Datasets:
license: cc-by-4.0
task_categories:
- translation
language:
- hi
- as
- bn
- gom
- gu
- ks
- mai
- mr
- mni
- npi
- or
- pa
- sat
- sd
- te
- ur
- ta
- kn
- ml
size_categories:
- 1K<n<10K
pretty_name: Hindi → Indian Languages (Education)
Hindi → Indian Languages Education Translation Dataset
Overview
Parallel corpus for Hindi → multiple Indian languages focused on the education domain.
Content spans textbooks-style explanations and texts across all subjects like History, Geography, Chemisty, Biology etc.
Each subfolder maps to a language pair (e.g., HIN-ASM, HIN-BAN, HIN-DOI/ODI, HIN-GOM, HIN-GUJ, HIN-KAS, HIN-MAI, HIN-MAR, HIN-MNI, HIN-NPI, HIN-PAN, HIN-SAT, HIN-SND, HIN-TEL; and Tamil-centric pairs TAM-KAN, TAM-MAL, TAM-TEL if included).
Languages
Source: Hindi (hi)
Targets: Assamese (as), Bangla (bn), Goan Konkani (gom), Gujarati (gu), Kashmiri (ks), Maithili (mai), Marathi (mr), Manipuri/Meitei (mni), Nepali (npi), Odia (or), Punjabi (pa), Santali (sat), Sindhi (sd), Telugu (te), Tamil (ta), Kannada (kn), Malayalam (ml), Urdu (ur).
Sources
Replace with exact attributions:
- School education department circulars and notices
- NCERT/SCERT materials and summaries (publicly available)
- University/board announcements and FAQs
Format
- Folder arrangement: Each language pair is subdivided into sub-domains and each sub-domain is further divided into source-translated, source_reviewed and translated-reviewed language pairs.
- Type folders: source-reviewed translations are the translations of the highest quality which are reviewed after translation; whereas source-translated language pairs are larger in number but are unreviewed after manual translation. The difference between the qualities can be estimated using the translated-reviewed language pairs using TER.
- File type: TSV per language pair
- Fields:
id,src_hi,tgt_<lang>,domain="education" - UTF-8 encoding, normalized punctuation
Intended Use
- Training & evaluation of MT systems for educational content in India.