Automatic Readability Assessment

The computational task of predicting how difficult a text is for a reader, usually expressed as a grade level or a readability score. Modern systems treat readability as a machine-learning classification or regression problem that combines shallow surface features (sentence length, syllable counts), language-model perplexity, part-of-speech distributions, parsed syntactic structures, and discourse-level features such as entity density. Automatic readability assessment is a building block for text-simplification pipelines and content-adaptation systems that serve readers with intellectual disabilities, low literacy, cognitive disabilities, or who are reading in a second language.