Detection of Alzheimer’s Disease Through Speech Features and Machine Learning Classifiers

Author:

Gulapalli Ajay Sankar,Mittal Vinay Kumar

Publisher

Springer Nature Singapore

Reference49 articles.

1. Honma, S.M., Gorno-Tempini, M.L., Miller, B.L., Vossel, K.A., Nagarajan, S.S., Houde, J.F.: Abnormal vocal behavior predicts executive and memory deficits in Alzheimer’s disease. Neurobiol. Aging 52, 71–80 (Apr 2017)

2. Fraser, K.C., Rudzicz, F., Hirst, G.: “Detecting late-life depression in Alzheimer's disease through analysis of speech and language”. Linguistic Signal to Clinical Reality, pp. 1–11, San Diego, California (16 Jun 2016)

3. Greta, S., Ildiko, H., Veronika, V., Janos, K., Magdolna, P.: Speaking in Alzheimer’s disease, is that an early sign? importance of changes in language abilities in Alzheimer’s disease. Frontiers Aging Neurosci. 7, 195 (2015)

4. Zhang, J., Pan, Z., Gui, C., Xue, T., Lin, Y., Zhu, J., Cui, D.: Analysis on speech signal features of manic patients. J. Psychiatric Res. 98, 59–63 (2018)

5. Mohanta, A., Mittal, V.K.: “Analyzing autism speech of children in english vowels regions by analysis of changes in production features”, in Proc 15th International Conference on Natural Language Processing (ICON 2018), Punjabi University, Patiala, India (Dec 2018)

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