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--- |
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annotations_creators: [] |
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language_creators: |
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- crowdsourced |
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- expert-generated |
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- machine-generated |
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- found |
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- other |
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language: |
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- asm |
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- ben |
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- brx |
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- doi |
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- guj |
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- hin |
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- kan |
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- kas |
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- kok |
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- mai |
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- mal |
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- mar |
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- mni |
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- nep |
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- ori |
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- pan |
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- san |
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- sid |
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- tam |
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- tel |
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- urd |
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license: cc |
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multilinguality: |
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- multilingual |
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pretty_name: Aksharantar |
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source_datasets: |
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- original |
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task_categories: |
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- text-generation |
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task_ids: [] |
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--- |
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|
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# Dataset Card for Aksharantar |
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## Table of Contents |
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- [Table of Contents](#table-of-contents) |
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- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
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- [Languages](#languages) |
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- [Dataset Structure](#dataset-structure) |
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- [Data Instances](#data-instances) |
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- [Data Fields](#data-fields) |
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- [Data Splits](#data-splits) |
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- [Dataset Creation](#dataset-creation) |
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- [Curation Rationale](#curation-rationale) |
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- [Source Data](#source-data) |
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- [Annotations](#annotations) |
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- [Personal and Sensitive Information](#personal-and-sensitive-information) |
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- [Considerations for Using the Data](#considerations-for-using-the-data) |
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- [Social Impact of Dataset](#social-impact-of-dataset) |
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- [Discussion of Biases](#discussion-of-biases) |
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- [Other Known Limitations](#other-known-limitations) |
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- [Additional Information](#additional-information) |
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- [Dataset Curators](#dataset-curators) |
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- [Licensing Information](#licensing-information) |
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- [Citation Information](#citation-information) |
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- [Contributions](#contributions) |
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|
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## Dataset Description |
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- **Homepage:** https://indicnlp.ai4bharat.org/indic-xlit/ |
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- **Repository:** https://github.com/AI4Bharat/IndicXlit/ |
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- **Paper:** [Aksharantar: Towards building open transliteration tools for the next billion users](https://arxiv.org/abs/2205.03018) |
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- **Leaderboard:** |
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- **Point of Contact:** |
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### Dataset Summary |
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Aksharantar is the largest publicly available transliteration dataset for 20 Indic languages. The corpus has 26M Indic language-English transliteration pairs. |
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### Supported Tasks and Leaderboards |
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[More Information Needed] |
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### Languages |
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| <!-- --> | <!-- --> | <!-- --> | <!-- --> | <!-- --> | <!-- --> | |
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| -------------- | -------------- | -------------- | --------------- | -------------- | ------------- | |
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| Assamese (asm) | Hindi (hin) | Maithili (mai) | Marathi (mar) | Punjabi (pan) | Tamil (tam) | |
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| Bengali (ben) | Kannada (kan) | Malayalam (mal)| Nepali (nep) | Sanskrit (san) | Telugu (tel) | |
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| Bodo(brx) | Kashmiri (kas) | Manipuri (mni) | Oriya (ori) | Sindhi (snd) | Urdu (urd) | |
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| Gujarati (guj) | Konkani (kok) | Dogri (doi) | |
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## Dataset Structure |
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### Data Instances |
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``` |
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A random sample from Hindi (hin) Train dataset. |
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{ |
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'unique_identifier': 'hin1241393', |
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'native word': 'स्वाभिमानिक', |
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'english word': 'swabhimanik', |
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'source': 'IndicCorp', |
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'score': -0.1028788579 |
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} |
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``` |
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### Data Fields |
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- `unique_identifier` (string): 3-letter language code followed by a unique number in each set (Train, Test, Val). |
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- `native word` (string): A word in Indic language. |
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- `english word` (string): Transliteration of native word in English (Romanised word). |
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- `source` (string): Source of the data. |
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- `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. |
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For created data sources, depending on the destination/sampling method of a pair in a language, it will be one of: |
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- Dakshina Dataset |
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- IndicCorp |
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- Samanantar |
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- Wikidata |
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- Existing sources |
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- Named Entities Indian (AK-NEI) |
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- Named Entities Foreign (AK-NEF) |
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- Data from Uniform Sampling method. (Ak-Uni) |
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- Data from Most Frequent words sampling method. (Ak-Freq) |
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### Data Splits |
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| 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 | |
|
|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:| |
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| Training | 179K | 1231K | 36K | 1143K | 1299K | 2907K | 47K | 613K | 283K | 4101K | 10K | 1453K | 2397K | 346K | 515K | 1813K | 60K | 3231K | 2430K | 699K | |
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| Validation | 4K | 11K | 3K | 12K | 6K | 7K | 4K | 4K | 4K | 8K | 3K | 8K | 3K | 3K | 9K | 3K | 8K | 9K | 8K | 12K | |
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| Test | 5531 | 5009 | 4136 | 7768 | 5693 | 6396 | 7707 | 5093 | 5512 | 6911 | 4925 | 6573 | 4133 | 4256 | 4316 | 5334 | - | 4682 | 4567 | 4463 | |
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## Dataset Creation |
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|
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Information in the paper. [Aksharantar: Towards building open transliteration tools for the next billion users](https://arxiv.org/abs/2205.03018) |
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### Curation Rationale |
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[More Information Needed] |
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|
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### Source Data |
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#### Initial Data Collection and Normalization |
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Information in the paper. [Aksharantar: Towards building open transliteration tools for the next billion users](https://arxiv.org/abs/2205.03018) |
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#### Who are the source language producers? |
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[More Information Needed] |
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### Annotations |
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Information in the paper. [Aksharantar: Towards building open transliteration tools for the next billion users](https://arxiv.org/abs/2205.03018) |
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#### Annotation process |
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|
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Information in the paper. [Aksharantar: Towards building open transliteration tools for the next billion users](https://arxiv.org/abs/2205.03018) |
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|
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#### Who are the annotators? |
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Information in the paper. [Aksharantar: Towards building open transliteration tools for the next billion users](https://arxiv.org/abs/2205.03018) |
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|
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### Personal and Sensitive Information |
|
|
|
[More Information Needed] |
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|
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## Considerations for Using the Data |
|
|
|
### Social Impact of Dataset |
|
|
|
[More Information Needed] |
|
|
|
### Discussion of Biases |
|
|
|
[More Information Needed] |
|
|
|
### Other Known Limitations |
|
|
|
[More Information Needed] |
|
|
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## Additional Information |
|
|
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### Dataset Curators |
|
|
|
[More Information Needed] |
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|
|
### Licensing Information |
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<!-- <a rel="license" float="left" href="http://creativecommons.org/publicdomain/zero/1.0/"> |
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<img src="https://licensebuttons.net/p/zero/1.0/88x31.png" style="border-style: none;" alt="CC0" width="100" /> |
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<img src="https://mirrors.creativecommons.org/presskit/buttons/88x31/png/by.png" style="border-style: none;" alt="CC-BY" width="100" href="http://creativecommons.org/publicdomain/zero/1.0/"/> |
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</a> |
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<br/> --> |
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This data is released under the following licensing scheme: |
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|
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- Manually collected data: Released under CC-BY license. |
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- Mined dataset (from Samanantar and IndicCorp): Released under CC0 license. |
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- Existing sources: Released under CC0 license. |
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**CC-BY License** |
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|
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<a rel="license" float="left" href="https://creativecommons.org/about/cclicenses/"> |
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<img src="https://mirrors.creativecommons.org/presskit/buttons/88x31/png/by.png" style="border-style: none;" alt="CC-BY" width="100"/> |
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</a> |
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<br> |
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<br> |
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<!-- |
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and the Aksharantar benchmark and all manually transliterated data under the [Creative Commons CC-BY license (“no rights reserved”)](https://creativecommons.org/licenses/by/4.0/). --> |
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**CC0 License Statement** |
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<a rel="license" float="left" href="https://creativecommons.org/about/cclicenses/"> |
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<img src="https://licensebuttons.net/p/zero/1.0/88x31.png" style="border-style: none;" alt="CC0" width="100"/> |
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</a> |
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<br> |
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<br> |
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|
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- We do not own any of the text from which this data has been extracted. |
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- We license the actual packaging of the mined data under the [Creative Commons CC0 license (“no rights reserved”)](http://creativecommons.org/publicdomain/zero/1.0). |
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- To the extent possible under law, <a rel="dct:publisher" href="https://indicnlp.ai4bharat.org/aksharantar/"> <span property="dct:title">AI4Bharat</span></a> has waived all copyright and related or neighboring rights to <span property="dct:title">Aksharantar</span> manually collected data and existing sources. |
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- This work is published from: India. |
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### Citation Information |
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|
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``` |
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@misc{madhani2022aksharantar, |
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title={Aksharantar: Towards Building Open Transliteration Tools for the Next Billion Users}, |
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author={Yash Madhani and Sushane Parthan and Priyanka Bedekar and Ruchi Khapra and Anoop Kunchukuttan and Pratyush Kumar and Mitesh Shantadevi Khapra}, |
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year={2022}, |
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eprint={}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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``` |
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### Contributions |
