Automated language analysis for Alzheimer's and frontotemporal dementia in Latino and English-speaking communities
Official title: An automated machine learning approach to language changes in Alzheimer’s disease and frontotemporal dementia across Latino and English-speaking populations
Funded at University of California, San Francisco · NIH-11553466 · Data updated 2026-11-12
A low-cost, computer-based language analysis method is being developed to help identify Alzheimer’s disease and frontotemporal dementia in Latino and English-speaking people.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California, San Francisco NIH-funded |
| Lab location | 1 site (San Francisco, United States) |
| Project start | August 15, 2023 |
| Project end | June 30, 2028 |
| Funding year | 2026 |
| Award (this year) | $126,773 |
| NIH project number | 3R01AG075775-04S2 |
| Project ID | NIH-11553466 on NIH RePORTER |
Who could benefit from this research
✓Could help
Adults (and older adults) who are Latinos and English speakers, with diagnosed AD, FTD, or no cognitive impairment, across multiple countries and U.S. settings.
✕Less likely to help
Individuals without cognitive concerns or those outside the target linguistic and cultural groups may not benefit directly.
What this research studies
This project will create a computer-based system that uses speech and language patterns to detect and predict neurodegenerative changes in diverse Latino and English-speaking populations. It will collect natural speech data from thousands of participants, extract acoustic and linguistic features, and apply machine learning to differentiate Alzheimer’s disease from frontotemporal dementia and from healthy aging. The approach emphasizes cultural and socio-biological differences to ensure the tools work well across language and dialect groups. By focusing on scalable, accessible testing, the study aims to improve early and accurate diagnosis where traditional methods are less affordable. The research will be conducted at UC San Francisco with a large, diverse cohort to validate the framework across languages and ethnic backgrounds.
Why it matters
Potential benefit: If successful, the method could enable earlier, more accurate diagnosis of AD and FTD in diverse populations using affordable speech-based tests.
How similar studies have gone: Previous work shows promise for speech-based markers in neurodegenerative diseases, but validation across diverse Latino and English-speaking populations is limited, making this study novel.
Where this research is happening
-
University of California, San Francisco
San Francisco, United States Active
Researchers
- Principal investigator: Gorno Tempini, Maria Luisa — University of California, San Francisco
- Study coordinator: Gorno Tempini, Maria Luisa
Related research
Other NIH-funded projects on the same topics.
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Automated language analysis for Alzheimer’s disease and frontotemporal dementia in Latino and English speakers
A low-cost, automated speech and language analysis tool is being developed to help identify Alzheimer’s disease or frontotemporal dementia in Latino and English-speaking people.
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Automated language analysis for Alzheimer’s and frontotemporal dementia across Latino and English-speaking groups
A low-cost, automated language study aims to help diagnose and understand Alzheimer’s and FTD in diverse Spanish- and English-speaking communities.
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Automated language analysis to help diagnose Alzheimer’s and frontotemporal dementia in Latino and English speakers
A low-cost, computer-based method analyzes speech and language to help identify Alzheimer’s disease or frontotemporal dementia in Latino and English-speaking people.
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Automated language analysis to detect Alzheimer’s and frontotemporal dementia in Latino and English-speaking adults
A low-cost, computer-based language and speech analysis tool will help identify Alzheimer’s disease and frontotemporal dementia in Latino and English-speaking adults.
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Automated language analysis for Alzheimer’s disease and frontotemporal dementia in Latino and English speakers
A machine learning approach analyzes speech and language from Latino and English-speaking people to help detect Alzheimer’s disease and related dementias.
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Automated speech and language detection for Alzheimer’s and frontotemporal dementia in Spanish and English speakers
This project uses automated speech and language analysis to help spot signs of Alzheimer’s disease and frontotemporal dementia in Spanish- and English-speaking people, with special focus on Latino communities.
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.