---
language:
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license: cc-by-4.0
task_categories:
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  By accessing and using this dataset, you agree to comply with all applicable laws
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  This document is a legal contract between you and the dataset provider. By accessing
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<div align="justify">

**Corpus description**

*Nos_ParlaSpeech-GL* is an ASR corpus of more than 1,600 hours of automatically aligned speech and text, created from audio and official transcripts of Galician parliamentary sessions celebrated between 2015 and 2022. The content belongs to the Galician Parliament and the data is released according to their [terms of use](https://sede.parlamentodegalicia.gal/aviso-legal).

The corpus is split into two subcorpora, “clean” and “other”. The segments included in the “clean” subcorpus were filtered according to several alignment quality criteria, whereas the “other” subcorpus comprises the segments that were discarded in the filtering process. The details of both subcorpora can be found in the table below:

| **Subcorpus** | **No. of hours** | **No. of segments** | 
|---------------|------------------|---------------------|
| _clean_       | 1196.92          | 667,308             | 
| _other_       | 477.71           | 130,332             | 
| _Total_       | 1674.63          | 797,64              | 


For each subcorpora, we provide three splits: _train_, _dev_ and _test_. _Test_ and _dev_ splits contain between 10 and 15 hours of audio, balanced by gender; whereas the _train_ partition contains the rest of the audio segments. It must be noted that all the partitions have unique speakers, i.e., speakers from a partition do not appear in other partitions.
The repository structure is as follows: the _/data_ folder contains all the audio files, divided into _clean_ and _other_, and also split into _train_, _dev_ and _test_ for each subcorpora. The _/transcript_ folder follows the same structure, but it contains the metadata files. Each metadata file has the following fields:

- "path": the name of the audio file.
- "sentence": the transcript of the audio file.
- "speaker_id": the ID of the speaker.
- "gender": the gender of the speaker (M/F).
- "birth_year": the birth year of the speaker.
- "birth_place": the birth place of the speaker.


**Disclaimer**

We are not responsible for any inconsistencies in speaker identification that stem from misidentification in the original transcripts.

**Funding and acknowledgements**

This corpus was compiled in collaboration with [VICOMTECH](https://www.vicomtech.org/en/).

“The Nós project: Galician in the society and economy of Artificial Intelligence” is possible thanks to the funding resulting from the agreement 2021-CP080 between the Xunta de Galicia and the University of Santiago de Compostela, and thanks to the Investigo program, within the National Recovery, Transformation and Resilience Plan, within the framework of the European Recovery Fund (NextGenerationEU).

We would like to thank the Galician Parliament for their kind collaboration in providing the original data.

For more information, please go to [nos.gal](https://nos.gal/) or contact the Nós project at [proxecto.nos@usc.gal](mailto:proxecto.nos@usc.gal).

**Terms and Conditions**

By accessing and using this dataset, you agree to comply with all applicable laws and ethical standards regarding the protection of individual rights. The dataset contains voice files, transcripts, and metadata, including participant identity information, provided solely for research and development purposes. Users are strictly prohibited from using the dataset in any way that infringes upon the rights, privacy, or dignity of any individual represented within it. Any misuse, including but not limited to attempts to engage in discriminatory, harmful, or unlawful activities, is expressly forbidden.

**Citation information**

The original version of this dataset, in STM and JSON formats and non-segmented audio, can be found in [Zenodo](https://zenodo.org/records/7913218).

If you use this version of the dataset, please cite as follows:

Carmen Magariños, Adrián Vidal Miguéns, Javier González Corbelle, Adina Ioana Vladu, Noelia García Díaz, Marta Vázquez Abuín, Ainhoa Vivel Couso, Daniel Bardanca, & Elisa Fernández Rei. (2024). Nos_Parlaspeech-GL

URL: https://huggingface.co/datasets/proxectonos/Nos_Parlaspeech-GL