From the Wall Street JournalArticle excerpt : It used to be the case when I traveled abroad that I would take a little pocket dictionary that provided translations for commonly used phrases and words. If I wanted to construct a sentence, I would thumb through the dictionary for five minutes to develop a clunky expression with unconjugated verbs and my best approximation of the correct noun. Today I take out my phone and type the phrase into Google Translate, which returns a translation as fast as my Internet connection can provide it, in any of 90 languages.
Machine translation is leaps and bounds faster and more effective than my old dictionary method, but it still falls short in accuracy, functionality and delivery. That won’t be the case for long. A decade from now, I would predict, everyone reading this article will be able to converse in dozens of foreign languages, eliminating the very concept of a language barrier.
Today’s translation tools were developed by computing more than a billion translations a day for over 200 million people. With the exponential growth in data, that number of translations will soon be made in an afternoon, then in an hour. The machines will grow exponentially more accurate and be able to parse the smallest detail. Whenever the machine translations get it wrong, users can flag the error—and that data, too, will be incorporated into future attempts.It is just a matter of more data, more computing power and better software. These will come with the passage of time and will fill in the communication gaps in areas including pronunciation and interpreting a spoken response.
Link to the full article here.
InterpretAmerica's take: At InterpretAmerica, we have been following technological developments that affect language and interpreting for years. Technology news is an interesting beast. In many ways, it has become an exercise in one-upmanship. The latest report about the “next big thing” or the “newest technology” better have a wow factor to get readers’ attention. This recent essay from the Wall Street Journal serves as a perfect example. It makes many proverbial 10-year predictions, notes that the technology just isn’t quite there yet and reports that the latest tech buzzword, in this case “big data,” will fix all of this. Pardon us if we are a bit skeptical.
In the last five years, many books have been published on how technology is radically changing society. Two fairly recent publications, The Second Machine Age by MIT professors Erik Brynjofsson and Andrew McAfee and The New Digital Age by former Google CEO Eric Schmidt and Jared Cohen also contain sections on the future wonders of machine translation and interpreting, no human needed. Sadly, they are both sparse when it comes to specifics as well. Even so, both are well worth reading. (We'll be reading Industries of the Future by Alec Ross with great interest too.)
In reality, the language barrier fell a long time ago. Professional translators and interpreters have been facilitating multilingual communication for decades, initially without and later with the aid of technology. Granted, this tried-and-true technology-cum-human solution isn’t flashy and won’t necessarily fit in your ear, but interpreters have been whispering “what is being said to you in your native language” since the Tower of Babel. As we have reported before, the introduction of new technologies has made high-quality human interpretation more available than ever before in many new ways. True, human translation and interpreting don’t scale like fully automated solutions can, but when accuracy really counts, quality will always trump quantity.
If we were to take at face value the many press accounts published each month about new translation apps, services and gizmos, there would be no need for any kind of human intervention when translating anything from one language to another. The truth, however, is that translation and interpreting (the human kind) continue to grow at a marked clip, and even the companies that develop and market fully-automated machine translation solutions wouldn’t use them for their own high-value meetings or publications.
Will technology someday replace human translators and interpreters? We’ve learned to never say “never” but we will say "not today, not next week and not in 10 years."