Romanized to Native Malayalam Script Transliteration Using an Encoder-Decoder Framework

Bajiyo Baiju, Kavya Manohar, Leena G Pillai, Elizabeth Sherly
12/13/2024
cs.CL

No official code found. Best implementation: VRCLC-DUK/ml-en-transliteration (1 star, MIT, last commit 2024-12-17).

Abstract

In this work, we present the development of a reverse transliteration model to convert romanized Malayalam to native script using an encoder-decoder framework built with attention-based bidirectional Long Short Term Memory (Bi-LSTM) architecture. To train the model, we have used curated and combined collection of 4.3 million transliteration pairs derived from publicly available Indic language translitertion datasets, Dakshina and Aksharantar. We evaluated the model on two different test dataset provided by IndoNLP-2025-Shared-Task that contain, (1) General typing patterns and (2) Adhoc typing patterns, respectively. On the Test Set-1, we obtained a character error rate (CER) of 7.4%. However upon Test Set-2, with adhoc typing patterns, where most vowel indicators are missing, our model gave a CER of 22.7%.

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Code Implementations(1)

VRCLC-DUK/ml-en-transliterationCommunity100%
MIT

Romanized to Native Malayalam Script Transliteration

10Jupyter NotebookDec 11, 20241 years agoMIT

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Cite this paper

@article{baiju2024romanized,
  title  = {Romanized to Native Malayalam Script Transliteration Using an Encoder-Decoder Framework},
  author = {Bajiyo Baiju and Kavya Manohar and Leena G Pillai and Elizabeth Sherly},
  year   = {2024},
  eprint = {2412.09957},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2412.09957v1}
}

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