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Multilingual Pre-training with Language and Task Adaptation for Multilingual Text Style Transfer

2022-03-16 11:27:48
Huiyuan Lai, Antonio Toral, Malvina Nissim
arXiv_CL
       
Abstract

We exploit the pre-trained seq2seq model mBART for multilingual text style transfer. Using machine translated data as well as gold aligned English sentences yields state-of-the-art results in the three target languages we consider. Besides, in view of the general scarcity of parallel data, we propose a modular approach for multilingual formality transfer, which consists of two training strategies that target adaptation to both language and task. Our approach achieves competitive performance without monolingual task-specific parallel data and can be applied to other style transfer tasks as well as to other languages.

Abstract (translated)

URL

https://arxiv.org/abs/2203.08552

PDF

https://arxiv.org/pdf/2203.08552.pdf

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