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.
Original language | English |
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Title of host publication | Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics |
Publisher | Association for Computational Linguistics, ACL Anthology |
Publication status | E-pub ahead of print - 2022 |
Event | The 60th Annual Meeting of the Association for Computational Linguistics - Dublin, Ireland Duration: 22-May-2022 → 27-May-2022 |
Conference
Conference | The 60th Annual Meeting of the Association for Computational Linguistics |
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Country/Territory | Ireland |
City | Dublin |
Period | 22/05/2022 → 27/05/2022 |