arbml/ANETAC

# Dataset Card for ANETAC

## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [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)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)

## Dataset Description

- **Homepage: [info]**
- **Repository: [info]**
- **Paper: [info]**
- **Leaderboard: [info]**
- **Point of Contact: [info]**

### Dataset Summary

[More Information Needed]

### Supported Tasks and Leaderboards

[More Information Needed]

### Languages

[More Information Needed]

## Dataset Structure

### Data Instances

[More Information Needed]

### Data Fields

[More Information Needed]

### Data Splits

[More Information Needed]

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### 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

### Social Impact of Dataset

[More Information Needed]

### Discussion of 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{HADJAMEUR2017287,
title = "Arabic Machine Transliteration using an Attention-based Encoder-decoder Model",
journal = "Procedia Computer Science",
volume = "117",
pages = "287 - 297",
year = "2017",
note = "Arabic Computational Linguistics",
issn = "1877-0509",
doi = "https://doi.org/10.1016/j.procs.2017.10.120",
url = "http://www.sciencedirect.com/science/article/pii/S1877050917321774",
author = "Mohamed Seghir Hadj Ameur and Farid Meziane and Ahmed Guessoum",
keywords = "Natural Language Processing, Arabic Language, Arabic Transliteration, Deep Learning, Sequence-to-sequence Models, Encoder-decoder Architecture, Recurrent Neural Networks",
abstract = "Transliteration is the process of converting words from a given source language alphabet to a target language alphabet, in a way that best preserves the phonetic and orthographic aspects of the transliterated words. Even though an important effort has been made towards improving this process for many languages such as English, French and Chinese, little research work has been accomplished with regard to the Arabic language. In this work, an attention-based encoder-decoder system is proposed for the task of Machine Transliteration between the Arabic and English languages. Our experiments proved the efficiency of our proposal approach in comparison to some previous research developed in this area."
}
```

### Contributions

Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.

原始信息汇总

数据集概述

数据集描述

• 数据集名称: ANETAC
• 数据集总结: [更多信息待补充]
• 支持的任务和排行榜: [更多信息待补充]
• 语言: [更多信息待补充]

数据集结构

• 数据实例: [更多信息待补充]
• 数据字段: [更多信息待补充]
• 数据分割: [更多信息待补充]

数据集创建

• 精选理由: [更多信息待补充]
• 源数据:
  • 初始数据收集和标准化: [更多信息待补充]
  • 源语言生产者: [更多信息待补充]
• 注释:
  • 注释过程: [更多信息待补充]
  • 注释者: [更多信息待补充]
• 个人和敏感信息: [更多信息待补充]

使用数据的考虑

• 数据集的社会影响: [更多信息待补充]
• 偏见的讨论: [更多信息待补充]
• 其他已知限制: [更多信息待补充]

附加信息

• 数据集管理者: [更多信息待补充]

• 许可信息: [更多信息待补充]

• 引用信息:

  @article{HADJAMEUR2017287, title = "Arabic Machine Transliteration using an Attention-based Encoder-decoder Model", journal = "Procedia Computer Science", volume = "117", pages = "287 - 297", year = "2017", note = "Arabic Computational Linguistics", issn = "1877-0509", doi = "https://doi.org/10.1016/j.procs.2017.10.120", url = "http://www.sciencedirect.com/science/article/pii/S1877050917321774", author = "Mohamed Seghir Hadj Ameur and Farid Meziane and Ahmed Guessoum", keywords = "Natural Language Processing, Arabic Language, Arabic Transliteration, Deep Learning, Sequence-to-sequence Models, Encoder-decoder Architecture, Recurrent Neural Networks", abstract = "Transliteration is the process of converting words from a given source language alphabet to a target language alphabet, in a way that best preserves the phonetic and orthographic aspects of the transliterated words. Even though an important effort has been made towards improving this process for many languages such as English, French and Chinese, little research work has been accomplished with regard to the Arabic language. In this work, an attention-based encoder-decoder system is proposed for the task of Machine Transliteration between the Arabic and English languages. Our experiments proved the efficiency of our proposal approach in comparison to some previous research developed in this area." }

• 贡献: 感谢 @github-username 添加此数据集。