Environmental sound classification with convolutional neural networks

@article{Piczak2015EnvironmentalSC,
  title={Environmental sound classification with convolutional neural networks},
  author={Karol J. Piczak},
  journal={2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP)},
  year={2015},
  pages={1-6}
}
  • Karol J. Piczak
  • Published 12 November 2015
  • Computer Science
  • 2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP)
This paper evaluates the potential of convolutional neural networks in classifying short audio clips of environmental sounds. [] Key Method A deep model consisting of 2 convolutional layers with max-pooling and 2 fully connected layers is trained on a low level representation of audio data (segmented spectrograms) with deltas. The accuracy of the network is evaluated on 3 public datasets of environmental and urban recordings. The model outperforms baseline implementations relying on mel-frequency cepstral…

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