Bird detection in audio: a survey and a challenge
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2016
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| _version_ | 1866909088406831104 |
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| author | Stowell, Dan Wood, Mike Stylianou, Yannis Glotin, Hervé |
| author_facet | Stowell, Dan Wood, Mike Stylianou, Yannis Glotin, Hervé |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_1608_03417 |
| institution | arXiv |
| publishDate | 2016 |
| record_format | arxiv |
| spellingShingle | Bird detection in audio: a survey and a challenge Stowell, Dan Wood, Mike Stylianou, Yannis Glotin, Hervé Sound 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. |
| title | Bird detection in audio: a survey and a challenge |
| topic | Sound |
| url | https://arxiv.org/abs/1608.03417 |