VoxSRC 2019: The first VoxCeleb Speaker Recognition Challenge

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

arXiv.org Machine Learning 

ABSTRACT The V oxCeleb Speaker Recognition Challenge 2019 aimed to assess how well current speaker recognition technology is able to identify speakers in unconstrained or'in the wild' data. It consisted of: (i) a publicly available speaker recognition dataset from Y ouTube videos together with ground truth annotation and standardised evaluation software; and (ii) a public challenge and workshop held at Interspeech 2019 in Graz, Austria. This paper outlines the challenge and provides its baselines, results and discussions. Index T erms-- speaker verification, unconstrained conditions 1. INTRODUCTION The V oxCeleb Speaker Recognition Challenge (V oxSRC) 2019 was the first of a new series of speaker recognition challenges that are intended to be hosted annually. V oxSRC 2019 consisted of: (i) a publicly available speaker recognition dataset with speech segments'in the wild', together with ground truth annotations and standardised evaluation software; and (ii) a public challenge and workshop held at Interspeech 2019 in Graz, Austria.

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