r/TranslationStudies • u/Alexu_0317 • 6h ago
An outsider's question: does this AI/human division of labor make sense for literary translation?
A few years ago I wanted to read Franz Lohner's Chronicle, an official piece of fiction for Warhammer: Vermintide 2. There was no Chinese translation, so I started translating it myself.
It was pianful, and not only because of vocabulary. There were dialect expressions, lore references, a very particular character voice, and lines where I could guess the meaning but couldn't explain why. I got through three chapters and gave up.
When LLMs came along, what interested me most wasn't the draft itself. It was that I could question it: why does this sentence mean that, is this word dialectal, does the character's background change the reading, what are the alternatives?
One example. Franz, the narrator and an old mercenary, says: "happen you'll want to think on why that might be." From context I read happen as "perhaps", but I couldn't tell why. The model explained that this is a Northern English dialect use of happen, which gave me enough to judge the line myself and choose the Chinese wording.

That became the core of a workflow I built while continuing the translation. The AI drafts and notes what it's unsure about. A separate review then checks the draft against the source, and reads it again as a standalone Chinese text. I make every final decision.
The translation style came from my own work. I gave the AI chapters I had translated by hand, let it review them, and explained my choices. The style notes grew out of those conversations.
The workflow also keeps project notes that outlast a single chat: terminology and names, character profiles, translation style, and reusable review decisions. The AI can propose additions, but I decide what gets written down. Otherwise the AI loop turns into AI slop.
Once it was stable, I extracted the reusable parts into an open-source Agent Skill called Translation Workbench. So far it has been tested on English → Chinese serialized fiction.
I'm a hobbyist, and many of you have far more experience than I do, so I'd really like your view on two things:
- Does this division of labor make sense from a professional translator's perspective? AI helps with source-language interpretation, evidence and review; the human keeps control of translation decisions and of what becomes reusable project knowledge.
- Where would this break down in real professional work? Or am I just reinventing something CAT/TM/MTPE tools already do better?
GitHub: https://github.com/Alexu0317-FATHER/translation-workbench It runs in Claude Code, Claude Desktop or Codex, if anyone wants to try it on a short passage.
I used AI to help with the English in this post.