Update README.md

README.md

@@ -195,12 +195,12 @@ Results shown below can be reproduced using scripts provided in our [GitHub repo
 
 | Test Database        | ROC AUC | Accuracy | Precision | Recall | F1-score | FPR   | FNR   | EER (%) @ Threshold |
 |----------------------|---------|----------|-----------|--------|----------|-------|-------|----------------------|
-| ADD2023              | 0.752   | 0.591    | 0.867     | 0.528  | 0.656    | 0.230 | 0.472 | 35.34 @ 0.2385       |
-| DeepVoice            | 0.932   | 0.753    | 0.322     | 0.915  | 0.477    | 0.270 | 0.085 | 14.87 @ 0.7576       |
-| FakeOrReal           | 0.994   | 0.826    | 0.999     | 0.644  | 0.783    | 0.001 | 0.356 | 3.67 @ 0.0338        |
-| FakeOrReal-norm      | 0.910   | 0.784    | 0.991     | 0.563  | 0.718    | 0.005 | 0.437 | 15.52 @ 0.0760       |
+| ADD2023              | 0.752   | 0.591    | 0.867     | 0.528  | 0.656    | 0.230 | 0.472 | 35.34 @ 0.2345       |
+| DeepVoice            | 0.932   | 0.753    | 0.322     | 0.915  | 0.477    | 0.270 | 0.085 | 14.84 @ 0.7575       |
+| FakeOrReal           | 0.994   | 0.826    | 0.999     | 0.644  | 0.783    | 0.001 | 0.356 | 3.67 @ 0.0336        |
+| FakeOrReal-norm      | 0.910   | 0.784    | 0.991     | 0.563  | 0.718    | 0.005 | 0.437 | 15.56 @ 0.0758       |
 | In-the-Wild          | 0.919   | 0.733    | 0.969     | 0.594  | 0.737    | 0.032 | 0.406 | 17.99 @ 0.0841       |
-| Deepfake-Eval-2024  | 0.498   | 0.595    | 0.646     | 0.842  | 0.731    | 0.871 | 0.158 | 50.15 @ 0.5194       |
+| Deepfake-Eval-2024  | 0.507   | 0.560    | 0.623     | 0.744  | 0.678    | 0.743 | 0.257 | 50.99 @ 0.8029       |
 
 
 You can also fine-tune this model on a specific database, the corresponding code is provided in our [GitHub repository](https://github.com/nii-yamagishilab/AntiDeepfake). Fine-tuning will follow a similar process to training a new model, except that model weights will be initialized as AntiDeepfake checkpoints.
@@ -243,7 +243,7 @@ Below is a breakdown of the training set used for post-training of speech SSL mo
 | LibriTTS-R           | en               | 0              | 583.15      |
 | LibriTTS-Vocoded     | en               | 0              | 2345.14     |
 | LJSpeech             | en               | 23.92          | 0           |
-| MLADD                | 38 languages     | 0              | 377.96      |
+| MLAAD                | 38 languages     | 0              | 377.96      |
 | MLS                  | 8 languages      | 50558.11       | 0           |
 | SpoofCeleb           | Multilingual     | 173.00         | 1916.20     |
 | VoiceMOS             | en               | 0              | 448.44      |