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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 76100 of 435 papers

TitleStatusHype
Composing RNNs and FSTs for Small Data: Recovering Missing Characters in Old Hawaiian Text0
TArC: Tunisian Arabish Corpus First complete release0
Non-Linear Pairwise Language Mappings for Low-Resource Multilingual Acoustic Model Fusion0
Words.hk: A Comprehensive Cantonese Dictionary Dataset with Definitions, Translations and Transliterated Examples0
A Digital Swedish-Yiddish/Yiddish-Swedish Dictionary: A Web-Based Dictionary that is also Available Offline0
TArC: Tunisian Arabish Corpus, First complete release0
CLeLfPC: a Large Open Multi-Speaker Corpus of French Cued Speech0
From Inscription to Semi-automatic Annotation of Maya Hieroglyphic Texts0
HindiWSD: A package for word sense disambiguation in Hinglish & Hindi0
Extensions to Brahmic script processing within the Nisaba library: new scripts, languages and utilities0
Exploiting Transliterated Words for Finding Similarity in Inter-Language News Articles using Machine Learning0
Use of Transformer-Based Models for Word-Level Transliteration of the Book of the Dean of Lismore0
DE-ABUSE@TamilNLP-ACL 2022: Transliteration as Data Augmentation for Abuse Detection in Tamil0
UMUTeam@LT-EDI-ACL2022: Detecting homophobic and transphobic comments in Tamil0
Joint Transformer/RNN Architecture for Gesture Typing in Indic Languages0
Multilingual Abusiveness Identification on Code-Mixed Social Media Text0
Does Transliteration Help Multilingual Language Modeling?Code0
Learning to pronounce as measuring cross-lingual joint orthography-phonology complexity0
Towards a Broad Coverage Named Entity Resource: A Data-Efficient Approach for Many Diverse Languages0
DEEP: DEnoising Entity Pre-training for Neural Machine Translation0
English-to-Chinese Transliteration with Phonetic Back-transliteration0
ARGUABLY at ComMA@ICON: Detection of Multilingual Aggressive, Gender Biased, and Communally Charged Tweets Using Ensemble and Fine-Tuned IndicBERT0
Speech Synthesis for Low Resource Languages using Transliteration Enabled Transfer Learning0
IIITT@Dravidian-CodeMix-FIRE2021: Transliterate or translate? Sentiment analysis of code-mixed text in Dravidian languagesCode0
DEEP: DEnoising Entity Pre-training for Neural Machine Translation0
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