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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 226250 of 435 papers

TitleStatusHype
YAMAMA: Yet Another Multi-Dialect Arabic Morphological Analyzer0
CamelParser: A system for Arabic Syntactic Analysis and Morphological Disambiguation0
A House United: Bridging the Script and Lexical Barrier between Hindi and Urdu0
Opinion Mining in a Code-Mixed Environment: A Case Study with Government Portals0
Romanized Berber and Romanized Arabic Automatic Language Identification Using Machine Learning0
Improving Document Ranking using Query Expansion and Classification Techniques for Mixed Script Information Retrieval0
Query Translation for Cross-Language Information Retrieval using Multilingual Word Clusters0
A Simple but Effective Approach to Improve Arabizi-to-English Statistical Machine Translation0
Whose Nickname is This? Recognizing Politicians from Their Aliases0
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
Transliteration in Any Language with Surrogate Languages0
Neural Machine Transliteration: Preliminary Results0
Moses-based official baseline for NEWS 20160
IXA Biomedical Translation System at WMT16 Biomedical Translation Task0
PJAIT Systems for the WMT 20160
Target-Bidirectional Neural Models for Machine Transliteration0
The AFRL-MITLL WMT16 News-Translation Task Systems0
Leveraging Entity Linking and Related Language Projection to Improve Name Transliteration0
Linguistic Issues in the Machine Transliteration of Chinese, Japanese and Arabic Names0
A Multilinear Approach to the Unsupervised Learning of Morphology0
Whitepaper of NEWS 2016 Shared Task on Machine Transliteration0
NRC Russian-English Machine Translation System for WMT 20160
Applying Neural Networks to English-Chinese Named Entity Transliteration0
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