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.
|State||Published - 2010|
|Event||9th Biennial Conference of the Association for Machine Translation in the Americas, AMTA 2010 - Denver, CO, United States|
Duration: 31 Oct 2010 → 4 Nov 2010
|Conference||9th Biennial Conference of the Association for Machine Translation in the Americas, AMTA 2010|
|Period||31/10/10 → 4/11/10|