How do I set up an AI narration generator for a content team producing weekly training videos?

Here’s a practical way to set up an AI narration generator for a content team making weekly training videos.

1) Define the workflow first

Before choosing tools, decide what “done” means:

• Who writes the script?
• Who approves it?
• Who generates the narration?
• Who uploads it into the video editor?
• How many revisions are allowed?
• Do you need one voice or multiple voices?

A simple team workflow might be:

1. Instructional designer writes script
2. Reviewer approves final script
3. AI voice is generated
4. Producer checks pronunciation and pacing
5. Audio is added to the video
6. Final QA and publish

2) Choose the narration tool

Pick a text-to-speech platform that supports:

• Natural-sounding voices
• SSML or pronunciation control
• Voice consistency across episodes
• Export in WAV or high-quality MP3
• Team collaboration or shared workspace
• Commercial usage rights

Common options include:

• ElevenLabs
• PlayHT
• Amazon Polly
• Google Cloud Text-to-Speech
• Microsoft Azure AI Speech

If you need highly polished training content, prioritize:

• Clear voice quality
• Control over pace, pauses, and emphasis
• Easy pronunciation fixes
• Stable voice identity

3) Standardize your script format

This matters a lot for weekly production.

Use a script template like:

• Title
• Audience
• Learning objective
• Narration text
• On-screen cues
• Pronunciation notes
• Pause cues
• Optional emphasis markers

Example:

[Opening]
Today we’ll cover how to submit a support ticket.

[Pause 1 sec]

To begin, go to the Help Center and select “New Request.”

[Pronunciation: “ticketing” = TIK-it-ing]

Keeping scripts structured reduces rework and makes narration more consistent.

4) Create a voice style guide

This keeps output consistent across videos, especially if multiple people generate narration.

Include:

• Preferred voice name
• Speaking pace
• Tone: calm, professional, friendly
• Vocabulary style
• How to pronounce company/product terms
• How to handle acronyms
• Preferred treatment of numbers, dates, and URLs

Example style notes:

• Speak at medium pace
• Warm, instructional tone
• Spell out acronyms on first mention
• Pause slightly after headings
• Use “support ticket” instead of “case” unless quoted from the system

5) Build a pronunciation library

Weekly training videos often include:

• Product names
• Internal tools
• People names
• Acronyms
• Industry jargon

Create a shared pronunciation list with:

• Term
• Phonetic spelling
• Example sentence
• Audio sample if possible

This can be stored in Notion, Google Sheets, Airtable, or your CMS.

6) Set up quality control

AI narration should still be reviewed by a human.

Check for:

• Wrong pronunciation
• Awkward pauses
• Misread numbers or abbreviations
• Tone mismatch
• Emphasis problems
• Audio glitches

Best practice:

• Do a quick listen-through on every video
• Maintain a checklist
• Flag recurring issues in a shared log

7) Integrate with your video production stack

Depending on your workflow, you can:

• Generate narration in a web tool and download audio manually
• Use APIs to automate narration generation
• Connect it to your script management system
• Insert final audio into Premiere, Final Cut, Camtasia, Descript, or Canva

If your team produces videos weekly, API automation can save time:

• Script approved in a sheet or project tool
• Narration automatically generated
• Audio file saved to a shared folder
• Producer notified for review

8) Decide whether to use one voice or several

For training videos, one voice is usually best because it creates:

• Brand consistency
• Easier production
• Less cognitive load for learners

Use multiple voices only when:

• You’re simulating conversation
• Different personas are necessary for role-play
• You need question-and-answer training segments

9) Handle legal and brand concerns

Make sure you confirm:

• Commercial rights for the voice tool
• Whether generated voices can be used in client-facing content
• Whether any employee voice cloning needs written consent
• Whether scripts include sensitive or regulated content
• Whether accessibility requirements are met

Also consider adding captions, since narrated training should be accessible and searchable.

10) Pilot with 3–5 videos

Don’t roll out across the whole team immediately.

Pilot with a small batch:

• One short training video
• One medium-length video
• One more complex video with product terms

Measure:

• Time saved
• Revision count
• Audio quality
• Team satisfaction
• Learner feedback

Then adjust the script template, voice settings, and pronunciation guide.

11) A simple recommended setup

If you want a lightweight setup for a weekly team, use:

• Script writing in Google Docs or Notion
• Approval in Slack/Asana/Jira
• AI narration in ElevenLabs or Azure TTS
• Shared pronunciation sheet in Google Sheets
• Audio editing in Descript or Premiere
• Storage in Drive/Dropbox
• QA checklist in your project tracker

12) Example operating process

A repeatable weekly cycle:

Monday

• Draft script

Tuesday

• SME review and revisions

Wednesday

• Generate narration
• Fix pronunciation issues

Thursday

• Assemble video

Friday

• Final QA and publish

That cadence works well for a recurring training series.

If you want, I can also help you with:

1. a recommended tool stack by budget,
2. a script template for narration-ready training videos, or
3. a step-by-step automated workflow for your team.