What machine translation can and can’t do
May 28th, 2010
While WLS adamantly and singularly advocates human translation (that is, translation done by a professionally trained person, not processed by a computer), there is a case to be made for machine translation in select circumstances. A NYTimes editorial disputes the advantages and limitations, looking at Google Translate in particular.
When Haiti was devastated by an earthquake in January, aid teams poured in to the shattered island, speaking dozens of languages — but not Haitian Creole. How could a trapped survivor with a cellphone get usable information to rescuers? If he had to wait for a Chinese or Turkish or an English interpreter to turn up he might be dead before being understood. Carnegie Mellon University instantly released its Haitian Creole spoken and text data, and a network of volunteer developers produced a rough-and-ready machine translation system for Haitian Creole in little more than a long weekend. It didn’t produce prose of great beauty. But it worked.
But the editorial’s author David Bellos concludes that beyond emergency or wartime scenarios, machine translation doesn’t have much hope. No Google translation should ever be accepted as a “correct translation.” “Google Translate gives only an expression consisting of the most probable equivalent phrases as computed by its analysis of an astronomically large set of paired sentences trawled from the Web.”
And where do those probable equivalent phrases come from? Human translators!
The data comes in large part from the documentation of international organizations. Thousands of human translators working for the United Nations and the European Union and so forth have spent millions of hours producing precisely those pairings that Google Translate is now able to cherry-pick. The human translations have to come first for Google Translate to have anything to work with.
So, we must give credit where it is due. Credit to the astonishing advances in machine translation technology since Cold War spy games, and even more credit to the hardworking human minds that transform language and culture without having to manually compute a lexicon.
Click here to read the full editorial.






Google has refined its translation tool to a point that “can make the language barrier go away,” as one of the principal scientists of the company’s machine translation team said. Now handling 52 languages, Google is yet again a visionary in an area most internet/computer companies have ignored over the years.