Papers by Igor Ellakuria

1 papers
TANDO: A Corpus for Document-level Machine Translation (2022.lrec-1)

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Challenge: Document-level Neural Machine Translation aims to increase the quality of neural translation models by taking into account contextual information.
Approach: They propose to use document-level corpus for Basque-Spanish language pairs to take into account contextual information and perform fine-grained evaluations of gender and gender.
Outcome: The proposed corpus is suitable for fine-grained evaluation of document-level machine translation systems.

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