LIA system description for NIST SRE 2016

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 s...

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Bibliographic Details
Published inarXiv.org
Main Authors Rouvier, Mickael, Pierre-Michel Bousquet, Ajili, Moez, Waad Ben Kheder, Matrouf, Driss, Bonastre, Jean-François
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 15.12.2016
Subjects
Feature extraction
Speech recognition
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Summary: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.
ISSN:2331-8422