The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 246, in _split_generators
raise ValueError(
"`file_name`, `*_file_name`, `file_names` or `*_file_names` must be present as dictionary key in metadata files"
)
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 71, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/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.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
uncommon-meter-beat-dataset
English | 日本語
The uncommon-meter-beat-dataset repository is an annotation-only beat/downbeat dataset designed to improve coverage of odd and changing meter. Public beat-tracking datasets are often dominated by 4/4 material, which makes it harder to train and evaluate models on less common meters. This repository focuses on tracks that contain uncommon time signatures, meter changes, or both.
Audio is intentionally not distributed. The repository publishes annotation files and metadata only. youtube_id is the stable key for each track, and metadata.csv provides the lookup table.
Current Snapshot
This block is auto-generated from parsed_beats/ by python update_dataset_docs.py.
- 114 tracks
- 14,148 annotated measures
- About 420.4 minutes of annotated duration
- 17 distinct time signatures
- 81 tracks with meter changes
- 95 tracks containing odd meters
- 4/4 accounts for about 17.6% of all measures
- 54.9% of measures are outside the common set
{2/4, 3/4, 4/4, 6/8}
Why This Dataset Exists
The goal is not to represent everyday music uniformly. The goal is to cover a failure case: beat-tracking models often generalize poorly to odd meter and changing meter because these cases are sparse in many public datasets. This collection is intentionally biased toward that gap.
Repository Layout
beats/ Original .beat annotation files
parsed_beats/ Normalized JSON annotations used by the analysis scripts
output_graphs/ Dataset statistics figures
export_metadata_csv.py Generates metadata.csv from the annotation files
update_dataset_docs.py Updates snapshot sections in README and dataset cards
metadata.csv Track-level metadata keyed by youtube_id
Annotation Format
Each parsed JSON file contains:
youtube_id: stable track identifiermeasures: list of measure-level annotations
Each measure entry includes:
measure_indexdownbeat_sectime_sig_numtime_sig_dentempo_bpmbase_noteannotations
This makes the repository best described as an annotation-only downbeat and time-signature dataset. Audio retrieval and any licensing checks for source media are left to the user.
Metadata
metadata.csv is generated from parsed_beats/ and includes:
youtube_idandyoutube_url- track title inferred from the original filename
- original
.beatfilename and parsed JSON filename - measure count and estimated track duration
- unique time signatures per track
- flags for meter changes, odd meters, and uncommon meters
- annotation counts and annotation label inventory
Regenerate it with:
python export_metadata_csv.py
Statistics
The figures in output_graphs/ summarize the current dataset snapshot.
Reproducing the Derived Files
python parse_beats.py
python analyze_beat_data.py
python export_metadata_csv.py
python update_dataset_docs.py
analyze_beat_data.py requires matplotlib. The metadata export script and the document snapshot updater use only the Python standard library.
Limitations
- The collection is intentionally biased toward uncommon and changing meter, so it is not representative of general music.
- Audio is not included.
- Estimated track duration is derived from consecutive downbeats, with the final measure duration estimated from local tempo and time signature.
- Filenames keep their original human-readable titles;
youtube_idshould be treated as the canonical identifier.
Before Publishing
This repository is released under the MIT License. Audio is not included.
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