高级口译难度相当于 年3月高级口译上半场阅读理解第一篇原文

年3月高级口译上半场阅读理解第一篇原文  

本文内容为2012春季高口阅读上半场MC第一篇，原文出自businessweek，原文标题为MIT Professor Gives Language Lessons to Computers。
MIT Professor Gives Language Lessons to Computers
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There’s a scene in the 2008 movie Iron Man where Tony Stark
the film’s inventor-superhero
threatens to donate one of his robots to a city college. You can tell by its cowed response that the puterized assistant understands the connotation is decidedly negative. In real life
sofare can’t yet prehend that kind of abstract scolding. Programmers refer to such banter as “natural language
” and it’s tricky for puters to get because of its ambiguity and dependence on context.
Regina Barzilay
an associate professor at the Massachusetts Institute of Technology
is trying to make puters better listeners by making them play Civilization
a 20-year-old strategy game in which players build a city into an empire by vanquishing and absorbing neighboring cultures. A member of MIT’s Computer Science & Artificial Intelligence Lab
Barzilay
40
developed a sofare program that begins with no grasp of the game. The puter “reads” the manual and then keeps returning to it while playing. As it races through thousands of simulations
the puter learns to connect words in the directions (“attack
” “build
” “capture
” and “revolt”) as the game unfolds.
The puter gets positive reinforcement—a higher score and a win—when it makes correct guesses about the meaning of words. When the puter loses
it traces back through its reading of the manual to see where its interpretation went wrong. A similar program without access to the manual won the game 46 percent of the time; after reading the instructions
Barzilay’s puter won 79 percent of the time.
Barzilay grew interested in natural-language processing in the early 1990s
as an undergraduate at Ben-Gurion University in Beersheba
Israel. She was inspired in part by her own experience as a young emigrant from Moldavia who had to learn Hebrew and English. Just as she struggled at first to understand the use of articles such as “the
” which have no equivalent in her native Russian
logic-based puters have difficulties with the inconsistencies of natural language.
Research like Barzilay’s may help puters eventually interact with humans in a more normal way. “You’d like to be able to ask for the largest state bordering New York and have it e back with the answer
‘Pennsylvania
’” says Dan Roth
a puter science professor at the University of Illinois at Urbana-Champaign who does work similar to Barzilay’s. “And what happens inside the puter is none of your business.” Barzilay has been pushing this line of work forward
he says
in part by using a more interesting and plex game. She has a grant from the Defense Advanced Research Projects Agency to help robots understand natural language
not unlike those in Iron Man. As she puts it: “I want to see the puter benefit directly from human knowledge
without having a person in the middle who does a translation.”