Paper ID: 2306.03774

Exploring Hybrid Linguistic Features for Turkish Text Readability

Ahmet Yavuz Uluslu, Gerold Schneider

This paper presents the first comprehensive study on automatic readability assessment of Turkish texts. We combine state-of-the-art neural network models with linguistic features at lexical, morphosyntactic, syntactic and discourse levels to develop an advanced readability tool. We evaluate the effectiveness of traditional readability formulas compared to modern automated methods and identify key linguistic features that determine the readability of Turkish texts.

Submitted: Jun 6, 2023