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 |
| Projects: |
Idiap |
| Authors: | |
| Added by: | [UNK] |
| Total mark: | 0 |
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