The extraction of acoustic features of infant cry for emotion detection based on pitch and formants

In this paper, we present the development of a system for translating the normal infant cries, which come from pain, sadness, hunger, fear and anger cry sounds, of ages from one day up to nine months old. The aim of this research is to analyse the sound of the crying infant, and to derive the reason why the infant is crying. In this experiment we used acoustic features characteristic determined by pitch and formants. The acoustic feature vectors are then clustered using K-means algorithm to determine the class or the reason of the cry. The proposed system perform well with the maximum accuracy of 90%.