Abstract
In this paper, an automatic voice pathology recognition system is realized. The special features are extracted by the Adaptive Orthogonal Transform method, and to provide their statistical properties we calculated the average, variance, skewness and kurtosis values. The classification process uses two models that are widely used as a classification method in the field of signal processing: Support Vector Machine (SVM) and Multilayer Perceptron (MLP). The proposed system is tested by using a German voice database: the Saarbruecken Voice Database (SVD). The experimental results show that the Adaptive Orthogonal Transform method works perfectly with the Multilayer Perceptron Neural Network, which achieved 98.87% accuracy. On the other hand, the combination of the Adaptive Orthogonal Transform method and Support Vector Machine reached 85.79% accuracy.
Highlights
Signal processing is a science that analyzes and interprets the information contained in a signal
We found that there are several methods widely used for detection and classification of voice pathologies such as Mel-Frequency Cepstral Coefficients (MFCC), Discrete Wavelet Transform method (DWT), Empirical Mode Decomposition (EMD), Multilayer Perceptron (MLP), and Support Vector Machine (SVM)
We propose an automatic voice pathology detection and classification system using the Adaptive Orthogonal Transform method to extract the important features from the input signals with a small training dataset [13]–[15]
Summary
Signal processing is a science that analyzes and interprets the information contained in a signal. It has a great effect on our daily life. The number of people who suffer from voice problems increases, with the percentage being about 25% of the world population [1]. Voice pathology detection is done by an otolaryngologist, known as an ear, nose, and throat doctor, who performs a painless examination to visualize the vocal cords and the larynx, called indirect laryngoscopy [3]. The doctor puts a light source on the forehead and uses a small specific mirror, called a laryngeal mirror [4], to check the larynx and vocal cords. The doctor may ask the patient to make sounds to examine the mobility of the vocal cords, but depending on the suspected cause of hoarseness, other examinations may be prescribed to refine the diagnosis, such as a phoniatric assessment [5], an X-ray [6], or a CT scan
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