Abstract
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 ℓ <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> -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 F <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</inf> estimation for noise corrupted speech. The IRAPT (Instantaneous RAPT) for the estimated complex residual realizes the F <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</inf> estimation. This paper proposes an improved F <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</inf> estimation introducing a pre-filter as pre-processing and evaluates the performance.
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