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 "/src/services/worker/src/worker/job_runners/config/split_names.py", line 159, in compute
                  compute_split_names_from_info_response(
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 131, in compute_split_names_from_info_response
                  config_info_response = get_previous_step_or_raise(kind="config-info", dataset=dataset, config=config)
                File "/src/libs/libcommon/src/libcommon/simple_cache.py", line 567, in get_previous_step_or_raise
                  raise CachedArtifactError(
              libcommon.simple_cache.CachedArtifactError: The previous step failed.
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 499, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 175, in _split_generators
                  pa_metadata_table = self._read_metadata(downloaded_metadata_file, metadata_ext=metadata_ext)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 245, in _read_metadata
                  return paj.read_json(f)
                File "pyarrow/_json.pyx", line 308, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0
              
              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 75, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 572, in get_dataset_split_names
                  info = get_dataset_config_info(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 504, 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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This custom multilingual-multispeaker TTS speech corpus contains 12.800 balanced samples with audio files (wav format sampled with 16000 Hz) and related transcriptions (csv format with two columns) from 18 speakers. The dataset has been assembled from the following sources:

  • VCTK : 428 + 426 + 426 english male samples (p259, p274, p286) (CC BY 4.0)
  • LJSpeech : 1280 english female samples (public domain)
  • m-ailabs : 1280 french male samples (public free licence)
  • SIWIS : 1024 french female samples (CC BY 4.0)
  • Rhasspy : 1082 german female samples (CC0 1.0)
  • Thorsten : 1280 german male samples (CC0)
  • TTS-Portuguese-Corpus : 2560 portuguese male samples (CC BY 4.0)
  • Marylux : 663 luxembourgish & 198 german & 256 french female samples (CC BY-NC-SA 4.0)
  • uni.lu : 409 luxembourgish female & 231 luxembourgish male samples (© uni.lu)
  • rtl.lu : 1257 luxembourgish male samples (© RTL-CLT-UFA)
  • Charel : 11 luxembourgish boy samples from my grandchild

The dataset has been manually checked and the transcriptions have been expanded and eventually corrected to comply with the audio files. The data structure is equivalent to the mailabs format. The folder nesting is shown below:

mailabs
   language-1
      by_book
         female 
            speaker-1
               wavs/ folder
               metadata.csv
               metadata-train.csv
               metadata-eval.csv
            speaker-2
               wavs/ folder
               metadata.csv
               metadata-train.csv
               metadata-eval.csv
            ...
         male
            speaker-1   
               wavs/ folder
               metadata.csv
               metadata-train.csv
               metadata-eval.csv
            speaker-2
               wavs/ folder
               metadata.csv
               metadata-train.csv
               metadata-eval.csv
            ...               
   language-2
      by_book
         ...
   language-3
      by_book
         ...
   ...                                  

Thanks to RTL and to the University of Luxembourg for permission to use and share selected copyrighted data.

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