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arXiv · 2210.01677

The DKU-DukeECE Diarization System for the VoxCeleb Speaker Recognition Challenge 2022

Weiqing Wang·Xiaoyi Qin·Ming Cheng·Yucong Zhang·Kangyue Wang·Ming Li
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Abstract

This paper discribes the DKU-DukeECE submission to the 4th track of the VoxCeleb Speaker Recognition Challenge 2022 (VoxSRC-22). Our system contains a fused voice activity detection model, a clustering-based diarization model, and a target-speaker voice activity detection-based overlap detection model. Overall, the submitted system is similar to our previous year's system in VoxSRC-21. The difference is that we use a much better speaker embedding and a fused voice activity detection, which significantly improves the performance. Finally, we fuse 4 different systems using DOVER-lap and achieve 4.75 of the diarization error rate, which ranks the 1st place in track 4.

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Weiqing Wang, Xiaoyi Qin, Ming Cheng, Yucong Zhang, Kangyue Wang, Ming Li. 2022-10-04. The DKU-DukeECE Diarization System for the VoxCeleb Speaker Recognition Challenge 2022. https://arxiv.org/abs/2210.01677

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