Classification of Dysphonic Voices in Parkinson’s Disease with Semi-Supervised Competitive Learning Algorithm

Classification of Dysphonic Voices in Parkinson’s Disease with Semi-Supervised Competitive Learning Algorithm

This article proposes a novel semi-supervised competitive learning (SSCL) algorithm for vocal pattern classifications in Parkinson’s disease (PD). The acoustic parameters of voice records were grouped into the families of jitter, shimmer, harmonic-to-noise, frequency, and nonlinear measures, respect...

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Bibliographic Details
Main Authors: Guidong Bao, Mengchen Lin, Xiaoqian Sang, Yangcan Hou, Yixuan Liu, Yunfeng Wu
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Biosensors
Subjects:
Parkinson’s disease
semi-supervised learning
dysphonia
K-means clustering
competitive learning
k-nearest neighbor
Online Access:https://www.mdpi.com/2079-6374/12/7/502

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