LPC Prediction Error — Analysis of Its Variation with the Position of the Analysis Frame

The LPC prediction error provides one measure of the success of linear prediction analysis in modeling a speech signal. Although a great deal is known about the properties of the prediction errOr, relatively little has been published about its variation as a function of the position of the analysis frame. In this paper it is shown that a fairly substantial variation in the prediction error is obtained Within a single frame (i.e., 10 ms), independent of the analysis method (i.e., the covariance, autocorrelation, or lattice method). The implication of this result is that standard methods of LPC analysis may be inadequate for some applications. This is because the error signal is generally uniformly sampled at a low rate (on the order of 100 Hz), and this can lead to aliased results because of the variation of the error signal within the frame. For applications such as word recognition with frame-toframe distance calculations using the prediction error, the errors due to uniform sampling can accrue. For speech synthesis applications, the effect of uniform sampling of the error signal is a small, but noticeable roughness in, the synthetic speech. Various techniques for reducing the intraframe variation of the prediction error are discussed.