LIA system description for NIST SRE 2016

2016/12/15 by Rouvier, Mickael, Bousquet, Pierre-Michel, Ajili, Moez +3
#FOS: Computer and information sciences #Sound (cs.SD)

paper · doi:10.48550/arxiv.1612.05168

Abstract

This paper describes the LIA speaker recognition system developed for the Speaker Recognition Evaluation (SRE) campaign. Eight sub-systems are developed, all based on a state-of-the-art approach: i-vector/PLDA which represents the mainstream technique in text-independent speaker recognition. These sub-systems differ: on the acoustic feature extraction front-end (MFCC, PLP), at the i-vector extraction stage (UBM, DNN or two-feats posteriors) and finally on the data-shifting (IDVC, mean-shifting). The submitted system is a fusion at the score-level of these eight sub-systems.

Related

• The Intelligent Voice 2016 Speaker Recognition System
• UTD-CRSS Systems for 2016 NIST Speaker Recognition Evaluation
• I4U Submission to NIST SRE 2018: Leveraging from a Decade of Shared Experiences
• The IBM 2016 Speaker Recognition System
• HLT-NUS Submission for NIST 2019 Multimedia Speaker Recognition Evaluation