It is estimated that one in every ten people is affected by hearing impairment. Sound Classification challenge that is faced by the people of urban area to classify the sound from different sources could be solved by creating a deep learning model which helps people in classifying the noise. From personal security to critical surveillance, sound is a key element to develop the automated systems for these fields. The ability of convolutional neural networks (CNN) to learn discriminative spectrotemporal patterns makes them well suited to sound classification. Dataset used : UrbanSound8k. Keywords: Deep Learning, Convolutional Neural Network, Spectrograms,UrbanSound8k, Environmental Sounds.