International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 119 - Issue 12 |
Published: June 2015 |
Authors: Dharin Shah, Chirag Sachdev, Bhavik Shah |
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Dharin Shah, Chirag Sachdev, Bhavik Shah . Classification of Music Genre using Neural Networks with Cross-Entropy Optimization and Soft-Max Output. International Journal of Computer Applications. 119, 12 (June 2015), 33-38. DOI=10.5120/21123-4013
@article{ 10.5120/21123-4013, author = { Dharin Shah,Chirag Sachdev,Bhavik Shah }, title = { Classification of Music Genre using Neural Networks with Cross-Entropy Optimization and Soft-Max Output }, journal = { International Journal of Computer Applications }, year = { 2015 }, volume = { 119 }, number = { 12 }, pages = { 33-38 }, doi = { 10.5120/21123-4013 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2015 %A Dharin Shah %A Chirag Sachdev %A Bhavik Shah %T Classification of Music Genre using Neural Networks with Cross-Entropy Optimization and Soft-Max Output%T %J International Journal of Computer Applications %V 119 %N 12 %P 33-38 %R 10.5120/21123-4013 %I Foundation of Computer Science (FCS), NY, USA
In this paper, an abstract model to predict the genre of a music audio file is proposed (specifically a wave file). The output of the model is the probability distribution along the considered genres. A machine learning approach is employed. The adaptive learning process is modeled by neural networks with back-propagation as its learning algorithm and cross entropy as its optimization function. The emphasis is on feature extractors since the learning paradigm is well known to other applications. Simple Analysis on the Features were performed for appropriate selection.