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

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 r...

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Bibliografiske detaljer
Udgivet i:J Acoust Soc Am
Main Authors: Oikarinen, Tuomas, Srinivasan, Karthik, Meisner, Olivia, Hyman, Julia B., Parmar, Shivangi, Fanucci-Kiss, Adrian, Desimone, Robert, Landman, Rogier, Feng, Guoping
Format: Artigo
Sprog:Inglês
Udgivet: Acoustical Society of America 2019
Fag:
Signal Processing in Acoustics
Online adgang:https://ncbi.nlm.nih.gov/pmc/articles/PMC6786887/
https://ncbi.nlm.nih.gov/pubmed/30823820
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1121/1.5087827
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