The Phonexia VoxCeleb Speaker Recognition Challenge 2021 System Description

• URL: http://arxiv.org/abs/2109.02052v3
• Date: Wed, 8 Sep 2021 08:37:51 GMT
• Title: The Phonexia VoxCeleb Speaker Recognition Challenge 2021 System Description
• Authors: Josef Slav\'i\v{c}ek and Albert Swart and Michal Kl\v{c}o and Niko Br\"ummer
• Abstract summary: We describe the Phonexia submission for the VoxCeleb Speaker Recognition Challenge 2021 (VoxSRC-21) in the unsupervised speaker verification track. An embedding extractor was bootstrapped using momentum contrastive learning, with input augmentations as the only source of supervision. A score fusion was done, by averaging the zt-normalized cosine scores of five different embedding extractors.
• Score: 1.3687617973585977
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We describe the Phonexia submission for the VoxCeleb Speaker Recognition Challenge 2021 (VoxSRC-21) in the unsupervised speaker verification track. Our solution was very similar to IDLab's winning submission for VoxSRC-20. An embedding extractor was bootstrapped using momentum contrastive learning, with input augmentations as the only source of supervision. This was followed by several iterations of clustering to assign pseudo-speaker labels that were then used for supervised embedding extractor training. Finally, a score fusion was done, by averaging the zt-normalized cosine scores of five different embedding extractors. We briefly also describe unsuccessful solutions involving i-vectors instead of DNN embeddings and PLDA instead of cosine scoring.

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