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We present the BirdSet benchmark that covers a comprehensive range of classification datasets in avian bioacoustics.
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We offer a static set of evaluation datasets and a varied collection of training datasets, enabling the application of diverse methodologies.
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| [PER]
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| [NES]
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| [UHH]
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| [HSN]
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| [NBP]
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| [POW]
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| [SSW]
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| [SNE]
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| [XCM]
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| [XCL](
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| [XCL][10] | 528,434 | x | x | 484 | 9,734 |
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[1]: https://examplelinkforHSN.com
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[2]: https://examplelinkforNBP.com
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[3]: https://examplelinkforNES.com
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[4]: https://examplelinkforPER.com
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[5]: https://examplelinkforPOW.com
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[6]: https://examplelinkforSNE.com
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[7]: https://examplelinkforSSW.com
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[8]: https://examplelinkforUHH.com
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[9]: https://examplelinkforXCM.com
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[10]: https://examplelinkforXCL.com
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##### Train
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- Exclusively using focal audio data from Xeno-Canto (XC) with quality ratings A, B, C and excluding all recordings that are CC-ND.
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- Each dataset is tailored for specific target species identified in soundscape files.
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We present the BirdSet benchmark that covers a comprehensive range of classification datasets in avian bioacoustics.
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We offer a static set of evaluation datasets and a varied collection of training datasets, enabling the application of diverse methodologies.
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| | train | test | test_5s | size (GB) | #classes |
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|-------------------------------------|--------:|-----------:|--------:|-----------:|-------------:|
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| [PER][1] (Amazon Basin) | 16,802 | 14,798 | 15,120 | 10.5 | 132 |
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| [NES][2] (Colombia Costa Rica) | 16,117 | 6,952 | 24,480 | 14.2 | 89 |
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| [UHH][3] (Hawaiian Islands) | 3,626 | 59,583 | 36,637 | 4.92 | 25 tr, 27 te |
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| [HSN][4] (high_sierras) | 5,460 | 10,296 | 12,000 | 5.92 | 21 |
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| [NBP][5] (NIPS4BPlus) | 24,327 | 5,493 | 563 | 29.9 | 51 |
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| [POW][6] (Powdermill Nature) | 14,911 | 16,052 | 4,560 | 15.7 | 48 |
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| [SSW][7] (Sapsucker Woods) | 28,403 | 50,760 | 205,200| 35.2 | 81 |
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| [SNE][8] (Sierra Nevada) | 19,390 | 20,147 | 23,756 | 20.8 | 56 |
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| [XCM][9] (Xenocanto Subset M) | 89,798 | x | x | 89.3 | 409 |
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| [XCL][10](Xenocanto Subset Complete)| 528,434| x | x | 484 | 9,734 |
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[1]: https://zenodo.org/records/7079124
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[2]: https://zenodo.org/records/7525349
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[3]: https://zenodo.org/records/7078499
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[4]: https://zenodo.org/records/7525805
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[5]: https://github.com/fbravosanchez/NIPS4Bplus
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[6]: https://zenodo.org/records/4656848
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[7]: https://zenodo.org/records/7018484
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[8]: https://zenodo.org/records/7050014
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[9]: https://xeno-canto.org/
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[10]: https://xeno-canto.org
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##### Train
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- Exclusively using focal audio data from Xeno-Canto (XC) with quality ratings A, B, C and excluding all recordings that are CC-ND.
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- Each dataset is tailored for specific target species identified in soundscape files.
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