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Effective Cross-lingual Transfer of Neural Machine Translation Models without Shared Vocabularies

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Abstract

Transfer learning or multilingual model is essential for low-resource neural machine translation (NMT), but the applicability is limited to cognate languages by sharing their vocabularies. This paper shows effective techniques to transfer a pre-trained NMT model to a new, unrelated language without shared vocabularies.

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Publication details

DOI
10.18653/v1/p19-1120
OpenAlex
W2952614664
Document type
conference-paper
Language
EN
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