  This work provides a brief description of Human Language Technology (HLT)
Laboratory, National University of Singapore (NUS) system submission for 2020
NIST conversational telephone speech (CTS) speaker recognition evaluation
(SRE). The challenge focuses on evaluation under CTS data containing
multilingual speech. The systems developed at HLT-NUS consider time-delay
neural network (TDNN) x-vector and ECAPA-TDNN systems. We also perform domain
adaption of probabilistic linear discriminant analysis (PLDA) model and
adaptive s-norm on our systems. The score level fusion of TDNN x-vector and
ECAPA-TDNN systems is carried out, which improves the final system performance
of our submission to 2020 NIST CTS SRE.
