README.md

---
language:
- es
- ca
- gl
- eu
multilinguality:
- translation
annotations_creators:
- found
- expert-generated
- machine-generated
language_creators:
- crowdsourced
pretty_name: escagleu-64K
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- translation
- audio-to-audio
- automatic-speech-recognition
task_ids: []
license: cc-by-4.0
---

# Dataset Card for escagleu-64K corpus

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Splits](#data-instances)
- [Dataset Creation](#dataset-creation)
  - [Source Data](#source-data)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Author](#author)
  - [Contact Information](#contact-information)
  - [Copyright](#copyright)
  - [Licensing information](#licenciung-informatrion)
  - [Funding](#funding)

## Dataset Description

### Dataset Summary

escagleu-64k is a parallel corpus comprising 64091 sentences translated among Spanish, Catalan, Valencian Catalan, Galician, and Basque.

The original sentences are in Spanish and come from the [Spanish Common Voice Corpus](https://github.com/common-voice/common-voice/tree/main/server/data/es).

We prepared this corpus with the aim of creating a parallel speech dataset among these languages using the [Common Voice](https://commonvoice.mozilla.org) platform between the frame of the project [Ilenia](https://proyectoilenia.es/).

*Warning: The translation into Galician and Basque was done through machine translation, and post-editing is required. Additionally, we have identified some errors in the source sentences. A subsequent version of the corpus will include reviewed translations and source sentences.*

### Supported Tasks and Leaderboards

This dataset can be used for training Machine Translation (MT) models, Speech-to-Text translation models, and Speech-to-Speech translation models.

### Languages

This multilingual dataset is in Spanish (es), Catalan (ca), Valencian Catalan (ca-va), Galician (gl) and Basque (eu).

## Dataset Structure
Five separated tsv files are provided with the sentences sorted in the same order:

* escagleu-64k_ca.tsv: contains 64091 sentences translated into Catalan.
* escagleu-64k_ca_va.tsv: contains 64091 sentences adapted into Valencian Catalan.
* escagleu-64k_es.tsv: contains 64091 sentences in Spanish (authentic).
* escagleu-64k_gl.tsv: contains 64091 sentences translated into Galician using MT. 
* escagleu-64k_es.tsv: contains 64091 sentences translated into Basque using MT.
    
In addition, a tsv is provided with the sentences aligned in all the languages:

* escagleu-6k.tsv: the sentences in all the languages of the corpus.


### Data Splits

The dataset contains a single split.

## Dataset Creation

### Curation Rationale

We created this corpus with the goal of establishing a parallel speech dataset among Spanish, Catalan, Galician, and Basque using the Common Voice platform. The resulting dataset will be employed to train Speech-to-Text and Speech-to-Speech translation models.

### Source Data

The original sentences are in Spanish and come from the [Spanish Common Voice Corpus](https://github.com/common-voice/common-voice/tree/main/server/data/es).

#### Initial Data Collection and Normalization

We extracted a set of 223,261 sentences from the [Spanish Common Voice Corpus](https://github.com/common-voice/common-voice/tree/main/server/data/es) v.07.

An automatic selection was performed, removing sentences that:

*  Were repeated.
*  Exceeded 14 words in length.
*  Ended with a preposition.
*  Were in lowercase but Out of Vocabulary (OOV), utilizing the Hunspell dictionary.
*  Contained repeated words.
*  Featured characters not existing in Spanish or sequences of characters impossible in Spanish.

This filtering process resulted in the current selection of sentences. For some of these sentences, we conducted manual or automatic adjustments, such as capitalization, punctuation fixes, etc.

The selected sentences were translated from Spanish into Catalan by a professional translation company. Subsequently, they were adapted into Valencian by an expert team from the Universitat d'Alacant.

The same corpus of sentences was translated into Galician using [NOS-MT-OpenNMT-es-gl](https://huggingface.co/proxectonos/Nos_MT-OpenNMT-es-gl) and into Basque using [itzuli](https://www.euskadi.eus/itzuli/).

A subsequent version of the corpus will include reviewed translations and source sentences.

#### Who are the source language producers?

The [Common Voice](https://commonvoice.mozilla.org) is a corpus designed for speech-related tasks. 
The recorded sentences are sourced from diverse origins. 
For more information, please refer to the [project repository](https://github.com/common-voice).

### Annotations

This corpus doesn't have annotations.

#### Annotation process

N/A

#### Who are the annotators?

N/A

### Personal and Sensitive Information

The original sentences are in Spanish and come from the [Spanish Common Voice Corpus](https://github.com/common-voice/common-voice/tree/main/server/data/es). To our knowledge, there are no private person’s personal identifiers or sensitive information.

## Considerations for Using the Data

### Social Impact of Dataset

We expect that this corpus will contribute to the development of speech technologies in the targeted languages.

### Discussion of Biases

We are aware that some of the sentences in the corpus may convey stereotypes. Nonetheless, we have not applied any steps to reduce their impact.


### Other Known Limitations

The translation into Galician and Basque was done through machine translation, and post-editing is required. Additionally, we have identified some errors in the source sentences. A subsequent version of the corpus will include reviewed translations and source sentences.

## Additional Information

### Authors
[Grupo de Procesamiento del Lenguaje Natural y Sistemas de Información, Centro de Inteligencia Digital (CENID, Universidad de Alicante)](https://cenid.es/),

[Hizkuntza eta Politika Saila (Eusko Jaurlaritza)](https://www.euskadi.eus/itzuli),

[HiTZ Center - Aholab, University of the Basque Country UPV/EHU](https://www.hitz.eus/), 

[Language Technologies Unit (LangTech) at the Barcelona Supercomputing Center (BSC)](https://www.bsc.es/discover-bsc/organisation/research-departments/language-technologies-unit),

[Proxecto Nós (Universidade de Santiago de Compostela)](https://nos.gal/).

### Contact information
For further information, please send an email to [email protected].

### Copyright
Copyright Language Technologies Unit at Barcelona Supercomputing Center (2023).

### Licensing information
This dataset can be used for any purpose, whether academic or commercial, under the terms of the [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). 
Give appropriate credit, provide a link to the license, and indicate if changes were made.


### Funding

This work is funded by the Ministerio para la Transformación Digital y de la Función Pública - Funded by EU – NextGenerationEU within the framework of the [project ILENIA](https://proyectoilenia.es/) with reference 2022/TL22/00215337