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--- |
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task_categories: |
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- audio-classification |
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license: cc |
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tags: |
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- bird classification |
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- passive acoustic monitoring |
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--- |
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## Dataset Description |
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- **Repository:** [https://github.com/DBD-research-group/GADME](https://github.com/DBD-research-group/GADME) |
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- **Paper:** [GADME](https://arxiv.org/) |
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- **Point of Contact:** [Lukas Rauch](mailto:lukas.rauch@uni-kassel.de) |
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### Dataset Summary |
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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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##### 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 offer detected events and corresponding cluster assignments to identify bird sounds in each recording. |
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- We provide the full recordings from XC! These can generate multiple samples from a single instance. |
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##### Test |
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- Only soundscape data sourced from Zenodo. |
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- We provide the full recording with the complete label set and specified bounding boxes. |
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- This dataset excludes recordings that do not contain bird calls ("no_call"). |
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- Task: Multiclass ("ebird_code") |
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##### Test_5s |
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- Only soundscape data from Zenodo formatted acoording to the Kaggle evaluation scheme. |
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- Each recording is segmented into 5-second intervals without overlaps. |
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- This contains the "no_call" class. |
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- Task: Multilabel ("ebird_code_multilabel") |
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#### Subsets |
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Numbers need to be updated |
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| | train | test | test_5s | size (GB) | #classes | |
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|----------------------------|--------:|-----------:|--------:|-----------:|-------------:| |
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| HSN (high_sierras) | 5,197 | 10,296 | 12,000 | 6.2 | 21 | |
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| NBP (nips) | 24,327 | 5,493 | 563 | wip | 51 | |
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| NES (columbia_costa_rica) | 15,157 | 6,952 | 24,480 | 14 | 89 | |
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| PER (amazon_basin) | 15,679 | 14,798 | 15,120 | 10 | 132 | |
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| POW (powdermill_nature) | 13,922 | 16,052 | 4,560 | 16 | 48 | |
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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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```python |
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{ |
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"audio": datasets.Audio(sampling_rate=32_000, mono=True, decode=True), |
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"filepath": datasets.Value("string"), |
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"start_time": datasets.Value("float64"), |
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"end_time": datasets.Value("float64"), |
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"low_freq": datasets.Value("int64"), |
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"high_freq": datasets.Value("int64"), |
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"ebird_code": datasets.ClassLabel(names=class_list), |
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"ebird_code_multilabel": datasets.Sequence(datasets.ClassLabel(names=["no_call"] + class_list)), |
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"ebird_code_secondary": datasets.Sequence(datasets.Value("string")), |
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"call_type": datasets.Value("string"), |
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"sex": datasets.Value("string"), |
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"lat": datasets.Value("float64"), |
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"long": datasets.Value("float64"), |
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"length": datasets.Value("int64"), |
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"microphone": datasets.Value("string"), |
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"license": datasets.Value("string"), |
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"source": datasets.Value("string"), |
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"local_time": datasets.Value("string"), |
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"detected_events": datasets.Sequence(datasets.Sequence(datasets.Value("float64"))), |
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"event_cluster": datasets.Sequence(datasets.Value("int64")), |
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"quality": datasets.Value("string"), |
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"recordist": datasets.Value("string") |
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}) |
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``` |
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```python |
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EXAMPLE TRAIN |
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{'audio': {'path': '.ogg', |
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'array': array([ 6.24680333e-02, 7.57145062e-02, 4.91199419e-02, ..., |
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-2.04162002e-02, 8.73558223e-03, -6.23320229e-05]), |
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'sampling_rate': 32000}, |
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'filepath': '.ogg', |
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'start_time': None, |
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'end_time': None, |
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'low_freq': None, |
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'high_freq': None, |
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'ebird_code': 1, |
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'ebird_code_multiclass': None, |
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'call_type': 'call', |
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'sex': None, |
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'lat': 22.2029, |
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'long': -159.473, |
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'microphone': 'focal', |
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'license': '//creativecommons.org/licenses/by-nc-sa/4.0/', |
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'source': 'xenocanto', |
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'local_time': '12:49', |
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'detected_events': [[0.832, 2.48], |
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[2.992, 4.016], |
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[3.2, 3.904], |
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[5.472, 6.048], |
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[5.488, 6.432], |
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[7.088, 8.16], |
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[8.944, 10.432], |
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[10.72, 12.672], |
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[11.152, 13.2], |
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[13.488, 14.0], |
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[14.64, 16.496]], |
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'event_cluster': [1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1], |
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'quality': 'A'} |
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EXAMPLE TEST_5S |
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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': 0.0, |
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'end_time': 5.0, |
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'low_freq': 2678, |
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'high_freq': 6053, |
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'ebird_code': None, |
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'ebird_code_multiclass': [0], |
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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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### Citation Information |
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``` |
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@article{gadme, |
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author = {Rauch, Lukas and |
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Schwinger, Raphael and |
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Wirth, Moritz and |
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Heinrich, René and |
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Lange, Jonas and |
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Kahl, Stefan and |
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Sick, Bernhard and |
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Tomforde, Sven and |
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Scholz, Christoph}, |
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title = {GADME: A Benchmark Towards General Avian Diversity Monitoring Evaluation in Deep Bioacoustics, |
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journal = {CoRR}, |
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volume = {X}, |
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year = {2024}, |
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url = {X}, |
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archivePrefix = {arXiv}, |
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} |
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Note that each test in GADME dataset has its own citation. Please see the source to see |
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the correct citation for each contained dataset. Each file in the training dataset also has its own recordist. The licenses can be found in the metadata. |
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``` |
