ISCA Archive Interspeech 2013
ISCA Archive Interspeech 2013

Audio event classification using deep neural networks

Zvi Kons, Orith Toledo-Ronen

We present in this paper our work on audio event classification for outdoor events. As the main classification method we employ a deep neural network (DNN) and compare this to other classification methods. We propose a novel improvement to the pre-training process of the network which is useful when training with Gaussian data. Our experimental results are based on an audio corpus extracted from the FreeSound.org website repository. We show that the DNN has some advantage over other classification methods and that fusion of two methods can produce the best results.


doi: 10.21437/Interspeech.2013-384

Cite as: Kons, Z., Toledo-Ronen, O. (2013) Audio event classification using deep neural networks. Proc. Interspeech 2013, 1482-1486, doi: 10.21437/Interspeech.2013-384

@inproceedings{kons13b_interspeech,
  author={Zvi Kons and Orith Toledo-Ronen},
  title={{Audio event classification using deep neural networks}},
  year=2013,
  booktitle={Proc. Interspeech 2013},
  pages={1482--1486},
  doi={10.21437/Interspeech.2013-384}
}