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

Author:

Chaudhari Amol1ORCID,Shedge Dnyandeo1,Bairagi Vinayak1ORCID,Nanthaamornphong Aziz2ORCID

Affiliation:

1. Department of Electronics and Telecommunication Engineering, AISSMS Institute of Information Technology, Pune 411001, India

2. College of Computing, Prince of Songkla University, Phuket Campus, Phuket 83120, Thailand

Abstract

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.

Funder

the College of Computing at Prince of Songkla University, Thailand

Publisher

MDPI AG

Reference58 articles.

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