Exploring Hybrid Linguistic Features for Turkish Text Readability

The integration of complex morphological, syntactic, semantic, and Automatic Readability Assessment (ARA) is an discourse features in modern ARA approaches offers important task in computational linguistics that the possibility of significantly improving the aims to automatically determine the level of difficulty current readability studies in Turkish. In this paper, of understanding a written text, which has we present the first ARA study for Turkish. Our implications for various fields, such as healthcare, study combines traditional raw text features with education, and accessibility (Vajjala, 2021). In lexical, morpho-syntactic, and syntactic information the healthcare sector, medical practitioners can use to create an advanced readability assessment ARA tools to ensure patient information and consent tool for Turkish. We demonstrate the effectiveness forms are easily understandable (Ley and Florio, of our tool on a new corpus of Turkish popular 1996). In the field of education, teachers and science magazine articles, published for different learners alike can benefit from ARA systems to age groups and educational levels. Our study adapt materials to the appropriate language proficiency aims to contribute to the development of automated level (Kintsch and Vipond, 2014).