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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 231240 of 435 papers

TitleStatusHype
Romanized Berber and Romanized Arabic Automatic Language Identification Using Machine Learning0
CamelParser: A system for Arabic Syntactic Analysis and Morphological Disambiguation0
A Simple but Effective Approach to Improve Arabizi-to-English Statistical Machine Translation0
Query Translation for Cross-Language Information Retrieval using Multilingual Word Clusters0
YAMAMA: Yet Another Multi-Dialect Arabic Morphological Analyzer0
False-Friend Detection and Entity Matching via Unsupervised Transliteration0
Phonologically Aware Neural Model for Named Entity Recognition in Low Resource Transfer Settings0
Sequence-to-sequence neural network models for transliterationCode0
Neural Machine Transliteration: Preliminary Results0
Transliteration in Any Language with Surrogate Languages0
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