Time Windows for Linear Prediction of Speech
P. Kabal · 2009
This report examines the time windows used for linear prediction (LP) analysis of speech. The goal of windowing is to create frames of data each of which will be used to calculate an autocorrelation sequence. Several factors enter into the choice of window. The time and spectral properties of Hamming and Hann windows are examined. We also consider windows based on Discrete Prolate Spherical Sequences including multiwindow analysis. Multiwindow analysis biases the estimation of the correlation more than single window analysis. Windows with frequency responses based on the ultraspherical polynomials are discussed. This family of windows includes Dolph-Chebyshev and Saramaki windows. This report also considers asymmetrical windows as used in modern speech coders. The frequency response of these windows is poor relative to conventional windows. Finally, the presence of a “pedestal” in the time window (as in the case of a Hamming window) is shown to be deleterious to the time evolution of the LP parameters. Time Windows for Linear Prediction of Speech 1 TimeWindows for Linear Prediction of Speech