  This system description describes our submission system to the Third DIHARD
Speech Diarization Challenge. Besides the traditional clustering based system,
the innovation of our system lies in the combination of various front-end
techniques to solve the diarization problem, including speech separation and
target-speaker based voice activity detection (TS-VAD), combined with iterative
data purification. We also adopted audio domain classification to design
domain-dependent processing. Finally, we performed post processing to do system
fusion and selection. Our best system achieved DERs of 11.30% in track 1 and
16.78% in track 2 on evaluation set, respectively.
