Time normalization in voice analysis.

The harmonics-to-noise ratio (HNR) has been widely accepted for quantifying the irregular or noise component of voice. HNR, however, is usually inflated by cycle-to-cycle variations of fundamental frequency period because zero padding is used for time normalization of the wavelet. In this study, a new method was developed for analyzing waveform perturbations of voice. In this method, noise components of voice were calculated from the discrepancies between wavelets after they had been optimally aligned in time. The optimal time normalization of wavelets was accomplished using procedures of dynamic time warping (DTW). This method was evaluated using both synthetic and natural voices, and significant reductions in noise were obtained. The harmonics-to-noise ratio obtained using DTW for time normalization was also shown to be independent of fundamental frequency perturbations.