Exploring Linguistic Features for Turkish Text Readability
It addresses the problem of text readability for Turkish language users, but is incremental as it applies existing methods to a new language.
This paper tackled the problem of automatic readability assessment for Turkish texts by combining neural networks with linguistic features, resulting in the identification of key features that determine readability and evaluation of traditional versus modern methods.
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, morphological, 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.