Bird detection in audio : a survey and a challenge

Stowell, D, Wood, M ORCID: https://orcid.org/0000-0002-0635-2387, Stylianou, Y and Glotin, H 2016, 'Bird detection in audio : a survey and a challenge' , Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing , pp. 1-6.

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Abstract

Many biological monitoring projects rely on acoustic detection of birds. Despite increasingly large datasets, this detection is often manual or semi-automatic, requiring manual tuning/postprocessing. We review the state of the art in automatic bird sound detection, and identify a widespread need for tuning-free and species-agnostic approaches. We introduce new datasets and an IEEE research challenge to address this need, to make possible the development of fully automatic algorithms for bird sound detection.

Item Type:	Article
Additional Information:	Proceedings ISBN: 978-1-5090-0746-2
Schools:	Schools > School of Environment and Life Sciences > Ecosystems and Environment Research Centre
Journal or Publication Title:	Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing
Publisher:	IEEE Computer Society
ISBN:	9781509007462
Funders:	Natural Environment Research Council (NERC), Engineering and Physical Sciences Research Council (EPSRC)
Depositing User:	Prof Mike Wood
Date Deposited:	18 Jan 2017 13:41
Last Modified:	12 Nov 2019 16:05
URI:	http://usir.salford.ac.uk/id/eprint/41202

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