Identification of Reasons Behind Infant Crying Using Acoustic Signal Processing and Deep Neural Network for Neonatal Intensive Care Unit

Abstract. The infants admitted in the Neonatal Intensive Care Unit (NICU) always need a Hygienic environment and round clock observations. Infants or just born babies express their physical emotional needs through cry. Thus, detection of reasons behind infant cry plays vital role monitoring health NICU. In this paper, we have proposed novel approach for detecting Infant's signal is captured from signal, unique set features are extracted using MFCCs, LPCCs, Pitch. This used to differentiates patters signals recognize such as hunger, pain, sleep, discomfort represent different classes. Neural Network Multilayer classifier designed standard dataset can achieve accuracy 93.24% combined LPCCs Pitch