A Hybrid System for Automatic Infant Cry Recognition I

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Author(s): Carlos Alberto Reyes-García (Instituto Nacional de Astrofísica Óptica y Electrónica, Mexico), Ramon Zatarain (Instituto Tecnologico de Culiacan, Mexico), Lucia Barron (Instituto Tecnologico de Culiacan, Mexico)and Orion Fausto Reyes-Galaviz (Universidad Autónoma de Tlaxcala, Mexico)
Copyright: 2009
Pages: 7
Source title: Encyclopedia of Artificial Intelligence
Source Author(s)/Editor(s): Juan Ramón Rabuñal Dopico (University of A Coruña, Spain), Julian Dorado (University of A Coruña, Spain)and Alejandro Pazos (University of A Coruña, Spain)
DOI: 10.4018/978-1-59904-849-9.ch127

Keywords: Artificial Intelligence / Computer Science & IT / Information Science Reference

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Abstract

Crying in babies is a primary communication function, governed directly by the brain; any alteration on the normal functioning of the babies’ body is reflected in the cry (Wasz-Höckert, et al, 1968). Based on the information contained in the cry’s wave, the infant’s physical state can be determined; and even pathologies in very early stages of life detected (Wasz-Höckert, et al, 1970). To perform this detection, a Fuzzy Relational Neural Network (FRNN) is applied. The input features are represented by fuzzy membership functions and the links between nodes, instead of weights, are represented by fuzzy relations (Reyes, 1994). This paper, as the first of a two parts document, describes the Infant Cry Recognition System´s architecture as well as the FRNN model. Implementation and testing are reported in the complementary paper.

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A Hybrid System for Automatic Infant Cry Recognition I

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