Automated language analysis for Alzheimer’s disease and frontotemporal dementia in Latino and English speakers
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-11553470 · Data updated 2026-11-12
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.
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) | $139,133 |
| NIH project number | 3R01AG075775-04S5 |
| Project ID | NIH-11553470 on NIH RePORTER |
Who could benefit from this research
✓Could help
Individuals with or at risk for Alzheimer's disease or frontotemporal dementia, including Spanish-speaking and English-speaking adults across diverse backgrounds.
✕Less likely to help
People without cognitive impairment or with conditions outside AD/FTD are unlikely to benefit from this diagnostic tool.
What this research studies
This project creates a new, computer-based language analysis framework that uses speech data from diverse participants to detect and predict cognitive disruptions related to Alzheimer’s disease and frontotemporal dementia. It will collect natural speech samples and extract acoustic and linguistic features, then apply machine learning to separate disease signals from socio-biological factors like language, race, and bilingualism. The study plans to enroll about 2,740 participants, including Spanish and English speakers across multiple countries and the US, to ensure the approach works across diverse groups. By comparing with standard diagnostic measures, the work aims to produce a robust, scalable tool that remains valid across languages and dialects. The ultimate goal is to improve access to accurate diagnosis for Latino populations who face barriers to current testing.
Why it matters
Potential benefit: If successful, patients could receive earlier and more accessible diagnosis through a low-cost, language-adapted tool.
How similar studies have gone: Past work shows promise for language-based markers, but few studies have large, diverse Latino/English cohorts or cross-language validation; this project builds on emerging evidence with a broader, more inclusive approach.
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 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 for Alzheimer's and frontotemporal dementia in Latino and English-speaking communities
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.
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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.