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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 211220 of 435 papers

TitleStatusHype
Putting Figures on Influences on Moroccan Darija from Arabic, French and Spanish using the WordNet0
Leveraging Orthographic Similarity for Multilingual Neural Transliteration0
Sequence to Sequence Networks for Roman-Urdu to Urdu Transliteration0
PJIIT's systems for WMT 2017 Conference0
Transliterated Mobile Keyboard Input via Weighted Finite-State Transducers0
A Neural Network Transliteration Model in Low Resource Settings0
HCCL at SemEval-2017 Task 2: Combining Multilingual Word Embeddings and Transliteration Model for Semantic Similarity0
Joint Prediction of Morphosyntactic Categories for Fine-Grained Arabic Part-of-Speech Tagging Exploiting Tag Dictionary Information0
Learning Bilingual Projections of Embeddings for Vocabulary Expansion in Machine Translation0
Statistical Models for Unsupervised, Semi-Supervised Supervised Transliteration Mining0
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