Detection of speaker liveness with CNN isolated word ASR for verification systems
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F22%3A10247867" target="_blank" >RIV/61989100:27240/22:10247867 - isvavai.cz</a>
Výsledek na webu
<a href="https://link.springer.com/article/10.1007/s11042-021-11150-1" target="_blank" >https://link.springer.com/article/10.1007/s11042-021-11150-1</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s11042-021-11150-1" target="_blank" >10.1007/s11042-021-11150-1</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Detection of speaker liveness with CNN isolated word ASR for verification systems
Popis výsledku v původním jazyce
The article proposes a new speaker liveness test for speech verification systems. Biometric authentication systems based on speaker verification are often subject to presentation attacks which use the target speaker's recorded speech. We propose a liveness test which uses CNN isolated word ASR as a countermeasure to repel attacks during the verification process. The liveness test incorporates the extraction of MFCC coefficients and the CNN classifier. Reliability of the recognition of isolated words is verified against a validation dataset of various sizes. The achieved results verified the system's reliability, which decreased slightly as the size of the keyword dataset increased. The proposed method represents a simple and effective security component against presentation attacks for existing SV systems. (C) 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Název v anglickém jazyce
Detection of speaker liveness with CNN isolated word ASR for verification systems
Popis výsledku anglicky
The article proposes a new speaker liveness test for speech verification systems. Biometric authentication systems based on speaker verification are often subject to presentation attacks which use the target speaker's recorded speech. We propose a liveness test which uses CNN isolated word ASR as a countermeasure to repel attacks during the verification process. The liveness test incorporates the extraction of MFCC coefficients and the CNN classifier. Reliability of the recognition of isolated words is verified against a validation dataset of various sizes. The achieved results verified the system's reliability, which decreased slightly as the size of the keyword dataset increased. The proposed method represents a simple and effective security component against presentation attacks for existing SV systems. (C) 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
20203 - Telecommunications
Návaznosti výsledku
Projekt
<a href="/cs/project/LM2018140" target="_blank" >LM2018140: e-Infrastruktura CZ</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2022
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Multimedia Tools and Applications
ISSN
1380-7501
e-ISSN
—
Svazek periodika
18
Číslo periodika v rámci svazku
7
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
13
Strana od-do
9445-9457
Kód UT WoS článku
000662846600006
EID výsledku v databázi Scopus
2-s2.0-85108146563