Advertisement

A Cry-Based Babies Identification System

  • Ali Messaoud
  • Chakib Tadj
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6134)

Abstract

Human biological signals convey precious information about the physiological and neurological state of the body. Crying is a vocal signal through which babies communicate their needs to their parents who should then satisfy them properly. Most of the researches dealing with infant’s cry intend mainly to establish a relationship between the acoustic properties of a cry and the state of the baby such as hunger, pain, illness and discomfort. In this work, we are interested in recognizing babies only by analyzing their cries through the use of an automatic analysis and recognition system using a real cry database.

Keywords

Infant cry classification neural network acoustic features 

References

  1. 1.
    LaGasse, L.L., Neal, A.R., Lester, B.M.: Assessment of infant cry: Acoustic cry analysis and parental perception. Mental Retardation and Developmental Disabilities Research Reviews 11, 83–93 (2005)CrossRefGoogle Scholar
  2. 2.
    Wood, R.M., Gustafson, G.E.: Infant Crying and Adults’ Anticipated Caregiving Responses: Acoustic and Contextual Influences. Child Development 72, 1287–1300 (2001)CrossRefGoogle Scholar
  3. 3.
    Protopapas, A.: Perceptual differences in infant cries revealed by modifications of acoustic features. The Journal of the Acoustical Society of America 102, 3723–3734 (1997)CrossRefGoogle Scholar
  4. 4.
    Linwood, A.: Crying and Fussing in an Infant. Gale Encyclopedia of Children’s Health: Infancy through Adolescence. Thomson Gale (2006)Google Scholar
  5. 5.
    Fuller, B.F., Keefe, M.R., Curtin, M., Garvin, B.J.: Acoustic Analysis of Cries from “Normal” and “Irritable” Infants. West J. Nurs. Res. 16, 253 (1994)CrossRefGoogle Scholar
  6. 6.
    Goberman, A.M., Robb, M.P.: Acoustic characteristics of crying in infantile laryngomalacia. Logopedics Phoniatrics Vocology 30, 79–84 (2005)CrossRefGoogle Scholar
  7. 7.
    Green, J.A., Gustafson, G.E., McGhie, A.C.: Changes in Infants’ Cries as a Function of Time in a Cry Bout. Child Development 69, 271–279 (1998)Google Scholar
  8. 8.
    Galaviz, O.F.R.: Infant cry classification to identify hypo acoustics and asphyxia comparing an evolutionary-neural system with a neural network system. In: Gelbukh, A., de Albornoz, Á., Terashima-Marín, H. (eds.) MICAI 2005. LNCS (LNAI), vol. 3789, pp. 949–958. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  9. 9.
    Orozco, J., Garcia, C.A.R.: Detecting pathologies from infant cry applying scaled conjugate gradient neural networks. In: Proc. European Symposium on Artificial Neural Networks, pp. 349–354. d-side publi, Bruges-Belgium (2003)Google Scholar
  10. 10.
    Ortiz, S.D.C.: A radial basis function network oriented for infant cry classification. In: Sanfeliu, A., Martínez Trinidad, J.F., Carrasco Ochoa, J.A. (eds.) CIARP 2004. LNCS, vol. 3287, pp. 374–380. Springer, Heidelberg (2004)Google Scholar
  11. 11.
    Xu, M., Duan, L.-Y., Cai, J., Chia, L.-T., Xu, C., Tian, Q.: HMM-Based Audio Keyword Generation. pp. 566-574 (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Ali Messaoud
    • 1
  • Chakib Tadj
    • 1
  1. 1.Laboratoire de Traitement de l’Information et des SignauxÉcole de Technologie SupérieureMontréalCanada

Personalised recommendations