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croissant_rai_OpenWhistle-Classification-Finetuning.json ADDED
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+ "name": "unbalanced-review-sample_splits",
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+ "name": "unbalanced-review-sample",
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+ "description": "Deterministic unbalanced-configuration review sample for reviewer inspection.",
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+ }
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+ },
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+ "dataType": "sc:Text",
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+ },
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+ "extract": {
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+ "column": "whistle_name"
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+ }
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+ }
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+ },
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+ },
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+ "extract": {
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+ }
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+ "arrayShape": "-1"
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+ {
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+ "dataType": "cr:Float32",
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+ "source": {
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+ "@id": "parquet-files-for-config-unbalanced-review-sample"
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+ },
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+ "extract": {
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+ "column": "f0_hz"
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+ }
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+ },
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+ "isArray": true,
1675
+ "arrayShape": "-1"
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+ },
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+ {
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+ "@type": "cr:Field",
1679
+ "@id": "unbalanced-review-sample/f0_conf",
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+ "dataType": "cr:Float32",
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+ "source": {
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+ "fileSet": {
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+ "@id": "parquet-files-for-config-unbalanced-review-sample"
1684
+ },
1685
+ "extract": {
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+ "column": "f0_conf"
1687
+ }
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+ },
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+ "isArray": true,
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+ "arrayShape": "-1"
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+ },
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+ {
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+ "@type": "cr:Field",
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+ "@id": "unbalanced-review-sample/f0_ok",
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+ "dataType": "sc:Boolean",
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+ "source": {
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+ "fileSet": {
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+ "@id": "parquet-files-for-config-unbalanced-review-sample"
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+ },
1700
+ "extract": {
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+ "column": "f0_ok"
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+ }
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+ }
1704
+ },
1705
+ {
1706
+ "@type": "cr:Field",
1707
+ "@id": "unbalanced-review-sample/f0_bad_reason",
1708
+ "dataType": "sc:Text",
1709
+ "source": {
1710
+ "fileSet": {
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+ "@id": "parquet-files-for-config-unbalanced-review-sample"
1712
+ },
1713
+ "extract": {
1714
+ "column": "f0_bad_reason"
1715
+ }
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+ }
1717
+ },
1718
+ {
1719
+ "@type": "cr:Field",
1720
+ "@id": "unbalanced-review-sample/f0_spectrogram",
1721
+ "dataType": "sc:ImageObject",
1722
+ "source": {
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+ "fileSet": {
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+ "@id": "parquet-files-for-config-unbalanced-review-sample"
1725
+ },
1726
+ "extract": {
1727
+ "column": "f0_spectrogram"
1728
+ },
1729
+ "transform": {
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+ "jsonPath": "bytes"
1731
+ }
1732
+ }
1733
+ }
1734
+ ]
1735
+ }
1736
+ ],
1737
+ "rai:dataCollection": "The dataset was assembled from passive acoustic monitoring at Dolphin Reef, Eilat, a semi-natural marine site on the northern Gulf of Aqaba. Fixed hydrophones recorded a stable pod of known dolphins in a large natural marine area open to the sea. Whistle clips in this finetuning dataset come from curated OpenWhistle recordings and are packaged with timing metadata, F0 tracks, F0 spectrograms, and expert-refined whistle-type labels.",
1738
+ "rai:dataCollectionType": [
1739
+ "Physical data collection",
1740
+ "Direct measurement",
1741
+ "Manual Human Curator",
1742
+ "Software Collection"
1743
+ ],
1744
+ "rai:dataCollectionRawData": "Raw data consisted of underwater acoustic recordings captured by fixed and hidden hydrophones. The released classification dataset contains short whistle clips and metadata fields: audio, label, name, onset, offset, duration, recording_duration, whistle_type, whistle_name, f0_time, f0_hz, f0_conf, f0_ok, f0_bad_reason, and f0_spectrogram.",
1745
+ "rai:dataCollectionMissingData": "The public dataset does not include per-example video context, exact hydrophone coordinates, environmental conditions, full behavioral context, or human-identifying information. The balanced configuration intentionally excludes rare whistle categories to support reliable six-class evaluation, while all and unbalanced configurations retain a broader ten-class label space with imbalanced classes.",
1746
+ "rai:dataPreprocessingProtocol": [
1747
+ "Whistle clips were extracted from OpenWhistle recordings and packaged as Hugging Face parquet datasets with audio, timing metadata, F0 contours, F0 confidence values, and rendered F0 spectrogram images.",
1748
+ "The main balanced configuration uses six classes and exact class balancing with 2,100 train, 450 validation, and 450 test examples. Splits are session-disjoint, so no recording session appears in more than one split.",
1749
+ "The unbalanced and all configurations expose ten whistle classes for additional analysis. Review-sample configurations were generated deterministically after split creation and are intended for manual inspection, not reporting."
1750
+ ],
1751
+ "rai:dataAnnotationProtocol": "Whistle categories were obtained through an annotation pipeline combining automated contour-based grouping with expert refinement. Detected whistle segments were categorized into known signature-whistle and non-signature-whistle types, then manually refined by expert annotators through visual inspection of spectrograms to correct misclassifications and resolve ambiguous cases.",
1752
+ "rai:annotationsPerItem": "Each released example has one whistle-type class label. The label corresponds to either a signature whistle class or a non-signature whistle class, depending on the configuration.",
1753
+ "rai:machineAnnotationTools": [
1754
+ "ARTwarp and dynamic time warping were used in the annotation pipeline to cluster whistle contours before expert refinement.",
1755
+ "F0 extraction and spectrogram rendering software were used to create f0_time, f0_hz, f0_conf, f0_ok, f0_bad_reason, and f0_spectrogram fields.",
1756
+ "Hugging Face Datasets tooling was used to package and publish the dataset as parquet configurations."
1757
+ ],
1758
+ "rai:dataUseCases": "[\"Construct represented: short dolphin whistle clips with expert-refined whistle-type labels, timing metadata, F0 tracks, and F0 spectrograms.\", \"Validated use case: training, validation, and testing of dolphin whistle-type classifiers on the balanced six-class OpenWhistle benchmark with session-disjoint train, validation, and test splits.\", \"Validated use case: linear probing or finetuning of audio representation models for fine-grained intra-species dolphin whistle discrimination.\", \"Supported exploratory use case: analysis of ten-class whistle categories using the all and unbalanced configurations, with explicit attention to class imbalance.\", \"Supported reviewer use case: manual inspection through deterministic review-sample configurations.\", \"Not validated use case: inferring behavioral intent, communicative meaning, animal welfare state, individual identity beyond the released label definitions, or deployment performance in other sites without additional biological validation.\"]",
1759
+ "rai:dataLimitations": "[\"The balanced configuration is designed for six-class whistle-type classification and should not be treated as a complete representation of all dolphin whistle categories or all individuals at the site.\", \"The all and unbalanced configurations expose ten classes but contain strong class imbalance, including rare whistle types that may not support reliable standalone evaluation.\", \"The dataset comes from a semi-natural site with a stable pod of known dolphins, so results may not generalize to fully wild populations, other species, other recording devices, or different acoustic environments without validation.\", \"Labels describe whistle categories, not full behavioral intent, communicative meaning, animal state, or ecological outcomes.\", \"Review-sample configurations are for inspection only and should not replace the full configurations for model development or reporting.\", \"Session-disjoint splits reduce session leakage, but downstream users should still avoid mixing sessions or configurations in ways that invalidate the benchmark protocol.\"]",
1760
+ "rai:dataBiases": "[\"The dataset reflects recordings from Dolphin Reef, Eilat and may overrepresent acoustic, social, and environmental conditions at that semi-natural site.\", \"The naturally available whistle repertoire is imbalanced: some signature whistle and non-signature whistle categories are much more frequent than others.\", \"The main balanced configuration intentionally subsamples classes to equalize six labels, which improves benchmark comparability but no longer reflects natural production frequencies.\", \"Expert-refined labels depend on the available template contours, annotation pipeline, and annotator judgments, so ambiguous or low-quality whistles may be underrepresented.\", \"Examples with usable F0 tracks or clearer spectrograms may be easier to analyze and may not fully represent all noisy, overlapping, or low-SNR acoustic conditions.\"]",
1761
+ "rai:personalSensitiveInformation": "[\"No human subjects are involved in the dataset. Public columns contain animal audio clips, timing fields, whistle labels, F0 tracks, F0 spectrograms, and recording/session metadata.\", \"The data consists of underwater animal acoustic recordings. Users should nevertheless treat incidental non-target sounds as possible and avoid attempts to infer people, vessels, precise locations, or sensitive field-site details from the audio.\", \"Whistle labels may be associated with known dolphin signature-whistle categories, but the public dataset does not include sensitive human information.\"]",
1762
+ "rai:dataSocialImpact": "The dataset supports open research on dolphin bioacoustics, animal communication, passive acoustic monitoring, and fine-grained acoustic representation learning. Positive impacts include reproducible evaluation for dolphin whistle-type classification and tools that may support non-invasive monitoring. Misuse risks include overinterpreting whistle-type predictions as behavioral meaning, identity, or conservation evidence without biological validation, or deploying models trained on this dataset in other sites without local evaluation. The data collection was passive and non-invasive, did not interfere with dolphin behavior, and involved no human subjects.",
1763
+ "rai:hasSyntheticData": false,
1764
+ "rai:dataReleaseMaintenancePlan": "The dataset is hosted publicly on Hugging Face under OpenWhistleNeurIPS26/OpenWhistle-Classification-Finetuning and released under CC-BY 4.0. The repository includes deterministic review-sample configurations for reviewer inspection. Future OpenWhistle releases may expand labels, audio coverage, contextual metadata, or evaluation protocols.",
1765
+ "prov:wasDerivedFrom": [
1766
+ {
1767
+ "@id": "urn:openwhistle:classification-source-recordings-and-annotations:anonymous-neurips-2026",
1768
+ "prov:label": "OpenWhistle passive acoustic recordings and expert whistle annotations",
1769
+ "sc:license": "https://creativecommons.org/licenses/by/4.0/",
1770
+ "prov:wasAttributedTo": {
1771
+ "@id": "anonymous_openwhistle_authors",
1772
+ "prov:label": "Anonymous OpenWhistle authors"
1773
+ }
1774
+ }
1775
+ ],
1776
+ "prov:wasGeneratedBy": [
1777
+ {
1778
+ "@type": "prov:Activity",
1779
+ "prov:type": {
1780
+ "@id": "https://www.wikidata.org/wiki/Q4929239"
1781
+ },
1782
+ "prov:label": "Passive acoustic data collection",
1783
+ "sc:description": "Underwater audio was collected passively using fixed and hidden hydrophones. The collection did not interfere with dolphin behavior, did not train or constrain animals, and involved no human subjects.",
1784
+ "prov:wasAttributedTo": [
1785
+ {
1786
+ "@type": "prov:Agent",
1787
+ "@id": "anonymous_openwhistle_authors",
1788
+ "prov:label": "Anonymous OpenWhistle authors",
1789
+ "sc:description": "Anonymous research team responsible for the OpenWhistle data release and documentation during double-blind review."
1790
+ }
1791
+ ]
1792
+ },
1793
+ {
1794
+ "@type": "prov:Activity",
1795
+ "prov:type": {
1796
+ "@id": "https://www.wikidata.org/wiki/Q109719325"
1797
+ },
1798
+ "prov:label": "Whistle category annotation and expert refinement",
1799
+ "sc:description": "Whistle clips were categorized into signature-whistle and non-signature-whistle classes using contour-based grouping and expert visual inspection. Expert annotators refined assignments to correct misclassifications and resolve ambiguous cases.",
1800
+ "prov:wasAttributedTo": [
1801
+ {
1802
+ "@type": "prov:Agent",
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+ "@id": "anonymous_openwhistle_expert_annotators",
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+ "prov:label": "Anonymous OpenWhistle expert annotators",
1805
+ "sc:description": "Anonymous domain experts who reviewed spectrograms and refined whistle category labels."
1806
+ },
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+ {
1808
+ "@type": "prov:SoftwareAgent",
1809
+ "@id": "artwarp_and_dtw_annotation_pipeline",
1810
+ "prov:label": "ARTwarp and DTW annotation pipeline",
1811
+ "sc:description": "Automated contour-similarity tooling used before expert refinement."
1812
+ }
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+ ]
1814
+ },
1815
+ {
1816
+ "@type": "prov:Activity",
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+ "prov:type": {
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+ "@id": "https://www.wikidata.org/wiki/Q5227332"
1819
+ },
1820
+ "prov:label": "Feature extraction and dataset packaging",
1821
+ "sc:description": "Whistle clips, class labels, timing metadata, F0 contours, F0 confidence values, and rendered F0 spectrograms were packaged into Hugging Face parquet configurations. The balanced, unbalanced, and all configurations were split into train, validation, and test sets with session-disjoint assignment.",
1822
+ "prov:wasAttributedTo": [
1823
+ {
1824
+ "@type": "prov:SoftwareAgent",
1825
+ "@id": "hugging_face_datasets",
1826
+ "prov:label": "Hugging Face Datasets",
1827
+ "sc:description": "Software tooling used to package and publish the dataset with Audio, Image, and sequence features."
1828
+ },
1829
+ {
1830
+ "@type": "prov:Agent",
1831
+ "@id": "anonymous_openwhistle_authors",
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+ "prov:label": "Anonymous OpenWhistle authors",
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+ "sc:description": "Anonymous research team responsible for preprocessing, curation, and release during double-blind review."
1834
+ }
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+ ]
1836
+ },
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+ {
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+ "@type": "prov:Activity",
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+ "prov:type": {
1840
+ "@id": "https://www.wikidata.org/wiki/Q3306762"
1841
+ },
1842
+ "prov:label": "Review sample generation",
1843
+ "sc:description": "Deterministic review-sample configurations were generated after final train/validation/test splits. The balanced review sample preserves equal rows per class within each split; unbalanced and all review samples preserve the source class distribution proportionally.",
1844
+ "prov:wasAttributedTo": [
1845
+ {
1846
+ "@type": "prov:Agent",
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+ "@id": "anonymous_openwhistle_authors",
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+ "prov:label": "Anonymous OpenWhistle authors",
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+ "sc:description": "Anonymous research team responsible for creating reviewer inspection subsets."
1850
+ }
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+ ]
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+ }
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+ ]
1854
+ }