trainer/README.md

🎙️ Voice Detection Model Trainer

This sub-project is dedicated to fine-tuning a custom AI Voice Detection model tailored to your specific audio samples and languages (Tamil, English, Hindi, Malayalam, Telugu).

🏗️ Architecture

• Base Model: facebook/wav2vec2-large-xlsr-53 (Multilingual)
• Task: Audio Classification (Binary: HUMAN vs AI_GENERATED)

📁 Directory Structure

• data/: Put your training audio files here.
  • real/: Human voice samples.
  • fake/: AI generated voice samples.
• output/: Fine-tuned model checkpoints will be saved here.
• train.py: Main fine-tuning script.
• prepare_data.py: Script to convert audio folders into Hugging Face datasets.

🚀 Getting Started

1. Collect Data: The more data you have, the better the accuracy. Aim for at least 100-500 samples per category per language.
2. Setup Environment:

   pip install transformers datasets torch torchaudio accelerate
   

3. Run Training:

   python train.py
   

🔧 Why a Custom Model?

The public models (mo-thecreator, etc.) are trained on general datasets. A custom model fine-tuned on your specific AI voices (e.g., from specific TTS engines you use) will have much higher accuracy for your use case.