---
license: mit
datasets:
- fixie-ai/librispeech_asr
language:
- en
base_model:
- facebook/wav2vec2-base
pipeline_tag: voice-activity-detection
---
# Voice Detection AI - Real vs AI Audio Classifier

### **Model Overview**
This model is a fine-tuned Wav2Vec2-based audio classifier capable of distinguishing between **real human voices** and **AI-generated voices**. It has been trained on a dataset containing samples from various TTS models and real human audio recordings.

---

### **Model Details**
- **Architecture:** Wav2Vec2ForSequenceClassification
- **Fine-tuned on:** Custom dataset with real and AI-generated audio
- **Classes:**
  1. Real Human Voice
  2. AI-generated (e.g., Melgan, DiffWave, etc.)
- **Input Requirements:**
  - Audio format: `.wav`, `.mp3`, etc.
  - Sample rate: 16kHz
  - Max duration: 10 seconds (longer audios are truncated, shorter ones are padded)

---

### **Performance**
- **Validation Accuracy:** 99.8%
- **Robustness:** Successfully classifies across multiple AI-generation models.
- **Limitations:** Struggles with certain unseen AI-generation models (e.g., ElevenLabs).

---

### **How to Use**

#### **1. Install Dependencies**
Make sure you have `transformers` and `torch` installed:
```bash
pip install transformers torch torchaudio