arxiv:2308.08294

The ID R&D VoxCeleb Speaker Recognition Challenge 2023 System Description

Published on Aug 16, 2023

Authors:

Nikita Torgashov ,

Abstract

A deep learning solution combining ResNets and self-supervised learning models achieved top performance in the VoxSRC-23 challenge using a combination of VoxCeleb2 and VoxTube datasets.

AI-generated summary

This report describes ID R&D team submissions for Track 2 (open) to the VoxCeleb Speaker Recognition Challenge 2023 (VoxSRC-23). Our solution is based on the fusion of deep ResNets and self-supervised learning (SSL) based models trained on a mixture of a VoxCeleb2 dataset and a large version of a VoxTube dataset. The final submission to the Track 2 achieved the first place on the VoxSRC-23 public leaderboard with a minDCF(0.05) of 0.0762 and EER of 1.30%.

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