This paper introduces the third DIHARD challenge, the third 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 two tracks evaluating diarization performance when starting from a reference speech segmentation (track 1) and diarization from raw audio scratch (track 2). We describe the task, metrics, datasets, and evaluation protocol.

翻译：本文介绍了第三次DIHARD挑战,这是一系列发言方对称挑战中的第三个挑战,其目的是提高对称系统的稳健性,使之与记录设备、噪音条件和对话领域的差异相适应,挑战包括从参考语音分解(第1轨)和从原始音频抓取的对称(第2轨)开始评估对称性表现的两条轨道,我们描述了任务、指标、数据集和评价程序。