On Romanization for Model Transfer Between Scripts in Neural Machine Translation

Chantal Amrhein
Chantal Amrhein

EMNLP, pp. 2461-2469, 2020.

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Abstract:

Transfer learning is a popular strategy to improve the quality of low-resource machine translation. For an optimal transfer of the embedding layer, the child and parent model should share a substantial part of the vocabulary. This is not the case when transferring to languages with a different script. We explore the benefit of romanizat...More

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