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---
language:
- en
tags:
- audio
- audio-classification
- antispoofing
- deepfake-detection
- speech
license: other
pipeline_tag: audio-classification
---
# DF Arena 1B - Antispoofing Model
We are excited to release DF Arena 1B Universal Antispoofing model 🔥trained on traditional speech antispoofing datasets in addition to singing and environmental deepfake data.
Check out the release on [DF Arena leaderboard](https://huggingface.co/spaces/Speech-Arena-2025/Speech-DF-Arena)
# Training Data
- **ASVspoof 2019, 2021, 2023, 2024**
- **Codecfake**
- **LibriSeVoc**
- **DFADD**
- **CTRSVDD**
- **SpoofCeleb**
- **MLAAD**
- **SONAR**
- **EnvSDD**
## Usage
```python
from transformers import pipeline
import librosa
#load model
pipe = pipeline("antispoofing", model="Speech-Arena-2025/DF_Arena_1B_V_1", trust_remote_code=True, device='cuda')
audio, sr = librosa.load("sample.wav", sr=16000)
result = pipe(audio)
print(result)
# Output:
{'label': 'spoof', 'logits': [[1.5515458583831787, -1.2254822254180908]], 'score': 0.9414217472076416, 'all_scores': {'spoof': 0.9414217472076416, 'bonafide': 0.05857823044061661}}
```
# Evaluation
| Dataset | EER (%) | F1-score | Accuracy (%) |
|-------------------------|----------|-----------|---------------|
| dfadd | 0.00 | 0.9993 | 99.97 |
| add_2023_round_2 | 11.54 | 0.9188 | 88.46 |
| codecfake | 8.37 | 0.8695 | 91.63 |
| asvspoof_2021_la | 4.66 | 0.8037 | 95.34 |
| in_the_wild | 0.91 | 0.9928 | 99.10 |
| asvspoof_2019 | 1.14 | 0.9473 | 98.86 |
| add_2022_track_1 | 22.21 | 0.6678 | 77.79 |
| fake_or_real | 2.92 | 0.9711 | 97.11 |
| asvspoof_2024 | 17.25 | 0.6615 | 82.75 |
| add_2022_track_3 | 2.20 | 0.9357 | 97.80 |
| add_2023_round_1 | 5.08 | 0.9639 | 94.92 |
| librisevoc | 0.15 | 0.9958 | 99.84 |
| asvspoof_2021_df | 1.75 | 0.7577 | 98.25 |
| sonar | 1.09 | 0.9903 | 98.89 |
| Average | 5.919 | 0.8863 | 94.079 |
| Pooled | 9.52 | 0.81 | 90.47 |
## License
We use a non-commercial license which can be found [here](./LICENSE.txt)
## Contact
For questions or issues, please open an issue on the model repository or contact us at speech.arena.eval@gmail.com.
Stay tuned for upcoming versions of our models!
## Citation
If you use this model in your work, it can be cited as :
```bibtex
@misc{kulkarni_2024_df_arena_1b,
author = {Ajinkya Kulkarni and Atharva Kulkarni and Sandipana Dowerah and Matthew Magimai Doss and Tanel Alumäe},
title = {DF_Arena_1B_V_1 - Universal Audio Deepfake Detection},
year = {2025},
publisher = {Hugging Face},
url = {https://huggingface.co/Speech-Arena-2025/DF_Arena_1B_V_1/}
}
``` |