Speaker Tracking in Broadcast Audio Material in the Framework of the Thisl Project

In this paper, we present a first approach to build an automatic system for broadcast news speaker-based segmentation. Based on a Chop-and-Recluster method, this system is developed in the framework of the THISL project. A metric-based segmentation is used for the Chop procedure and different distances have been investigated. The Recluster procedure relies on a bottom-up clustering of segments obtained beforehand and represented by non-parametricmodels. Various hierarchical clustering schemes have been tested. Some experiments on BBC broadcast news recordings show that the system can detect real speaker changes with high accuracy (mean error ' 0.7s) and fair false alarm rate (mean false alarm rate ' 5.5% ). The Recluster procedure can produce homogeneous clusters but it is not already robust enough to tackle too complex classification tasks.