Web: http://arxiv.org/abs/2209.06295

Sept. 15, 2022, 1:14 a.m. | Nathaniel R. Robinson, Cameron J. Hogan, Nancy Fulda, David R. Mortensen

cs.CL updates on arXiv.org arxiv.org

Multilingual transfer techniques often improve low-resource machine
translation (MT). Many of these techniques are applied without considering data
characteristics. We show in the context of Haitian-to-English translation that
transfer effectiveness is correlated with amount of training data and
relationships between knowledge-sharing languages. Our experiments suggest that
for some languages beyond a threshold of authentic data, back-translation
augmentation methods are counterproductive, while cross-lingual transfer from a
sufficiently related language is preferred. We complement this finding by
contributing a rule-based French-Haitian orthographic …

arxiv case case study data study transfer transfer learning translation

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