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ARTICLE

Readability Assessment of Textbooks in Low Resource Languages

Zhijuan Wang1,2, Xiaobin Zhao1,2, Wei Song1,*, Antai Wang3
Minzu University of China, Beijing, China.
National Language Resource Monitoring & Research Center of Minority Languages, Beijing, China.
New Jersey Institute of Technology, 323 Dr Martin Luther King Jr Blvd, Newark, NJ 07102, USA.
* Corresponding Author: Wei Song. Email: .

Computers, Materials & Continua 2019, 61(1), 213-225. https://doi.org/10.32604/cmc.2019.05690

Abstract

Readability is a fundamental problem in textbooks assessment. For low re-sources languages (LRL), however, little investigation has been done on the readability of textbook. In this paper, we proposed a readability assessment method for Tibetan textbook (a low resource language). We extract features based on the information that are gotten by Tibetan segmentation and named entity recognition. Then, we calculate the correlation of different features using Pearson Correlation Coefficient and select some feature sets to design the readability formula. Fit detection, F test and T test are applied on these selected features to generate a new readability assessment formula. Experiment shows that this new formula is capable of assessing the readability of Tibetan textbooks.

Keywords

Readability assessment, low resource language, textbook in Tibetan, linear regression, named entity

Cite This Article

Z. Wang, X. Zhao, W. Song and A. Wang, "Readability assessment of textbooks in low resource languages," Computers, Materials & Continua, vol. 61, no.1, pp. 213–225, 2019.

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This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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