Baby Cry Detection in Domestic Environment using Convolutional Neural Networks
Arokia Jesu Prabhu L1, Reethu M2, Sabaritha M3, Santhiya S4, Subramanian N5

1Arokia Jesu Prabhu.L*, Ph.D from Anna University, Chennai.
2M M.Reethu, B.E Computer Science and En Engineering in Sri Shakthi Institute of Engineering and technology, Tamil Nadu.
3M.Sabaritha , B.E Computer Science and En Engineering in Sri Shakthi Institute of Engineering and Technology, Tamil Nadu.
4S. Santhiya, B.E Computer Science and  Engineering in Sri Shakthi Institute of Engineering and Technology, Tamil Nadu.
5N.Subramanian, B.E Computer Science and En Engineering in Sri Shakthi Institute of Engineering and Technology, Tamil Nadu.
Manuscript received on April 20, 2020. | Revised Manuscript received on April 30, 2020. | Manuscript published on May 10, 2020. | PP: 793-795 | Volume-9 Issue-7, May 2020. | Retrieval Number: G5260059720/2020©BEIESP | DOI: 10.35940/ijitee.G5260.059720
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In this paper we will identify a cry signals of infants and the explanation behind the screams below 0-6 months of segment age. Detection of baby cry signals is essential for the pre-processing of various applications involving crial analysis for baby caregivers, such as emotion detection. Since cry signals hold baby well-being information and can be understood to an extent by experienced parents and experts. We train and validate the neural network architecture for baby cry detection and also test the fastAI with the neural network. Trained neural networks will provide a model and this model can predict the reason behind the cry sound. Only the cry sounds are recognized, and alert the user automatically. Created a web application by responding and detecting different emotions including hunger, tired, discomfort, belly pain. 
Keywords: React, Fastai, Convolutionary neural network, Cry of infants,  Classified.
Scope of the Article: Classification