Part 2 of our series on AI in eLearning Localisation
In Part 1 of this series, we looked at how AI is reshaping the localisation of written eLearning content – such as course modules, assessments, and on-screen text – helping L&D teams deliver multilingual training faster and more cost-effectively.
In this article, we focus on the localisation of audiovisual learning content, including training videos, animations, and module narration. We explore how AI voiceover and automated subtitling tools are enabling L&D teams to scale global training programmes, reduce production time, and improve accessibility, while highlighting where human oversight is still essential to ensure clarity, tone, and learner engagement.
💡 Want a comprehensive look at all the tools and workflows? Download the AI in eLearning Localisation Guide.
What is AI voiceover, and how does it work?
Also known as text-to-speech or synthetic voiceover, AI voice technology uses neural networks to generate audio that sounds convincingly human. It’s available in dozens of languages and accents, and removes the need to book voice talent or studios for every project.
If you’re exploring AI voiceover in more detail, don’t miss our in-depth blog: How to use AI to create a multilingual voiceover – packed with expert tips, practical examples, and key things to consider when scaling voiceover production across languages.
Why use AI voiceover?
✅ Speed: Generate multilingual audio in minutes
✅ Flexibility: Easily update or edit lines without a full re-record
✅ Scalability: Localise content across regions quickly
✅ Budget: Save on actors, studios, and rework costs
It’s perfect for training videos, animated explainers, or modules with frequent updates.
Where AI voiceover needs human backup
Even the best AI platforms still stumble on:
- Names, numbers, and acronyms
- Emotional tone or natural intonation
- Cultural missteps in phrasing or pacing
Top tips for better AI voiceover:
- Get translated transcripts signed off first
- Choose voices carefully – —listen before committing
- Ask a native linguist to review pronunciation and tone
- Split long sentences to improve flow
- Use human voiceover for high-stakes, emotionally engaging content
What about subtitles?
AI-generated subtitles use automatic speech recognition (ASR) and machine translation to create captions in multiple languages.
Subtitles are an excellent tool for:
- Accessibility (for deaf or hard-of-hearing learners)
- Faster localisation of training videos
- Supporting non-native speakers
- Learning in quiet/shared spaces
AI subtitles: When to use, and when to refine
Best use cases:
- Scripted, clearly spoken instructional content
- Content with tight timelines or low risk
- Quick updates across multiple markets
When human review is essential:
- Courses with slang, variation in speaker tone, or industry-specific jargon
- Subtitles need to match precise timing
- Cultural tone and nuance are important
Top tip: Share terminology lists and brand preferences with your subtitle post-editors to improve accuracy and consistency.
Final thoughts: Balance automation with quality control
AI voice and subtitles are game-changers for eLearning localisation, but only when used with care. A hybrid model that blends automation with expert human input delivers the best of both worlds: speed and quality.
If you haven’t yet read Part 1, take a look at how AI can also streamline text-based localisation and translation workflows.
👉 Download our complete guide: AI in eLearning Localisation to get expert tips, comparison charts, and benchmarks to help you choose the right approach for your project.