Multi-Task Neural Models for Translating Between Styles Within and Across Languages

Xing Niu; Sudha Rao; Marine Carpuat

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arXiv · 1806.04357

Multi-Task Neural Models for Translating Between Styles Within and Across Languages

Xing Niu·Sudha Rao·Marine Carpuat

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Abstract

Generating natural language requires conveying content in an appropriate style. We explore two related tasks on generating text of varying formality: monolingual formality transfer and formality-sensitive machine translation. We propose to solve these tasks jointly using multi-task learning, and show that our models achieve state-of-the-art performance for formality transfer and are able to perform formality-sensitive translation without being explicitly trained on style-annotated translation examples.

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Xing Niu, Sudha Rao, Marine Carpuat. 2018-06-12. Multi-Task Neural Models for Translating Between Styles Within and Across Languages. https://arxiv.org/abs/1806.04357

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