Adaptive speech recognition method with noise compensation

An adaptive speech recognition method with noise compensation capable of compensating noises of an input speech by adjusting parameters of a HMM (Hidden Markov Model) speech model, the input speech having a plurality of speech frames, the method comprising the steps of:

• (A) determining, based on the plurality of speech frames of the input speech and the speech model, optimal equalization factors for feature vectors of the plurality of speech frames corresponding to each probability density function in the speech model, wherein the optimal equalization factor is determined based on the parameters θik=(μik, Σik) of the speech model, and is equivalent to a projection of the speech frame upon Σik−1μik, where μik and Σik are respectively the mean vector and covariance matrix of the k-th mixture density function for a state ŝt=i in the speech model;
• and
• (B) adapting the parameters of the speech model by the optimal equalization factor and a bias compensation vector corresponding to and retrieved by the optimal equalization factor, wherein the optimal equalization factor is provided to adjust a distance of the mean vector in the speech model, and the bias compensation vector is provided to adjust a direction change of the mean vector in the speech model.