The Short Version
Researchers have built a tool that does something most AI systems don’t: it creates languages that have never existed before. Not translations. Not paraphrases. Entire linguistic systems, complete with their own phonology, syntax, and lexicon.
The tool, called ConlangCrafter, was introduced in a paper at the Proceedings of the Association for Computational Linguistics. It’s already produced over 60 original languages, and the code is publicly available if you want to try your hand at linguistic invention.
How Does an AI Actually Build a Language?
The process isn’t magic — it’s modular. Instead of asking a large language model to generate a whole language in one shot, the researchers broke the task into smaller, manageable pieces.
“We split the problem apart and have the LLMs solve each sub-problem and combine them together,” said Morris Alper, the paper’s lead author and soon-to-be assistant professor at the University of Miami.
Here’s what happens in practice:
- You give ConlangCrafter a set of instructions — anything from “no consonants” to “designed for a species that communicates through color.”
- The AI generates vocabulary and grammar rules that fit those constraints.
- It then translates sample sentences into the new language, checks its own output, and fixes inconsistencies.
- Throughout the process, it maintains a running rulebook of the language’s grammar.
That self-correction loop is what separates this from earlier attempts. The AI isn’t just producing random strings; it’s building a coherent system and then auditing itself against it.
What Kinds of Languages Has It Created?
The team has pushed the boundaries of what a language can look like. One experiment produced a language with zero consonant sounds — something no natural human language achieves. Another was built for an alien squid-like species that communicates through color and gesture rather than speech.
These aren’t just novelty exercises. By forcing the AI to work within extreme constraints, the researchers can explore the outer limits of linguistic possibility.
Why Would Anyone Need a Made-Up Language?
The most obvious use case is fiction. Writers and filmmakers have long struggled to create believable constructed languages — think Game of Thrones or Lord of the Rings. Those languages took years of painstaking work by dedicated linguists. ConlangCrafter could compress that timeline dramatically.
But the researchers see deeper applications, too. The tool could help scholars study poorly documented languages by generating hypotheses about how they might have evolved. It could also serve as a laboratory for understanding language change over time — how sounds shift, how grammar simplifies, how new structures emerge.
Alper and his co-authors — Moran Yanuka, Raja Giryes, and Gašper Beguš — aren’t just building a party trick. They’re building a research instrument.
What’s Next for ConlangCrafter?
Right now, the tool is a research prototype. The code is public, so anyone with technical skills can experiment with it. But the team is already thinking about what comes after.
One direction is making the tool more accessible to non-linguists. Another is integrating it with existing worldbuilding workflows for games and media. And there’s the question of whether AI-generated languages can ever feel as organic as ones that evolved naturally over centuries.
That last question is still open. But for now, the idea that a machine can spin up a fully formed language on demand is both fascinating and slightly unsettling. Which, honestly, is exactly what good science should feel like.
