Cohort selection for text-dependent speaker verification score normalization

Houssemeddine Khemiri, Dijana Petrovska-Delacretaz

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper a speaker dependent cohort selection for T-norm score normalization is proposed in the context of text-dependent speaker verification. The goal of the proposed technique is to find a set of cohort speakers who are close to the target speaker. In order to properly select the subset of speakers for the normalization, a distance between each target speaker model and the the available normalization models is computed and the nearest models are chosen to represent the cohort set for that target model. The proposed system is evaluated on Part1 of the RSR2015 database. With the proposed normalization method a relative improvement of 71% in terms of the Equal Error Rater (EER) is achieved.

Original languageEnglish
Title of host publication2nd International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages689-692
Number of pages4
ISBN (Electronic)9781467385268
DOIs
Publication statusPublished - 26 Jul 2016
Externally publishedYes
Event2nd International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2016 - Monastir, Tunisia
Duration: 21 Mar 201624 Mar 2016

Publication series

Name2nd International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2016

Conference

Conference2nd International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2016
Country/TerritoryTunisia
CityMonastir
Period21/03/1624/03/16

Keywords

  • T-norm
  • cohort selection
  • text-dependent speaker verification

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