AI Voice Navigation

A custom voice assistant trained with 20-30B parameter LLMs on 32GB VRAM. Capable of executing natural-language commands for seamless desktop interactions (e.g., "Open YouTube").

Development Steps:

  1. Data Collection: Curated datasets for voice-command training.
  2. Model Training: Fine-tuning LLMs on dual GPUs.
  3. Voice Recognition Integration: Leveraging open-source speech-to-text APIs.
  4. Command Processing: Mapping voice input to desktop actions.
  5. Deployment: Packaging for real-time responsiveness.