SOTAVerified

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 176200 of 435 papers

TitleStatusHype
Part-of-Speech Tagging for Code-Switched, Transliterated Texts without Explicit Language Identification0
Efficient Sequence Labeling with Actor-Critic TrainingCode0
Bootstrapping Transliteration with Constrained Discovery for Low-Resource LanguagesCode0
SentiALG: Automated Corpus Annotation for Algerian Sentiment Analysis0
Hybrid approach for transliteration of Algerian arabizi: a primary study0
Design Challenges in Named Entity TransliterationCode0
Identifying Aggression and Toxicity in Comments using Capsule Network0
Indigenous language technologies in Canada: Assessment, challenges, and successes0
Transliteration Better than Translation? Answering Code-mixed Questions over a Knowledge Base0
Statistical Machine Transliteration Baselines for NEWS 20180
Comparison of Assorted Models for Transliteration0
Low-Resource Machine Transliteration Using Recurrent Neural Networks of Asian Languages0
A Deep Learning Based Approach to Transliteration0
Neural Machine Translation Techniques for Named Entity TransliterationCode0
Report of NEWS 2018 Named Entity Transliteration Shared Task0
Addressing Noise in Multidialectal Word Embeddings0
Simple Features for Strong Performance on Named Entity Recognition in Code-Switched Twitter Data0
NEWS 2018 Whitepaper0
Gender Prediction in English-Hindi Code-Mixed Social Media Content : Corpus and Baseline System0
Meaningless yet meaningful: Morphology grounded subword-level NMT0
Normalization of Transliterated Words in Code-Mixed Data Using Seq2Seq Model & Levenshtein Distance0
A Bird's-eye View of Language Processing Projects at the Romanian Academy0
Creating Large-Scale Multilingual Cognate TablesCode0
Creating a Translation Matrix of the Bible's Names Across 591 LanguagesCode0
The French-Algerian Code-Switching Triggered audio corpus (FACST)0
Show:102550
← PrevPage 8 of 18Next →

No leaderboard results yet.