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Using Natural Language Processing and Speech Processing Techniques to Understand and Predict Cognitive Decline

Award Number: F99AG088590
ORGANIZATION: NATIONAL INSTITUTE ON AGING
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: FELLOWSHIP/SCHOLARSHIP/STUDENT LOANS
PERIOD OF PERFORMANCE START DATE: 09/17/2025
PERIOD OF PERFORMANCE END DATE: 09/16/2027

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Using Natural Language Processing and Speech Processing Techniques to Understand and Predict Cognitive Decline - Abstract Alzheimer’s disease and related dementias are a significant public health concern, especially for disaster responders and construction workers exposed to neurotoxic hazards. Although valuable data about occupational exposure and cognitive health can be obtained from open-ended questions, analyzing such unstructured text and audio data is often time-consuming and underutilized. Recent advancements in Natural Language Processing (NLP) and Speech Processing (SP) offer new opportunities to efficiently extract this information and predict cognitive outcomes. This proposal aims to leverage NLP and SP tools to analyze unstructured free text and audio data from the World Trade Center (WTC) responder cohort, a population at high risk for cognitive decline due to disaster- related neurotoxic exposures. I developed and validated a linguistic tool (NLP method) to extract occupational exposure variables—termed WTC Exposure to Response Activities (WERA) —from free text descriptions of work activities. In the F99 phase, these WERA variables will be used to predict mild cognitive impairment (MCI) incidence, cognitive trajectory, and neurodegenerative biomarker distributions, with mask usage as a potential mediator. This NLP method will advance research in occupational cognition health by reducing reliance on structured lists and manual categorization of occupational activity exposures. In the K00 phase, I will expand the research by utilizing advanced NLP and SP techniques to analyze interview transcripts and audio recordings. By extracting both linguistic and acoustic features—such as word-finding difficulties, reduced vocabulary, pitch, pauses, and vocal quality—through pre-trained models like RoBERTa and Wav2Vec, I aim to predict future cognitive changes in domain-specific cognitive functions. These features will be processed using machine learning models (e.g., random forest regressor, support vector regression, and neural networks) to predict cognitive decline over time. This approach offers a non-invasive, scalable, and cost-effective method for early detection of cognitive impairment, potentially benefiting other at-risk populations, including veterans and older adults exposed to neurotoxic hazards.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $43,980 )
2026	2026	THE RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK	W5510 FRANKS MELVILLE MEMORIAL LIBRARY	STONY BROOK	NY	11794	SUFFOLK	USA	Aging Research	001	2	9/2/2026	NON-COMPETING CONTINUATION	$42,480
2026	2025	THE RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK	W5510 FRANKS MELVILLE MEMORIAL LIBRARY	STONY BROOK	NY	11794	SUFFOLK	USA	Aging Research	000	1	3/4/2026	NEW	$1,500
														Subtotal = $43,980

Issue Date FY: 2025 ( Subtotal = $41,904 )
2025	2025	THE RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK	W5510 FRANKS MELVILLE MEMORIAL LIBRARY	STONY BROOK	NY	11794	SUFFOLK	USA	Aging Research	000	1	9/17/2025	NEW	$41,904
2025	2025	THE RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK	W5510 FRANKS MELVILLE MEMORIAL LIBRARY	STONY BROOK	NY	11794	SUFFOLK	USA	Aging Research	001	1	9/17/2025	NEW	$0
														Subtotal = $41,904

Grand Total All Awards = $85,884

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Using Natural Language Processing and Speech Processing Techniques to Understand and Predict Cognitive Decline

Award Number: F99AG088590

ORGANIZATION: NATIONAL INSTITUTE ON AGING

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: FELLOWSHIP/SCHOLARSHIP/STUDENT LOANS

PERIOD OF PERFORMANCE START DATE: 09/17/2025

PERIOD OF PERFORMANCE END DATE: 09/16/2027

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