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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 251260 of 435 papers

TitleStatusHype
Latent Semantic Transliteration using Dirichlet Mixture0
Latin script keyboards for South Asian languages with finite-state normalization0
Learning Bilingual Projections of Embeddings for Vocabulary Expansion in Machine Translation0
Learning Cross-lingual Mappings for Data Augmentation to Improve Low-Resource Speech Recognition0
Learning to Find Translations and Transliterations on the Web0
Learning to pronounce as measuring cross-lingual joint orthography-phonology complexity0
Leveraging Alignment and Phonology for low-resource Indic to English Neural Machine Transliteration0
Leveraging Entity Linking and Related Language Projection to Improve Name Transliteration0
Leveraging Orthographic Similarity for Multilingual Neural Transliteration0
Leveraging Statistical Transliteration for Dictionary-Based English-Bengali CLIR of OCR`d Text0
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