Publication Details

Deepfake Speech Detection: A Spectrogram Analysis

FIRC Anton, MALINKA Kamil and HANÁČEK Petr. Deepfake Speech Detection: A Spectrogram Analysis. In: Proceedings of the ACM Symposium on Applied Computing. Avila: Association for Computing Machinery, 2024, pp. 1312-1320. ISBN 979-8-4007-0243-3. Available from: https://dl.acm.org/doi/10.1145/3605098.3635911
Czech title
Detekce deepfake řeči: Analýza spektrogramů
Type
conference paper
Language
english
Authors
Firc Anton, Ing. (DITS FIT BUT)
Malinka Kamil, Mgr., Ph.D. (DITS FIT BUT)
Hanáček Petr, doc. Dr. Ing. (DITS FIT BUT)
URL
Keywords

Deepfake, Speech, Image-based, Deepfake Detection, Spectrogram

Abstract

The current voice biometric systems have no natural mechanics to defend against deepfake spoofing attacks. Thus, supporting these systems with a deepfake detection solution is necessary. One of the latest approaches to deepfake speech detection is representing speech as a spectrogram and using it as an input for a deep neural network. This work thus analyzes the feasibility of different spectrograms for deepfake speech detection. We compare types of them regarding their performance, hardware requirements, and speed. We show the majority of the spectrograms are feasible for deepfake detection. However, there is no general, correct answer to selecting the best spectrogram. As we demonstrate, different spectrograms are suitable for different needs.

Published
2024
Pages
1312-1320
Proceedings
Proceedings of the ACM Symposium on Applied Computing
Conference
ACM Symposium On Applied Computing, Avila, ES
ISBN
979-8-4007-0243-3
Publisher
Association for Computing Machinery
Place
Avila, ES
DOI
UT WoS
001236958200192
EID Scopus
BibTeX
@INPROCEEDINGS{FITPUB12908,
   author = "Anton Firc and Kamil Malinka and Petr Han\'{a}\v{c}ek",
   title = "Deepfake Speech Detection: A Spectrogram Analysis",
   pages = "1312--1320",
   booktitle = "Proceedings of the ACM Symposium on Applied Computing",
   year = 2024,
   location = "Avila, ES",
   publisher = "Association for Computing Machinery",
   ISBN = "979-8-4007-0243-3",
   doi = "10.1145/3605098.3635911",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/12908"
}
Back to top