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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 5160 of 435 papers

TitleStatusHype
A Multilinear Approach to the Unsupervised Learning of Morphology0
A Simple but Effective Approach to Improve Arabizi-to-English Statistical Machine Translation0
ASMA: A System for Automatic Segmentation and Morpho-Syntactic Disambiguation of Modern Standard Arabic0
Assamese-English Bilingual Machine Translation0
Assamese WordNet based Quality Enhancement of Bilingual Machine Translation System0
A Statistical Model for Unsupervised and Semi-supervised Transliteration Mining0
A systematic comparison of methods for low-resource dependency parsing on genuinely low-resource languages0
A Tightly-coupled Unsupervised Clustering and Bilingual Alignment Model for Transliteration0
A two-stage transliteration approach to improve performance of a multilingual ASR0
Applying mpaligner to Machine Transliteration with Japanese-Specific Heuristics0
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