File size: 3,078 Bytes
7cae769 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 | # DeepFense Paper Scores
Canonical, reproducible score bundle for the DeepFense camera-ready paper.
**Hugging Face:** [DeepFense/prediction_scores](https://huggingface.co/datasets/DeepFense/prediction_scores)
---
## Directory layout
```
scores/
├── README.md
├── {train_recipe}/ # dataset the model was TRAINED on
│ ├── {backend}/ # AASIST | MLP | Nes2Net | TCM
│ │ └── {frontend}/ # Wav2Vec2 | HuBERT | WavLM | EAT
│ │ └── seed{2|42|240}/
│ │ └── {eval_benchmark}/ # held-out TEST set
│ │ ├── predictions.txt # per-utterance scores (TSV)
│ │ └── metrics.json # EER, ACC, F1, …
│ └── _summaries/{eval_benchmark}.json # optional cross-architecture tables
└── bias_fairness/
└── {accent|emotions|gender|language|quality}/
└── {eval_benchmark}/
└── {train_recipe}/{backend}/{frontend}/seed{N}/
└── utterances.txt # scores + subgroup metadata (TSV)
```
### Example
From checkpoint `DeepFense_ADD23_Wav2Vec2_TCM_NoAug_Seed240` evaluated on `add22_test_track1`:
```
ADD23/TCM/Wav2Vec2/seed240/add22_test_track1/predictions.txt
ADD23/TCM/Wav2Vec2/seed240/add22_test_track1/metrics.json
```
---
## Naming conventions
| Token | Canonical form | Notes |
|-------|----------------|-------|
| **Train recipe** | `ASV5`, `ASV19`, `ADD23`, `CodecFake`, `HABLA`, `PartialSpoof` | Training dataset (not the eval set). `ASV5` = trained on ASVspoof 5; do not confuse with eval `asvspoof5_test`. |
| **Frontend** | `Wav2Vec2`, `HuBERT`, `WavLM`, `EAT` | Always PascalCase; `Hubert` → `HuBERT`. |
| **Backend** | `AASIST`, `MLP`, `Nes2Net`, `TCM` | Uppercase acronym. |
| **Seed** | `seed2`, `seed42`, `seed240` | Three seeds per recipe. |
| **Eval benchmark** | lowercase snake_case | e.g. `asvspoof5_test`, `asvspoof2019_la_eval`, `mlaad_final`, `add22_test_track1`. |
### Eval benchmarks (20)
`add22_test_track1`, `add22_test_track3`, `add23_test_R1`, `add23_test_R2`, `asvspoof2019_la_eval`, `asvspoof21_df_eval`, `asvspoof21_la_eval`, `asvspoof5_test`, `codecfake_eval`, `ctrsvdd_eval`, `fakemusiccaps_eval`, `habla_test`, `itw_eval`, `mlaad_final`, `odss_test`, `partialedit_eval`, `partialspoof_eval`, `replaydf_all_eval`, `spoofceleb_eval`
---
## File formats (`.txt` / `.json` only)
### `predictions.txt` — clip-level (TSV)
```
utterance_id label score_spoof score_bonafide
LA_E_12345 0 -2.14895 3.14895
LA_T_67890 1 4.37140 -3.37140
```
- `label`: `0` = spoof, `1` = bonafide
- LLR = `score_bonafide − score_spoof`
### `metrics.json`
Per-run aggregated metrics (EER, ACC, F1, confidence intervals).
### `bias_fairness/.../utterances.txt`
Per-utterance scores with subgroup columns (gender, accent, NISQA quality, etc.).
Score columns: `score_spoof`, `score_bonafide` (renamed from legacy `class0`/`class1`).
|