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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 6170 of 435 papers

TitleStatusHype
Learning Cross-lingual Mappings for Data Augmentation to Improve Low-Resource Speech Recognition0
Towards Transliteration between Sindhi Scripts from Devanagari to Perso-Arabic0
Investigating Lexical Sharing in Multilingual Machine Translation for Indian Languages0
Romanization-based Large-scale Adaptation of Multilingual Language Models0
Unsupervised Language agnostic WER Standardization0
EPIK: Eliminating multi-model Pipelines with Knowledge-distillation0
Benchmarking Evaluation Metrics for Code-Switching Automatic Speech Recognition0
Towards Zero-Shot Code-Switched Speech Recognition0
DuDe: Dual-Decoder Multilingual ASR for Indian Languages using Common Label Set0
Gui at MixMT 2022 : English-Hinglish: An MT approach for translation of code mixed data0
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