logo Idiap Research Institute        
 [BibTeX] [Marc21]
Joint Operation of Voice Biometrics and Presentation Attack Detection
Type of publication: Conference paper
Citation: Korshunov_BTAS-2_2016
Publication status: Published
Booktitle: IEEE International Conference on Biometrics: Theory, Applications and Systems
Year: 2016
Month: September
Address: Niagara Falls, Buffalo, New York, USA
Note: Open source software for the paper: https://pypi.python.org/pypi/bob.paper.btas_j2016
Crossref: Korshunov_Idiap-RR-25-2016:
URL: https://pypi.python.org/pypi/b...
Abstract: Research in the area of automatic speaker verification (ASV) has advanced enough for the industry to start using ASV systems in practical applications. However, as it was also shown for fingerprints, face, and other verification systems, ASV systems are highly vulnerable to spoofing or presentation attacks, limiting their wide practical deployment. Therefore, to protect against such attacks, effective anti-spoofing detection techniques, more formally known as presentation attack detection (PAD) systems, need to be developed. These techniques should be then seamlessly integrated into existing ASV systems for practical all-in-one solutions. In this paper, we focus on the integration of PAD and ASV systems. We consider the state of the art i-vector and ISV-based ASV systems and demonstrate the effect of score-based integration with a PAD system on the verification and attack detection accuracies. In our experiments, we rely on AVspoof database that contains realistic presentation attacks, which are considered by the industry to be the threat to practical ASV systems. Experimental results show a significantly increased resistance of the joint ASV-PAD system to the attacks at the expense of slightly degraded performance for scenarios without spoofing attacks. Also, an important contribution of the paper is an open source and an online-based implementations of the separate and joint ASV-PAD systems.
Projects Idiap
Authors Korshunov, Pavel
Marcel, S├ębastien
Added by: [UNK]
Total mark: 0
  • Korshunov_BTAS-2_2016.pdf