Finding the Blank with Sequence Labeling for English Learning

Shivam Mehta, I. Smetannikov
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Abstract

Previous approaches to generate fill in the blanks (FITB) questions for English learning mostly are limited to corpus-based approaches that generate Cloze collocates or most frequent co-occurring words. In this study, we propose a Natural Language Processing based approach to generate Fill In The Blank English learning exercises. First, we classify the nature of the problem, and second, we look into the generation of learning exercises. We limited the scope of this research to verb conjugation exercises but it can be extended to other types of learning exercises as well. We looked into the generation of English learning exercises as two types of problems, a sequence labeling problem where we label each token from a sentence whether it could be a potential blank or not and as a sequence to sequence generation problem where we measure its effectiveness in generating such English learning exercises. Generation of FITB for English grammar through these approaches can be useful in the field of Education and can act as a baseline for future work on this problem.
用序列标注寻找英语学习空白
以往生成英语填空题(FITB)的方法大多局限于基于语料库的方法,即生成完形搭配或最常出现的单词。在这项研究中,我们提出了一种基于自然语言处理的方法来生成填空英语学习练习。首先,我们对问题的性质进行分类,其次,我们研究学习练习的生成。我们将这项研究的范围局限于动词变位练习,但它也可以扩展到其他类型的学习练习。我们将英语学习练习的生成作为两种类型的问题进行研究,一种是序列标记问题,我们标记句子中的每个标记是否可能是潜在的空白,另一种是序列到序列生成问题,我们衡量它在生成此类英语学习练习中的有效性。通过这些方法生成英语语法的FITB在教育领域是有用的,并且可以作为将来解决这个问题的基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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