Iberoamerican Congress on Pattern Recognition

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications pp 135-142

Homogeneity Measure for Forensic Voice Comparison: A Step Forward Reliability

  • Moez Ajili
  • Jean-François Bonastre
  • Solange Rossato
  • Juliette Kahn
  • Itshak Lapidot
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9423)

Abstract

In forensic voice comparison, it is strongly recommended to follow the Bayesian paradigm to present a forensic evidence to the court. In this paradigm, the strength of the forensic evidence is summarized by a likelihood ratio (LR). But in the real world, to base only on the LR without looking to its degree of reliability does not allow experts to have a good judgement. This work is mainly motivated by the need to quantify this reliability. In this concept, we think that the presence of speaker specific information and its homogeneity between the two signals to compare should be evaluated. This paper is dedicated to the latter, the homogeneity. We propose an information theory based homogeneity measure which determines whether a voice comparison is feasible or not.

Keywords

Forensic voice comparison Reliability Homogeneity Speaker recognition 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Moez Ajili
    • 1
    • 2
  • Jean-François Bonastre
    • 1
  • Solange Rossato
    • 2
  • Juliette Kahn
    • 3
  • Itshak Lapidot
    • 4
  1. 1.Laboratoire Informatique d’Avignon (LIA)University of AvignonAvignonFrance
  2. 2.Laboratoire Informatique de Grenoble (LIG)University of GrenobleGrenobleFrance
  3. 3.Laboratoire National de Métrologie et d’Essais (LNE)ParisFrance
  4. 4.Afeka Center for Language Processing (ACLP)Tel AvivIsrael

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