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Environmental Noise Classification Using Convolution Neural Networks

In order to achieve automatic analysis of environmental noise and related data, a method for classifying noise based on a convolutional neural network (CNN) model was proposed. First, the time-frequency conversion of the noise signal is performed by Short-Time Fourier Transform (STFT), and then the Log Mel-Frequency Spectral Coefficients (MFSCs) of the noise signal are extracted. Finally, the noise-established CNN model is classified. The whole system is implemented on tensorflow. The experimental results show that this method can obtain better classification results, which proves that this method has certain practicability.