Datasets:
submissions: add rescapsguard
Browse files
submissions/rescapsguard.yaml
ADDED
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schema_version: 4
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system:
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name: ResCapsGuard
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slug: rescapsguard
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description: 'Capsule-based anti-spoofing countermeasure: sinc-convolution front-end,
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Res2Net-style encoder, primary capsules, and dynamic routing to two output capsules
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(bona fide vs. spoof). ASVspoof2019 LA pretrained, FP32, deterministic first-64600-sample
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window (no random crop).
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'
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code: https://github.com/lab260ru/ResCapsGuard
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checkpoint: https://huggingface.co/SpeechAntiSpoofingBenchmarks/ResCapsGuard/blob/4f7f2bc745cb3980f9fd3c29811afe0744a28edd/new_capsules_changed_sinc_layer.pth
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paper:
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arxiv_id: 10.48084/etasr.8906
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url: https://etasr.com/index.php/ETASR/article/view/8906
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bibtex: "@article{Borodin_Kudryavtsev_Mkrtchian_Gorodnichev_2024,\n place={Greece},\n\
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\ title={Capsule-based and TCN-based Approaches for Spoofing Detection in Voice\
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\ Biometry},\n volume={14},\n number={6},\n url={https://etasr.com/index.php/ETASR/article/view/8906},\n\
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\ DOI={10.48084/etasr.8906},\n journal={Engineering, Technology & Applied\
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\ Science Research},\n author={Borodin, Kirill and Kudryavtsev, Vasiliy and\
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\ Mkrtchian, Grach and Gorodnichev, Mikhail},\n year={2024},\n month={Dec.},\n\
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\ pages={18409--18414}\n}\n"
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params_millions: 1.606664
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dataset:
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id: SpeechAntiSpoofingBenchmarks/CFAD
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revision: a7a016fb0773761ee79d646fe467aaf1a7c53649
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split: test
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scores:
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eer_percent: 37.83095238095238
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n_trials: 62999
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n_skipped: 0
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artifact:
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scores_url: https://huggingface.co/SpeechAntiSpoofingBenchmarks/ResCapsGuard/resolve/3ff17bc878b85daa46d87336bfedddc3d714ffcb/.eval_results/SpeechAntiSpoofingBenchmarks/CFAD/scores.txt
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scores_sha256: f2dafdbee2ae420f6077f9495d8831ed2939a50405f303f7602a67382ffaa29d
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bench_version: speech-spoof-bench==0.3.4
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reproduction: {}
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submitter:
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hf_username: korallll
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contact: k.n.borodin@mtuci.ru
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submitted_at: '2026-06-08'
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notes: Deterministic first-64600-sample window (no random crop).
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