The ELISA consortium approaches in speaker segmentation during the NIST 2002 speaker recognition evaluation

Abstract

This paper presents the ELISA consortium activities in automatic speaker segmentation during last NIST 2002 evaluation: two different approaches from CLIPS and LIA laboratories are presented and the possibility of combining them either by applying them consecutively, or by fusing the decisions made by each of them, is investigated. Various types of data were available for NIST 2002. The ELISA systems obtained the lower error rates for two corpora: the CLIPS system obtained the best performance on the Meeting data, the LIA system obtained the best performance on the Switchboard data. The combining strategies proposed in this paper allowed us to improve the performance of the best single system on both data types (up to 30 % of error rate reduction).