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| license: apache-2.0 |
| title: DeepFense |
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| emoji: 🛡️ |
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| # 🛡️ DeepFense: Modular Deepfake Audio Detection 🎙️ |
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| 👋 **Welcome to the official Hugging Face home of the DeepFense Framework!** |
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| We are the **DeepFense Team**. Our mission is to provide the research community with a robust, modular, and configuration-driven framework for building, training, and evaluating state-of-the-art audio deepfake detectors. |
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| ### 🚀 The Framework at a Glance |
| DeepFense simplifies audio forensics by decoupling frontends, backends, and loss functions. Whether you are a researcher or a developer, you can swap components via simple YAML configs—no code changes required. |
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| * **Modular Design:** Mix-and-match components like `WavLM`, `HuBERT`, or `EAT` (Frontends) with `AASIST`, `Nes2Net`, or `ECAPA-TDNN` (Backends). |
| * **Hugging Face Native:** Access **455+ pretrained models** and **12 benchmark datasets** (ASVSpoof19, CompSpoof, etc.) directly through our CLI. |
| * **Reproducible Research:** Automatic tracking of EER, minDCF, and F1 metrics with built-in WandB logging. |
| * **Rich Augmentations:** Built-in RawBoost, RIR, Codec, and more to ensure model robustness. |
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| ### 🛠️ Quick Start |
| Get started with DeepFense in under 5 minutes: |
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| ```bash |
| # Install the framework |
| pip install deepfense |
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| # Download a specific model & dataset |
| deepfense download dataset CompSpoof |
| deepfense download model ASV19_WavLM_Nes2Net_NoAug_Seed42 |
| ``` |
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| ### 🛠️ Small Tutorial |
| [](https://colab.research.google.com/drive/1bdTl0GdYybCYQX8nDioT_Z-XIpwZFRPb?usp=sharing) |
