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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Detalles Bibliográficos
Autores principales: Bao, Guidong, Lin, Mengchen, Sang, Xiaoqian, Hou, Yangcan, Liu, Yixuan, Wu, Yunfeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9312485/
https://www.ncbi.nlm.nih.gov/pubmed/35884305
http://dx.doi.org/10.3390/bios12070502

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9312485/
https://www.ncbi.nlm.nih.gov/pubmed/35884305
http://dx.doi.org/10.3390/bios12070502

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