A comparison of several recent methods of fundamental frequency and voicing decision estimation

Abstract

The authors are interested in the comparison of several kinds of methods for fundamental frequency estimation and GCI (glottal closure instant) detection. These methods operate in various domains (time-, frequency- or joint time-frequency domains). Their performances have been compared for both fundamental frequency estimation and voicing decision tasks as well as GCI detection, when applicable. This comparison was designed to be as unbiased as possible, so as to reflect the intrinsic properties of each method. A method based on a "Born-Jordan" kernel bilinear time-frequency representation of speech signals achieves the best performance in terms of GCI detection accuracy but is not as robust to inter-speaker variability as the SIFT algorithm. An auditory model, which has been applied on the same data in a previous study has been shown to compare favourably to other methods (such as SIFT) in adverse noisy conditions only.