The viewer is disabled because this dataset repo requires arbitrary Python code execution. Please consider
removing the
loading script
and relying on
automated data support
(you can use
convert_to_parquet
from the datasets
library). If this is not possible, please
open a discussion
for direct help.
Dataset Card for ParlamentParla
Dataset Summary
This is the ParlamentParla speech corpus for Catalan prepared by Col·lectivaT. The audio segments were extracted from recordings the Catalan Parliament (Parlament de Catalunya) plenary sessions, which took place between 2007/07/11 - 2018/07/17. We aligned the transcriptions with the recordings and extracted the corpus. The content belongs to the Catalan Parliament and the data is released conforming their terms of use.
Preparation of this corpus was partly supported by the Department of Culture of the Catalan autonomous government, and the v2.0 was supported by the Barcelona Supercomputing Center, within the framework of Projecte AINA of the Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya.
As of v2.0 the corpus is separated into 211 hours of clean and 400 hours of other quality segments. Furthermore, each speech segment is tagged with its speaker and each speaker with their gender. The statistics are detailed in the readme file.
Supported Tasks and Leaderboards
The dataset can be used for:
- Language Modeling.
- Automatic Speech Recognition (ASR) transcribes utterances into words.
- Speaker Identification (SI) classifies each utterance for its speaker identity as a multi-class classification, where speakers are in the same predefined set for both training and testing.
Languages
The dataset is in Catalan (ca-ES
).
Dataset Structure
Data Instances
{
'path': 'clean_train/c/c/ccca4790a55aba3e6bcf_63.88_74.06.wav'
'audio': {
'path': 'clean_train/c/c/ccca4790a55aba3e6bcf_63.88_74.06.wav',
'array': array([-6.10351562e-05, -6.10351562e-05, -1.22070312e-04, ...,
-1.22070312e-04, 0.00000000e+00, -3.05175781e-05]),
'sampling_rate': 16000
},
'speaker_id': 167,
'sentence': "alguns d'ells avui aquí presents un agraïment a aquells que mantenen viva la memòria aquest acte de reparació i dignitat és",
'gender': 0,
'duration': 10.18
}
Data Fields
path
(str): The 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 todataset.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 overdataset["audio"][0]
.speaker_id
(int): The speaker ID.sentence
(str): The sentence the user was prompted to speak.gender
(ClassLabel): The gender of the speaker (0: 'F', 1: 'M').duration
(float): Duration of the speech.
Data Splits
The dataset is split in: "train", "validation" and "test".
Dataset Creation
The dataset is created by aligning the parliamentary session transcripts and the audiovisual content. For more detailed information please consult this paper.
Curation Rationale
We created this corpus to contribute to the development of language models in Catalan, a low-resource language.
Source Data
Initial Data Collection and Normalization
The audio segments were extracted from recordings the Catalan Parliament (Parlament de Catalunya) plenary sessions, which took place between 2007/07/11 - 2018/07/17. The cleaning procedures are in the archived repository Long Audio Aligner
Who are the source language producers?
The parliamentary members of the legislatures between 2007/07/11 - 2018/07/17
Annotations
The dataset is unannotated.
Annotation process
[N/A]
Who are the annotators?
[N/A]
Personal and Sensitive Information
The initial content is publicly available furthermore, the identities of the parliamentary members are anonymized.
Considerations for Using the Data
Social Impact of Dataset
We hope this corpus contributes to the development of language models in Catalan, a low-resource language.
Discussion of Biases
This dataset has a gender bias, however since the speakers are tagged according to their genders, creating a balanced subcorpus is possible.
Subcorpus | Gender | Duration (h) |
---|---|---|
other_test | F | 2.516 |
other_dev | F | 2.701 |
other_train | F | 109.68 |
other_test | M | 2.631 |
other_dev | M | 2.513 |
other_train | M | 280.196 |
other total | 400.239 | |
clean_test | F | 2.707 |
clean_dev | F | 2.576 |
clean_train | F | 77.905 |
clean_test | M | 2.516 |
clean_dev | M | 2.614 |
clean_train | M | 123.162 |
clean total | 211.48 | |
Total | 611.719 |
Other Known Limitations
The text corpus belongs to the domain of Catalan politics
Additional Information
Dataset Curators
Text Mining Unit (TeMU) at the Barcelona Supercomputing Center (bsc-temu@bsc.es)
This work was funded by the Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya within the framework of Projecte AINA.
Licensing Information
Creative Commons Attribution 4.0 International.
Citation Information
@dataset{kulebi_baybars_2021_5541827,
author = {Külebi, Baybars},
title = {{ParlamentParla - Speech corpus of Catalan
Parliamentary sessions}},
month = oct,
year = 2021,
publisher = {Zenodo},
version = {v2.0},
doi = {10.5281/zenodo.5541827},
url = {https://doi.org/10.5281/zenodo.5541827}
}
For the paper:
@inproceedings{kulebi2022parlamentparla,
title={ParlamentParla: A Speech Corpus of Catalan Parliamentary Sessions},
author={K{\"u}lebi, Baybars and Armentano-Oller, Carme and Rodr{\'\i}guez-Penagos, Carlos and Villegas, Marta},
booktitle={Workshop on Creating, Enriching and Using Parliamentary Corpora},
volume={125},
number={130},
pages={125},
year={2022}
}
Contributions
Thanks to @albertvillanova for adding this dataset.
- Downloads last month
- 153