  This report describes the UNISOUND submission for Track1 and Track2 of
VoxCeleb Speaker Recognition Challenge 2023 (VoxSRC 2023). We submit the same
system on Track 1 and Track 2, which is trained with only VoxCeleb2-dev.
Large-scale ResNet and RepVGG architectures are developed for the challenge. We
propose a consistency-aware score calibration method, which leverages the
stability of audio voiceprints in similarity score by a Consistency Measure
Factor (CMF). CMF brings a huge performance boost in this challenge. Our final
system is a fusion of six models and achieves the first place in Track 1 and
second place in Track 2 of VoxSRC 2023. The minDCF of our submission is 0.0855
and the EER is 1.5880%.
