Construction of a Quality Estimation Dataset for Automatic Evaluation of Japanese Grammatical Error Correction

• URL: http://arxiv.org/abs/2201.08038v1
• Date: Thu, 20 Jan 2022 08:07:42 GMT
• Title: Construction of a Quality Estimation Dataset for Automatic Evaluation of Japanese Grammatical Error Correction
• Authors: Daisuke Suzuki, Yujin Takahashi, Ikumi Yamashita, Taichi Aida, Tosho Hirasawa, Michitaka Nakatsuji, Masato Mita, Mamoru Komachi
• Abstract summary: In grammatical error correction (GEC), automatic evaluation is an important factor for research and development of GEC systems. In this study, we created a quality estimation dataset with manual evaluation to build an automatic evaluation model for Japanese GEC.
• Score: 21.668187919351496
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In grammatical error correction (GEC), automatic evaluation is an important factor for research and development of GEC systems. Previous studies on automatic evaluation have demonstrated that quality estimation models built from datasets with manual evaluation can achieve high performance in automatic evaluation of English GEC without using reference sentences.. However, quality estimation models have not yet been studied in Japanese, because there are no datasets for constructing quality estimation models. Therefore, in this study, we created a quality estimation dataset with manual evaluation to build an automatic evaluation model for Japanese GEC. Moreover, we conducted a meta-evaluation to verify the dataset's usefulness in building the Japanese quality estimation model.

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