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.
Original language | English |
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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
Conference | 9th Biennial Conference of the Association for Machine Translation in the Americas, AMTA 2010 |
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Country/Territory | United States |
City | Denver, CO |
Period | 31/10/10 → 4/11/10 |