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This paper provides a detailed description of the Hitachi-JHU system that wassubmitted to the Third DIHARD Speech Diarization Challenge. The system outputsthe ensemble results of the five subsystems: two x-vector-based subsystems, twoend-to-end neural diarization-based subsystems, and one hybrid subsystem. Werefine each system and all five subsystems become competitive andcomplementary. After the DOVER-Lap based system combination, it achieveddiarization error rates of 11.58 % and 14.09 % in Track 1 full and core, and16.94 % and 20.01 % in Track 2 full and core, respectively. With their results,we won second place in all the tasks of the challenge.

The Hitachi-JHU DIHARD III System: Competitive End-to-End Neural Diarization and X-Vector Clustering Systems Combined by DOVER-Lap