Tuesday, July 20, 2010

More on computer "decipherment" of Ugaritic

CUNEIFORM DAY! National Geographic has an article on that recent computer "decipherment" of Ugaritic:
"Lost" Languages to Be Resurrected by Computers?

New program can translate ancient Biblical script.


Tim Hornyak

for National Geographic News

Published July 19, 2010

A new computer program has quickly deciphered a written language last used in Biblical times—possibly opening the door to "resurrecting" ancient texts that are no longer understood, scientists announced last week.

Created by a team at the Massachusetts Institute of Technology, the program automatically translates written Ugaritic, which consists of dots and wedge-shaped stylus marks on clay tablets. The script was last used around 1200 B.C. in western Syria.

[...]
As I have already noted, the program did not decipher Ugaritic, although it does sound like a useful tool to aid human decipherment of lost languages.

The rest of the article describes what the program actually does. But the most interesting bit was this part at the end:
The next step should be to see whether the program can help crack the handful of ancient scripts that remain largely incomprehensible.

Etruscan, for example, is a script that was used in northern and central Italy around 700 B.C. but was displaced by Latin by about A.D. 100. Few written examples of Etruscan survive, and the language has no known relations, so it continues to baffle archaeologists.

(Related: "Languages Racing to Extinction in Five Global 'Hotspots.'")

"In the case [of Ugaritic], you're dealing with a small and simple writing system, and there are closely related languages," noted Richard Sproat, an Oregon Health and Science University computational linguist who was not involved in the new work.

"It's not always going to be the case that there are closely related languages that one can use" for Rosetta Stone-like comparisons.

But study leader Barzilay thinks the decoding program can overcome this hurdle by scanning multiple languages at once and taking contextual information into account—improvements that could uncover unexpected similarities or links to known languages.
If this program leads to the decipherment of, say, Etruscan or Linear A, I will indeed be impressed.