Employing Energy and Statistical Features for Automatic Diagnosis of Voice Disorders

Employing Energy and Statistical Features for Automatic Diagnosis of Voice Disorders

The presence of laryngeal disease affects vocal fold(s) dynamics and thus causes changes in pitch, loudness, and other characteristics of the human voice. Many frameworks based on the acoustic analysis of speech signals have been created in recent years; however, they are evaluated on just one or tw...

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Bibliographic Details
Main Authors: Avinash Shrivas, Shrinivas Deshpande, Girish Gidaye, Jagannath Nirmal, Kadria Ezzine, Mondher Frikha, Kamalakar Desai, Sachin Shinde, Ankit D. Oza, Dumitru Doru Burduhos-Nergis, Diana Petronela Burduhos-Nergis
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Diagnostics
Subjects:
statistical features
inverse filtering
glottal flow
feature selection
voice disorder
wavelet transform
Online Access:https://www.mdpi.com/2075-4418/12/11/2758

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https://www.mdpi.com/2075-4418/12/11/2758

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