README.md

---
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
dataset_info:
  features:
  - name: audio
    dtype:
      audio:
        sampling_rate: 16000
  - name: audio_end
    dtype: float64
  - name: audio_length
    dtype: float64
  - name: audio_source
    dtype: string
  - name: audio_start
    dtype: float64
  - name: id
    dtype: string
  - name: sentence_id
    dtype: string
  - name: speaker_info
    struct:
    - name: Agenda
      dtype: string
    - name: Body
      dtype: string
    - name: Date
      dtype: string
    - name: ID
      dtype: string
    - name: Lang
      dtype: string
    - name: Meeting
      dtype: string
    - name: Party_orientation
      dtype: string
    - name: Party_status
      dtype: string
    - name: Session
      dtype: string
    - name: Sitting
      dtype: string
    - name: Speaker_ID
      dtype: string
    - name: Speaker_MP
      dtype: string
    - name: Speaker_birth
      dtype: string
    - name: Speaker_gender
      dtype: string
    - name: Speaker_minister
      dtype: string
    - name: Speaker_name
      dtype: string
    - name: Speaker_party
      dtype: string
    - name: Speaker_party_name
      dtype: string
    - name: Speaker_role
      dtype: string
    - name: Subcorpus
      dtype: string
    - name: Term
      dtype: string
    - name: Text_ID
      dtype: string
    - name: Title
      dtype: string
  - name: text
    dtype: string
  - name: text_end
    dtype: int64
  - name: text_start
    dtype: int64
  - name: words
    list:
    - name: char_e
      dtype: int64
    - name: char_s
      dtype: int64
    - name: id
      dtype: string
    - name: time_e
      dtype: float64
    - name: time_s
      dtype: float64
  splits:
  - name: train
    num_bytes: 187604534404.769
    num_examples: 720091
  download_size: 40094695351
  dataset_size: 187604534404.769
---
# Dataset Card for "ParlaSpeech-CZ.v1.0"


The ParlaSpeech-CZ dataset is built from the transcripts of parliamentary proceedings available in the Czech part of the ParlaMint corpus, and the parliamentary recordings available from the Czech Parliament's YouTube channel.

The corpus 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",
}
```