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    <abstract>An implementation of a non-structural Example-Based Machine Translation system that translates sentences from Arabic to English, using a parallel corpus aligned at the sentence level, is described. Source-language synonyms were derived automatically and used to help locate potential translation examples for fragments of a given input sentence. The smaller the parallel corpus, the greater the contribution provided by synonyms. Considering the degree of relevance of the subject matter of a potential match contributes to the quality of the final results.</abstract>
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%0 Conference Proceedings
%T Using Synonyms for Arabic-to-English Example-Based Translation
%A Bar, Kfir
%A Dershowitz, Nachum
%S Proceedings of the 9th Conference of the Association for Machine Translation in the Americas: Student Research Workshop
%D 2010
%8 oct 31 nov 4
%I Association for Machine Translation in the Americas
%C Denver, Colorado, USA
%F bar-dershowitz-2010-using
%X An implementation of a non-structural Example-Based Machine Translation system that translates sentences from Arabic to English, using a parallel corpus aligned at the sentence level, is described. Source-language synonyms were derived automatically and used to help locate potential translation examples for fragments of a given input sentence. The smaller the parallel corpus, the greater the contribution provided by synonyms. Considering the degree of relevance of the subject matter of a potential match contributes to the quality of the final results.
%U https://aclanthology.org/2010.amta-srw.3/

Markdown (Informal)

[Using Synonyms for Arabic-to-English Example-Based Translation](https://aclanthology.org/2010.amta-srw.3/) (Bar & Dershowitz, AMTA 2010)

• Using Synonyms for Arabic-to-English Example-Based Translation (Bar & Dershowitz, AMTA 2010)

ACL

• Kfir Bar and Nachum Dershowitz. 2010. Using Synonyms for Arabic-to-English Example-Based Translation. In Proceedings of the 9th Conference of the Association for Machine Translation in the Americas: Student Research Workshop, Denver, Colorado, USA. Association for Machine Translation in the Americas.