  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.
