doctoralThesis
Sistema inteligente para diagnóstico de patologias na laringe utilizando máquinas de vetor de suporte
Fecha
2010-07-23Registro en:
ALMEIDA, Náthalee Cavalcanti de. Sistema inteligente para diagnóstico de patologias na laringe
utilizando máquinas de vetor de suporte. 2010. 119 f. Tese (Doutorado em Automação e Sistemas; Engenharia de Computação; Telecomunicações) - Universidade Federal do Rio Grande do Norte, Natal, 2010.
Autor
Almeida, Náthalee Cavalcanti de
Resumen
The human voice is an important communication tool and any disorder of the
voice can have profound implications for social and professional life of an individual.
Techniques of digital signal processing have been used by acoustic analysis of vocal
disorders caused by pathologies in the larynx, due to its simplicity and noninvasive
nature. This work deals with the acoustic analysis of voice signals affected by
pathologies in the larynx, specifically, edema, and nodules on the vocal folds. The
purpose of this work is to develop a classification system of voices to help pre-diagnosis
of pathologies in the larynx, as well as monitoring pharmacological treatments and after
surgery. Linear Prediction Coefficients (LPC), Mel Frequency cepstral coefficients
(MFCC) and the coefficients obtained through the Wavelet Packet Transform (WPT)
are applied to extract relevant characteristics of the voice signal. For the classification
task is used the Support Vector Machine (SVM), which aims to build optimal
hyperplanes that maximize the margin of separation between the classes involved. The
hyperplane generated is determined by the support vectors, which are subsets of points
in these classes. According to the database used in this work, the results showed a good
performance, with a hit rate of 98.46% for classification of normal and pathological
voices in general, and 98.75% in the classification of diseases together: edema and
nodules