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