Add AASIST-L submission for PyAra

submissions/aasist-l.yaml

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+schema_version: 4
+system:
+  name: AASIST-L
+  slug: aasist-l
+  description: 'AASIST-L: the lightweight variant of AASIST (audio anti-spoofing using integrated spectro-temporal
+    graph attention networks). Same architecture as AASIST — sinc-convolution front-end, RawNet2-style
+    residual encoder, and heterogeneous stacking graph attention over spectral and temporal sub-graphs
+    with a learnable readout — but with a narrower residual stack and graph dimensions (~85k params vs
+    AASIST''s ~298k). Official clovaai/aasist ASVspoof2019 LA pretrained checkpoint, FP32, deterministic
+    first-64600-sample window (no random crop).'
+  code: https://github.com/clovaai/aasist
+  checkpoint: https://huggingface.co/SpeechAntiSpoofingBenchmarks/AASIST-L/blob/e4185b270ec20077c918e06a45093717a1bd5e30/AASIST-L.pth
+  params_millions: 0.085306
+  paper:
+    arxiv_id: '2110.01200'
+    url: https://arxiv.org/abs/2110.01200
+    bibtex: "@inproceedings{jung2022aasist,\n  title={{AASIST}: Audio Anti-Spoofing Using Integrated Spectro-Temporal\
+      \ Graph Attention Networks},\n  author={Jung, Jee-weon and Heo, Hee-Soo and Tak, Hemlata and Shim,\
+      \ Hye-jin and Chung, Joon Son and Lee, Bong-Jin and Yu, Ha-Jin and Evans, Nicholas},\n  booktitle={ICASSP\
+      \ 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},\n\
+      \  pages={6367--6371},\n  year={2022},\n  organization={IEEE}\n}\n"
+dataset:
+  id: SpeechAntiSpoofingBenchmarks/PyAra
+  revision: 43f03384ee9ad701a64e0baaa531c8aedd724cd8
+  split: test
+scores:
+  eer_percent: 30.784284413519426
+  n_trials: 201778
+  n_skipped: 0
+artifact:
+  scores_url: https://huggingface.co/SpeechAntiSpoofingBenchmarks/AASIST-L/resolve/18b8d33d9ce4bdc6f3de1c0fba3139bc3ad2013a/.eval_results/SpeechAntiSpoofingBenchmarks/PyAra/scores.txt
+  scores_sha256: 15033d1ad154e0540f8dc29d53cf7c30a065c5503fecceac99b1f273434e2546
+  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: Lightweight AASIST-L variant (not the full AASIST). Same _net.py Model class as AASIST; differs
+  only in model_config (filts [..,[32,24],[24,24]], gat_dims [24,32], pool_ratios [0.4,0.5,0.7,0.5]) and
+  checkpoint. Deterministic first-64600-sample window (no random crop), matching clovaai/aasist data_utils.pad()
+  used at eval. Checkpoint mirrored to SpeechAntiSpoofingBenchmarks/AASIST-L (pinned at publish).