Offline AI Audio Transcriber – Local LLM-Powered Speech-to-Text Tool I built a fully offline, privacy-first AI Audio Transcriber for clients who handle sensitive audio data.

This desktop application converts audio recordings into accurate, structured PDF reports without sending any data to the cloud.

Key Features: • Runs 100% locally on user hardware (no internet required) • Uses multiple local LLMs and speech-to-text models for high accuracy (96%+) • Automatically generates well-formatted PDF reports with timestamps and summaries • Strong focus on data privacy and security • Supports multiple audio formats

Built with Python, leveraging local AI models to ensure complete confidentiality — perfect for professionals, researchers, lawyers, and businesses dealing with confidential recordings.

This project demonstrates my skills in Python desktop application development, AI/ML integration, local LLM deployment, and creating secure, high-performance tools.

Ideal for users who need powerful AI capabilities without compromising privacy.