Voice Disorders Detection Through Multiband Cepstral Features of Sustained Vowel

xlomafota13 shared this article with you from Inoreader Voice Disorders Detection Through Multiband Cepstral Features of Sustained Vowel Via Journal of Voice This study aims to detect voice disorders related to vocal fold nodule, Reinke's edema and neurological pathologies through multiband cepstral features of the sustained vowel /a/. Detection is performed between pairs of study groups and multiband analysis is accomplished using the wavelet transform. For each pair of groups, a parameters selection is carried out. Time series of the selected parameters are used as input for four classifiers with leave-one-out cross validation. Classification accuracies of 100% are achieved for all pairs including the control group, surpassing the state-of-art methods based on cepstral features, while accuracies higher than 88.50% are obtained for the pathological pairs. View on the web Inoreader. Take back control of your news feed. Follow us on Twitter and Facebook.