| --- |
| dataset_info: |
| - config_name: all |
| features: |
| - name: audio |
| dtype: |
| audio: |
| decode: false |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': NSW_3 |
| '1': NSW_2 |
| '2': NSW_1 |
| '3': SW_Dana |
| '4': SW_Luna |
| '5': SW_Nana |
| '6': SW_Neo |
| '7': SW_Nikita |
| '8': SW_Shy |
| '9': SW_Yosefa |
| - name: name |
| dtype: string |
| - name: onset |
| dtype: float32 |
| - name: offset |
| dtype: float32 |
| - name: duration |
| dtype: float32 |
| - name: recording_duration |
| dtype: float32 |
| - name: whistle_type |
| dtype: int64 |
| - name: whistle_name |
| dtype: string |
| - name: f0_time |
| sequence: float32 |
| - name: f0_hz |
| sequence: float32 |
| - name: f0_conf |
| sequence: float32 |
| - name: f0_ok |
| dtype: bool |
| - name: f0_bad_reason |
| dtype: string |
| - name: f0_spectrogram |
| dtype: image |
| - name: snr_db |
| dtype: float64 |
| splits: |
| - name: train |
| num_examples: 5848 |
| - name: validation |
| num_examples: 1253 |
| - name: test |
| num_examples: 1253 |
| - config_name: all-review-sample |
| features: |
| - name: audio |
| dtype: |
| audio: |
| decode: false |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': NSW_3 |
| '1': NSW_2 |
| '2': NSW_1 |
| '3': SW_Dana |
| '4': SW_Luna |
| '5': SW_Nana |
| '6': SW_Neo |
| '7': SW_Nikita |
| '8': SW_Shy |
| '9': SW_Yosefa |
| - name: name |
| dtype: string |
| - name: onset |
| dtype: float32 |
| - name: offset |
| dtype: float32 |
| - name: duration |
| dtype: float32 |
| - name: recording_duration |
| dtype: float32 |
| - name: whistle_type |
| dtype: int64 |
| - name: whistle_name |
| dtype: string |
| - name: f0_time |
| sequence: float32 |
| - name: f0_hz |
| sequence: float32 |
| - name: f0_conf |
| sequence: float32 |
| - name: f0_ok |
| dtype: bool |
| - name: f0_bad_reason |
| dtype: string |
| - name: f0_spectrogram |
| dtype: image |
| - name: snr_db |
| dtype: float64 |
| splits: |
| - name: train |
| num_examples: 336 |
| - name: validation |
| num_examples: 72 |
| - name: test |
| num_examples: 72 |
| - config_name: balanced |
| features: |
| - name: audio |
| dtype: |
| audio: |
| decode: false |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': NSW_1 |
| '1': SW_Luna |
| '2': SW_Nana |
| '3': SW_Neo |
| '4': SW_Nikita |
| '5': SW_Yosefa |
| - name: name |
| dtype: string |
| - name: onset |
| dtype: float32 |
| - name: offset |
| dtype: float32 |
| - name: duration |
| dtype: float32 |
| - name: recording_duration |
| dtype: float32 |
| - name: whistle_type |
| dtype: int64 |
| - name: whistle_name |
| dtype: string |
| - name: f0_time |
| sequence: float32 |
| - name: f0_hz |
| sequence: float32 |
| - name: f0_conf |
| sequence: float32 |
| - name: f0_ok |
| dtype: bool |
| - name: f0_bad_reason |
| dtype: string |
| - name: f0_spectrogram |
| dtype: image |
| splits: |
| - name: train |
| num_examples: 2100 |
| - name: validation |
| num_examples: 450 |
| - name: test |
| num_examples: 450 |
| - config_name: balanced-review-sample |
| features: |
| - name: audio |
| dtype: |
| audio: |
| decode: false |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': NSW_1 |
| '1': SW_Luna |
| '2': SW_Nana |
| '3': SW_Neo |
| '4': SW_Nikita |
| '5': SW_Yosefa |
| - name: name |
| dtype: string |
| - name: onset |
| dtype: float32 |
| - name: offset |
| dtype: float32 |
| - name: duration |
| dtype: float32 |
| - name: recording_duration |
| dtype: float32 |
| - name: whistle_type |
| dtype: int64 |
| - name: whistle_name |
| dtype: string |
| - name: f0_time |
| sequence: float32 |
| - name: f0_hz |
| sequence: float32 |
| - name: f0_conf |
| sequence: float32 |
| - name: f0_ok |
| dtype: bool |
| - name: f0_bad_reason |
| dtype: string |
| - name: f0_spectrogram |
| dtype: image |
| splits: |
| - name: train |
| num_examples: 336 |
| - name: validation |
| num_examples: 72 |
| - name: test |
| num_examples: 72 |
| - config_name: unbalanced |
| features: |
| - name: audio |
| dtype: |
| audio: |
| decode: false |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': NSW_3 |
| '1': NSW_2 |
| '2': NSW_1 |
| '3': SW_Dana |
| '4': SW_Luna |
| '5': SW_Nana |
| '6': SW_Neo |
| '7': SW_Nikita |
| '8': SW_Shy |
| '9': SW_Yosefa |
| - name: name |
| dtype: string |
| - name: onset |
| dtype: float32 |
| - name: offset |
| dtype: float32 |
| - name: duration |
| dtype: float32 |
| - name: recording_duration |
| dtype: float32 |
| - name: whistle_type |
| dtype: int64 |
| - name: whistle_name |
| dtype: string |
| - name: f0_time |
| sequence: float32 |
| - name: f0_hz |
| sequence: float32 |
| - name: f0_conf |
| sequence: float32 |
| - name: f0_ok |
| dtype: bool |
| - name: f0_bad_reason |
| dtype: string |
| - name: f0_spectrogram |
| dtype: image |
| splits: |
| - name: train |
| num_examples: 2442 |
| - name: validation |
| num_examples: 523 |
| - name: test |
| num_examples: 523 |
| - config_name: unbalanced-review-sample |
| features: |
| - name: audio |
| dtype: |
| audio: |
| decode: false |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': NSW_3 |
| '1': NSW_2 |
| '2': NSW_1 |
| '3': SW_Dana |
| '4': SW_Luna |
| '5': SW_Nana |
| '6': SW_Neo |
| '7': SW_Nikita |
| '8': SW_Shy |
| '9': SW_Yosefa |
| - name: name |
| dtype: string |
| - name: onset |
| dtype: float32 |
| - name: offset |
| dtype: float32 |
| - name: duration |
| dtype: float32 |
| - name: recording_duration |
| dtype: float32 |
| - name: whistle_type |
| dtype: int64 |
| - name: whistle_name |
| dtype: string |
| - name: f0_time |
| sequence: float32 |
| - name: f0_hz |
| sequence: float32 |
| - name: f0_conf |
| sequence: float32 |
| - name: f0_ok |
| dtype: bool |
| - name: f0_bad_reason |
| dtype: string |
| - name: f0_spectrogram |
| dtype: image |
| splits: |
| - name: train |
| num_examples: 336 |
| - name: validation |
| num_examples: 72 |
| - name: test |
| num_examples: 72 |
| task_categories: |
| - audio-classification |
| tags: |
| - arxiv:2609.34839 |
| - dolphin |
| - bioacoustics |
| - whistle-classification |
| - audio |
| - f0 |
| - spectrogram |
| configs: |
| - config_name: all |
| data_files: |
| - split: train |
| path: all/train-* |
| - split: validation |
| path: all/validation-* |
| - split: test |
| path: all/test-* |
| - config_name: all-review-sample |
| data_files: |
| - split: train |
| path: all-review-sample/train-* |
| - split: validation |
| path: all-review-sample/validation-* |
| - split: test |
| path: all-review-sample/test-* |
| - config_name: balanced |
| data_files: |
| - split: train |
| path: balanced/train-* |
| - split: validation |
| path: balanced/validation-* |
| - split: test |
| path: balanced/test-* |
| - config_name: balanced-review-sample |
| data_files: |
| - split: train |
| path: balanced-review-sample/train-* |
| - split: validation |
| path: balanced-review-sample/validation-* |
| - split: test |
| path: balanced-review-sample/test-* |
| - config_name: unbalanced |
| data_files: |
| - split: train |
| path: unbalanced/train-* |
| - split: validation |
| path: unbalanced/validation-* |
| - split: test |
| path: unbalanced/test-* |
| - config_name: unbalanced-review-sample |
| data_files: |
| - split: train |
| path: unbalanced-review-sample/train-* |
| - split: validation |
| path: unbalanced-review-sample/validation-* |
| - split: test |
| path: unbalanced-review-sample/test-* |
| --- |
| |
| # OpenWhistle Classification Finetuning Dataset |
|
|
| `dolphinteam/OpenWhistle-Classification-Finetuning` is the public |
| classification finetuning dataset used for dolphin whistle identity |
| classification. It contains short whistle clips, whistle-level metadata, |
| fundamental-frequency tracks, rendered F0 spectrograms, and integer class |
| labels. |
|
|
| The main reviewer-facing subset is the balanced `balanced` config. It contains |
| six classes: |
|
|
| - `NSW_1` (`label=0`) |
| - `SW_Luna` (`label=1`) |
| - `SW_Nana` (`label=2`) |
| - `SW_Neo` (`label=3`) |
| - `SW_Nikita` (`label=4`) |
| - `SW_Yosefa` (`label=5`) |
|
|
| The full dataset is split by recording session, so no session appears in more |
| than one of `train`, `validation`, or `test`. Smaller deterministic review |
| configs are also provided so reviewers can inspect representative examples |
| quickly without downloading the complete data first. |
|
|
| ## Dataset Contents |
|
|
| - Hugging Face repo: `dolphinteam/OpenWhistle-Classification-Finetuning` |
| - Main balanced config: `balanced` |
| - Reviewer convenience config: `balanced-review-sample` |
| - Public columns common to all configs: `audio`, `label`, `name`, `onset`, `offset`, `duration`, |
| `recording_duration`, `whistle_type`, `whistle_name`, `f0_time`, `f0_hz`, |
| `f0_conf`, `f0_ok`, `f0_bad_reason`, `f0_spectrogram` |
| - The `all` and `all-review-sample` configs additionally include `snr_db`, the |
| estimated clip-level signal-to-noise ratio in dB. |
|
|
| ## Balanced Dataset Splits |
|
|
| | Split | Rows | NSW_1 | SW_Luna | SW_Nana | SW_Neo | SW_Nikita | SW_Yosefa | Sessions | |
| | --- | ---: | ---: | ---: | ---: | ---: | ---: | ---: | ---: | |
| | `train` | 2,100 | 350 | 350 | 350 | 350 | 350 | 350 | 161 | |
| | `validation` | 450 | 75 | 75 | 75 | 75 | 75 | 75 | 54 | |
| | `test` | 450 | 75 | 75 | 75 | 75 | 75 | 75 | 37 | |
| | **Total** | **3,000** | **500** | **500** | **500** | **500** | **500** | **500** | **252** | |
|
|
| The split assignment was generated with seed `42` and exact class balancing. |
| Session leakage checks found no overlap between any pair of splits. |
|
|
| ## Available Subsets |
|
|
| The repository provides three full classification subsets and their smaller |
| review counterparts: |
|
|
| | Subset/config | Rows | Classes | Sessions | Purpose | |
| | --- | ---: | ---: | ---: | --- | |
| | `balanced` | 3,000 | 6 | 252 | Main balanced six-class finetuning dataset | |
| | `unbalanced` | 3,488 | 10 | 258 | Ten-class finetuning dataset with capped rare classes | |
| | `all` | 8,354 | 10 | 261 | Ten-class dataset preserving the full available class distribution | |
| | `balanced-review-sample` | 480 | 6 | Same source split design | Small reviewer sample from `balanced` | |
| | `unbalanced-review-sample` | 480 | 10 | Same source split design | Small reviewer sample from `unbalanced` | |
| | `all-review-sample` | 480 | 10 | Same source split design | Small reviewer sample from `all` | |
|
|
| The ten-class subsets use the following labels: |
|
|
| - `NSW_3` |
| - `NSW_2` |
| - `NSW_1` |
| - `SW_Dana` |
| - `SW_Luna` |
| - `SW_Nana` |
| - `SW_Neo` |
| - `SW_Nikita` |
| - `SW_Shy` |
| - `SW_Yosefa` |
|
|
| The `balanced` subset keeps the six classes listed above and is the recommended |
| starting point for reviewers and model finetuning. The `unbalanced` and `all` |
| subsets expose the broader ten-class label space for additional analysis. |
|
|
| ## Review Samples |
|
|
| Review samples are small deterministic subsets of the same public dataset. They |
| were created only to make review and manual inspection easier. They are not a |
| replacement for the full configs used for model development or reporting. |
|
|
| ### How The Review Samples Were Created |
|
|
| All review samples were built after the session-disjoint train/validation/test |
| splits were finalized. The review-sample scripts preserve the original split |
| assignment: reviewer training examples come only from the original `train` |
| split, reviewer validation examples only from `validation`, and reviewer test |
| examples only from `test`. |
|
|
| For `balanced-review-sample`, rows were sampled separately within each split and |
| class. Each class group was shuffled deterministically with |
| `numpy.default_rng(seed + split_index)` using seed `42`, then capped at 56 rows |
| per class for `train` and 12 rows per class for both `validation` and `test`. |
| This keeps the same 70/15/15 split ratio as the full `balanced` config while |
| keeping every class equally represented. |
|
|
| For `unbalanced-review-sample` and `all-review-sample`, the same deterministic |
| shuffle was used, but the target rows were allocated proportionally to the |
| source class distribution inside each split. This preserves the class imbalance |
| of the larger source configs while keeping the review download small. |
|
|
| ### Review Sample Sizes |
|
|
| | Config | Source config | Strategy | Train | Validation | Test | Total | |
| | --- | --- | --- | ---: | ---: | ---: | ---: | |
| | `balanced-review-sample` | `balanced` | Equal rows per class within each split | 336 | 72 | 72 | 480 | |
| | `unbalanced-review-sample` | `unbalanced` | Proportional class distribution within each split | 336 | 72 | 72 | 480 | |
| | `all-review-sample` | `all` | Proportional class distribution within each split | 336 | 72 | 72 | 480 | |
|
|
| The reviewer-facing sample for the main balanced dataset is |
| `balanced-review-sample`. The other review samples are included so each full |
| subset has a matching small inspection subset. |
|
|
| ## Loading The Data |
|
|
| ```python |
| from datasets import load_dataset |
| |
| full = load_dataset( |
| "dolphinteam/OpenWhistle-Classification-Finetuning", |
| "balanced", |
| ) |
| review = load_dataset( |
| "dolphinteam/OpenWhistle-Classification-Finetuning", |
| "balanced-review-sample", |
| ) |
| ``` |
|
|
| Optional broader configs can be loaded by passing `"unbalanced"` or `"all"` as |
| the second `load_dataset` argument. Their corresponding review configs are |
| `"unbalanced-review-sample"` and `"all-review-sample"`. |
|
|
| ## Paper, collection, and authors |
|
|
| - Paper: [OpenWhistle: A Large-Scale Longitudinal Dataset and Benchmark of Bottlenose Dolphin Vocalizations](https://arxiv.org/abs/2609.34839) |
| - Hugging Face collection: [NeurIPS 2026 OpenWhistle](https://huggingface.co/collections/dolphinteam/neurips26-openwhistle) |
| - This repository: [https://huggingface.co/datasets/dolphinteam/OpenWhistle-Classification-Finetuning](https://huggingface.co/datasets/dolphinteam/OpenWhistle-Classification-Finetuning) |
|
|
| Authors: Faadil Mustun, Chiara Semenzin, Roberto Dessi, Pablo Robin Guerrero, Pierre Orhan, Alexis Emanuelli, Emanuele Rossi, Yair Lakretz, Gonzalo de Polavieja, and German Sumbre. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{mustun2026openwhistle, |
| title = {OpenWhistle: A Large-Scale Longitudinal Dataset and Benchmark of Bottlenose Dolphin Vocalizations}, |
| author = {Mustun, Faadil and Semenzin, Chiara and Dessi, Roberto and Robin Guerrero, Pablo and Orhan, Pierre and Emanuelli, Alexis and Rossi, Emanuele and Lakretz, Yair and de Polavieja, Gonzalo and Sumbre, German}, |
| year = {2026}, |
| eprint = {2609.34839}, |
| archivePrefix = {arXiv}, |
| primaryClass = {cs.CL}, |
| url = {https://arxiv.org/abs/2609.34839} |
| } |
| ``` |
|
|
