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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 151–175 of 435 papers

TitleStatusHype
Entity Clustering Across Languages—0
EPIK: Eliminating multi-model Pipelines with Knowledge-distillation—0
English-to-Chinese Transliteration with Phonetic Auxiliary Task—0
English to Bengali Multimodal Neural Machine Translation using Transliteration-based Phrase Pairs Augmentation—0
Benchmarking Evaluation Metrics for Code-Switching Automatic Speech Recognition—0
Exploiting Transliterated Words for Finding Similarity in Inter-Language News Articles using Machine Learning—0
Exploring Linguistic Similarity and Zero-Shot Learning for Multilingual Translation of Dravidian Languages—0
Exploring the Role of Transliteration in In-Context Learning for Low-resource Languages Written in Non-Latin Scripts—0
English-Korean Named Entity Transliteration Using Substring Alignment and Re-ranking Methods—0
Factored Machine Translation Systems for Russian-English—0
False-Friend Detection and Entity Matching via Unsupervised Transliteration—0
Finite State Approach to the Kazakh Nominal Paradigm—0
Finite-state script normalization and processing utilities: The Nisaba Brahmic library—0
Foreign Words and the Automatic Processing of Arabic Social Media Text Written in Roman Script—0
End-to-End Natural Language Understanding Pipeline for Bangla Conversational Agents—0
Fourteen Light Tasks for comparing Analogical and Phrase-based Machine Translation—0
Bangla Phonetic Input Method with Foreign Words Handling—0
Further Developments in Treebank Error Detection Using Derivation Trees—0
An Omni-Font Gurmukhi to Shahmukhi Transliteration System—0
Gender Prediction in English-Hindi Code-Mixed Social Media Content : Corpus and Baseline System—0
A Hybrid Word Alignment Model for Phrase-Based Statistical Machine Translation—0
A Conventional Orthography for Tunisian Arabic—0
Gui at MixMT 2022 : English-Hinglish: An MT approach for translation of code mixed data—0
HCCL at SemEval-2017 Task 2: Combining Multilingual Word Embeddings and Transliteration Model for Semantic Similarity—0
Egyptian Arabic to English Statistical Machine Translation System for NIST OpenMT'2015—0
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