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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 391400 of 435 papers

TitleStatusHype
A Correlational Encoder Decoder Architecture for Pivot Based Sequence Generation0
Addressing Noise in Multidialectal Word Embeddings0
A Deep Learning Based Approach to Transliteration0
A Digital Swedish-Yiddish/Yiddish-Swedish Dictionary: A Web-Based Dictionary that is also Available Offline0
A Framework for the Classification and Annotation of Multiword Expressions in Dialectal Arabic0
Agreement on Target-bidirectional Neural Machine Translation0
A House United: Bridging the Script and Lexical Barrier between Hindi and Urdu0
A Hybrid Transliteration Model for Chinese/English Named Entities ---BJTU-NLP Report for the 5th Named Entities Workshop0
A Hybrid Word Alignment Model for Phrase-Based Statistical Machine Translation0
AIDA2: A Hybrid Approach for Token and Sentence Level Dialect Identification in Arabic0
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