REVIEW OF CONVOLUTIONAL NEURAL NETWORK FOR SOUND CLASSIFICATION

Authors

  • Anam Bansal Assistant Professor, Central University of Punjab, Bathinda

Keywords:

Deep Learning, Convolutional Neural Network, Audio classification, Audio detection.

Abstract

Audio event detection and audio event classification are emerging field. The detection and classification of audio and sounds are prominently accomplished using the machine learning models like Support Vector Machines, K- Nearest Neighbour, Artificial Neural Networks, etc. These models give considerable accuracy. But deep learning models have surpassed the machine learning models in detecting and classifying the audio events, sources of sound and audio scenes. Convolutional Neural Network(CNN) is the deep learning model that has been used extensively in the field of audio. It has already made astonishing achievements in the field of image classification and other computer vision applications. This paper introduces the usage of CNN in the field of audio classification, describes the CNN model, layers of CNN, feature extraction in CNN. Then, the use of CNN in the various areas related to sound are described.

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Published

2019-04-15

How to Cite

Bansal, A. . (2019). REVIEW OF CONVOLUTIONAL NEURAL NETWORK FOR SOUND CLASSIFICATION. International Journal of Technical Innovation in Modern Engineering & Science, 5(4), 982–985. Retrieved from https://ijtimes.com/IJTIMES/index.php/ijtimes/article/view/2883