About

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

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Datasets

Greatest papers with code

Neural Machine Translation of Rare Words with Subword Units

ACL 2016 facebookresearch/fairseq-py

Neural machine translation (NMT) models typically operate with a fixed vocabulary, but translation is an open-vocabulary problem.

TRANSLITERATION

Processing South Asian Languages Written in the Latin Script: the Dakshina Dataset

LREC 2020 google-research-datasets/dakshina

This paper describes the Dakshina dataset, a new resource consisting of text in both the Latin and native scripts for 12 South Asian languages.

LANGUAGE MODELLING TRANSLITERATION

Design Challenges in Named Entity Transliteration

COLING 2018 steveash/NETransliteration-COLING2018

We analyze some of the fundamental design challenges that impact the development of a multilingual state-of-the-art named entity transliteration system, including curating bilingual named entity datasets and evaluation of multiple transliteration methods.

TRANSLITERATION

Sequence-to-sequence neural network models for transliteration

29 Oct 2016googlei18n/transliteration

Transliteration is a key component of machine translation systems and software internationalization.

TRANSLITERATION

Applying the Transformer to Character-level Transduction

20 May 2020shijie-wu/neural-transducer

The transformer has been shown to outperform recurrent neural network-based sequence-to-sequence models in various word-level NLP tasks.

MORPHOLOGICAL INFLECTION TRANSLITERATION

ANETAC: Arabic Named Entity Transliteration and Classification Dataset

6 Jul 2019MohamedHadjAmeur/ANETAC

The ANETAC dataset is mainly aimed for the researchers that are working on Arabic named entity transliteration, but it can also be used for named entity classification purposes.

CLASSIFICATION TRANSLITERATION

How Grammatical is Character-level Neural Machine Translation? Assessing MT Quality with Contrastive Translation Pairs

EACL 2017 rsennrich/lingeval97

Analysing translation quality in regards to specific linguistic phenomena has historically been difficult and time-consuming.

TRANSLITERATION

Efficient Sequence Labeling with Actor-Critic Training

30 Sep 2018SaeedNajafi/ac-tagger

We set out to establish RNNs as an attractive alternative to CRFs for sequence labeling.

DECISION MAKING TRANSLITERATION