Anyone who's turned to a website to translate a foreign language knows that perfect computer translation remains elusive. That's especially true for hundreds of lesser-known languages.
So linguists are trying to harness the wisdom of crowds to do what machines can't. It's known as crowd-sourcing, and researchers think it could help them get closer to something they've been pursuing for decades: the perfect translation machine.
"There are aspects to the translation problem that are undeniably, unavoidably human," says Philip Resnik, who teaches linguistics at the University of Maryland. Resnik says computer translators like Babelfish and Google Translate work best when they have lots of translation data to learn from. And we only have that data for a handful of languages, like French and Chinese.
"There's an awful lot more than six languages in the world," Resnik says. "And an awful lot of people in the world who have a need for something that provides more reliability than you're going to get from Google Translate."
Read/Listen to the rest of this story by Joel Rose at NPR
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