An improved maximum model distance approach was proposed to train HMM.By adopting a more realistic model distance definition

discriminative information contained in the training data could be used to improve the performance of recognizer.HMM parameter adjustment rules were induced.Both isolated word and continuous speech recognition experiments on TIMIT database showed that significant error reduction could be achieved by the improved approach.