New score normalization method in speaker verification
说话人确认中分数归一化的一种新方法

In the speaker verification field, the distributions of the target and imposter scores are bimodal, and the output score distributions of different target speaker models are different too, so it is difficult to estimate a common threshold. The most frequently used score normalization techniques: T-Norm and Z-Norm were analyzed. A new technique D-Norm was introduced based on the KL distance. Then a new method ZD-Norm was proposed based on Z-Norm and D-Norm. The experiments show that the ZD-Norm method can improve the performance efficiently and make the estimation of threshold easier.