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Multi-Task Neural Models for Translating Between Styles Within and Across Languages (1806.04357v1)
Published 12 Jun 2018 in cs.CL
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.