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The DKU-MSXF Diarization System for the VoxCeleb Speaker Recognition Challenge 2023

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arxiv 2308.07595 v2 pith:33FIRXID submitted 2023-08-15 eess.AS

Ming Cheng , Weiqing Wang , Xiaoyi Qin , Yuke Lin , Ning Jiang , Guoqing Zhao , Ming Li This is my paper · ORCID
classification eess.AS
keywords diarizationchallengedetectionactivityclustering-baseddku-msxfrecognitionspeaker
verification ladder T0 review T1 audit T2 compute T3 formal
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This paper describes the DKU-MSXF submission to track 4 of the VoxCeleb Speaker Recognition Challenge 2023 (VoxSRC-23). Our system pipeline contains voice activity detection, clustering-based diarization, overlapped speech detection, and target-speaker voice activity detection, where each procedure has a fused output from 3 sub-models. Finally, we fuse different clustering-based and TSVAD-based diarization systems using DOVER-Lap and achieve the 4.30% diarization error rate (DER), which ranks first place on track 4 of the challenge leaderboard.

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