README.md

metadata

annotations_creators:
  - no-annotation
language_creators:
  - found
languages:
  - ar
licenses:
  - unknown
multilinguality:
  - monolingual
size_categories:
  - n>1M
source_datasets:
  - original
task_categories:
  - sequence-modeling
task_ids:
  - language-modeling
  - other-diacritics-prediction

Dataset Card for Tashkeela

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Discussion of Social Impact and Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information

Dataset Description

• Homepage: Tashkeela
• Repository: Tashkeela
• Paper: Tashkeela: Novel corpus of Arabic vocalized texts, data for auto-diacritization systems
• Point of Contact: Taha Zerrouki

Dataset Summary

It contains 75 million of fully vocalized words mainly 97 books from classical and modern Arabic language.

Supported Tasks and Leaderboards

The dataset was published on this paper.

Languages

The dataset is based on Arabic.

Dataset Structure

Data Instances

The dataset contains 97 books and 75 million of fully vocalized words.

Data Fields

[More Information Needed]

Data Splits

The dataset is not split.

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

[More Information Needed]

Initial Data Collection and Normalization

The Modern Standard Arabic texts crawled from the Internet.

Who are the source language producers?

Websites.

Annotations

The dataset does not contain any additional annotations.

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Discussion of Social Impact and Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

[More Information Needed]

Citation Information

@article{zerrouki2017tashkeela,
  title={Tashkeela: Novel corpus of Arabic vocalized texts, data for auto-diacritization systems},
  author={Zerrouki, Taha and Balla, Amar},
  journal={Data in brief},
  volume={11},
  pages={147},
  year={2017},
  publisher={Elsevier}
}