Experiments on speaker tracking and segmentation in radio broadcast news

In this paper we describe the speaker tracking and clustering system that we implemented for the ESTER evaluation campaign. We present some experiments on normalization in speaker tracking, in particular concerning the use of t-norm for speaker tracking in broadcast news. Results show that the use of t-norm significantly improves the performance at low false alarm rates. In a second part of the paper, we study the possible interactions between speaker tracking and speaker segmentation (also known as speaker diarization). We show that speaker segmentation benefits from the use of speaker tracking as a prior information while the contrary is not true. Using speaker tracking before clustering can decrease the speaker segmentation error by 4% absolute.