On the Use of Asymmetric Windows for Robust Speech Recognition

This paper deals with the problem of searching for a suitable window for robust speech recognition in noisy conditions. A set of asymmetric windows, so-called DDRc,w, are proposed which are controlled by two parameters, center c and width w. These windows are derived from the DDR window used in the higher-lag autocorrelation spectrum estimation (HASE) method and act over the OSA (One-Sided Autocorrelation) in order to perform spectral estimation. The two parameters, c and w, allow us to control the level of weight given to the first noisy autocorrelation coefficients and to emphasize the important ones. Finally, it is shown that the best window of the proposed set is the DDR62,200. This window is centered around the average pitch of human speech and it provides a higher speech recognition performance over the Aurora-2 and Aurora-3 databases than those obtained by previously proposed windows.