Add mms-300m-antideepfake submission for EmoFake_test (EER 1.60%, reproduced: scoring)

submissions/mms-300m-antideepfake.yaml

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+schema_version: 4
+system:
+  name: MMS-300M-AntiDeepfake
+  slug: mms-300m-antideepfake
+  description: 'AntiDeepfake detector (MMS-300M backbone): a self-supervised speech
+    foundation model post-trained for deepfake/spoof detection, with an AdaptiveAvgPool1d
+    + single fully-connected layer head over the SSL features. Released by nii-yamagishilab
+    (arXiv:2506.21090). Trained with RawBoost data augmentation (default variant).
+    Checkpoint copied bit-exactly from nii-yamagishilab/mms-300m-anti-deepfake. Evaluated
+    here with a deterministic first-4 s window and batching (NOT the paper''s whole-utterance
+    protocol).
+
+    '
+  code: https://github.com/nii-yamagishilab/AntiDeepfake
+  checkpoint: https://huggingface.co/SpeechAntiSpoofingBenchmarks/MMS-300M-AntiDeepfake
+  paper:
+    arxiv_id: '2506.21090'
+    url: https://arxiv.org/abs/2506.21090
+    bibtex: "@article{ge2025posttraining,\n  title={Post-training for Deepfake Speech\
+      \ Detection},\n  author={Ge, Wanying and Wang, Xin and Kawahara, Tomoki and\
+      \ Yamamoto, Yuto and Delgado, Hector and Todisco, Massimiliano and Evans, Nicholas\
+      \ and Yamagishi, Junichi},\n  journal={arXiv preprint arXiv:2506.21090},\n \
+      \ year={2025}\n}\n"
+  params_millions: 315.0
+dataset:
+  id: SpeechAntiSpoofingBenchmarks/EmoFake_test
+  revision: b9cd4b93c615bd4fd8750a6c18591635e954f94c
+  split: test
+scores:
+  eer_percent: 1.6
+  n_trials: 17500
+  n_skipped: 0
+artifact:
+  scores_url: https://huggingface.co/SpeechAntiSpoofingBenchmarks/MMS-300M-AntiDeepfake/resolve/e566250ec64726784a3956d1deac2626c52e6921/.eval_results/SpeechAntiSpoofingBenchmarks/EmoFake_test/scores.txt
+  scores_sha256: 19df43cb5f16dc465d5959709ef1e9a40493d73c7f816781bdb2d65b71839814
+  bench_version: speech-spoof-bench==0.4.1
+reproduction:
+  reproduced_by: SpeechAntiSpoofingBenchmarks
+  reproduced_at: '2026-06-24'
+  reproduced_bench_version: speech-spoof-bench==0.4.1
+  match: scoring
+submitter:
+  hf_username: korallll
+  contact: k.n.borodin@mtuci.ru
+submitted_at: '2026-06-24'
+notes: 'score = output logit for class 1 (real / bona fide); higher = more bona fide.
+  Backbone built from the source fairseq config (mms_300m); the released model.safetensors
+  overwrites every weight (220-key exact match family-wide). Input: fixed first 64000
+  samples (4.0 s @ 16 kHz), tile-repeated if shorter, per-utterance layer_norm; no
+  resampling. Checkpoint license: CC BY-NC-SA 4.0. STRICTLY PROHIBITED on the model''s
+  in-domain corpora (see README); Arena runs ArAD + In-the-Wild only.
+
+  '