Symmetry (Jun 2024)

Replay Attack Detection Using Integrated Glottal Excitation Based Group Delay Function and Cepstral Features

  • Amol Chaudhari,
  • Dnyandeo Shedge,
  • Vinayak Bairagi,
  • Aziz Nanthaamornphong

DOI
https://doi.org/10.3390/sym16070788
Journal volume & issue
Vol. 16, no. 7
p. 788

Abstract

Read online

The automatic speaker verification system is susceptible to replay attacks. Recent literature has focused on score-level integration of multiple features, phase information-based features, high frequency-based features, and glottal excitation for the detection of replay attacks. This work presents glottal excitation-based all-pole group delay function (GAPGDF) features for replay attack detection. The essence of a group delay function based on the all-pole model is to exploit information from the speech signal phase spectrum in an effective manner. Further, the performance of integrated high-frequency-based CQCC features with cepstral features, subband spectral centroid-based features (SCFC and SCMC), APGDF, and LPC-based features is evaluated on the ASVspoof 2017 version 2.0 database. On the development set, an EER of 3.08% is achieved, and on the evaluation set, an EER of 9.86% is achieved. The proposed GAPGDF features provide an EER of 10.5% on the evaluation set. Finally, integrated GAPGDF and GCQCC features provide an EER of 8.80% on the evaluation set. The computation time required for the ASV systems based on various integrated features is compared to ensure symmetry between the integrated features and the classifier.

Keywords