Influence of Target Reader Background and Text Features on Text Readability in Bangla: A Computational Approach
Manjira Sinha, Tirthankar Dasgupta, Anupam Basu · International Conference on Computational Linguistics · 2014
In this paper, we have studied the effect of two important factors influencing text readability in Bangla: the target reader and text properties. Accordingly, at first we have built a novel Bangla readability dataset of 135 documents annotated by 50 readers from two different backgrounds. We have identified 20 different features that can affect the readability of Bangla texts; the features were divided in two groups, namely, „classic‟ and „non-classic‟. Preliminary correlation analysis reveals that text features have varying influence on the text hardness stated by the two groups. We have employed support vector machine (SVM) and support vector regression (SVR) techniques to model the reading difficulties of Bangla texts. In addition to developing different models targeted towards different type of readers, separate combinations of features were tested to evaluate their comparative contributions. Our study establishes that the perception of text difficulty varies largely with the background of the reader. To the best of our knowledge, no such work on text readability has been recorded earlier in Bangla.