  In this report, we describe the submission of ShaneRun's team to the VoxCeleb
Speaker Recognition Challenge (VoxSRC) 2020. We use ResNet-34 as encoder to
extract the speaker embeddings, which is referenced from the open-source
voxceleb-trainer. We also provide a simple method to implement optimum fusion
using t-SNE normalized distance of testing utterance pairs instead of original
negative Euclidean distance from the encoder. The final submitted system got
0.3098 minDCF and 5.076 % ERR for Fixed data track, which outperformed the
baseline by 1.3 % minDCF and 2.2 % ERR respectively.
