INTERSPEECH 2013
14thAnnual Conference of the International Speech Communication Association

Lyon, France
August 25-29, 2013

Audio Event Classification Using Deep Neural Networks

Zvi Kons, Orith Toledo-Ronen

IBM Research Haifa, Israel

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.

Full Paper

Bibliographic reference.  Kons, Zvi / Toledo-Ronen, Orith (2013): "Audio event classification using deep neural networks", In INTERSPEECH-2013, 1482-1486.