New feedback method of hybrid HMM/ANN methods for continuous speech recognition

In the continuous speech recognition, the co-pronunciation between two successive phonemes seriously disturb recognition effect. It is difficult for pure hidden Markov model(HMM) methods to cope with the co-pronunciation, because HMM methods consider that two successive frames of speech are independant. The hybrid HMM and artificial neural networks(ANN) methods with feedback MLP[1,3] provide the ability to cope with the co-pronunciation by means of the feedback input. In this paper, we propose a new feedback method for feedback hybrid HMM/ANN methods on the basis of the original methods[1,3]. New feedback method provides the more information of co-pronunciation to feedback ANN. As a result, new feedback method falls the error rate 20.4%. Additionally, By means of our previous work, the hybrid mthods HMM/ANN with the feedback double MLP structure, we discuss the method that reduces the computation of the feedback MLP during the recognition.