metadata
task_categories:
- sequence-modeling
multilinguality:
- translation
task_ids:
- language-modeling
languages:
- hi
- te
- ta
- ml
- gu
- ur
- bn
- or
- mr
- pa
- en
annotations_creators:
- no-annotation
source_datasets:
- original
size_categories:
- 1K<n<10K
licenses:
- cc-by-4-0
Dataset Card Creation Guide
Table of Contents
- Dataset Card Creation Guide
Dataset Description
- Homepage: Link
- Repository:
- Paper: ARXIV
- Leaderboard:
- Point of Contact: [email protected]
Dataset Summary
Indian Prime Minister's speeches - Mann Ki Baat, on All India Radio, translated into many languages.
Supported Tasks and Leaderboards
[MORE INFORMATION NEEDED]
Languages
Hindi, Telugu, Tamil, Malayalam, Gujarati, Urdu, Bengali, Oriya, Marathi, Punjabi, and English
Dataset Structure
Data Instances
[MORE INFORMATION NEEDED]
Data Fields
src_tag
:string
text in source languagetgt_tag
:string
translation of source language in target language
Data Splits
[MORE INFORMATION NEEDED]
Dataset Creation
Curation Rationale
[MORE INFORMATION NEEDED]
Source Data
[MORE INFORMATION NEEDED]
Initial Data Collection and Normalization
[MORE INFORMATION NEEDED]
Who are the source language producers?
[MORE INFORMATION NEEDED]
Annotations
Annotation process
[MORE INFORMATION NEEDED]
Who are the annotators?
[MORE INFORMATION NEEDED]
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
The datasets and pretrained models provided here are licensed under Creative Commons Attribution-ShareAlike 4.0 International License.
Citation Information
@misc{siripragada2020multilingual,
title={A Multilingual Parallel Corpora Collection Effort for Indian Languages},
author={Shashank Siripragada and Jerin Philip and Vinay P. Namboodiri and C V Jawahar},
year={2020},
eprint={2007.07691},
archivePrefix={arXiv},
primaryClass={cs.CL}
}