Abstract
Current multilingual word translation methods are focused on jointly learning mappings from each language to a shared space. The actual translation, however, is still performed as an isolated bilingual task. In this study we propose a multilingual translation procedure that uses all the learned mappings to translate a word from one language to another. For each source word, we first search for the most relevant languages. We then use the auxiliary translations to these languages to form an improved representation of the source word. Finally, this representation is used for the actual translation to the target language. Experiments on a standard multilingual word translation benchmark demonstrate that our model outperforms state of the art results.
| Original language | English |
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| Title of host publication | EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, Proceedings of the Conference |
| Publisher | Association for Computational Linguistics |
| Pages | 1330-1335 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781950737901 |
| State | Published - 2019 |
| Event | 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, EMNLP-IJCNLP 2019 - Hong Kong, China Duration: 3 Nov 2019 → 7 Nov 2019 |
Publication series
| Name | EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, Proceedings of the Conference |
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Conference
| Conference | 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, EMNLP-IJCNLP 2019 |
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| Country/Territory | China |
| City | Hong Kong |
| Period | 3/11/19 → 7/11/19 |
Bibliographical note
Publisher Copyright:© 2019 Association for Computational Linguistics