Edson Cataldo

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This article proposes and evaluates a method to classify vocal aging using artificial neural network (ANN) and support vector machine (SVM), using the parameters extracted from the speech signal as inputs. For each recorded speech, from a corpus of male and female speakers of different ages, the corresponding glottal signal is obtained using an inverse(More)
The vocal cords play an important role on voice production. Air coming from the lungs is forced through the narrow space between the two vocal cords that are set in motion in a frequency that is governed by the tension of the attached muscles. The motion of the vocal cords changes the type of flow, that comes from the lungs, to pulses of air, and as the(More)
The classification of voice diseases has many applications in health, in diseases treatment, and in the design of new medical equipment for helping doctors in diagnosing pathologies related to the voice. This work uses the parameters of the glottal signal to help the identification of two types of voice disorders related to the pathologies of the vocal(More)
The aim of this paper is to use Bayesian statistics to update a probability density function (p.d.f.) related to the tension parameter of the vocal folds, which is one of the main parameters responsible for the changing of the fundamental frequency of a voice signal, generated by a mechanical/mathematical model for producing voiced sounds. Three parameters(More)
— Classification of voice aging has many applications in health care and geriatrics. This work focuses on finding the most relevant parameters to classify voice aging. The most significant parameters extracted from the glottal signal are chosen to identify the voice aging process of men and women. After analyzing their statistics, the chosen parameters are(More)
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