Whisper AI Tutorial | Free Offline Transcription for Developers

I run every video I record through Whisper - OpenAI's free, offline speech-to-text AI. In minutes, I get timestamps for YouTube chapters and a transcript for writing descriptions. No subscriptions, no uploads, completely offline.

In this tutorial, I'll show you exactly how to set it up and use it in your workflow. By the end, you'll have professional transcriptions running locally on your machine.

⏱️ TIMESTAMPS:
00:00 Introduction to Whisper Tool
00:30 Prerequisites: Python and FFmpeg
00:42 Installing FFmpeg on Mac, Linux, and Windows
01:51 Installing OpenAI Whisper
02:35 Running Your First Transcription
04:39 Understanding Whisper Models (Tiny to Large)
06:33 Speed and Accuracy Comparison: Tiny vs Small vs Medium
11:35 optimizing with Language Flags
11:53 Customizing Output Formats (SRT, TXT, JSON)
13:43 My Complete Video Workflow for YouTube
15:45 Pro Tips for Performance and Accuracy

🔗 RESOURCES:
- Whisper GitHub: https://github.com/openai/whisper
- FFmpeg: https://ffmpeg.org/

📌 QUICK START:
pip install openai-whisper
brew install ffmpeg (Mac)
whisper video.mp4 --model small --language en

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