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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 4150 of 435 papers

TitleStatusHype
A two-stage transliteration approach to improve performance of a multilingual ASR0
How Transliterations Improve Crosslingual AlignmentCode0
Exploring the Role of Transliteration in In-Context Learning for Low-resource Languages Written in Non-Latin Scripts0
Can Small Language Models Learn, Unlearn, and Retain Noise Patterns?Code0
Breaking the Script Barrier in Multilingual Pre-Trained Language Models with Transliteration-Based Post-Training AlignmentCode0
Jailbreaking LLMs with Arabic Transliteration and ArabiziCode0
Review of Computational Epigraphy0
TransMI: A Framework to Create Strong Baselines from Multilingual Pretrained Language Models for Transliterated DataCode0
Swa Bhasha: Message-Based Singlish to Sinhala Transliteration0
Charles Translator: A Machine Translation System between Ukrainian and Czech0
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