On an improved F0 estimation based on ℓ2-norm regularized TV-CAR speech analysis using pre-filter

LP (Linear Prediction) analysis is the most commonly used and successful speech analysis implemented in smartphones. We have been proposing time-varying complex AR (TV-CAR) speech analysis for an analytic signal to solve the shortcomings of the LP. Recently, we proposed ℓ2-norm regularization TV-CAR analysis that penalizes rapid spectral changes in time-domain and frequency-domain, called hybrid RLP (Regularized LP) and TRLP (Time-RLP) method, and we have already evaluated performance using F0 estimation for noise corrupted speech. The IRAPT (Instantaneous RAPT) for the estimated complex residual realizes the F0 estimation. This paper proposes an improved F0 estimation introducing a pre-filter as pre-processing and evaluates the performance.