Papers with DocRepair
Context-Aware Monolingual Repair for Neural Machine Translation (D19-1)
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| Challenge: | et al., 2018) show that human raters prefer corrected translations over the baseline ones. |
| Approach: | They propose a monolingual model to correct inconsistencies between sentences . they use monolingual document-level data to train the model . |
| Outcome: | The proposed model improves translations of contextual phenomena in English-Russian translation task. |
Lexical Translation Inconsistency-Aware Document-Level Translation Repair (2023.findings-acl)
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| Challenge: | Experimental results show document-level translation repair improves translation consistency but still suffers from lexical translation inconsistency due to the lack of inter-sentence context. |
| Approach: | They propose a document-level translation repair model to model translation inconsistency via automatic post-editing. |
| Outcome: | The proposed model improves translation quality and lexical consistency on document-level translation datasets. |