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arXiv · 2011.01518

ShaneRun System Description to VoxCeleb Speaker Recognition Challenge 2020

Shen Chen
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Abstract

In this report, we describe the submission of ShaneRun's team to the VoxCeleb Speaker Recognition Challenge (VoxSRC) 2020. We use ResNet-34 as encoder to extract the speaker embeddings, which is referenced from the open-source voxceleb-trainer. We also provide a simple method to implement optimum fusion using t-SNE normalized distance of testing utterance pairs instead of original negative Euclidean distance from the encoder. The final submitted system got 0.3098 minDCF and 5.076 % ERR for Fixed data track, which outperformed the baseline by 1.3 % minDCF and 2.2 % ERR respectively.

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Shen Chen. 2020-11-03. ShaneRun System Description to VoxCeleb Speaker Recognition Challenge 2020. https://arxiv.org/abs/2011.01518

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