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---
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---
# Dataset Card for ChrEn
## 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
- **Repository:** [Github repository for ChrEn](https://github.com/ZhangShiyue/ChrEn)
- **Paper:** [ChrEn: Cherokee-English Machine Translation for Endangered Language Revitalization](https://arxiv.org/abs/2010.04791)
- **Point of Contact:** [benfrey@email.unc.edu](benfrey@email.unc.edu)
### Dataset Summary
ChrEn is a Cherokee-English parallel dataset to facilitate machine translation research between Cherokee and English.
ChrEn is extremely low-resource contains 14k sentence pairs in total, split in ways that facilitate both in-domain and out-of-domain evaluation.
ChrEn also contains 5k Cherokee monolingual data to enable semi-supervised learning.
### Supported Tasks and Leaderboards
The dataset is intended to use for `machine-translation` between Enlish (`en`) and Cherokee (`chr`).
### Languages
The dataset contains Enlish (`en`) and Cherokee (`chr`) text. The data encompasses both existing dialects of Cherokee: the Overhill dialect, mostly spoken in Oklahoma (OK), and the Middle dialect, mostly used in North Carolina (NC).
## 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
Many of the source texts were translations of English materials, which means that the Cherokee structures may not be 100% natural in terms of what a speaker might spontaneously produce. Each text was translated by people who speak Cherokee as the first language, which means there is a high probability of grammaticality. These data were originally available in PDF version. We apply the Optical Character Recognition (OCR) via Tesseract OCR engine to extract the Cherokee and English text.
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
The sentences were manually aligned by Dr. Benjamin Frey a proficient second-language speaker of Cherokee, who also fixed the errors introduced by OCR. This process is time-consuming and took several months.
### 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
The dataset was gathered and annotated by Shiyue Zhang, Benjamin Frey, and Mohit Bansal at UNC Chapel Hill.
### Licensing Information
The copyright of the data belongs to original book/article authors or translators (hence, used for research purpose; and please contact Dr. Benjamin Frey for other copyright questions).
### Citation Information
```
@inproceedings{zhang2020chren,
title={ChrEn: Cherokee-English Machine Translation for Endangered Language Revitalization},
author={Zhang, Shiyue and Frey, Benjamin and Bansal, Mohit},
booktitle={EMNLP2020},
year={2020}
}
```
### Contributions
Thanks to [@yjernite](https://github.com/yjernite), [@lhoestq](https://github.com/lhoestq) for adding this dataset. |