Datasets:
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.
WaveMaster External Vibrato Evaluation Set
This dataset supports the external-corpus analysis in Presence Is Not
Placement: Auditing What Vibrato Metrics Measure. It contains unaccompanied
recordings of eight professional singers performing Caro mio ben. A full
release may additionally include the counterfactual renders used to test
whether a learned vibrato-presence judge responds to note-level vibrato
placement; metadata.csv is the authoritative list of included files.
Consent and identifiability
The singers participated through the Bach-Millennium Program. Each participant gave written informed consent before recording, including consent to redistribute their voice recording. A singing voice is inherently identifiable; the singer IDs in this repository are pseudonyms, not a claim that the audio is anonymous. Names, contact information, consent forms, and unrelated recordings are not included.
The recordings were used only as an external evaluation set. They were not used to train WaveMaster or any of its five fold-specific classifiers.
Contents
Every release contains the eight original recordings:
audio/
original/singer_01.mp3 ... singer_08.mp3
metadata.csv
If redistribution of modified derivatives is also authorized, the builder can add the exact audit renders:
audio/
identity/singer_01.wav ... singer_08.wav
shuffle/singer_01.wav ... singer_08.wav
jitter/singer_01.wav ... singer_08.wav
depth_0p5/singer_01.wav ... singer_08.wav
depth_2/singer_01.wav ... singer_08.wav
constant_130/singer_01.wav ... singer_08.wav
constant_420/singer_01.wav ... singer_08.wav
original contains the contributed performances. When included, identity is a WORLD
round-trip with no intended pitch change. shuffle reassigns the measured
vibrato depths among notes. jitter applies a similarly sized random note-level
perturbation. depth_0p5 and depth_2 globally halve or double vibrato depth.
constant_130 and constant_420 assign the same target depth, in cents, to
every measured note.
metadata.csv records the pseudonymous singer ID, condition, manipulation
amount, source-versus-derived status, duration, sample rate, channel count,
codec, file size, and SHA-256 checksum.
Only the Caro mio ben files used in the paper are included. The singers also recorded scales, passaggio exercises, and other songs; those recordings are not part of this research release.
Dataset creation
The original recordings were made in a room and with equipment different from VocalSet. When included, the counterfactual files were generated with the paper's public analysis code. Fundamental frequency was decomposed into a slow trend, a 3--9 Hz vibrato component, and a residual. Only the vibrato component was scaled or reassigned, after which WORLD resynthesized the audio while retaining the analyzed spectral envelope and aperiodicity parameters.
Intended use and limitations
The intended use is reproduction and extension of research on vibrato measurement, expressive-placement evaluation, and singing synthesis. The set is small: eight singers, one Western classical song, one take per singer, and one recording context. It should not be treated as representative of singers, singing traditions, or listeners generally. Counterfactual files contain WORLD resynthesis artifacts and are controlled stimuli, not natural performances.
Do not infer identity or sensitive traits from the recordings. Do not use the recordings to impersonate a participant. See TERMS.md for the applicable release terms.
Citation
Citation information will be added when the paper has a stable public URL.
Contact
Questions about the dataset can be opened as a discussion on its Hugging Face repository or sent to the corresponding author listed in the paper.
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