Hardmeier, Christian

Nivre, Joakim

Stymne, Sara

Tiedemann, Jörg

This paper presents experiments with document-level machine translation with readability constraints. We describe the task of producing simplified translations from a given source with the aim to optimize machine translation for specific target users such as language learners. In our approach, we introduce global features that are known to affect readability into a document-level SMT decoding framework. We show that the decoder is capable of incorporating those features and that we can influence the readability of the output as measured by common metrics. This study presents the first attempt of jointly performing machine translation and text simplification, which is demonstrated through the case of translating parliamentary texts from English to Swedish

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Statistical Machine Translation with Readability Constraints

https://www.pure.ed.ac.uk/ws/files/116811916/Statistical_Machine_Translation_STYMME_DOA22102019_VOR_CC_BY.pdf

Statistical Machine Translation with Readability Constraints

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