Researchers have been working for decades in order to establish computer systems capable of translating from one natural language to another. These systems do so by essentially deconstructing the components of the text such as the punctuation marks, recognized idioms, single word terminology, and sentence structure and then reconstructing these elements in the target language by applying specific linguistic rules and “learning” from already existing translations.

This all sounds promising, but we are forgetting that languages are filled with ambiguities and complex rules that not even a computer can successfully resolve. As all translators know, the process of translation involves much more than simply replacing the source word with the target language word. This process involves using cultural, grammatical, syntactic and semantic knowledge in order to interpret the real meaning and ensure that it makes sense to native readers.

Machine translations offer an attractive package for users, ensuring instant turnaround times and a systematic and consistent approach when handling translations. However, we must consider that while the process of human translations is much slower in this sense, only humans can determine the suitability of a translation for a particular audience and make linguistic and style choices based on experience instead of a database.

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