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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Mar 22, 2025
Date Accepted: Sep 5, 2025

The final, peer-reviewed published version of this preprint can be found here:

Automated Speech Markers of Alzheimer Dementia: Test of Cross-Linguistic Generalizability

Pérez-Toro PA, Ferrante F, Pérez G, Tee BL, de Leon J, Nöth E, Schuster M, Maier A, Slachevsky A, Gorno-Tempini ML, Ibáñez A, Orozco-Arroyave JR, García A

Automated Speech Markers of Alzheimer Dementia: Test of Cross-Linguistic Generalizability

J Med Internet Res 2025;27:e74200

DOI: 10.2196/74200

PMID: 41091545

PMCID: 12572752

Automated speech markers of Alzheimer’s dementia: A test of cross-linguistic generalizability

  • Paula Andrea Pérez-Toro; 
  • Franco Ferrante; 
  • Gonzalo Pérez; 
  • Boon Lead Tee; 
  • Jessica de Leon; 
  • Elmar Nöth; 
  • Maria Schuster; 
  • Andreas Maier; 
  • Andrea Slachevsky; 
  • Maria Luisa Gorno-Tempini; 
  • Agustín Ibáñez; 
  • Juan Rafael Orozco-Arroyave; 
  • Adolfo García

ABSTRACT

Background:

Automated speech and language analysis can reveal early markers of Alzheimer’s disease (AD). However, most studies target uninterpretable features in Anglophone samples only, overlooking clinical utility and cross-linguistic validity.

Objective:

Here we aimed to tackle both gaps by examining whether interpretable speech and language markers of AD generalize between two typologically different languages.

Methods:

We analyzed semi-spontaneous recordings from 211 participants, including English- and Spanish-speaking patients and controls. We automatically extracted speech timing features (indicating semantic memory retrieval effort) and vocabulary selection features (capturing semantic memory navigation patterns). Classifiers trained on English-speaking participants were tested in a within-language setting (involving English-speaking patients and controls) and in a between-language setting (involving Spanish-speaking patients and controls).

Results:

AD detection was maximal upon combining timing and vocabulary features in the within-language setting (AUC = .88) and when considering timing features in the between-language setting (AUC = .75). Timing features also predicted cognitive outcomes in both settings.

Conclusions:

Automated proxies of semantic memory processes can yield interpretable AD markers within and across languages.


 Citation

Please cite as:

Pérez-Toro PA, Ferrante F, Pérez G, Tee BL, de Leon J, Nöth E, Schuster M, Maier A, Slachevsky A, Gorno-Tempini ML, Ibáñez A, Orozco-Arroyave JR, García A

Automated Speech Markers of Alzheimer Dementia: Test of Cross-Linguistic Generalizability

J Med Internet Res 2025;27:e74200

DOI: 10.2196/74200

PMID: 41091545

PMCID: 12572752

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