# Deepfake Audio Detector

## Description
Deepfake Audio Detector is a CLI tool that uses pre-trained speech analysis models to detect potential deepfake audio clips. It analyzes frequency artifacts, temporal inconsistencies, and synthetic noise patterns to determine the authenticity of audio files. This tool is particularly useful for verifying AI-generated interviews and podcasts.

## Installation

1. Clone the repository:
   ```bash
   git clone https://github.com/your-repo/deepfake_audio_detector.git
   cd deepfake_audio_detector
   ```

2. Install dependencies:
   ```bash
   pip install -r requirements.txt
   ```

## Usage

To analyze an audio file:

```bash
python deepfake_audio_detector.py --input sample_audio.mp3
```

Example output:
```
Confidence Score: 75.32%
Likelihood: Deepfake
```

## Features
- Detects deepfake audio artifacts using AI
- Supports multiple audio file formats (e.g., mp3, wav)
- Provides a confidence score for detection

## Limitations
- Currently, the deepfake detection logic is a placeholder. Replace it with a pre-trained AI model for real-world use.

## License
MIT License