Abstract
It has been recognized that existing methods for rating English texts by reading level are mostly aimed at native speakers of English and therefore are not completely appropriate for Japanese learners of the language. Here we propose a method for rating English texts by reading level specifically targeted at Japanese learners of the language. To rate the reading level of a text for a Japanese learner of English, our method takes two types of information regarding a given text into account, namely, vocabulary and grammatical structure. Specifically, we rate the reading level of a text by using a vocabulary list and parser to extract particularly difficult vocabulary items or grammatical structures as features. To rate a text's reading level, two types of model are used: multiple regression and neural networks. Our experiments show that the proposed methods rate the reading level of a text with the following levels of accuracy: an average of 75% accuracy for multiple regression and 81.3% when using neural networks. These constitute improvements on existing methods. Β© 2005 Wiley Periodicals, Inc. Syst Comp Jpn, 36(6): 1β13, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.20326