
# 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.
task_categories:fill-mask task_categories:text-generation task_categories:translation task_ids:language-modeling task_ids:masked-language-modeling annotations_creators:expert-generated annotations_creators:found annotations_creators:no-annotation language_creators:found multilinguality:monolingual multilinguality:multilingual multilinguality:translation size_categories:100K<n<1M size_categories:10K<n<100K size_categories:1K<n<10K source_datasets:original language:chr language:en license:other arxiv:2010.04791 region:us
{"annotations_creators": ["expert-generated", "found", "no-annotation"], "language_creators": ["found"], "language": ["chr", "en"], "license": ["other"], "multilinguality": ["monolingual", "multilingual", "translation"], "size_categories": ["100K<n<1M", "10K<n<100K", "1K<n<10K"], "source_datasets": ["original"], "task_categories": ["fill-mask", "text-generation", "translation"], "task_ids": ["language-modeling", "masked-language-modeling"], "paperswithcode_id": "chren", "config_names": ["monolingual", "monolingual_raw", "parallel", "parallel_raw"], "dataset_info": [{"config_name": "monolingual", "features": [{"name": "sentence", "dtype": "string"}], "splits": [{"name": "chr", "num_bytes": 882824, "num_examples": 5210}, {"name": "en5000", "num_bytes": 615275, "num_examples": 5000}, {"name": "en10000", "num_bytes": 1211605, "num_examples": 10000}, {"name": "en20000", "num_bytes": 2432298, "num_examples": 20000}, {"name": "en50000", "num_bytes": 6065580, "num_examples": 49999}, {"name": "en100000", "num_bytes": 12130164, "num_examples": 100000}], "download_size": 16967664, "dataset_size": 23337746}, {"config_name": "monolingual_raw", "features": [{"name": "text_sentence", "dtype": "string"}, {"name": "text_title", "dtype": "string"}, {"name": "speaker", "dtype": "string"}, {"name": "date", "dtype": "int32"}, {"name": "type", "dtype": "string"}, {"name": "dialect", "dtype": "string"}], "splits": [{"name": "full", "num_bytes": 1210056, "num_examples": 5210}], "download_size": 410646, "dataset_size": 1210056}, {"config_name": "parallel", "features": [{"name": "sentence_pair", "dtype": {"translation": {"languages": ["en", "chr"]}}}], "splits": [{"name": "train", "num_bytes": 3089562, "num_examples": 11639}, {"name": "dev", "num_bytes": 260401, "num_examples": 1000}, {"name": "out_dev", "num_bytes": 78126, "num_examples": 256}, {"name": "test", "num_bytes": 264595, "num_examples": 1000}, {"name": "out_test", "num_bytes": 80959, "num_examples": 256}], "download_size": 2143266, "dataset_size": 3773643}, {"config_name": "parallel_raw", "features": [{"name": "line_number", "dtype": "string"}, {"name": "sentence_pair", "dtype": {"translation": {"languages": ["en", "chr"]}}}, {"name": "text_title", "dtype": "string"}, {"name": "speaker", "dtype": "string"}, {"name": "date", "dtype": "int32"}, {"name": "type", "dtype": "string"}, {"name": "dialect", "dtype": "string"}], "splits": [{"name": "full", "num_bytes": 5010734, "num_examples": 14151}], "download_size": 2018726, "dataset_size": 5010734}], "configs": [{"config_name": "monolingual", "data_files": [{"split": "chr", "path": "monolingual/chr-*"}, {"split": "en5000", "path": "monolingual/en5000-*"}, {"split": "en10000", "path": "monolingual/en10000-*"}, {"split": "en20000", "path": "monolingual/en20000-*"}, {"split": "en50000", "path": "monolingual/en50000-*"}, {"split": "en100000", "path": "monolingual/en100000-*"}]}, {"config_name": "monolingual_raw", "data_files": [{"split": "full", "path": "monolingual_raw/full-*"}]}, {"config_name": "parallel", "data_files": [{"split": "train", "path": "parallel/train-*"}, {"split": "dev", "path": "parallel/dev-*"}, {"split": "out_dev", "path": "parallel/out_dev-*"}, {"split": "test", "path": "parallel/test-*"}, {"split": "out_test", "path": "parallel/out_test-*"}], "default": true}, {"config_name": "parallel_raw", "data_files": [{"split": "full", "path": "parallel_raw/full-*"}]}]}
TAGS
#task_categories-fill-mask #task_categories-text-generation #task_categories-translation #task_ids-language-modeling #task_ids-masked-language-modeling #annotations_creators-expert-generated #annotations_creators-found #annotations_creators-no-annotation #language_creators-found #multilinguality-monolingual #multilinguality-multilingual #multilinguality-translation #size_categories-100K<n<1M #size_categories-10K<n<100K #size_categories-1K<n<10K #source_datasets-original #language-Cherokee #language-English #license-other #arxiv-2010.04791 #region-us 


# Dataset Card for ChrEn

## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - 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
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions

## Dataset Description

- Repository: Github repository for ChrEn
- Paper: ChrEn: Cherokee-English Machine Translation for Endangered Language Revitalization
- Point of Contact: benfrey@URL

### 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



### Data Fields



### Data Splits



## Dataset Creation

### Curation Rationale



### 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?



### Annotations

#### Annotation process



#### 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



## Considerations for Using the Data

### Social Impact of Dataset



### Discussion of Biases



### Other Known Limitations



## 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).





### Contributions

Thanks to @yjernite, @lhoestq for adding this dataset.
# Dataset Card for ChrEn ## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - 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
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions ## Dataset Description

- Repository: Github repository for ChrEn
- Paper: ChrEn: Cherokee-English Machine Translation for Endangered Language Revitalization
- Point of Contact: benfrey@URL ### 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 ### Data Fields ### Data Splits ## Dataset Creation ### Curation Rationale ### 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? ### Annotations #### Annotation process #### 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 ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations ## 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). ### Contributions

Thanks to @yjernite, @lhoestq for adding this dataset.
TAGS
#task_categories-fill-mask #task_categories-text-generation #task_categories-translation #task_ids-language-modeling #task_ids-masked-language-modeling #annotations_creators-expert-generated #annotations_creators-found #annotations_creators-no-annotation #language_creators-found #multilinguality-monolingual #multilinguality-multilingual #multilinguality-translation #size_categories-100K<n<1M #size_categories-10K<n<100K #size_categories-1K<n<10K #source_datasets-original #language-Cherokee #language-English #license-other #arxiv-2010.04791 #region-us 
 # Dataset Card for ChrEn ## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - 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
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions ## Dataset Description

- Repository: Github repository for ChrEn
- Paper: ChrEn: Cherokee-English Machine Translation for Endangered Language Revitalization
- Point of Contact: benfrey@URL ### 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 ### Data Fields ### Data Splits ## Dataset Creation ### Curation Rationale ### 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? ### Annotations #### Annotation process #### 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 ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations ## 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). ### Contributions

Thanks to @yjernite, @lhoestq for adding this dataset.
passage: TAGS
#task_categories-fill-mask #task_categories-text-generation #task_categories-translation #task_ids-language-modeling #task_ids-masked-language-modeling #annotations_creators-expert-generated #annotations_creators-found #annotations_creators-no-annotation #language_creators-found #multilinguality-monolingual #multilinguality-multilingual #multilinguality-translation #size_categories-100K<n<1M #size_categories-10K<n<100K #size_categories-1K<n<10K #source_datasets-original #language-Cherokee #language-English #license-other #arxiv-2010.04791 #region-us 
# Dataset Card for ChrEn## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - 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
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions## Dataset Description

- Repository: Github repository for ChrEn
- Paper: ChrEn: Cherokee-English Machine Translation for Endangered Language Revitalization
- Point of Contact: benfrey@URL### 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').