With the rapid aging of the world's population, the global burden of agingrelated mental
disorders, such as Alzheimer's dementia (AD), is also on the rise. Unfortunately global …

Alzheimer's dementia (AD) is a chronic neurodegenerative illness that manifests in a
gradual decline of cognitive function. Early identification of AD is essential for managing the …

This Signal Processing Grand Challenge (SPGC) targets a difficult automatic prediction
problem of societal and medical relevance, namely, the detection of Alzheimer's Dementia …

Developing a possible diagnostic test for Alzheimer's disease (AD) based on speech is used
throughout this book to illustrate the application of the machine learning methods we …

Automated techniques to detect Alzheimer's Dementia through the use of audio recordings
of spontaneous speech are now available with varying degrees of reliability. Here, we …

This paper is a submission to the Alzheimer's Dementia Recognition through Spontaneous
Speech (ADReSS) challenge, which aims to develop methods that can assist in the …

Automatic screening of Alzheimer's Dementia (AD) can have significant impact on society
and the well-being of the patients. Early detection of AD from spontaneous speech offers …

Alzheimer's disease (AD) represents a major problem for society and a heavy burden for
those affected. The study of changes in speech offers a potential means for large-scale AD …

Introduction: Research related to the automatic detection of Alzheimer's disease (AD) is
important, given the high prevalence of AD and the high cost of traditional diagnostic …

We explore ways to use speech data to screen for indications of Alzheimer's dementia (AD).
In particular, we describe our approach to the ICASSP 2023 Signal Processing Grand …