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README.md
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- bird classification
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- passive acoustic monitoring
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---
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### Datasets
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| SNE (sierra_nevada) | 18,307 | 20,147 | 23,756 | 22 | 56 |
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| SSW (sapsucker_woods) | 26,487 | 50,760 | 205,200| 36 | 81 |
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| UHH (hawaiian_islands) | 3,427 | 59,583 | 36,637 | 5.1 | 25 tr, 27 te |
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| XCM
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| XCL (xenocanto) | 492,676| x |
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#### FEATURES
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'event_cluster': None,
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'quality': None}
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EXAMPLE TEST
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{'audio': {'path': '.ogg',
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'array': array([-5.03219722e-04, 9.99580720e-04, 2.58744985e-05, ...,
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-4.06746846e-03, -3.79991997e-03, 2.88472045e-04]),
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'sampling_rate': 32000},
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'filepath': '.ogg',
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'start_time': 6.8,
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'end_time': 8.2,
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'low_freq': 2678,
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'high_freq': 6053,
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'ebird_code': 22,
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'ebird_code_multiclass': None,
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'call_type': None,
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'sex': None,
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'lat': 19.801668,
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'long': -155.609444,
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'microphone': 'Soundscape',
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'license': 'Creative Commons Attribution 4.0 International Public License',
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'source': 'https://zenodo.org/record/7078499',
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'local_time': '15:00:06',
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'detected_events': None,
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'event_cluster': None,
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'quality': None}
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```
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### Citation Information
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```
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- bird classification
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- passive acoustic monitoring
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---
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We present the GADME benchmark that covers a comprehensive range of avian monitoring datasets.
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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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### Datasets
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| SNE (sierra_nevada) | 18,307 | 20,147 | 23,756 | 22 | 56 |
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| SSW (sapsucker_woods) | 26,487 | 50,760 | 205,200| 36 | 81 |
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| UHH (hawaiian_islands) | 3,427 | 59,583 | 36,637 | 5.1 | 25 tr, 27 te |
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| XCM (xenocanto) | 80,012 | x | x | 83 | 409 |
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| XCL (xenocanto) | 492,676| x | x | 485 | 9,734 |
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#### FEATURES
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'event_cluster': None,
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'quality': None}
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### Citation Information
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```
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