Machine Translation with Many Manually Labeled Discourse Connectives
Type of publication: | Conference paper |
Citation: | Meyer_DISCOMT-2_2013 |
Publication status: | Published |
Booktitle: | Proceedings of the 1st DiscoMT Workshop at ACL 2013 (51st Annual Meeting of the Association for Computational Linguistics) |
Year: | 2013 |
Month: | June |
Pages: | 43-50 |
Location: | Sofia, Bulgaria |
Abstract: | The paper presents machine translation experiments from English to Czech with a large amount of manually annotated discourse connectives. The gold-standard discourse relation annotation leads to better translation performance in ranges of 4–60% for some ambiguous English connectives and helps to find correct syntactical constructs in Czech for less ambiguous connectives. Automatic scoring confirms the stability of the newly built discourse-aware translation systems. Error analysis and human translation evaluation point to the cases where the annotation was most and where less helpful. |
Keywords: | disambiguation, discourse connectives, Statistical Machine Translation |
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Idiap |
Authors | |
Added by: | [UNK] |
Total mark: | 0 |
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