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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 201225 of 435 papers

TitleStatusHype
Learning to Find Translations and Transliterations on the Web0
Learning to pronounce as measuring cross-lingual joint orthography-phonology complexity0
Leveraging Alignment and Phonology for low-resource Indic to English Neural Machine Transliteration0
Leveraging Entity Linking and Related Language Projection to Improve Name Transliteration0
Leveraging Orthographic Similarity for Multilingual Neural Transliteration0
Leveraging Statistical Transliteration for Dictionary-Based English-Bengali CLIR of OCR`d Text0
Leveraging supplemental representations for sequential transduction0
Lexicon Stratification for Translating Out-of-Vocabulary Words0
Linguistic Analysis of Sinhala YouTube Comments on Sinhala Music Videos: A Dataset Study0
Linguistic Issues in the Machine Transliteration of Chinese, Japanese and Arabic Names0
Lost in Transliteration: Bridging the Script Gap in Neural IR0
Low-Resource Machine Transliteration Using Recurrent Neural Networks of Asian Languages0
Low-Resource Transliteration for Roman-Urdu and Urdu Using Transformer-Based Models0
Machine Translation Pre-training for Data-to-Text Generation -- A Case Study in Czech0
Machine Translation Pre-training for Data-to-Text Generation - A Case Study in Czech0
Machine Translation without Words through Substring Alignment0
MADAMIRA: A Fast, Comprehensive Tool for Morphological Analysis and Disambiguation of Arabic0
Manually Annotated Corpus of Polish Texts Published between 1830 and 19180
Mapping it differently: A solution to the linking challenges0
Mapping Source to Target Strings without Alignment by Analogical Learning: A Case Study with Transliteration0
Map Translation Using Geo-tagged Social Media0
MATra: A Multilingual Attentive Transliteration System for Indian Scripts0
Meaningless yet meaningful: Morphology grounded subword-level NMT0
Mining Hindi-English Transliteration Pairs from Online Hindi Lyrics0
Model Invertibility Regularization: Sequence Alignment With or Without Parallel Data0
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