论文标题

Voxsrc 2020:第二个Voxceleb扬声器识别挑战

VoxSRC 2020: The Second VoxCeleb Speaker Recognition Challenge

论文作者

Nagrani, Arsha, Chung, Joon Son, Huh, Jaesung, Brown, Andrew, Coto, Ernesto, Xie, Weidi, McLaren, Mitchell, Reynolds, Douglas A, Zisserman, Andrew

论文摘要

我们与Interspeech 2020结合使用了Voxceleb扬声器识别挑战的第二部分。这一挑战的目的是评估当前的说话者识别技术能够在野外或“野生”数据中或“无约束”中识别说话者的能力。它由:(i)YouTube视频中的公开发言人识别和诊断数据集以及地面真相注释和标准化评估软件; (ii)在Interspeech 2020举行的虚拟公共挑战和研讨会。本文概述了挑战,并描述了基本线,所使用的方法和结果。最后,我们讨论了挑战第一部分的进展。

We held the second installment of the VoxCeleb Speaker Recognition Challenge in conjunction with Interspeech 2020. The goal of this challenge was to assess how well current speaker recognition technology is able to diarise and recognize speakers in unconstrained or `in the wild' data. It consisted of: (i) a publicly available speaker recognition and diarisation dataset from YouTube videos together with ground truth annotation and standardised evaluation software; and (ii) a virtual public challenge and workshop held at Interspeech 2020. This paper outlines the challenge, and describes the baselines, methods used, and results. We conclude with a discussion of the progress over the first installment of the challenge.

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