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Mel-frequency cepstrum coefficients extraction from infant cry for classification of normal and pathological cry with feed-forward neural networks

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2 Author(s)
Garcia, J.O. ; Instituto Nacional de Astrofisica, Opt. y Electron., Puebla, Mexico ; Reyes Garcia, C.A.

This work presents the development of an automatic recognition system of infant cry, with the objective to classify two types of cry: normal and pathological cry from deaf babies. In this study, we used acoustic characteristics obtained by the mel-frequency cepstrum technique and as a classifier a feedforward neural network that was trained with several learning methods, resulting in a better scaled conjugate gradient algorithm. Current results are shown, which, at the moment, are very encouraging with an accuracy up to 97.43%.

Published in:

Neural Networks, 2003. Proceedings of the International Joint Conference on  (Volume:4 )

Date of Conference:

20-24 July 2003