Datasets:

mikulrai
/

coral-reef-bioacoustics

Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 246, in _split_generators
                  raise ValueError(
              ValueError: `file_name`, `*_file_name`, `file_names` or `*_file_names` must be present as dictionary key in metadata files
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 65, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                         ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

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Coral Reef Bioacoustics Dataset

Underwater audio recordings from two contrasting coral reef sites in Moreton Bay, Queensland, Australia, labeled for binary reef health classification.

Dataset Description

This dataset contains 19 WAV recordings captured using a Cetacean Research Technology CRT-40P hydrophone (48 kHz / 24-bit) deployed 0.5-1 m above the seafloor in November 2025. The recordings capture the natural soundscape of sub-tropical turbid reefs, including invertebrate activity (snapping shrimp), fish vocalizations, and ambient noise.

Sites

Site	Label	Coral Cover	Description
Myora Reef	Healthy	~23-42%	Acropora-dominated reef benefiting from oceanic flushing
Goat Island	Degraded	Low	Sediment-impacted reef damaged by 2022 flood events and riverine runoff

Statistics

Total recordings: 19 WAV files
Healthy (Myora Reef): 11 files (~349 MB, ~50.8 min)
Degraded (Goat Island): 8 files (~220 MB, ~30.0 min)
Format: WAV, 48 kHz, 24-bit, mono
Total duration: ~80.8 minutes

Dataset Structure

data/
  healthy/
    myora_01.WAV ... myora_11.WAV
  degraded/
    goat_01.WAV ... goat_08.WAV
metadata.csv

Usage

This dataset is designed for use with Google's SurfPerch bioacoustic foundation model. Audio segments are typically processed as 5-second non-overlapping windows at 32 kHz.

from huggingface_hub import snapshot_download

snapshot_download(
    repo_id="mikulrai/coral-reef-bioacoustics",
    repo_type="dataset",
    local_dir="./reef_audio",
)

Citation

If you use this dataset, please cite:

Mikul Rai. "Classification of Sub-tropical Reef Health using Bioacoustic Embeddings." 2025.

License

This dataset is released under the Creative Commons Attribution 4.0 International License.

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