Paper: Reading Level Assessment Using Support Vector Machines And Statistical Language Models

ACL ID P05-1065
Title Reading Level Assessment Using Support Vector Machines And Statistical Language Models
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2005
Authors

Reading pro ciency is a fundamen- tal component of language competency. However, nding topical texts at an appro- priate reading level for foreign and sec- ond language learners is a challenge for teachers. This task can be addressed with natural language processing technology to assess reading level. Existing measures of reading level are not well suited to this task, but previous work and our own pilot experiments have shown the bene- t of using statistical language models. In this paper, we also use support vector machines to combine features from tradi- tional reading level measures, statistical language models, and other language pro- cessing tools to produce a better method of assessing reading level.