Identification of pain from infant cry vocalizations using artificial neural networks (ANNs)

Marco Petroni; Alfred S. Malowany; C. Celeste Johnston; Bonnie J. Stevens

doi:10.1117/12.205186

6 April 1995 Identification of pain from infant cry vocalizations using artificial neural networks (ANNs)

Marco Petroni, Alfred S. Malowany, C. Celeste Johnston, Bonnie J. Stevens

Proceedings Volume 2492, Applications and Science of Artificial Neural Networks; (1995) https://doi.org/10.1117/12.205186
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

Abstract

The analysis of infant cry vocalizations has been the focus of a number of efforts over the past thirty years. Since the infant cry is one of the only means that an infant has for communicating with its care-giving environment, it is thought that information regarding the state of an infant, such as hunger or pain, can be determined from an infant's cry. To date, research groups have determined that adult listeners can differentiate between different types of cries auditorialy, and at least one group has attempted to automate this classification process. This paper presents the results of another attempt at automating the discrimination process, this time using artificial neural networks (ANNs). The input data consists of successive frames of one or two parametric representations generated from the first second of a cry following the application of either an anger, fear, or pain stimulus. From tests conducted to date, it is determined that ANNs are a useful tool for cry classification and merit further study in this domain.

Citation Download Citation

Marco Petroni, Alfred S. Malowany, C. Celeste Johnston, and Bonnie J. Stevens "Identification of pain from infant cry vocalizations using artificial neural networks (ANNs)", Proc. SPIE 2492, Applications and Science of Artificial Neural Networks, (6 April 1995); https://doi.org/10.1117/12.205186

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