Artificial intelligence, speech, and language processing approaches to monitoring Alzheimer's disease: a systematic review

S De la Fuente Garcia, CW Ritchie… - Journal of Alzheimer's …, 2020 - content.iospress.com
Background: Language is a valuable source of clinical information in Alzheimer's disease,
as it declines concurrently with neurodegeneration. Consequently, speech and language …

[HTML][HTML] Applications of artificial intelligence to aid early detection of dementia: a scoping review on current capabilities and future directions

R Li, X Wang, K Lawler, S Garg, Q Bai, J Alty - Journal of biomedical …, 2022 - Elsevier
Abstract Background & Objective With populations aging, the number of people with
dementia worldwide is expected to triple to 152 million by 2050. Seventy percent of cases …

Alzheimer's dementia recognition through spontaneous speech

S Luz, F Haider, S de la Fuente Garcia… - Frontiers in computer …, 2021 - frontiersin.org
The need for inexpensive, safe, accurate and non-invasive biomarkers for Alzheimer's
disease (AD) has motivated much current research (Mandell and Green, 2011). While …

Detecting cognitive decline using speech only: The adresso challenge

S Luz, F Haider, S de la Fuente, D Fromm… - arXiv preprint arXiv …, 2021 - arxiv.org
Building on the success of the ADReSS Challenge at Interspeech 2020, which attracted the
participation of 34 teams from across the world, the ADReSSo Challenge targets three …

A federated learning based privacy-preserving smart healthcare system

J Li, Y Meng, L Ma, S Du, H Zhu, Q Pei… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The rapid development of the smart healthcare system makes the early-stage detection of
dementia disease more user-friendly and affordable. However, the main concern is the …

An assessment of paralinguistic acoustic features for detection of Alzheimer's dementia in spontaneous speech

F Haider, S De La Fuente, S Luz - IEEE Journal of Selected …, 2019 - ieeexplore.ieee.org
Speech analysis could provide an indicator of Alzheimer's disease and help develop clinical
tools for automatically detecting and monitoring disease progression. While previous studies …

An exploration of log-mel spectrogram and MFCC features for Alzheimer's dementia recognition from spontaneous speech

A Meghanani, CS Anoop… - 2021 IEEE spoken …, 2021 - ieeexplore.ieee.org
In this work, we explore the effectiveness of log-Mel spectrogram and MFCC features for
Alzheimer's dementia (AD) recognition on ADReSS challenge dataset. We use three …

[PDF][PDF] Automated Screening for Alzheimer's Dementia Through Spontaneous Speech.

MSS Syed, ZS Syed, M Lech, E Pirogova - Interspeech, 2020 - researchgate.net
Dementia is a neurodegenerative disease that leads to cognitive and (eventually) physical
impairments. Individuals who are affected by dementia experience deterioration in their …

Multimodal inductive transfer learning for detection of Alzheimer's dementia and its severity

U Sarawgi, W Zulfikar, N Soliman, P Maes - arXiv preprint arXiv …, 2020 - arxiv.org
Alzheimer's disease is estimated to affect around 50 million people worldwide and is rising
rapidly, with a global economic burden of nearly a trillion dollars. This calls for scalable, cost …

[PDF][PDF] Using the Outputs of Different Automatic Speech Recognition Paradigms for Acoustic-and BERT-Based Alzheimer's Dementia Detection Through Spontaneous …

Y Pan, B Mirheidari, JM Harris, JC Thompson… - Interspeech, 2021 - isca-archive.org
Exploring acoustic and linguistic information embedded in spontaneous speech recordings
has proven to be efficient for automatic Alzheimer's dementia detection. Acoustic features …