Lesson 9 of 13 · Module 3: AI-Assisted Post-Production
AI Voiceover
Generate an AI voiceover read of a written script and judge, against named criteria, whether it’s usable as-is or needs a human read instead.
Interactive demo · Same Line, Two Takes, Four Criteria
Objective
Why This Matters
AI voiceover is good enough to ship for a lot of content right now, and an instant giveaway for the rest. The skill here isn’t generating a voiceover, that part is trivial. It’s knowing exactly why a given read does or doesn’t work, so you’re making a deliberate call every time instead of gambling. Publishing AI voice without that judgment, on content where it doesn’t hold up, is exactly how a creator earns the reputation for “AI slop” that costs trust with an audience.
The Technique
Know what current-generation AI voice models are actually good at: clean articulation, consistent pacing on straightforward informational copy, a wide range of language and accent options. Know where they still commonly break: emotional peaks and sarcasm, comedic timing, natural pause placement inside long or complex sentences, and mispronunciation of proper nouns and technical jargon, especially anything specific to your industry.
Test method, every time: read the same script with at least 2 different voices or settings, then score each one against the same 4 named criteria: pacing and pauses, emphasis placement, pronunciation accuracy, and emotional tone match. Don’t pick a favorite on vibes and back into a justification afterward. Score first, decide second.
Route content to a human read when the criteria say to, not when it’s convenient. Anything emotionally loaded, comedic, or brand-critical is a strong signal to use a human voice regardless of how good the AI take sounds in isolation, because the failure mode on that content is expensive.
Watch For This
Good
- You can name specifically which of the 4 criteria a take passed or failed, for every take tried.
- The accepted take’s emotional tone genuinely matches the script’s intent, not just “technically clean audio.”
Classic Failure
- A take is accepted because “it’s fine” without actually checking pacing, emphasis, pronunciation, and tone individually, so a real problem (a mispronounced proper noun) slips through unnoticed.
- A good take is rejected for a vague “something’s off” reason that can’t be tied to any of the 4 criteria, which means the next attempt isn’t actually being evaluated any better.
- Emotionally loaded or comedic content is voiced with AI by default, without ever considering routing it to a human read.
Your Drill
Take a 30 to 60 second script. Generate at least 2 voice takes with different voices or settings. Score each against the 4 named criteria in writing. Submit the script, both takes, the scorecard, and your final decision.
Done? Paste what you made into the AI coach below for notes against this lesson's pass checklist.
Pass Checklist
Lesson complete
Criterion met: You produce a written pass/fail judgment against 4 named criteria (pacing and pauses land naturally, emphasis falls on the right words, no mispronunciations, emotional tone matches the script’s intent) for each voice tried, and for any rejected take you can name the specific criterion it failed, not a general impression.
Next: Lesson 10: AI Writing as Drafting PartnerHow solid did that feel?
Noted.
Coach Note
The mispronunciation failure is the sneakiest one because your brain autocorrects it on the first listen, you already know what the word is supposed to be. Listen to your top take a second time specifically hunting for pronunciation errors on any proper noun or technical term, treating it like you’ve never heard the script before.
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