A linguist trains a language model to reconstruct proto-vocabulary using phonetic drift. The model identifies 120 likely cognates in a language family, but 15% are false positives. How many reliable cognates are estimated?

Mon, 04 May 2026 11:44:03 +0000

**Unlocking Ancient Speech: How AI Reconstructs Lost Vocabulary Through Sound Change** In a world increasingly shaped by language’s digital footprint, a quiet revolution is unfolding behind the scenes: one linguist’s use of artificial intelligence to reconstruct ancient word forms is challenging how we understand linguistic evolution. Using advanced machine learning models trained on phonetic drift, this researcher is identifying reliable roots hidden within complex language families—offering fresh insights into how words have shifted across millennia. With 120 likely cognates discovered, the journey reveals not just data points, but a deeper understanding of human communication’s roots. But here’s the critical question: if the model flags 120 possible cognates in a language family, and experts estimate 15% are false positives, how many truly reliable reconstructions remain? ### Why This Approach Is Gaining Traction