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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
Lost in Transliteration: Bridging the Script Gap in Neural IR0
Low-Resource Machine Transliteration Using Recurrent Neural Networks of Asian Languages0
Low-Resource Transliteration for Roman-Urdu and Urdu Using Transformer-Based Models0
Machine Translation Pre-training for Data-to-Text Generation -- A Case Study in Czech0
Machine Translation Pre-training for Data-to-Text Generation - A Case Study in Czech0
Machine Translation without Words through Substring Alignment0
MADAMIRA: A Fast, Comprehensive Tool for Morphological Analysis and Disambiguation of Arabic0
Manually Annotated Corpus of Polish Texts Published between 1830 and 19180
Mapping it differently: A solution to the linking challenges0
Mapping Source to Target Strings without Alignment by Analogical Learning: A Case Study with Transliteration0
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