| 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. |
|
|
