Deep convolutional network for animal sound classification and source attribution using dual audio recordings

Tuomas Oikarinen, Karthik Srinivasan, Olivia Meisner, Julia B Hyman, Shivangi Parmar, Adrian Fanucci-Kiss, Robert Desimone, Rogier Landman, Guoping Feng. The Journal of the Acoustical Society of America, Mar 2019.


This paper introduces an end-to-end feedforward convolutional neural network that is able to reliably classify the source and type of animal calls in a noisy environment using two streams of audio data after being trained on a dataset of modest size and imperfect labels. The data consists of audio recordings from captive marmoset monkeys housed in pairs, with several other cages nearby. The network in this paper can classify both the call type and which animal made it with a single pass through…