What is it about?
Ten Linear Predictive Coefficients (LPCs) plus a nonlinear one stated as Bilinear Intermittent Factor (BIF) per 20ms analysis window for 40 normal and loss hearing (deaf) newborn cries each have been extracted for classification by using the Expectation Maximization (EM) algorithm over a Mixture of Experts (ME) .
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Why is it important?
Because it is an easier manner to obtain features in time-domain and classify them as well.
Perspectives
It is possible to extract less features by orthogonal decomposition and therefore employ a simpler classifier.
Gibran Etcheverry
Universidad de las Americas Puebla
Read the Original
This page is a summary of: Newborn cry nonlinear features extraction and classification, Journal of Intelligent & Fuzzy Systems, May 2018, IOS Press,
DOI: 10.3233/jifs-169510.
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