A language-independent approach to automatic text difficulty assessment for second-language learners

Shen, Wade, Williams, Jennifer, Marius, Tamas and Salesky, Elisabeth (2013) A language-independent approach to automatic text difficulty assessment for second-language learners. In Proceedings of the Second Workshop on Predicting and Improving Text Readability for Target Reader Populations. Association for Computational Linguistics (ACL). 9 pp .

Record type: Conference or Workshop Item (Paper)

Abstract

In this paper, we introduce a new baseline for language-independent text difficulty assessment applied to the Interagency Language Roundtable (ILR) proficiency scale. We demonstrate that reading level assessment is a discriminative problem that is best-suited for regression. Our baseline uses z-normalized shallow length features and TF-LOG weighted vectors on bag-of-words for Arabic, Dari, English, and Pashto. We compare Support Vector Machines and the Margin-Infused Relaxed Algorithm measured by mean squared error. We provide an analysis of which features are most predictive of a given level.

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