A Study on Replay Attack and Anti-Spoofing for Automatic Speaker Verification

被引：25
|
作者：
Li, Lantian [1 ]
Chen, Yixiang [1 ]
Wang, Dong [1 ]
Zheng, Thomas Fang [1 ]
机构：
[1] Tsinghua Univ, Dept Comp Sci & Technol, Res Inst Informat Technol, Ctr Speech & Language Technol, Beijing 100084, Peoples R China
来源：
18TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2017), VOLS 1-6: SITUATED INTERACTION | 2017年
基金：
中国国家自然科学基金;
关键词：
replay attack; spoofing countermeasures;
D O I：
10.21437/Interspeech.2017-456
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
For practical automatic speaker verification (ASV) systems, replay attack poses a true risk. By replaying a pre-recorded speech signal of the genuine speaker, ASV systems tend to be easily fooled. An effective replay detection method is therefore highly desirable. In this study, we investigate a major difficulty in replay detection: the over-fitting problem caused by variability factors in speech signal. An F-ratio probing tool is proposed and three variability factors are investigated using this tool: speaker identity, speech content and playback & recording device. The analysis shows that device is the most influential factor that contributes the highest over-fitting risk. A frequency warping approach is studied to alleviate the over-fitting problem, as verified on the ASV-spoof 2017 database.
引用
收藏
页码：92 / 96
页数：5
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