Modelling Lexical Characteristics of the Healthy Aging Population with a Natural Speech Dataset
Track: Non-traditional track
Keywords: NLP tools, psycholinguistic metrics, natural language, cognitive aging
TL;DR: Using NLP tools and psycholinguistic metrics to process natural language datasets can help to set a normative benchmark of aging language
Abstract: Modelling baseline language variation in normal aging is important for our understanding of healthy aging. Large-language databases and NLP tools enable us to conduct automated quantitative analysis of natural language data. In this study, we aim to demonstrate that using NLP tools and psycholinguistic metrics to process natural language datasets can help to set a normative benchmark of aging language. The benchmark can be applied to the assessment of cognitive aging.
Presentation And Attendance Policy: I have read and agree with the symposium's policy on behalf of myself and my co-authors.
Ethics Board Approval: Yes, we have/will include(d) information about IRB approval or its equivalent, in the manuscript.
Data And Code Availability: No, we will not be making any data and/or code public.
Primary Area: Datasets and benchmarks
Student First Author: Yes, the primary author of the manuscript is a student.
Submission Number: 11
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