Nonstationary environment compensation based on sequential estimation

Sequential approaches are proposed to compensate for the effects of the nonstationary environment for robust speech recognition. Unlike the batch approaches, the proposed methods derive a different parameter estimate for each time using the sequential expectation maximization (EM) algorithm. Moreover, we also propose the forward-backward estimation scheme as an improvement of the sequential parameter estimation.