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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 291300 of 435 papers

TitleStatusHype
Name Translation based on Fine-grained Named Entity Recognition in a Single Language0
NCU IISR English-Korean and English-Chinese Named Entity Transliteration Using Different Grapheme Segmentation Approaches0
Neural Machine Translation on Scarce-Resource Condition: A case-study on Persian-English0
Neural Machine Transliteration: Preliminary Results0
Neural Network Transduction Models in Transliteration Generation0
NEWS 2018 Whitepaper0
Noise-Aware Character Alignment for Bootstrapping Statistical Machine Transliteration from Bilingual Corpora0
Non-Linear Pairwise Language Mappings for Low-Resource Multilingual Acoustic Model Fusion0
Normalization and Back-Transliteration for Code-Switched Data0
Normalization of Dutch User-Generated Content0
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