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• W2989492704 abstract "Linear Prediction (LP) analysis is speech analysis to estimate AR (Auto-Regressive) coefficients to represent the all-pole spectrum that is applied in speech synthesis recently besides speech coding. We have proposed l <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</sub> -norm optimization based TV-CAR (Time-Varying Complex AR) speech analysis for an analytic signal, MMSE (Minimizing Mean Square Error) or ELS (Extended Least Square) method, and we have applied them into the speech processing such as robust ASR or F <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>0</sub> estimation of speech. On the other hand, B.Kleijn et al. have proposed Regularized Linear Prediction (RLP) method to suppress pitch related bias that is an overestimation of the first formant. In the RLP, l <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</sub> -norm regularized term that is the norm of spectral changes in the frequencies is introduced to suppress the rapid spectral changes. The RLP estimates the parameter so as to minimize l <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</sub> -norm criterion added by the l <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</sub> -norm regularized penalty term. In this paper, the RLP-based TV-CAR speech analysis is proposed and evaluated with the F <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>0</sub> estimation of speech using IRAPT (Instantaneous RAPT) with Keele Pitch Database under noisy conditions." @default.
• W2989492704 created "2019-11-22" @default.
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• W2989492704 date "2019-09-01" @default.
• W2989492704 modified "2023-09-25" @default.
• W2989492704 title "TV-CAR speech analysis based on Regularized LP" @default.
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• W2989492704 doi "https://doi.org/10.23919/eusipco.2019.8902667" @default.
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