Talking-face identity verification, audiovisual forgery, and robustness issues

  • Authors:

  • Walid Karam;Hervé Bredin;Hanna Greige;Gérard Chollet;Chafic Mokbel

  • Affiliations:

  • Computer Science Department, University of Balamand, El-Koura, Lebanon;SAMoVA Team, IRIT-UMR, CNRS, Toulouse, France;Mathematics Department, University of Balamand, El-Koura, Lebanon;TSI, Ecole Nationale Supérieure des Télécommunications, Paris, France;Computer Science Department, University of Balamand, El-Koura, Lebanon

  • Venue:
  • EURASIP Journal on Advances in Signal Processing - Special issue on recent advances in biometric systems: a signal processing perspective
  • Year:
  • 2009

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Abstract

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.