CSE Colloquium: Supporting Cognitive Wellness through Spoken Language Analysis

ABSTRACT: Natural language processing can be used to facilitate cognitive wellness in many ways, including through automated cognitive health assessment. In this talk I discuss two novel strategies for assessing cognitive health directly from individuals’ free speech, focusing on the problem at different levels of granularity. First, we design a neural model that leverages semantic and psycholinguistic features to classify patients as belonging to coarse-grained dementia or control groups. Then, we examine the utility of a variety of lexicosyntactic, psycholinguistic, discourse-based, and acoustic features to predict fine-grained, continuous scores indicative of cognitive health status. We achieve high performance surpassing existing benchmarks for both tasks. I conclude by introducing some intriguing directions for future work.

BIOGRAPHY: Natalie Parde is an Assistant Professor in the Department of Computer Science at the University of Illinois at Chicago, where she also co-directs UIC’s Natural Language Processing Laboratory. Her research interests are in natural language processing, with emphases in healthcare applications, interactive systems, multimodality, and creative language. She serves on the program committees for EMNLP, ACL, and NAACL, and the Senior Program Committee for AAAI, among other conferences and workshops. In her spare time, Dr. Parde enjoys engaging in mentorship and outreach for underrepresented CS students.