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Transliteration

Transliteration is a mechanism for converting a word in a source (foreign) language to a target language, and often adopts approaches from machine translation. In machine translation, the objective is to preserve the semantic meaning of the utterance as much as possible while following the syntactic structure in the target language. In Transliteration, the objective is to preserve the original pronunciation of the source word as much as possible while following the phonological structures of the target language.

For example, the city’s name “Manchester” has become well known by people of languages other than English. These new words are often named entities that are important in cross-lingual information retrieval, information extraction, machine translation, and often present out-of-vocabulary challenges to spoken language technologies such as automatic speech recognition, spoken keyword search, and text-to-speech.

Source: Phonology-Augmented Statistical Framework for Machine Transliteration using Limited Linguistic Resources

Papers

Showing 241250 of 435 papers

TitleStatusHype
IXA Biomedical Translation System at WMT16 Biomedical Translation Task0
PJAIT Systems for the WMT 20160
Target-Bidirectional Neural Models for Machine Transliteration0
The AFRL-MITLL WMT16 News-Translation Task Systems0
Leveraging Entity Linking and Related Language Projection to Improve Name Transliteration0
Linguistic Issues in the Machine Transliteration of Chinese, Japanese and Arabic Names0
A Multilinear Approach to the Unsupervised Learning of Morphology0
Whitepaper of NEWS 2016 Shared Task on Machine Transliteration0
NRC Russian-English Machine Translation System for WMT 20160
Applying Neural Networks to English-Chinese Named Entity Transliteration0
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