Translating English Discourse Connectives into Arabic: a Corpus-based Analysis and an Evaluation Metric

Discourse connectives can often signal multiple discourse relations, depending on their context. The automatic identification of the Arabic translations of seven English discourse connectives shows how these connectives are differently translated depending on their actual senses. Automatic labelling of English source connectives can help a machine translation system to translate them more correctly. The corpus-based analysis of Arabic translations also enables the definition of a connective-specific evaluation metric for machine translation, which is here validated by human judges on sample English/Arabic translation data.


Presented at:
Fourth Workshop on Computational Approaches to Arabic Script-based Languages at Proceedings of the Tenth Biennial Conference of the Association for Machine Translation in the Americas (AMTA)
Year:
2012
Keywords:
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 Record created 2013-12-19, last modified 2018-09-13

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