Automatically Trained TTS for Effective Attacks to Anti-spoofing System

被引:0
作者
Lavrentyeva, Galina [1 ]
Kozlov, Alexandr [1 ]
Novoselov, Sergey [1 ]
Simonchik, Konstantin [1 ,2 ]
Shchemelinin, Vadim [1 ,2 ]
机构
[1] Speech Technol Ctr Ltd, St Petersburg, Russia
[2] ITMO Univ, St Petersburg, Russia
来源
SPEECH AND COMPUTER (SPECOM 2015) | 2015年 / 9319卷
关键词
Spoofing; Anti-spoofing; Speaker recognition; TTS;
D O I
10.1007/978-3-319-23132-7_17
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:137 / 143
页数:7
相关论文
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