SOTAVerified

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 426435 of 435 papers

TitleStatusHype
Cross-Lingual Text Classification of Transliterated Hindi and MalayalamCode0
Context Independent Term Mapper for European LanguagesCode0
IIITT@Dravidian-CodeMix-FIRE2021: Transliterate or translate? Sentiment analysis of code-mixed text in Dravidian languagesCode0
Can Small Language Models Learn, Unlearn, and Retain Noise Patterns?Code0
Neural Machine Translation Techniques for Named Entity TransliterationCode0
Breaking the Script Barrier in Multilingual Pre-Trained Language Models with Transliteration-Based Post-Training AlignmentCode0
TransMI: A Framework to Create Strong Baselines from Multilingual Pretrained Language Models for Transliterated DataCode0
Neural String Edit DistanceCode0
Bilingual dictionaries for all EU languagesCode0
Towards Offensive Language Identification for Dravidian LanguagesCode0
Show:102550
← PrevPage 18 of 18Next →

No leaderboard results yet.