Singularity detection of electroglottogram signal by multiscale product method

This paper deals with singularity detection in electroglottogram (EGG) signal using multiscale product method. Wavelet transform of EGG signal is operated by a windowed first derivative of a Gaussian function. This wavelet transform acts as a derivative of a smoothed signal by the Gaussian function. The wavelet coefficients of EGG calculated for different scales, show modulus maxima at discontinuities. The detected singularities correspond to glottal opening and closure instants called GOIs and GCIs. Multiscale product is the multiplication of wavelet coefficients of the signal at three successive scales. This multiscale analysis enhances edge detection, and gives better estimation of the maxima. Geometric mean of the three scale wavelet coefficients is calculated by applying cubic root amplitude function on product. This method gives a good representation of GCI and a best detection of GOI, so as the product is a nonlinear combination of different scales which reduces noise and spurious peaks. The presented method is effective and robust in all cases even for particular signal showing undetermined GOIs and multiple closure peaks.