Papers with adapting neural machine translation systems
Rapid Adaptation of Neural Machine Translation to New Languages (D18-1)
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| Challenge: | Existing approaches to adapt neural machine translation systems to low-resource languages are difficult to implement and require large amounts of training data. |
| Approach: | They propose a method to train neural machine translation systems to new low-resource languages . they propose to start with massively multilingual "seed models" and continue training on data related to the LRL . |
| Outcome: | The proposed method achieves BLEU scores of up to 15.5 with no data from the LRL and improves over other adaptation methods by 1.7 BLUE points average over 4 LRL settings. |