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README.md
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### Dataset Summary
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escagleu-64k
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The original sentences are in Spanish and
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### Supported Tasks and Leaderboards
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* escagleu-6k.tsv: the sentences in all the languages of the corpus.
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### Data Splits
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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.
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An automatic
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* Were repeated.
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* Exceeded 14 words in length.
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* Contained repeated words.
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* Featured characters not existing in Spanish or sequences of characters impossible in Spanish.
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This filtering
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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.
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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/).
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#### Who are the source language producers?
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### Personal and Sensitive Information
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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).
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## Considerations for Using the Data
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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.
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### Other Known Limitations
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The
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## Additional Information
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Copyright Language Technologies Unit at Barcelona Supercomputing Center (2023).
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### Licensing information
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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/).
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Give appropriate credit, provide a link to the license, and indicate if changes were made.
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### Funding
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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
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### Dataset Summary
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This is the second version of escagleu-64k, a parallel corpus containing approximately 64k sentences translated across Spanish, Catalan, Valencian Catalan, Galician, and Basque.
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The original sentences are in Spanish and are sourced from the [Spanish Common Voice Corpus](https://github.com/common-voice/common-voice/tree/main/server/data/es).
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This corpus was prepared with the goal of creating a parallel speech dataset for these languages using the [Common Voice](https://commonvoice.mozilla.org) platform as part of the [Ilenia](https://proyectoilenia.es/) project.
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In the first version of the corpus, translations into Galician and Basque were carried out via machine translation, and several errors were identified in the source sentences.
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In this second version, all translations have been reviewed by a professional team, and the source sentences have been corrected. During the manual revision process, 199 sentences were removed. However, to maintain continuity for future reference, we have preserved the original sentence indexing from v1. As a result, some index numbers are now missing.
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Version 2 of the corpus includes 63,892 parallel sentences.
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### Supported Tasks and Leaderboards
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* escagleu-6k.tsv: the sentences in all the languages of the corpus.
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Please note that, in relation to v1, 199 sentences have been removed, so the corresponding numbers are missing from the index.
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### Data Splits
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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.
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An automatic filtering process was first applied to the source sentences, removing those that:
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* Were repeated.
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* Exceeded 14 words in length.
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* Contained repeated words.
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* Featured characters not existing in Spanish or sequences of characters impossible in Spanish.
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This filtering resulted in the selection of 64,091 sentences, which constitute v1 of the corpus.
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For v1, the selected sentences were translated from Spanish into Catalan by a professional translation company and subsequently adapted into Valencian Catalan by an expert team from the Universitat d'Alacant.
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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/).
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In this second version, the following improvements have been performed:
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* Revision of the Galician and Basque translations by specialized companies.
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* Revision of the original Spanish text and its Catalan (general and Valencian) translations by our specialist team.
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* Removal of ambiguous sentences.
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* A general review to ensure consistency across all language versions.
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During this manual revision process, 199 sentences were removed. However, to maintain continuity for future reference, we have preserved the original sentence indexing from v1. As a result, some index numbers are now missing.
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Version 2 of the corpus includes 63,892 parallel sentences.
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#### Who are the source language producers?
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### Personal and Sensitive Information
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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). The sentences have been manually reviewed and no personal information has been detected.
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## Considerations for Using the Data
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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.
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### Other Known Limitations
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The translations made automatically in v1 have been manually reviewed. Likewise, errors detected in the source sentences and their translations have been corrected. Finally, a final review has been carried out to ensure consistency between the languages.
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## Additional Information
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Copyright Language Technologies Unit at Barcelona Supercomputing Center (2023).
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### Licensing information
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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/).
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Give appropriate credit, provide a link to the license, and indicate if changes were made.
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### Funding
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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
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