A kepstrum approach to filtering, smoothing and prediction with application to speech enhancement
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Abstract
A kepstrum (or complex-cepstrum) approach to minimum-phase Wiener filtering of stationary scalar processes is proposed and solved for the case of signal plus coloured noise, where the noise possibly includes a white-noise component. A general solution is found in an innovations form. The spectral factorization of the noise model and of the signal-plus-noise model required for the solution are determined from data using the kepstrum technique with the fast Fourier transform. This approach avoids dependence on any form of multidimensional state-space or polynomial-based model and so avoids use of recursive parameter estimation or of Diophantine equations.
