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Error code: DatasetGenerationCastError Exception: DatasetGenerationCastError Message: An error occurred while generating the dataset All the data files must have the same columns, but at some point there are 1 new columns ({'score'}) This happened while the json dataset builder was generating data using zip://asm_train.json::/tmp/hf-datasets-cache/heavy/datasets/32350809506324-config-parquet-and-info-ai4bharat-Aksharantar-b37e448d/downloads/3c3f99420a34268b8e9c098500c8f2a2b060e17ebbe6b65d63bebb608ea7313e Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations) Traceback: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single writer.write_table(table) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table pa_table = table_cast(pa_table, self._schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast return cast_table_to_schema(table, schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema raise CastError( datasets.table.CastError: Couldn't cast unique_identifier: string native word: string english word: string source: string score: double to {'unique_identifier': Value(dtype='string', id=None), 'native word': Value(dtype='string', id=None), 'english word': Value(dtype='string', id=None), 'source': Value(dtype='string', id=None)} because column names don't match During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1321, in compute_config_parquet_and_info_response parquet_operations = convert_to_parquet(builder) File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 935, in convert_to_parquet builder.download_and_prepare( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare self._download_and_prepare( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, in _download_and_prepare self._prepare_split(split_generator, **prepare_split_kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split for job_id, done, content in self._prepare_split_single( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2013, in _prepare_split_single raise DatasetGenerationCastError.from_cast_error( datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset All the data files must have the same columns, but at some point there are 1 new columns ({'score'}) This happened while the json dataset builder was generating data using zip://asm_train.json::/tmp/hf-datasets-cache/heavy/datasets/32350809506324-config-parquet-and-info-ai4bharat-Aksharantar-b37e448d/downloads/3c3f99420a34268b8e9c098500c8f2a2b060e17ebbe6b65d63bebb608ea7313e Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
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unique_identifier
string | native word
string | english word
string | source
string |
---|---|---|---|
asm1 | লক্ষীনগৰস্থিত | lakhyeenogorsthito | AK-Freq |
asm2 | চতুৰ্থ | soturtho | AK-Freq |
asm3 | এইখন | eikhan | AK-Freq |
asm4 | প্ৰতিমূৰ্তিসমূহ | protimurtixomuh | AK-Freq |
asm5 | প্ৰতিযোগিতাতে | protijugitate | AK-Freq |
asm6 | নিয়া | niya | AK-Freq |
asm7 | আঁচন | aason | AK-Freq |
asm8 | দেউতালৈ | deutaloi | AK-Freq |
asm9 | ঈগলনেষ্ট | eaglenest | AK-Freq |
asm10 | সিহঁতক | xeehotok | AK-Freq |
asm11 | পূর্বাঞ্চলজুৰি | poorbancholjuri | AK-Freq |
asm12 | পৰিদৰ্শক | poridorxok | AK-Freq |
asm13 | হেৰুৱাইছিলো | heruwaisilu | AK-Freq |
asm14 | সদস্যসকলে | sodoxyosokole | AK-Freq |
asm15 | সংক্রান্তিৰ | xongkrantir | AK-Freq |
asm16 | শিক্ষাগতভাৱে | xikhyagotobhabe | AK-Freq |
asm17 | কৰিলো | korilu | AK-Freq |
asm18 | তচেন | tosen | AK-Freq |
asm19 | গোৰ্খাসকলক | gurkhahokolok | AK-Freq |
asm20 | ছাত্ৰগৰাকীক | satrogorakik | AK-Freq |
asm21 | প্ৰতিযোগীগৰাকীক | protizugeegorakeek | AK-Freq |
asm22 | ভালেসংখ্যক | bhalexonkhyok | AK-Freq |
asm23 | বাক্য | bakyo | AK-Freq |
asm24 | তাৎপৰ্য্যপূৰ্ণৰূপে | tatporzyopurnorupe | AK-Freq |
asm25 | প্ৰতিনিধিয়ে | protinidhiye | AK-Freq |
asm26 | কার্যক্রমৰ | karzokromor | AK-Freq |
asm27 | কোকৰাঝাৰত | kokrajharot | AK-Freq |
asm28 | নামিলেই | namilae | AK-Freq |
asm29 | ভোলাৰামে | bhularame | AK-Freq |
asm30 | ৰাজ্যপাল | rajjyopal | AK-Freq |
asm31 | টকামানৰ | tokamanor | AK-Freq |
asm32 | আন্দোলনত | aandulonot | AK-Freq |
asm33 | ঐচিছক | oisichok | AK-Freq |
asm34 | আঁঠুৱাটোৰ | athuwatur | AK-Freq |
asm35 | দুর্নীতি | durneeti | AK-Freq |
asm36 | মুখ্য | mukhyo | AK-Freq |
asm37 | শাসিত | xasito | AK-Freq |
asm38 | উপৰিও | upario | AK-Freq |
asm39 | আবৃত্তিও | abrittiu | AK-Freq |
asm40 | কাৰ্যসূচীৰপৰা | karzyoxusirpora | AK-Freq |
asm41 | লাহে | lahe | AK-Freq |
asm42 | কাৰ্যসূচীৰ | karzoxuseer | AK-Freq |
asm43 | তেতিয়ালৈকে | tetiyaloike | AK-Freq |
asm44 | মিনিটতকৈ | minitotkoy | AK-Freq |
asm45 | য়হা | yaha | AK-Freq |
asm46 | এমৰ | emor | AK-Freq |
asm47 | শিল্পীগৰাকীৰ | xilpeegorakeer | AK-Freq |
asm48 | বেগ | beg | AK-Freq |
asm49 | ঘটাৰ | ghotar | AK-Freq |
asm50 | সামান্য | xamanyo | AK-Freq |
asm51 | শুদ্ধ | xuddho | AK-Freq |
asm52 | ৰাভাই | rabhai | AK-Freq |
asm53 | খালৈআটি | khaaloiaati | AK-Freq |
asm54 | প্ৰশিক্ষকসকল | prosikhyokhokol | AK-Freq |
asm55 | সর্বাধিক | xorbadhik | AK-Freq |
asm56 | মিঃ | mih | AK-Freq |
asm57 | ৰফী | rofi | AK-Freq |
asm58 | টাকৈ | takoy | AK-Freq |
asm59 | কাজকে | kajoke | AK-Freq |
asm60 | স্বাস্থ্যমন্ত্ৰীয়ে | swasthyomontreeye | AK-Freq |
asm61 | এমৰ | amor | AK-Freq |
asm62 | ভোলাৰামে | vularame | AK-Freq |
asm63 | বসুদেৱৰ | bosudebor | AK-Freq |
asm64 | নিৰ্মাণ | nirman | AK-Freq |
asm65 | প্রতিক্রিয়াৰ | protikriyaar | AK-Freq |
asm66 | নিয়াত | niyaat | AK-Freq |
asm67 | বিক্ৰীৰ | bikreer | AK-Freq |
asm68 | কেঁচা | kesaa | AK-Freq |
asm69 | নিৰ্মমভাবে | nirmombhabe | AK-Freq |
asm70 | বিভাগকেইটাৰ | bivagkeytar | AK-Freq |
asm71 | বাৰিষা | barixa | AK-Freq |
asm72 | বিস্ফোৰণকেইটাত | bishforonkeitat | AK-Freq |
asm73 | সকীয়াই | xokeeyai | AK-Freq |
asm74 | ফটকা | fotoka | AK-Freq |
asm75 | নহয় | nohoy | AK-Freq |
asm76 | মহোৎসৱস্থলীত | mohutxowstholit | AK-Freq |
asm77 | শুভেচ্ছাবাৰ্তা | xubhessabarta | AK-Freq |
asm78 | দানবীৰ | daanbir | AK-Freq |
asm79 | খোজেপতি | khujepoti | AK-Freq |
asm80 | আগুৱাই | aguwai | AK-Freq |
asm81 | আপত্তি | aapottee | AK-Freq |
asm82 | পশ্চিম | poschim | AK-Freq |
asm83 | ৱাই | y | AK-Freq |
asm84 | ভোটকেন্দ্রত | bhotkendrot | AK-Freq |
asm85 | ৰইল | royl | AK-Freq |
asm86 | বসুদেৱৰ | boxudebor | AK-Freq |
asm87 | প্রতিনিধি | protinidhi | AK-Freq |
asm88 | পণ্ডিচেৰীত | pondicherryt | AK-Freq |
asm89 | ইতিহাসেৰে | itihaaxere | AK-Freq |
asm90 | উৎসৱৰ | utsovor | AK-Freq |
asm91 | ডিমা | dimaa | AK-Freq |
asm92 | শিক্ষাৰ্থীসকললৈ | xikhyarthixokololoi | AK-Freq |
asm93 | নগৰত | nogorot | AK-Freq |
asm94 | ভাষমান | bhaxoman | AK-Freq |
asm95 | দহটি | dohti | AK-Freq |
asm96 | শিক্ষাবিদগৰাকী | xikhyabidgoraki | AK-Freq |
asm97 | মুখলৈ | mukholoi | AK-Freq |
asm98 | বাউন্সাৰ | bouncer | AK-Freq |
asm99 | নিৰুক্ত | nirookto | AK-Freq |
asm100 | এৰি | eri | AK-Freq |
Dataset Card for Aksharantar
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
CC0 License Statement
- 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}
}
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