  This paper introduces the second DIHARD challenge, the second in a series of
speaker diarization challenges intended to improve the robustness of
diarization systems to variation in recording equipment, noise conditions, and
conversational domain. The challenge comprises four tracks evaluating
diarization performance under two input conditions (single channel vs.
multi-channel) and two segmentation conditions (diarization from a reference
speech segmentation vs. diarization from scratch). In order to prevent
participants from overtuning to a particular combination of recording
conditions and conversational domain, recordings are drawn from a variety of
sources ranging from read audiobooks to meeting speech, to child language
acquisition recordings, to dinner parties, to web video. We describe the task
and metrics, challenge design, datasets, and baseline systems for speech
enhancement, speech activity detection, and diarization.
