Res2TCNGuard / meta.yaml
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system:
name: "Res2TCNGuard"
slug: "res2tcnguard"
description: >
TCN-based anti-spoofing countermeasure: sinc-convolution front-end, Res2Net
encoder, and dual temporal convolutional networks. ASVspoof2019 LA
pretrained, FP32, deterministic first-64600-sample window (no random crop).
code: "https://github.com/lab260ru/Res2TCNGuard"
checkpoint: "https://huggingface.co/SpeechAntiSpoofingBenchmarks/Res2TCNGuard/blob/523ef915d798df3deee2be4fd06af7e1965ede14/best_1.495.pth"
params_millions: 0.172102
paper:
arxiv_id: "10.48084/etasr.8906"
url: "https://etasr.com/index.php/ETASR/article/view/8906"
bibtex: |
@article{Borodin_Kudryavtsev_Mkrtchian_Gorodnichev_2024,
place={Greece},
title={Capsule-based and TCN-based Approaches for Spoofing Detection in Voice Biometry},
volume={14},
number={6},
url={https://etasr.com/index.php/ETASR/article/view/8906},
DOI={10.48084/etasr.8906},
journal={Engineering, Technology & Applied Science Research},
author={Borodin, Kirill and Kudryavtsev, Vasiliy and Mkrtchian, Grach and Gorodnichev, Mikhail},
year={2024},
month={Dec.},
pages={18409--18414}
}
notes: "Deterministic first-64600-sample window (no random crop)."