Evaluation of F0 estimation using ZFR based on time-varying speech analysis

We have proposed F₀ estimation based on time-varying complex AR (TV-CAR) speech analysis in which F₀ is estimated using an weighted auto-correlation function for complex-valued residual signal calculated by the estimated time-varying complex-valued parameter for analytic signal. On the other hand, Zero Frequency Resonance (ZFR) has been proposed and it has been reported that the ZFR can estimate more accurate F₀. The ZFR employs Zero Frequency Filtering (ZFF) for Hilbert envelope(HE) of LP residual to emphasize the resonance at zero frequency. In this paper, the ZFR based on TV-CAR speech analysis is proposed to estimate more accurate F₀. In the proposed method, the HE is calculated with complex LP residual estimated by the complex parameters for analytic signal. The ZFR signal is calculated from the HE. The ZFR signal is used for the weighted auto-correlation to estimate F₀. We have conducted the evaluation of F₀ estimation using Keele Pitch database. The experimental results show that LP residual-based ZFR method performs best.