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/webdataset/webdataset.py", line 81, in _split_generators
first_examples = list(islice(pipeline, self.NUM_EXAMPLES_FOR_FEATURES_INFERENCE))
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
fs: fsspec.AbstractFileSystem = fsspec.filesystem("memory")
~~~~~~~~~~~~~~~~~^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 302, in filesystem
cls = get_filesystem_class(protocol)
File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 239, in get_filesystem_class
raise ValueError(f"Protocol not known: {protocol}")
ValueError: Protocol not known: memory
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 66, 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.
🗣️ Synthetic Voice Description Dataset for Voice Conversion
Overview
This dataset contains 3.180 synthetically generated voice samples, each paired with a caption that roughly describes how the voice sounds. Captions typically include information about the age, gender, accent, and sometimes general vocal qualities (e.g., "old woman, Irish accent").
All voices are synthetically generated and do not represent any real person. This makes the dataset ideal for training and evaluating voice conversion models without infringing on personhood or identity rights.
📁 Dataset Contents
- A CSV file containing pairs of:
description: A short text caption describing the voicematched_filename: The name of the corresponding.wavfile
Example rows from the CSV:
description,matched_filename
"old woman, Irish accent",00399-000.wav
"old man, valley girl accent",01074-001.wav
"young man, Scottish accent",18297-001.wav
"middle-aged man, Chinese accent",00952-002.wav
- A TAR archive that contains:
- The
voice-captions.csvfile (as described above) - All 3.180 corresponding
.wavaudio files
- The
🎯 Purpose
The dataset is designed to serve as a target files for voice conversion tasks. It can be used to:
- Convert existing voice data into synthetic voices with known, described properties
⚙️ Google Colab for Seed-VC Fine-Tuning
A community-developed fine-tuning notebook for Seed-VC (a voice conversion model) is available on Google Colab:
This notebook allows you to take real or synthetic voice data and convert it into one of the target voices.
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