But there is progress. Companies have combined the power of humans and computers to simultaneously double the speed of translation and nearly halve its cost. Where each translator once converted 2,500 words a day at a cost of some 25¢ per word, they can now offer 5,000 words a day at around 12¢-15¢ a word. The savings add up mightily when a project can, for example, involve several million words.
In the White House paper, A Strategy for American Innovation: Driving Towards Sustainable Growth and Quality Jobs, the Administration lays out what it expects from the $1 billion federal investment in innovation. Amid new energy, health-care, and education goals, the report offers several specific "grand challenges" for the 21st century. Among them: "Automatic, highly accurate and real-time translation between the major languages of the world—greatly lowering the barriers to international commerce and collaboration."
While it is not clear how much of the $1 billion in stimulus money will go directly toward translation efforts, any federal investment could go far in the industry. The machine translation industry hasn't grown much, hovering around $100 million for years, and the recession has only exacerbated the situation, leaving plenty of linguists looking for work, says Don DePalma, chief research officer at Common Sense Advisory, a Lowell (Mass.)-based translation consultancy. "There's a lot of pent-up intellectual capacity that could really improve natural language processing," he says.
In August 2009, Common Sense surveyed 27 corporations, two government offices, and two nongovernmental organizations that used human-assisted machine translation. Individual answers were not released publicly, but companies reported that HAMT doubled the translation output of what humans could do alone. The companies also reported that the hybrid method is up to 45% cheaper than using humans alone. Online tools such as Google Translate (GOOG) and Yahoo's (YHOO) Babel Fish are not yet accurate enough to do the job without humans, DePalma says.
Language translation is far from being mastered by humans, computers, or any mix of the two. Inherent obstacles, such as the speed of computers and the sophistication of software, are restraining the progress of automated translation, says Rayid Ghani, a senior researcher at Accenture Technology Labs (ACN) in Chicago. "More basic research and development is needed," he says. Much of that work will need to take place outside the U.S., he says, because of a lack of texts written in nonmajor languages for researchers to analyze.
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