A Study of Data-based Translation of English Financial News into Korean

Abstract

This paper shows how to translate English financial news into Korean appropriately on the basis of both the corpus of English financial news and that of Korean financial news. Technical words, phrases, and linguistic constructions that occur typically in English financial news are translated into Korean through consultation of the words and expressions that are really used in Korean financial news. For example, technical or typical English expressions and diverse English verbs that convey fluctuating financial situations are translated into Korean based on the search of their corresponding ones in the corpus of Korean financial news. This data-based translation makes it possible to obtain a translation output that is natural and free from the problem of translationese. Furthermore, a parallel corpus that can be constructed by this method of data-based translation may be used in teaching a way of composing sentences that are relevant to the domain of financial news and in laying a foundation for statistical machine translation of that type of news.