Disfluencies in spontaneous speech in persons with low-grade glioma before and after surgery.

Impaired lexical retrieval is common in persons with low-grade glioma (LGG). Several studies have reported a discrepancy between subjective word-finding difficulties and results on formal tests. Analysis of spontaneous speech might be more sensitive to signs of word-finding difficulties, hence we aimed to explore disfluencies in a spontaneous-speech task performed by participants with presumed LGG before and after surgery.

Using a Discourse Task to Explore Semantic Ability in Persons With Cognitive Impairment.

This paper uses a discourse task to explore aspects of semantic production in persons with various degree of cognitive impairment and healthy controls. The purpose of the study was to test if an in-depth semantic analysis of a cognitive-linguistic challenging discourse task could differentiate persons with a cognitive decline from those with a stable cognitive impairment. Both quantitative measures of semantic ability, using tests of oral lexical retrieval, and qualitative analysis of a narrative were used to detect semantic difficulties.

Predicting MCI Status From Multimodal Language Data Using Cascaded Classifiers.

Recent work has indicated the potential utility of automated language analysis for the detection of mild cognitive impairment (MCI). Most studies combining language processing and machine learning for the prediction of MCI focus on a single language task; here, we consider a cascaded approach to combine data from multiple language tasks. A cohort of 26 MCI participants and 29 healthy controls completed three language tasks: picture description, reading silently, and reading aloud.

Automated Syntactic Analysis of Language Abilities in Persons with Mild and Subjective Cognitive Impairment.

In this work we analyze the syntactic complexity of transcribed Swedish-language picture descriptions using a variety of automated syntactic features, and investigate the features' predictive power in classifying narratives from people with subjective and mild cognitive impairment and healthy controls. Our results indicate that while there are no statistically significant differences, syntactic features can still be moderately successful at distinguishing the participant groups when used in a machine learning framework.