Audio-replay attack detection countermeasures
Abstract
This paper presents the Speech Technology Center (STC) replay attack detection systems proposed for Automatic Speaker Verification Spoofing and Countermeasures Challenge 2017. In this study we focused on comparison of different spoofing detection approaches. These were GMM based methods, high level features extraction with simple classifier and deep learning frameworks. Experiments performed on the development and evaluation parts of the challenge dataset demonstrated stable efficiency of deep learning approaches in case of changing acoustic conditions. At the same time SVM classifier with high level features provided a substantial input in the efficiency of the resulting STC systems according to the fusion systems results.
Cite
@article{arxiv.1705.08858,
title = {Audio-replay attack detection countermeasures},
author = {Galina Lavrentyeva and Sergey Novoselov and Egor Malykh and Alexander Kozlov and Oleg Kudashev and Vadim Shchemelinin},
journal= {arXiv preprint arXiv:1705.08858},
year = {2017}
}
Comments
11 pages, 3 figures, accepted for Specom 2017