Why Do Translation Engines Handle IDML Files Differently?
This article explains why Google Translate, ChatGPT, and DeepL behave differently when processing IDML (InDesign Markup Language) files, why certain errors occur, and how you can prevent them in your translation workflow.
If you’re seeing discrepancies when translating IDML files, it’s not a bug—it’s a reflection of how different translation engines process files.
IDML files don’t just contain text. They carry complex formatting, layout, and style information, and each engine prioritizes these elements differently:
- Google Translate: Prioritizes preserving structure and formatting, but translation quality may be weaker. The layout usually stays intact, but the language may feel unnatural.
- ChatGPT (via Pairaphrase): Prioritizes fluent, human-like translations, but doesn’t natively understand IDML formatting. This can lead to:
- Misinterpreted style tags (e.g., bold, italics, case changes).
- Added or missing whitespace/line breaks.
- Duplicated or dropped text during sentence reflow.
Essentially, ChatGPT sees “content first, formatting second.”
- DeepL: Strikes a middle ground. It’s typically better at balancing formatting and translation quality but isn’t flawless in either category.
Why These Errors Happen
- File Parsing Differences
- Google and DeepL are designed with CAT (computer-assisted translation) and document-processing workflows in mind. They “read” IDML structure and try to maintain tags.
- ChatGPT, meanwhile, was trained as a general-purpose language model. It wasn’t built for strict XML/markup fidelity.
- Formatting Loss During Processing
- When IDML content is extracted for ChatGPT, formatting tags may be flattened, altered, or inconsistently reinserted.
-
- This explains bolding changes, spacing shifts, and missing/repeated text.
- Text Reflow
- ChatGPT often “rewrites” text for fluency. While this improves readability, it can also add/remove lines or duplicate content, unlike engines designed for 1:1 segment consistency.
How to Prevent These Issues
Use a structured translation pipeline
Preprocess IDML files so style and layout tags are “locked” or protected before sending them to ChatGPT.
Segment locking
Keep each sentence or paragraph as a fixed unit, preventing ChatGPT from dropping or duplicating them.
Adopt a hybrid approach
- Use Google or DeepL when formatting fidelity is critical.
- Use ChatGPT when fluency and style are the top priorities—then refine formatting afterward.
- The differences you see aren’t errors—they’re the natural result of how each engine was designed. By choosing the right tool for your goals (or combining them in a hybrid workflow), you can minimize issues and get the best of both worlds.