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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 1120 of 435 papers

TitleStatusHype
ParsiPy: NLP Toolkit for Historical Persian Texts in PythonCode1
Processing South Asian Languages Written in the Latin Script: the Dakshina DatasetCode1
Sub-Character Tokenization for Chinese Pretrained Language ModelsCode1
Taqyim: Evaluating Arabic NLP Tasks Using ChatGPT ModelsCode1
A machine transliteration tool between Uzbek alphabetsCode1
Applying the Transformer to Character-level TransductionCode1
KLPT – Kurdish Language Processing ToolkitCode1
DeepScribe: Localization and Classification of Elamite Cuneiform Signs Via Deep LearningCode1
ParaNames: A Massively Multilingual Entity Name CorpusCode1
Agreement on Target-bidirectional Neural Machine Translation0
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