Speaker Change Detection Based on the Pairwise Distance Matrix

Speaker change detection is most commonly done by statistically determining whether the two adjacent segments of a speech stream are significantly different or not. In this paper, we propose a novel method to detect speaker change points based on the minimum statistics of the pairwise distance matrix of feature vectors. The use of the minimum statistics makes it possible to compare between the similar acoustic groups, which is effective in suppressing the phonetic variation. Experimental results showed that the proposed method is promising for speech change detection problem.