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Controlling Translation Formality Using Pre-trained Multilingual Language Models (2205.06644v1)

Published 13 May 2022 in cs.CL

Abstract: This paper describes the University of Maryland's submission to the Special Task on Formality Control for Spoken Language Translation at \iwslt, which evaluates translation from English into 6 languages with diverse grammatical formality markers. We investigate to what extent this problem can be addressed with a \textit{single multilingual model}, simultaneously controlling its output for target language and formality. Results show that this strategy can approach the translation quality and formality control achieved by dedicated translation models. However, the nature of the underlying pre-trained LLM and of the finetuning samples greatly impact results.

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