This paper investigates the effects of using multiple time intervals for the calculation of regression coefficients. The technique that we have used is referred to as Wavelet-Like regression (WLR). Using this approach we have found that the underlying time series in the cepstral domain differs slightly depending upon the index of the series, and that by employing a technique that accounts for this, such as WLR, we may achieve an incremental improvement in recognition performance, at negligble extra costs.