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

We present a method to transliterate names in the framework of end-to-end statistical
machine translation. The system is trained to learn when to transliterate. For Arabic to …

We analyze some of the fundamental design challenges that impact the development of a
multilingual state-of-the-art named entity transliteration system, including curating bilingual …

The article highlights the importance of transliteration in the field of machine translation,
correct writing of personal and place names, and information retrieval. It provides an …

Code-switching is a commonly occurring phenomenon in many multilingual communities,
wherein a speaker switches between languages within a single utterance. Conventional …

Transliterating named entities from one language into another can be approached as neural
machine translation (NMT) problem, for which we use deep attentional RNN encoder …

Most machine transliteration systems transliterate out of vocabulary (OOV) words through
intermediate phonemic mapping. A framework has been presented that allows direct …

This report documents the details of the Machine Transliteration Shared Task conducted as
a part of the Named Entities Workshop (NEWS), an ACL-IJCNLP 2009 workshop. The …

We present a novel approach to integrate transliteration into Hindi-to-Urdu statistical
machine translation. We propose two probabilistic models, based on conditional and joint …

Cross-lingual entity linking (XEL) is the task of finding referents in a target-language
knowledge base (KB) for mentions extracted from source-language texts. The first step of (X) …