Papers with Sapir
Getting Gender Right in Neural Machine Translation (D18-1)
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| Challenge: | linguistics studies show that the language used by males and females differs in terms of style and syntax. |
| Approach: | They integrate gender information into NMT systems to improve translation quality for multiple language pairs by incorporating gender information to a large dataset. |
| Outcome: | The proposed system significantly improves translation quality for some language pairs. |