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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 411420 of 435 papers

TitleStatusHype
TransliCo: A Contrastive Learning Framework to Address the Script Barrier in Multilingual Pretrained Language ModelsCode0
An Empirical Study of Chinese Name Matching and ApplicationsCode0
On Biasing Transformer Attention Towards MonotonicityCode0
Jailbreaking LLMs with Arabic Transliteration and ArabiziCode0
Creating a Translation Matrix of the Bible's Names Across 591 LanguagesCode0
Bootstrapping Transliteration with Constrained Discovery for Low-Resource LanguagesCode0
Sinhala Transliteration: A Comparative Analysis Between Rule-based and Seq2Seq ApproachesCode0
How Grammatical is Character-level Neural Machine Translation? Assessing MT Quality with Contrastive Translation PairsCode0
Towards Offensive Language Identification for Tamil Code-Mixed YouTube Comments and PostsCode0
Event detection in Twitter: A keyword volume approachCode0
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