XBIC: Real-Time Cross Probabilities Measure for Speaker Segmentation

In this paper a novel probability based measure is presented that shows good results for real time blind speaker segmentation. In such task there is no previous information about the identity or how many speakers there are. Similar to the Bayesian Information Criterion (BIC), the proposed measure indicates the similarity between two speech segments on either side of a given test point. By computing cross probabilities between both segments, an abrupt decrease of the measure value indicates the existence of an acoustic change point. A scrolling window implementation, in a similar way that is used in metric based techniques, is shown to give better results regarding speed and change detection. This measure allows building real-time systems. Tests with Broadcast news data show a general improvement compared to the commonly used BIC method.

ICSI Technical Report TR-05-008

Speech