Automatic speech analysis for the assessment of patients with predementia and Alzheimer's disease

By A. König, Aharon Satt, Alexander Sorin, Ron Hoory, Orith Toledo-Ronen, A. Derreumaux, Valeria Manera, F. Verhey, P. Aalten, P. Robert and 1 more. Alzheimer's & Dementia, 2015

381 citations recorded by the source corpus.

To evaluate the interest of using automatic speech analyses for the assessment of mild cognitive impairment (MCI) and early‐stage Alzheimer's disease (AD).

Subfields: Artificial Intelligence, Experimental and Cognitive Psychology, Physiology

View Paper: https://www.semanticscholar.org/paper/9bbcf941d8b10dc17a99ac91d4e586b70d93591c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Tong Niu
2. Mohit Bansal
3. Sweta Karlekar
4. Caiming Xiong
5. Jianfeng Gao
6. Douwe Kiela
7. Zhe Gan
8. Kevin Gimpel

In Experimental and Cognitive Psychology

1. Mohit Bansal

Citations in the corpus

• Detecting Linguistic Characteristics of Alzheimer’s Dementia by Interpreting Neural Models (2018, methodology): “Language-based Alzheimer’s Detection: Previous works using language to detect AD relied mainly on hand-crafted features from transcripts (Orimaye et al., 2017, 2015), occasionally using acoustic data (König et al., 2015; Rudzicz et al., 2014).”