TY  - JOUR
T1  - English-Korean Neural Machine Translation using MASS with Relative Position Representation
AU  - Jung, Youngjun 
AU  - Park, Cheoneum 
AU  - Lee, Changki 
AU  - Kim, Junseok 
JO  - Journal of KIISE, JOK
PY  - 2020
DA  - 2020/1/14
DO  - 10.5626/JOK.2020.47.11.1038
KW  - machine translation
KW  - relative position representation
AB  - Neural Machine Translation has been mainly studied for a Sequence-to-Sequence model using supervised learning. However, since the supervised learning method shows low performance when the data is insufficient, recently, a transfer learning method of fine-tuning using the pre-training model based on a large amount of monolingual data such as BERT and MASS has been mainly studied in the field of natural language processing. In this paper, MASS using the pre-training method for language generation, was applied to the English-Korean machine translation. As a result of the experiment, the performance of the English-Korean machine translation model using MASS showed better performance than the existing models, and the performance of the machine translation model was further improved by applying the relative position representation method to MASS.