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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 361370 of 435 papers

TitleStatusHype
Statistical Machine Transliteration Baselines for NEWS 20180
Statistical Models for Unsupervised, Semi-Supervised Supervised Transliteration Mining0
Stochastic Contextual Edit Distance and Probabilistic FSTs0
Structured Belief Propagation for NLP0
Study of the impact of proper name transliteration on the performance of word alignment in French-Arabic parallel corpora (Etude de l'impact de la translitt\'eration de noms propres sur la qualit\'e de l'alignement de mots \`a partir de corpus parall\`eles fran -arabe) [in French]0
Sublexical Translations for Low-Resource Language0
Substring-based unsupervised transliteration with phonetic and contextual knowledge0
Swa Bhasha: Message-Based Singlish to Sinhala Transliteration0
Syllable-based Machine Transliteration with Extra Phrase Features0
Tajik-Farsi Persian Transliteration Using Statistical Machine Translation0
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