Analysis on Emotion Detection for Infant Cry

Abstract

Crying is an infant behavior, a part of behavioral system in human which assures persuade of the helpless neonate by eliciting others to meet their basic needs. It is one of the way of communications and a positive sign of healthy life for the infant. The reasons involved for infant’s cry includes hungry, unhappy, discomfort, sadness, stomach pain, has colic or any other diseased conditions. The health of new born babies are effectively identified by the analysis of infant cry. Researchers made a huge analysis of infants by using methods like spectrography, melody shape method, and inverse filtering etc. The paper proposes a procedure to detect the emotion of infant cry by using Feature Extraction techniques including Mel-frequency and Linear predictive coding methods. A statistical tool is used to compare the efficiency of the two techniques (Mel-frequency and linear predictive coding). Present work is carried out mainly for five reasons which includes infant crying, has colic, hungry, sad, stomach pain, unhappy.