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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 3140 of 435 papers

TitleStatusHype
Event detection in Twitter: A keyword volume approachCode0
How Grammatical is Character-level Neural Machine Translation? Assessing MT Quality with Contrastive Translation PairsCode0
Creating Large-Scale Multilingual Cognate TablesCode0
Context Independent Term Mapper for European LanguagesCode0
Can Small Language Models Learn, Unlearn, and Retain Noise Patterns?Code0
Creating a Translation Matrix of the Bible's Names Across 591 LanguagesCode0
Design Challenges in Named Entity TransliterationCode0
Cross-Lingual Text Classification of Transliterated Hindi and MalayalamCode0
Bilingual dictionaries for all EU languagesCode0
Bootstrapping Transliteration with Constrained Discovery for Low-Resource LanguagesCode0
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