  In this report, we describe the submission of Brno University of Technology
(BUT) team to the VoxCeleb Speaker Recognition Challenge (VoxSRC) 2019. We also
provide a brief analysis of different systems on VoxCeleb-1 test sets.
Submitted systems for both Fixed and Open conditions are a fusion of 4
Convolutional Neural Network (CNN) topologies. The first and second networks
have ResNet34 topology and use two-dimensional CNNs. The last two networks are
one-dimensional CNN and are based on the x-vector extraction topology. Some of
the networks are fine-tuned using additive margin angular softmax. Kaldi FBanks
and Kaldi PLPs were used as features. The difference between Fixed and Open
systems lies in the used training data and fusion strategy. The best systems
for Fixed and Open conditions achieved 1.42% and 1.26% ERR on the challenge
evaluation set respectively.
