We present a compensation technique that corrects for the effects of noise and variability of speaker and environment on speech recognition accuracy by modifying the positions of the poles representing the speech signal in the z-plane. This modification yields pole locations with statistics that more closely match the statistics of the distribution of clean training speech. The parameters of the mapping are obtained from statistics of the distribution of the poles of the training and testing speech. Compensation is performed by direct modification of both the angle and the radius of pole locations, and also by evaluating the cepstrum along a cirele of radius less than 1 in the z-plane to enhance the salience of spectral peaks. These procedures are evaluated using the DARPA Resource Management database using added white noise. They are shown to compensate for the effects of environmental degradation, patvcularly at low SNRs.