Neural networks draw on context to improve machine translations

Researchers at the University of Amsterdam are using neural networks to help statistical machine translation systems learn what all human translators know—that the best translation of a word often depends on the context.

The neural network is able to derive grammatical functions of words without having explicit knowledge of the grammar, said Ke Tran, one of the researchers. This means that to learn word functions the method does not depend on examples hand-picked by the researchers, which can be a difficult and costly process, especially for languages with few speakers.

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