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Data entered the field of machine translation in the late eighties and early nineties when researchers at IBM’s Thomas J. Watson Research Center reported successes with their statistical approach to machine translation. Until that time machine translation worked more or less the same way as human translators with grammars, dictionaries and transfer rules as the main tools. The syntactic and rule-based Machine Translation (MT) engines appealed much more to the imagination of linguistically trained translators, while the new pure data-driven MT engines with probabilistic models turned translation technology more into an alien threat for many translators. Not only because the quality...
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The question is: are we all on the same evolutionary path? Or do some of us take different turns, make shortcuts and even arrive in different places? The TAUS Executive Forum on April 25 and 26 in Beijing opened new perspectives on translation in China that many of us had perhaps not expected. China typically copies what others have already built and done before them. Fast trains are modeled to the TGV in France, electric cars are inspired by Tesla, and fashion in China follows the trends around the world closely. So when Eric Liu of LocaTran Translations at the TAUS...
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