한국어 구어 문장 파파고 한-영 번역 오류 유형 고찰
A study of error types in Korean-English translation from Korean spoken language to Papago
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참고문헌
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초록
This research seeks to evaluate the accuracy and usefulness of Papago Translator based on translation error rates, patterns, and frequency when used on spoken Korean utterances. The study analyzed a total of 777 spoken Korean sentences that were provided by 32 undergraduate students and seven graduate students majoring in English education, who were enrolled in the spring semester of 2021. We found that 434 (55.9%) sentences were translated correctly, and 343 (44.1%) were translated incorrectly. There were four categories of errors in general. The most frequent were inaccurate semantic errors, 286 (83.4%). This was followed by grammatical errors, 36 (10.5%), and omission errors, 19 (5.5%). Furthermore, there were 343 more detailed errors identified with 14 subcategories. Nighty-seven errors were due to differences in meaning between Korean and English, 57 involved Korean idioms that could not be pragmatically translated, and 38 were as a result of double meaning. Our findings suggest that it is necessary to carry out post-editing of machine translation results to ensure successful communication and proper use of translated English expressions.
Abstract
This research seeks to evaluate the accuracy and usefulness of Papago Translator based on translation error rates, patterns, and frequency when used on spoken Korean utterances. The study analyzed a total of 777 spoken Korean sentences that were provided by 32 undergraduate students and seven graduate students majoring in English education, who were enrolled in the spring semester of 2021. We found that 434 (55.9%) sentences were translated correctly, and 343 (44.1%) were translated incorrectly. There were four categories of errors in general. The most frequent were inaccurate semantic errors, 286 (83.4%). This was followed by grammatical errors, 36 (10.5%), and omission errors, 19 (5.5%). Furthermore, there were 343 more detailed errors identified with 14 subcategories. Nighty-seven errors were due to differences in meaning between Korean and English, 57 involved Korean idioms that could not be pragmatically translated, and 38 were as a result of double meaning. Our findings suggest that it is necessary to carry out post-editing of machine translation results to ensure successful communication and proper use of translated English expressions.
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