This research investigates the psycholinguistic origins of language impairments in Alzheimer’s Disease (AD), questioning if these impairments result from language-specific structural disruptions or from a universal deficit in generating meaningful content.
Cross-linguistic analysis was conducted on language samples from 184 English and 52 Persian speakers, comprising both AD patients and healthy controls, to extract various language features. Furthermore, we introduced a machine learning-based metric, Language Informativeness Index (LII), to quantify informativeness.