  In this paper, we present the system description of the joint efforts of Brno
University of Technology (BUT) and Omilia -- Conversational Intelligence for
the ASVSpoof2019 Spoofing and Countermeasures Challenge. The primary submission
for Physical access (PA) is a fusion of two VGG networks, trained on single and
two-channels features. For Logical access (LA), our primary system is a fusion
of VGG and the recently introduced SincNet architecture. The results on PA show
that the proposed networks yield very competitive performance in all conditions
and achieved 86\:\% relative improvement compared to the official baseline. On
the other hand, the results on LA showed that although the proposed
architecture and training strategy performs very well on certain spoofing
attacks, it fails to generalize to certain attacks that are unseen during
training.
