annotations_creators: []
language_creators:
- crowdsourced
- expert-generated
- machine-generated
- found
- other
language:
- asm
- ben
- brx
- doi
- guj
- hin
- kan
- kas
- kok
- mai
- mal
- mar
- mni
- nep
- ori
- pan
- san
- sid
- tam
- tel
- urd
license: cc
multilinguality:
- multilingual
pretty_name: Aksharantar
source_datasets:
- original
task_categories:
- text-generation
task_ids: []
Dataset Card for Aksharantar
Table of Contents
- Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://indicnlp.ai4bharat.org/indic-xlit/
- Repository: https://github.com/AI4Bharat/IndicXlit/
- Paper: Aksharantar: Towards building open transliteration tools for the next billion users
- Leaderboard:
- Point of Contact:
Dataset Summary
Aksharantar is the largest publicly available transliteration dataset for 20 Indic languages. The corpus has 26M Indic language-English transliteration pairs.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
Assamese (asm) | Hindi (hin) | Maithili (mai) | Marathi (mar) | Punjabi (pan) | Tamil (tam) |
Bengali (ben) | Kannada (kan) | Malayalam (mal) | Nepali (nep) | Sanskrit (san) | Telugu (tel) |
Bodo(brx) | Kashmiri (kas) | Manipuri (mni) | Oriya (ori) | Sindhi (snd) | Urdu (urd) |
Gujarati (guj) | Konkani (kok) | Dogri (doi) |
Dataset Structure
Data Instances
A random sample from Hindi (hin) Train dataset.
{
'unique_identifier': 'hin1241393',
'native word': 'स्वाभिमानिक',
'english word': 'swabhimanik',
'source': 'IndicCorp',
'score': -0.1028788579
}
Data Fields
unique_identifier
(string): 3-letter language code followed by a unique number in each set (Train, Test, Val).native word
(string): A word in Indic language.english word
(string): Transliteration of native word in English (Romanised word).source
(string): Source of the data.score
(num): Character level log probability of indic word given roman word by IndicXlit (model). Pairs with average threshold of the 0.35 are considered.For created data sources, depending on the destination/sampling method of a pair in a language, it will be one of:
- Dakshina Dataset
- IndicCorp
- Samanantar
- Wikidata
- Existing sources
- Named Entities Indian (AK-NEI)
- Named Entities Foreign (AK-NEF)
- Data from Uniform Sampling method. (Ak-Uni)
- Data from Most Frequent words sampling method. (Ak-Freq)
Data Splits
Subset | asm-en | ben-en | brx-en | guj-en | hin-en | kan-en | kas-en | kok-en | mai-en | mal-en | mni-en | mar-en | nep-en | ori-en | pan-en | san-en | sid-en | tam-en | tel-en | urd-en |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Training | 179K | 1231K | 36K | 1143K | 1299K | 2907K | 47K | 613K | 283K | 4101K | 10K | 1453K | 2397K | 346K | 515K | 1813K | 60K | 3231K | 2430K | 699K |
Validation | 4K | 11K | 3K | 12K | 6K | 7K | 4K | 4K | 4K | 8K | 3K | 8K | 3K | 3K | 9K | 3K | 8K | 9K | 8K | 12K |
Test | 5531 | 5009 | 4136 | 7768 | 5693 | 6396 | 7707 | 5093 | 5512 | 6911 | 4925 | 6573 | 4133 | 4256 | 4316 | 5334 | - | 4682 | 4567 | 4463 |
Dataset Creation
Information in the paper. Aksharantar: Towards building open transliteration tools for the next billion users
Curation Rationale
[More Information Needed]
Source Data
Initial Data Collection and Normalization
Information in the paper. Aksharantar: Towards building open transliteration tools for the next billion users
Who are the source language producers?
[More Information Needed]
Annotations
Information in the paper. Aksharantar: Towards building open transliteration tools for the next billion users
Annotation process
Information in the paper. Aksharantar: Towards building open transliteration tools for the next billion users
Who are the annotators?
Information in the paper. Aksharantar: Towards building open transliteration tools for the next billion users
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
This data is released under the following licensing scheme:
- Manually collected data: Released under CC-BY license.
- Mined dataset (from Samanantar and IndicCorp): Released under CC0 license.
- Existing sources: Released under CC0 license.
CC-BY License
![CC-BY](https://mirrors.creativecommons.org/presskit/buttons/88x31/png/by.png)
CC0 License Statement
![CC0](https://licensebuttons.net/p/zero/1.0/88x31.png)
- We do not own any of the text from which this data has been extracted.
- We license the actual packaging of the mined data under the Creative Commons CC0 license (“no rights reserved”).
- To the extent possible under law, AI4Bharat has waived all copyright and related or neighboring rights to Aksharantar manually collected data and existing sources.
- This work is published from: India.
Citation Information
@misc{madhani2022aksharantar,
title={Aksharantar: Towards Building Open Transliteration Tools for the Next Billion Users},
author={Yash Madhani and Sushane Parthan and Priyanka Bedekar and Ruchi Khapra and Anoop Kunchukuttan and Pratyush Kumar and Mitesh Shantadevi Khapra},
year={2022},
eprint={},
archivePrefix={arXiv},
primaryClass={cs.CL}
}