  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.
