Statistical method for classifying cries of baby based on pattern recognition of power spectrum
by Xinping Wang, Tomomasa Nagashima, Kentarou Fukuta, Yoshifumi Okada, Masahiro Sawai, Hidenori Tanaka, Takashi Uozumi
International Journal of Biometrics (IJBM), Vol. 2, No. 2, 2010

Abstract: We develop a novel method applicable to classify the causes of crying infant based on pattern recognition of power spectrum of the cry. In our frame relied on F-value, it is available in power spectrum to order a statistical significance of frequency points which will contribute to the classification of cries. We verify performance of the method by taking the painful cries of infant with the genetic disease (ADEL). The result of our method achieves an excellent prediction. We also give a discussion on the relation between the set of frequency points extracted and the formants of cries.

Online publication date: Wed, 24-Feb-2010

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