Early Dementia Detection Using Multiple Spontaneous Speech Prompts: The PROCESS Challenge

TL;DR

This paper introduces the PROCESS challenge, providing a new speech corpus and baseline models aimed at early detection of dementia through spontaneous speech analysis.

Contribution

It presents a novel speech dataset with neurologist-designed prompts and baseline models for early dementia detection, advancing research in this area.

Findings

Baseline F1-score of 55.0% on classification

Baseline RMSE of 2.98 on regression

New corpus with neurologist-designed prompts

Abstract

Dementia is associated with various cognitive impairments and typically manifests only after significant progression, making intervention at this stage often ineffective. To address this issue, the Prediction and Recognition of Cognitive Decline through Spontaneous Speech (PROCESS) Signal Processing Grand Challenge invites participants to focus on early-stage dementia detection. We provide a new spontaneous speech corpus for this challenge. This corpus includes answers from three prompts designed by neurologists to better capture the cognition of speakers. Our baseline models achieved an F1-score of 55.0% on the classification task and an RMSE of 2.98 on the regression task.