Acoustic based Scene Event Identification Using Deep Learning CNN

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R. Abinaya, et. al.

Abstract

Deep learning is becoming popular nowadays on solving the classification problems when compared with conventional classifiers. Large number of researchers are exploiting deep learning regarding sound event detection for environmental scene analysis. In this research, deep learning convolutional neural network (CNN) classifier is modelled using the extracted MFCC features for classifying the environmental event sounds. The experiment results clearly show that proposed MFCC-CNN outperform other existing methods with a high classification accuracy of 90.65%.

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