Incorporating Syntactic Uncertainty in Neural Machine Translation with Forest-to-Sequence Model

19 Nov 2017Poorya ZaremoodiGholamreza Haffari

Incorporating syntactic information in Neural Machine Translation models is a method to compensate their requirement for a large amount of parallel training text, especially for low-resource language pairs. Previous works on using syntactic information provided by (inevitably error-prone) parsers has been promising... (read more)

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