The ability to read and to understand text is a crucial competence to communicate and to exchange information. For different reasons, understanding written language can be a challenge for different target groups like language learners, students, or people with cognitive limitations, but also for people with less experience or knowledge about the text's content. All these user groups have different needs in terms of readable texts. A machine-based evaluation of subjective text readability addresses these needs and provides groundwork for applications like text simplification.
The project aims at developing a system that predicts the subjective readability rating of both, experts and non-experts of a specific text domain. Data base are texts provided by DATEV, a German IT service provider. The linguistic properties of the texts are examined to detect correlations between syntactical, morphological, and lexical features and the subjective perception of readability.
This is a SoftwareCampus project in cooperation with DATEV eG as industry partner.