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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 371380 of 435 papers

TitleStatusHype
Mapping Source to Target Strings without Alignment by Analogical Learning: A Case Study with Transliteration0
Factored Machine Translation Systems for Russian-English0
The CMU Machine Translation Systems at WMT 2013: Syntax, Synthetic Translation Options, and Pseudo-References0
Bootstrapping Entity Translation on Weakly Comparable Corpora0
A Tightly-coupled Unsupervised Clustering and Bilingual Alignment Model for Transliteration0
A Hybrid Word Alignment Model for Phrase-Based Statistical Machine Translation0
Accurate Word Segmentation using Transliteration and Language Model Projection0
Yandex School of Data Analysis Machine Translation Systems for WMT130
Rule Based Transliteration Scheme for English to Punjabi0
Improving the quality of Gujarati-Hindi Machine Translation through part-of-speech tagging and stemmer-assisted transliteration0
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