Paper ID: 2210.05092

The DKU-Tencent System for the VoxCeleb Speaker Recognition Challenge 2022

Xiaoyi Qin, Na Li, Yuke Lin, Yiwei Ding, Chao Weng, Dan Su, Ming Li

This paper is the system description of the DKU-Tencent System for the VoxCeleb Speaker Recognition Challenge 2022 (VoxSRC22). In this challenge, we focus on track1 and track3. For track1, multiple backbone networks are adopted to extract frame-level features. Since track1 focus on the cross-age scenarios, we adopt the cross-age trials and perform QMF to calibrate score. The magnitude-based quality measures achieve a large improvement. For track3, the semi-supervised domain adaptation task, the pseudo label method is adopted to make domain adaptation. Considering the noise labels in clustering, the ArcFace is replaced by Sub-center ArcFace. The final submission achieves 0.107 mDCF in task1 and 7.135% EER in task3.

Submitted: Oct 11, 2022