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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 111120 of 435 papers

TitleStatusHype
Towards Offensive Language Identification for Tamil Code-Mixed YouTube Comments and PostsCode0
Samsung R&D Institute Poland submission to WAT 2021 Indic Language Multilingual Task0
Hybrid Statistical Machine Translation for English-Myanmar: UTYCC Submission to WAT-20210
ANVITA Machine Translation System for WAT 2021 MultiIndicMT Shared Task0
Language Relatedness and Lexical Closeness can help Improve Multilingual NMT: IITBombay@MultiIndicNMT WAT20210
End-to-End Natural Language Understanding Pipeline for Bangla Conversational Agents0
Specializing Multilingual Language Models: An Empirical StudyCode0
Balanced End-to-End Monolingual pre-training for Low-Resourced Indic Languages Code-Switching Speech Recognition0
Exploiting Language Relatedness for Low Web-Resource Language Model Adaptation: An Indic Languages StudyCode0
Normalization and Back-Transliteration for Code-Switched Data0
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