Synthesizer to speech analysis based on pseudo Wigner distribution

For the past five decades, the spectrogram has been one of the classical time-frequency representations (TFRs) for the analysis of speech signals. However, other TFRs incorporating a Wigner distribution (WD). Smoothing which is less extensive than that of the spectrogram may be advantageous whenever the ''fine structure'' of a speech signal is of interest. The smoothed pseudo Wigner distribution SPWD is shown to be a useful tool for the analysis of speech data. In particular, comparisons of the SPWD to that of the spectrogram reveals that much better resolution is achieved when using the SPWD. To reduce the degree of linear smoothing in the computation of the SPWD we propose an adaptive masking scheme for the suppression of interference terms.