Multilingual Alzheimer’s Dementia Recognition through Spontaneous Speech: A Signal Processing Grand Challenge
Author:
Affiliation:
1. The University of Edinburgh,Usher Institute, Edinburgh Medical School,UK
2. Carnegie Mellon University,Department of Psychology,USA
3. Information Technologies Institute,CERTH,Greece
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10094559/10094560/10433923.pdf?arnumber=10433923
Reference5 articles.
1. Artificial Intelligence, Speech, and Language Processing Approaches to Monitoring Alzheimer’s Disease: A Systematic Review
2. The Natural History of Alzheimer's Disease
3. Causality
4. The Geneva Minimalistic Acoustic Parameter Set (GeMAPS) for Voice Research and Affective Computing
5. An Assessment of Paralinguistic Acoustic Features for Detection of Alzheimer's Dementia in Spontaneous Speech
Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. HAFFormer: A Hierarchical Attention-Free Framework for Alzheimer’s Disease Detection From Spontaneous Speech;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14
2. Alzheimer's disease recognition from spontaneous speech using large language models;ETRI Journal;2024-01-29
3. An Overview of the ADReSS-M Signal Processing Grand Challenge on Multilingual Alzheimer's Dementia Recognition Through Spontaneous Speech;IEEE Open Journal of Signal Processing;2024
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