Automatic transliteration and back-transliteration across languages with drastically different alphabets and phonemes inventories such as English/Korean, English/Japanese, English/Arabic, English/Chinese, etc, have practical importance in machine translation, crosslingual information retrieval, and automatic bilingual dictionary compilation, etc. In this paper, a bi-directional and to some exte...

-Machine transliteration plays an important role in natural language applications such as information retrieval and machine translation, especially for handling proper nouns and technical terms. Transliteration is a crucial factor in CLIR and MT. It is important for Machine Translation, especially when the languages do not use the same scripts. This paper addresses the issue of statistical mach...

We present a generative model that efficiently mines transliteration pairs in a consistent fashion in three different settings, unsupervised, semi-supervised and supervised transliteration mining. The model interpolates two sub-models, one for the generation of transliteration pairs and one for the generation of non-transliteration pairs (i.e. noise). The model is trained on noisy unlabelled da...

Machine transliteration is a method for automatically converting words in one language into phonetically equivalent ones in another language. Machine transliteration plays an important role in natural language applications such as information retrieval and machine translation, especially for handling proper nouns and technical terms. Four machine transliteration models – grapheme-based translit...

This paper describes our approach to “NEWS 2009 Machine Transliteration Shared Task.” We built multiple transliteration engines based on different combinations of two transliteration models and three machine learning algorithms. Then, the outputs from these transliteration engines were combined using re-ranking functions. Our method was applied to all language pairs in “NEWS 2009 Machine Transl...

Transliteration mining is aimed at building high quality multi-lingual named entity (NE) lexicons for improving performance in various Natural Language Processing (NLP) tasks including Machine Translation (MT) and Cross Language Information Retrieval (CLIR). In this paper, we apply two Dynamic Bayesian network (DBN)-based edit distance (ED) approaches in mining transliteration pairs from Wikipe...

Machine Transliteration is to transcribe a word written in a script with approximate phonetic equivalence in another language. It is useful for machine translation, cross-lingual information retrieval, multilingual text and speech processing. Punjabi Machine Transliteration (PMT) is a special case of machine transliteration and is a process of converting a word from Shahmukhi (based on Arabic s...

We present in this paper the method of English-to-Korean(E-K) transliteration and back-transliteration. In Korean technical documents, many English words are transliterated into Korean words in various forms in diverse ways. As English words and Korean transliterations are usually technical terms and proper nouns, it is hard to nd a transliteration and its variations in a dictionary. Therefore ...

We present Brahmi-Net an online system for transliteration and script conversion for all major Indian language pairs (306 pairs). The system covers 13 Indo-Aryan languages, 4 Dravidian languages and English. For training the transliteration systems, we mined parallel transliteration corpora from parallel translation corpora using an unsupervised method and trained statistical transliteration sy...