Readability Assessment

Readability assessment focuses on automatically determining how easy a text is to understand, aiming to improve accessibility and comprehension across diverse audiences and languages. Current research emphasizes developing robust multilingual models, often employing neural networks like BERT and transformer-based architectures, and incorporating linguistic features to enhance accuracy, particularly in low-resource languages. This field is crucial for applications ranging from education and content analysis to improving the accessibility of scientific literature and software testing, driving advancements in natural language processing and impacting various sectors.