We have recently teamed up Rami Cohen of Technion, Israel Institute of Technology and Yizhar Lavner of Tel-Hai Academic College in order to incorporate their cry detection algorithm in one of the custom apps we are currently developing at our lab.
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“The proposed algorithm is based on two main stages. The first stage involves feature extraction, in which pitch related parameters, MFC (mel-frequency cepstrum) coefficients and short-time energy parameters are extracted from the signal. In the second stage, the signal is classified using k-NN and later verified as a cry signal.”