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Audio-Replay Attack Detection Countermeasures

  • Galina Lavrentyeva
  • Sergey Novoselov
  • Egor Malykh
  • Alexander Kozlov
  • Oleg Kudashev
  • Vadim Shchemelinin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10458)

Abstract

This paper presents the Speech Technology Center (STC) replay attack detection systems proposed for Automatic Speaker Verification Spoofing and Countermeasures Challenge 2017. In this study we focused on comparison of different spoofing detection approaches. These were GMM based methods, high level features extraction with simple classifier and deep learning frameworks. Experiments performed on the development and evaluation parts of the challenge dataset demonstrated stable efficiency of deep learning approaches in case of changing acoustic conditions. At the same time SVM classifier with high level features provided a substantial input in the efficiency of the resulting STC systems according to the fusion systems results.

Keywords

Spoofing Anti-spoofing Speaker recognition Replay attack detection ASVspoof 

Notes

Acknowledgements

This work was financially supported by the Ministry of Education and Science of the Russian Federation, Contract 14.578.21.0126 (ID RFMEFI57815X0126).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Galina Lavrentyeva
    • 1
  • Sergey Novoselov
    • 1
    • 2
  • Egor Malykh
    • 1
  • Alexander Kozlov
    • 2
  • Oleg Kudashev
    • 1
    • 2
  • Vadim Shchemelinin
    • 1
  1. 1.ITMO UniversitySt. PetersburgRussia
  2. 2.STC-innovations Ltd.St. PetersburgRussia

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