한국어 번역을 위한 문화소의 기계번역 연구-중국 외교연설문 번역의 정확도 평가를 중심으로-

Abstract

The development of translation machines represented by machine translation and AI translation has recently become a hot topic in the society. Particularly, in recent years, the accuracy and fluency of translation machines have been greatly improved thanks to the use of neural network technology (NMT,Neural Machine Translation), and translation machines have become the main focus of public attention. In addition, the translation machine was previously considered to be dedicated to professional translators because of technical problems, but now the translation machine has already become an accessible tool that people can easily use in daily life. This study will analyze the implementation of machine translation between Chinese and Korean by targeting at Papago, which is a translation machine developed by Korean famous online company Naver that Chinese-speaking learners can easily have access to, and Baidu, which is a well-known translation machine in China. Besides, in order to evaluate the translation accuracy between Chinese and Korean of the famous Google Translate which is currently used worldwide, Google Translate is also included in the study. Ten translators were invited to evaluate the translation results of the machine and in this way the accuracy of the machine translation has been obtained. The analysis objects selected in this study are representative cultural vocabulary arising from language differences: idioms, poems, proverbs and proper nouns, all of which are cultural vocabulary that are the most dependent on the culture in translation. Although the object of evaluation is linguistic expression, considering the contextual information of translation and interpretation, the entire sentence containing cultural vocabulary is presented to the evaluator so that they can realize the environment in which the expression is used. In this study, the evaluation scores, evaluation items, and evaluation criteria of the translation are listed, and the results are obtained from a combination of all these factors. This study reveals the development direction of machine translation and seeks the common development between translators and machines, through the comparison between machine translation and human translation. Therefore, if the translation pattern such as the error pattern of the translation machine can be understood before using, it is expected to further improve the efficiency.