Readability Assessment of Textbooks in Low Resource Languages
Zhijuan Wang, Xiaobin Zhao, Wei Guo Song, Antai Wang · Computers, materials & continua/Computers, materials & continua (Print) · 2019
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.