Evaluation of F0 estimation using ZFR based on time-varying speech analysis
Keiichi Funaki, Takehito Higa · 2012
We have proposed F0estimation based on time-varying complex AR (TV-CAR) speech analysis in which F0is 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 F0estimation using Keele Pitch database. The experimental results show that LP residual-based ZFR method performs best.