The goal of this study is to find out why the English subtitles of Korean TV dramas have frequent errors. It is anticipated that the findings would shed light on innovative ways for machine translation technology to agglutinate languages. To do this, as a first step, Korean-English subtitles were grammatically tagged according to the category part of speech (POS) to find out which POS has the most frequent errors in each language. Thirty-one groups were analyzed and categorized by tagging the part of speech. Then, for the Korean language, the Kokoma Korean morpheme analyzer was run to tag the Korean script according to the category noun, verb, adjective, etc. These were categorized into forty-five groups. This categorization included nine subsets of <i>josa</i> (postposition) and fourteen of <i>eomi</i> (ending), which are the most difficult parts of Korean to translate into English due to differences in linguistic structure. As a next step, the subtitles were scored and graded as the most corrected and the least corrected by Korean-American bilinguals. The results show that the most frequent error of <i>josa</i> is JX (auxiliary particle) among nine groups whereas the frequent error of <i>eomi</i> is EPT (tense prefinal ending).

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The popular Korean drama Good Doctor (Ki & Kim, 2013) was adapted and remade in the US and broadcast from September, 2018 by ABC as The Good Doctor (Daly, 2018). Consequently, the role of subtitling also plays an important part among a variety of countries with different cultures and languages. This paper concentrates on a comparison and analysis of the subtitles for both the American The Good Doctor and the Korean Good Doctor, aiming to identify the lexical differences and frequency of English words, phrases and sentences in both. First, the lexical differences and occurrences of expressions in English open class word groups are analyzed according to a text analyzer and parts-of-speech tagger (POS tagger). Next, they are divided into three phrase groups -noun phrases, verb phrases, and prepositional phrases, which are compared and analyzed. The data is then divided into seven categories according the Bhagat and Hovy's (2013) 25 classes. This study shows that even though the number of characters, syllables, words, and sentences in the Korean Good Doctor (KG) is higher than that of the American The Good Doctor (AG), the lexical density in AG is higher than that of KG. This implies that AG uses more vocabulary variety and less vocabulary repetition.

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