README.md

---
language:
- ca
- en
multilinguality:
- multilingual
pretty_name: CA-EN Parallel Corpus
size_categories:
- 10M<n<100M
task_categories:
- translation
task_ids: []
license: cc-by-4.0
---

# Dataset Card for CA-EN Parallel Corpus

## Dataset Description

### Dataset Summary

The CA-EN Parallel Corpus is a Catalan-English dataset of **14.967.979** parallel sentences. The dataset was created to support Catalan in NLP tasks, specifically 
Machine Translation.

### Supported Tasks and Leaderboards

The dataset can be used to train Bilingual Machine Translation models between English and Catalan in any direction, 
as well as Multilingual Machine Translation models.

### Languages

The sentences included in the dataset are in Catalan (CA) and English (EN).

## Dataset Structure

### Data Instances

The dataset is a single tsv file where each row contains a parallel sentence pair, as well as the following information per sentence: 

* language probability score calculated with the language detector [lingua.py](https://github.com/pemistahl/lingua-py), 
* alignment score calculated with [LaBSE](https://huggingface.co/sentence-transformers/LaBSE), 
* domain,
* text type.


### Data Fields

Each example contains the following 7 fields: 

* ca: Catalan sentence
* en: English sentence
* ca_prob: Language probability for the Catalan sentence calculated with the language detector [lingua.py](https://github.com/pemistahl/lingua-py)
* en_prob: Language probability for the English sentence calculated with the language detector [lingua.py](https://github.com/pemistahl/lingua-py)
* alignment: Sentence pair alignment score calculated with [LaBSE](https://huggingface.co/sentence-transformers/LaBSE)
* Domain: Domain (see List of domains)
* Type: Text type (see list of text types)

#### Example:

<pre>
[
  {
    Pel que fa als motors de cerca, també es basen en l'estructura del seu contingut d'informació al lloc web per analitzar i indexar el seu lloc web.	As for the search engines, they also rely on the structure of your information content on the website to analyze and index your website.	0.9999799355804416	0.9993718600460302	0.91045034	MWM	SM

  },
  ...
]

</pre>

List of domains (and number of sentences per domain)

AUT: Automotive, transport, traffic regulations (2.289.951)

LEG: legal, law, HR, certificates, degrees (498.676)

MWM: Marketing, web, merchandising, customer support and service, e-commerce , advertising, surveys (1.066.111)

LSM: Medicine, natural sciences, food/nutrition, biology, sexology, cosmetics, chemistry, genetics (457.647)

ENV: Environment, agriculture, forestry, fisheries, farming, zoology, ecology

FIN: Finance, economics, business, entrepreneurship, business, competitions, labour, employment, accounting, insurance, insurance

POL: Politics, international relations, European Union, international organisations, defence, military

PRN: Porn, inappropriate content

COM: Computers, IT, robotics, domotics, home automation, telecommunications

ING: Pure engineering (mechanical, electrical, electronic, aerospace...), meteorology, mining, engineering, maritime, acoustics

ARC: Architecture, civil engineering, construction, public engineering

MAT: Mathematics, statistics, physics

HRM: History, religion, mythology, folklore, philosophy, psychology, ethics, anthropology, tourism

CUL: Art, poetry, literature, cinema, video games, theatre, theatre/film scripts, esotericism, astrology, sports, music, photography 

GEN: General - generic cathegory with topics such as clothing, textiles, gastronomy,  etc.


List of text types

PAT: Patents

SM: Social Media (social networks, chats, forums, tweets...)

CON: Vernacular (transcription of conversations, subtitles)

EML: Emails

MNL: Manuals, data sheets 

NEW: News, journalism

GEN: Prose, generic type of text


### 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 Catalan and other languages, specifically English.

### Source Data

#### Initial Data Collection and Normalization

The data is a brand new collection of parallel sentences in Catalan and English, partially derived from web crawlings and belonging to a mix of different 
domains and styles.
The source data is Catalan authentic text translated to English or authentic English text translated to Catalan.

The data was obtained through a combination of human translation and machine translation with human proofreading.

The obtained corpus consists of **14.967.979** parallel sentences of human quality.

#### Who are the source language producers?

The original data gathering was entrusted to an external company through a public tender process.

### Annotations

#### Annotation process

The dataset does not contain any annotations.

#### Who are the annotators?

[N/A]

### Personal and Sensitive Information

No anonymisation process was performed.

## Considerations for Using the Data

### Social Impact of Dataset

By providing this resource, we intend to promote the use of Catalan across NLP tasks, thereby improving the accessibility and visibility of the Catalan 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 several specific domains. The dataset can be used as a whole or extracting subsets per domain or text types. 
Applications of this dataset in domains other than the ones included in the domain list would be of limited use.

## Additional Information

### Dataset Curators

Language Technologies Unit at the Barcelona Supercomputing Center (langtech@bsc.es).

This work has been promoted and financed by the Generalitat de Catalunya through the [Aina project](https://projecteaina.cat/).


### Licensing Information

This work is licensed under a Creative Commons Attribution 4.0 International license(https://creativecommons.org/licenses/by/4.0/).

### Citation Information

[N/A]

### Contributions

[N/A]