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---
language:
- ca
- de
- multilingual
multilinguality:
- translation
pretty_name: CA-DE Parallel Corpus
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- translation
task_ids: []
---

# Dataset Card for CA-DE Parallel 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)
  - [Data preparation](#data-preparation)
  - [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

The CA-PT Parallel Corpus is a Catalan-German dataset of **9.892.953** parallel sentences. The dataset was created to support Catalan NLP tasks, e.g., 
Machine Translation.

### Supported Tasks and Leaderboards

The dataset can be used to train a model for Multilingual Machine Translation. Success on this task is typically measured by achieving a high BLEU score.

### Languages

The texts in the dataset are in Catalan and German.

## Dataset Structure

Two separated txt files are provided with the sentences sorted in the same order:

- ca-de_all_2023_09_11.ca: contains XXX Catalan sentences.

- ca-de_all_2023_09_11.de: contains XXX German sentences.

### Data Splits

The dataset contains a single split: `train`.

## Dataset Creation

### Source Data

The dataset is a combination of the following authentic datasets:

| Dataset       | Sentences |
|---------------|-----------|

All corpora except Europarl were collected from [Opus](https://opus.nlpl.eu/).
The Europarl corpus is a synthetic parallel corpus created from the original Spanish-Catalan corpus by [SoftCatalà](https://github.com/Softcatala/Europarl-catalan).

The remaining **3.733.322** sentences are synthetic parallel data created from a random sampling of the Spanish-German corpora available on [Opus](https://opus.nlpl.eu/) and translated into Catalan using the [PlanTL es-ca](https://huggingface.co/PlanTL-GOB-ES/mt-plantl-es-ca) model.

### Data preparation

 All datasets are deduplicated and filtered to remove any sentence pairs with a cosine similarity of less than 0.75.
 This is done using sentence embeddings calculated using [LaBSE](https://huggingface.co/sentence-transformers/LaBSE).
 The filtered datasets are then concatenated to form a final corpus of **XXX** parallel sentences and before training the punctuation is normalized using a modified version of the join-single-file.py script from [SoftCatalà](https://github.com/Softcatala/nmt-models/blob/master/data-processing-tools/join-single-file.py).

### Personal and Sensitive Information

No anonymisation process was performed.

## Considerations for Using the Data

### Social Impact of Dataset

The purpose of this dataset is to help develop Machines Translation tasks for low-resource languages such as Catalan.

### Discussion of Biases

We are aware that since part of the data comes from unreliable web pages and non-curated texts, some biases may be present in the dataset.
Nonetheless, we have not applied any steps to reduce their impact.

### Other Known Limitations

The dataset contains data of a general domain. Application of this dataset in more specific domains such as biomedical, legal etc. would be of limited use.

## Additional Information

### Author
Language Technologies Unit (LangTech) at the Barcelona Supercomputing Center.

### 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 work is licensed under a [Attribution-NonCommercial-ShareAlike 4.0 International](https://creativecommons.org/licenses/by-nc-sa/4.0/).

### Funding
This work was funded by the [Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya](https://politiquesdigitals.gencat.cat/ca/inici/index.html#googtrans(ca|en) within the framework of [Projecte AINA](https://politiquesdigitals.gencat.cat/ca/economia/catalonia-ai/aina).