Combining a Statistical Language Model with Logistic Regression to Predict the Lexical and Syntactic Difficulty of Texts for FFL

Reading is known to be an essential task in language learning, but finding the ap-propriate text for every learner is far from easy. In this context, automatic procedures can support the teacher’s work. Some tools exist for English, but at present there are none for French as a foreign language (FFL). In this paper, we present an origi-nal approach to assessing the readability of FFL texts using NLP techniques and extracts from FFL textbooks as our cor-pus. Two logistic regression models based on lexical and grammatical features are explored and give quite good predictions on new texts. The results show a slight superiority for multinomial logistic re-gression over the proportional odds model.