Baby cry recognition in real-world conditions

Abstract

Studies have shown that there are different types of cries depending on the newborns' need such as hunger, tiredness, discomfort and so on. Neonatologist or pediatricians can distinguish between different types of cries and can find a pattern in each type of cry. Unfortunately, this is a real problem for the parents who want to act as fast as possible to comfort the newborn. In this paper, we propose a fully automatic system that attempts to discriminate between different types of cries. The baby cry classification system is based on Gaussian Mixture Models and i-vectors. The evaluation is performed on an audio database comprising six types of cries (colic, eructation, discomfort, hunger, pain, tiredness) from 127 babies. The experiments show promising results despite the difficulty of the task.