Multilingual Pre-training with Language and Task Adaptation for Multilingual Text Style Transfer
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 propos...
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| creator | Lai, Huiyuan Toral, Antonio Nissim, Malvina |
| description | 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. |
| doi_str_mv | 10.48550/arxiv.2203.08552 |
| format | Article |
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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
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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
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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><doi>10.48550/arxiv.2203.08552</doi><oa>free_for_read</oa></addata></record> |
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| title | Multilingual Pre-training with Language and Task Adaptation for Multilingual Text Style Transfer |
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