Low-Resource Noisy Transliteration Normalization Using Large-Scale Language Model

Low-Resource Noisy Transliteration Normalization Using Large-Scale Language Model

Transliteration normalization is a crucial task for low-resource languages, particularly for Mongolian, where noisy text from social media presents significant challenges. The frequent use of non-standard transliteration can contribute to the gradual erosion of linguistic knowledge, particularly amo...

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Bibliographic Details
Main Authors: Zolzaya Byambadorj, Ulziibayar Sonom-Ochir, Munkhsukh Enkhbayar, Hyun-Chul Kim, Altangerel Ayush
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Data-driven method
GPT2 model
noisy text
seq2seq model
text normalization
token
Online Access:https://ieeexplore.ieee.org/document/11017577/
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