Datasets:

Chakshu
/

gujarati-tts

Tasks:

Text-to-Speech

Languages:

Gujarati

Size:

1K<n<10K

License:

Dataset card Files Files and versions

xet

Community

Dataset Viewer

The dataset viewer is not available for this subset.

Cannot get the split names for the config 'default' of the dataset.

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.

Gujarati TTS Dataset

SPICOR Gujarati Female TTS dataset in WebDataset format.

Dataset Details

Total Files: 9100
Duration: ~33.6 hours
Speaker: Spk0001 (Female, Age 33)
Language: Gujarati
Domains: 19 domains (Agriculture, Entertainment, Finance, Health, Science, Sports, etc.)
Recording: 48kHz, 24-bit, Studio quality

Loading the Dataset

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("webdataset", data_dir="Chakshu/gujarati-tts/resolve/main/data")

# Access audio and text
for sample in dataset["train"]:
    audio = sample["wav"]  # Audio bytes (WAV format)
    metadata = sample["json"]  # Metadata dict
    print(metadata["text"])  # Gujarati transcription
    print(metadata["speaker_id"])  # Speaker ID
    print(metadata["domain"])  # Domain

Columns

Each sample contains:

audio (.wav file): Raw WAV audio bytes
metadata (.json file):
- text: Gujarati transcription
- file_id: Unique identifier
- category: Category code (e.g., SPOR, AGRI)
- domain: Full domain name
- speaker_id: Spk0001
- speaker_gender: Female
- speaker_age: 33
- language: gu (Gujarati)

Splits

train: 8242 files in 17 TAR shards
test: 858 files in 2 TAR shards

Citation

@misc{SPICOR_TTS_2.0_Corpus,
    Title = {SPICOR TTS_2.0 Corpus - A 57+ hour domain-rich Gujarati TTS Corpus},
    Authors = {Abhayjeet Et al.},
    Year = {2025}
}

License

CC-BY-4.0

Downloads last month: 9

Total file size:

26 GB