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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 411420 of 435 papers

TitleStatusHype
An Omni-Font Gurmukhi to Shahmukhi Transliteration System0
An unsupervised EM method to infer time variation in sense probabilities0
ANVITA Machine Translation System for WAT 2021 MultiIndicMT Shared Task0
Applying mpaligner to Machine Transliteration with Japanese-Specific Heuristics0
Applying Neural Networks to English-Chinese Named Entity Transliteration0
Applying Sanskrit Concepts for Reordering in MT0
Approche Hybride pour la translit\'eration de l'Arabizi Alg\'erien : une \'etude pr\'eliminaire (A hybrid approach for the transliteration of Algerian Arabizi: A primary study)0
Arabic Diacritization: Stats, Rules, and Hacks0
Arabic Diacritization with Recurrent Neural Networks0
Arabic Retrieval Revisited: Morphological Hole Filling0
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