submissions: add whisper-mfcc-mesonet (#9)

- submissions: add whisper-mfcc-mesonet (1ef7f0c97b65027fc89ef70133f5c98791b87ed0)
- fill reproduction (match: scoring) for whisper-mfcc-mesonet (eb8d124dc9901b91ca0e23f8aae441bb08f5818b)

submissions/whisper-mfcc-mesonet.yaml

@@ -0,0 +1,49 @@
+schema_version: 4
+system:
+  name: Whisper-MFCC-MesoNet
+  slug: whisper-mfcc-mesonet
+  description: '(Whisper + MFCC) MesoNet anti-spoofing countermeasure: a Whisper tiny.en
+    audio encoder front-end concatenated (2 channels) with an MFCC+Δ+ΔΔ front-end,
+    feeding a MesoInception4 classifier. Whisper encoder fine-tuned end-to-end. FP32.
+    Upstream eval pipeline reproduced: sox silence-trim (silence 1 0.2 1% -1 0.2 1%)
+    then a 30 s (480000-sample) repeat-pad window. This is the best MesoNet configuration
+    from the paper.
+
+    '
+  code: https://github.com/piotrkawa/deepfake-whisper-features
+  checkpoint: https://huggingface.co/SpeechAntiSpoofingBenchmarks/WhisperMFCCMesoNet
+  paper:
+    arxiv_id: '2306.01428'
+    url: https://arxiv.org/abs/2306.01428
+    bibtex: "@inproceedings{kawa23b_interspeech,\n  title     = {Improved DeepFake\
+      \ Detection Using Whisper Features},\n  author    = {Piotr Kawa and Marcin Plata\
+      \ and Micha{\\l} Czuba and Piotr Szyma{\\'n}ski and Piotr Syga},\n  year   \
+      \   = {2023},\n  booktitle = {Proc. INTERSPEECH 2023},\n  pages     = {4009--4013},\n\
+      \  doi       = {10.21437/Interspeech.2023-1537},\n}\n"
+  params_millions: 7.660881
+dataset:
+  id: SpeechAntiSpoofingBenchmarks/CFAD
+  revision: 0713bfc413326170ec52cfdb4ae9cbd546d38f7a
+  split: test
+scores:
+  eer_percent: 31.934854040668604
+  n_trials: 62999
+  n_skipped: 0
+artifact:
+  scores_url: https://huggingface.co/SpeechAntiSpoofingBenchmarks/WhisperMFCCMesoNet/resolve/8dac50082c1b98b0c2825c61d507b67a3744c236/.eval_results/SpeechAntiSpoofingBenchmarks/CFAD/scores.txt
+  scores_sha256: 6a62d2d8a63e51052b1f40454709670abd3c6fdfc3089a5eb6154978fa06a774
+  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: 'Fine-tuned Whisper+MFCC MesoNet (best MesoNet config from the paper). Reproduces
+  the paper''s In-the-Wild EER (26.72%) to within 0.01 pp with the upstream sox silence-trim
+  + 30 s repeat-pad preprocessing.
+
+  '