Using Arabic Transliteration to Improve Word Alignment from French- Arabic Parallel Corpora

Houda Saadane, Ouafa Benterki, Nasredine Semmar, Christian Fluhr


Abstract
In this paper, we focus on the use of Arabic transliteration to improve the results of a linguistics-based word alignment approach from parallel text corpora. This approach uses, on the one hand, a bilingual lexicon, named entities, cognates and grammatical tags to align single words, and on the other hand, syntactic dependency relations to align compound words. We have evaluated the word aligner integrating Arabic transliteration using two methods: A manual evaluation of the alignment quality and an evaluation of the impact of this alignment on the translation quality by using the Moses statistical machine translation system. The obtained results show that Arabic transliteration improves the quality of both alignment and translation.
Anthology ID:
2012.amta-caas14.6
Volume:
Fourth Workshop on Computational Approaches to Arabic-Script-based Languages
Month:
November 1
Year:
2012
Address:
San Diego, California, USA
Editors:
Ali Farghaly, Farhad Oroumchian
Venue:
AMTA
SIG:
Publisher:
Association for Machine Translation in the Americas
Note:
Pages:
38–46
Language:
URL:
https://aclanthology.org/2012.amta-caas14.6
DOI:
Bibkey:
Cite (ACL):
Houda Saadane, Ouafa Benterki, Nasredine Semmar, and Christian Fluhr. 2012. Using Arabic Transliteration to Improve Word Alignment from French- Arabic Parallel Corpora. In Fourth Workshop on Computational Approaches to Arabic-Script-based Languages, pages 38–46, San Diego, California, USA. Association for Machine Translation in the Americas.
Cite (Informal):
Using Arabic Transliteration to Improve Word Alignment from French- Arabic Parallel Corpora (Saadane et al., AMTA 2012)
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PDF:
https://aclanthology.org/2012.amta-caas14.6.pdf