임의의 참조 데이터를 활용하여 음성 번역 시스템의 정확도 개선 연구

Accuracy Improvement of Speech Translation System Using Intentional Reference Data

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.