Semi-Automatic Construction of a Readability Corpus for the Vietnamese Language

Abstract

Text readability is a measure of how easy or difficult it is to read a text. This readability factor plays a crucial role in the processes of drafting and comprehending the texts, affecting the choice of proper texts for reading. While text readability has been a focus in research on computational linguistics for English and other resource-rich languages, there is still little work on this subject in understudied languages like Vietnamese. In this study, we propose a semi-automated method to build a corpus for text readability purposes for the Vietnamese language. This method performs the classification of new documents based on comparing the correlation readability with the documents that have been manually pre-assessed by language experts. The evaluation results of experts show that the classification accuracy of documents in the corpus is over 90%. The experimental results on other available corpus also show that our proposed method can not only address the lack of corpora that are graded on various difficulty levels in Vietnamese, but it can also be extended to the analysis of other resource-poor languages without requiring major adjustments.