Time: 1245pm-145pm, Friday, March 5, 2010 Place: Room 6496, CUNY Graduate Center, 365 Fifth Ave (34str&35str). Speaker: Lijun Feng (CUNY) Title: Automatic Readability Assessment Abstract: What makes a text easy or hard to read? Previous research in automatic readability assessment has looked at a limited class of lexical and syntactic properties of texts. In this study, we explore linguistic features at several levels (lexical, syntactic, discourse, etc.) to investigate and analyze their possible impact on and correlations with text readability. In addition to systematically analyzing well studied lexical and syntactic features and expanding new features at these levels, we investigate a set of novel features at various discourse levels which may impact text readability from a text comprehension point of view. We combine NLP and machine learning techniques to build and evaluate an automatic readability assessment tool based on these features. Our best performing model derived from stepwise greedy approach showed significant improvement compared with previous studies in the field. Speaker Bio: Lijun Feng is a PhD student in the Computer Science Department at the Graduate Center, the City University of New York (CUNY). Her research interests include natural language processing (NLP), in particular readability, text comprehension and text simplification, and machine learning. Her thesis research combines NLP and machine learning techniques to build and evaluate an automatic text readability assessment tool, both for general audience and readers with intellectual disabilities in particular.