Communications of the ACM

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software helps Linguists
Reconstruct, Decipher
Ancient Languages

Linguists who once spent an entire career reconstructing a major
language family now can accomplish that in just a few hours.

the early language from which they all descended. The result? More than 85% of the system’s reconstructions were within one character of the manual reconstruction provided by a linguist who specialized in Austronesian languages—and, of course, the differences are not necessarily errors.

How does the system work?

The way we produce words differs from the way our ancestors pronounced those same words. As time goes by, minute, ongoing alterations help turn an ancestral language like Latin into modern descendants like French, Italian, and Portuguese.

The sound changes are almost
always regular, with similar words
While previously it might have
taken a linguist their entire career to
reconstruct a major language family,
now software running computations
on, say, a large experiment that may
involve a sixth of the world’s languages
can be completed in just a few hours.

The achievement is not about speed, cautions Dan Klein, associate professor of computer science at the University of California, Berkeley. It’s about being able to do things in a large-scale, data-driven manner without losing all the important insights that historical linguists have gained in working on these sorts of problems for decades, he says.

Indeed, linguistic researchers compare these techniques to those used for gene sequence evolution.

“This achievement should not be compared to, for example, Deep Blue, IBM’s chess-playing computer,” Klein insists. “This is not a human-versus-machine story in which humans used to be better until finally a computer was able to take the crown. This is a story of computation giving human linguists new tools that supplement their weaknesses and let them work in new ways.” The efforts of Klein and his colleagues are described in their paper, “Automated Reconstruction of Ancient Languages Using Probabilistic Models of Sound Change,” published by the National Academy of Sciences in February.

According to Klein, the work’s main contribution was a new tool that researchers can use to automatically reconstruct the vocabularies of ancient languages using only their modern-language descendants.

The goal, he says, is not to just rewind the clock; rather, it is to better understand the processes that give rise to language change, and to model how the evolution of language proceeds. “And so we want to know things like what kind of sound changes are more likely and what kind of sound changes go together,” he explains.