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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 7180 of 435 papers

TitleStatusHype
A Multi-Orthography Parallel Corpus of Yiddish Nouns0
A Simple but Effective Approach to Improve Arabizi-to-English Statistical Machine Translation0
A Multilinear Approach to the Unsupervised Learning of Morphology0
A Digital Swedish-Yiddish/Yiddish-Swedish Dictionary: A Web-Based Dictionary that is also Available Offline0
ARGUABLY at ComMA@ICON: Detection of Multilingual Aggressive, Gender Biased, and Communally Charged Tweets Using Ensemble and Fine-Tuned IndicBERT0
AraNLP: a Java-based Library for the Processing of Arabic Text.0
Arabizi sentiment analysis based on transliteration and automatic corpus annotation0
Arabizi Detection and Conversion to Arabic0
amLite: Amharic Transliteration Using Key Map Dictionary0
A Deep Learning Based Approach to Transliteration0
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