  This paper provides a detailed description of the Hitachi-JHU system that was
submitted to the Third DIHARD Speech Diarization Challenge. The system outputs
the ensemble results of the five subsystems: two x-vector-based subsystems, two
end-to-end neural diarization-based subsystems, and one hybrid subsystem. We
refine each system and all five subsystems become competitive and
complementary. After the DOVER-Lap based system combination, it achieved
diarization error rates of 11.58 % and 14.09 % in Track 1 full and core, and
16.94 % and 20.01 % in Track 2 full and core, respectively. With their results,
we won second place in all the tasks of the challenge.
