weezygeezer/Spanish-Asturian_Parallel-Corpus

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The Spanish-Asturian Parallel Corpus is a dataset created to support the development of Machine Translation (MT) systems for translating from Spanish (es) into Asturian (ast).

Dataset Details

The dataset was created to support low-resource machine translation.

Recently the Workshop for Machine Translation (WMT) has released the first edition of the Shared Task on Translation into Low-Resource Languages of Spain 2024. This dataset further supports the endeavor by improving accessibility to quality resources.

Dataset Description

• Curated by: [More Information Needed]
• Funded by [optional]: [More Information Needed]
• Shared by [optional]: [More Information Needed]
• Language(s) (NLP): Spanish, Asturian
• License: The Spanish-Asturian_Parallel-Corpus is released under no license. The use of its contents should respect license restrictions on part of the original data.

Dataset Sources [optional]

• OPUS: OPUS corpora
• PILAR: GitHub repository

Uses

Direct Use

The dataset is intended to train a Machine Translation system between Asturian and Spanish (ast -> es).

Out-of-Scope Use

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Dataset Structure

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Dataset Creation

Curation Rationale

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Source Data

Data Collection and Processing

This dataset separates both synthetic and existing data. The existing parallel data come from OPUS (Spanish-Asturian) under their respective entities. The synthetic data consist of Spanish translations generated from the Asturian monolingual corpus of the PILAR dataset. To create the synthetic Spanish translations we used the OPUS-MT model.

The data filtering process incorporated language identification using the Idiomata Cognitor tool. No other preprocessing steps (e.g. alignment) were used, therefore any peculiarities exist solely from the data itself. However, this is not the case for the synthetic data—peculiarities certainly exist. Notably the synthetic data was filtered twice by the language identifier.

	Tatoeba	OpenSubtitles	KDE4	wikimedia	GNOME
ast	159	17,486	26,023	45,506	68,668
langid	94	8,091	12,025	39,958	37,551

Table 1: Parallel Data.

	PILAR - literary	PILAR - crawled
ast	14,776	24,094
langid (ast)	10,538	17,121
langid (es)	9,329	15,409

Table 2: Monolingual Data.

Who are the source data producers?

The text was extracted from Opus under the following resources: OpenSubtitles, Tatoeba, KDE4, wikimedia, GNOME. Additionally, the data from PILAR was used to create synthetic corpora.

Annotations [optional]

Annotation process

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Who are the annotators?

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Personal and Sensitive Information

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Bias, Risks, and Limitations

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Recommendations

Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

Citation [optional]

@InProceedings{TIEDEMANN12.463,
  author = {Jörg Tiedemann},
  title = {Parallel Data, Tools and Interfaces in OPUS},
  booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
  year = {2012},
  month = {may},
  date = {23-25},
  address = {Istanbul, Turkey},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Ugur Dogan and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {978-2-9517408-7-7},
  language = {english}
 }

@inproceedings{lison-tiedemann-2016-opensubtitles2016,
    title = "{O}pen{S}ubtitles2016: Extracting Large Parallel Corpora from Movie and {TV} Subtitles",
    author = {Lison, Pierre  and
      Tiedemann, J{\"o}rg},
    editor = "Calzolari, Nicoletta  and
      Choukri, Khalid  and
      Declerck, Thierry  and
      Goggi, Sara  and
      Grobelnik, Marko  and
      Maegaard, Bente  and
      Mariani, Joseph  and
      Mazo, Helene  and
      Moreno, Asuncion  and
      Odijk, Jan  and
      Piperidis, Stelios",
    booktitle = "Proceedings of the Tenth International Conference on Language Resources and Evaluation ({LREC}`16)",
    month = may,
    year = "2016",
    address = "Portoro{\v{z}}, Slovenia",
    publisher = "European Language Resources Association (ELRA)",
    url = "https://aclanthology.org/L16-1147/",
    pages = "923--929",
    abstract = "We present a new major release of the OpenSubtitles collection of parallel corpora. The release is compiled from a large database of movie and TV subtitles and includes a total of 1689 bitexts spanning 2.6 billion sentences across 60 languages. The release also incorporates a number of enhancements in the preprocessing and alignment of the subtitles, such as the automatic correction of OCR errors and the use of meta-data to estimate the quality of each subtitle and score subtitle pairs."
}

@misc{PILAR,
  editor = {Galiano-Jiménez, Aarón and Sánchez-Martínez, Felipe and Pérez-Ortiz, Juan Antonio},
  title = {PILAR},
  url = {https://github.com/transducens/PILAR},
  year = {2024}
}

@misc{idiomatacognitor,
  author = {Galiano-Jiménez, Aarón and Sánchez-Martínez, Felipe and Pérez-Ortiz, Juan Antonio},
  title = {Idiomata Cognitor},
  url = {https://github.com/transducens/idiomata_cognitor},
  year = {2024}
}

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