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VoxSRC 2022: The Fourth VoxCeleb Speaker Recognition Challenge

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arxiv 2302.10248 v2 pith:WS2LWDOD submitted 2023-02-20 cs.SD cs.LGeess.AS

Jaesung Huh , Andrew Brown , Jee-weon Jung , Joon Son Chung , Arsha Nagrani , Daniel Garcia-Romero , Andrew Zisserman This is my paper · ORCID
classification cs.SDcs.LGeess.AS
keywords challengerecognitionspeakerheldinterspeechvoxcelebvoxsrc-22along
verification ladder T0 review T1 audit T2 compute T3 formal
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This paper summarises the findings from the VoxCeleb Speaker Recognition Challenge 2022 (VoxSRC-22), which was held in conjunction with INTERSPEECH 2022. The goal of this challenge was to evaluate how well state-of-the-art speaker recognition systems can diarise and recognise speakers from speech obtained "in the wild". The challenge consisted of: (i) the provision of publicly available speaker recognition and diarisation data from YouTube videos together with ground truth annotation and standardised evaluation software; and (ii) a public challenge and hybrid workshop held at INTERSPEECH 2022. We describe the four tracks of our challenge along with the baselines, methods, and results. We conclude with a discussion on the new domain-transfer focus of VoxSRC-22, and on the progression of the challenge from the previous three editions.

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  1. Generic Speech Enhancement with Self-Supervised Representation Space Loss

    eess.AS 2025-07 conditional novelty 5.0 of 10

    A speech enhancement training loss based on self-supervised model features improves ASR, speaker verification, intent classification, and Whisper ASR while keeping perceptual quality.

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