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---
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",
}
``` |