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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 91100 of 435 papers

TitleStatusHype
Multilingual Abusiveness Identification on Code-Mixed Social Media Text0
Does Transliteration Help Multilingual Language Modeling?Code0
Learning to pronounce as measuring cross-lingual joint orthography-phonology complexity0
Towards a Broad Coverage Named Entity Resource: A Data-Efficient Approach for Many Diverse Languages0
DEEP: DEnoising Entity Pre-training for Neural Machine Translation0
English-to-Chinese Transliteration with Phonetic Back-transliteration0
ARGUABLY at ComMA@ICON: Detection of Multilingual Aggressive, Gender Biased, and Communally Charged Tweets Using Ensemble and Fine-Tuned IndicBERT0
Speech Synthesis for Low Resource Languages using Transliteration Enabled Transfer Learning0
IIITT@Dravidian-CodeMix-FIRE2021: Transliterate or translate? Sentiment analysis of code-mixed text in Dravidian languagesCode0
DEEP: DEnoising Entity Pre-training for Neural Machine Translation0
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