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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 381390 of 435 papers

TitleStatusHype
Tilde's Parallel Corpus Filtering Methods for WMT 20180
Towards a Broad Coverage Named Entity Resource: A Data-Efficient Approach for Many Diverse Languages0
Towards an Efficient Code-Mixed Grapheme-to-Phoneme Conversion in an Agglutinative Language: A Case Study on To-Korean Transliteration0
Towards Cross-Cultural Machine Translation with Retrieval-Augmented Generation from Multilingual Knowledge Graphs0
Towards Transliteration between Sindhi Scripts from Devanagari to Perso-Arabic0
Towards Zero-Shot Code-Switched Speech Recognition0
Training a Bilingual Language Model by Mapping Tokens onto a Shared Character Space0
Training Automatic Transliteration Models on DBPedia Data0
Translation of Unseen Bigrams by Analogy Using an SVM Classifier0
TRANSLIT: A Large-scale Name Transliteration Resource0
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