The change in voice quality is affected by many of voice disorders that coming from pathogical
conditions of voice generation organs. The aim of this study is to help that the clinicians could be
diagnosed about voice disorders with non-invasive based analysis. In our work, amplitude
perturbation quotient, pitch period perturbation quotient, degree of unvoiceness, Teager Energy
Operators averages of wavelet transform coefficients, and higher-order statistics parameters have
formed the feature vectors. The voice segments belonging to different pathological or normal classes
were classified by backpropagation based multilayer perceptron networks. In backpropagation based
multilayer perceptron networks, resilient, scaled-conjugate gradient, and Brodyen-Fletcher-GoldfarbShanno
learning algorithms were used in training. According to the results of the simulation studies,
scaled-conjugate gradient algorithm gave the best results.
Voice analysis Acoustic parameters Wavelet transform Higher-order statistics Classification Artificial neural networks
conditions of voice generation organs. The aim of this study is to help that the clinicians could be diagnosed about voice disorders with non-invasive based analysis. In our work, amplitude perturbation quotient, pitch period perturbation quotient, degree of unvoiceness, Teager Energy Operators averages of wavelet transform coefficients, and higher-order statistics parameters have formed the feature vectors. The voice segments belonging to different pathological or normal classes were classified by backpropagation based multilayer perceptron networks. In backpropagation based multilayer perceptron networks, resilient, scaled-conjugate gradient, and Brodyen-Fletcher-Goldfarb- Shanno learning algorithms were used in training. According to the results of the simulation studies, scaled-conjugate gradient algorithm gave the best results
Ses analizi Akustik parametreler Dalgacık dönüşümü Yüksek dereceli istatistikler Sınıflandırma Yapay sinir ağları
Diğer ID | JA56HG82JM |
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Bölüm | Araştırma Makalesi |
Yazarlar | |
Yayımlanma Tarihi | 1 Ocak 2012 |
Yayımlandığı Sayı | Yıl 2012 Cilt: 14 Sayı: 1 |
Dokuz Eylül Üniversitesi, Mühendislik Fakültesi Dekanlığı Tınaztepe Yerleşkesi, Adatepe Mah. Doğuş Cad. No: 207-I / 35390 Buca-İZMİR.