Voice-Quality Features for Replay Attack Detection
Loading...
Access rights
openAccess
Journal Title
Journal ISSN
Volume Title
A4 Artikkeli konferenssijulkaisussa
This publication is imported from Aalto University research portal.
View publication in the Research portal
View/Open full text file from the Research portal
Other link related to publication
View publication in the Research portal
View/Open full text file from the Research portal
Other link related to publication
Author
Date
2022
Department
Major/Subject
Mcode
Degree programme
Language
en
Pages
5
384-388
384-388
Series
2022 30th European Signal Processing Conference (EUSIPCO), European Signal Processing Conference
Abstract
Replay attacks are attempts to get fraudulent access to an automatic speaker verification system. In this paper, we investigate the usefulness of voice quality features to detect replay attacks. The voice quality features are used together with the state-of-the-art constant Q cepstral coefficients (CQCC) features. The two feature sets are fused at the score level. Thus, the log-likelihood scores estimated from the two feature sets are linearly weighted to obtain a single fused score. The fused score is used to classify whether a given speech sample is genuine or spoofed. Our experiments with the ASVspoof 2017 dataset demonstrate that the fusion of log-likelihood scores extracted from the CQCC and voice quality features improve the Equal Error Rate (EER) compared to the baseline system which is based only on CQCC features.Description
Keywords
Other note
Citation
Zewoudie, A & Bäckström, T 2022, Voice-Quality Features for Replay Attack Detection . in 2022 30th European Signal Processing Conference (EUSIPCO) . European Signal Processing Conference, IEEE, pp. 384-388, European Signal Processing Conference, Belgrade, Serbia, 29/08/2022 . < https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9909802 >