A universal translator could ease the plight of an American in Paris, or aid a diner trying to decide whether to order "cuy chactado" at a Peruvian restaurant.

Those of us for whom Star Trek serves as a benchmark for technological progress can only bemoan the fact that hopes for faster-than-light travel to other galaxies seem to be receding at warp speed, given that we no longer even have faster-than-sound travel to France. But I would prefer to focus on the bright side: We’re rapidly closing in on the Universal Translator, which means that when I do finally arrive in France, I’ll be able to communicate as easily as if I were on Earth.

The Universal Translator, of course, was a handheld device that 
instantly converted Captain Kirk’s futuristically clipped English into the language of whichever vaguely humanoid alien was offering to buy him a blue drink. It is impossible to overemphasize the potential usefulness of such a device on a visit to France, whose vaguely humanoid populace turns Klingon when confronted by a nonspeaker of their primitive but pretty language. Imagine the delight of the garçon when I mumble into my translator, “Can you bring me a good California chardonnay to drown the stench of this cheese?” and out comes flawless French. And back from the device will come a translation of the waiter’s enthusiastic response.

In fact, I already have something surprisingly close to a Universal Translator in my pocket, courtesy of a growing number of automated spoken-language-translating services that run on smartphones. I’m not counting on getting my favorite blue drink in any bar in the world just yet: “These systems still make mistakes that a 4-year-old wouldn’t make,” says Ashish Venugopal, a researcher at Google who works on the company’s Google Translate service. But unlike most 4-year-olds, Google has about a googol million dollars to throw at the problem, and more computing power, too.


Some of that power is spent prowling the web 24/7 to find examples of text—on websites, in email, or anywhere else—that can be paired with translations of that text into another language. The pairs of documents are digested by Google’s computers in chunks of three or so words, with each chunk analyzed and matched to its best translation. Having built in this way a constantly growing database of millions of translation chunks, Google Translate is armed to take on any sentence, find the set of phrases that most closely matches it, and spit back the translation into any of 64 languages. You can go to www.translate.google.com to try the results. Go ahead, do it now. I’ll wait right here.

Not bad, right? This take on machine translation is called a statistical approach because it involves finding the most likely phrase match across a giant sample. Over the past decade it has become the dominant model in the field, largely replacing longstanding efforts of human linguists to painstakingly draw up lists of rules of translation to guide computers. A major benefit of the statistical approach is simplicity, notes Robert Palmquist, CEO of SpeechGear, a machine translation company in Northfield, Minnesota. “A statistical system takes about a third as much time to develop as a rule-based system,” he says, “and it adapts much more easily to constantly changing vocabulary.” And as computing power becomes cheaper, statistical systems will be able to digest larger chunks of words, improving accuracy.

Now throw in a system that recognizes speech—also statistically driven, except it deals with chunks of phonemes, or spoken sounds, rather than written words—and add the sort of text-to-speech function that has been annoying us for years in our various talking devices, and you’ve got a complete system for translating a spoken language on the fly. Google offers Google Translate in Conversation Mode on smartphones for free, and less-free services for phones, tablets, or other devices are available from SpeechGear, IBM, SayHi Translate, and Jibbigo.