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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 5160 of 435 papers

TitleStatusHype
A Rule-based Kurdish Text Transliteration SystemCode0
Role of Language Relatedness in Multilingual Fine-tuning of Language Models: A Case Study in Indo-Aryan LanguagesCode0
Sequence-to-sequence neural network models for transliterationCode0
On Biasing Transformer Attention Towards MonotonicityCode0
Analyzing Urdu Social Media for Sentiments using Transfer Learning with Controlled Translations0
Agreement on Target-bidirectional Neural Machine Translation0
A Tightly-coupled Unsupervised Clustering and Bilingual Alignment Model for Transliteration0
A systematic comparison of methods for low-resource dependency parsing on genuinely low-resource languages0
A two-stage transliteration approach to improve performance of a multilingual ASR0
Analyzing English-Spanish Named-Entity enhanced Machine Translation0
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