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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 71–80 of 435 papers

TitleStatusHype
A Hybrid Word Alignment Model for Phrase-Based Statistical Machine Translation—0
Accurate Word Segmentation using Transliteration and Language Model Projection—0
BenLLMEval: A Comprehensive Evaluation into the Potentials and Pitfalls of Large Language Models on Bengali NLP—0
AyutthayaAlpha: A Thai-Latin Script Transliteration Transformer—0
Beyond Specialization: Benchmarking LLMs for Transliteration of Indian Languages—0
Bidirectional Bengali Script and Meetei Mayek Transliteration of Web Based Manipuri News Corpus—0
Applying mpaligner to Machine Transliteration with Japanese-Specific Heuristics—0
Bilingual Dictionary Construction with Transliteration Filtering—0
Automatic word stress annotation of Russian unrestricted text—0
A Neural Network Transliteration Model in Low Resource Settings—0
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