Language Analysis of Speakers with Dementia of the Alzheimer's Type

This research is a discriminative analysis of conversational dialogs involving individuals suffering from dementia of Alzheimer’s type. Several metric analyses are applied to the transcripts of the Carolina Conversation Corpus (Pope and Davis 2011) in order to determine if there are significant statistical differences between individuals with and without Alzheimer’s disease. Results from the analysis indicate that go-ahead utterances, certain fluency measures, and paraphrasing provide defensible means of differentiating the linguistic characteristics of spontaneous speech between healthy individuals and those with Alzheimer’s disease. Several machine learning algorithms were used to classify the speech of individuals with and without dementia of the Alzheimer’s type.

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