Abstract: Based on adaptation data and training data,a state restructuring method was proposed.In the method,parameters between confused states were shared,which improved the posterior probability,made better use of adaptation data and indirectly restructured the decision tree of the baseline.Experimental results showed when a varying number of adaptation sentences were taken from each speaker,restructured system increased recognition rate consistently compared with the baseline and achieved an average recognition increase of 15.60% by combining with MLLR speaker adaptation than MLLR alone.Such results proved the state-restructuring method could effectively reduce the recognition rate decreasing led by the difference between the decision tree structures of training data and testing data.