Abstract To improve the precision of Speaker Segmentation (SS), this paper propose a two-step SS algorithm by making use of silence and gender information. Two-step criterion is used to decide the Speaker Change Point (SCP) within detected speech segmentations. In the first step, pitch difference between different speakers and gender model are used to locate the SCP within neighboring speech segments; In the second step, a gender-based modified T2 criterion formula is used to locate SCP among the same gender speakers, and potential speaker change point is detected based on chunk. The experiment results show that the proposed algorithm improved SS precision and F1 can reach 85.14%. For SS with duration less than 2 s, the algorithm can reduce missed detection rate of about 16%, compared with Bayesian information Criterion.
2010, Vol. 32 
