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  • Research Article
  • Open Access

Talking-Face Identity Verification, Audiovisual Forgery, and Robustness Issues

  • 1Email author,
  • 2,
  • 3,
  • 4 and
  • 1
EURASIP Journal on Advances in Signal Processing20092009:746481

  • Received: 1 October 2008
  • Accepted: 3 April 2009
  • Published:


The robustness of a biometric identity verification (IV) system is best evaluated by monitoring its behavior under impostor attacks. Such attacks may include the transformation of one, many, or all of the biometric modalities. In this paper, we present the transformation of both speech and visual appearance of a speaker and evaluate its effects on the IV system. We propose MixTrans, a novel method for voice transformation. MixTrans is a mixture-structured bias voice transformation technique in the cepstral domain, which allows a transformed audio signal to be estimated and reconstructed in the temporal domain. We also propose a face transformation technique that allows a frontal face image of a client speaker to be animated. This technique employs principal warps to deform defined MPEG-4 facial feature points based on determined facial animation parameters (FAPs). The robustness of the IV system is evaluated under these attacks.


  • Face Image
  • Audio Signal
  • Transformation Technique
  • Identity Verification
  • Facial Animation

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Authors’ Affiliations

Computer Science Department, University of Balamand, 100 El-Koura, Lebanon
SAMoVA Team, IRIT-UMR 5505, CNRS, 5505 Toulouse, France
Mathematics Department, University of Balamand, 100 El-Koura, Lebanon
TSI, Ecole Nationale Supérieure des Télécommunications, 46 rue Barrault, 75634 Paris, France


© Walid Karam et al. 2009

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.