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ParlaSpeech-HR / README.md
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metadata
dataset_info:
  features:
    - name: id
      dtype: string
    - name: audio
      dtype:
        audio:
          sampling_rate: 16000
    - name: text
      dtype: string
    - name: text_normalised
      dtype: string
    - name: words
      list:
        - name: char_e
          dtype: int64
        - name: char_s
          dtype: int64
        - name: time_e
          dtype: float64
        - name: time_s
          dtype: float64
    - name: audio_length
      dtype: float64
    - name: date
      dtype: string
    - name: speaker_name
      dtype: string
    - name: speaker_gender
      dtype: string
    - name: speaker_birth
      dtype: string
    - name: speaker_party
      dtype: string
    - name: party_orientation
      dtype: string
    - name: party_status
      dtype: string
  splits:
    - name: train
      num_bytes: 162874686121.866
      num_examples: 867581
  download_size: 179092718936
  dataset_size: 162874686121.866
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*

The Croatian Parliamentary Spoken Dataset ParlaSpeech-HR 2.0

The master dataset can be found at http://hdl.handle.net/11356/1914.

The ParlaSpeech-HR dataset is built from the transcripts of parliamentary proceedings available in the Croatian part of the ParlaMint corpus (http://hdl.handle.net/11356/1859), and the parliamentary recordings available from the Croatian Parliament's YouTube channel (https://www.youtube.com/c/InternetTVHrvatskogasabora).

The dataset consists of audio segments that correspond to specific sentences in the transcripts. The transcript contains word-level alignments to the recordings, each instance consisting of character and millisecond start and end offsets, allowing for simple further segmentation of long sentences into shorter segments for ASR and other memory-sensitive applications. Sequences longer than 30 seconds have already been removed from this dataset, which should allow for a simple usage on most modern GPUs.

Each segment has an identifier reference to the ParlaMint 4.0 corpus (http://hdl.handle.net/11356/1859) via the utterance ID and character offsets.

While in the original dataset all the speaker information from the ParlaMint corpus is available via the speaker_info attribute, in the HuggingFace version only a subset of metadata is available, namely: the date, the name of the speaker, their gender, year of birth, party affiliation at that point in time, status of the party at that point in time (coalition or opposition), and party orientation (left, right, centre etc.).

Different to the original dataset, this version has also a text_normalised attribute, which contains the text with parliamentary comments ([[Applause]] and similar) removed.

If you use the dataset, please cite the following paper:

@inproceedings{ljubesic-etal-2022-parlaspeech,
    title = "{P}arla{S}peech-{HR} - a Freely Available {ASR} Dataset for {C}roatian Bootstrapped from the {P}arla{M}int Corpus",
    author = "Ljube{\v{s}}i{\'c}, Nikola  and
      Kor{\v{z}}inek, Danijel  and
      Rupnik, Peter  and
      Jazbec, Ivo-Pavao",
    editor = "Fi{\v{s}}er, Darja  and
      Eskevich, Maria  and
      Lenardi{\v{c}}, Jakob  and
      de Jong, Franciska",
    booktitle = "Proceedings of the Workshop ParlaCLARIN III within the 13th Language Resources and Evaluation Conference",
    month = jun,
    year = "2022",
    address = "Marseille, France",
    publisher = "European Language Resources Association",
    url = "https://aclanthology.org/2022.parlaclarin-1.16",
    pages = "111--116",
}

@inproceedings{ljubesic2024parlaspeech,
  title={The ParlaSpeech Collection of Automatically Generated Speech and Text Datasets from Parliamentary Proceedings},
  author={Ljube{\v{s}}i{\'c}, Nikola and Rupnik, Peter and Kor{\v{z}}inek, Danijel},
  booktitle={International Conference on Speech and Computer},
  pages={137--150},
  organization={Springer},
  month = jun,
  year = "2022",
  address = "Belgrade, Serbia",
}