We introduce Aksharantar, the largest publicly available transliteration dataset for 21 Indic
languages containing 26 million transliteration pairs. We build this dataset by mining …

Abstract Grapheme-to-phoneme (g2p) models are rarely available in low-resource
languages, as the creation of training and evaluation data is expensive and time-consuming …

We address the task of joint training of transliteration models for multiple language pairs
(multilingual transliteration). This is an instance of multitask learning, where individual tasks …

We take up the task of large-scale evaluation of neural machine transliteration between
English and Indic languages, with a focus on multilingual transliteration to utilize …

Cross-lingual named-entity lexica are an important resource to multilingual NLP tasks such
as machine translation and cross-lingual wikification. While knowledge bases contain a …

A notable challenge in cross-lingual wikification is the problem of retrieving English
Wikipedia title candidates given a non-English mention, a step that requires translating …

This report presents the results from the Machine Transliteration Shared Task conducted as
part of The Sixth Named Entities Workshop (NEWS 2016) held at ACL 2016in Berlin …

This study evaluates the performance of transformer-based state-of-the-art machine
transliteration systems in processing noisy transliterated texts (non-canonical form) from …

We focus on Burmese name Romanization, a critical task in the translation of Burmese into
languages using Latin script. As Burmese is under researched and not well resourced, we …

Machine transliteration is the process of automatically transforming the script of a word from
a source language to a target language, while preserving pronunciation. Sequence to …