Cognitive Decline Detection using DLB Extraction Pipelines

The Prediction and Recognition of Cognitive Decline through Spontaneous Speech (PROCESS) Signal Processing Grand Challenge focuses on detecting dementia by analyzing spontaneous speech production. The challenge proposes a classification task to distinguish between subjects categorized as healthy controls, mild cognitive impairment, and dementia. Our team tackled this task by leveraging Digital Linguistic Biomarkers (DLBs) extracted from speech. Our system outperformed over 100 competing systems, earning us first place in the classification task.

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Publication Details

Published
2025-03-12
DOI
https://doi.org/10.1109/icassp49660.2025.10890866
Primary Topic
Reservoir Engineering and Simulation Methods
Type
article
Field-Weighted Citation Impact
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article

Cognitive Decline Detection using DLB Extraction Pipelines

Marcello Ferro, Gloria Gagliardi, Shibingfeng Zhang, Fabio Tamburini et al.
Reservoir Engineering and Simulation Methods
article

Cognitive Decline Detection using DLB Extraction Pipelines

Marcello Ferro, Gloria Gagliardi, Shibingfeng Zhang, Fabio Tamburini, Nadia Khlif
article en

Abstract

The Prediction and Recognition of Cognitive Decline through Spontaneous Speech (PROCESS) Signal Processing Grand Challenge focuses on detecting dementia by analyzing spontaneous speech production. The challenge proposes a classification task to distinguish between subjects categorized as healthy controls, mild cognitive impairment, and dementia. Our team tackled this task by leveraging Digital Linguistic Biomarkers (DLBs) extracted from speech. Our system outperformed over 100 competing systems, earning us first place in the classification task.

Institute for Computational Linguistics “A. Zampolli” (IT), University of Bologna (IT)
Openalex Percentile: Top 95%
Reservoir Engineering and Simulation Methods
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Cognitive Decline Detection using DLB Extraction Pipelines — Marcello Ferro, Gloria Gagliardi, et al. · (2025) | TGRS Research Map | TGRS