Datasets:
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README.md
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### Dataset Summary
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The CA-EN Parallel Corpus is a Catalan-English dataset of **14.967.979** parallel sentences.
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Machine Translation.
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### Supported Tasks and Leaderboards
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* ca_prob: Language probability for the Catalan sentence calculated with the language detector [lingua.py](https://github.com/pemistahl/lingua-py)
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* en_prob: Language probability for the English sentence calculated with the language detector [lingua.py](https://github.com/pemistahl/lingua-py)
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* alignment: Sentence pair alignment score calculated with [LaBSE](https://huggingface.co/sentence-transformers/LaBSE)
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* Domain: Domain (see
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* Type: Text type (see list of text types)
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#### Example:
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### Data Splits
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The dataset contains a single split: `train`.
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## Dataset Creation
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#### Initial Data Collection and Normalization
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The data is a
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domains and styles.
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The source data is Catalan authentic text translated
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The data was obtained through a combination of human translation and machine translation with human proofreading.
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The obtained corpus consists of **14.967.979** parallel sentences
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#### Who are the source language producers?
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### Social Impact of Dataset
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By providing this resource, we intend to promote the use of Catalan across NLP tasks,
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### Discussion of Biases
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### Dataset Summary
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The CA-EN Parallel Corpus is a Catalan-English dataset of **14.967.979** parallel sentences.
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The dataset was created to support Catalan in NLP tasks, specifically Machine Translation.
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### Supported Tasks and Leaderboards
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* ca_prob: Language probability for the Catalan sentence calculated with the language detector [lingua.py](https://github.com/pemistahl/lingua-py)
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* en_prob: Language probability for the English sentence calculated with the language detector [lingua.py](https://github.com/pemistahl/lingua-py)
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* alignment: Sentence pair alignment score calculated with [LaBSE](https://huggingface.co/sentence-transformers/LaBSE)
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* Domain: Domain (see list of domains)
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* Type: Text type (see list of text types)
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#### Example:
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### Data Splits
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The dataset contains a single split: `train`.
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Individual domain or style specific subsets can be extracted from the original dataset
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by filtering by the previously mentioned domains and text types.
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## Dataset Creation
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#### Initial Data Collection and Normalization
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The data is a collection of parallel sentences in Catalan and English, partially derived from web crawlings
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and belonging to a mix of different domains and styles.
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The source data is partially Catalan authentic text translated into English and partially authentic English text translated into Catalan.
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The data was obtained through a combination of human translation and machine translation with human proofreading.
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The obtained corpus consists of **14.967.979** parallel sentences.
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#### Who are the source language producers?
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### Social Impact of Dataset
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By providing this resource, we intend to promote the use of Catalan across NLP tasks,
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thereby improving the accessibility and visibility of the Catalan language.
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### Discussion of Biases
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