NIH-funded research R01 grant

Automated speech and language detection for Alzheimer’s and frontotemporal dementia in Spanish 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-11404660 · Data updated 2026-11-12

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.

More s Disease research and trials

Quick facts

Grant typeR01 grant
Study typeNIH-funded research
Funding institutionUniversity of California, San Francisco
NIH-funded
Lab location1 site (San Francisco, United States)
Project startAugust 15, 2023
Project endJune 30, 2028
Funding year2025
Award (this year)$136,781
NIH project number3R01AG075775-03S6
Project IDNIH-11404660 on NIH RePORTER

Who could benefit from this research

Could help

Ideal participants include Spanish-speaking adults from the participating Latin American countries and English-speaking adults in the US who have memory or language concerns, have been diagnosed with Alzheimer’s disease or frontotemporal dementia, or are healthy controls willing to provide speech samples.

Less likely to help

People who cannot produce usable speech (for example, severe nonverbal aphasia), those who do not speak Spanish or English, or those with conditions not targeted by the project are unlikely to benefit directly from this work.

What this research studies

You would provide short samples of natural speech that are recorded and converted into acoustic and language data. The team uses machine and deep learning to find patterns in sound waves and word use that link to Alzheimer’s disease or frontotemporal dementia. They are collecting a large, diverse group of participants from five Latin American countries and the United States to make sure the tools work across languages, dialects, and backgrounds. The project also compares these speech markers with standard clinical measures and accounts for factors like bilingualism, sex, and brain profiles.

Why it matters

Potential benefit: If successful, this could lead to low-cost, scalable language-based tools for earlier and more accessible detection and monitoring of dementia across languages and cultures.

How similar studies have gone: Previous smaller studies using automated speech and language analysis have shown promising signals for detecting dementia, but large multilingual and culturally validated efforts like this are relatively new.

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.

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page.
Last reviewed 2026-11-14 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.