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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 401410 of 435 papers

TitleStatusHype
Does Transliteration Help Multilingual Language Modeling?Code0
Role of Language Relatedness in Multilingual Fine-tuning of Language Models: A Case Study in Indo-Aryan LanguagesCode0
A Multi-cascaded Deep Model for Bilingual SMS ClassificationCode0
Sequence-to-sequence neural network models for transliterationCode0
Design Challenges in Named Entity TransliterationCode0
A Large-scale Evaluation of Neural Machine Transliteration for Indic LanguagesCode0
A Rule-based Kurdish Text Transliteration SystemCode0
Efficient Sequence Labeling with Actor-Critic TrainingCode0
Romanized to Native Malayalam Script Transliteration Using an Encoder-Decoder FrameworkCode0
Creating Large-Scale Multilingual Cognate TablesCode0
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