임의의 참조 데이터를 활용하여 음성 번역 시스템의 정확도 개선 연구

• 영문명: Accuracy Improvement of Speech Translation System Using Intentional Reference Data
• 발행기관: 한국산업기술융합학회(구. 산업기술교육훈련학회)
• 저자명: 김규석(Kyuseok Kim)
• 간행물 정보: 『산업기술연구논문지』산업기술연구논문지 제25권 4호, 49~56쪽, 전체 8쪽
• 주제분류: 공학 > 산업공학
• 파일형태: PDF
• 발행일자: 2020.12.30

영문 초록

In the fourth industrial revolution, speech recognizers are widely used to operate machines, such as artificial intelligence secretaries, phones, and factory machines. Hence, the accuracy of speech recognition is crucial. In previous studies, methods for improving the accuracy of speech recognition have been proposed. These methods may have led to improved accuracy of speech recognition and speech translation. However, it is still not entirely accurate to use speech translation to interpret sentences in another language because both results from the speech recognizers and translators have problems of misunderstanding the language. In this study, a method for improving the accuracy of speech translation from Korean to English using intentional reference data was developed. Korean sentences, which are usually used in software engineering classes, were used to evaluate the proposed method. From the results, the translated sentences were more fluently understandable than those that were not modified using the intentional reference data. It is expected that the proposed method will be useful for human communication, particularly in professional settings, such as conferences, meetings, or major classes in colleges.

목차

Ⅰ. 서 론

Ⅱ. 관련 연구

Ⅲ. 시스템 구성

Ⅳ. 실험 방법 및 결과

Ⅴ. 결 론

참고문헌

키워드

음성 번역 참조 데이터 번역 정확도 음성 인식 구글 번역기 기계 번역 구글 음성인식기 Speech Translation Reference Data Translation Accuracy Speech Recognition Google Translator Machine Translation Google Speech Recognizer