The analysis and understanding of sound in the urban environment is very important to the growth of cities and populations for the future. Studies have shown a direct impact on health and child development from noise pollution
DataSet Used:- UrbanSound8k You can download it from https://urbansounddataset.weebly.com/urbansound8k.html
In this I have provded convolutional neural network which extracts features on the basis of Mel-frequency cestrum coefficients which collectively make up an MFC. The Mel-frequency cestrum (MFC) is a representation of the short-term power spectrum of a sound, based on a linear cosine transform of a log power spectrum on a nonlinear Mel scale of frequency which provides better accuracy compared to other pretrained models, thus overcoming the drawbacks mentioned above for environmental sound classification.