Broadcast news speaker tracking for ESTER 2005 campaign

This paper presents the speaker tracking system of the LIA laboratory, validated during ESTER 2005 campaign on a radio broadcast news corpus of about 90 h. The LIA speaker tracking system firstly uses an acoustic class segmentation in order to suppress non speech frames and to detect the speech conditions. Secondly, a speaker diarization process is applied in order to provide speaker detection system (the last step) with speaker homogeneous segments (boundaries and clustering). The speaker detection system uses UBM/GMM likelihood ratios in order to decide if a segment belongs to one tracked speaker. The speaker tracking system is presented and some results obtained during ESTER 2005 campaign are proposed. The presented systems are based on the ALIZE platform and are available thanks to an open software licence.