A vector statistical piecewise polynomial approximation algorithm for environment compensation in telephone LVCSR

A vector statistical piecewise polynomial (VPP) approximation algorithm is proposed for environment compensation in speech signals that are degraded by both additive and convolutive noise. By investigating the model of the telephone environment, we address a piecewise polynomial, namely two linear polynomials and a quadratic polynomial, to approximate the environment function precisely. The VPP is applied either to stationary noise, or to non-stationary noise. In the first case, batch EM is used in the log-spectral domain; in the second case, recursive EM with iterative stochastic approximation is developed in the 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) in background noise and different transmission channels (such as fixed telephone line and GSM). The method can reduce the average character error rate (CER) by about 18%.