Jul 28, 2016 · Abstract: In our study we present a method to identity pathological voices using Support Vector Machines (SVM). Speech signals were sampled ...
In our study we present a method to identity pathological voices using Support Vector Machines (SVM). Speech signals were sampled from the sustained vowel ...
Nov 19, 2021 · This paper presents a voice pathology detection system based on a different number of voice signals. In this work, the voice signals for the ...
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Jun 30, 2024 · The study introduces MEEL (Mel-Frequency Energy Line) features as a new set of acoustic properties for classifying diseased voices.
This paper proposed a support vector machine (SVM) based classification method to identify diversified pathological voices. Sound signals were sampled from ...
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Abstract—In voice pathology detection system, machine learning algorithms play an important role in the classification process.
A voice pathology detection system based on a different number of voice signals and the Support Vector Machine (SVM) is used to classify the voice signals ...
The classification of pathological voice from normal voice is implemented using Support Vector Machine (SVM) and Radial Basis Functional Neural Network (RBFNN).
In this paper it is shown that the scheme proposed fed with short-term cepstral and noise parameters can be applied for the detection of voice impairments with ...
... Support Vector Machines (SVM) classify healthy and pathological voices. The evaluation shows SVM achieves 84.37% accuracy, 90.90% specificity, and 80.95 ...