"Auto-Captions Aren't Good Enough"
"We've been told auto captions aren't acceptable. But manually editing 200 lecture videos will take months."
— Instructional Designer, r/instructionaldesign (53 upvotes)
YouTube and Zoom auto-captions are full of errors. Manual editing takes hours per video. Here's how to speed it up 10x with AI cleanup.
2-4 hours
Manual caption editing per 60-min video
15-30 min
With Aelira AI cleanup + review
Why Auto-Captions Fail WCAG Compliance
1. Technical Terms Mangled
Auto-captions don't know discipline-specific vocabulary. Results are gibberish.
Auto-Caption
"the mitochondria is responsible for 80 p production"
Should Be
"the mitochondria is responsible for ATP production"
2. Missing Punctuation
Auto-captions run sentences together. Screen readers can't parse meaning.
Auto-Caption
"the results were significant however we need more data to confirm our hypothesis lets look at the next slide"
Should Be
"The results were significant. However, we need more data to confirm our hypothesis. Let's look at the next slide."
3. Names and Acronyms Wrong
Proper nouns, researcher names, and acronyms are frequently incorrect.
• "nietzsche" "neat chick"
• "WCAG" "weak egg"
• "Foucault" "fu co"
• "PyTorch" "pie torch"
4. No Speaker Labels
WCAG 1.2.2 requires identifying speakers in multi-person videos. Auto-captions don't do this.
Auto-Caption
"that's a great point what do you think about X?"
Should Be
Professor Smith: That's a great point.
Student Johnson: What do you think about X?
Manual Caption Editing: The Time Sink
Typical workflow for 60-minute lecture video:
1. Download auto-captions from YouTube/Zoom: 5 min
2. Watch video + fix technical terms: 90 min
3. Add punctuation + capitalization: 30 min
4. Add speaker labels (if panel/interview): 45 min
5. Final review + upload: 15 min
Total: 3 hours per video
× 200 videos per semester = 600 hours of work
How Aelira Speeds Up Caption Cleanup 10x
AI-Powered Caption Enhancement
Upload Auto-Captions (VTT/SRT)
Export auto-generated captions from YouTube/Zoom/Teams. Upload VTT or SRT file to Aelira.
Provide Context (Optional)
Give AI a list of technical terms, names, acronyms used in the video.
Names: Dr. Sarah Johnson, Dr. Michael Chen
Acronyms: WCAG, ADA, NVDA
AI Cleanup (30 seconds)
Aelira's AI (Llama 3.2) automatically:
- Fixes technical term errors
- Adds punctuation and capitalization
- Corrects names and acronyms
- Adds speaker labels (if requested)
Quick Review (15-30 min)
Review AI-cleaned captions. Fix any remaining edge cases. Export final VTT/SRT.
What Aelira Fixes Automatically
- Technical terminology (discipline-specific)
- Punctuation (periods, commas, question marks)
- Capitalization (proper nouns, start of sentences)
- Names and acronyms (from context list)
- Speaker identification (multi-person videos)
Time Savings
Manual Editing
3 hours/video
With Aelira
20 min/video
90% faster
Save 2.5 hours per video
Process 200 videos in 67 hours (vs 600 hours)
Real Example: Biology Lecture with Technical Terms
YouTube Auto-Caption
Unintelligible to students relying on captions
After Aelira AI Cleanup
Fully accessible and accurate (30 seconds AI processing)
Total Time Comparison (60-min video)
Manual Editing
- Watch + fix terms: 90 min
- Add punctuation: 30 min
- Review: 15 min
- Total: 135 min
With Aelira
- Upload + AI cleanup: 1 min
- Review AI output: 15 min
- Final polish: 5 min
- Total: 21 min
Save 114 minutes per video (85% time reduction)
Stop Spending Hours on Caption Editing
Let AI clean up auto-captions in seconds, not hours.
30-day free trial · Process 10 videos free · No credit card required
See Caption Cleanup Demo
Watch Aelira clean up a 60-minute lecture caption file in 30 seconds. Join 500+ universities preparing for April 2026.