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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 61–70 of 435 papers

TitleStatusHype
A Unified Model for Arabizi Detection and Transliteration using Sequence-to-Sequence Models—0
A Universal Dependencies Treebank for Marathi—0
Applying mpaligner to Machine Transliteration with Japanese-Specific Heuristics—0
ANVITA Machine Translation System for WAT 2021 MultiIndicMT Shared Task—0
AIDA2: A Hybrid Approach for Token and Sentence Level Dialect Identification in Arabic—0
An unsupervised EM method to infer time variation in sense probabilities—0
An Omni-Font Gurmukhi to Shahmukhi Transliteration System—0
A Hybrid Word Alignment Model for Phrase-Based Statistical Machine Translation—0
A Conventional Orthography for Tunisian Arabic—0
Automatic word stress annotation of Russian unrestricted text—0
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