Generalizing Back-Translation in Neural Machine Translation

WS 2019 Miguel GraçaYunsu KimJulian SchamperShahram KhadiviHermann Ney

Back-translation - data augmentation by translating target monolingual data - is a crucial component in modern neural machine translation (NMT). In this work, we reformulate back-translation in the scope of cross-entropy optimization of an NMT model, clarifying its underlying mathematical assumptions and approximations beyond its heuristic usage... (read more)

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