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Circuits, Systems, and Signal Processing

, Volume 37, Issue 1, pp 232–254 | Cite as

Significance of Higher-Order Spectral Analysis in Infant Cry Classification

  • Anshu Chittora
  • Hemant A. Patil
Article
  • 176 Downloads

Abstract

In this paper, higher-order spectral analysis is applied to infant cry signals for classification of normal infant cries from pathological infant cries. From the family of higher-order spectra, bispectrum is considered for the proposed task. Bispectrum is the Fourier transform of the third-order cumulant function. To extract features from the bispectrum, application of higher-order singular value decomposition theorem is proposed. Experimental results show the average classification accuracy of \({82.44} \pm {4.03}{ \%}\) and Matthew’s correlation coefficient (MCC) of 0.62 with proposed bispectrum features. In all of the experiments reported in this paper, support vector machine with radial basis function kernel is used as the pattern classifier. Performance of the proposed features is also compared with the state-of-the-art methods such as linear frequency cepstral coefficients, Mel frequency cepstral coefficients, perceptual linear prediction coefficients, linear prediction coefficients, linear prediction cepstral coefficients and perceptual linear prediction cepstral coefficients, and is found to be better than that given by these feature sets. The proposed bispectrum-based features are shown to be robust under signal degradation or noisy conditions at various SNR levels. Performance in the presence of noise is compared with the state-of-the-art spectral feature sets using MCC scores. In addition, effectiveness of cryunit segmentation in normal and pathological infant cry classification task is reported.

Keywords

Bispectrum Cumulants Higher-order singular value decomposition theorem Higher-order spectral analysis Support vector machine classifier 

Notes

Acknowledgements

The authors would like to thank authorities of DA-IICT, Gandhinagar, Department of Electronics and Information Technology (DeitY), New Delhi, and Department of Science and Technology (DST), New Delhi, for providing necessary resources to carry out this research work.

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Dhirubhai Ambani Institute of Information and Communication TechnologyGandhinagarIndia

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