Add AASIST-L scores for HABLA

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/HABLA
+  revision: 520797e46fdeb1f3a3765664a6a4e25b509c72f5
+  split: test
+scores:
+  eer_percent: 34.84310344827586
+  n_trials: 80816
+  n_skipped: 0
+artifact:
+  scores_url: https://huggingface.co/SpeechAntiSpoofingBenchmarks/AASIST-L/resolve/4ffd41b02b1cc50a5f98a7eff645990710bc08de/.eval_results/SpeechAntiSpoofingBenchmarks/HABLA/scores.txt
+  scores_sha256: df55dad5046efe1a4c717a28c76383309b57550548b8dda3849d782e45e1ee3d
+  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).