  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.
