Learning to Generate Word- and Phrase-Embeddings for Efficient Phrase-Based Neural Machine Translation (D19-56)
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| Challenge: | Neural machine translation (NMT) often fails in one-to-many translation, e.g., in the translation of multi-word expressions, compounds, and collocations. |
| Approach: | They propose a phrase-based NMT model that generates embeddings of words or phrases. |
| Outcome: | The proposed model performs on par with state-of-the-art phrase-based NMT. |
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