Vocabulary Profiling of Reading Materials for Learning Chinese

Since extensive reading is important for language learning, students should engage in extra-curricular reading as much as possible. To facilitate efficient learning, language teachers need to select reading materials at the appropriate difficulty level, and adapt them if necessary. This paper describes a text analysis and revision tool that assists teachers in preparing reading materials in Chinese. On the basis of a graded vocabulary list, the tool estimates the percentage of words in a text that are known to students at the target school grade. Further, it highlights words that are expected to be new vocabulary, and suggests alternatives that better fit the expected vocabulary proficiency at the target grade. Evaluation results show that the use of Forward Maximal Matching improves word matching with the vocabulary list, and that dynamic editing of word segmentation leads to more accurate assessment of the text difficulty level. © 2024 IEEE