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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 110 of 435 papers

TitleStatusHype
Optimizing Multilingual Text-To-Speech with Accents & Emotions0
Rethinking Hate Speech Detection on Social Media: Can LLMs Replace Traditional Models?0
Beyond Specialization: Benchmarking LLMs for Transliteration of Indian Languages0
Lost in Transliteration: Bridging the Script Gap in Neural IR0
Bridging the Gap: An Intermediate Language for Enhanced and Cost-Effective Grapheme-to-Phoneme Conversion with Homographs with Multiple Pronunciations Disambiguation0
Proper Name Diacritization for Arabic Wikipedia: A Benchmark Dataset0
Low-Resource Transliteration for Roman-Urdu and Urdu Using Transformer-Based Models0
ParsiPy: NLP Toolkit for Historical Persian Texts in PythonCode1
Connecting the Persian-speaking World through Transliteration0
NusaAksara: A Multimodal and Multilingual Benchmark for Preserving Indonesian Indigenous Scripts0
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