Abstract:
:Alzheimer disease and other dementias have become the 7th cause of death worldwide. Still lacking a cure, an early detection of the disease in order to provide the best intervention is crucial. To develop an assessment system for the general public, speech analysis is the optimal solution since it reflects the speaker's cognitive skills abundantly and data collection is relatively inexpensive compared with brain imaging, blood testing, etc. While most of the existing literature extracted statistics-based features and relied on a feature selection process, we have proposed a novel Feature Sequence representation and utilized a data-driven approach, namely, the recurrent neural network to perform classification in this study. The system is also shown to be fully-automated, which implies the system can be deployed widely to all places easily. To validate our study, a series of experiments have been conducted with 120 speech samples, and the score in terms of the area under the receiver operating characteristic curve is as high as 0.838.
journal_name
Sci Repjournal_title
Scientific reportsauthors
Chien YW,Hong SY,Cheah WT,Yao LH,Chang YL,Fu LCdoi
10.1038/s41598-019-56020-xsubject
Has Abstractpub_date
2019-12-20 00:00:00pages
19597issue
1issn
2045-2322pii
10.1038/s41598-019-56020-xjournal_volume
9pub_type
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