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LTRC Hindi-Telugu Parallel Corpus

We provide a Hindi‑Telugu parallel corpus across various technical domains (natural sciences, computer science, law, healthcare, and general domain). The corpus contains 700 K parallel sentences, of which 535 K were created through extraction, alignment, manual translation, iterative back‑translation with post‑editing, and 165 K were collected from the public domain. We report comparative evaluations of the corpus’s representativeness and diversity. The corpus is pre‑processed for machine translation; we trained a neural MT system and reported state‑of‑the‑art baselines on several domains and benchmarks. This defines a new task for domain‑specific MT for low‑resource language pairs such as Hindi‑Telugu. The 535 K curated corpus is freely available for non‑commercial research and is, to our knowledge, the largest, carefully curated, publicly available Hindi‑Telugu domain parallel corpus.

Updated 10/22/2024
github

Description

The LTRC Hindi‑Telugu Parallel Corpus

Dataset Overview

  • Title: The LTRC Hindi‑Telugu Parallel Corpus
  • Authors: Vandan Mujadia, Dipti Sharma
  • Publishing Institution: European Language Resources Association
  • Release Date: June 2022
  • Conference: Proceedings of the Thirteenth Language Resources and Evaluation Conference
  • Location: Marseille, France
  • Publisher: European Language Resources Association

Dataset Content

  • Language Pair: Hindi‑Telugu
  • Domains: Natural Sciences, Computer Science, Law, Healthcare, and General Domain
  • Scale: 700 K parallel sentences (535 K created via multiple methods, 165 K from public domain)
  • Creation Methods: Extraction, alignment, manual translation, iterative back‑translation with post‑editing

Dataset Uses

  • Pre‑processing: Suitable for machine translation
  • Task: Defines a new domain MT task for low‑resource language pairs (Hindi‑Telugu)

Dataset Characteristics

  • Representativeness & Diversity: Comparative evaluation performed
  • Availability: Free for non‑commercial research
  • Scale Claim: Largest, carefully curated, publicly available Hindi‑Telugu domain parallel corpus to date

Dataset Source

  • Development Institution: LTRC, IIIT‑Hyderabad
  • Funding: Meity, Government of India
  • Project: ILMT Hindi‑Telugu Pilot

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Topics

Machine Translation
Low‑Resource Languages

Source

Organization: github

Created: 10/22/2024

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