submissions: add aasist3

submissions/aasist3.yaml

@@ -0,0 +1,58 @@
+schema_version: 4
+system:
+  name: AASIST3
+  slug: aasist3
+  description: 'KAN-enhanced AASIST speech deepfake detector with a wav2vec 2.0 (XLS-R-53)
+    self-supervised front-end. SSL features are projected to 128-d through a Kolmogorov-Arnold
+    (KAN) bridge, processed by a RawNet2-style residual encoder and spectro-temporal
+    graph-attention layers, and classified by a four-branch inference head with a
+    KAN output layer. ASVspoof 2024 Challenge system; the published lab260/AASIST3
+    checkpoint (note: these weights differ from the paper results). FP32, preemphasis
+    (0.97), deterministic first-64600-sample window (no random crop). score = output
+    logit for class 1 (bona fide).
+
+    '
+  code: https://github.com/mtuciru/AASIST3
+  checkpoint: https://huggingface.co/lab260/AASIST3
+  paper:
+    arxiv_id: '2408.17352'
+    url: https://arxiv.org/abs/2408.17352
+    bibtex: "@inproceedings{borodin24_asvspoof,\n  title={AASIST3: KAN-enhanced AASIST\
+      \ speech deepfake detection using SSL features and additional regularization\
+      \ for the ASVspoof 2024 Challenge},\n  author={Borodin, Kirill and Kudryavtsev,\
+      \ Vasiliy and Korzh, Dmitrii and Efimenko, Alexey and Mkrtchian, Grach and Gorodnichev,\
+      \ Mikhail and Rogov, Oleg Y.},\n  booktitle={The Automatic Speaker Verification\
+      \ Spoofing Countermeasures Workshop (ASVspoof 2024)},\n  pages={48--55},\n \
+      \ year={2024},\n  doi={10.21437/ASVspoof.2024-8}\n}\n"
+  params_millions: 321.7495
+dataset:
+  id: SpeechAntiSpoofingBenchmarks/CFAD
+  revision: cab5d325b83b412d2e81fcf4a90b6dbab54b991f
+  split: test
+scores:
+  eer_percent: 33.12619047619047
+  n_trials: 62999
+  n_skipped: 0
+artifact:
+  scores_url: https://huggingface.co/lab260/AASIST3/resolve/318479ea6652f29efedefd512a8dc07738147d63/.eval_results/SpeechAntiSpoofingBenchmarks/CFAD/scores.txt
+  scores_sha256: 4f4c8a38cc960a15511eba3bdd1c57be55e85286adeddf172b89006cd6b3b2fe
+  bench_version: speech-spoof-bench==0.3.4
+reproduction:
+  reproduced_by: SpeechAntiSpoofingBenchmarks
+  reproduced_at: '2026-06-08'
+  reproduced_bench_version: speech-spoof-bench==0.3.4
+  match: scoring
+submitter:
+  hf_username: korallll
+  contact: k.n.borodin@mtuci.ru
+submitted_at: '2026-06-08'
+notes: 'AASIST3 (KAN-enhanced AASIST + wav2vec 2.0 XLS-R-53 SSL front-end) from mtuciru/AASIST3,
+  weights from lab260/AASIST3 (model.safetensors, self-contained incl. the SSL encoder).
+  Loaded via PyTorchModelHubMixin.from_pretrained; the XLS-R architecture is built
+  from the wav2vec2-large-xlsr-53 config then every weight is overwritten by the checkpoint.
+  Preemphasis (0.97) applied to the full waveform before a deterministic first-64600-sample
+  window, matching the source datasets/generic.py eval pipeline. score = logit for
+  class 1 (bona fide); higher = more bona fide (source label map bonafide=1, validation
+  uses outputs[:, 1]).
+
+  '