| --- |
| YAML tags: null |
| language: |
| - es |
| - ast |
| pretty_name: ES-AST Parallel Corpus |
| task_categories: |
| - translation |
| size_categories: |
| - size category |
| license: cc-by-sa-4.0 |
| --- |
| |
| # Dataset Card for ES-AST Parallel Corpus |
|
|
| ## Dataset Description |
|
|
| - **Point of Contact:** langtech@bsc.es |
|
|
|
|
| ### Dataset Summary |
|
|
| The ES-AST Parallel Corpus is a Spanish-Asturian dataset created to support the use of under-resourced languages from Spain, |
| such as Asturian, in NLP tasks, specifically Machine Translation. |
|
|
|
|
| ### Supported Tasks and Leaderboards |
|
|
| The dataset can be used to train Bilingual Machine Translation models between Asturian and Spanish in any direction, as well as Multilingual Machine Translation models. |
|
|
| ### Languages |
|
|
| The sentences included in the dataset are in Spanish (ES) and Asturian (AST). |
|
|
| ## Dataset Structure |
|
|
| ### Data Instances |
|
|
| Two separate txt files are provided: |
|
|
| - es-ast_corpus.es |
| - es-ast_corpus.ast |
|
|
| The dataset is additionally provided in parquet format: es-ast_corpus.parquet. |
| |
| The parquet file contains two columns of parallel text obtained from the two original text files. |
| Each row in the file represents a pair of parallel sentences in the two languages of the dataset. |
| |
| |
| ### Data Fields |
| |
| [N/A] |
| |
| ### Data Splits |
| |
| The dataset contains a single split: `train`. |
| |
| ## Dataset Creation |
| |
| ### Curation Rationale |
| |
| This dataset is aimed at promoting the development of Machine Translation between Spanish and under-resourced languages from Spain, specifically Asturian. |
| |
| ### Source Data |
| |
| #### Initial Data Collection and Normalization |
| |
| This dataset was created as part of the participation of Language Technologies Unit at BSC in the WMT24 Shared Task: |
| [Translation into Low-Resource Languages of Spain](https://www2.statmt.org/wmt24/romance-task.html). |
| The corpus is the result of a thorough cleaning and preprocessing, as described in detail in the paper ["Training and Fine-Tuning |
| NMT Models for Low-Resource Languages using Apertium-Based Synthetic Corpora"](https://aclanthology.org/2024.wmt-1.90/). |
| As no filtering based on alignment score was applied, the dataset may contain poorly aligned sentences. |
| |
| This dataset aggregates both synthetic and authentic data. |
| The authentic parallel data come from [OPUS](https://opus.nlpl.eu/) (Spanish-Asturian), while the synthetic data consist of Spanish translations generated from the Asturian monolingual corpus of the [PILAR](https://github.com/transducens/PILAR) dataset. |
| To create the synthetic Spanish we used the rule-based [Apertium](https://www.apertium.org/) translator. |
| |
| #### Who are the source language producers? |
| |
| [Opus](https://opus.nlpl.eu/) |
| |
| [PILAR](https://github.com/transducens/PILAR) |
| |
| [WMT24](https://www2.statmt.org/wmt24/romance-task.html) |
| |
| |
| ### Annotations |
| |
| #### Annotation process |
| |
| The dataset does not contain any annotations. |
| |
| #### Who are the annotators? |
| |
| [N/A] |
| |
| ### Personal and Sensitive Information |
| |
| Given that this dataset is partly derived from pre-existing datasets that may contain crawled data, and that no specific anonymisation process has been applied, |
| personal and sensitive information may be present in the data. This needs to be considered when using the data for training models. |
| |
| ## Considerations for Using the Data |
| |
| ### Social Impact of Dataset |
| |
| By providing this resource, we intend to promote the use of Asturian across NLP tasks, |
| thereby improving the accessibility and visibility of the Asturian language. |
| |
| ### Discussion of Biases |
| |
| No specific bias mitigation strategies were applied to this dataset. |
| Inherent biases may exist within the data. |
| |
| ### Other Known Limitations |
| |
| The dataset contains data of a general domain. Applications of this dataset in more specific domains such as biomedical, legal etc. would be of limited use. |
| |
| ## Additional Information |
| |
| ### Dataset Curators |
| |
| Language Technologies Unit at the Barcelona Supercomputing Center (langtech@bsc.es). |
| |
| This work is funded by the Ministerio para la Transformación Digital y de la Función Pública and Plan de Recuperación, |
| Transformación y Resiliencia - Funded by EU – NextGenerationEU within the framework of the project ILENIA with reference |
| 2022/TL22/00215337. |
| |
| The publication is part of the project PID2021-123988OB-C33, funded by MCIN/AEI/10.13039/501100011033/FEDER, EU. |
| |
| |
| ### Licensing Information |
| |
| This work is licensed under an [Attribution-Share Alike 4.0 International](https://creativecommons.org/licenses/by-sa/4.0/). |
| |
| ### Citation Information |
| |
| [N/A] |
| |
| ### Contributions |
| |
| [N/A] |
