Detecting Loneliness and Social Isolation through Speech Analysis
Author Information
Author(s): Lee Ellen, Wang Ning, Badal varsha, Goel Sanchit, Subbalakshmi Koduvayur
Primary Institution: University of California San Diego
Hypothesis
Can unstructured speech data be used to detect loneliness and social isolation in older adults?
Conclusion
Analyzing speech data can help identify loneliness and social isolation, which are linked to negative health outcomes in older adults.
Supporting Evidence
- Loneliness and social isolation can lead to increased mortality in older adults.
- Current assessments of loneliness are lengthy and do not capture individual experiences.
- Speech analysis can provide insights into social disconnection.
Takeaway
This study looks at how the way older people talk can show if they feel lonely or isolated, which can help doctors help them better.
Methodology
The study used Natural Language Processing and openSMILE to analyze speech data and identify features related to social disconnection.
Participant Demographics
Older adults living independently in senior housing communities in San Diego.
Digital Object Identifier (DOI)
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