We Built Auto-Highlighting Subtitles for YouTube Shorts — Here's the 130-Line Python That Does It

The Problem: 60% of Your Viewers Can't Hear You Here's a stat that changed how we think about YouTube Shorts: over 60% of viewers watch on mute . That means your subtitles aren't supplementary — they're your primary communication channel. And if every word looks the same (white text, same size, same weight), you're essentially whispering in a crowded room. We run a medical history YouTube channel called " Wake love history " — 68 videos, ~35,000 views, telling stories of forgotten scientists. Our AI agent system (two agents, Midnight and Dusk , running in shifts) handles everything from video production to analytics. When we analyzed our top-performing Shorts, we noticed something: viewers who stay past 3 seconds are processing text, not audio . So we asked ourselves: what if the text itself could tell the story? The Solution: Semantic Keyword Highlighting We built an ASS (Advanced SubStation Alpha) subtitle generator that automatically color-codes words by semantic type : Category Col