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http://dx.doi.org/10.14400/JDC.2021.19.12.353

Diagnosis of Parkinson's disease based on audio voice using wav2vec  

Yoon, Hee-Jin (Department of Software convergence, Jangan University)
Publication Information
Journal of Digital Convergence / v.19, no.12, 2021 , pp. 353-358 More about this Journal
Abstract
Parkinson's disease is the second most common degenerative brain disease after Alzheimer's in old age. Symptoms of Parkinson's disease are factors that reduce the quality of life in daily life, such as shaking hands, slowing behavior and cognitive function. Parkinson's disease that can slow the progression of the disease through early diagnosis. To diagnoze Parkinson's disease early, an algorithm was implemented to extract features using wav2vec and to diagnose the presence or absence of Parkinson's disease with deep learning(ANN). As a results of the experiment, the accuracy was 97.47%. It was better than the results of diagnosing Parkinson's disease using the existing neural network. The audio voice file could simply reduce the experiment process and obtain improved results.
Keywords
Parkinson's disease; human audio voice; wav2vec; deep learning; classification;
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