Classification of Environmental Sounds Using Neural Networks

Urban sound classification remarkable progress and is still an active research area in audio pattern recognition. This article analyzes advances in environmental sound recognition and classification using neural networks. The problem of sound classification is considered, existing datasets are reviewed, as well as practical implementations of audio classification models using neural networks. The main goal of this study is to provide an up-to-date brief overview of the various approaches of Convolutional neural network (CNN), Recurrent neural network (RNN), and Long short-term memory (LSTM) models in the field of audio and to identify their challenges to improve future research directions of sound classification systems.