Comprehensive Multiparametric Analysis of Human Deepfake Speech Recognition
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F24%3APU151920" target="_blank" >RIV/00216305:26230/24:PU151920 - isvavai.cz</a>
Result on the web
<a href="https://jivp-eurasipjournals.springeropen.com/articles/10.1186/s13640-024-00641-4" target="_blank" >https://jivp-eurasipjournals.springeropen.com/articles/10.1186/s13640-024-00641-4</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1186/s13640-024-00641-4" target="_blank" >10.1186/s13640-024-00641-4</a>
Alternative languages
Result language
angličtina
Original language name
Comprehensive Multiparametric Analysis of Human Deepfake Speech Recognition
Original language description
In this paper, we undertake a novel two-pronged investigation into the human recognition of deepfake speech, addressing critical gaps in existing research. First, we pioneer an evaluation of the impact of prior information on deepfake recognition, setting our work apart by simulating real-world attack scenarios where individuals are not informed in advance of deepfake exposure. This approach simulates the unpredictability of real-world deepfake attacks, providing unprecedented insights into human vulnerability under realistic conditions. Second, we introduce a novel metric to evaluate the quality of deepfake audio. This metric facilitates a deeper exploration into how the quality of deepfake speech influences human detection accuracy. By examining both the effect of prior knowledge about deepfakes and the role of deepfake speech quality, our research reveals the importance of these factors, contributes to understanding human vulnerability to deepfakes, and suggests measures to enhance human detection skills.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Eurasip Journal on Image and Video Processing
ISSN
1687-5176
e-ISSN
1687-5281
Volume of the periodical
2024
Issue of the periodical within the volume
24
Country of publishing house
US - UNITED STATES
Number of pages
25
Pages from-to
1-25
UT code for WoS article
001302501400001
EID of the result in the Scopus database
2-s2.0-85202737368