웹 코퍼스를 기반으로 한 한불 번역 등가어 연구 : 코로나19를 중심으로
A Web as corpus-based study on Korean-French translation equivalences : focused on COVID-19
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Translators generally use a bilingual dictionary to find equivalences between two different languages. However, one disadvantage of existing dictionaries is that they do not immediately reflect new expressions and their real usage. In this context, Web as corpus serves as a useful translation dictionary. In this article, we investigated Korean-French translation equivalences of certain keywords related to an infectious disease, COVID-19, from the Web as corpus. We took translated words or expressions suggested by existing Korean-French dictionary, and searched for them using the Web as a corpus to ascertain their real-life usages. We confirmed that while existing dictionaries play an important role in translation, they have some restrictions. While this finding does not mean that the Web as corpus wholly substitutes existing bilingual dictionaries, we confirmed that it could support the dictionaries in identifying the real usage of target language or in recognizing real-world expressions used by native speakers.
Abstract
Translators generally use a bilingual dictionary to find equivalences between two different languages. However, one disadvantage of existing dictionaries is that they do not immediately reflect new expressions and their real usage. In this context, Web as corpus serves as a useful translation dictionary. In this article, we investigated Korean-French translation equivalences of certain keywords related to an infectious disease, COVID-19, from the Web as corpus. We took translated words or expressions suggested by existing Korean-French dictionary, and searched for them using the Web as a corpus to ascertain their real-life usages. We confirmed that while existing dictionaries play an important role in translation, they have some restrictions. While this finding does not mean that the Web as corpus wholly substitutes existing bilingual dictionaries, we confirmed that it could support the dictionaries in identifying the real usage of target language or in recognizing real-world expressions used by native speakers.
참고문헌 (35)
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