Papers › HLT-NUS SUBMISSION FOR 2020 NIST Conversational Telephone Speech SRE

HLT-NUS SUBMISSION FOR 2020 NIST Conversational Telephone Speech SRE

12 Nov 2021arXiv:2111.06671archive 2025-07-28

Rohan Kumar Das, Ruijie Tao, Haizhou Li

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.

PaperPDFCode

Code

taoruijie/ecapatdnn officialmentioned in papermentioned on GitHubpytorchMIT report
taoruijie/ecapa-tdnn mentioned on GitHubpytorchMIT report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Tasks

Domain AdaptationSpeaker Recognition

Results from the paper archive 2025-07-28

No leaderboard rows for this paper in the archive.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections