Allpass Modeling of Phase Spectrum of Speech Signals for Formant Tracking

Abstract

Formant tracking is a very important task in speech applications. Most of the current formant tracking methods bank on peak picking from linear prediction (LP) spectrum of speech, which suffers from merged/spurious peaks in LP spectra, resulting in unreliable formant candidates. In this paper, we present the significance of phase spectrum of speech in refining the formant candidates from LP analysis. The short-time phase spectrum of speech is modeled as phase response of an allpass (AP) system, where the coefficients of AP system are initialized with LP coefficients and estimated with an iterative procedure. This technique refines the initial formants from LP analysis using phase spectrum of speech through an AP analysis, thereby accomplishing fusion of information from magnitude and phase spectra. The group delay of the resultant AP system exhibits unambiguous peaks at formants and, delivers reliable formant candidates. The formant trajectories obtained by selection of formants from these candidates are reported to be more accurate than those obtained from LP analysis. The fused information from magnitude and phase spectra has rendered relative improvements of 25%, 15% and 18% in tracking accuracy of first, second and third formants, respectively, over those from magnitude spectrum alone.