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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 281290 of 435 papers

TitleStatusHype
Boosting English-Chinese Machine Transliteration via High Quality Alignment and Multilingual Resources0
Joint Arabic Segmentation and Part-Of-Speech Tagging0
Classifying Arab Names Geographically0
Whitepaper of NEWS 2015 Shared Task on Machine Transliteration0
Data representation methods and use of mined corpora for Indian language transliteration0
A Hybrid Transliteration Model for Chinese/English Named Entities ---BJTU-NLP Report for the 5th Named Entities Workshop0
How do you spell that? A journey through word representations0
Report of NEWS 2015 Machine Transliteration Shared Task0
NCU IISR English-Korean and English-Chinese Named Entity Transliteration Using Different Grapheme Segmentation Approaches0
AIDA2: A Hybrid Approach for Token and Sentence Level Dialect Identification in Arabic0
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