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arXiv · 2111.12284

A Self-Supervised Automatic Post-Editing Data Generation Tool

Hyeonseok Moon·Chanjun Park·Sugyeong Eo·Jaehyung Seo·SeungJun Lee·Heuiseok Lim
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Abstract

Data building for automatic post-editing (APE) requires extensive and expert-level human effort, as it contains an elaborate process that involves identifying errors in sentences and providing suitable revisions. Hence, we develop a self-supervised data generation tool, deployable as a web application, that minimizes human supervision and constructs personalized APE data from a parallel corpus for several language pairs with English as the target language. Data-centric APE research can be conducted using this tool, involving many language pairs that have not been studied thus far owing to the lack of suitable data.

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Hyeonseok Moon, Chanjun Park, Sugyeong Eo, Jaehyung Seo, SeungJun Lee, Heuiseok Lim. 2021-11-24. A Self-Supervised Automatic Post-Editing Data Generation Tool. https://arxiv.org/abs/2111.12284

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