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
, in: 26th IEEE International Workshop on Machine Learning for Signal Processing, 13-16 Sept 2016, Salerno, Italy.
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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: | Conference or Workshop Item (Paper) |
|---|---|
| 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: | 28 Aug 2021 16:30 |
| URI: | http://usir.salford.ac.uk/id/eprint/41202 |
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