Classification of voice aging using ANN and glottal signal parameters

Author

Mendoza, Leonardo Alfredo Forero ; Cataldo, Edson ; Vellasco, Marley ; Silva, Marco Aurélio ; Canón, Alvaro David Orjuela ; De Seixas, Jose Manoel

Author_Institution

Eletrical Eng. Dept., Pontificia Univ. Catolica do Rio de Janeiro, Rio de Janeiro, Brazil

fYear

2010

fDate

15-17 Sept. 2010

Firstpage

1

Lastpage

5

Abstract

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 used as entries to a neural network to classify male and female Brazilian speakers in three different age groups: young (from 15 to 30 years old), adult (from 31 to 60 years old), and senior (from 61 to 90 years old). The corpus used for this work was composed by one hundred and twenty Brazilian speakers (both males and females) of different ages. As compared to similar works, we employ a larger corpus and obtain a superior classification rate.

Keywords

geriatrics; health care; neural nets; signal classification; speech synthesis; ANN; Brazilian speaker; artificial neural network; geriatric; glottal signal parameters; health care; voice aging classification; voice aging process; Aging; Artificial neural networks; Databases; Dispersion; Feature extraction; Filtering; Power harmonic filters; artificial neural networks ANN; glottal signal parameters; inverse filtering;

fLanguage

English

Publisher

ieee

Conference_Titel

ANDESCON, 2010 IEEE

Conference_Location

Bogota

Print_ISBN

978-1-4244-6740-2

Type

conf

DOI

10.1109/ANDESCON.2010.5633362

Filename

5633362