Machine versus Human Translations
January 7, 2015
I am fascinated with the notion of real time translation. I recall with fondness lunches with my colleagues at Ziff in Foster City. Then we talked about the numerous opportunities to create killer software solutions. Translation would be “solved”. Now 27 years later, progress has been made, just slowly.
Every once in a while an old technical cardboard box gets hauled out from under the car port. There are old ideas that just don’t have an affordable, reliable, practical solution. After rummaging in the box, the enthusiasts put it back on the shelf and move on to the next YouTube video.
I read “The Battle of the Translators: Man vs Machine.” The write up tackles Skype’s real time translation feature. Then there is a quick excursion through Google Translate.
The passage I noted was:
So, while machine translations may be great for rudimentary translations or even video calls, professional human translators are expert craftsmen, linguists, wordsmiths and proofreaders all wrapped in one. In addition to possessing cultural insight, they also are better editors who shape and perfect a piece for better public consumption, guaranteeing a level of faithfulness to the original document — a skill that not even the most cutting-edge machine translation technology is capable of doing just yet. Machine translators are simply not yet at the level of their chess-playing counterparts, which can beat humans at their own game. As long as automatic translators lack the self-awareness, insight and fluency of a professional human translator, a combination of human translation assisted by machine translation may be the optimal solution.
I include a chapter about automated translation in CyberOSINT: Next Generation Information Access. You can express interest in ordering by writing benkent2020 at yahoo dot com. In the CyberOSINT universe, machine translation exists cheek-by-jowl with humans.
For large flows of information in many different languages, there are not enough human translators to handle the work load. Machine based translations , therefore, are an essential component of most cyber OSINT systems. For certain content, a human has to make sure that the flagged item is what the smart software thinks it is.
The problem becomes one of having enough capacity to handle first the machine translation load and then the human part of the process. For many language pairs, there are not enough humans. I don’t see a quick fix for this multi-lingual talent shortfall.
The problem is a difficult one. Toss in slang, aliases, code words and phrases, and neologisms. Stir in a bit of threat with or without salt. Do the best you can with what you have.
Translation is a thorny problem. The squabbles of the math oriented and the linguistic camps are of little interest to me. Good enough translation is what we have from both machines and humans.
I don’t see a fix that will allow me to toss out the cardboard box with its musings from 30 years ago.
Stephen E Arnold, January 7, 2015
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