Abstract: The task of Speaker diarization is to group together speech segments uttered by the same sp-eaker. This paper presents an approach to speaker diarization based on a novel combination of Cross Log-likelihood Ratio (CLR) and standard Bayesian information criterion (BIC). Cross Log-likelihood Ratio provides an inter-cluster distance measure,while BIC provides a proper stopping criterion for clustering. The method combines the advantage of these two methods and yields favorable performance in unsupervised speaker diarization. Experiment results show that the performance of the proposed approach based on combination of the CLR and BIC,is better than the approach only based on CLR clustering.