Improving speaker verification performance under spoofing attacks by fusion of different operational modes

Saeid Safavi, Hock Gan, Iosif Mporas

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

In this paper, we propose a methodology for the fusion of different modes of speaker verification (SV) operation (fixed-passphrase, text-dependent and text-independent mode), using regression fusion models. The experimental results with and without spoofing attack conditions and using different single mode speaker verification engines, GMM-UBM, HMM-UBM and i-vector, indicated improvement in all the experiments. The 6.75 % in terms of EER is achieved as the best speaker verification performance, when using fusion of scores from three modes of operation of HMM-UBM based speaker verification systems. Relative improvement of 22.32 % achieved compare to the best performing single mode engine.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE 13th International Colloquium on Signal Processing and its Applications, CSPA 2017
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages219-223
Number of pages5
ISBN (Electronic)9781509011841
DOIs
Publication statusPublished - 10 Oct 2017
Event13th IEEE International Colloquium on Signal Processing and its Applications, CSPA 2017 - Penang, Malaysia
Duration: 10 Mar 201712 Mar 2017

Publication series

NameProceedings - 2017 IEEE 13th International Colloquium on Signal Processing and its Applications, CSPA 2017

Conference

Conference13th IEEE International Colloquium on Signal Processing and its Applications, CSPA 2017
Country/TerritoryMalaysia
CityPenang
Period10/03/1712/03/17

Keywords

  • anti-spoofing
  • Automatic speaker verification
  • GMM-UBM
  • HMM-UBM
  • i-vector
  • MLP
  • regression fusion
  • spoofing attack
  • SVM

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