An unsupervised audio segmentation method using Bayesian information criterion

Audio segmentation is a well-known problem which can be considered from various angles. In the context of this paper, audio segmentation problem is to extract small “homogeneous” pieces of audio in which the content does not change in terms of the present audio events. The proposed method is compared with the well-known segmentation method; Bayesian Information Criterion (BIC) based Divide-and-Conquer, in terms of average segment duration and computational complexity.