  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.
