Add W2V2-AASIST scores for DECRO

submissions/w2v2-aasist.yaml

@@ -0,0 +1,44 @@
+schema_version: 4
+system:
+  name: W2V2-AASIST
+  slug: w2v2-aasist
+  description: wav2vec 2.0 (XLS-R 300M) self-supervised front-end fine-tuned end-to-end with an AASIST spectro-temporal graph-attention
+    back-end for speech anti-spoofing. The XLS-R features are projected to 128-d, max-pooled, and fed through a RawNet2-style
+    residual encoder and heterogeneous stacking graph-attention layers. Official TakHemlata/SSL_Anti-spoofing LA checkpoint
+    (LA_model.pth), trained on ASVspoof2019 LA with RawBoost augmentation, FP32, deterministic first-64600-sample window (no
+    random crop).
+  code: https://github.com/TakHemlata/SSL_Anti-spoofing
+  checkpoint: https://huggingface.co/SpeechAntiSpoofingBenchmarks/W2V2-AASIST
+  params_millions: 317.8378
+  paper:
+    arxiv_id: '2202.12233'
+    url: https://arxiv.org/abs/2202.12233
+    bibtex: "@inproceedings{tak2022automatic,\n  title={Automatic speaker verification spoofing and deepfake detection using\
+      \ wav2vec 2.0 and data augmentation},\n  author={Tak, Hemlata and Todisco, Massimiliano and Wang, Xin and Jung, Jee-weon\
+      \ and Yamagishi, Junichi and Evans, Nicholas},\n  booktitle={The Speaker and Language Recognition Workshop (Odyssey\
+      \ 2022)},\n  pages={112--119},\n  year={2022}\n}\n"
+dataset:
+  id: SpeechAntiSpoofingBenchmarks/DECRO
+  revision: bb6df2524eadaab6aa6a2366a41a2a5fe1e4104d
+  split: test
+scores:
+  eer_percent: 9.572731637061931
+  n_trials: 37314
+  n_skipped: 0
+artifact:
+  scores_url: https://huggingface.co/SpeechAntiSpoofingBenchmarks/W2V2-AASIST/resolve/e22d2e6af8e8245c2ac1f2810e4c913bf4368865/.eval_results/SpeechAntiSpoofingBenchmarks/DECRO/scores.txt
+  scores_sha256: 06908e4d92bba6ef92924d400f1ab86faa82dc0b2e9e0578f9fbc549c7b36f68
+  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 + AASIST back-end ("W2V2-AASIST"), the LA variant (LA_model.pth) from TakHemlata/SSL_Anti-spoofing.
+  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. score
+  = output logit for class 1 (bona fide); higher = more bona fide.