On account of the bad accuracy and rob ustness of unimodal biometric recognition,a novel approach is proposed based on total error rate (TER) and feature correlation adaptive fusion method.This study aims at voiding calculating posterior probability of a certain score transfers scores into TER based on corresponding false reject rates (FRRs) and false accept rates (FARs) at first.Secondly,a new adaptive fusion method named based on information e ntropy theory and uncertainty measurement theory is proposed,which considers the correlation between face information and speech information,and the new adaptive fusion method adjusts the fusion weights adapt ively between weight sum fusion sc heme and multiplicative fusion scheme using the characteristic of correlation coefficient.Experimental results show that the proposed method outperforms the traditional score level fusion schemes,the experimental result also confirms the effectiveness of the proposed method to improve the performance of multibiometric system is confirmed.