mlsanityData to 7 Oct 2026

The DKU-DukeECE-Lenovo System for the Diarization Task of the 2021 VoxCeleb Speaker Recognition Challenge

arXiv 2109.02002 ↗First posted 5 Sep 2021eess.AS cs.SDcited by 7

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Abstract (arXiv)

This report describes the submission of the DKU-DukeECE-Lenovo team to the VoxCeleb Speaker Recognition Challenge (VoxSRC) 2021 track 4. Our system including a voice activity detection (VAD) model, a speaker embedding model, two clustering-based speaker diarization systems with different similarity measurements, two different overlapped speech detection (OSD) models, and a target-speaker voice activity detection (TS-VAD) model. Our final submission, consisting of 5 independent systems, achieves a DER of 5.07% on the challenge test set.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Sep 2021.

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Citing papers per year: 2021: 1; 2022: 3; 2023: 1; 2024: 2.

7 papers.

  1. 2021Transcribe-to-Diarize: Neural Speaker Diarization for Unlimited Number of Speakers using End-to-End Speaker-Attributed ASRcited by 22
  2. 2024Sortformer: A Novel Approach for Permutation-Resolved Speaker Supervision in Speech-to-Text Systemscited by 12
  3. 2024The VoxCeleb Speaker Recognition Challenge: A Retrospectivecited by 9
  4. 2023VoxSRC 2022: The Fourth VoxCeleb Speaker Recognition Challengecited by 8
  5. 2022Target Speaker Voice Activity Detection with Transformers and Its Integration with End-to-End Neural Diarizationcited by 7
  6. 2022Royalflush Speaker Diarization System for ICASSP 2022 Multi-channel Multi-party Meeting Transcription Challengecited by 2
  7. 2022TSUP Speaker Diarization System for Conversational Short-phrase Speaker Diarization Challengecited by 1