A Study on Replay Attack and Anti-Spoofing for Automatic Speaker Verification
Abstract
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.
Keywords
Cite
@article{arxiv.1706.02101,
title = {A Study on Replay Attack and Anti-Spoofing for Automatic Speaker Verification},
author = {Lantian Li and Yixiang Chen and Dong Wang and Thomas Fang Zheng},
journal= {arXiv preprint arXiv:1706.02101},
year = {2017}
}