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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 181190 of 435 papers

TitleStatusHype
Indigenous language technologies in Canada: Assessment, challenges, and successes0
Identifying Aggression and Toxicity in Comments using Capsule Network0
Statistical Machine Transliteration Baselines for NEWS 20180
Report of NEWS 2018 Named Entity Transliteration Shared Task0
Transliteration Better than Translation? Answering Code-mixed Questions over a Knowledge Base0
Simple Features for Strong Performance on Named Entity Recognition in Code-Switched Twitter Data0
Comparison of Assorted Models for Transliteration0
A Deep Learning Based Approach to Transliteration0
NEWS 2018 Whitepaper0
Neural Machine Translation Techniques for Named Entity TransliterationCode0
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