The centrality of language to human existence, as well as questions over the human capacity for language has been a hot topic for linguists over numerous decades. Noam Chomsky famously proposed the idea that humans possess a ‘’universal grammar’’ – suggesting that people instinctively organise a new language according to a logical hierarchy, not simply by learning which words go together, as computer translation programs do.
So what place do computer translation programmes have in the development and future of language? As technology improves, machine translation is becoming increasingly popular – where services such as Google and Bing can give quick (though often rough) translations for tourists. Computer translated material for professional use is usually post-edited for both accuracy and style, but machine translation systems can be trained to deal effectively with restricted subject matter, choosing the best translation for words with multiple meanings. The European Union is the best example of this, with the legalistic and narrow base of bureaucratic language making machine translation much easier.
Although machine translation is still in its infancy, historian of languages Nicholas Oster (whose recent book The Last Lingua Franca will be absorbing reading for students of English, Modern Languages, Oriental Studies, Linguistics and Anthropology) pins his hopes on the power of computer translation as the best means of preserving English as one of the world’s foremost languages. Oster’s book highlights how the percentage of people who have English as their mother tongue is actually shrinking, casting doubt on whether people in the future will want to learn English at all.
The increasing capabilities of machine translation, on the other hand, Oster argues, should mean that, for the vast majority of the world’s people, the quick-and-dirty translations available from the likes of Google can only get better. In the grand scheme of things, computer translations will be a better option for most rather than the tireless hours spent learning English.
Oster’s overriding faith in preserving powers of technology has drawn some criticism, with some questioning whether speech recognition of computer translations will ever come far enough to replace the generally unstructured conversations people have on a daily basis. Nevertheless, the case can still be made that machine translation has come a long way in the past decade, and will continue becoming more important in the future. As Johnson, the Economist’s language blog anticipates, ‘’For many people who are born, live and die without ever leaving their home regions, MT [machine translation] will be good enough for the few times in their lives they need to interact with foreigners. Speech recognition has got a lot better, making slow and carefully enunciated speech decently (if not brilliantly) translatable.’’
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