Add Nes2Net submission for PyAra

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by korallll - opened
Files changed (1) hide show
  1. submissions/nes2net.yaml +48 -0
submissions/nes2net.yaml ADDED
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+ schema_version: 4
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+ system:
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+ name: Nes2Net
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+ slug: nes2net
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+ description: wav2vec 2.0 (XLS-R 300M) self-supervised front-end fine-tuned end-to-end with a Nes2Net-X
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+ (Nested Res2Net TDNN) back-end for speech anti-spoofing. The nested Res2Net structure couples multi-scale
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+ residual groups with squeeze- excitation, replacing dimensionality-reducing necks; mean temporal pooling
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+ + linear classifier. Only ~0.51M back-end params. Official Nes2Net-X single checkpoint (ASVspoof2021
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+ LA 1.73% / DF 1.65% EER as reported), trained on ASVspoof2019 LA with RawBoost, FP32, deterministic
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+ first-64600-sample window (no random crop).
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+ code: https://github.com/Liu-Tianchi/Nes2Net_ASVspoof_ITW
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+ checkpoint: https://huggingface.co/SpeechAntiSpoofingBenchmarks/Nes2Net
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+ params_millions: 317.9026
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+ paper:
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+ arxiv_id: '2504.05657'
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+ url: https://arxiv.org/abs/2504.05657
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+ bibtex: "@article{Nes2Net,\n author={Liu, Tianchi and Truong, Duc-Tuan and Das, Rohan Kumar and Lee,\
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+ \ Kong Aik and Li, Haizhou},\n journal={IEEE Transactions on Information Forensics and Security},\n\
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+ \ title={Nes2Net: A Lightweight Nested Architecture for Foundation Model Driven Speech Anti-Spoofing},\n\
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+ \ year={2025},\n volume={20},\n pages={12005--12018},\n doi={10.1109/TIFS.2025.3626963}\n}\n"
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+ dataset:
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+ id: SpeechAntiSpoofingBenchmarks/PyAra
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+ revision: 43f03384ee9ad701a64e0baaa531c8aedd724cd8
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+ split: test
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+ scores:
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+ eer_percent: 4.013155212481144
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+ n_trials: 201778
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+ n_skipped: 0
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+ artifact:
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+ scores_url: https://huggingface.co/SpeechAntiSpoofingBenchmarks/Nes2Net/resolve/e2c486f08d074d1dc74d350d8d1cdc4d5332cad6/.eval_results/SpeechAntiSpoofingBenchmarks/PyAra/scores.txt
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+ scores_sha256: 6cfd6bb6226241647bbb225d26b844ff1f6b7417836acd6717defc3cd6bc6860
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+ bench_version: speech-spoof-bench==0.3.4
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+ reproduction:
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+ reproduced_by: SpeechAntiSpoofingBenchmarks
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+ reproduced_at: '2026-06-10'
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+ reproduced_bench_version: speech-spoof-bench==0.3.4
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+ match: scoring
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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: '2026-06-10'
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+ notes: XLS-R 300M (wav2vec 2.0) front-end + Nes2Net-X back-end, the single (non-averaged) checkpoint from
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+ Liu-Tianchi/Nes2Net_ASVspoof_ITW (Nes_ratio [8,8], SE_ratio [1], pool_func 'mean', dilation 2). Architecture
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+ is built from the base xlsr2_300m.pt model config, then every weight is overwritten by the fine-tuned
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+ checkpoint. Deterministic first-64600-sample window (no random crop), matching the source data_utils_SSL.py::pad
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+ used at eval (default --test_protocol 4sec). score = output logit for class 1 (bona fide); higher =
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+ more bona fide. Back-end params ~0.51M; params_millions reports the full deployed model incl. the XLS-R
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+ front-end.