Abstract | ||
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This article is the proceeding of the priority research direction of the voice biometrics systems spoofing problem. We continue exploring speech synthesis spoofing attacks based on creating a text-to-speech voice. In our work we focused on the completely automatic way to create new voices for text-to-speech system and the investigation of the state-of-art spoofing detection system vulnerability to this spoofing attacks. Results obtained during our experiments demonstrate that 10 seconds of speech material is enough for EER increasement up to 19.67 %. Considering the fact, that automatic method for synthesis voiced training allows perpetrators to increase the amount of spoofing attacks to biometric systems, we raise the issue of relevance of a new type of spoofing attack, and development of the effective methods to detect it. |
Year | DOI | Venue |
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2015 | 10.1007/978-3-319-23132-7_17 | Lecture Notes in Artificial Intelligence |
Keywords | Field | DocType |
Spoofing,Anti-spoofing,Speaker recognition,TTS | Speech synthesis,Spoofing attack,Computer security,Computer science,Speech recognition,Speaker recognition,Biometrics,Anti spoofing,Vulnerability | Conference |
Volume | ISSN | Citations |
9319 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 9 | 5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Galina Lavrentyeva | 1 | 24 | 7.40 |
Alexander Kozlov | 2 | 37 | 6.27 |
Sergey Novoselov | 3 | 51 | 10.57 |
Konstantin Simonchik | 4 | 28 | 6.52 |
Vadim Shchemelinin | 5 | 26 | 4.56 |