from an SPWD but are far less obvious in the spectrogram. Moreover, it will be shown that the SPWD is more appropriate for the analysis of formant structure.