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Cannot get the split names for the dataset.
Error code:   SplitsNamesError
Exception:    TypeError
Message:      __init__() got an unexpected keyword argument 'audio_file_path_column'
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/responses/splits.py", line 79, in get_splits_response
                  split_full_names = get_dataset_split_full_names(dataset, hf_token)
                File "/src/services/worker/src/worker/responses/splits.py", line 39, in get_dataset_split_full_names
                  return [
                File "/src/services/worker/src/worker/responses/splits.py", line 42, in <listcomp>
                  for split in get_dataset_split_names(dataset, config, use_auth_token=hf_token)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 426, in get_dataset_split_names
                  info = get_dataset_config_info(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 355, in get_dataset_config_info
                  builder = load_dataset_builder(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1478, in load_dataset_builder
                  builder_instance: DatasetBuilder = builder_cls(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1285, in __init__
                  super().__init__(*args, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 313, in __init__
                  info.update(self._info())
                File "/tmp/modules-cache/datasets_modules/datasets/collectivat--tv3_parla/03b65a8c7bb12abcbcf5bfc7732e5e9c708ca5088569a985856290c6abf148a2/tv3_parla.py", line 77, in _info
                  AutomaticSpeechRecognition(audio_file_path_column="path", transcription_column="text")
              TypeError: __init__() got an unexpected keyword argument 'audio_file_path_column'

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Dataset Card for TV3Parla

Dataset Summary

This corpus includes 240 hours of Catalan speech from broadcast material. The details of segmentation, data processing and also model training are explained in Külebi, Öktem; 2018. The content is owned by Corporació Catalana de Mitjans Audiovisuals, SA (CCMA); we processed their material and hereby making it available under their terms of use.

This project was supported by the Softcatalà Association.

Supported Tasks and Leaderboards

The dataset can be used for:

  • Language Modeling.
  • Automatic Speech Recognition (ASR) transcribes utterances into words.

Languages

The dataset is in Catalan (ca).

Dataset Structure

Data Instances

{
  'path': 'tv3_0.3/wav/train/5662515_1492531876710/5662515_1492531876710_120.180_139.020.wav',
  'audio': {'path': 'tv3_0.3/wav/train/5662515_1492531876710/5662515_1492531876710_120.180_139.020.wav',
   'array': array([-0.01168823,  0.01229858,  0.02819824, ...,  0.015625  ,
          0.01525879,  0.0145874 ]),
   'sampling_rate': 16000},
  'text': 'algunes montoneres que que et feien anar ben col·locat i el vent també hi jugava una mica de paper bufava vent de cantó alguns cops o de cul i el pelotón el vent el porta molt malament hi havia molts nervis'
}

Data Fields

  • path (str): Path to the audio file.
  • audio (dict): A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate. Note that when accessing the audio column: dataset[0]["audio"] the audio file is automatically decoded and resampled to dataset.features["audio"].sampling_rate. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus, it is important to first query the sample index before the "audio" column, i.e. dataset[0]["audio"] should always be preferred over dataset["audio"][0].
  • text (str): Transcription of the audio file.

Data Splits

The dataset is split into "train" and "test".

train test
Number of examples 159242 2220

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

Creative Commons Attribution-NonCommercial 4.0 International.

Citation Information

@inproceedings{kulebi18_iberspeech,
  author={Baybars Külebi and Alp Öktem},
  title={{Building an Open Source Automatic Speech Recognition System for Catalan}},
  year=2018,
  booktitle={Proc. IberSPEECH 2018},
  pages={25--29},
  doi={10.21437/IberSPEECH.2018-6}
}

Contributions

Thanks to @albertvillanova for adding this dataset.

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