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Construction of a Quality Estimation Dataset for Automatic Evaluation of Japanese Grammatical Error Correction. (arXiv:2201.08038v1 [cs.CL])
Jan. 21, 2022, 2:10 a.m. | Daisuke Suzuki, Yujin Takahashi, Ikumi Yamashita, Taichi Aida, Tosho Hirasawa, Michitaka Nakatsuji, Masato Mita, Mamoru Komachi
cs.CL updates on arXiv.org arxiv.org
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 …
More from arxiv.org / cs.CL updates on arXiv.org
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