# The ByteDance Speaker Diarization System for the VoxCeleb Speaker Recognition Challenge 2021

arXiv: https://arxiv.org/abs/2109.02047 · HTML: https://mlsanity.com/paper/2109.02047/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Sep 2021.

## Built on by (most cited first, 7 of 7)

- [VoxSRC 2022: The Fourth VoxCeleb Speaker Recognition Challenge](https://mlsanity.com/paper/2302.10248/) (2023)
- [The VoxCeleb Speaker Recognition Challenge: A Retrospective](https://mlsanity.com/paper/2408.14886/) (2024)
- [Multi-scale speaker embedding-based graph attention networks for speaker diarisation](https://mlsanity.com/paper/2110.03361/) (2021)
- [Target Speaker Voice Activity Detection with Transformers and Its Integration with End-to-End Neural Diarization](https://mlsanity.com/paper/2208.13085/) (2022)
- [The Volcspeech system for the ICASSP 2022 multi-channel multi-party meeting transcription challenge](https://mlsanity.com/paper/2202.04261/) (2022)
- [SVVAD: Personal Voice Activity Detection for Speaker Verification](https://mlsanity.com/paper/2305.19581/) (2023)
- [TSUP Speaker Diarization System for Conversational Short-phrase Speaker Diarization Challenge](https://mlsanity.com/paper/2210.14653/) (2022)

## Abstract (arXiv)

This paper describes the ByteDance speaker diarization system for the fourth track of the VoxCeleb Speaker Recognition Challenge 2021 (VoxSRC-21). The VoxSRC-21 provides both the dev set and test set of VoxConverse for use in validation and a standalone test set for evaluation. We first collect the duration and signal-to-noise ratio (SNR) of all audio and find that the distribution of the VoxConverse's test set and the VoxSRC-21's test set is more closer. Our system consists of voice active detection (VAD), speaker embedding extraction, spectral clustering followed by a re-clustering step based on agglomerative hierarchical clustering (AHC) and overlapped speech detection and handling. Finally, we integrate systems with different time scales using DOVER-Lap. Our best system achieves 5.15% of the diarization error rate (DER) on evaluation set, ranking the second at the diarization track of the challenge.