Abstract
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.- Anthology ID:
- 2012.amta-caas14.1
- Volume:
- Fourth Workshop on Computational Approaches to Arabic-Script-based Languages
- Month:
- November 1
- Year:
- 2012
- Address:
- San Diego, California, USA
- Venue:
- AMTA
- SIG:
- Publisher:
- Association for Machine Translation in the Americas
- Note:
- Pages:
- 1–8
- Language:
- URL:
- https://aclanthology.org/2012.amta-caas14.1
- DOI:
- Cite (ACL):
- Najeh Hajlaoui and Andrei Popescu-Belis. 2012. Translating English Discourse Connectives into Arabic: a Corpus-based Analysis and an Evaluation Metric. In Fourth Workshop on Computational Approaches to Arabic-Script-based Languages, pages 1–8, San Diego, California, USA. Association for Machine Translation in the Americas.
- Cite (Informal):
- Translating English Discourse Connectives into Arabic: a Corpus-based Analysis and an Evaluation Metric (Hajlaoui & Popescu-Belis, AMTA 2012)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2012.amta-caas14.1.pdf