A nice article on The New York Times‘s Bits Blog yesterday, about Carnegie Mellon University computer scientist Luis von Ahn and his Duolingo experiment:

Language does not come naturally to machines. Unlike humans, computers cannot easily distinguish between, say, a river bank and a savings bank. Satire and jokes? Algorithms have great trouble with that. Irony? Wordplay? Cultural context? Forget it.

 

That human edge in decoding what things mean is what a computer scientist turned entrepreneur, Luis von Ahn, is betting on. His start-up, Duolingo, which opened to the public on Tuesday, proposes to put armies of language learners to work translating text on the Web [more following the link].

 

For the learners, Duolingo offers basic lessons, followed by sentences to translate, one at a time, from simple to more difficult. For online content providers wanting translations, Duolingo offers, for now at least, free labor. Because it is still in its early days, there are no independent assessments available of how accurate or efficient it can be.

 

The site has been available by invitation only for the last five months and is now limited to English, Spanish, French and German. People and companies can submit their content to Duolingo for translation, a service the company may begin to charge for. To provide content for its lessons, Duolingo can also harness whatever text is not under copyright or is released under a liberal Creative Commons license. Users vote for the best translations, providing some measure of quality control.

 

“You’re learning a language and at the same time, helping to translate the Web,” Mr. von Ahn said. “You’re learning by doing.”

 

 

Google Translate, by contrast, relies entirely on machines to do the work — and while it usually captures the essence of a piece of text, it can sometimes produce bewildering passages. Google leverages vast amounts of data to produce its output, feeding its translation engine with texts that have been translated into multiple languages, including United Nations proceedings, which are then used to train its machines.

 

Mr. von Ahn, by contrast, is leveraging what he hopes will be crowds flocking to Duolingo for free language lessons…

 

Mr. von Ahn, an associate professor at Carnegie Mellon University in Pittsburgh, where Duolingo is based, came up with the translation idea when he noticed that friends and relatives in his native Guatemala had far less content available to them online if they did not know English. The Web, Mr. von Ahn argued, is inferior in Spanish. “It’s got much less information. I see people struggling with that a lot,” he said. “They don’t get the information we take for granted.”

 

Human and machine translation can work in different scenarios, said Alon Lavie, another Carnegie Mellon professor who has a machine translation company called Safaba, aimed at corporate clients. When businesses need to translate large amounts of text into multiple languages, machine translation can be more useful, said Mr. Lavie, particularly if business confidentiality is at stake.

 

“Where I think Duolingo’s crowdsourcing makes a lot of sense is in scenarios where a consumer or enterprise has a small translation job that needs to be done quickly and cheaply, and the translation needs to come out at ‘human’ quality — similar to what a human translator or bilingual speaker would generate,” Mr. Lavie said…

Check out the rest of the post as it originally appeared on the Bits Blog here.

(Contributed by Erwin Gianchandani, CCC Director)