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http://dx.doi.org/10.14400/JDC.2021.19.7.199

Recent Automatic Post Editing Research  

Moon, Hyeonseok (Department of Computer Science and Engineering, Korea University)
Park, Chanjun (Department of Computer Science and Engineering, Korea University)
Eo, Sugyeong (Department of Computer Science and Engineering, Korea University)
Seo, Jaehyung (Department of Computer Science and Engineering, Korea University)
Lim, Heuiseok (Department of Computer Science and Engineering, Korea University)
Publication Information
Journal of Digital Convergence / v.19, no.7, 2021 , pp. 199-208 More about this Journal
Abstract
Automatic Post Editing(APE) is the study that automatically correcting errors included in the machine translated sentences. The goal of APE task is to generate error correcting models that improve translation quality, regardless of the translation system. For training these models, source sentence, machine translation, and post edit, which is manually edited by human translator, are utilized. Especially in the recent APE research, multilingual pretrained language models are being adopted, prior to the training by APE data. This study deals with multilingual pretrained language models adopted to the latest APE researches, and the specific application method for each APE study. Furthermore, based on the current research trend, we propose future research directions utilizing translation model or mBART model.
Keywords
Deep Learning; Natural Language Process; Language Convergence; Machine Translation; Automatic Post Editing; Pretrained model;
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