Papers by Rihards Krišlauks
Training and Adapting Multilingual NMT for Less-resourced and Morphologically Rich Languages (L18-1)
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| Challenge: | Using multilingual and multi-way neural machine translation approaches is a major advantage . training NMT systems for individual language pairs takes significantly more time than training of SMT systems . |
| Approach: | They propose to employ multilingual and multi-way neural machine translation approaches for morphologically rich languages such as Estonian and Russian. |
| Outcome: | The proposed approach improves translation quality by +3.27 BLEU points over baseline models. |