A Study on the evaluation of Korean-English patent machine translation – Focusing on KIPRIS K2E-PAT translation.
이화여자대학교, Hyo-eun Choi, Jieun Lee · 통역과 번역 · 2017
This study aims at assessing the quality of patent translations by K2E-PAT, a Korean-English machine translation system run by Korean Intellectual Property Office, based on the analysis of machine translations of 38 semiconductor-related patent abstracts. In the study, we’ve conducted both automated evaluation widely used in the machine translation evaluation and human evaluation which can complement the shortcomings of automated evaluation. For the automated evaluation, case insensitive BLEU was adopted as an automated score, as it is the most widespread in the intellectual property field. For human evaluation, two examiners examined the quality of machine translation in terms of fidelity and readability. Both automated and human evaluations revealed the machine translations are mostly not satisfactory according to the criteria. Human evaluation indicates that the patent abstract translations contain numerous semantic and syntactic errors as well as terminological ones, severely hampering fidelity and readability. The findings highlight the need to improve the quality standards of K2E-PAT machine translation by fostering collaboration between translation experts and computational linguists.