UNISOUND System for VoxCeleb Speaker Recognition Challenge 2023
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Abstract (arXiv)
This report describes the UNISOUND submission for Track1 and Track2 of VoxCeleb Speaker Recognition Challenge 2023 (VoxSRC 2023). We submit the same system on Track 1 and Track 2, which is trained with only VoxCeleb2-dev. Large-scale ResNet and RepVGG architectures are developed for the challenge. We propose a consistency-aware score calibration method, which leverages the stability of audio voiceprints in similarity score by a Consistency Measure Factor (CMF). CMF brings a huge performance boost in this challenge. Our final system is a fusion of six models and achieves the first place in Track 1 and second place in Track 2 of VoxSRC 2023. The minDCF of our submission is 0.0855 and the EER is 1.5880%.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 10 of its 16 references that are in the map. First posted on arXiv 24 Aug 2023.
Builds on
10 of 16 references.
References · 10
- 2015Deep Residual Learning for Image Recognitioncited by 52,096
- 2018CosFace: Large Margin Cosine Loss for Deep Face Recognitioncited by 971
- 2018VoxCeleb2: Deep Speaker Recognitioncited by 875
- 2021RepVGG: Making VGG-style ConvNets Great Againcited by 522
- 2015MUSAN: A Music, Speech, and Noise Corpuscited by 425
- 2018Additive Margin Softmax for Face Verificationcited by 278
- 2021The SpeakIn System for VoxCeleb Speaker Recognition Challange 2021cited by 20
- 2020The IDLAB VoxCeleb Speaker Recognition Challenge 2020 System Descriptioncited by 17
- 2020The DKU-DukeECE Systems for VoxCeleb Speaker Recognition Challenge 2020cited by 10
- 2021Multi-query multi-head attention pooling and Inter-topK penalty for speaker verificationcited by 9
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Citing papers per year: 2024: 3.
3 papers.