7 common mistakes in AI subtitle workflows

✅ 3-minute summary — 5-step subtitle routine (1 hour → 10–20 min)

1. Auto-generate

2. Bulk-replace proper nouns and numbers

3. Strip fillers and errors

4. Adjust timing (only on outliers)

5. Check style against Channel Rules

Mistake 1 · Proper nouns

"Musk → Mask", "Socar → Soka", "Tesla → Tessla" type misrecognition.

Fix: keep a per-video proper-noun list → bulk-replace with Ctrl+F in the caption editor.

Mistake 2 · Numbers spelled phonetically

Mistake 3 · Timing drift

• Minimum on-screen time per line: 0.8–1.2s
• Shorts: recommended 1.5s
• Leave 0.3s after the sentence ends

Mistake 4 · Line overflow

💡 MeteorStudio wraps Korean lines without breaking words mid-syllable.

Mistake 5 · Fillers verbatim

• ❌ "uh…", "um…", "you know"
• ✅ Keep emotional fillers ("whoa!", "huh!") intentionally

Mistake 6 · Inconsistent EN/KR spelling

Register them in Channel Rules → team-level auto-consistency.

Mistake 7 · Low color/font contrast

• ✅ Subtitle vs background brightness gap ≥ 60%
• ✅ Bold or SemiBold↑
• ✅ Outline or translucent background box
• ✅ Shorts: bigger and bolder

Pre-publish checklist

• [ ] Proper-noun replacements done
• [ ] Numbers and units consistent
• [ ] Minimum on-screen time met
• [ ] 18–24 chars per line
• [ ] Fillers cleaned
• [ ] EN/KR spelling consistent
• [ ] Mobile contrast holds

FAQ

Do subtitles raise retention?

Many mobile viewers watch muted → typically fewer early drop-offs. Low quality flips this.

Use auto-translation as-is?

Domestic OK. Global → manual review required (cultural context, local spelling).

Export to SRT for external editing?

Supported. External edit → re-upload → final render.

Read next: Pre-publish checklist · Channel rules

💡 MeteorStudio caption editor = replace + min-display time + channel rules in one place.

Note: Voice recognition quality varies by environment. Don't ship AI drafts unreviewed.