---
license: cc0-1.0
annotations_creators: []
language_creators:
- crowdsourced
- expert-generated
- machine-generated
- found
- other
language:
- asm
- ben
- brx
- guj
- hin
- kan
- kas
- kok
- mai
- mal
- mar
- mni
- nep
- ori
- pan
- san
- sat
- sid
- snd
- tam
- tel
- urd
multilinguality:
- multilingual
pretty_name: Bhasha-Abhijnaanam
size_categories: []
source_datasets:
- original
task_categories:
- text-generation
task_ids: []
---
# Dataset Card for Aksharantar
## 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:**
- **Repository:** https://github.com/AI4Bharat/IndicLID
- **Paper:** [Bhasha-Abhijnaanam: Native-script and romanized Language Identification for 22 Indic languages](https://arxiv.org/abs/2305.15814)
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
Bhasha-Abhijnaanam is a language identification test set for native-script as well as Romanized text which spans 22 Indic languages.
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
| | | | | | |
| -------------- | -------------- | -------------- | --------------- | -------------- | ------------- |
| Assamese (asm) | Hindi (hin) | Maithili (mai) | Nepali (nep) | Sanskrit (san) | Tamil (tam) |
| Bengali (ben) | Kannada (kan) | Malayalam (mal)| Oriya (ori) | Santali (sat) | Telugu (tel) |
| Bodo(brx) | Kashmiri (kas) | Manipuri (mni) | Punjabi (pan) | Sindhi (snd) | Urdu (urd) |
| Gujarati (guj) | Konkani (kok) | Marathi (mar)
## Dataset Structure
### Data Instances
```
A random sample from Hindi (hin) Test dataset.
{
"unique_identifier": "hin1",
"native sentence": "",
"romanized sentence": "",
"language": "Hindi",
"script": "Devanagari",
"source": "Dakshina",
}
```
### Data Fields
- `unique_identifier` (string): 3-letter language code followed by a unique number in Test set.
- `native sentence` (string): A sentence in Indic language.
- `romanized sentence` (string): Transliteration of native sentence in English (Romanized sentence).
- `language` (string): Language of native sentence.
- `script` (string): Script in which native sentence is written.
- `source` (string): Source of the data.
For created data sources, depending on the destination/sampling method of a pair in a language, it will be one of:
- Dakshina Dataset
- Flores-200
- Manually Romanized
- Manually generated
### Data Splits
| Subset | asm | ben | brx | guj | hin | kan | kas (Perso-Arabic) | kas (Devanagari) | kok | mai | mal | mni (Bengali) | mni (Meetei Mayek) | mar | nep | ori | pan | san | sid | tam | tel | urd |
|:------:|:---:|:---:|:---:|:---:|:---:|:---:|:------------------:|:----------------:|:---:|:---:|:---:|:-------------:|:------------------:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
| Native | 1012 | 5606 | 1500 | 5797 | 5617 | 5859 | 2511 | 1012 | 1500 | 2512 | 5628 | 1012 | 1500 | 5611 | 2512 | 1012 | 5776 | 2510 | 2512 | 5893 | 5779 | 5751 | 6883 |
| Romanized | 512 | 4595 | 433 | 4785 | 4606 | 4848 | 450 | 0 | 444 | 439 | 4617 | 0 | 442 | 4603 | 423 | 512 | 4765 | 448 | 0 | 4881 | 4767 | 4741 | 4371 |
## Dataset Creation
Information in the paper. [Bhasha-Abhijnaanam: Native-script and romanized Language Identification for 22 Indic languages](https://arxiv.org/abs/2305.15814)
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
Information in the paper. [Bhasha-Abhijnaanam: Native-script and romanized Language Identification for 22 Indic languages](https://arxiv.org/abs/2305.15814)
#### Who are the source language producers?
[More Information Needed]
### Annotations
Information in the paper. [Bhasha-Abhijnaanam: Native-script and romanized Language Identification for 22 Indic languages](https://arxiv.org/abs/2305.15814)
#### Who are the annotators?
Information in the paper. [Bhasha-Abhijnaanam: Native-script and romanized Language Identification for 22 Indic languages](https://arxiv.org/abs/2305.15814)
## 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 CC0 license.
**CC0 License Statement**
- We do not own any of the text from which this data has been extracted.
- We license the actual packaging of manually collected data under the [Creative Commons CC0 license (“no rights reserved”)](http://creativecommons.org/publicdomain/zero/1.0).
- 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{madhani2023bhashaabhijnaanam,
title={Bhasha-Abhijnaanam: Native-script and romanized Language Identification for 22 Indic languages},
author={Yash Madhani and Mitesh M. Khapra and Anoop Kunchukuttan},
year={2023},
eprint={2305.15814},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```
### Contributions
---