Infants portray suggestive unique cries while sick, having belly pain, discomfort, tiredness, attention
and desire for a change of diapers among other needs. There exists limited knowledge in accessing
the infants’ needs as they only relay
information through suggestive cries. Many teenagers tend to give birth at an early
age, thereby exposing them to be the key monitors of their own babies. They
tend not to have sufficient skills in monitoring the infant’s dire needs, more so during the early stages of infant development.
Artificial intelligence has shown promising efficient predictive analytics
from supervised, and unsupervised to reinforcement learning models. This study, therefore, seeks to develop an android app that could be used to discriminate
the infant audio cries by leveraging the strength of convolution neural networks
as a classifier model. Audio analytics from many kinds of literature is an untapped area
by researchers as it’s attributed to messy and
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