An Approach to Example-Based Machine Translator using Translation Memory

This paper presents example-based machine translation architecture using translation memory that integrates the use of examples for flexible, idiomatic translations with the use of linguistic rules for broad coverage and grammatical accuracy. In examplebased machine translation (EBMT) approach to machine translation is often characterized by its use of a bilingual corpus with parallel texts as its main knowledge base, at run-time or we can say, basis for EBMT is the existence of a large volume of translated texts (i.e., parallel bilingual texts), which have been translated by professionals with not only language proficiency but also specialist expertise. Keywords— corpus, EBMT, Interlingua, MT, STMT, TM.