mlsanityData to 14 Oct 2026

IndoNLP 2025: Shared Task on Real-Time Reverse Transliteration for Romanized Indo-Aryan languages

arXiv 2501.05816 ↗First posted 10 Jan 2025cs.CLcited by 3

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Abstract (arXiv)

The paper overviews the shared task on Real-Time Reverse Transliteration for Romanized Indo-Aryan languages. It focuses on the reverse transliteration of low-resourced languages in the Indo-Aryan family to their native scripts. Typing Romanized Indo-Aryan languages using ad-hoc transliterals and achieving accurate native scripts are complex and often inaccurate processes with the current keyboard systems. This task aims to introduce and evaluate a real-time reverse transliterator that converts Romanized Indo-Aryan languages to their native scripts, improving the typing experience for users. Out of 11 registered teams, four teams participated in the final evaluation phase with transliteration models for Sinhala, Hindi and Malayalam. These proposed solutions not only solve the issue of ad-hoc transliteration but also empower low-resource language usability in the digital arena.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 8 of its 28 references that are in the map. First posted on arXiv 10 Jan 2025.

Builds on

8 of 28 references.

References · 8

  1. 2019Survey on Publicly Available Sinhala Natural Language Processing Tools and Researchcited by 46
  2. 2020Processing South Asian Languages Written in the Latin Script: the Dakshina Datasetcited by 35
  3. 2022Aksharantar: Open Indic-language Transliteration datasets and models for the Next Billion Userscited by 19
  4. 2024Sinhala Transliteration: A Comparative Analysis Between Rule-based and Seq2Seq Approachescited by 6
  5. 2024A Survey on Lexical Ambiguity Detection and Word Sense Disambiguationcited by 5
  6. 2024Decoding the Diversity: A Review of the Indic AI Research Landscapecited by 4
  7. 2024Swa Bhasha: Message-Based Singlish to Sinhala Transliterationcited by 3
  8. 2024Romanized to Native Malayalam Script Transliteration Using an Encoder-Decoder Frameworkcited by 1

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Cited by year

Citing papers per year: 2025: 3.

3 papers.

  1. 2025Modeling Romanized Hindi and Bengali: Dataset Creation and Multilingual LLM Integrationcited by 1
  2. 2025Beyond Specialization: Benchmarking LLMs for Transliteration of Indian Languagescited by 0
  3. 2025Swa-bhasha Resource Hub: Romanized Sinhala to Sinhala Transliteration Systems and Data Resourcescited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Historic Scripts to Modern Vision: A Novel Dataset and A VLM Framework for Transliteration of Modi Script to Devanagari
  2. 2022Does Transliteration Help Multilingual Language Modeling?
  3. 2021Cross-Lingual Text Classification of Transliterated Hindi and Malayalam
  4. 2026NADIR: Differential Attention Flow for Non-Autoregressive Transliteration in Indic Languages
  5. 2025NusaAksara: A Multimodal and Multilingual Benchmark for Preserving Indonesian Indigenous Scripts
  6. 2024How Transliterations Improve Crosslingual Alignment
  7. 2022EPIK: Eliminating multi-model Pipelines with Knowledge-distillation
  8. 2026TharuChat: Bootstrapping Large Language Models for a Low-Resource Language via Synthetic Data and Human Validation