Abstract: A Vector piecewise polynomial (VPP) approximation algorithm is proposed for environment compensation of speech signals degraded by both additive and convolutive noises. By investigating the model of the telephone environment, we propose a piecewise polynomial, namely two linear polynomials and a cuadratic polynomial, to approximate the environment function precisely. The VPP is applied either to the stationary noise, or to the non-stationary noise. In the first case, the batch EM is used m log spectral domain; in the second case the recursive EM with iterative stochastic approximation is developed in cepstral domain. Both approaches are based on the minimum mean squared error (MMSE) sense. Experimental results are presented on the application of this approach in improving the performance of Mandarin large vocabulary continuous speech recognition (LVCSR) due to the background noises and different transmission channels (such as fixed telephone line and GSM). The method can reduce the average character error rate (CER) by about 18%.