Zhijuan Wang1,2, Xiaobin Zhao1,2, Wei Song1,*, Antai Wang3
CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 213-225, 2019, DOI: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… More >
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