Wed-1-7-2 THUEE System for NIST SRE19 CTS Challenge

Ruyun Li(Tsinghua University), Tianyu Liang(Tsinghua University), Dandan Song(TsingMicro Co. Ltd.), yi liu(tsinghua university), Yangcheng Wu(Tsinghua University), Can Xu(Tsinghua University), Peng Ouyang(TsingMicro Co. Ltd.), Xianwei Zhang(Tsinghua University), Shouyi Yin(Tsinghua University), Xianhong Chen(Tsinghua University), Weiqiang Zhang(Tsinghua University) and Liang HE(Tsinghua University)
Abstract: In this paper we present the systems submitted by THUEE to NIST 2019 Speaker Recognition Evaluation CTS Challenge (SRE19). Similar to the previous SREs, mismatch of language and channel between the training sets and enrollment/test sets, remains as a major challenge in this evaluation. Our primary system was a linear fusion of six subsystems, which focus on: (i) building deeper and wider speaker embedding model trained on a great number of public large-scale data resources, (ii) exploring novel speaker discriminative embedding system combined with phonetic information, and (iii) investigating effective back-ends against the domain mismatch. The final resulting systems are shown to be both complementary and effective in achieving overall improvements of speaker recognition performance.
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